Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586), William Q. Meeker and  Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).

Graphical data analysis of accelerated life tests. Methods derived from  Wayne Nelson (1990, ISBN: 9780471522775), William Q. Meeker and  Lois A. Escobar (1998, ISBN: 1-471-14328-6).

Providing quantitative tools for input estimation, portfolio construction, and performance evaluation.

Estimates high-dimensional multivariate normal copula regression models with the weighted composite likelihood estimating equations in Nikoloulopoulos (2023) <doi:10.1016/j.csda.2022.107654>. It provides autoregressive moving average correlation structures and binary, ordinal, Poisson, and negative binomial regressions.

Clusters state sequences and weighted data. It provides an optimized weighted PAM algorithm as well as functions for aggregating replicated cases, computing cluster quality measures for a range of clustering solutions, sequence analysis typology validation using parametric bootstraps and plotting (fuzzy) clusters of state sequences. It further provides a fuzzy and crisp CLARA algorithm to cluster large database with sequence analysis, and a methodological framework for Robustness Assessment of Regressions using Cluster Analysis Typologies (RARCAT).

The weighted ensemble method is a valuable approach for combining forecasts. This algorithm employs several optimization techniques to generate optimized weights. This package has been developed using algorithm of Armstrong (1989) <doi:10.1016/0024-6301(90)90317-W>.

R interface to the 'weightederm' package for 'Python', which
    provides 'scikit-learn'-style estimators for offline change point
    regression (data segmentation) via weighted empirical risk minimization.
    Supports least-squares, Huber, and logistic losses with fixed or
    cross-validated numbers of change points. Wraps 'Python' via 'reticulate'.
    Arpino and Venkataramanan (2026) <doi:10.48550/arXiv.2604.11746>.