共查询到20条相似文献,搜索用时 15 毫秒
1.
This paper presents a procedure for testing the hypothesis that the underlying distribution of the data is elliptical when using robust location and scatter estimators instead of the sample mean and covariance matrix. Under mild assumptions that include elliptical distributions without first moments, we derive the test statistic asymptotic behavior under the null hypothesis and under special alternatives. Numerical experiments allow to compare the behavior of the tests based on the sample mean and covariance matrix with that based on robust estimators, under various elliptical distributions and different alternatives. We also provide a numerical comparison with other competing tests. 相似文献
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Gemai Chen Richard A. Lockhart Michael A. Stephens 《Revue canadienne de statistique》2002,30(2):177-209
The authors provide a rigorous large sample theory for linear models whose response variable has been subjected to the Box‐Cox transformation. They provide a continuous asymptotic approximation to the distribution of estimators of natural parameters of the model. They show, in particular, that the maximum likelihood estimator of the ratio of slope to residual standard deviation is consistent and relatively stable. The authors further show the importance for inference of normality of the errors and give tests for normality based on the estimated residuals. For non‐normal errors, they give adjustments to the log‐likelihood and to asymptotic standard errors. 相似文献
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Hend Auda 《统计学通讯:模拟与计算》2013,42(8):2401-2412
ABSTRACTWang et al. (2013) provided a comprehensive study of 14 tests, including two tests based on the Gini mean difference (GMD) introduced by Auda (2006), applicable for data from populations with an unknown median. This paper is a similar study of symmetry tests applicable for data from populations with a known median. We are showing that GMD tests compare favorably with several existing procedures in controlling the type I error as well as in power. Results of the study are shown graphically, which makes the tests’ power easy to assess. 相似文献
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Delphine Cassart Marc Hallin Davy Paindaveine 《Journal of statistical planning and inference》2008,138(8):2499-2525
We consider a general class of skewed univariate densities introduced by Fechner [1897. Kollectivmasslehre. Engleman, Leipzig], and derive optimal testing procedures for the null hypothesis of symmetry within that class. Locally and asymptotically optimal (in the Le Cam sense) tests are obtained, both for the case of symmetry with respect to a specified location as for the case of symmetry with respect to some unspecified location. Signed-rank based versions of these tests are also provided. The efficiency properties of the proposed procedures are investigated by a derivation of their asymptotic relative efficiencies with respect to the corresponding Gaussian parametric tests based on the traditional Pearson–Fisher coefficient of skewness. Small-sample performances under several types of asymmetry are investigated via simulations. 相似文献
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This paper is dedicated to the study of the composite quantile regression (CQR) estimations of time-varying parameter vectors for multidimensional diffusion models. Based on the local linear fitting for parameter vectors, we propose the local linear CQR estimations of the drift parameter vectors, and verify their asymptotic biases, asymptotic variances and asymptotic normality. Moreover, we discuss the asymptotic relative efficiency (ARE) of the local linear CQR estimations with respect to the local linear least-squares estimations. We obtain that the local estimations that we proposed are much more efficient than the local linear least-squares estimations. Simulation studies are constructed to show the performance of the estimations proposed. 相似文献
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Gauss M. Cordeiro Thiago G. Ramires Edwin M. M. Ortega 《Journal of Statistical Computation and Simulation》2018,88(3):432-456
We introduce a new class of distributions called the Burr XII system of densities with two extra positive parameters. We provide a comprehensive treatment of some of its mathematical properties. We estimate the model parameters by maximum likelihood. We assess the performance of the maximum likelihood estimators in terms of biases and mean squared errors by means of a simulation study. We also introduce a new family of regression models based on this system of densities. The usefulness of the proposed models is illustrated by means of three real data sets. 相似文献
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《Journal of Statistical Computation and Simulation》2012,82(10):2101-2114
We introduce conditional median absolute deviation to characterize how the local variability of one quantitative random variable varies with another one. A two-step estimation procedure is proposed and the resultant estimator possesses an adaptiveness property. Simulation indicates that this estimator is much more efficient than its competitors such as the conditional semi-interquartile range. 相似文献
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《Scandinavian Journal of Statistics》2018,45(3):444-464
We propose a semiparametric estimator for single‐index models with censored responses due to detection limits. In the presence of left censoring, the mean function cannot be identified without any parametric distributional assumptions, but the quantile function is still identifiable at upper quantile levels. To avoid parametric distributional assumption, we propose to fit censored quantile regression and combine information across quantile levels to estimate the unknown smooth link function and the index parameter. Under some regularity conditions, we show that the estimated link function achieves the non‐parametric optimal convergence rate, and the estimated index parameter is asymptotically normal. The simulation study shows that the proposed estimator is competitive with the omniscient least squares estimator based on the latent uncensored responses for data with normal errors but much more efficient for heavy‐tailed data under light and moderate censoring. The practical value of the proposed method is demonstrated through the analysis of a human immunodeficiency virus antibody data set. 相似文献
10.
