rec.reg: Computes Recursive Regression.

Description

This function computes Recursive Regression.

Usage

rec.reg(y,x=NULL,c=NULL)

Value

class reg object, list of

$y.hat: fitted (forecasted) values
$AIC: Akaike Information Criterion (from the current set of observations)
$AICc: Akaike Information Criterion with a correction for finite sample sizes (from the current set of observations)
$BIC: Bayesian Information Criterion (from the current set of observations)
$MSE: Mean Squared Error (from the current set of observations)
$coeff.: regression coefficients
$p.val: p-values for t-test for statistical significance of regression coefficients
$y: y, forecasted time-series

Arguments

y: numeric or a column matrix of a dependent variable
x: matrix of independent variables, different columns should correspond to different variables, if not specified only a constant will be used
c: optional, logical, a parameter indicating whether constant is included, if not specified c=TRUE is used, i.e., constant is included

Details

It might happen during computations that lm (which is used inside rec.reg) will produce NA or NaN. In such a case regression coefficients for a given period are taken as $0$ and p-values for t-test for statistical significance of regression coefficients are taken as $1$.

It is not possible to set c=FALSE if x=NULL. In such a case the function will automatically reset c=TRUE inside the code.

Examples

Run this code

wti <- crudeoil[-1,1]
drivers <- (lag(crudeoil[,-1],k=1))[-1,]
ld.wti <- (diff(log(wti)))[-1,]
ld.drivers <- (diff(log(drivers)))[-1,]
rec1 <- rec.reg(y=ld.wti,x=ld.drivers)
rec2 <- rec.reg(y=ld.wti)