This repository contains R code for reproducing the case studies and simulation experiments of the paper "Efficient smoothness selection for nonparametric Markov-switching models via quasi restricted maximum likelihood".

In the paper, we develop an efficient method for selecting the smoothness parameter in nonparametric Markov-switching models called quasi restricted maximum likelihood (qREML). The method is implemented in the qreml() function contained in the R package LaMa.

The structure of the repository is really simple as all .R files are self-contained. The folder case_studies contains the three case studies from the paper and the folder simulation_experiments contains one .R file for reproducing the simulation experiments.

The figures presented in the paper are provided in the subfolders figs and all data necessary will either be downloaded automatically by running the case study code, or is included in the folder data and will be loaded automatically.

When using LaMa, please cite the package as follows:

Koslik Jan-Ole (2024). LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models. R package version 2.0.1 https://CRAN.R-project.org/package=LaMa.

Or in R type citation(package = "LaMa").