A Bernstein inequality for exponentially growing graphs

In this article, we present a Bernstein inequality for sums of random variables which are defined on a graphical network whose nodes grow at an exponential rate. The inequality can be used to derive concentration inequalities in highly connected networks. It can be useful to obtain consistency properties for non parametric estimators of conditional expectation functions which are derived from such networks.     

An effective estimation strategy for population mean under random non-response situations in two-phase successive sampling

This paper presents a modified exponential type estimation strategy for the current population mean in the presence of random non-response situations in two-occasion successive sampling under two-phase set-up. The properties of the proposed estimators have been examined with the assumption that numbers of sampling units follow a distribution due to random non-response. The performances of the proposed estimators are compared with the estimators designated for the complete response situations. Empirical studies are carried out to show the dominance nature of the proposed estimators over the estimator defined for complete response situations. Appropriate recommendations have been made to the survey practitioners/researchers for their real-life practical applications.     

Tobit regression for modeling mean survival time using data subject to multiple sources of censoring

Mean survival time is often of inherent interest in medical and epidemiologic studies. In the presence of censoring and when covariate effects are of interest, Cox regression is the strong default, but mostly due to convenience and familiarity. When survival times are uncensored, covariate effects can be estimated as differences in mean survival through linear regression. Tobit regression can validly be performed through maximum likelihood when the censoring times are fixed (ie, known for each subject, even in cases where the outcome is observed). However, Tobit regression is generally inapplicable when the response is subject to random right censoring. We propose Tobit regression methods based on weighted maximum likelihood which are applicable to survival times subject to both fixed and random censoring times. Under the proposed approach, known right censoring is handled naturally through the Tobit model, with inverse probability of censoring weighting used to overcome random censoring. Essentially, the re‐weighting data are intended to represent those that would have been observed in the absence of random censoring. We develop methods for estimating the Tobit regression parameter, then the population mean survival time. A closed form large‐sample variance estimator is proposed for the regression parameter estimator, with a semiparametric bootstrap standard error estimator derived for the population mean. The proposed methods are easily implementable using standard software. Finite‐sample properties are assessed through simulation. The methods are applied to a large cohort of patients wait‐listed for kidney transplantation.     

Hybrid pairwise‐likelihood estimation methods for incomplete longitudinal binary data

In longitudinal data, missing observations occur commonly with incomplete responses and covariates. Missing data can have a ‘missing not at random’ mechanism, a non‐monotone missing pattern, and moreover response and covariates can be missing not simultaneously. To avoid complexities in both modelling and computation, a two‐stage estimation method and a pairwise‐likelihood method are proposed. The two‐stage estimation method enjoys simplicities in computation, but incurs more severe efficiency loss. On the other hand, the pairwise approach leads to estimators with better efficiency, but can be cumbersome in computation. In this paper, we develop a compromise method using a hybrid pairwise‐likelihood framework. Our proposed approach has better efficiency than the two‐stage method, but its computational cost is still reasonable compared to the pairwise approach. The performance of the methods is evaluated empirically by means of simulation studies. Our methods are used to analyse longitudinal data obtained from the National Population Health Study.     

心理学的遗忘理论对二语损耗的解释力

语言损耗经过三十年的发展,取得了许多有价值的研究成果。在回顾二语损耗研究的基础上,运用心理学遗忘理论中的提取变慢说（或提取失败说）、干扰说以及遗忘曲线,通过对国内外的二语损耗研究结果进行解释,发现提取速度变慢说（或提取失败说）可以解释二语损耗研究中受损者在产出性技能损耗方面的表现以及产出性技能与接受性技能在损耗方面的差异;干扰说可以解释二语损耗研究中受损者在音素、词汇以及形态-句法等方面的损耗。但是,遗忘曲线却无法解释二语损耗研究中出现的＂最初的稳定状态＂现象与二语损耗的倒置假设。     

长沙夜市居民环境意识现状研究

夜市经济在给社会带来繁荣的同时,也造成了环境质量的下降。本研究采用问卷调查的方式,对长沙夜市集中地段的居民就居民的环境意识、居民对夜市与环境的认识、政府对夜市环境的管理力度等方面的情况进行了随机调查。结果表明：长沙夜市环境虽然在政府的努力下有所改善,但仍然存在许多问题。因此,应该划定和设立专门的夜市经营区域,实行准入制度,打击无照经营,加强对占道经营的专项整治,整顿夜市行业卫生,加强居民及经营者的环境保护宣传教育工作。     

共因失效修理工多重休假的两相同部件串联系统的可靠性分析[

研究了共因失效修理工多重休假的两相同部件串联系统的可靠性,在假定部件的失效分布服从指数分布,修理工修理时间和休假时间均服从一般连续型分布的条件下,利用补充变量法,得到了该系统的瞬时可用度和稳态可用度、系统的可靠度、系统的瞬时和稳态故障频度等重要可靠性指标。     

On MLEs of the parameters of a modified Weibull distribution for progressively type-2 censored samples

Lifetimes of modern mechanic or electronic units usually exhibit bathtub-shaped failure rates. An appropriate probability distribution to model such data is the modified Weibull distribution proposed by Lai et al. [15]. This distribution has both the two-parameter Weibull and type-1 extreme value distribution as special cases. It is able to model lifetime data with monotonic and bathtub-shaped failure rates, and thus attracts some interest among researchers because of this property. In this paper, the procedure of obtaining the maximum likelihood estimates (MLEs) of the parameters for progressively type-2 censored and complete samples are studied. Existence and uniqueness of the MLEs are proved.     

Search boundaries of the truncated discrete sequential test

The theme of this paper is improved planning of binomial sequential probability ratio tests in the context of comparison of two objects as to their time between failures or to failure, assumed to be exponentially distributed. The authors’ earlier works established that the probabilities of I- and II- type errors (α and β) are discrete in character and do not lend themselves to analytical expression. Accordingly, the choice of the optimal parameters for the decision boundaries necessitates a search for extrema in discrete sets. The present work outlines a procedure that involves application of the continued-fractions theory, and permits finding the set of boundary positions in which the test characteristics undergo changes. It was established, that in the domains described in the earlier papers, the relationships of α and β versus these positions are close to planar and – within narrow limits – stepwise. The step sizes are highly variable, so that the standard minimum search procedures are either cumbersome or actually useless. On the basis of these relationships~– and others – a search algorithm is proposed for the optimal test boundaries. An example is presented – planning and implementation of this test in the integrated-circuit industry.     

Detection of changes in a random financial sequence with a stable distribution

Quick detection of unanticipated changes in a financial sequence is a critical problem for practitioners in the finance industry. Based on refined logarithmic moment estimators for the four parameters of a stable distribution, this article presents a stable-distribution-based multi-CUSUM chart that consists of several CUSUM charts and detects changes in the four parameters in an independent and identically distributed random sequence with the stable distribution. Numerical results of the average run lengths show that the multi-CUSUM chart is superior (robust and quick) on the whole to a single CUSUM chart in detecting the shift change of the four parameters. A real example that monitors changes in IBM's stock returns is used to demonstrate the performance of the proposed method.