Semiparametric Likelihood Ratio Inference Revisited
ثبت نشده
چکیده
منابع مشابه
Semiparametric Likelihood Ratio Inference Revisited
2000 We extend the Semiparametric Likelihood Ratio Theorem of Murphy and Van del' Vaart for one-dimensional to Euclidean paramet(;rs of auy dimension. The as:VIrlptotic distribution of the likelihood ratio statistic for testing a k-dimensional Euclidean paramet'"r is shown to be the usual under the null hypothesis. This result is useful not only for testing purposes but also in forming likeliho...
متن کاملMerging Information for Semiparametric Density Estimation
KONSTANTINOS FOKIANOS Abstra t. The density ratio model specifies that the likelihood ratio of m 1 probability density functions with respect to the m’th is of known parametric form without reference to any parametric model. We study the semiparametric inference problem related to the density ratio model by appealing to the methodology of empirical likelihood. The combined data from all the sam...
متن کاملA Note on Empirical Likelihood Inference of Residual Life Regression
Mean residual life function, or life expectancy, is an important function to characterize distribution of residual life. The proportional mean residual life model by Oakes and Dasu (1990) is a regression tool to study the association between life expectancy and its associated covariates. Although semiparametric inference procedures have been proposed in the literature, the accuracy of such proc...
متن کاملSemiparametric Regression Analysis under Imputation for Missing Response Data
We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator, a marginal average estimator and a (marginal) propensity score weighted estimator are defined. All the estimators are proved to be asymptotically normal, with the same asymptotic variance. They achieve the semiparametric efficiency bound in the homoskedas...
متن کاملCase–Control Studies and Monte Carlo Methods
It is well known that the presence of untractable normalizing constants in a probability density function complicates the calculation of maximum likelihood estimators. Usually numerical or Monte Carlo methods are employed in order to obtain an approximation. We propose a new statistical method for carrying out the calculations regarding maximum likelihood estimation by avoiding calculation of t...
متن کامل