MULTIVARIATE LOCAL POLYNOMIAL REGRESSION FOR TIME SERIES:UNIFORM STRONG CONSISTENCY AND RATES 论文

1996Journal of Time Series Analysis引用 470
Financial Risk and Volatility ModelingBayesian Methods and Mixture ModelsStatistical Distribution Estimation and Applications

摘要

Abstract. Local high‐order polynomial fitting is employed for the estimation of the multivariate regression function m ( x 1 ,… x d ) = E {φ( Y d )φ X 1 = x 1 ,…, X d = x d }, and of its partial derivatives, for stationary random processes { Y i , X i }. The function φ may be selected to yield estimates of the conditional mean, conditional moments and conditional distributions. Uniform strong consistency over compact subsets of R d , along with rates, are established for the regression function and its partial derivatives for strongly mixing processes.