# PR.IARM: Improved Augmented Regression Method (IARM) for Predictive... In VAR.etp: VAR modelling: estimation, testing, and prediction

## Description

Function for Improved ARM (IARM) estimation and testing

## Usage

 `1` ```PR.IARM(x, y, p, Rmat = diag(k * p), rvec = matrix(0, nrow = k * p)) ```

## Arguments

 `x` predictor or a matrix of predictors in column `y` variable to be predicted, usually data1 return `p` AR order `Rmat` Restriction matrix, refer to function Rmatrix `rvec` Restriction matrix, refer to function Rmatrix

## Details

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance, 26, 13-25.

## Value

 `LS ` Ordinary Least Squares Estimators `IARM ` IARM Estimators `AR ` AR parameter estimators `ARc ` Bias-corrected AR parameter estimators `Fstats ` Fstats and their p-values `Covbc ` Covariance matrix of the IARM estimators (for the predictive coefficients only)

## Note

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance, 26, 13-25.

Jae H. Kim

## References

Kim J.H., 2014, Predictive Regression: Improved Augmented Regression Method, Journal of Empirical Finance, 26, 13-25.

## Examples

 ```1 2 3 4 5 6 7``` ```data(data1) # Replicating Table 5 (excess return) of Kim (2014) y=data1\$ret.nyse.vw*100 -data1\$tbill*100 x=cbind(log(data1\$dy.nyse), data1\$tbill*100); Rmat1=Rmatrix(p=1,k=2,type=1,index=0); Rmat=Rmat1\$Rmat; rvec=Rmat1\$rvec M=PR.IARM(x,y,p=1,Rmat,rvec) ```

VAR.etp documentation built on May 29, 2017, 10:51 a.m.