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

Usage

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

Arguments

formula: Formula specifying the model formula
data: Data frame containing the data
group_by: Column name in data representing the grouping variable
n.cores: The number of CPU cores to use for parallel processing. If set to NULL (default), the number of available CPU cores will be automatically detected.
cl_type: cluster type (default "PSOCK"). "FORK" is recommended for linux.
log_file: File path to save the log messages (default : Rtmpdir/htrfit.log)
...: Additional arguments to be passed to the glmmTMB::glmmTMB function

Value

List of fitted model objects or NULL for any errors

Examples

fitModelParallel(formula = Sepal.Length ~ Sepal.Width + Petal.Length, 
                 data = iris, group_by = "Species", n.cores = 1) 
#> Log file location: /tmp/RtmpS86cq0/htrfit.log
#> 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  
#> 
#> $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  
#>