共查询到20条相似文献,搜索用时 31 毫秒
1.
J. A. Cristóbal J. L. Ojeda J. T. Alcalá 《Annals of the Institute of Statistical Mathematics》2004,56(3):475-496
In this paper we deduce a confidence bands construction for the nonparametric estimation of a regression curve from length
biased data, where a result from Bickel and Rosenblatt (1973,The Annals of Statistics,1, 1071–1095) is adapted to this new situation. The construction also involves the estimation of the variance of the local
linear estimator of the regression, where we use a finite sample modification in order to improve the performance of these
confidence bands in the case of finite samples. 相似文献
2.
本文对非参数回归曲线提出一种新的核估计量和窗宽选择方法及其修正偏倚置信带 .仅利用该回归曲线的估计量和选择数据的窗宽构造这些置信带 .证明了在大样本的意义下 ,这种修正偏倚置信带和Bonferroni型带具有渐近修正范围概率的性质 .并且通过MonteCarlo实验研究了它在小样本中的性质 .在模拟研究中已经证明 ,这种修正偏倚置信带方法是很有效的 ,即使在样本容量n=1 0 0的情况下 ,它也接近给定的范围概率 . 相似文献
3.
The nonparametric estimator of the conditional survival function proposed by Beran is a useful tool to evaluate the effects of covariates in the presence of random right censoring. However, censoring indicators of right censored data may be missing for different reasons in many applications. We propose some estimators of the conditional cumulative hazard and survival functions which allow to handle this situation. We also construct the likelihood ratio confidence bands for them and obtain their asymptotic properties. Simulation studies are used to evaluate the performances of the estimators and their confidence bands. 相似文献
4.
线性混合模型中方差分量的广义推断 总被引:1,自引:0,他引:1
本文考虑了线性混合模型中方差分量的假设检验和区间估计问题.基于广义P-值和广义置信区间的概念,构造了对应于随机效应的单个方差分量的精确检验和置信区间.所构造的广义p-值和广义置信区间是最小充分统计量的函数.对于两个独立线性混合模型中对应于随机效应的方差分量的比较,建立了精确检验和置信区间.进-步,研究了所给检验和置信区间的统计性质,给出了这些检验方法与文献中已有方法的功效比较的模拟结果.模拟结果表明,新检验在功效方面有显著的改进.最后,通过-个实例来演示本文方怯. 相似文献
5.
In this paper, we establish uniform-in-bandwidth limit laws of the logarithm for nonparametric Inverse Probability of Censoring
Weighted (I.P.C.W.) estimators of the multivariate regression function under random censorship. A similar result is deduced
for estimators of the conditional distribution function. The uniform-in-bandwidth consistency for estimators of the conditional
density and the conditional hazard rate functions are also derived from our main result. Moreover, the logarithm laws we establish
are shown to yield almost sure simultaneous asymptotic confidence bands for the functions we consider. Examples of confidence
bands obtained from simulated data are displayed.
相似文献
6.
In this paper, a fixed design regression model where the errors follow a strictly stationary process is considered. In this model the conditional mean function and the conditional variance function are unknown curves. Correlated errors when observations are missing in the response variable are assumed. Four nonparametric estimators of the conditional variance function based on local polynomial fitting are proposed. Expressions of the asymptotic bias and variance of these estimators are obtained. A simulation study illustrates the behavior of the proposed estimators. 相似文献
7.
This paper investigates the estimation in a class of single-index varying coefficient regression model when some covariates are contaminated with measurement errors. A bias-corrected least square procedure based on the observed data is proposed. By replacing the nonparametric single index part with a local linear approximation, an iterative algorithm for estimating the index parameter is proposed. More importantly, a special case is identified in which the naive procedure provides consistent estimates for the single index parameters. Large sample properties of the proposed estimators are established. The finite sample performance of the proposed estimators are evaluated by simulation studies. 相似文献
8.
In this paper, two new tests for heteroscedasticity in nonparametric regression are presented and compared. The first of these
tests consists in first estimating nonparametrically the unknown conditional variance function and then using a classical
least-squares test for a general linear model to test whether this function is a constant. The second test is based on using
an overall distance between a nonparametric estimator of the conditional variance function and a parametric estimator of the
variance of the model under the assumption of homoscedasticity. A bootstrap algorithm is used to approximate the distribution
of this test statistic. Extended versions of both procedures in two directions, first, in the context of dependent data, and
second, in the case of testing if the variance function is a polynomial of a certain degree, are also described. A broad simulation
study is carried out to illustrate the finite sample performance of both tests when the observations are independent and when
they are dependent. 相似文献
9.
This paper focuses on the variable selections for semiparametric varying coefficient partially linear models when the covariates in the parametric and nonparametric components are all measured with errors. A bias-corrected variable selection procedure is proposed by combining basis function approximations with shrinkage estimations. With appropriate selection of the tuning parameters, the consistency of the variable selection procedure and the oracle property of the regularized estimators are established. A simulation study and a real data application are undertaken to evaluate the finite sample performance of the proposed method. 相似文献
10.
