On a study of the exponential and Poisson characteristics of the Poisson process

Based on the exponential and Poisson characteristics of the Poisson process, in this work we present some characterizations of the Poisson process as a renewal process. More precisely, let γ_t be the residual life at time t of the renewal process A={A(t),t≥0 }, under suitable condition, we prove that if Var(γ_t)=E ² (γ_t),∀t≥0, then A is a Poisson process. Secondly, we show that if Var (A(t)) is proportional to E (A(t)), then A is a Poisson process also, and Var (A(t))=E (A(t)). Received: August 1999     

A note on finite sample breakdown points of projection based multivariate location and scatter statistics

In this note, general results of finite sample breakdown point are obtained for two classes of projection based location and scatter statistics: the Stahel-Donoho statistics and the Maronna-Yohai statistics. It is shown that these projection based location and scatter statistics can achieve the maximum breakdown point of affine equivariant multivariate location and scatter statistics. General relationships between the finite sample breakdown point of these statistics and the uniform finite sample breakdown point of the sample median and a modified sample median absolute deviation are formally established. Received: May 1999     

Relevance weighted likelihood for dependent data

The relevance-weighted likelihood function weights individual contributions to the likelihood according to their relevance for the inferential problem of interest. Consistency and asymptotic normality of the weighted maximum likelihood estimator were previously proved for independent sequences of random variables. We extend these results to apply to dependent sequences, and, in so doing, provide a unified approach to a number of diverse problems in dependent data. In particular, we provide a heretofore unknown approach for dealing with heterogeneity in adaptive designs, and unify the smoothing approach that appears in many foundational papers for independent data. Applications are given in clinical trials, psychophysics experiments, time series models, transition models, and nonparametric regression. Received: April 2000     

Intra-industry trade and heterogeneity in pollution emission

This paper develops a model of intermediate goods firms heterogeneity with respect to a pollution parameter to analyze the effects of intra-industry trade on final good output, pollution and welfare. By focusing on intra-industry trade we consider trade between similar countries. We analyze both trade between developed countries, and trade between developing countries. In our model, final good producers pay an environmental tax on the total pollution emitted in their country. Therefore, final good producers determine the overall level of pollution by demanding ‘cleaner’ or ‘dirtier’ intermediate goods. To focus on intra-industry trade we consider only intermediate goods firms trade. We analyze three scenarios: closed economy; open economy with no impediments to trade; and open economy with transportation cost. Our main findings are: i. a developing country closed to trade faces lower final good output and higher total pollution and is thus worse off than a developed country; ii. countries are better off under trade than under autarky, regardless of their development level; and iii. an open economy with low transportation costs are better off than an open economy with no impediments to trade.     

Multiproject team assignments

We consider expected profit maximizing mechanisms for a principal who has to allocate a group of agents among a number of projects, assuming that the principal has incomplete information about each agent's ability type, and the agents follow the Bayes-Nash or the dominant strategy equilibrium behavior. We find that while expected profit maximizing mechanisms are similar to the optimal auction (Myerson, 1981), the incentive compatibility constraints are much more restrictive. Interestingly, these constraints are satisfied if each agent's characteristics change in a consistent manner not only with types, but also from project to project. Received: 30 April 1997 / Accepted: 22 December 1998     

Multivariate L1 mean

The center of a univariate data set {x ₁,…,x _n} can be defined as the point μ that minimizes the norm of the vector of distances y′=(|x ₁−μ|,…,|x _n−μ|). As the median and the mean are the minimizers of respectively the L ₁- and the L ₂-norm of y, they are two alternatives to describe the center of a univariate data set. The center μ of a multivariate data set {x ₁,…,x _n} can also be defined as minimizer of the norm of a vector of distances. In multivariate situations however, there are several kinds of distances. In this note, we consider the vector of L ₁-distances y′₁=(∥x ₁- μ∥₁,…,∥x _n- μ∥₁) and the vector of L ₂-distances y′₂=(∥x ₁- μ∥₂,…,∥x _n-μ∥₂). We define the L ₁-median and the L ₁-mean as the minimizers of respectively the L ₁- and the L ₂-norm of y ₁; and then the L ₂-median and the L ₂-mean as the minimizers of respectively the L ₁- and the L ₂-norm of y ₂. In doing so, we obtain four alternatives to describe the center of a multivariate data set. While three of them have been already investigated in the statistical literature, the L ₁-mean appears to be a new concept. Received January 1999     

The analysis of ranked data in blocked factorial experiments

A non-parametric method for the analysis of blocked factorial experiments, based on ranking within blocks, is proposed and shown to be equivalent to partitioning Friedman's test statistic into a set of contrasts reflecting polynomial components of the main effects and interaction. A slightly modified version of the procedure is suggested to partially overcome the problem of loss of power to detect one component when the model includes other components. This alternative procedure is shown to be equivalent to applying a standard normal theory analysis of variance to the ranks. The null distributions and power comparisons are investigated using simulation methods, and it is shown that the non-parametric methods are almost as powerful as the analysis of variance. Received: February 1999     

Is bootstrap really helpful in point process statistics?

There are some papers which describe the use of bootstrap techniques in point process statistics. The aim of the present paper is to show that the form in which bootstrap is used there is dubious. In case of variance estimation of pair correlation function estimators the used bootstrap techniques lead to results which can be obtained simpler without simulation; furthermore, they differ from the desired results. The problem to obtain confidence regions for the intensity function of inhomogeneous Poisson processes can be easily solved without bootstrap techniques. Received: June 1999     

Sales management control and job performance

A national firm's salespeoples' perceptions of their management control system were related to their performance and satisfaction. Salespeople who perceived job goal clarity, control over their work, and job rewards as being based upon performance were found to be relatively higher performers and better satisfied with their job.     

Strategyproof multiple assignment using quotas

The allocation of heterogeneous and indivisible objects is considered where there is no medium of exchange. We characterize the set of strategyproof, nonbossy, Pareto-optimal, and neutral social choice functions when preferences are monotonic and quantity-monotonic. The characterized sets of social choice functions are sequential; agents are assigned their favorite objects among the objects not given to others before them, subject to a quota. Received: 5 January 1999 / Accepted: 14 June 1999