# SpatParam-class: Class '"SpatParam"' In HBSTM: Hierarchical Bayesian Space-Time Models for Gaussian Space-Time Data

 SpatParam-class R Documentation

## Class `"SpatParam"`

### Description

`"SpatParam"` contains the values of the spatial parameters and is an internal class stored in the classes `"Mu"` and `"Autorregressive"`.

### Slots

`alpha`:

A `"vector"` of length: the number of horizontal (east-west) spatial lags. It contains the fitted values of the horizontal spatial parameters.

`beta`:

A `"vector"` of length: the number of vertical (north-south) spatial lags. It contains the fitted values of the vertical spatial parameters.

`phi`:

A `"vector"` of length: the number of diagonal (southeast-northwest) spatial lags. It contains the fitted values of the diagonal spatial parameters.

`theta`:

A `"vector"` of length: the number of inverse-diagonal (southwest-northeast) spatial lags. It contains the fitted values of the inverse-diagonal spatial parameters.

`Cmat`:

An SxS `"matrix"` (S is the number of spatial points of the predicted grid) containing all the spatial parameters.

`lags`:

A `"vector"` containing the spatial lags for each direction. Each position of the vector is related to the lags of alpha, beta, phi and theta, respectively.

`dirs`:

A `"vector"` containing the considered spatial directions of the model.

### Methods

[

`signature(x = "SpatParam", i = "character", j = "missing", drop = "missing")`: extract the components of the model.

[<-

`signature(x = "SpatParam", i = "character", j = "missing")`: assign values to the components of the model.

### Author(s)

Pilar Munyoz and Alberto Lopez Moreno

Overview: `HBSTM-package`
Classes : ```HBSTM,Parameters,Mu,Mt,Xt,Autoregressive,Seas,SpatParam,VectSubdiag, Hyperpriors,Mu0,Mt0,Xt0,Seas0,Autoregressive0,SpatParam0,VectSubdiag0```
Methods : `hbstm,hbstm.fit,results,estimation,resid,mse`
Plot : `plotRes,plotFit`
Data: `hirlam,coordinates`