An implementation of several machine learning algorithms for 
    multivariate time series. The package includes functions allowing the
    execution of clustering, classification or outlier detection methods,
    among others. It also incorporates a collection of multivariate time
    series datasets which can be used to analyse the performance of new
    proposed algorithms. Some of these datasets are stored in GitHub data
    packages 'ueadata1' to 'ueadata8'. To access these data packages, run
    'install.packages(c('ueadata1', 'ueadata2', 'ueadata3', 'ueadata4', 'ueadata5', 'ueadata6', 'ueadata7', 'ueadata8'), repos='<https://anloor7.github.io/drat/>')'.
    The installation takes a couple of minutes but we strongly encourage the
    users to do it if they want to have available all datasets of mlmts.
    Practitioners from a broad variety of fields could
    benefit from the general framework provided by 'mlmts'.

Convenience functions and datasets to be used with Practical Multilevel Modeling using R. The package includes functions for calculating group means, group mean centered variables, and displaying some basic missing data information. A function for computing robust standard errors for linear mixed models based on Liang and Zeger (1986) <doi:10.1093/biomet/73.1.13> and Bell and 'McCaffrey' (2002) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2002002/article/9058-eng.pdf?st=NxMjN1YZ> is included as well as a function for checking for level-one homoskedasticity (Raudenbush & Bryk, 2002, ISBN:076191904X).

Maximum likelihood estimation of random utility discrete
             choice models. The software is described in Croissant (2020)
              <doi:10.18637/jss.v095.i11> and the underlying methods in
              Train (2009) <doi:10.1017/CBO9780511805271>.

Provides a modified function bic.glm of the BMA package that can be applied to multinomial logit (MNL) data. The data is converted to binary logit using the Begg & Gray approximation. The package also contains functions for maximum likelihood estimation of MNL.