Skip to contents

Summary for stats_dm Objects

Source: R/formatting_stats_dm.R
summary.stats_dm.Rd

Summary and corresponding printing methods for objects of the classes stats_dm, basic_stats, cafs, quantiles, delta_funs, fit_stats, sum_dist, and stats_dm_list. These object types result from a call to calc_stats().

Usage

# S3 method for class 'stats_dm'
summary(object, ..., round_digits = drift_dm_default_rounding())

# S3 method for class 'basic_stats'
summary(object, ...)

# S3 method for class 'cafs'
summary(object, ...)

# S3 method for class 'quantiles'
summary(object, ...)

# S3 method for class 'delta_funs'
summary(object, ...)

# S3 method for class 'fit_stats'
summary(object, ...)

# S3 method for class 'sum_dist'
summary(object, ...)

# S3 method for class 'stats_dm_list'
summary(object, ...)

# S3 method for class 'summary.stats_dm'
print(x, ..., show_header = TRUE, drop_cols = NULL)

# S3 method for class 'summary.basic_stats'
print(x, ...)

# S3 method for class 'summary.cafs'
print(x, ...)

# S3 method for class 'summary.quantiles'
print(x, ...)

# S3 method for class 'summary.delta_funs'
print(x, ...)

# S3 method for class 'summary.fit_stats'
print(x, ...)

# S3 method for class 'summary.sum_dist'
print(x, ...)

# S3 method for class 'summary.stats_dm_list'
print(x, ...)

Arguments

object

an object of the respective class

...

additional arguments passed forward.

round_digits

integer, specifying the number of decimal places for rounding the summary of the underlying data.frame. Default is 3.

x

an object of the respective class.

show_header

logical. If TRUE, a header specifying the type of statistic will be displayed.

drop_cols

character vector, specifying which columns of the table summarizing the underlying data.frame should not be displayed.

Value

For summary.*() methods, a summary object of class corresponding to the input class.

For print.*() methods, the respective object is returned invisibly

Details

  • summary.stats_dm(): Summarizes stats_dm objects, returning the type, a summary of the underlying data.frame (summary_dataframe), and, if possible, the number of unique IDs (n_ids).

  • summary.sum_dist(): Extends summary.stats_dm() with additional information about the source (source).

  • summary.basic_stats(): Extends summary.sum_dist() with additional information about the conditions (conds).

  • summary.cafs(): Extends summary.sum_dist() with additional information about the bins (bins) and conditions (conds).

  • summary.quantiles(): Extends summary.sum_dist() with additional information about the quantile levels (probs) and conditions (conds).

  • summary.delta_funs(): Extends summary.sum_dist() with additional information about the quantile levels (probs).

  • summary.fit_stats(): Identical to summary.stats_dm.

  • summary.stats_dm_list(): Applies the summary function to each element of the list and returns a list of the respective summary objects.

Note the following class relationships and properties:

  • basic_stats, cafs, quantiles, and delta_funs are all inheriting from sum_dist.

  • All sum_dist and fit_stats objects are inheriting from stats_dm.

  • Each stats_dm_list object is just a list containing instances of stats_dm.

Examples

# get a model with data for demonstration purpose
a_model <- dmc_dm(dx = .0025, dt = .0025, t_max = 2)
obs_data(a_model) <- dmc_synth_data

# now get some statistics and call the summary functions
some_stats <- calc_stats(a_model, type = c("quantiles", "fit_stats"))
summary(some_stats) # summary.stats_dm_list
#> Summary of Element 1: quantiles
#> 
#> Dependent Variables:
#>    Quant_corr      Quant_err    
#>  Min.   :0.324   Min.   :0.299  
#>  1st Qu.:0.410   1st Qu.:0.360  
#>  Median :0.464   Median :0.430  
#>  Mean   :0.475   Mean   :0.437  
#>  3rd Qu.:0.530   3rd Qu.:0.491  
#>  Max.   :0.672   Max.   :0.698  
#> 
#> Sources: obs, pred 
#> Conditions: comp, incomp 
#> Probs: 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 
#> -------
#> 
#> Summary of Element 2: fit_stats
#> 
#> Dependent Variables:
#>     Log_Like        AIC            BIC      
#>  Min.   :137   Min.   :-260   Min.   :-230  
#>  1st Qu.:137   1st Qu.:-260   1st Qu.:-230  
#>  Median :137   Median :-260   Median :-230  
#>  Mean   :137   Mean   :-260   Mean   :-230  
#>  3rd Qu.:137   3rd Qu.:-260   3rd Qu.:-230  
#>  Max.   :137   Max.   :-260   Max.   :-230  
#> 
#> -------
summary(some_stats$quantiles) # summary.quantiles
#> Type of Statistic: quantiles
#> 
#> Dependent Variables:
#>    Quant_corr      Quant_err    
#>  Min.   :0.324   Min.   :0.299  
#>  1st Qu.:0.410   1st Qu.:0.360  
#>  Median :0.464   Median :0.430  
#>  Mean   :0.475   Mean   :0.437  
#>  3rd Qu.:0.530   3rd Qu.:0.491  
#>  Max.   :0.672   Max.   :0.698  
#> 
#> Sources: obs, pred 
#> Conditions: comp, incomp 
#> Probs: 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9