Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: cafpe
See also: tp/cafpe/xorigst

Quantlet: xorigex
Description: Quantlet to construct matrix of lagged variables

Usage: { xorigau,yorig }= xorigex(xraw,xresid,lags,volat)
Input:
xraw n x 1 matrix, the observed time series
xresid (nr x 1) vector of residuals for selecting lags of conditional volatility function; if not needed set xresid = 0
lags (d x 1) vector of lags to be considered
volat "no": lag selection for conditional mean function; "resid": lag selection for conditional volatility function, the residuals of fitting a conditional mean function have to be contained in xresid
Output:
xorigau ((t-max(lags)+min(lags)) x d) matrix of regression values
yorig ((t-max(lags)) x 1) matrix of dependent variable

Example:
pathcafpe = "tp/cafpe/"
func(pathcafpe + "xorigex.xpl")
xraw = #(1:100)
lags = 1|10
{ xorigau,yorig }= xorigex(xraw,0,lags,"no")
"xorigau" xorigau
"yorig" yorig
Result:
The matrix of dependent and independent variables
Note that for regressing yorig on xorigau you have to
use the submatrix
xorig = xorigau[1:rows(yorig),]
since xorigau contains all possible observations for density
estimation

Library: cafpe
See also: tp/cafpe/xorigst

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Author: Tschernig 000420
(C) MD*TECH Method and Data Technologies, 27.4.2000