MetropolisHastingsCppD: C++ implementation of the algorithm for parameter calibration...

Description Usage Arguments Value

Description

Run a Metropolis Hastings within Gibbs algorithm and a Metropolis Hastings algorithm with the covariance matrix estimated on the the sample set generated in the Metropolis within Gibbs. This algorithm is suitable only for models with discrepancy.

Usage

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MetropolisHastingsCppD(Ngibbs, Nmh, theta_init, r, SIGMA, Yf, binf, bsup,
  LogTest, stream)

Arguments

Ngibbs

the number of iteration in the Metropolis within Gibbs

Nmh

the number of iteration in the Metropolis Hastings

theta_init

the starting point

r

regulation percentage in the modification of the k

SIGMA

the covariance of the proposition distribution

Yf

the vector of recorded data

binf

the lower bound of the parameters to calibrate

bsup

the upper bound of the parameters to calibrate

LogTest

the log posterior density distribution

stream

(default=1) if stream=0 the progress bar is disabled

Value

list of outputs:


CaliCo documentation built on May 2, 2019, 4:05 p.m.