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Fit models in parallel for each group using mclapply and handle logging. Uses parallel_fit to fit the models.

parallel_fit.Rd

Fit models in parallel for each group using mclapply and handle logging. Uses parallel_fit to fit the models.

Usage

parallel_fit(
  groups,
  group_by,
  formula,
  data,
  n.cores = NULL,
  log_file = paste(tempdir(check = FALSE), "htrfit.log", sep = "/"),
  cl_type = "PSOCK",
  ...
)

Arguments

groups

Vector of unique group values

group_by

Column name in data representing the grouping variable

formula

Formula specifying the model formula

data

Data frame containing the data

n.cores

The number of CPU cores to use for parallel processing. If set to NULL (default), the number of available CPU (minus 1) cores will be automatically detected.

log_file

File to write log (default : Rtmpdir/htrfit.log)

cl_type

cluster type (defautl "PSOCK"). "FORK" is recommanded for linux.

...

Additional arguments to be passed to the glmmTMB::glmmTMB function

Value

List of fitted model objects or NULL for any errors

Examples

parallel_fit(group_by = "Species", groups =  iris$Species, 
               formula = Sepal.Length ~ Sepal.Width + Petal.Length, 
               data = iris, n.cores = 1 )
#> CPU(s) number : 1
#> Cluster type : PSOCK
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $setosa
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>      AIC      BIC   logLik df.resid 
#>  2.38185 10.02994  2.80907       46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0523 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.3037        0.6674        0.2834  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $versicolor
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  38.88241  46.53050 -15.44120        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.109 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       2.1164        0.2476        0.7356  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#> 
#> $virginica
#> Formula:          Sepal.Length ~ Sepal.Width + Petal.Length
#> Data: data
#>       AIC       BIC    logLik  df.resid 
#>  31.94600  39.59409 -11.97300        46 
#> 
#> Number of obs: 50
#> 
#> Dispersion estimate for gaussian family (sigma^2): 0.0945 
#> 
#> Fixed Effects:
#> 
#> Conditional model:
#>  (Intercept)   Sepal.Width  Petal.Length  
#>       0.6248        0.2600        0.9348  
#>