mcsm: Functions for Monte Carlo Methods with R

Share:

mcsm contains a collection of functions that allows the reenactment of the R programs used in the book EnteR Monte Carlo Methods without further programming. Programs being available as well, they can be modified by the user to conduct one's own simulations.

Author
Christian P. Robert, Universite Paris Dauphine
Date of publication
2009-04-28 10:10:13
Maintainer
Christian P. Robert <xian@ceremade.dauphine.fr>
License
GPL (>= 2)
Version
1.0

View on CRAN

Man pages

adapump
Illustration of the danger of adaptive MCMC for the pump...
betagen
Plot explaining accept-reject on a Beta(2.7,6.3) target
Braking
Quadratic regression on the car braking dataset
challenge
Slice sampler analysis of the challenger dataset
challenger
O-ring failures against temperature for shuttle launches
dmunorm
Density function of the multivariate normal distribution
dyadic
A dyadic antithetic improvement for a toy problem
EMcenso
EM paths for a censored normal model
Energy
Energy intake
gibbsmix
Implementation of a Gibbs sampler on a mixture posterior
hastings
Reproduction of Hastings' experiment
jamestein
Monte Carlo plots of the risks of James-Stein estimators
kscheck
Convergence assessment for the pump failure data
logima
Logistic analysis of the Pima.tr dataset with control...
maximple
Graphical representation of a toy example of simulated...
mhmix
Implement two Metropolis-Hastings algorithms on a mixture...
mochoice
An MCMC model choice illustration for the linear model
mump
Illustration of Gelman and Rubin's diagnostic on the pump...
normbyde
Compare two double-exponentials approximations to a normal...
pimamh
Langevin MCMC algorithm for the probit posterior
pimax
Monte Carlo approximation of a probit posterior marginal
randogibs
First illustrations of coda's output for the one-way random...
randogit
MCEM resolution for a probit maximum likelihood
randomeff
Gibbs sampler for a one-way random effect model
rdirichlet
Dirichlet generator
reparareff
Reparameterized version of the one-way random effect model
rmunorm
Random generator for the multivariate normal distribution
SAmix
Graphical representation of the simulated annealing sequence...
sqar
Illustration of some of coda's criterions on the noisy...
sqaradap
Illustration of the dangers of doing adaptive MCMC on a noisy...
test1
Poor chi-square generator
test2
Generic chi-square generator
test3
Approximate Poisson generator
test4
Replicate Poisson generator

Files in this package

mcsm
mcsm/data
mcsm/data/Energy.txt
mcsm/data/challenger.txt
mcsm/R
mcsm/R/mhmix.R
mcsm/R/SAmix.R
mcsm/R/dmunorm.R
mcsm/R/mump.R
mcsm/R/rdirichlet.R
mcsm/R/betagen.R
mcsm/R/maximple.R
mcsm/R/test1.R
mcsm/R/normbyde.R
mcsm/R/pimax.R
mcsm/R/jamestein.R
mcsm/R/randogit.R
mcsm/R/randomeff.R
mcsm/R/kscheck.R
mcsm/R/mochoice.R
mcsm/R/logima.R
mcsm/R/test3.R
mcsm/R/challenge.R
mcsm/R/rmunorm.R
mcsm/R/dyadic.R
mcsm/R/hastings.R
mcsm/R/adapump.R
mcsm/R/sqar.R
mcsm/R/reparareff.R
mcsm/R/EMcenso.R
mcsm/R/sqaradap.R
mcsm/R/randogibs.R
mcsm/R/gibbsmix.R
mcsm/R/Braking.R
mcsm/R/pimamh.R
mcsm/DESCRIPTION
mcsm/NAMESPACE
mcsm/demo
mcsm/demo/Chapter.1.R
mcsm/demo/Chapter.6.R
mcsm/demo/Chapter.5.R
mcsm/demo/Chapter.4.R
mcsm/demo/Chapter.7.R
mcsm/demo/Chapter.3.R
mcsm/demo/Chapter.8.R
mcsm/demo/Chapter.2.R
mcsm/demo/00Index
mcsm/man
mcsm/man/rmunorm.Rd
mcsm/man/pimamh.Rd
mcsm/man/mhmix.Rd
mcsm/man/dyadic.Rd
mcsm/man/test2.Rd
mcsm/man/sqar.Rd
mcsm/man/betagen.Rd
mcsm/man/normbyde.Rd
mcsm/man/maximple.Rd
mcsm/man/sqaradap.Rd
mcsm/man/test1.Rd
mcsm/man/rdirichlet.Rd
mcsm/man/kscheck.Rd
mcsm/man/randogibs.Rd
mcsm/man/mump.Rd
mcsm/man/dmunorm.Rd
mcsm/man/EMcenso.Rd
mcsm/man/Energy.Rd
mcsm/man/gibbsmix.Rd
mcsm/man/pimax.Rd
mcsm/man/hastings.Rd
mcsm/man/reparareff.Rd
mcsm/man/jamestein.Rd
mcsm/man/mochoice.Rd
mcsm/man/challenger.Rd
mcsm/man/SAmix.Rd
mcsm/man/logima.Rd
mcsm/man/Braking.Rd
mcsm/man/test3.Rd
mcsm/man/randogit.Rd
mcsm/man/test4.Rd
mcsm/man/adapump.Rd
mcsm/man/randomeff.Rd
mcsm/man/challenge.Rd