Simulated Maximum Likelihood Estimation of Mixed Logit Models for Large Datasets
Calculates the Variance-Covariance Matrix of the mixl summary
Extract the availabilites matrix from the dataset, using column indici...
Check the inputs to the draw function
Check the inputs to the estimate function
compileUtilityFunction Deprecated, please see specify_model()
Create a standard set of Halton draws to use in estimation
Runs a maximum likelihood estimation on a mixl choice model
Extract the availabilites matrix from the dataset using a column name ...
Extract the individual level data from the dataset for use in posterio...
Generate a ones-matrix of availabilities
Estimate mixed multinomial logit models
Calculate the posteriors for a specified and estimated model
Prints the output of a model
Print a model summary
Calculate the probabilities for a specified and estimated model. Note ...
Validate the utility functions against the dataset and generate the op...
Create a model summary
Return tex formatted output of a model summary. If an output_file para...
Return the the utilities for a set of coefficients
Specification and estimation of multinomial logit models. Large datasets and complex models are supported, with an intuitive syntax. Multinomial Logit Models, Mixed models, random coefficients and Hybrid Choice are all supported. For more information, see Molloy et al. (2021) <https://www.research-collection.ethz.ch/handle/20.500.11850/477416>.
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