savefit function

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

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

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

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.

Returns

A pointer to a python object of type StepMix.

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

Author(s)

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

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)