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11.
讨论增长曲线模型Y =X1BX2 +ε中回归矩阵B的函数C1BC2 的估计L1YL2 +A ,在矩阵损失 (LT2 L1)Y +A - (ST2 XT2 S1X1)B (LT2 L1)Y +A - (ST2 XT2 S1X1)B T 下 ,我们得到了非齐次线性估计L1YL2 +A在非齐次线性估计类Г ={L1YL2 +A|L1:t×p ,L2 ;n×n ,A :t×s均为已知实阵 }中可容许的充要条件 :L1YL2在Г0 ={L1YL2 |L1:t×p ,L2 :n×s均为已知实阵 }中容许且当LT2 XT2 L1X1=ST2 XT2 S1X1时有A =0。 相似文献
12.
Yue Fang 《Journal of statistical planning and inference》2003,110(1-2):55-73
Generalized method of moments (GMM) is used to develop tests for discriminating discrete distributions among the two-parameter family of Katz distributions. Relationships involving moments are exploited to obtain identifying and over-identifying restrictions. The asymptotic relative efficiencies of tests based on GMM are analyzed using the local power approach and the approximate Bahadur efficiency. The paper also gives results of Monte Carlo experiments designed to check the validity of the theoretical findings and to shed light on the small sample properties of the proposed tests. Extensions of the results to compound Poisson alternative hypotheses are discussed. 相似文献
13.
Merging information for semiparametric density estimation 总被引:1,自引:0,他引:1
Konstantinos Fokianos 《Journal of the Royal Statistical Society. Series B, Statistical methodology》2004,66(4):941-958
Summary. The density ratio model specifies that the likelihood ratio of m −1 probability density functions with respect to the m th is of known parametric form without reference to any parametric model. We study the semiparametric inference problem that is related to the density ratio model by appealing to the methodology of empirical likelihood. The combined data from all the samples leads to more efficient kernel density estimators for the unknown distributions. We adopt variants of well-established techniques to choose the smoothing parameter for the density estimators proposed. 相似文献
14.
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
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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
17.
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
18.
The authors study the local influence of observations in multilevel regression models. To this end, they perturb simultaneously the variances, responses and design matrix. To measure the local change caused by these perturbations, they use generalized Cook statistics for the fixed and random parameter estimates. Closed form local influence measures also allow them to assess the joint influence of various observations. They suggest a simple computation method and illustrate their results using two examples. 相似文献
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