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11.
A Semi-parametric Regression Model with Errors in Variables 总被引:4,自引:0,他引:4
Abstract. In this paper, we consider a partial linear regression model with measurement errors in possibly all the variables. We use a method of moments and deconvolution to construct a new class of parametric estimators together with a non-parametric kernel estimator. Strong convergence, optimal rate of weak convergence and asymptotic normality of the estimators are investigated. 相似文献
12.
By approximating the nonparametric component using a regression spline in generalized partial linear models (GPLM), robust generalized estimating equations (GEE), involving bounded score function and leverage-based weighting function, can be used to estimate the regression parameters in GPLM robustly for longitudinal data or clustered data. In this paper, score test statistics are proposed for testing the regression parameters with robustness, and their asymptotic distributions under the null hypothesis and a class of local alternative hypotheses are studied. The proposed score tests reply on the estimation of a smaller model without the testing parameters involved, and perform well in the simulation studies and real data analysis conducted in this paper. 相似文献
13.
Gabriela Beganu 《Statistical Methods and Applications》2007,16(3):347-356
It is known that the Henderson Method III (Biometrics 9:226–252, 1953) is of special interest for the mixed linear models
because the estimators of the variance components are unaffected by the parameters of the fixed factor (or factors). This
article deals with generalizations and minor extensions of the results obtained for the univariate linear models. A MANOVA
mixed model is presented in a convenient form and the covariance components estimators are given on finite dimensional linear
spaces. The results use both the usual parametric representations and the coordinate-free approach of Kruskal (Ann Math Statist
39:70–75, 1968) and Eaton (Ann Math Statist 41:528–538, 1970). The normal equations are generalized and it is given a necessary
and sufficient condition for the existence of quadratic unbiased estimators for covariance components in the considered model. 相似文献
14.
Peter Hall Qiwei Yao 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(2):425-442
Summary. We develop a general methodology for tilting time series data. Attention is focused on a large class of regression problems, where errors are expressed through autoregressive processes. The class has a range of important applications and in the context of our work may be used to illustrate the application of tilting methods to interval estimation in regression, robust statistical inference and estimation subject to constraints. The method can be viewed as 'empirical likelihood with nuisance parameters'. 相似文献
15.
Sarah Brown Karl Taylor 《Journal of the Royal Statistical Society. Series A, (Statistics in Society)》2008,171(3):615-643
Summary. We explore the determinants of debt, financial assets and net worth at the household level by using survey data for Germany, Great Britain and the USA. To identify which households are potentially vulnerable to adverse changes in the economic environment, we also explore the determinants of a range of measures of financial pressure: the probability that a household has negative net worth; the debt-to-income ratio; mortgage income gearing; the saving-to-income ratio. Our empirical findings suggest that the poorest and the youngest households are the most vulnerable to adverse changes in their financial circumstances. 相似文献
16.
Mohammad Salehi M. George A.F. Seber 《Australian & New Zealand Journal of Statistics》2004,46(3):483-494
Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation. 相似文献
17.
To reduce nonresponse bias in sample surveys, a method of nonresponse weighting adjustment is often used which consists of multiplying the sampling weight of the respondent by the inverse of the estimated response probability. The authors examine the asymptotic properties of this estimator. They prove that it is generally more efficient than an estimator which uses the true response probability, provided that the parameters which govern this probability are estimated by maximum likelihood. The authors discuss variance estimation methods that account for the effect of using the estimated response probability; they compare their performances in a small simulation study. They also discuss extensions to the regression estimator. 相似文献
18.
Nicholas T. Longford 《Statistics and Computing》2003,13(1):67-80
The weaknesses of established model selection procedures based on hypothesis testing and similar criteria are discussed and an alternative based on synthetic (composite) estimation is proposed. It is developed for the problem of prediction in ordinary regression and its properties are explored by simulations for the simple regression. Extensions to a general setting are described and an example with multiple regression is analysed. Arguments are presented against using a selected model for any inferences. 相似文献
19.
Jason P. Fine David V. Glidden Kristine E. Lee 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2003,65(1):317-329
Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin. 相似文献
20.
Janusz L. Wywiał 《Statistical Papers》2008,49(2):277-289
The sampling designs dependent on sample moments of auxiliary variables are well known. Lahiri (Bull Int Stat Inst 33:133–140,
1951) considered a sampling design proportionate to a sample mean of an auxiliary variable. Sing and Srivastava (Biometrika
67(1):205–209, 1980) proposed the sampling design proportionate to a sample variance while Wywiał (J Indian Stat Assoc 37:73–87,
1999) a sampling design proportionate to a sample generalized variance of auxiliary variables. Some other sampling designs
dependent on moments of an auxiliary variable were considered e.g. in Wywiał (Some contributions to multivariate methods in,
survey sampling. Katowice University of Economics, Katowice, 2003a); Stat Transit 4(5):779–798, 2000) where accuracy of some
sampling strategies were compared, too.These sampling designs cannot be useful in the case when there are some censored observations
of the auxiliary variable. Moreover, they can be much too sensitive to outliers observations. In these cases the sampling
design proportionate to the order statistic of an auxiliary variable can be more useful. That is why such an unequal probability
sampling design is proposed here. Its particular cases as well as its conditional version are considered, too. The sampling
scheme implementing this sampling design is proposed. The inclusion probabilities of the first and second orders were evaluated.
The well known Horvitz–Thompson estimator is taken into account. A ratio estimator dependent on an order statistic is constructed.
It is similar to the well known ratio estimator based on the population and sample means. Moreover, it is an unbiased estimator
of the population mean when the sample is drawn according to the proposed sampling design dependent on the appropriate order
statistic. 相似文献