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

 Quantlet: simex Description: SIMEX (SIMulation EXtrapolation) is a simulation-based method of estimating and reducing bias due to measurement error. simex is applicable to general estimation methods, for example, least-squares, maximum likelihood, quasi-likelihood, etc.

Reference(s):
The 5th and 6th chapters of Carroll, R.J., Ruppert, D. and Stefanski, L.A. (1995): Nonlinear Measurement Error Models. Chapman and Hall, New York.

 Usage: {simexl,simexq} = simex(y, w, z, su2, lam, b) Input: y n x 1 matrix, the design variables w n x 1 matrix, surrogate variable of unobservable variable z n x 1 matrix, covariate measured without error su2 the variance of the measurement error lam pseudo-parameter for generating pseudo-errors b the number of replication in each simulation Output: simexl the estimate based on linear extrapolant function simexq the estimate based on quadratic extrapolant function

Example:
```library("xplore")
library("eiv")
n=100
randomize(n)
y=floor(uniform(n)+0.3)
w=uniform(n)^2
z=floor(uniform(n)+0.45)
su2=var(w)/4
lam=aseq(0.01,6,0.5)
b=20
gest=simex(y,w,z,su2,lam,b)
gest.simexl
gest.simexq

```
Result:
```Contents of simexl
[1,]  -2.2569  0.92894  0.90323
Contents of simexq
[1,]  -2.265   0.95407  0.90822
```

Author: H. Liang, W. Haerdle, 19970818 license MD*Tech
(C) MD*TECH Method and Data Technologies, 05.02.2006