Model-Based Clustering and Classification with Mixtures of Modified t Factor Analyzers (mmtfa)
Fits a family of mixtures of multivariate t-distributions under a continuous t-distributed latent variable structure for the purpose of clustering or classification. The alternating expectation-conditional maximization algorithm is used for parameter estimation.

Parametric Frailty Models (parfm)
Fits Parametric Frailty Models by maximum marginal likelihood. Possible baseline hazards: Weibull, inverse Weibull, exponential, Gompertz, lognormal and loglogistic. Possible Frailty distributions: gamma, inverse Gaussian, positive stable and lognormal.

Ordinal Regression Analysis for Continuous Scales (ordinalCont)
A regression framework for response variables which are continuous self-rating scales such as the Visual Analog Scale (VAS) used in pain assessment, or the Linear Analog Self-Assessment (LASA) scales in quality of life studies. These scales measure subjects’ perception of an intangible quantity, and cannot be handled as ratio variables because of their inherent nonlinearity. We treat them as ordinal variables, measured on a continuous scale. A function (the g function, currently the generalized logistic function) connects the scale with an underlying continuous latent variable. The link function is the inverse of the CDF of the assumed underlying distribution of the latent variable. Currently the logit link, which corresponds to a standard logistic distribution, is implemented.