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

# Simulated Maximum Likelihood Estimation of Mixed Logit Models for Large Datasets

## Documentation for package ‘mixl’ version 1.3.5

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

mixl-package | Estimate mixed multinomial logit models
av_matrix | Extract the availabilites matrix from the dataset, using column indicies
check_draw_inputs | Check the inputs to the draw function
check_inputs | Check the inputs to the estimate function
compileUtilityFunction | compileUtilityFunction Deprecated, please see 'specify_model()'
create_halton_draws | Create a standard set of Halton draws to use in estimation
estimate | Runs a maximum likelihood estimation on a mixl choice model
extract_av_cols | Extract the availabilites matrix from the dataset using a column name prefix
extract_indiv_data | Extract the individual level data from the dataset for use in posterior analysis
generate_default_availabilities | Generate a ones-matrix of availabilities
mixl | Estimate mixed multinomial logit models
posteriors | Calculate the posteriors for a specified and estimated model
print.mixl | Prints the output of a model
print.summary.mixl | Print a model summary
probabilities | 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
specify_model | Validate the utility functions against the dataset and generate the optimised logliklihood function
summary.mixl | Create a model summary
summary_tex | Return tex formatted output of a model summary. If an output_file parameter is provided, save the object to that location
utilities | Return the the utilities for a set of coefficients
vcov.mixl | Calculates the Variance-Covariance Matrix of the mixl summary