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Split choice data into a train and a test subset

Source: R/choice_data.R
train_test.Rd

This function splits choice data by deciders or by choice occasions, for example to fit a model on the train subset and to evaluate its predictions on the test subset.

Usage

train_test(
  data_frame,
  test_proportion = NULL,
  test_number = NULL,
  by = "decider",
  random = FALSE,
  column_decider = "deciderID",
  column_occasion = NULL
)

Arguments

data_frame

[data.frame]
Contains the choice data.

test_proportion

[numeric(1) | NULL]
The proportion of deciders or occasions in the test subset.

test_number

[integer(1) | NULL]
The number of deciders, or of occasions per decider, in the test subset.

by

[character(1)]
Split by "decider" or by "occasion".

random

[logical(1)]
Draw the test subset at random? Else, it is the last deciders or occasions.

column_decider

[character(1)]
Column name with decider identifiers.

column_occasion

[character(1) | NULL]
Column name with occasion identifiers. Set to NULL in cross-sectional data.

Value

A list of two subsets of data_frame, named train and test.

Details

Exactly one of test_proportion and test_number sets the size of the test subset. Splitting by occasions keeps every decider in both subsets and applies the size per decider, which requires panel data.

Examples

data("Train", package = "mlogit")

### 20% of the deciders in the test subset
parts <- train_test(Train, test_proportion = 0.2, column_decider = "id")
lengths(lapply(parts, function(part) unique(part$id)))
#> train  test 
#>   188    47 

### the last choice occasion of every decider in the test subset
parts <- train_test(
  Train, test_number = 1, by = "occasion",
  column_decider = "id", column_occasion = "choiceid"
)
nrow(parts$test)
#> [1] 235