Collate: mc.R mcompanion.R utils_Jordan.R mat.R sim.R class_MC.R

Imports: methods, Matrix (>= 1.5-0), gbutils, MASS, Rdpack

Title: Marginalized Count Regression Models
Description: Implementation of marginalized models for zero-inflated count data. This package provides a tool to implement an estimation algorithm for the marginalized count models, which
directly makes inference on the effect of each covariate on the marginal mean of the outcome.
The method involves the marginalized zero-inflated Poisson model described

Title: Regression with Multiple Change Points
Description: Flexible and informed regression with Multiple Change Points (MCP). 'mcp' can infer change points in means, variances, autocorrelation structure, and any combination of these, as well as the parameters of the segments in between. All parameters are estimated with uncertainty and prediction intervals are supported - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey density ratio, posterior contrasts, and cross-validation. 'mcp' provides a generalization of the approach described in Carlin, Gelfand, & Smith (1992) <doi:10.2307/2347570> and Stephens (1994) <doi:10.2307/2986119>.
Imports: parallel, future, future.apply, rjags (>= 4.9), coda (>=
Suggests: hexbin, testthat (>= 2.1.0), knitr, rmarkdown, covr

Description: Flexible and informed regression with Multiple Change Points (MCP). 'mcp' can infer change points in means, variances, autocorrelation structure, and any combination of these, as well as the parameters of the segments in between. All parameters are estimated with uncertainty and prediction intervals are supported - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey density ratio, posterior contrasts, and cross-validation. 'mcp' is described in Lindeløv (submitted) <doi:10.31219/osf.io/fzqxv> and generalizes the approach described in Carlin, Gelfand, & Smith (1992) <doi:10.2307/2347570> and Stephens (1994) <doi:10.2307/2986119>.
ggplot2 (>= 3.2.1), patchwork (>= 1.0.0), stats, rlang (>=
Suggests: hexbin, testthat (>= 2.1.0), purrr (>= 0.3.3), knitr,