Estimation of an exponential quantile under pitman's measure of closeness

We consider the problem of estimating a quantile of an exponential distribution with unknown location and scale parameters under Pitman's measure of closeness (PMC). The loss function is required to satisfy some mild conditions but is otherwise arbitrary. An optimal estimator is obtained in the class of location-scale-equivariant estimators, and its admissibility in the sense of PMC is investigated.     

Nonparametric estimation of discrete hazard functions

A smoothing procedure for discrete time failure data is proposed which allows for the inclusion of covariates. This purely nonparametric method is based on discrete or continuous kernel smoothing techniques that gives a compromise between the data and smoothness. The method may be used as an exploratory tool to uncover the underlying structure or as an alternative to parametric methods when prediction is the primary objective. Confidence intervals are considered and alternative techniques of cross validation based choices of smoothing parameters are investigated.     

Estimation of the MSE matrix of the stein estimator

Uniformly minimum-variance unbiased (UMVU) estimators of the total risk and the mean-squared-error (MSE) matrix of the Stein estimator for the multivariate normal mean with unknown covariance matrix are proposed. The estimated MSE matrix is helpful in identifying the components which contribute most to the total risk. It also contains information about the performance of the shrinkage estimator with respect to other quadratic loss functions.     

ESTIMATION OF GUARANTEE TIME AND MEAN LIFE AFTER WARRANTY FOR TWO-PARAMETER EXPONENTIAL FAILURE MODEL

Suppose manufactured items have failure times distributed with the two-parameter exponential density function à-^le-(x-μ)/à (x≥μ≥0). The paper considers estimation of the guarantee time μ and mean life after warranty à. Properties of various estimators are given for both separate and simultaneous estimation of μ and à. Criteria for comparing estimators are entropy loss, LINEX loss, and (generalized) Pitman nearness.     

On Loss Distributions from Installment-Repaid Loans

The banks have been accumulating huge data bases for many years and are increasingly turning to statistics to provide insight into customer behaviour, among other things. Credit risk is an important issue and certain stochastic models have been developed in recent years to describe and predict loan default. Two of the major models currently used in the industry are considered here, and various ways of extending their application to the case where a loan is repaid in installments are explored. The aspect of interest is the probability distribution of the total loss due to repayment default at some time. Thus, the loss distribution is determined by the distribution of times to default, here regarded as a discrete-time survival distribution. In particular, the probabilities of large losses are to be assessed for insurance purposes.     

What is Loss Aversion?

A behavioral definition of loss aversion is proposed and its implications for original and cumulative prospect theory are analyzed. Original prospect theory is in agreement with the new loss aversion condition, and there utility is capturing all effects of loss aversion. In cumulative prospect theory loss aversion is captured by both the weighting functions and the utility function. Further, some restrictions apply for the weighting functions involved in the latter model.We are indebted to Michèle Cohen and Peter Wakker for helpful comments. The suggestions of an anonymous referee have improved the presentation of the paper.     

How Unique Are the Price–Anderson Limitations on Nuclear Accident Liability?

In this paper we extend the work reported in prior studies. The conclusion drawn from the aggregate of those studies was that the limitation on liability imposed by the Price–Anderson Act for a catastrophic accident at a nuclear power plant ($560 million) is comparable to de facto limitations on recovery following catastrophic events in many other industries. The analysis in those reports was at a high level of abstraction, comparing almost exclusively the potential loss from high consequence accidents with the current assets of major firms in relevant industries. We found that potential loss exceeded assets.     

有耗介质涂覆导体平面上的表面波分析

用横向谐振法分析有耗介质涂覆导体平面上的表面波。结果表明,这种表面波在传播过程中将受到衰减,但不辐射。可见,用有耗介质材料涂覆的雷达目标上的表面波对RCS将没有直接的贡献,但是当传播过程中遇到不连续性或不均匀性时,表面波可能转变成新的辐射源,因此应当考虑对表面波的抑制。     

基于不确定因素的食品安全问题频发的伦理分析

不良食品生产行为给社会带来的危害应由食品生产者及相关的政府职能部门负担起相应的伦理及法律责任。政府职能部门责任伦理意识缺失、消费者生命健康意识淡薄及社会道德监督机制缺失,造成了政府监管、公众安全认知、食品生产行业的道德与法律风险等方面的不确定性,成为食品安全事故频发的深层根源。只有通过健全食品安全监管制度、建构政府信用问责机制,提高政府监管者的责任伦理素养,培养公众的生命健康意识和食品安全问题防范意识,建立食品供应链道德信用跟踪系统,才能真正解决食品安全问题。     

The use of GARCH models in VaR estimation

We evaluate the performance of an extensive family of ARCH models in modeling the daily Value-at-Risk (VaR) of perfectly diversified portfolios in five stock indices, using a number of distributional assumptions and sample sizes. We find, first, that leptokurtic distributions are able to produce better one-step-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecast, whereas the specification of the conditional mean is indifferent. Finally, the ARCH structure producing the most accurate forecasts is different for every portfolio and specific to each equity index.