MASS, Matrix, numDeriv, xtable, latex2exp, grid, reshape2,
plyr
Dynamic modeling of all kinds in R. These include models of
processes in discrete time or continuous time. They also include processes
that are linear or nonlinear. Latent variables can be continuous (e.g. state
space models) or discrete (e.g. regime-switching models). The general approach
involves maximum likelihood estimation of single- and multi-subject models of
latent time series with the extended Kalman filter and Kim filter. The user
provides recipes and data which are combined into a model that is then cooked to
obtain free parameter estimates.

Dynamic stochastic block model that combines a stochastic block model (SBM) for its static part with independent Markov chains for the evolution of the nodes groups through time, developed in  Matias and Miele (2016) <doi:10.1111/rssb.12200>.
Rcpp, parallel, riverplot, RColorBrewer, grDevices, graphics,
stats

An R implementation of dynamic simulations of autoregressive
relationships
Laron K Williams, Guy D Whitten, and Christopher Gandrud

Christopher Gandrud, Guy D Whitten, and Laron K Williams

Dynamic Simulations of Autoregressive Relationships
c(
person("Christopher", "Gandrud", email = "christopher.gandrud@gmail.com",
role = c("aut", "cre")),
person("Laron K.", "Williams", role = "aut"),
person("Guy D.", "Whitten", role = "aut")
)
Dynamic simulations and graphical depictions of autoregressive
relationships.
Christopher Gandrud [aut, cre],
Laron K. Williams [aut],
Guy D. Whitten [aut]

Dynamic simulations and graphical depictions of autoregressive relationships.
ggplot2, grid, gridExtra (>= 2.0.0), MASS

Xiaojing Wang <wangxj03@gmail.com>,
Jun Yan <jun.yan@uconn.edu>, and
Ming-Hui Chen <ming-hui.chen@uconn.edu>
Functions to fit time-varying coefficient models for interval
censored and right censored survival data. Three major
approaches are implemented: 1) Bayesian Cox model with
time-independent, time-varying or dynamic coefficients for
right censored and interval censored data; 2) Spline based
time-varying coefficient Cox model for right censored data;
3) Transformation model with time-varying coefficients for
right censored data using estimating equations.