共查询到20条相似文献,搜索用时 15 毫秒
1.
Zhan-Qian Lu 《Journal of multivariate analysis》1996,59(2):187-205
Nonparametric regression estimator based on locally weighted least squares fitting has been studied by Fan and Ruppert and Wand. The latter paper also studies, in the univariate case, nonparametric derivative estimators given by a locally weighted polynomial fitting. Compared with traditional kernel estimators, these estimators are often of simpler form and possess some better properties. In this paper, we develop current work on locally weighted regression and generalize locally weighted polynomial fitting to the estimation of partial derivatives in a multivariate regression context. Specifically, for both the regression and partial derivative estimators we prove joint asymptotic normality and derive explicit asymptotic expansions for their conditional bias and conditional convariance matrix (given observations of predictor variables) in each of the two important cases of local linear fit and local quadratic fit. 相似文献
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Han-Ying Liang Elias Ould Saïd 《Annals of the Institute of Statistical Mathematics》2018,70(1):155-189
Based on empirical likelihood method, we construct new weighted estimators of conditional density and conditional survival functions when the interest random variable is subject to random left-truncation; further, we define a plug-in weighted estimator of the conditional hazard rate. Under strong mixing assumptions, we derive asymptotic normality of the proposed estimators which permit to built a confidence interval for the conditional hazard rate. The finite sample behavior of the estimators is investigated via simulations too. 相似文献
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在回归模型中,对一类因变量函数的条件期望方程的附加信息,我们提出了基于极大经验似然方法的局部线性点估计,在一定条件下证明了这些估计的相合性和渐近正态性,而且估计的方差小于通常不带附加信息核估计的方差.模拟结果也显示了估计的优良性. 相似文献
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Zhi-hua SUN Academy of Mathematics Systems Science Chinese Academy of Science Beijing China 《中国科学A辑(英文版)》2007,50(1):1-12
In this paper, the estimation of average treatment effects is considered when we have the model information of the conditional mean and conditional variance for the responses given the covariates. The quasi-likelihood method adapted to treatment effects data is developed to estimate the parameters in the conditional mean and conditional variance models. Based on the model information, we define three estimators by imputation, regression and inverse probability weighted methods. All the estimators are shown asymptotically normal. Our simulation results show that by using the model information, the substantial efficiency gains are obtained which are comparable with the existing estimators. 相似文献
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《应用数学年刊》2018,(4)
Under some mild conditions, we derive the asymptotic normality of the Nadaraya-Watson and local linear estimators of the conditional hazard function for left-truncated and dependent data. The estimators were proposed by Liang and Ould-Sa?d [1]. The results confirm the guess in Liang and Ould-Sa?d [1]. 相似文献
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Hazard function estimation is an important part of survival analysis. Interest often centers on estimating the hazard function
associated with a particular cause of death. We propose three nonparametric kernel estimators for the hazard function, all
of which are appropriate when death times are subject to random censorship and censoring indicators can be missing at random.
Specifically, we present a regression surrogate estimator, an imputation estimator, and an inverse probability weighted estimator.
All three estimators are uniformly strongly consistent and asymptotically normal. We derive asymptotic representations of
the mean squared error and the mean integrated squared error for these estimators and we discuss a data-driven bandwidth selection
method. A simulation study, conducted to assess finite sample behavior, demonstrates that the proposed hazard estimators perform
relatively well. We illustrate our methods with an analysis of some vascular disease data. 相似文献
8.
Lihua Sun 《Operations Research Letters》2010,38(4):246-251
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are important risk measures. They are often estimated by using importance-sampling (IS) techniques. In this paper, we derive the asymptotic representations for IS estimators of VaR and CVaR. Based on these representations, we are able to prove the consistency and asymptotic normality of the estimators and to provide simple conditions under which the IS estimators have smaller asymptotic variances than the ordinary Monte Carlo estimators. 相似文献
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在响应变量满足MAR缺失机制下,我们分别研究了基于观察到的完全样本数据对、基于固定补足后的“完全洋本”和基于分数线性回归填补后的“完全洋本”得到的回归系数的最小二乘估计的弱相合性、强相合性及渐近正态性,我们还通过数值模拟,比较了基于上述估计得到的β的置信区间的优劣。 相似文献
10.
The probability density estimation problem with surrogate data and validation sample is considered. A regression calibration kernel density estimator is defined to incorporate the information contained in both surrogate variates and validation sample. Also, we define two weighted estimators which have less asymptotic variances but have bigger biases than the regression calibration kernel density estimator. All the proposed estimators are proved to be asymptotically normal. And the asymptotic representations for the mean squared error and mean integrated square error of the proposed estimators are established, respectively. A simulation study is conducted to compare the finite sample behaviors of the proposed estimators. 相似文献
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A. Pérez-González J. M. Vilar-Fernández W. González-Manteiga 《Annals of the Institute of Statistical Mathematics》2009,61(1):85-109
The main objective of this work is the nonparametric estimation of the regression function with correlated errors when observations
are missing in the response variable. Two nonparametric estimators of the regression function are proposed. The asymptotic
properties of these estimators are studied; expresions for the bias and the variance are obtained and the joint asymptotic
normality is established. A simulation study is also included. 相似文献
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该文考虑协变量缺失时的多元线性EV模型参数的估计, 其中协变量的缺失机制是Rubin(1976)提出的随机缺失(MAR).
