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: stats
See also: gls linreg linregfs

Quantlet: linregres
Description: linregres computes some residual analysis for a linear regression.

Reference(s):

Usage: {res,out} = linregres (x, y, yh)
Input:
x n x p regressors
y n x 1
yh n x 1
Output:
xfs n x 4
out n x 2

Note:

Example:

; loads the library stats

library("stats")   

; reset random generator 

randomize(0)

; generate x

x = normal(100, 3)

; generate y

y = 10*x[,3]+x[,1].*x[,2]

; do the forward selection

{xfs,bfs}=linregfs(x, y, 0.05)

; compute residual number

{res,out}=linregres(xfs, y, xfs*bfs)

; create a display fro plotting

disp = createdisplay(2,2)

; show residual plots

;    residuals               leverage   

;    standardized residuals  Cook distance

show (disp, 1, 1, y~res[,1])

show (disp, 2, 1, y~res[,3])

show (disp, 1, 2, y~res[,2])

show (disp, 2, 2, y~res[,4])

Result:

shows the residual plots. From the standardized residuals

we find three points in the bottom with an absolute value 

larger than 3. The leverage plot shows on the right and

the left sets of points with a leverage larger than 0.04

(thus they are influential). The Cook distance plot shows 

no datapoints larger than 1 and we can not find outliers

in x. 


Library: stats
See also: gls linreg linregfs

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: Sigbert Klinke 970522
(C) MD*TECH Method and Data Technologies, 21.9.2000