TSP, shiny, testthat, numDeriv, kdecopula (>= 0.8.0), network

Provides tools for the statistical analysis of regular vine copula
models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and
Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>.
The package includes tools for parameter estimation, model selection,
simulation, goodness-of-fit tests, and visualization. Tools for estimation,
selection and exploratory data analysis of bivariate copula models are also
provided.

Simulation of Populations by Sampling Waiting-Time Distributions
c(person("Frans", "Willekens", , "willekens@nidi.nl", role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-6125-0212")),
person("Tim", "Riffe", role = "ctb",
email = "tim.riffe@gmail.com", comment = c(ORCID = "0000-0002-2673-4622")))
Generates lifespans and fertility histories in continuous time using individual-level state transition (multi-state) models and data from the Human Mortality Database and the Human Fertility Database. To facilitate virtual population analysis, data on virtual individuals are stored in a data structure commonly used in sample surveys. Life histories are generated for multiple generations. The genealogies that result facilitate the study of family ties.

Tomoki Tokuda and Francis
Tuerlinckx<tomoki.tokuda@psy.kuleuven.be>
<francis.tuerlinckx@psy.kuleuven.be>
R (>= 2.12.0), bayesm, MASS, clusterGeneration, TeachingDemos,
scatterplot3d, KernSmooth
Visualization of distributions of covariance matrices

Visualizing of distributions of covariance matrices
Tomoki Tokuda <tomoki.tokuda@psy.kuleuven.be>; Ben Goodrich
<bg2382@columbia.edu>; Iven Van Mechelen
<iven.vanmechelen@psy.kuleuven.be>; Andrew Gelman
<gelman@stat.columbia.edu>; Francis Tuerlinckx
<francis.tuerlinckx@psy.kuleuven.be>
Tomoki Tokuda <tomoki.tokuda@psy.kuleuven.be>; Francis
Tuerlinckx <francis.tuerlinckx@psy.kuleuven.be>

Modeling and Forecasting Visitor Counts Using Social Media
c(
person("Russell", "Goebel", email = "rgoebel@bu.edu", role = "aut"),
person("Robert", "Bowen", email = "robertbowen.bham@gmail.com", role = c("aut", "cre")),
person("Beth Ann", "Brackett", email = "eliannkb@gmail.com", role = "ctb"),
person("Kimihiro", "Noguchi", email = "Kimihiro.noguchi@wwu.edu", role = "aut")
)
Russell Goebel [aut],
Robert Bowen [aut, cre],
Beth Ann Brackett [ctb],
Kimihiro Noguchi [aut]
Performs modeling and forecasting of park visitor counts
using social media data and (partial) on-site visitor counts.
Specifically, the model is built based on an automatic decomposition
of the trend and seasonal components of the social media-based park visitor counts,
from which short-term forecasts of the visitor counts and percent changes
in the visitor counts can be made. A reference for generating social media-based
visitor counts can be found at
Wood, Guerry, Silver, and Lacayo (2013) <doi:10.1038/srep02976>.
Rssa, ggplot2, ggthemes, tibble, methods