Monte Carlo EM algorithms and Bayesian methods for fitting
Tweedie compound Poisson linear models
This package provides methods for fitting Tweedie compound
Poisson linear models using Monte Carlo EM algorithm and MCMC
methods. Models that are handled in the package are generalized
linear models, mixed-effect models and their corresponding
Bayesian models.

Fit Tweedie compound Poisson linear and linear
mixed-effect models using Monte Carlo EM, Laplacian
approximation and MCMC methods.
coda, lme4, Matrix, methods, stats, tweedie

Fit Tweedie compound Poisson linear and linear mixed-effect models using Monte Carlo EM, Laplacian approximation and MCMC methods.

Fit Tweedie compound Poisson linear models and their Bayesian extensions.
amer, biglm, coda, lme4, Matrix, methods, tweedie

Likelihood-based and Bayesian methods for various compound
Poisson linear models.
minqa, reshape2, statmod, stats, stats4, tweedie
R (>= 2.10), amer, biglm, coda, ggplot2, lme4, Matrix, methods

R (>= 2.10), biglm, coda, ggplot2, lme4, Matrix, splines,
methods

Likelihood-based and Bayesian methods for various compound Poisson linear models.
biglm, ggplot2, minqa, nlme, reshape2, statmod, stats, stats4,
tweedie
R (>= 2.10), coda, Matrix, splines, methods

Likelihood-based and Bayesian methods for various compound Poisson linear models based on Zhang, Yanwei (2013) <https://link.springer.com/article/10.1007/s11222-012-9343-7>.
R (>= 3.2.0), coda, Matrix, splines, methods

Danli Xu <dxu452@aucklanduni.ac.nz>, Yong Wang <yongwang@auckland.ac.nz>
Provides functions to produce some circular plots for circular data, in a height- or area-proportional manner. They include barplots, smooth density plots, stacked dot plots, histograms, multi-class stacked smooth density plots, and multi-class stacked histograms. The new methodology for general area-proportional circular visualization is described in an article submitted (after revision) to Journal of Computational and Graphical Statistics.

c(
person("Danli", "Xu", email = "dxu452@aucklanduni.ac.nz",
role = c("aut")),
person("Yong", "Wang", email = "yongwang@auckland.ac.nz",
role = c("aut","cre")))
Provides functions to produce some circular plots for circular data, in a height- or area-proportional manner. They include bar plots, smooth density plots, stacked dot plots, histograms, multi-class stacked smooth density plots, and multi-class stacked histograms.