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161.
Non-central chi-squared distribution plays a vital role in statistical testing procedures. Estimation of the non-centrality parameter provides valuable information for the power calculation of the associated test. We are interested in the statistical inference property of the non-centrality parameter estimate based on one observation (usually a summary statistic) from a truncated chi-squared distribution. This work is motivated by the application of the flexible two-stage design in case–control studies, where the sample size needed for the second stage of a two-stage study can be determined adaptively by the results of the first stage. We first study the moment estimate for the truncated distribution and prove its existence, uniqueness, and inadmissibility and convergence properties. We then define a new class of estimates that includes the moment estimate as a special case. Among this class of estimates, we recommend to use one member that outperforms the moment estimate in a wide range of scenarios. We also present two methods for constructing confidence intervals. Simulation studies are conducted to evaluate the performance of the proposed point and interval estimates. 相似文献
162.
Continuous non-Gaussian stationary processes of the OU-type are becoming increasingly popular given their flexibility in modelling stylized features of financial series such as asymmetry, heavy tails and jumps. The use of non-Gaussian marginal distributions makes likelihood analysis of these processes unfeasible for virtually all cases of interest. This paper exploits the self-decomposability of the marginal laws of OU processes to provide explicit expressions of the characteristic function which can be applied to several models as well as to develop efficient estimation techniques based on the empirical characteristic function. Extensions to OU-based stochastic volatility models are provided. 相似文献
163.
Rosa Arboretti Giancristofaro Stefano Bonnini Fortunato Pesarin 《Statistics and Computing》2009,19(2):209-216
In many sciences researchers often meet the problem of establishing if the distribution of a categorical variable is more
concentrated, or less heterogeneous, in population P
1 than in population P
2. An approximate nonparametric solution to this problem is discussed within the permutation context. Such a solution has similarities
to that of testing for stochastic dominance, that is, of testing under order restrictions, for ordered categorical variables.
Main properties of given solution and a Monte Carlo simulation in order to evaluate its degree of approximation and its power
behaviour are examined. Two application examples are also discussed. 相似文献
164.
165.
The data collection process and the inherent population structure are the main causes for clustered data. The observations in a given cluster are correlated, and the magnitude of such correlation is often measured by the intra-cluster correlation coefficient. The intra-cluster correlation can lead to an inflated size of the standard F test in a linear model. In this paper, we propose a solution to this problem. Unlike previous adjustments, our method does not require estimation of the intra-class correlation, which is problematic especially when the number of clusters is small. Our simulation results show that the new method outperforms the existing methods. 相似文献
166.
Lili Tian Albert Vexler Li Yan Enrique F. Schisterman 《Journal of statistical planning and inference》2009
In many diagnostic studies, multiple diagnostic tests are performed on each subject or multiple disease markers are available. Commonly, the information should be combined to improve the diagnostic accuracy. We consider the problem of comparing the discriminatory abilities between two groups of biomarkers. Specifically, this article focuses on confidence interval estimation of the difference between paired AUCs based on optimally combined markers under the assumption of multivariate normality. Simulation studies demonstrate that the proposed generalized variable approach provides confidence intervals with satisfying coverage probabilities at finite sample sizes. The proposed method can also easily provide P-values for hypothesis testing. Application to analysis of a subset of data from a study on coronary heart disease illustrates the utility of the method in practice. 相似文献
167.
Modified inference about the mean of the exponential distribution using moving extreme ranked set sampling 总被引:1,自引:1,他引:0
The maximum likelihood estimator (MLE) and the likelihood ratio test (LRT) will be considered for making inference about the
scale parameter of the exponential distribution in case of moving extreme ranked set sampling (MERSS). The MLE and LRT can
not be written in closed form. Therefore, a modification of the MLE using the technique suggested by Maharota and Nanda (Biometrika
61:601–606, 1974) will be considered and this modified estimator will be used to modify the LRT to get a test in closed form
for testing a simple hypothesis against one sided alternatives. The same idea will be used to modify the most powerful test
(MPT) for testing a simple hypothesis versus a simple hypothesis to get a test in closed form for testing a simple hypothesis
against one sided alternatives. Then it appears that the modified estimator is a good competitor of the MLE and the modified
tests are good competitors of the LRT using MERSS and simple random sampling (SRS). 相似文献
168.
This paper is concerned with semiparametric discrete kernel estimators when the unknown count distribution can be considered to have a general weighted Poisson form. The estimator is constructed by multiplying the Poisson estimate with a nonparametric discrete kernel-type estimate of the Poisson weight function. Comparisons are then carried out with the ordinary discrete kernel probability mass function estimators. The Poisson weight function is thus a local multiplicative correction factor, and is considered as the uniform measure to detect departures from the equidispersed Poisson distribution. In this way, the effects of dispersion and zero-proportion with respect to the standard Poisson distribution are also minimized. This method of estimation is also applied to the weighted binomial form for the count distribution having a finite support. The proposed estimators, in addition to being simple, easy-to-implement and effective, also outperform the competing nonparametric and parametric estimators in finite-sample situations. Two examples illustrate this new semiparametric estimation. 相似文献
169.
170.
缺失数据时两个对数正态分布的估计和检验 总被引:1,自引:0,他引:1
讨论了部分缺失数据两对敷正态分布的参数估计和关于总体相同的似然比检验.证明了估计的强相合性和渐近正态性,给出了似然比检验统计量的极限分布,并讨论基于精确分布的检验问题. 相似文献