Collection of ancillary functions and utilities to be used in conjunction with the 'TraMineR' package for sequence data exploration. Includes, among others, specific functions such as state survival plots, position-wise group-typical states, dynamic sequence indicators, and dissimilarities between event sequences. Also includes contributions by non-members of the TraMineR team such as methods for polyadic data and for the comparison of groups of sequences.

Likelihood-based estimation of mixed-effects transformation models
    using the Template Model Builder ('TMB', Kristensen et al., 2016)
    <doi:10.18637/jss.v070.i05>. The technical details of transformation models
    are given in Hothorn et al. (2018) <doi:10.1111/sjos.12291>. Likelihood
    contributions of exact, randomly censored (left, right, interval) and
    truncated observations are supported. The random effects are assumed to be
    normally distributed on the scale of the transformation function, the
    marginal likelihood is evaluated using the Laplace approximation, and the
    gradients are calculated with automatic differentiation (Tamasi & Hothorn,
    2021) <doi:10.32614/RJ-2021-075>. Penalized smooth shift terms can be
    defined using 'mgcv'.

Partially penalized versions of specific transformation models
    implemented in package 'mlt'. Available models include a fully parametric version
    of the Cox model, other parametric survival models (Weibull, etc.), models for
    binary and ordered categorical variables, normal and transformed-normal (Box-Cox type)
    linear models, and continuous outcome logistic regression. Hyperparameter tuning
    is facilitated through model-based optimization functionalities from package 'mlrMBO'.
    The accompanying vignette describes the methodology used in 'tramnet' in detail.
    Transformation models and model-based optimization are described in
    Hothorn et al. (2019) <doi:10.1111/sjos.12291> and
    Bischl et al. (2016) <arxiv:1703.03373>, respectively.