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Extract Model Statistics for fits_ids_dm Object

Source: R/extended_s3_methods.R
logLik.fits_ids_dm.Rd

These methods are wrappers to extract specific model fit statistics (log-likelihood, AIC, BIC) for each model in a fits_ids_dm object.

Usage

# S3 method for class 'fits_ids_dm'
logLik(object, ...)

# S3 method for class 'fits_ids_dm'
AIC(object, ..., k = 2)

# S3 method for class 'fits_ids_dm'
BIC(object, ...)

Arguments

object

a fits_ids_dm object (see estimate_model_ids)

...

additional arguments (currently not used)

k

numeric; penalty parameter for the AIC calculation. Defaults to 2 (standard AIC).

Value

An object of type fit_stats containing the respective statistic in one column (named Log_Like, AIC, or BIC) and a corresponding ID column. If any of the statistics can't be calculated, the function returns NULL.

Details

Each function retrieves the relevant statistics by calling calc_stats with type = "fit_stats" and selects the columns for ID and the required statistic.

See also

stats::AIC(), stats::BIC(), logLik.drift_dm

Examples

# get an auxiliary fits_ids object for demonstration purpose;
# such an object results from calling load_fits_ids
all_fits <- get_example_fits("fits_ids_dm")

# AICs
AIC(all_fits)
#> Type of Statistic: fit_stats
#> 
#>   ID      AIC
#> 1  1 -785.129
#> 2  2 -741.929
#> 3  3 -931.496
#> 
#> (access the data.frame's columns/rows as usual)

# BICs
BIC(all_fits)
#> Type of Statistic: fit_stats
#> 
#>   ID      BIC
#> 1  1 -758.410
#> 2  2 -715.251
#> 3  3 -904.776
#> 
#> (access the data.frame's columns/rows as usual)

# Log-Likelihoods
logLik(all_fits)
#> Type of Statistic: fit_stats
#> 
#>   ID Log_Like
#> 1  1  399.565
#> 2  2  377.965
#> 3  3  472.748
#> 
#> (access the data.frame's columns/rows as usual)

# All unique and free parameters
coef(all_fits)
#> Object Type: coefs_dm
#> 
#>   ID   muc     b non_dec sd_non_dec   tau     A alpha
#> 1  1 4.700 0.446   0.341      0.032 0.032 0.102 6.605
#> 2  2 4.696 0.391   0.297      0.041 0.101 0.089 5.038
#> 3  3 5.960 0.626   0.318      0.012 0.110 0.195 3.334
#> 
#> (access the data.frame's columns/rows as usual)

# Or all parameters across all conditions
coef(all_fits, select_unique = FALSE)
#> Object Type: coefs_dm
#> 
#>   ID   Cond   muc     b non_dec sd_non_dec   tau a      A alpha peak_l
#> 1  1   comp 4.700 0.446   0.341      0.032 0.032 2  0.102 6.605  0.032
#> 2  1 incomp 4.700 0.446   0.341      0.032 0.032 2 -0.102 6.605  0.032
#> 3  2   comp 4.696 0.391   0.297      0.041 0.101 2  0.089 5.038  0.101
#> 4  2 incomp 4.696 0.391   0.297      0.041 0.101 2 -0.089 5.038  0.101
#> 5  3   comp 5.960 0.626   0.318      0.012 0.110 2  0.195 3.334  0.110
#> 6  3 incomp 5.960 0.626   0.318      0.012 0.110 2 -0.195 3.334  0.110
#> 
#> (access the data.frame's columns/rows as usual)