logitr (version 0.2.0)

predictChoices: Predict choices

Description

Returns the expected choices for a set of one or more alternatives based on the results from an estimated model.

Usage

predictChoices(model, alts, obsIDName = NULL)

Arguments

model

The output of a model estimated model using the logitr() function. Include if you want to compare true choices from actual observations (e.g. hold outs) to the predicted choices.

alts

A data frame of a set of alternatives for which to predict choices. Each row is an alternative and each column an attribute corresponding to parameter names in the estimated model.

obsIDName

The name of the column that identifies each set of alternatives. Required if simulating results for more than one set of alternatives. Defaults to NULL (for a single set of alternatives).

Value

A data frame with the predicted choices for each alternative in alts.

Examples

# NOT RUN {
# Run a MNL model in the Preference Space:
library(logitr)

mnl_pref <- logitr(
  data = yogurt,
  choiceName = "choice",
  obsIDName = "obsID",
  parNames = c("price", "feat", "brand")
)

# You can predict choices for any set of alternative, such as hold out
# samples or within-sample. For this example I will predict choices on
# the full yogurt data set, which was used to estimate the model.

# Run the simulation using the preference space MNL model:
choices_mnl_pref <- predictChoices(
  model      = mnl_pref,
  alts       = yogurt,
  obsIDName  = "obsID"
)

head(choices_mnl_pref)

# Compute the accuracy
chosen <-  subset(choices, choice == 1)
chosen$correct <- chosen$choice == chosen$choice_predict
sum(chosen$correct) / nrow(chosen)
# }