Testing for linearity

A nonparametric large sample test is proposed for testing the linearity of a regression model with independent and identically distributed errors satisfying only a very mild tail condition. The statistic is based on the functional least squares estimator of the slope vector. The test is applied to the stack loss data.     

Percentage points and power of a K-S type test for linearity in autoregressive time series

1. IntroductionA Kolmogorov-Smirnov type test for linearity in autoregressive models has been con-sidered by An and Chengl']. They showed that the asymptotic null di8tribution of the teststati8tic is related to the supremum of the 8tandard Brownian motion. Their simulationshowed that the test was easy to conduct and more powerful than the tests of Hinich[2],Keenanl3j, Tasyl4] and Chan and TOngl5]. However, the percentage points of the null dis-tribution of the test have not been tabulated…     

Certain characterizations with linearity of regression in additive damage models

This paper investigates the characterizations of certain discrete distributions within the framework of a multivariate additive damage model. The univariate case for such a model appeared in an article by [2]. In this model a p-dimensional observation is subjected to damage according to a specified probability law represented by a joint survival distribution. Here, it is shown that the linearity of regression of the damaged part on the undamaged ones leads to the characterizations of the multivariate binomial, and multiple inverse hypergeometric distribution as survival distributions.     

A multivariate adaptive regression splines cutting plane approach for solving a two-stage stochastic programming fleet assignment model

The fleet assignment model assigns a fleet of aircraft types to the scheduled flight legs in an airline timetable published six to twelve weeks prior to the departure of the aircraft. The objective is to maximize profit. While costs associated with assigning a particular fleet type to a leg are easy to estimate, the revenues are based upon demand, which is realized close to departure. The uncertainty in demand makes it challenging to assign the right type of aircraft to each flight leg based on forecasts taken six to twelve weeks prior to departure. Therefore, in this paper, a two-stage stochastic programming framework has been developed to model the uncertainty in demand, along with the Boeing concept of demand driven dispatch to reallocate aircraft closer to the departure of the aircraft. Traditionally, two-stage stochastic programming problems are solved using the L-shaped method. Due to the slow convergence of the L-shaped method, a novel multivariate adaptive regression splines cutting plane method has been developed. The results obtained from our approach are compared to that of the L-shaped method, and the value of demand-driven dispatch is estimated.     

Testing heteroscedasticity by wavelets in a nonparametric regression model

In the nonparametric regression models, a homoscedastic structure is usually assumed. However, the homoscedasticity cannot be guaranteed a priori. Hence, testing the heteroscedasticity is needed. In this paper we propose a consistent nonparametric test for heteroscedasticity, based on wavelets. The empirical wavelet coefficients of the conditional variance in a regression model are defined first. Then they are shown to be asymptotically normal, based on which a test statistic for the heteroscedasticity is constructed by using Fan's wavelet thresholding idea. Simulations show that our test is superior to the traditional nonparametric test.     

The empirical likelihood goodness-of-fit test for regression model

Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology.     

半参数回归模型独立情形的分离法估计

对半参数回归模型,用L2最佳逼近加矩估计的方法,推出其非参数部分的依L2与强相合联合收敛意义下的估计,及参数部分的强相合与相合渐近正态估计,并设计实行了一个模拟实验.     

Bootstrap approximation of wavelet estimates in a semiparametric regression model

The inference for the parameters in a semiparametric regression model is studied by using the wavelet and the bootstrap methods. The bootstrap statistics are constructed by using Efron＇s resampling technique, and the strong uniform convergence of the bootstrap approximation is proved. Our results can be used to construct the large sample confidence intervals for the parameters of interest. A simulation study is conducted to evaluate the finite-sample performance of the bootstrap method and to compare it with the normal approximation-based method.     

Simple analysis of graph tests for linearity and PCP

We give a simple analysis of the PCP with low amortized query complexity of Samorodnitsky and Trevisan [16]. The analysis also applies to the linearity testing over finite fields, giving a better estimate of the acceptance probability in terms of the distance of the tested function to the closest linear function. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 22: 139–160, 2003     

A PROJECTION NT-TYPE TEST OF ELLIPTICAL SYMMETRY BASED ON THE SKEWNESS AND KURTOSIS MEASURES

1.IntroductionTheunivariateandmultivariatenormaldistributionshaveplayedacentralroleinstatistics.However,therearemanynaturalphenomenathatdonotfollowthenormallaw.Thereisaneedtostatisticalmodellingbytheuseofmultivariatenon-normaldistributions.Amongthemthesphericallysymmetricandellipticallysymmetricdistributions(sphericalandellipticaldistributionsforsimplicity)haveattractedmuchattentionduringthelasttwodecadesbecausetheellipticaldistributionspossessmanynicepropertieswhicharesimilartothoseofthemulti…     

Some remarks concerning the consistency of LS and LAD estimates of multiple regression

