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: eiv
See also: eivknownatt eivknownratue

Macro: eivknownvaru
Description: eivknownvaru presents the moment estimates of the parameters in the measurement error models, which has only one variable x. The variance of measurement error sigma_u is known. All of the variables obey normal distributions. See Fuller(1987), section 1.2.

Link:
Usage: {mux,beta1,beta0,sigmax, sigmae} = eivknownvaru(X,Y,sigmau)
Input:
X n x 1 matrix, the design variables
Y n x 1 matrix, the response
sigmau scalar, the variance of measurement error sigma_u
Output:
mux scalar, the mean value of X
beta1 scalar, the estimate
beta0 scalar, the estimate
sigmax scalar, the estimate of the variance of X
sigmae scalar, the estimate of the variance of error e

Example:
library("eiv")
n = 100
randomize(n)
x= normal(n)*9
w=x+9*normal(n)
Y =0.9+0.8*x+0.01*normal(n)
sigmau=81
gest=eivknownvaru(w,Y,sigmau)
gest.mux
gest.beta1
gest.beta0
gest.sigmax
gest.sigmae
Result:
gest.mux=-0.93396; gest.beta1=0.88828
gest.beta0=0.41544
gest.sigmax=64.17; gest.sigmae=2.3624

Library: eiv
See also: eivknownatt eivknownratue

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: Hua Liang, 961212
(C) MD*TECH Method and Data Technologies, 28.6.1999