MWG: Metropolis within Gibbs algorithm for RSMD

In agathasr/rsmd: Fits the weibull, gamma, lognormal or loglogistic model for repairable system with masked data.

Description

MWG obtains MCMC sample from posterior distribution via MwG algorithm for RSMD (Repairable System Masked Data).

Usage

MWG(guess, Data, distribution, burn, jump, prior1, prior2, n.size = 1000)

Arguments

guess	Vector of initial values for the parameters. The default are (0,0).
Data	Data in the format as data_to_rsmd.
distribution	The chose distribution: weibull, gamma, lnorm, llogis.
burn	Burn-in sample.
jump	Jump sample.
prior1	Hyperparameter for prior distribution for parameter 1.
prior2	Hyperparameter for prior distribution for parameter 2.
n.size	Number of MCMC sample.

Value

A list with the following components:

post.values	Samples from posterior distribution with size n.size.
acceptance	Acceptance rate.
time	Computational time.
matrix.cpo	n.sys by n.size matrix cointaining CPO values for n.sys systems in n.size posterior sample.

agathasr/rsmd documentation built on May 4, 2020, 4:09 p.m.