.BayesFitTFP | R Documentation |
Estimates the parameters and states of a two-dimensional state-space model by Bayesian methods to obtain the tfp trend.
.BayesFitTFP(
model,
prior = initializePrior(model),
R = 10000,
burnin = ceiling(R/10),
thin = 1,
HPDIprob = 0.85,
FUN = mean,
MLEfit = NULL
)
model |
An object of class TFPmodel. |
prior |
A list of matrices with parameters for the prior distribution and box
constraints. By default, |
R |
An integer specifying the number of MCMC draws. The default is |
burnin |
An integer specifying the burn-in phase of the MCMC chain. The default is
|
thin |
An integer specifying the thinning interval between consecutive draws. The
default is |
HPDIprob |
A numeric in the interval |
FUN |
A function to be used to compute estimates from the posterior distribution.
Possible options are |
MLEfit |
(Optional) An object of class |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.