利用加权调整最小二乘方法给出参数估计, 证明了估计的相合性和渐近正态性. 数值模拟结果表明所给的估计性态良好. 相似文献
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该文研究了响应变量缺失下半参数部分非线性变系数EV模型的统计推断问题,利用逆概率加权局部纠偏profile最小二乘法构造了模型中非参数分量和参数分量的估计,证明了估计量的渐近正态性.通过数值模拟和实际数据分析,验证了所提出的估计方法是有效的. 相似文献
15.
《Journal of Computational and Applied Mathematics》2006,186(1):232-252
We determine the joint asymptotic normality of kernel and weighted least-squares estimators of the upper tail index of a regularly varying distribution when each estimator is a bivariate function of two parameters: the tuning parameter is motivated by possible underlying second-order behavior in regular variation, while no such behavior is assumed, and the fraction parameter determines that upper portion of the sample on which the estimator is based. Under the hypothesis that the scaled asymptotic biases of the estimators vanish uniformly in the parameter points considered, these results imply joint asymptotic normality for deviations of ratios of the estimators from 1, which in turn yield asymptotic chi-square tests for checking the small-bias hypothesis, equivalent to the constructibility of asymptotic confidence intervals. The test procedure suggests adaptive choices of the tuning and fraction parameters: data-driven (t)estimators. 相似文献
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主要研究因变量存在缺失且协变量部分包含测量误差情形下,如何对变系数部分线性模型同时进行参数估计和变量选择.我们利用插补方法来处理缺失数据,并结合修正的profile最小二乘估计和SCAD惩罚对参数进行估计和变量选择.并且证明所得的估计具有渐近正态性和Oracle性质.通过数值模拟进一步研究所得估计的有限样本性质. 相似文献
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分位数的估计在生物医学、社会经济调查等领域有着广泛的应用,然而在实际问题的研究中,往往由于各种人为或不可控因素造成数据收集不完全.本文在随机缺失(MAR)假设条件下,利用非参数核补法和局部多重插补法给出了响应变量缺失时样本分位数的估计,并利用经验过程等理论证明了由这两种方法得到的分位数估计的大样本性质,同时,使用重抽样方法给出了估计的渐近方差的估计,模拟结果验证了这两种方法的有效性.文章所提两种方法的优点在于:首先,所提出的缺失修正方法不需要对缺失概率的模型做任何假设;其次,方法亦适用于其他有关参数不可微的估计目标函数;最后,方法很容易地推广到一般M估计的情况,并可以对多个分位数同时进行估计. 相似文献
18.
Frederico Caeiro M. Ivette Gomes Björn Vandewalle 《Methodology and Computing in Applied Probability》2014,16(1):1-29
In this paper, for heavy-tailed models and through the use of probability weighted moments based on the largest observations, we deal essentially with the semi-parametric estimation of the Value-at-Risk at a level p, the size of the loss occurred with a small probability p, as well as the dual problem of estimation of the probability of exceedance of a high level x. These estimation procedures depend crucially on the estimation of the extreme value index, the primary parameter in Statistics of Extremes, also done on the basis of the same weighted moments. Under regular variation conditions on the right-tail of the underlying distribution function F, we prove the consistency and asymptotic normality of the estimators under consideration in this paper, through the usual link of their asymptotic behaviour to the one of the extreme value index estimator they are based on. The performance of these estimators, for finite samples, is illustrated through Monte-Carlo simulations. An adaptive choice of thresholds is put forward. Applications to a real data set in the field of insurance as well as to simulated data are also provided. 相似文献
19.
陈敏 《高校应用数学学报(A辑)》1993,(1):1-16
本文在一组相当广泛的条件下,证明了线性平稳时间序列逆自相关函数自回归估计的渐近正态性,并获得了由这一估计所得的MA(q)模型参数估计的渐近正态性和优效渐近正态性。 相似文献
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Here we study the problems of local asymptotic normality of the parametric family of distributions and asymptotic minimax efficient estimators when the observations are subject to right censoring. Local asymptotic normality will be established under some mild regularity conditions. A lower bound for local asymptotic minimax risk is given with respect to a bowl-shaped loss function, and furthermore a necessary and sufficient condition is given in order to achieve this lower bound. Finally, we show that this lower bound can be attained by the maximum likelihood estimator in the censored case and hence it is local asymptotic minimax efficient. 相似文献