This paper is concerned with developing a semiparametric panel model to explain the trend in UK temperatures and other … twenty six Meteorological Office stations. The data is an unbalanced panel. We allow the trend to evolve in a nonparametric …

This paper is concerned with developing a semiparametric panel model to explain the trend in UK temperatures and other … twenty six Meteorological Office stations. The data is an unbalanced panel. We allow the trend to evolve in a nonparametric …

-to-implement semiparametric method to estimate each entry of the covariance matrix via model averaging marginal regression, and then apply a …

Local linear fitting is a popular nonparametric method in nonlinear statistical and econometric modelling. Lu and … nonparametric regression function under the condition of near epoch dependence. We further investigate the uniform consistency of … established under mild conditions. Furthermore, general results of uniform convergence rates for nonparametric kernel …

We use local polynomial fitting to estimate the nonparametric M-regression function for strongly mixing stationary …

This paper derives the asymptotic distribution of nonparametric neural network estimator of the Lyapunov exponent in a …

We propose semiparametric model averaging schemes for nonlinear dynamic time series regression models with a very large … forecasts of a response variable making use of a large number of conditioning variables in a nonparametric way. We propose two … semiparametric schemes of dimension reduction among the exogenous regressors and the auto-regressors. (lags of the response variable …

We investigate a class of semiparametric ARCH(infinity) models that includes as a special case the partially … nonparametric (PNP) model introduced by Engle and Ng (1993) and which allows for both flexible dynamics and flexible function form … pointwise distribution of the nonparametric component of the model. We also discuss efficiency of both the parametric and …