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.

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...

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...

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...

This paper is concerned with the estimating problem of the varying-coefficient partially linear regression model. We apply the empirical method to this semiparametric model. An empirical log-likelihood ratio for the parametric components, which are of primary interest, is proposed and the...