Name
Title | ||
|---|---|---|
Minimum MSE regression estimator with estimated population quantities of auxiliary variables |
Abstract | ||
|---|---|---|
Construction of a regression estimator in which the population means of auxiliary variables are estimated with a larger sample is considered. Using the variances of the estimated population means, and the correlation between auxiliary variables and the variable of interest, a design consistent regression estimator that has minimum model mean squared error under a working model is derived. A limited simulation study shows that the minimum model mean squared error regression estimator performs well compared to the generalized least squares regression estimator, even when the working model is inappropriate. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.csda.2008.08.003 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
estimated population,error regression estimator,squares regression estimator,limited simulation study,estimated population quantity,minimum mse regression estimator,auxiliary variable,regression estimator,minimum model,larger sample,design consistent regression estimator,working model,generalized least squares,mean square error | Econometrics,Efficient estimator,Minimum-variance unbiased estimator,James–Stein estimator,Newey–West estimator,Mean squared error,Bias of an estimator,Statistics,Mathematics,Estimator,Consistent estimator | Journal |
Volume | Issue | ISSN |
53 | 2 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mingue Park | 1 | 1 | 1.11 |
| Hyungjun Cho | 2 | 104 | 8.44 |