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排序方式: 共有4694条查询结果,搜索用时 15 毫秒
1.
In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples. 相似文献
2.
AbstractThe problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example. 相似文献
3.
针对目前金属疲劳裂纹扩展检测方法存在效率低、操作繁琐、精度不高,不能实现实时性等缺点,文章提出了基
于机器视觉的裂纹检测方法。根据金属疲劳裂纹扩展试验过程中裂纹图像的采集要求,设计了摄像头位置可自动调整
的疲劳裂纹图像采集系统,包括摄像头安装运动装置,裂纹图像采集装置以及摄像头运动控制系统。图像采集装置由高
分辨率黑白面阵CCD摄像头、光学镜头,光源照明装置和图像采集卡组成,前3者安装在摄像头支架上,与摄像头运动
装置相连。摄像头运动装置中的X,Y,,Z轴运动机构由步进电机带动滚珠导轨机构。在基于ARM技术的运动控制系统
的控制下摄像头可沿X,Y,,Z轴作高精度直线运动,实现和试件之间精确位置的调整。实验结果表明,所设计的系统可
采集到疲劳裂纹扩展试验过程中高清晰度、高分辨率的试件裂纹图像,满足下一步裂绞尺寸计算的要求;摄像头运动定
位精度可达到0. 02 mm,满足精确的系统聚焦、位置调整、跟踪采集的要求。 相似文献
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Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time. 相似文献
7.
We propose testing procedures for the hypothesis that a given set of discrete observations may be formulated as a particular time series of counts with a specific conditional law. The new test statistics incorporate the empirical probability-generating function computed from the observations. Special emphasis is given to the popular models of integer autoregression and Poisson autoregression. The asymptotic properties of the proposed test statistics are studied under the null hypothesis as well as under alternatives. A Monte Carlo power study on bootstrap versions of the new methods is included as well as real-data examples. 相似文献
8.
Nuttanan Wichitaksorn 《统计学通讯:理论与方法》2020,49(8):1801-1817
AbstractThis article proposes a new approach to analyze multiple vector autoregressive (VAR) models that render us a newly constructed matrix autoregressive (MtAR) model based on a matrix-variate normal distribution with two covariance matrices. The MtAR is a generalization of VAR models where the two covariance matrices allow the extension of MtAR to a structural MtAR analysis. The proposed MtAR can also incorporate different lag orders across VAR systems that provide more flexibility to the model. The estimation results from a simulation study and an empirical study on macroeconomic application show favorable performance of our proposed models and method. 相似文献
9.
The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets. 相似文献
10.
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