Imports: alabama, evd, methods, nleqslv, nloptr (>= 1.2.0), Rcpp (>=
Suggests: boot, cobs, knitr, MASS, mvPot (>= 0.1.4), mvtnorm, gmm,
revdbayes, ismev, tinytest, TruncatedNormal (>= 1.1)

Description: Exact simulation from max-stable processes and multivariate extreme value distributions for various parametric models.

Authors@R: c(person(given="Leo", family="Belzile", role = c("aut", "cre"),
email = "leo.belzile@epfl.ch"), person(given="Jennifer L.", family="Wadsworth", role=c("aut")), person(given="Paul J.", family="Northrop", role=c("aut")), person(given="Claire L.", family="Coleman", role=c("aut")))
Imports: stats, Rcpp (>= 0.11.6), ismev, evd

Authors@R: c(person(given="Leo", family="Belzile", role = c("aut", "cre"), email = "leo.belzile@epfl.ch"), person(given="Jennifer L.", family="Wadsworth", role=c("aut")), person(given="Paul J.", family="Northrop", role=c("aut")), person(given="Claire L.", family="Coleman", role=c("aut")), person(given="Jin.", family="Zhang", role=c("ctb")), person(given="Michael A.", family="Newton", role=c("ctb")), person(given="Art", family="Owen", role=c("ctb")))

Title: A Fixed Memeory Moving Expanding Window Average
Author: Adam L. Pintar and Zachary H. Levine
Maintainer: Adam L. Pintar <adam.pintar@nist.gov>
Description: Computes the average of a sequence of random vectors
in a moving expanding window using a fixed amount of storage

Description: Compute the average of a sequence of random vectors
in a moving expanding window using a fixed amount of memory.

Title: Mixed Effect Excess Hazard Models
Description: Fit flexible (excess) hazard regression models with a random effect defined at the cluster level.

Description: Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty).
Imports: statmod, MASS, numDeriv, splines, lamW

Description: Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty). A detailed description of the package functionalities is provided in Charvat and Belot (2021) <doi: 10.18637/jss.v098.i14>.