Estimation of harmonic component in regression with cyclically dependent errors

Estimation in Nonparametric Regression with Nonregular Errors

For sufficiently nonregular distributions with bounded support, the extreme observations converge to the boundary points at a faster rate than the square root of the sample size. In a nonparametric regression model with such a nonregular error distribution, this fact can be used to construct an estimator for the regression function that converges at a faster rate than the Nadaraya– Watson estim...

Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors

More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors

We propose a modification of kernel time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that has to be estimated from the data. We establish the asymptotic distribution of our estimator under weak dependence conditions. It is shown that the proposed estimation...

Instrumental Variables Regression with Measurement Errors and Multicollinearity in Instruments

In this paper we obtain a consistent estimator when there exist some measurement errors and multicollinearity in the instrumental variables in a two stage least square estimation of parameters. We investigate the asymptotic distribution of the proposed estimator and discuss its properties using some theoretical proofs and a simulation study. A real numerical application is also provided for mor...

Efficient estimation of a polynomial regression model with stationary errors

Starting point is a polynomial regression model with weakly stationary errors. We investigate the asymptotic covariance of the least–squares estimator (LSE) and consider situations where the LSE fails to be asymptotically efficient. For that reason alternative estimators are derived, which are the best linear unbiased estimators for certain spectral densities. We show for a large class of spect...