Packaged: Tue Jun 17 18:40:17 2008; arthur

Packaged: Fri Jan 30 18:08:58 2009; arthur

Packaged: Thu Apr 9 18:30:24 2009; arthur

Title: Nelson-Aalen Estimator of the Cumulative Hazard in Multistate
Description: Computes the Nelson-Aalen estimator of the cumulative transition hazard for arbitrary Markov multistate models <ISBN:978-0-387-68560-1>.

Author: Matteo Fasiolo, employing the C++ parallel RNG provided by Thijs van den Berg
Description: The package provides computationally efficient tools related to the multivariate normal distribution. The main functionalities are: simulating multivariate normal random vectors, evaluating multivariate normal densities and Mahalanobis distances. These tools are very efficient thanks to the use of C++ code and of the OpenMP API.
Suggests: knitr, testthat, mvtnorm, microbenchmark, MASS, plyr

Author: Matteo Fasiolo, using the C++ parallel RNG of Thijs van den Berg and Ziggurat algorithm of Jens Maurer and Steven Watanabe (boost)

Author: Matteo Fasiolo, using the C++ parallel RNG of Thijs van den Berg and
Ziggurat algorithm of Jens Maurer and Steven Watanabe (boost)
Description: Provides computationally efficient tools related to
the multivariate normal distribution. The main functionalities are:
simulating multivariate normal random vectors, evaluating multivariate
normal densities and Mahalanobis distances. These tools are very efficient
thanks to the use of C++ code and of the OpenMP API.

Suggests: knitr, testthat, mvtnorm, microbenchmark, MASS, plyr,

Title: Fast Multivariate Normal and Student's t Methods
the multivariate normal and Student's t distributions. The main functionalities are:
simulating multivariate random vectors, evaluating multivariate
normal or Student's t densities and Mahalanobis distances. These tools are very efficient

Author: Matteo Fasiolo, using the C++ parallel RNG of Thijs van den Berg

person("Thijs", " van den Berg", role = c("ctb")))
Suggests: knitr, rmarkdown, testthat, mvtnorm, microbenchmark, MASS,

Description: Provides computationally efficient tools related to the
multivariate normal and Student's t distributions. The main functionalities
are: simulating multivariate random vectors, evaluating multivariate normal or
Student's t densities and Mahalanobis distances. These tools are very efficient