| Library: | eiv |
| See also: | eivknownatt eivknownratue |
| Quantlet: | 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. |
| Usage: | {mux,beta1,beta0,sigmax,sigmae,varbeta1,varbeta0} = eivknownvaru(w,y,sigmau) | |
| Input: | ||
| w | 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 | |
| varbeta1 | scalar, the estimate of the variance of the estimate of beta1 | |
| varbeta0 | scalar, the estimate of the variance of the estimate of beta0 | |
library("eiv")
n = 100
randomize(n)
x=9*normal(n)
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
gest.varbeta1 ; the estimate of the variance of the estimate of beta1
gest.varbeta0 ; the estimate of the variance of the estimate of beta0
Contents of mux [1,] -0.93396 Contents of beta1 [1,] 0.89725 Contents of beta0 [1,] 0.42382 Contents of sigmax [1,] 64.17 Contents of sigmae [1,] 1.3344 Contents of varbeta1 [1,] 0.036895 Contents of varbeta0 [1,] 0.70441