Author: Josep A. Sanchez-Espigares, Alberto Lopez-Moreno
Maintainer: Josep A. Sanchez-Espigares <josep.a.sanchez@upc.edu>
Description: Univariate Autoregressive Markov Switching Models for
Depends: methods, nlme, graphics, snowfall

Depends: methods, nlme, graphics, parallel

Description: Univariate Autoregressive Markov Switching Models for Linear and Generalized Models

Description: 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.

Description: 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>).

email = "ronan.ysebaert@cnrs.fr", role = c("aut")),
email = "nicolas.lambert@cnrs.fr", role = c("aut")),
email = "timothee.giraud@cnrs.fr", role = c("aut", "cre")))
Description: Build multiscalar territorial analysis based on various contexts.
Suggests: cartography, knitr, rmarkdown, ineq, png, reshape2

Imports: methods, stats, sp, igraph, sf, cartography
Suggests: knitr, rmarkdown, ineq, png, reshape2

Imports: methods, stats, graphics, igraph, sf, cartography

Imports: methods, stats, graphics, igraph, sf
Suggests: knitr, rmarkdown, ineq, png, mapsf

Title: Multi-Trait Analysis of Rare-Variant Association Study
Authors@R: c(person("Lan", "Luo", role = c("aut", "cre"), email =
Description: 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).
CompQuadForm (>= 1.4.3), stats, graphics, grDevices, Matrix (>=

Imports: CompQuadForm (>= 1.4.3), MASS (>= 7.3-51.4), Matrix (>=