Function reference • cmdlr

All functions
`adj_rho_sqrd()`	Calculate Adjusted Rho Squared
`aic()`	Calculate AIC
`aic3()`	Calculate AIC3
`augment(<cmdlr>)`	Augment a cmdlr object
`bic()`	Calculate BIC
`bic_star()`	Calculate BIC*
`bread()`	Create the bread of the sandwich
`caic()`	Calculate CAIC
`caic_star()`	Calculate CAIC*
`cat_summary_info()`	Wrapper for cat sequence
`clean_global_env()`	Tidying the environment to prepare for estimation
`cmldr`	cmdlr: Choice Modeling in R
`coef(<cmdlr>)`	S3 generic for coef
`collate()`	Collate different model objects into a single .csv file
`compare_choice_shares()`	Compare choice shares
`convergence_criteria()`	Calculate the convergence criteria
`data_petr_test`	A simulated dataset to use for speed comparison between software
`dbic()`	Calculate DBIC
`detach_objects()`	Detach objects from the environment
`difference_utility()`	Take the difference between all utilities and the chosen alternative
`digitize()`	Expand the sequence of integers
`.onAttach()`	Print package startup message
`estimate()`	Function to estimate a choice model using cmdlr
`estimate_bgw()`	Estimate the model using the 'bgw' package
`estimate_maxlik()`	Estimate the model using the maxLik package
`estimate_model()`	Estimate the model
`estimate_ucminf()`	Estimate the model using the 'ucminf' package
`exp_v()`	Take the exponent of V
`expand_choices()`	Expand choice variable
`fn_1()`	Helper function fn_1
`fn_1d()`	Helper function fn_1d
`fn_1dv()`	Helper function fn_1dv
`fn_2()`	Helper function fn_2
`fn_2d()`	Helper function fn_2d
`fn_2dv()`	Helper function fn_2dv
`fn_3()`	Helper function fn_3
`fn_3d()`	Helper function fn_3d
`fn_3dv()`	Helper function fn_3dv
`fn_4()`	Helper function fn_4
`fn_4d()`	Helper function fn_4d
`fn_4dv()`	Helper function fn_4dv
`fn_se_corr()`	Calculate the standard error of the correlation
`fn_se_cov()`	Calculate the standard error of the covariance
`fn_se_std()`	Calcualte the standard error of the standard deviation
`fn_se_var()`	Calculate the standard error of the variance
`get_control()`	Extract the control list
`get_convergence()`	Extract the convergence of the model
`get_convergence_code()`	Extract the convergence code
`get_convergence_message()`	Extract the convergence message
`get_description()`	Extract the description of the model
`get_estimation_end()`	Extract end time for estimation
`get_estimation_start()`	Extract start time for estimation
`get_function_value()`	Extract the function value from the model object
`get_function_value_zero()`	Extract the function value at zero from the model object
`get_function_values()`	Extract the function values
`get_gradient()`	Extract the gradient of a model object
`get_gradient_obs()`	Extract the gradient observations from a model object
`get_hessian()`	Extract the Hessian
`get_model_frame()`	Extract the model_frame
`get_name()`	Extract the name of the model
`get_param_final()`	Extract final parameters from the model object
`get_param_fixed()`	Extract fixed parameters from the model object
`get_param_free()`	Extract free parameters from the model object
`get_param_start()`	Extract starting parameters from the model object
`get_split_index()`	Get the split index
`get_v_chosen()`	Calculate the utility of the chosen alternative
`get_worker_info()`	Function for getting worker info
`glance(<cmdlr>)`	Glance at a cmdlr model object
`hessian()`	Calculate the Hessian
`hessian_complete()`	Check if the Hessian matrix is complete
`hessian_condition_number()`	Get the hessian condition number
`hqic()`	Calculate HQIC
`ht_aic()`	Calculate HTAIC
`identify_choice_patterns()`	Identify choice patterns
`inspect_list()`	Inspect a list
`is_used()`	Checks if the supplied character string is used in the function
`lc_conditional()`	Calculate the conditional probabilities
`lc_unconditional()`	Calculate the unconditional probabilities
`ll_ratio_test()`	Calculate the log likelihood ratio test for nested models
`load_packages()`	Load a multiple packages
`make_draws()`	Make random draws
`make_mlhs()`	Make Modified Latin Hypercube Draws
`make_model_name()`	Create the model name used when saving the data
`make_pseudo_random()`	Make pseudo random draws
`make_scrambled_halton()`	Make scrambled Halton draws
`make_scrambled_sobol()`	Make scrambled sobol draws
`make_standard_halton()`	Wrapper for halton()
`make_standard_sobol()`	Make sobol draws
`meat()`	Create the meat of the sandwich
`mnl_probabilities()`	Calculate the MNL probability
`mnl_zero()`	Calculate the probability at zero
`model_fit()`	Calculate model fit
`nid()`	Function for extracting number of individuals
`nobs(<cmdlr>)`	S3 generic for nobs
`normal_vcov()`	Normal variance-covariance matrix
`num_deriv()`	Obtain the numerical derivative by central difference
`ordered_logit()`	Ordered logit
`pairwise_chisq_test()`	A pairwise Chi-squared test
`panel_product()`	Take product over the sequence of choices
`parameter_info()`	Summary of parameter info
`plot_choice()`	Plot choice shares
`poe_test()`	Test for the difference in empirical distributions
`prepare()`	Prepare the estimation environment
`prepare_alt_avail()`	Prepare the alternative availabilities
`prepare_data()`	Prepare the data for estimation
`prepare_draws()`	Prepares the draws
`prepare_estimation_environment()`	Prepare the estimation environment
`prepare_log_lik()`	Prepares the log likelihood function
`prepare_num_grad()`	Prepares the numerical gradient
`print(<cmdlr>)`	A generic print function for printing a 'cmdlr' object
`pval()`	Calculate p-values
`radical_inverse()`	Compute the radical inverse
`rep_cols()`	Repeat columns
`rep_rows()`	Repeat rows
`replace_na_padding()`	Replace the NAs introduced by padding the data
`reshape_panel()`	Reshape the panel
`robust_vcov()`	A sandwich estimator for robust standard errors
`save()`	Stores the results of the model to files
`save_hessian()`	Save the hessian matrix
`save_object()`	Save the model object
`save_summary()`	Save the summary to file
`save_vcov()`	Save the variance covariance matrix
`search_simple()`	Simple search
`search_smart()`	Smart search
`search_start_values()`	Search for starting values
`set_controls()`	Validate and set default estimation controls
`shuffle()`	Shuffle the order of points in the unit interval.
`split_data()`	Split the data into a list
`standardize()`	Standardize a variable
`stars()`	Create significance stars
`subset_data()`	Subset the data to only include used variables
`summary(<cmdlr>)`	S3 Generic for model summary
`summary_poe_test()`	Summary function for poe_test()
`summary_worker_info()`	Function for summarizing worker information
`tidy(<cmdlr>)`	Tidy a cmdlr object
`transform_distribution()`	Transform distribution
`transform_lognormal()`	Transform to the lognormal distribution
`transform_normal()`	Transform to the normal distribution
`transform_triangular()`	Transform to the triangular distribution
`transform_uniform()`	Transform to the uniform distribution
`validate()`	Validate model options
`vcov(<cmdlr>)`	S3 generic for vcov

Reference

All functions