dot-checkBayesInput: Checks the input parameters of '.BayesFitTFP' and...

In RGAP: Production Function Output Gap Estimation

Checks the input parameters of .BayesFitTFP and .BayesFitNAWRU for consistency.

Description

Checks the input parameters of .BayesFitTFP and .BayesFitNAWRU for consistency.

Usage

.checkBayesInput(
  model,
  type,
  prior = NULL,
  R = NULL,
  burnin = NULL,
  thin = NULL,
  HPDIprob = NULL,
  FUN = NULL,
  MLEfit = NULL
)

Arguments

model	An object of class TFPmodel.
type	A character specifying whether a "nawru" or "tfp" model should be checked.
prior	A list of matrices with parameters for the prior distribution and box constraints. By default, prior is initialized by initializePrior(model). See details. Only used if method = "bayesian".
R	An integer specifying the number of MCMC draws. The default is R = 10000. Only used if method = "bayesian".
burnin	An integer specifying the burn-in phase of the MCMC chain. The default is burnin = ceiling(R / 10). Only used if method = "bayesian".
thin	An integer specifying the thinning interval between consecutive draws. The default is thin = 1, implying that no draws are dopped. For thin = 2, every second draw is dropped and so on. Only used if method = "bayesian".
HPDIprob	A numeric in the interval (0,1) specifying the target probability of the highest posterior density intervals. The default is HPDIprob = 0.9. Only used if method = "bayesian".
FUN	A function to be used to compute estimates from the posterior distribution. Possible options are "mean" and "median". The default is FUN = "mean". Only used if method = "bayesian".
MLEfit	(Optional) An object of class TFPfit which is used for initialization. Only used if method = "bayesian".

RGAP documentation built on Nov. 2, 2023, 6:02 p.m.