1.IntroductionConsideralinearregressionmodelwhereK,xi,doandeiaretheobservationofthetargetvariable,aknownHvector,theunknownparametervector,andtherandomerror,respectively.LetpbeaconvexfunctiondefinedonRI.TheM-estimateofpo,tobedenotedbyac,isdefinedasaminimizingpointofthefunctionH(P)=ZP(K--x:g).Denotetheleftandrightderivativesofpbyop--andi=1op .Regardingtheweakconsistencyofac,Zhao,RaoandChenll]establishedthefollowingresult:TheoremA.Lete15eZt'belid.Supposethatthereexistsfunctionop,satisfy…     

On asymptotically efficient estimation for a semiparametric regression model

1.IntroductionConsiderthemodelY=X"0 g(T) E,(1'1)whereX"~(xl,',xo)areexplanatoryvariablesthatenterlinearly,Pisakx1vectorofunknownparameters,Tisanotherexplanatoryvariablesthatentersinanonlinearfashion,g')isanunknownsmoothfunctionofTinR',(X,T)andeareindependent,andeistheerrorwithmean0andvariancea2.Trangesoveranondegeneratecompact1-dimensionalilltervalC*;withoutlossofgenerality,C*=[0,1].Chenl2]discussedasymptoticnormalityofestimatorsP.of0byusingpiecewisepolynthacaltoapproximateg.Speckmanls…     

具有线性趋势回归信度模型异方差的score检验

回归信度模型在保险研究中具有重要的作用.本文分险种内部,险种之间,险种内部及之间三种情形讨论了具有线性趋势回归信度模型异方差的score检验问题.首先推导了异方差存在性检验的score检验统计量,然后利用Monte-Carlo方法模拟了这几种检验统计量的功效,功效模拟结果显示：这几种检验统计量都有很好的检验效果.最后利用文中所得到的检验方法对旅客意外身体伤害保险数据进行了实例分析.     

Beta回归模型的影响诊断

应用曲率方法研究了Beta回归模型的局部影响分析问题,分别在加权扰动、响应变量扰动和自变量扰动模式下得到了相应的影响诊断统计量.同时还讨论了模型中散度参数的齐性检验问题,得到了Score检验统计量.最后通过具体的数值实例说明了所得统计量的有效性.     

Existence of unbiased estimate of regression parameters in simple linear EV models

It is well known that for one-dimensional normal EV regression model X = x u,Y =α βx e, where x, u, e are mutually independent normal variables and Eu=Ee=0, the regression parameters a and βare not identifiable without some restriction imposed on the parameters. This paper discusses the problem of existence of unbiased estimate for a and βunder some restrictions commonly used in practice. It is proved that the unbiased estimate does not exist under many such restrictions. We also point out one important case in which the unbiased estimates of a and βexist, and the form of the MVUE of a and βare also given.     

带缺失数据的偏正态众数回归模型的参数估计

针对现实生活中大量数据存在偏斜的情况,构建偏正态数据下的众数回归模型.又加之数据的缺失常有发生,采用插补方法处理缺失数据集,为比较插补效果,考虑对响应变量随机缺失情形进行统计推断研究.利用高斯牛顿迭代法给出众数回归模型参数的极大似然估计,比较该模型在均值插补,回归插补,众数插补三种插补条件下的插补效果.随机模拟和实例分...     

偏正态数据下众数回归模型的统计诊断

为了更好地拟合偏态数据,充分提取偏态数据的信息,针对偏正态数据建立了众数回归模型,并基于Pena距离统计量对众数回归模型进行统计断研究,得到了众数回归模型的Pena距离表达式以及高杠杆异常点的诊断方法.利用EM算法与梯度下降法给出了众数回归模型参数的极大似然估计,根据数据删除模型计算似然距离、Cook距离和Pena距离统计量,绘制诊断统计图.通过Monte Carlo模拟试验和实例分析比较,说明文章提出的方法行之有效,并在一定条件下Pena距离对异常点或强影响点的诊断优于似然距离和Cook距离.     

时空模型的局部众数回归

时空数据经常含有奇异点或来自重尾分布,此时基于最小二乘的估计方法效果欠佳,需要更稳健的估计方法.本文提出时空模型的基于局部众数(local modal, LM)的局部线性估计方法.理论和数据分析结果都显示,若数据含有奇异点或来自重尾分布,基于局部众数的局部线性方法比基于最小二乘的局部线性方法有效;若数据无奇异点且来自正态分布,两种方法效率渐近一致.本文采用众数期望最大化(modal expectation-maximization, MEM)算法,并在数据相依情形下得出估计量的渐近正态性.     

On asymptotics of t-type regression estimation in multiple linear model

We consider a robust estimator (t-type regression estimator) of multiple linear regression model by maximizing marginal likelihood of a scaled t-type error t-distribution. The marginal likelihood can also be applied to the de-correlated response when the within-subject correlation can be consistently estimated from an initial estimate of the model based on the independent working assumption. This paper shows that such a t-type estimator is consistent.