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81.
Robust tests for the common principal components model 总被引:1,自引:0,他引:1
Graciela Boente Ana M. Pires Isabel M. Rodrigues 《Journal of statistical planning and inference》2009
When dealing with several populations, the common principal components (CPC) model assumes equal principal axes but different variances along them. In this paper, a robust log-likelihood ratio statistic allowing to test the null hypothesis of a CPC model versus no restrictions on the scatter matrices is introduced. The proposal plugs into the classical log-likelihood ratio statistic robust scatter estimators. Using the same idea, a robust log-likelihood ratio and a robust Wald-type statistic for testing proportionality against a CPC model are considered. Their asymptotic distributions under the null hypothesis and their partial influence functions are derived. A small simulation study allows to compare the behavior of the classical and robust tests, under normal and contaminated data. 相似文献
82.
This paper is mainly concerned with minimax estimation in the general linear regression model y=Xβ+ε under ellipsoidal restrictions on the parameter space and quadratic loss function. We confine ourselves to estimators that are linear in the response vector y . The minimax estimators of the regression coefficient β are derived under homogeneous condition and heterogeneous condition, respectively. Furthermore, these obtained estimators are the ridge-type estimators and mean dispersion error (MDE) superior to the best linear unbiased estimator b=(X′W-1X)-1X′W-1y under some conditions. 相似文献
83.
In this paper, we study the MDPDE (minimizing a density power divergence estimator), proposed by Basu et al. (Biometrika 85:549–559,
1998), for mixing distributions whose component densities are members of some known parametric family. As with the ordinary
MDPDE, we also consider a penalized version of the estimator, and show that they are consistent in the sense of weak convergence.
A simulation result is provided to illustrate the robustness. Finally, we apply the penalized method to analyzing the red
blood cell SLC data presented in Roeder (J Am Stat Assoc 89:487–495, 1994).
This research was supported (in part) by KOSEF through Statistical Research Center for Complex Systems at Seoul National University. 相似文献
84.
In this note we consider the equality of the ordinary least squares estimator (OLSE) and the best linear unbiased estimator
(BLUE) of the estimable parametric function in the general Gauss–Markov model. Especially we consider the structures of the
covariance matrix V for which the OLSE equals the BLUE. Our results are based on the properties of a particular reparametrized version of the
original Gauss–Markov model.
相似文献
85.
Nonparametric density estimation in the presence of measurement error is considered. The usual kernel deconvolution estimator
seeks to account for the contamination in the data by employing a modified kernel. In this paper a new approach based on a
weighted kernel density estimator is proposed. Theoretical motivation is provided by the existence of a weight vector that
perfectly counteracts the bias in density estimation without generating an excessive increase in variance. In practice a data
driven method of weight selection is required. Our strategy is to minimize the discrepancy between a standard kernel estimate
from the contaminated data on the one hand, and the convolution of the weighted deconvolution estimate with the measurement
error density on the other hand. We consider a direct implementation of this approach, in which the weights are optimized
subject to sum and non-negativity constraints, and a regularized version in which the objective function includes a ridge-type
penalty. Numerical tests suggest that the weighted kernel estimation can lead to tangible improvements in performance over
the usual kernel deconvolution estimator. Furthermore, weighted kernel estimates are free from the problem of negative estimation
in the tails that can occur when using modified kernels. The weighted kernel approach generalizes to the case of multivariate
deconvolution density estimation in a very straightforward manner. 相似文献
86.
Guillaume Chauvet 《Mathematical Population Studies》2016,23(3):147-163
In the 2006 French housing survey, information is collected on many aspects of housing to describe the housing stock in France and the housing conditions of French households. The basic national sample results from a multistage sampling design. Complementary samples were selected to perform accurate estimations for socio-demographic domains. Some French regions proceeded to a regional and local extension of the national sample. The variance is estimated for a region with a regional and local extension of the basic national sample. 相似文献
87.
Zawar Hussain Mashail M. Al-Sobhi Bander Al-Zahrani Housila P. Singh Tanveer A. Tarray 《Mathematical Population Studies》2016,23(4):205-221
Randomized response models deal with stigmatizing variables appearing in health surveys. Additive and subtractive scrambling in split sample and double response yield unbiased mean and sensitivity estimators of high precision. The split sample method is protective of privacy. The double response method is as protective only conditionally. To achieve the maximum efficiency, the scrambling variables must be similar to each other and the probability of obtaining a true response must be as large as possible. The randomized response procedures yield more efficient estimates of the average total number of classes missed by university students. 相似文献
88.
The censored δ-shock model is a special kind of shock model and it has very important research values in the reliability theory. In this paper, we discuss the parameter estimation of the censored δ-shock model when the inter-arrival times between two successive shocks follows uniform distribution on [a, b]. With the maximum likelihood estimation, we obtain the parameter estimator and expectation of estimator and lifetime of the model. By numerical simulation, we get the empirical result on the estimator of δ and the relationship between δ and other parameters. 相似文献
89.
Here we consider an exponentiated version of the reduced Kies distribution and discuss some of its properties. The parameters of the distribution are estimated by the method of maximum likelihood and illustrated with the help of certain real-life data sets. Asymptotic behavior of the maximum likelihood estimators of the parameters of the distribution is also studied by using certain simulated data sets. 相似文献
90.
We propose an adaptive functional autoregressive (AFAR) forecast model to predict electricity price curves. With time-varying operators, the AFAR model can be safely used in both stationary and nonstationary situations. A closed-form maximum likelihood (ML) estimator is derived under stationarity. The result is further extended for nonstationarity, where the time-dependent operators are adaptively estimated under local homogeneity. We provide theoretical results of the ML estimator and the adaptive estimator. Simulation study illustrates nice finite sample performance of the AFAR modeling. The AFAR model also exhibits a superior accuracy in the forecast exercise of the California electricity daily price curves compared to several alternatives. 相似文献