Library: | eiv |
See also: | eivknownvaru eivknownratue |
Macro: | eivknownatt | |
Description: | eivknownatt presents the moment estimates of the parameters in the measurement error models, which has only one variable x. The degree of attenuation (also called reliability ratio) is known. All of the variables obey normal distributions. See Fuller(1987), section 1.1 |
Usage: | {mux,beta1,beta0,sigmax,sigmau,sigmae} = eivknownatt(X,Y,kxx) | |
Input: | ||
X | n x 1 matrix, the design variables | |
Y | n x 1 matrix, the response | |
kxx | scalar, the degree of attenuation | |
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 | |
sigmau | scalar, the estimate of the variance of u | |
sigmae | scalar, the estimate of the variance of e |
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) kwx =0.5 gest=eivknownatt(w,Y,kwx) gest.mux ; the estimate of the mean of X gest.beta1 ; the estimate of b (true value is 0.8) gest.beta0 ; the estimate of a (true value is 0.9) gest.sigmax ; the estimate of the variance of x gest.sigmau ; the estimate of the variance of u gest.sigmae ; the estimate of the variance of e
gest.mux=-0.93396; gest.beta1=0.7853 gest.beta0=0.31926; gest.sigmax=72.585 gest.sigmau=72.585; gest.sigmae=8.2323
Library: | eiv |
See also: | eivknownvaru eivknownratue |