| 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 | |
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
Contents of b [1,] 9.97 [2,] 1.9116 [3,] 3.0123
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
Contents of b2 [1,] 9.9977 [2,] 1.9946 [3,] 3.0093
| Library: | xplore |