Consider a repeated measurement regression model yij=g(xi)+[epsilon]ij where i=1,...,n, j=1,...,m, yij's are responses, g(·) is an unknown function, xi's are design points, [epsilon]ij's are random errors with a one-way error component structure, i.e. [epsilon]ij=[mu]i+[nu]ij, [mu]i and...

A new estimation is proposed for seemingly unrelated nonparametric regression models where variance of disturbance in an equation is larger than that in the preceding equation, and all of the correlation coefficients between the disturbances across the equations are positive.

In this paper, we are concerned with the estimating problem of functional coefficient regression models with generated covariates. A new local polynomial estimation is proposed, which is based on error covariance matrix correction. It is shown that the resulting estimators are consistent,...

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We report the preparation of ZnO quantum dot hybrid luminescent resists for nanoimprint lithography. Photoluminescence spectra indicate that ZnO QDs@AMONIL have a significant increase in the luminescent intensity, an obvious blue-shift of emission peak and the Stoke's shift, revealing that ZnO...

Varying-coefficient models are useful extension of classical linear models. This paper is concerned with the statistical inference of varying-coefficient regression models with autoregressive errors. By combining the estimated residuals, the smoothly clipped absolute deviation (SCAD) penalty and...

The growth curve model is a useful tool for studying the growth problems, repeated measurements and longitudinal data. A key point using the growth curve model to fit data is determining the degree of polynomial profile form, choosing suitable explanatory variables, shrinking some regression...

In this paper, we investigate the estimation problem of fixed effects panel data partially linear additive regression models. Semi‐parametric fixed effects panel data regression models are tools that are well suited to econometric analysis and the analysis of cDNA micro‐arrays. By applying a...