Sequential LND sensitivity test for binary response data

Sensitivity tests are used to make inferences about a sensitivity, a characteristic property of some products that cannot be observed directly. For binary response sensitivity data (dead or alive, explode or unexplode), the Langlie and Neyer are two well-known sensitivity tests. The priorities of the Langlie and Neyer tests are investigated in this paper. It is shown that the Langlie test has an advantage in getting an overlap, while the Neyer test has better estimation precision. Aiming at improving both the speed of getting an overlap and the estimation precision, we propose a new sensitivity test which replaces the first part of the Neyer test with the Langlie test. Our simulation studies indicate that the proposed test outperforms the Langlie, Neyer and Dror and Steinberg tests from the viewpoints of estimation precision and probability of obtaining an overlap.     

Clustering algorithm for proximity-relation matrix and its applications

In this paper, we present a new algorithm for clustering proximity-relation matrix that does not require the transitivity property. The proposed algorithm is first inspired by the idea of Yang and Wu [16] then turned into a self-organizing process that is built upon the intuition behind clustering. At the end of the process subjects belonging to be the same cluster should converge to the same point, which represents the cluster center. However, the performance of Yang and Wu's algorithm depends on parameter selection. In this paper, we use the partition entropy (PE) index to choose it. Numerical result illustrates that the proposed method does not only solve the parameter selection problem but also obtains an optimal clustering result. Finally, we apply the proposed algorithm to three applications. One is to evaluate the performance of higher education in Taiwan, another is machine–parts grouping in cellular manufacturing systems, and the other is to cluster probability density functions.     

On the exact distribution of the likelihood ratio criterion for testing

The exact null distribution of the likelihood ratio criter- 2 ion for testing the hypothesis H: y = y~; z = a I, a unknown and UQ a given known vector against the alternative A =f H in a p-vari- ate normal population N (y,z) has been derived in the form of Meijer's G-function using mellin integral transform and also in a chisquare series form. Asymptotic behavior of the distribution of -2 log L has also been discussed. Percentage points for p=2(l)10for various level of significance and various degrees of freedom have been computed, but only selected tables have been presented in this paper.     

基于熵理论的DQAF信息量研究

摘要：通过运用信息熵理论对DqAF框架本身的维度、指标信息量问题进行研究,得出：DqAF各维度、指标在账户内部以及不同账户间体现的信息量不同;统计数据账户的生产主体和账户数据类型对于数据质量具有明显的影响作用。基于上述结论,提出对DQAF框架的改进设想：1．对该框架中评估能力欠佳的维度和指标进行改进,制定可行的量化标度用于数据评估;2．根据数据生产部门不同和数据类型差异制定不同的考核评价标准和量化细则。     

Optimization of a product performance using mixture experiments including process variables

This article presents a case study of a chemical compound used in the delay mechanism to start a rocket engine. The compound consists in a three-component mixture. Besides the components proportions, two process variables are considered. The aim of the study is to investigate the mix components proportions and the levels of process variables that set the expected delay time as close as possible to the target value and, at the same time, minimize the width of prediction interval for the response. A linear regression model with normal responses was fitted. Through the model developed, the optimal components proportions and the levels of the process variables were determined. For the model selection, the use of the backward method with an information criterion proved to be efficient in the case under study.     

Markow chain markov field dynamics:models and statistics

This study deals with time dynamics of Markov fields defined on a finite set of sites with State Space E, focussing on Markow Chain Markow Field (MCMF) evolution. Such a model is characterized by two families of potentials:the instantaneous interaction potentials, and the time delay potentials. Four models are specified:auto-exponential dynamics (E=R⁺), auto-normal dynamics (E = R), auto-Poissonian dynamics (E = N) and auto-logistic dynamics (E qualitative and finite). Sufficient conditions ensuring ergodicity and strong law of large numbers are given by using a Lyapunov criterion of stability, and the conditional pseudo-likelihood statistics are summarized. We discuss the identification procedure of the two Markovian graphs and look for validation tests using martingale central limit theorems. An application to meteorological data illustrates such a modelling.     

Change-points in stochastic ordering

This article studies the problem of testing and locating changepoints in stochas¬tic ordering. We propose a sequential process to detect the changepoints from two multinomial distributions. We also obtain the maximum likelihood estimators of two multinomial probability vectors under the assumption that the cumulative distribu¬tions have a changepoint. Asymptotically unbiased Akaike's information criterion is used to estimate the changepoints of two discrete probability distributions. Finally. we demonstrate our procedure by studying a data set pertaining to average daily insulin dose from the Boston Collaborative Drug Surveillance Program and locate the changepoints in stochastic ordering.     

An entropic structure in capability indices

Abstract

Analysis capability indices for symmetric process in normal case is obtained via maximum entropy approach of distribution function of the data. In view of it, we have perused on production processes to be in statistical control. Generally a process is capable based on capability indices when its reasonable index was more than a known threshold value. Thus by conditioning on indices, the most general distribution is found out whose parameters can be approximated by using the data of process. Also analysis via Kullback-Leibler information measure based on the above arguments is obtained in the last part of the paper.     

Slustep size probabilities for generalized poisson distributions

A general theorem is given relating the cluster-size distribution to the Fisher-type limiting form of the distribution resulting from a Poisson distribution of such clusters. The theorem provides a new method for obtaining the cluster-size probabilities. It also yields a necessary and sufficient condition for the infinite divisibility of a distribution on the nonnegative integers. The ethod and the criterion are illustrated using the shifted logarithmic and the shifted zero-truncated Poisson distributions.