A procedure based on the empirical characteristic function is proposed for the estimation of the center of symmetric distributions. The method is an adaptive modification of the procedure proposed by Koutrouvelis (1985). The asymptotic behavior of the resulting estimator is investigated and finite sample comparisons are made with the previous nonadaptive estimator and an adaptive trimmed mean proposed by Hogg (1974). 相似文献
11.
Let X and Y be independent and identically distributed random variables having a continuous distribution function. We study new consistent tests for symmetry around a known median based on the fact that the distribution of X is symmetric around 0 if, and only if, |X| and |max(X,Y)| have the same distribution. 相似文献
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In this paper, we consider the weighted composite quantile regression for linear model with left-truncated data. The adaptive penalized procedure for variable selection is proposed. The asymptotic normality and oracle property of the resulting estimators are also established. Simulation studies are conducted to illustrate the finite sample performance of the proposed methods. 相似文献
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In this paper, we propose two new tests to test the symmetry of a distribution. These tests are built up on the asymptotic normality of the L1-distance to the symmetry of the Kernel and histogram density estimates. A simulation study is carried out to evaluate performances of the kernel based test. 相似文献
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James P. McDermott G. Jogesh Babu John C. Liechty Dennis K. J. Lin 《Statistics and Computing》2007,17(4):311-321
We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In
this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic.
We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve
that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed
for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation.
For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation
study to perform well and to have several distinct advantages over existing methods. 相似文献
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《Journal of Statistical Computation and Simulation》2012,82(17):3480-3497
We develop two tests sensitive to various departures from composite goodness-of-fit hypothesis of normality. The tests are based on the sums of squares of some components naturally arising in decomposition of the Shapiro–Wilk-type statistic. Each component itself has diagnostic properties. The numbers of squared components in sums are determined via some novel selection rules based on the data. The new solutions prove to be effective tools in detecting a broad spectrum of sources of non-Gaussianity. We also discuss two variants of the new tests adjusted to verification of simple goodness-of-fit hypothesis of normality. These variants also compare well to popular competitors. 相似文献
19.
There are a variety of economic areas, such as studies of employment duration and of the durability of capital goods, in which data on important variables typically are censored. The standard techinques for estimating a model from censored data require the distributions of unobservable random components of the model to be specified a priori up to a finite set of parameters, and misspecification of these distributions usually leads to inconsistent parameter estimates. However, economic theory rarely gives guidance about distributions and the standard estimation techniques do not provide convenient methods for identifying distributions from censored data. Recently, several distribution-free or semiparametric methods for estimating censored regression models have been developed. This paper presents the results of using two such methods to estimate a model of employment duration. The paper reports the operating characteristics of the semiparametric estimators and compares the semiparametric estimates with those obtained from a standard parametric model. 相似文献
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ABSTRACTValue-at-Risk (VaR) is one of the best known and most heavily used measures of financial risk. In this paper, we introduce a non-iterative semiparametric model for VaR estimation called the single index quantile regression time series (SIQRTS) model. To test its performance, we give an application to four major US market indices: the S&P 500 Index, the Russell 2000 Index, the Dow Jones Industrial Average, and the NASDAQ Composite Index. Our results suggest that this method has a good finite sample performance and often outperforms a number of commonly used methods. 相似文献