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Functions for fitting general continuous-time Markov and hidden Markov multi-state models to longitudinal data. Both Markov transition rates and the hidden Markov output process can be modeled in terms of covariates. A variety of observation schemes are supported, including processes observed at arbitrary times, completely-observed processes, and censored states.
This R package contains functions for simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models.
Non-parametric bootstrap and permutation resampling-based multiple testing procedures for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Single-step and step-wise methods are implemented. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models) are included. Results are reported in terms of adjusted p-values, confindence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments. This Library is a part of the Bioconductor (bioconductor.org) proejct.
Provides easy access to, and manipulation of, the Munsell colours. Provides a mapping between Munsell's original notation (e.g. "5R 5/10") and hexadecimal strings suitable for use directly in R graphics. Also provides utilities to explore slices through the Munsell colour tree, to transform Munsell colours and display colour palettes.