HBSTM: hbstm.fit – R documentation

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hbstm.fit

Fitted function for Hierarchical Bayesian Space Time models

Description

This is the basic computing engine that hbstm uses to fit Hierarchical Bayesian Space Time models. In general, this should not be used directly, unless by experienced users.

Usage

hbstm.fit(HBSTM,nIter,nBurn,time,timerem,plots,posterior,save)

Arguments

`HBSTM`	An object of class `"HBSTM"`.
`nIter`	Number of Gibbs Sampling iterations. Default value is 1000.
`nBurn`	Number of burn-in samples. This number of samples will be discarded before making any inference. Default value is the 20 percent of nIter.
`time`	A `"logical"` indicating whether the method shows the estimated time of execution.
`timerem`	A `"logical"` indicating whether the method shows the estimated remaining time of execution.
`plots`	A `"logical"` indicating whether the method shows the plots of the execution (the mse, Zt vs K*Yt and the ACF/PACF of the residuals

`posterior`	A `"character"` indicating whether the function returns the mean and the standard deviation of the fitted values of Yt or returns the median with its 95 percent credibility intervals.
`save`	A `"character"` indicating if, for each iteration, the algorithm save the estimation of certain parameters. See "Details" for more information.

Details

The save argument is a "character" that can have any of the following options:

-"all": Save an object of class Parameters.

-"Mu": Save an object of class Mu.

-"Mt": Save an object of class Mt.

-"Xt": Save an object of class Xt.

Value

hbstm.fit returns an object of class HBSTM

Author(s)

Pilar Munyoz and Alberto Lopez Moreno

Examples

## See 'tutorial.pdf', included in the documentation of the package, to see a full example

HBSTM

Hierarchical Bayesian Space-Time models for Gaussian space-time data.

v1.0.1

GPL (>= 2.0)

Authors

Pilar Munyoz, Alberto Lopez Moreno

Initial release

2014-1-18