Estimation and Bootstrap with Censored Data in Fixed Design Nonparametric Regression

We study Beran's extension of the Kaplan-Meier estimator for thesituation of right censored observations at fixed covariate values. Thisestimator for the conditional distribution function at a given value of thecovariate involves smoothing with Gasser-Müller weights. We establishan almost sure asymptotic representation which provides a key tool forobtaining central limit results. To avoid complicated estimation ofasymptotic bias and variance parameters, we propose a resampling methodwhich takes the covariate information into account. An asymptoticrepresentation for the bootstrapped estimator is proved and the strongconsistency of the bootstrap approximation to the conditional distributionfunction is obtained.     

误差为鞅差序列的非参数回归模型的完全相合性

在误差为鞅差序列的条件下,利用截尾方法及鞅差序列的指数不等式,研究了非参数回归模型P-C估计量的完全收敛性,且得到了完全收敛的收敛速度.     

NA样本非参数回归权函数估计的强相合性

在 NA样本下 ,讨论了非参数回归模型中权函数估计的强相合性及强一致相合性 ,并把这个结果应用于 Gasser- Muller估计和 Priestley and Chao估计 .     

带有误差变量的自回归模型的局部多项式估计

该文主要研究带有误差变量的自回归模型的自回归函数的非参数估计问题,应用卷积核函数,给出了自回归函数的局部多项式估计,考察了局部多项式估计的相合性和渐近正态性,最后作了模拟计算.     

m0相依误差下非线性回归模型LS估计的大偏差

该文获得了m0相依误差下非线性回归模型LS估计的大偏差，推广了Sieders和Dzhaparidze在独立误差下的相应结果     

On Complete Consistency for the Estimator of Nonparametric Regression Model Based on Asymptotically Almost Negatively Associated Errors

Methodology and Computing in Applied Probability - In this paper, we mainly study the consistency for the estimator of nonparametric regression model based on asymptotically almost negatively...     

房价变动对固定资产投资影响的实证分析

在定性分析房价对固定资产投资影响机制的基础上,利用2003-2016年期间固定资产投资额、国内生产总值、商品房平均销售价格以及1-3年期央行贷款利率等指标的年度数据,对包含房价的固定资产投资函数进行协整回归,得出我国房价对投资有显著的正向刺激效应,同时对可能的原因进行分析,并给出房价调控的政策建议.     

删失数据回归误差项的非参数密度估计的一致相合性(英文)

回归误差项是不可观测的. 由于回归误差项的密度函数在实际中有许多应用, 故使用非参数方法对其进行估计就成为回归分析中的一个基本问题. 针对完全观测数据回归模型, 曾有作者对此问题进行了研究. 然而在实际应用中, 经常会有数据被删失的情况发生, 在此情况下, 可以利用删失回归残差, 并使用核估计的方法对回归误差项的密度函数进行估计. 本文研究了该估计的大样本性质, 并证明了估计量的一致相合性.     

误差为NSD序列的广义线性模型的M估计的强相合性

研究了以NSD序列(negatively superadditive dependent)为误差的广义线性模型,得到了未知参数的M估计.在较弱的条件下,利用指数不等式、NSD序列加权和的强收敛性和Borel-Cantelli引理等证明了未知参数M估计的强相合性.此结果推广了独立误差和NSD误差的线性模型的相应结果.     

Asymptotic Normality of the Whittle Estimator in Linear Regression Models with Long Memory Errors

This paper establishes the asymptotic normality of the Whittle estimator of the unknown dependence parameters in a linear regression model with long memory moving average errors. The design variables are taken to be deterministic or random. In the latter case they are assumed to have a moving average representation that includes both short and long memory. In all cases, it is observed that the rate of consistency of the regression parameter estimator has an effect on the asymptotic normality of the Whittle estimator.     

实线性锥距离空间中带有锥W-距离的不动点定理

在实线性锥距离空间中给出锥、W-距离的概念及一些性质．由此在实线性锥距离空间中建立了压缩型和扩张型两类不动点定理,其中压缩条件和扩张条件中均含有锥W-距离．     

外部压力对学生的数学及科学成绩效应的纵向研究 ——- 非参数分位回归方法

过去, 许多研究主要集中在学生的经济背景与心理因素对其成绩的影响方面. 然而, 很少注意到外部压力对学生成绩的影响, 诸如来自家长与同学方面的压力. 本文重点放在这一有趣而且很重要的主题上, 利用非参数分位回归中的``双核'法对美国青年人进行了深入地纵向研究, 得到了几个很有趣的发现. 这些研究的方法、结果不光对学生家长有用, 而且对教育政策制定者与咨询者也有所裨益.     

鞅差误差下线性EV模型最小二乘估计的中偏差

研究了线性EV模型:η_i=θ+βx_i+ε_i,ξ_i=x_i+δ_i,1≤i≤n.当误差(ε_i,δ_i)为鞅差序列情形时,讨论了未知参数β和θ的最小二乘估计的中偏差问题.     

Laplace Variational Approximation for Semiparametric Regression in the Presence of Heteroscedastic Errors

Variational approximations provide fast, deterministic alternatives to Markov chain Monte Carlo for Bayesian inference on the parameters of complex, hierarchical models. Variational approximations are often limited in practicality in the absence of conjugate posterior distributions. Recent work has focused on the application of variational methods to models with only partial conjugacy, such as in semiparametric regression with heteroscedastic errors. Here, both the mean and log variance functions are modeled as smooth functions of covariates. For this problem, we derive a mean field variational approximation with an embedded Laplace approximation to account for the nonconjugate structure. Empirical results with simulated and real data show that our approximate method has significant computational advantages over traditional Markov chain Monte Carlo; in this case, a delayed rejection adaptive Metropolis algorithm. The variational approximation is much faster and eliminates the need for tuning parameter selection, achieves good fits for both the mean and log variance functions, and reasonably reflects the posterior uncertainty. We apply the methods to log-intensity data from a small angle X-ray scattering experiment, in which properly accounting for the smooth heteroscedasticity leads to significant improvements in posterior inference for key physical characteristics of an organic molecule.     

含有时滞的固定资产投资模型解的性质

给出带有时滞的一类固定资产投资模型,此模型为含有非局部和时滞边界条件的分布参数系统.运用泛函分析和积分方程理论,证明了系统解的存在唯一性,得到解的解析表达式,进而讨论了解的稳定性.     

A Note on the Use of V and U Statistics in Nonparametric Models of Regression

We establish the asymptotic equivalence of V and U statistics when the statistic’s kernel depends on n. Combined with a lemma of B. Lee this result provides conditions under which U statistics projections and V statistics are asymptotically equivalent. The use of this equivalence in nonparametric regression models is illustrated with several examples; the estimation of conditional variances, skewness, kurtosis and the construction of a nonparametric R-squared measure.     

中国房地产价格的多元线性回归模型

近几年,房价的迅速增长,已经远远超过了GDP和居民可支配收入的增长.那么,我国房地产市场是否已经过热,是否已经出现了泡沫.基于2000~2006年的数据对我国房地产价格函数的影响因素进行了多元线性回归分析.尽管我国部分地区价格偏高,但是并没有出现商品房价格泡沫.