savefit {stepmixr}

Save the fit of a mixture using the stepmix python package.

Description

This function saves the stepmix fitted object in python using the pickle package.

Usage

savefit(fitx, f)
loadfit(f)

Arguments

fitx

An object created with the stepmix function.

f

String indicating the name of the file

Details

This methods allows to save/load the stepmix object in a binary file using the pickle package.

Value

A pointer to a python object of type StepMix.

Author(s)

Éric Lacourse, Roxane de la Sablonnière, Charles-Édouard Giguère, Sacha Morin, Robin Legault, Félix Laliberté, Zsusza Bakk

References

Bolck, A., Croon, M., and Hagenaars, J. Estimating latent structure models with categorical variables: One-step versus three-step estimators. Political analysis, 12(1): 3-27, 2004.

Vermunt, J. K. Latent class modeling with covariates: Two improved three-step approaches. Political analysis, 18 (4):450-469, 2010.

Bakk, Z., Tekle, F. B., and Vermunt, J. K. Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociological Methodology, 43(1):272-311, 2013.

Bakk, Z. and Kuha, J. Two-step estimation of models between latent classes and external variables. Psychometrika, 83(4):871-892, 2018

Examples

## Not run: 
if (reticulate::py_module_available("stepmix")) {
  model1 <- stepmix(n_components = 2, n_steps = 3, progress_bar = 0)
  X <- data.frame(x1 = c(0,1,1,1,1,0,0,0,0,0,1,1,0),
                  x2 = c(0,1,1,0,0,1,1,0,0,0,1,0,1))
  fit1 <- fit(model1, X)
  savefit(fit1, "fit1.pickle")
  
  ### clean the directory.
  file.remove("fit1.pickle")
}

## End(Not run)