# ar.egls: Subset Autoregressive Model In LPM: Linear Parametric Models Applied to Hydrological Series

## Description

Estimate VAR(p) model fixing some parameter values to zero

## Usage

 `1` ```ar.egls(x, R, order.max , na.action = na.fail, series = NULL, ...) ```

## Arguments

 `x` Univariate or multivariate series with nil mean `R` Matrices of parameters selection `order.max` Model order `na.action` Function to be called to handle missing values `series` Names for the series. Defaults to 'deparse(substitute(x))' `...` See ar.ols

## Details

R matrix is a list of p matrices, with p the autoregressive order. In R value '1' allows parameter estimation, '0' fix the parameter value to zero.

See ar.ols

## Note

Function is created modifing ar.ols by Adrian Trapletti and Brian Ripley

## References

Grimaldi S. , Serinaldi F. & Tallerini C. (2004) 'Multivariate linear parametric models applied to daily rainfall time series' Mediterranean Storms, 6rd EGU Plinius Conference held in Mediterranean Sea, Italy, October 2004

Lutkepohl, H. (1993) Introduction to Multiple Time Series Analysis 2nd Edition ._ Springer Verlag, NY

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```## S1=matrix(0,3,3) ## S1[1,1]=1 ## S1[1,2]=1 ## S=list() ## S[[1]]=S1 ## S[[2]]=S1 ## ar.egls(series.rainfall[,1:3],S,order.max=2) ## --> Apply a Subset VAR(2) model restricted to 4 parameters (position (1,1) ## --> and (1,2) in both matrices) to first 3 series of series.rainfall ## --> dataset ```

LPM documentation built on Jan. 26, 2020, 1:07 a.m.