We propose to approximate the unknown error density of a nonparametric regression model by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. This mixture density has the form of a kernel density estimator of error realizations....

The unknown error density of a nonparametric regression model is approximated by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. Such a mixture density has the form of a kernel density estimator of error realizations. An...

Error density estimation in a nonparametric functional regression model with functional predictor and scalar response is considered. The unknown error density is approximated by a mixture of Gaussian densities with means being the individual residuals, and variance as a constant parameter. This...

This paper considers forecasting life table, and proposes a model averaging approach to improve point and interval forecast accuracy. Illustrated by data of eleven countries, we compare point and interval forecasts among ten principal component and two random walk methods. Based on averaged...

We propose a sampling approach to bandwidth estimation for a nonparametric regression model with continuous and discrete types of regressors and unknown error density. The unknown error density is approximated by a location-mixture of Gaussian densities with means being the individual errors,...

We present a nonparametric method to forecast a seasonal univariate time series, and propose four dynamic updating methods to improve point forecast accuracy. Our methods consider a seasonal univariate time series as a functional time series. We propose first to reduce the dimensionality by...

We present a nonparametric method to forecast a seasonal univariate time series, and propose four dynamic updating methods to improve point forecast accuracy. Our methods consider a seasonal univariate time series as a functional time series. We propose first to reduce the dimensionality by...

Accurate forecasts of age-specific fertility rates are critical for government policy, planning and decision making. With the availability of Human Fertility Database (2011), we compare the empirical accuracy of the point and interval forecasts, obtained by the approach of Hyndman and Ullah...