Josep A. Sanchez-Espigares, Alberto Lopez-Moreno
Univariate Autoregressive Markov Switching Models for
Linear and Generalized Models

Univariate Autoregressive Markov Switching Models for Linear and Generalized Models

Estimation, inference and diagnostics for Univariate Autoregressive Markov Switching Models for Linear and Generalized Models. Distributions for the series include gaussian, Poisson, binomial and gamma cases. The EM algorithm is used for estimation.

Estimation, inference and diagnostics for Univariate Autoregressive Markov Switching Models for Linear and Generalized Models. Distributions for the series include gaussian, Poisson, binomial and gamma cases. The EM algorithm is used for estimation (see Perlin (2012) <doi:10.2139/ssrn.1714016>).

c(person("Ronan", "Ysebaert",
email = "ronan.ysebaert@cnrs.fr", role = c("aut")),
person("Nicolas", "Lambert",
email = "nicolas.lambert@cnrs.fr", role = c("aut")),
person("Timothée", "Giraud",
email = "timothee.giraud@cnrs.fr", role = c("aut", "cre")))
Build multiscalar territorial analysis based on various contexts.
cartography, knitr, rmarkdown, ineq, png, reshape2
Ronan Ysebaert [aut],
Nicolas Lambert [aut],
Timothée Giraud [aut, cre]

methods, stats, sp, igraph, sf, cartography

methods, stats, graphics, igraph, sf, cartography

Multi-Trait Analysis of Rare-Variant Association Study
c(person("Lan", "Luo", role = c("aut", "cre"), email =
"lanluoruc@gmail.com"))
Perform multi-trait rare-variant association tests using the summary statistics and adjust for possible sample overlap. Package is based on "Multi-Trait Analysis of Rare-Variant Association Summary Statistics using MTAR" by Luo, L., Shen, J., Zhang, H., Chhibber, A. Mehrotra, D.V., Tang, Z., 2019 (submitted).
SKAT (>= 1.3.2.1), MASS (>= 7.3-51.4), seqMeta (>= 1.6.7),
CompQuadForm (>= 1.4.3), stats, graphics, grDevices, Matrix (>=
1.2.2), utils

Mass Transportation Distance Rank Histogram
Didem Sari<dsari@iastate.edu>, Sarah M. Ryan <smryan@iastate.edu>
The Mass Transportation Distance rank histogram was developed to assess the reliability of scenarios with equal or different probabilities of occurrence <doi:10.1002/we.1872>.