Observed Information in Semiparametric ModelsS
نویسندگان
چکیده
We discuss the estimation of the asymptotic covariance matrix of semiparametric maximum likelihood estimators by the observed proole information. We show that a discretized version of the second derivative of the proole likelihood function yields consistent estimators of minus the eecient information matrix.
منابع مشابه
Semiparametric Bootstrap Prediction Intervals in time Series
One of the main goals of studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by an autoregressive process. The...
متن کاملSemiparametric Mixtures in Case-control Studies
We consider likelihood based inference in a class of logistic models for case-control studies with a partially observed covariate. The likelihood is a combination of a nonparametric mixture, a parametric likelihood and an empirical likelihood. We prove the asymptotic normality of the maximum likelihood estimator for the regression slope, the asymptotic chisquared distribution of the likelihood ...
متن کاملOn Proole Likelihood
We show that semiparametric proole likelihoods, where the nuisance parameter has been prooled out, behave like ordinary likelihoods in that they have a quadratic expansion. In this expansion the score function and the Fisher information are replaced by the eecient score function and eecient Fisher information, respectively. The expansion may be used, among others, to prove the asymptotic normal...
متن کاملWavelet Threshold Estimator of Semiparametric Regression Function with Correlated Errors
Wavelet analysis is one of the useful techniques in mathematics which is used much in statistics science recently. In this paper, in addition to introduce the wavelet transformation, the wavelet threshold estimation of semiparametric regression model with correlated errors with having Gaussian distribution is determined and the convergence ratio of estimator computed. To evaluate the wavelet th...
متن کاملA Least-Squares Approach to Consistent Information Estimation in Semiparametric Models
A method is proposed for consistent information estimation in a class of semiparametric models. The method is based on the geometric interpretation of the efficient score function, that it is the residual of the orthogonal projection of the score function for the finite-dimensional parameter onto the tangent space for the infinitedimensional parameter. The empirical version of this projection i...
متن کامل