PAN Jiazhu & WU Guangxu LMAM School of Mathematical Sciences Peking University Beijing China 《中国科学A辑(英文版)》2005,48(9):1169-1181
We study the tail probability of the stationary distribution of nonparametric non- linear autoregressive functional conditional heteroscedastic (NARFCH) model with heavy- tailed innovations.Our result shows that the tail of the stationary marginal distribution of an NARFCH series is heavily dependent on its conditional variance.When the innovations are heavy-tailed,the tail of the stationary marginal distribution of the series will become heavier or thinner than that of its innovations.We give some specific formulas to show how the increment or decrement of tail heaviness depends on the assumption on the con- ditional variance function.Some examples are given. 相似文献
11.
This paper is concerned with the conditional bias and variance of local quadratic regression to the multivariate predictor variables. Data sharpening methods of nonparametric regression were first proposed by Choi, Hall, Roussion. Recently, a data sharpening estimator of local linear regression was discussed by Naito and Yoshizaki. In this paper, to improve mainly the fitting precision, we extend their results on the asymptotic bias and variance. Using the data sharpening estimator of multivariate local quadratic regression, we are able to derive higher fitting precision. In particular, our approach is simple to implement, since it has an explicit form, and is convenient when analyzing the asymptotic conditional bias and variance of the estimator at the interior and boundary points of the support of the density function. 相似文献
12.
13.
回归模型的同方差检验 总被引:2,自引:0,他引:2
本文利用局部经验似然和WNW方法对条件分布函数和条件分位数进行估计,并利用条件分位数的方法对回归模型中的误差方差进行了同方差假设检验,获得了零假设下检验统计量的渐近分布为X2分布.模拟计算表明同方差假设检验的条件分位数方法具有较好的功效. 相似文献
14.
In this paper, we consider the statistical inference for the partially liner varying coefficient model with measurement error in the nonparametric part when some prior information about the parametric part is available. The prior information is expressed in the form of exact linear restrictions. Two types of local bias-corrected restricted profile least squares estimators of the parametric component and nonparametric component are conducted, and their asymptotic properties are also studied under some regularity conditions. Moreover, we compare the efficiency of the two kinds of parameter estimators under the criterion of Lo?ner ordering. Finally, we develop a linear hypothesis test for the parametric component. Some simulation studies are conducted to examine the finite sample performance for the proposed method. A real dataset is analyzed for illustration. 相似文献
15.
Irène Gijbels 《Applications of Mathematics》2008,53(3):177-194
For nonparametric estimation of a smooth regression function, local linear fitting is a widely-used method. The goal of this
paper is to briefly review how to use this method when the unknown curve possibly has some irregularities, such as jumps or
peaks, at unknown locations. It is then explained how the same basic method can be used when estimating unsmooth probability
densities and conditional variance functions.
This research was supported by GOA/07/04-project of the Research Fund KULeuven. Support from the IAP research network nr.
P6/03 of the Federal Science Policy, Belgium, is also acknowledged. 相似文献
16.
In this paper a two-stage bootstrap method is proposed for nonparametric regression with right censored data. The method is applied to construct confidence intervals and bands for a conditional survival function. Its asymptotic validity is established using counting process techniques and martingale central limit theory. The performance of the bootstrap method is investigated in a Monte Carlo study. An illustration is given using a real data. 相似文献
17.
Heleno Bolfarine 《Annals of the Institute of Statistical Mathematics》1990,42(3):435-444
In this paper, Bayesian linear prediction of the total of a finite population is considered in situations where the observation error variance is parameter dependent. Connections with least squares prediction (Royall (1976, J. Amer. Statist. Assoc., 71, 657–664)) in mixed linear models (Theil (1971, Principles of Econometrics, Wiley, New York)), are established. Extensions to the case of dynamic (state dependent) superpopulation models are also proposed. 相似文献
18.
Sangyeol Lee Okyoung Na Seongryong Na 《Annals of the Institute of Statistical Mathematics》2003,55(3):467-485
In this paper we consider the problem of testing for a variance change in nonstationary and nonparametric time series models.
The models under consideration are the unstable AR(q) model and the fixed design nonparametric regression model with a strong mixing error process. In order to perform a test,
we employ the cusum of squares test introduced by Inclán and Tiao (1994,J. Amer. Statist. Assoc.,89, 913–923). It is shown that the limiting distribution of the test statistic is the sup of a standard Brownian bridge as seen
in iid random samples. Simulation results are provided for illustration. 相似文献
19.
Simultaneous optimal estimates of fixed effects and variance components in the mixed model 总被引:2,自引:0,他引:2
WU Mixia & WANG SongguiCollege of Applied Sciences Beijing University of Technology Beijing 《中国科学A辑(英文版)》2004,47(5):787-799
For a general linear mixed model with two variance components, a set of simple conditions is obtained, under which, (i) the least squares estimate of the fixed effects and the analysis of variance (ANOVA) estimates of variance components are proved to be uniformly minimum variance unbiased estimates simultaneously; (ii) the exact confidence intervals of the fixed effects and uniformly optimal unbiased tests on variance components are given; (iii) the exact probability expression of ANOVA estimates of variance components taking negative value is obtained. 相似文献
20.
A monotone estimate of the conditional variance function in a heteroscedastic, nonparametric regression model is proposed.
The method is based on the application of a kernel density estimate to an unconstrained estimate of the variance function
and yields an estimate of the inverse variance function. The final monotone estimate of the variance function is obtained
by an inversion of this function. The method is applicable to a broad class of nonparametric estimates of the conditional
variance and particularly attractive to users of conventional kernel methods, because it does not require constrained optimization
techniques. The approach is also illustrated by means of a simulation study. 相似文献