A test for abrupt change in hazard regression models with Weibull baselines

We develop a likelihood ratio test for an abrupt change point in Weibull hazard functions with covariates, including the two-piece constant hazard as a special case. We first define the log-likelihood ratio test statistic as the supremum of the profile log-likelihood ratio process over the interval which may contain an unknown change point. Using local asymptotic normality (LAN) and empirical measure, we show that the profile log-likelihood ratio process converges weakly to a quadratic form of Gaussian processes. We determine the critical values of the test and discuss how the test can be used for model selection. We also illustrate the method using the Chronic Granulomatous Disease (CGD) data.     

Econometric Applications of the Forward Search in Regression: Robustness,Diagnostics, and Graphics

The article illustrates the use of the forward search to provide robust analyses of econometric data. The emphasis is on informative plots that reveal the inferential importance of each observation. The division of observations into “good” and “bad” leverage points is shown to be potentially misleading.     

A Novel Method for Visualization of Clustering Results

Sammon mapping is an approach of nonlinear dimension reduction and can be used for visualization. To avoid numerical complexity of the algorithm of traditional Sammon mapping, Kovacs and Abonyi (2004 Kovacs , A. , Abonyi , J. ( 2004 ). Visualization of fuzzy clustering results by modified Sammon mapping . Proceedings of the 3rd International Symposium of Hungarian Researchers on Computational Intelligence 177 – 188 . [Google Scholar]) proposed a modified Sammon mapping method. However, this improvement can only be applied to fuzzy clustering results. By using the property of Fermat point, we develop a new method in this article that can be applied to any clustering results. Different from other methods of visualization, we transfer information of clustering results into concentric circles around the Fermat points. So our procedure can demonstrate the data structure in a more informative way and the clustering results become easier to understand, especially for nonprofessionals. The effectiveness of the proposed method is studied by application to a real data in this article.     

A Novel Method to Calculate Mean Survival Time for Time-to-Event Data

In the analysis of time-to-event data, restricted mean survival time has been well investigated in the literature and provided by many commercial software packages, while calculating mean survival time remains as a challenge due to censoring or insufficient follow-up time. Several researchers have proposed a hybrid estimator of mean survival based on the Kaplan–Meier curve with an extrapolated tail. However, this approach often leads to biased estimate due to poor estimate of the parameters in the extrapolated “tail” and the large variability associated with the tail of the Kaplan–Meier curve due to small set of patients at risk. Two key challenges in this approach are (1) where the extrapolation should start and (2) how to estimate the parameters for the extrapolated tail. The authors propose a novel approach to calculate mean survival time to address these two challenges. In the proposed approach, an algorithm is used to search if there are any time points where the hazard rates change significantly. The survival function is estimated by the Kaplan–Meier method prior to the last change point and approximated by an exponential function beyond the last change point. The parameter in the exponential function is estimated locally. Mean survival time is derived based on this survival function. The simulation and case studies demonstrated the superiority of the proposed approach.     

Storage Life Prediction for a High-Performance Capacitor Using Multi-Phase Wiener Degradation Model

Capacitance is a critical performance characteristic of high-voltage-pulse capacitor which is used to store and discharge electrical energy rapidly. The capacitors usually are stored for a long period of time before put into use. Experimental result and engineering experience indicate that the capacitance increases with storage time and will eventually exceed the failure threshold, which means that the capacitor may fail during storage. This is a typical mode of degradation failure for long storage products. Further, the capacitance degradation path can be extrapolated in several stages based on the shifting characteristics. That is, the capacitance increases slowly or fluctuates in the initial storage stage that lasts about three months. Then it increases sharply in the middle stage which lasts about four months. After the two stages, the capacitor enters into the third stage in which capacitance increases constantly. This degradation phenomenon motivates us to study the storage life prediction method based on multi-phase degradation path model. The storage performance degradation mechanism of high-voltage-pulse capacitor was investigated, which provides the physical basis for multi-phase Wiener degradation model. Identification procedure for the transition points in the degradation path was proposed using maximum likelihood principle (MLP). The result of Kruskal-Wallis test which is the method to test whether two populations are consistent or not in statistics showed that the transition points are statistically effective. Other parameters in the multi-phase degradation model are estimated with maximum likelihood estimation (MLE) after the transition points have been specified. The multi-phase Inverse Gaussian (IG) distribution for storage life was deduced for the capacitor, and the point and interval estimation procedure for reliable storage life are constructed with bootstrap method. The efficiency and effectiveness of the proposed multi-phase degradation model is compared with storage life prediction under single-phase condition.     

Locally optimal invariant tests for change in level

The classical change point problem is considered, from the invariance point of view. Locally optimal invariant tests are derived for the change in level, when the initial level and the common variance are assumed to be unknown. The tests derived by Chernoff and Zacks (1964) and Gardner (1969), for the change in level, when variance is known, are shown to be locally optimal invariant tests.     

On adaptive statistical inferences

k?i=1 T_l T_k     

Bayesian Estimation of Change Point in Inverse Weibull Sequence

A sequence of independent lifetimes X ₁,…, X _m , X _m+1,…, X _n were observed from inverse Weibull distribution with mean stress θ₁ and reliability R ₁(t ₀) at time t ₀ but later it was found that there was a change in the system at some point of time m and it is reflected in the sequence after X _m by change in mean stress θ₁ and in reliability R ₂(t ₀) at time t ₀. The Bayes estimators of m, R ₁(t ₀) and R ₂(t ₀) are derived when a poor and a more detailed prior information is introduced into the inferential procedure. The effects of correct and wrong prior information on the Bayes estimators are studied.     

新西兰托幼一体化课程纲要介绍与启示

学前教育应当为儿童提供什么样的经验以及如何组织这些经验,将直接影响儿童的成长与发展。随着托幼一体化成为我国学前教育发展的趋势,寻求建设一体化课程体系的有效路径是我国亟须解决的问题。新西兰已建立起比较完善的托育在内的托幼一体化课程标准,从培养目标、内容、实施到评价等一系列经验,给世界各国提供了典型借鉴。目前,我国托幼一体化课程建设处于探索阶段,相关研究比较有限。本文通过解析新西兰托幼一体化课程纲要的逻辑起点和内容要素,以期为破解我国托幼一体化课程体系的建构提供思考方向。