rmunorm
(Package: mcsm) :
Random generator for the multivariate normal distribution
This function produces one random vector distributed from the multivariate normal distribution N(mu,sig).
● Data Source:
CranContrib
● Keywords: distribution
● Alias: rmunorm
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pimamh
(Package: mcsm) :
Langevin MCMC algorithm for the probit posterior
This function implements a Langevin version of the Metropolis-Hastings algorithm on the posterior of a probit model, applied to the Pima.tr dataset.
● Data Source:
CranContrib
● Keywords: datagen, hplot, optimize
● Alias: pimamh
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mhmix
(Package: mcsm) :
Implement two Metropolis-Hastings algorithms on a mixture posterior
This function runs a Metropolis-Hastings algorithm on a posterior distribution associated with a mixture model and 500 datapoints. Depending on the value of the boolean indicator lange, the function uses a regular Gaussian random-walk proposal or a Langevin alternative.
● Data Source:
CranContrib
● Keywords: datagen, hplot
● Alias: mhmix
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dyadic
(Package: mcsm) :
A dyadic antithetic improvement for a toy problem
Using dyadic replicas of a uniform sample, when evaluating the mean of h(x)=(cos(50*x) +sin(20*x))^2, this function shows the corresponding improvement in variance. The parameter q is used to break the unit interval into 2^q blocks where a transform of the original uniform sample is duplicated.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: dyadic
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test2
(Package: mcsm) :
Generic chi-square generator
This function is a front-end for rchisq, designed for comparison with test1.
● Data Source:
CranContrib
● Keywords: datagen, distribution
● Alias: test2
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sqar
(Package: mcsm) :
Illustration of some of coda's criterions on the noisy squared AR model
This function illustrates some of coda's criterions on the noisy squared AR model, using a Metro-polis-Has-tings algorithm based on a random walk. Depending on the value of the boolean multies, those criterions are either the geweke.diag and heidel.diag diagnostics, along with a Kolmo-gorov-Smir-nov test of our own, or plot(mcmc.list()) if several parallel chains are produced together.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: sqar
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betagen
(Package: mcsm) :
Plot explaining accept-reject on a Beta(2.7,6.3) target
This function of Nsim represents Nsim points simulated from either a uniform or a Beta(2,6) proposal in terms of their location above versus below the density of the Beta(2.7,6.3) target in order to explain accept-reject methods.
● Data Source:
CranContrib
● Keywords: datagen, distribution, hplot
● Alias: betagen, rbeta
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normbyde
(Package: mcsm) :
Compare two double-exponentials approximations to a normal distribution
This simple program compares a double-exponential distribution with parameter a=1 and a double-exponential distribution with parameter a!=1 in their approximation to the standard normal distribution. Quite obviously, this function is not to be used when compared when rnorm.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: normbyde
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maximple
(Package: mcsm) :
Graphical representation of a toy example of simulated annealing
For the toy function h(x)=(cos(50*x)+sin(20*x))^2, this function represents simulated annealing sequences converging to a local or global maxima as paths on top of the function h itself. The simulated annealing parameters ratemp and powemp can be changed, as well as the stopping rule tolerance.
● Data Source:
CranContrib
● Keywords: optimize
● Alias: maximple
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sqaradap
(Package: mcsm) :
Illustration of the dangers of doing adaptive MCMC on a noisy squared AR model
This function constructs a non-parametric proposal after each iteration of the MCMC algorithm, based on the earlier simulations. It shows how poorly this "natural" solution fares.
● Data Source:
CranContrib
● Keywords: hplot
● Alias: sqaradap
●
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