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921.
Suppose that some information is available for the particular factor. The experimenter may apply the technique of foldover to isolate the factor and the two-factor interactions involving this factor. In fact, under some situations this can be done by the method of semi-folding. We will discuss this property in detail in this article. Furthermore, we use the computer to search the corresponding optimal semi-folding design for the given 2 k?p designs that are tabulated in Chen et al. (1993) research. 相似文献
922.
923.
Cheng-Hung Lee 《统计学通讯:理论与方法》2013,42(23):4308-4321
In this article, we consider the problem of sequentially estimating the mean of a Poisson distribution under LINEX (linear exponential) loss function and fixed cost per observation within a Bayesian framework. An asymptotically pointwise optimal rule with a prior distribution is proposed and shown to be asymptotically optimal for arbitrary priors. The proposed asymptotically pointwise optimal rule is illustrated using a real data set. 相似文献
924.
We consider non-parametric estimation of a continuous cdf of a random vector (X 1, X 2). With bivariate RC data, it is stated in van der Laan (1996, p. 59810, Ann. Statist.), Quale et al. (2006, JASA) etc. that “it is well known that the NPMLE for continuous data is inconsistent (Tsai et al. (1986)).” The claim is based on a result in Tsai et al. (1986, p.1352, Ann. Statist.) that if X 1 is right censored but not X 2, then common ways for defining one NPMLE lead to inconsistency. If X 1 is right censored and X 2 is type I right-censored (which includes the case in Tsai et al.), we present a consistent NPMLE. The result corrects a common misinterpretation of Tsai's example (Tsai et al., 1986, Ann. Statist.). 相似文献
925.
Correlated binary data is obtained in many fields of biomedical research. When constructing a confidence interval for the proportion of interest, asymptotic confidence intervals have already been developed. However, such asymptotic confidence intervals are unreliable in small samples. To improve the performance of asymptotic confidence intervals in small samples, we obtain the Edgeworth expansion of the distribution of the studentized mean of beta-binomial random variables. Then, we propose new asymptotic confidence intervals by correcting the skewness in the Edgeworth expansion in one direct and two indirect ways. New confidence intervals are compared with the existing confidence intervals in simulation studies. 相似文献
926.
In this article, we propose a method based on the Lagrangian probability distributions for developing new dependence models. Specifically, a generalized Poisson–gamma dependence model is derived. The maximum likelihood estimation (MLE) technique is proposed for estimating the dependence model parameters. Application of the generalized Poisson–gamma dependence model is illustrated by using an operational risks dataset. 相似文献
927.
ABSTRACTA common method for estimating the time-domain parameters of an autoregressive process is to use the Yule–Walker equations. Tapering has been shown intuitively and proven theoretically to reduce the bias of the periodogram in the frequency domain, but the intuition for the similar bias reduction in the time-domain estimates has been lacking. We provide insightful reasoning for why tapering reduces the bias in the Yule–Walker estimates by showing them to be equivalent to a weighted least-squares problem. This leads to the derivation of an optimal taper which behaves similarly to commonly used tapers. 相似文献
928.
This paper proposes the use of tne likelihood ratio statistic in choosing between a Neibull or gamma model, values of the probability of correct seeiection are obtained by Monte Carlo simulation. This method provides some basis for decision even when the sample size is small. The technique is applied to four sets of data from the literature. 相似文献
929.
930.
This paper addresses the problem of identifying groups that satisfy the specific conditions for the means of feature variables. In this study, we refer to the identified groups as “target clusters” (TCs). To identify TCs, we propose a method based on the normal mixture model (NMM) restricted by a linear combination of means. We provide an expectation–maximization (EM) algorithm to fit the restricted NMM by using the maximum-likelihood method. The convergence property of the EM algorithm and a reasonable set of initial estimates are presented. We demonstrate the method's usefulness and validity through a simulation study and two well-known data sets. The proposed method provides several types of useful clusters, which would be difficult to achieve with conventional clustering or exploratory data analysis methods based on the ordinary NMM. A simple comparison with another target clustering approach shows that the proposed method is promising in the identification. 相似文献