probabilities: Calculate the probabilities for a specified and estimated...

In mixl: Simulated Maximum Likelihood Estimation of Mixed Logit Models for Large Datasets

Description

Calculate the probabilities for a specified and estimated model. Note that if new data or draws are provided, the model will not be re-estimated

Usage

probabilities(
  model,
  data = NULL,
  availabilities = NULL,
  draws = NULL,
  nDraws = NULL,
  num_threads = 1
)

Arguments

model	The estimated Model
data	(Optional) New data to use instead of that in the dataset
availabilities	(Optional) New availabilites to use
draws	(Optional) Optional new set of random draws to use
nDraws	(Optional) Optional new number of random draws to use
num_threads	Enable parallel computing where available using this many cores

Value

Dataframe of individual-level posteriors

Examples

	data("Train", package="mlogit")
	Train$ID <- Train$id
	Train$CHOICE <- as.numeric(Train$choice)
	    
	mnl_test <- "
	U_A = @B_price * $price_A / 1000 + @B_time * $time_A / 60;
	U_B = @asc + @B_price * $price_B / 1000 + @B_timeB * $time_B / 60;
	"

	model_spec <- mixl::specify_model(mnl_test, Train, disable_multicore=T)

	#only take starting values that are needed
	est <- stats::setNames(c(1, 1,1,1), c("asc", "B_price", "B_time", "B_timeB"))
	availabilities <- mixl::generate_default_availabilities(
		Train, model_spec$num_utility_functions
	)

	model <- mixl::estimate(model_spec, est, Train, availabilities = availabilities)
	probabilities(model)

	#hypothetical scenario where the travel time of option A doubles
	Train$time_A = Train$time_A * 2
	probabilities(model, Train)

mixl documentation built on Dec. 11, 2021, 9:07 a.m.