A Note On Beta Inverse-Weibull Distribution

The inverse Weibull distribution is one of the widely applied distribution for problems in reliability theory. In this article, we introduce a generalization—referred to as the Beta Inverse-Weibull distribution—generated from the logit of a beta random variable. We provide a comprehensive treatment of the mathematical properties of the Beta Inverse-Weibull distribution. The shapes of the corresponding probability density function and the hazard rate function have been obtained and graphical illustrations have been given. The distribution is found to be unimodal. Results for the non central moments are obtained. The relationship between the parameters and the mean, variance, skewness, and kurtosis are provided. The method of maximum likelihood is proposed for estimating the model parameters. We hope that this generalization will attract wider applicability to the problems in reliability theory and mechanical engineering.     

Tail Functions and Iterative Weights in Binary Regression

In interpreting the binary regression models often used in the analysis of dose-response data, it is common to introduce the idea of an underlying continuous tolerance distribution. Different choices of link function lead to different tolerance distributions. A useful way of comparing these alternatives is to compare the hazard functions or tail functions associated with each tolerance distribution. Tail functions can also be applied to give numerically preferable formulas for the iterative weights and the adjusted dependent variable in the fitting of binary regression models by the iteratively reweighted least-squares algorithm.     

Robust Bayesian analysis of generalized inverted family of distributions

ABSTRACT

In the current study we develop the robust Bayesian inference for the generalized inverted family of distributions (GIFD) under an ε-contamination class of prior distributions for the shape parameter α, with different possibilities of known and unknown scale parameter. We used Type II censoring and Bartholomew sampling scheme (1963) for the following derivations under the squared-error loss function (SELF) and linear exponential (LINEX) loss function : ML-II Bayes estimators of the i) parameters; ii) Reliability function and; iii) Hazard function. We also present simulation study and analysis of a real data set.     

The largest SNR distribution

The probability distribution of the maximum of normalized SNRs (signal-to-noise ratios) is studied for wireless systems with multiple branches. Explicit expressions and bounds are derived for the cumulative distribution function, probability density function, hazard rate function, moment generating function, nth moment, variance, skewness, kurtosis, mean deviation, Shannon entropy, order statistics and the asymptotic distribution of the extreme order statistics. Estimation procedures are derived by the methods of moments and maximum likelihood. An application is illustrated with respect to performance assessment of wireless systems.     

Survey non-response and the duration of unemployment

Summary.  Social surveys are often used to estimate unemployment duration distributions. Survey non-response may then cause a bias. We study this by using a data set that combines survey information of individual workers with administrative records of the same workers. The latter provide information on durations of unemployment and personal characteristics of all survey respondents and non-respondents. We develop a method to distinguish empirically between two explanations for a bias in results based on only survey data: selectivity due to related unobserved determinants of durations of unemployment and non-response and a causal effect of a job exit on non-response. The latter may occur even in fully homogeneous populations. The methodology exploits variation in the timing of the duration outcome relative to the survey moment. The results show evidence for both explanations. We discuss implications for standard methods to deal with non-response bias.     

基于电容近感原理的无源探测信号分析

无源近感探测系统信号处理模块中的振荡网络设计是产生探测信号的关键所在,系统通过产生准静电场敏感近距目标的存在与否。鉴于此,讨论了一种基于电容原理的无源近感探测系统的探测信号。通过对三导体进行电磁分析,描述了探测信号产生的机理。仿真实验指出了相关部件设计的关键点所在,并描述了不同弹目交会条件下,鉴频信号变化的特点。     

电容近炸引信的综合参数测试系统

测试电容近炸引信的信号处理电路的动态性能参数,是产品研制、调试、生产的重要环节.利用计算机、信号调理板、数据采集板和在LabView平台上开发的软件,构成一套完整的电容近炸引信综合参数测试系统.该系统针对电容近炸引信的检波放大信号、积分信号、微分信号和启动信号等技术指标进行测试和分析,判断电路工作情况,分析有故障电路的故障原因.该系统具有测试精度高、开发成本低、检测效率高、操作简单等优点.     

Parental Housing Assistance and Parent‐Child Proximity in Italy

Many studies of intergenerational exchanges include parent‐child proximity as an exogenous explanatory variable. Proximity may itself be a consequence of intergenerational resource flows, however. We analyze patterns of economic transfers between generations and their relationship to parent‐child proximity in Italy. Parental support for a child's home purchase may influence the child's choice of location, whether to facilitate parent‐child contacts, grandchild care, or parent care. We examine the situation of married couples, focusing on housing help received and the association of that help with proximity to each spouse's parents. Using 1998 survey data and multinomial logistic regression models, we find that past housing assistance has a significant effect on current proximity to each spouse's parents, controlling for parents' survival, family composition, and other factors.     

Stochastic comparisons of parallel and series systems of dependent components equipped with starting devices

This paper deals with series and parallel systems of dependent components equipped with starters. We study the hazard rate order, the dispersive order and the usual stochastic order of system lifetimes in the context of component lifetimes having proportional hazard rates. The main results either generalize or extend corresponding conclusions of Joo and Mi (2010) and Da, Ding, and Li (2010).     

Bhattacharyya and Kshirsagar Bounds in Generalized Gamma Distribution

In this article, we consider the exact computation of the famous halfspace depth (HD) and regression depth (RD) from the view of cutting a convex cone with hyperplanes. Two new algorithms are proposed for computing these two notions of depth. The first one is relatively straightforward but quite inefficient, whereas the second one is much faster. It is noteworthy that both of them can be implemented to spaces with dimension beyond three. Some numerical examples are also provided in what follows to illustrate the performances.