Name
Abstract | ||
|---|---|---|
In this paper, we consider the application of the empirical likelihood method to a partly linear model with measurement errors in possibly all the variables. It is shown that the empirical log-likelihood ratio at the true parameters converges to the standard chi-square distribution. Also, a class of estimators for the parameter are constructed, and the asymptotic distributions of the proposed estimators are obtained. Some simulations and an application are conducted to illustrate the proposed method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.jmva.2014.06.007 | Journal of Multivariate Analysis |
Keywords | Field | DocType |
62f12,62g05,maximum empirical likelihood estimate,measurement error,confidence regions,coverage probability,empirical likelihood | Econometrics,M-estimator,Likelihood function,Likelihood-ratio test,Empirical likelihood,Empirical probability,Restricted maximum likelihood,Statistics,Mathematics,Estimator,Likelihood principle | Journal |
Volume | Issue | ISSN |
130 | 1 | 0047-259X |
Citations | PageRank | References |
2 | 0.71 | 0 |
Authors | ||
2 | ||