mcsm: Functions for Monte Carlo Methods with R

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.

AuthorChristian P. Robert, Universite Paris Dauphine
Date of publication2009-04-28 10:10:13
MaintainerChristian P. Robert <xian@ceremade.dauphine.fr>
LicenseGPL (>= 2)
Version1.0

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

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