Implementation of hypothesis testing procedures described in Hansen (1992) <doi:10.1002/jae.3950070506>, Carrasco, Hu, & Ploberger (2014) <doi:10.3982/ECTA8609>, Dufour & Luger (2017) <doi:10.1080/07474938.2017.1307548>, and Rodriguez Rondon & Dufour (2022) <https://grodriguezrondon.com/files/RodriguezRondon_Dufour_MonteCarlo_LikelihoodRatioTest_MarkovSwitchingModels.pdf> that can be used to identify the number of regimes in Markov switching models.

Software to aid in modeling and analyzing mass-spectrometry-based
    proteome melting data. Quantitative data is imported and normalized and
    thermal behavior is modeled at the protein level. Methods exist for
    normalization, modeling, visualization, and export of results. For a
    general introduction to MS-based thermal profiling, see Savitski et al.
    (2014) <doi:10.1126/science.1255784>.

Implements the MST-kNN clustering algorithm which was proposed by Inostroza-Ponta, M. (2008) <https://trove.nla.gov.au/work/28729389?selectedversion=NBD44634158>.

Generation of response patterns under dichotomous and polytomous computerized multistage testing (MST) framework. It holds various item response theory (IRT) and score-based methods to select the next module and estimate ability levels (Magis, Yan and von Davier (2017, ISBN:978-3-319-69218-0)).

Interface for creating data sets and extracting data through the
    'MicroStrategy' REST API. Access the demo API at
    <https://demo.microstrategy.com/MicroStrategyLibrary/api-docs/index.html>.

Distance between multivariate t distributions, as presented by N. Bouhlel and D. Rousseau (2023) <doi:10.1109/LSP.2023.3324594>.

Estimators for multivariate symmetrical uncertainty based
    on the work of Gustavo Sosa et al. (2016) <arXiv:1709.08730>,
    total correlation, information gain and symmetrical uncertainty of
    categorical variables.

Estimation, inference and diagnostics for Univariate Autoregressive Markov Switching Models for Linear and Generalized Models. Distributions for the series include gaussian, Poisson, binomial and gamma cases. The EM algorithm is used for estimation (see Perlin (2012) <doi:10.2139/ssrn.1714016>).