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: xplore

Quantlet: gls
Description: Computes the Generalized Least Squares estimate for the coefficients of a linear model when the errors have as covariance matrix sigma^2 * om.

Usage: b = gls (x, y{, om})
Input:
x n x p x d1 x ... x dn array
y n x 1 x d1 x ... x dn array
om optional, n x n x d1 x ... x dn array
Output:
b p x 1 x d1 x ... x dn array

Note:

Example:

library("xplore")

randomize(1964)

n = 50

x = matrix(n)~normal(n,2)

beta = #(10, 2, 3)

u = 0.5 * normal(n)

y = x*beta .+ u

b = gls (x, y)

b

Result:

Contents of b

[1,]     9.97 

[2,]   1.9116 

[3,]   3.0123 

Example:

library("xplore")

randomize(1964)

n = 50

x = matrix(n)~normal(n,2)

beta = #(10, 2, 3) 

covar = (0.5.*x[,2] .+ 0.3.*x[,3]).^2

y = x*beta .+ sqrt(covar).*u

b2 = gls (x, y, diag(covar))

b2

Result:

Contents of b2

[1,]   9.9977 

[2,]   1.9946 

[3,]   3.0093  


Library: xplore

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, 920424, 960327, 960425
(C) MD*TECH Method and Data Technologies, 21.9.2000