Asymptotic Equivalence of Probabilistic Serial and Random Priority Mechanisms

The random priority (random serial dictatorship) mechanism is a common method for assigning objects. The mechanism is easy to implement and strategy‐proof. However, this mechanism is inefficient, because all agents may be made better off by another mechanism that increases their chances of obtaining more preferred objects. This form of inefficiency is eliminated by a mechanism called probabilistic serial, but this mechanism is not strategy‐proof. Thus, which mechanism to employ in practical applications is an open question. We show that these mechanisms become equivalent when the market becomes large. More specifically, given a set of object types, the random assignments in these mechanisms converge to each other as the number of copies of each object type approaches infinity. Thus, the inefficiency of the random priority mechanism becomes small in large markets. Our result gives some rationale for the common use of the random priority mechanism in practical problems such as student placement in public schools.     

Absolute error criteria for bandwidth selection in density estimation from censored data

In Kernel density estimation, a criticism of bandwidth selection techniques which minimize squared error expressions is that they perform poorly when estimating tails of probability density functions. Techniques minimizing absolute error expressions are thought to result in more uniform performance and be potentially superior. An asympotic mean absolute error expression for nonparametric kernel density estimators from right-censored data is developed here. This expression is used to obtain local and global bandwidths that are optimal in the sense that they minimize asymptotic mean absolute error and integrated asymptotic mean absolute error, respectively. These estimators are illustrated fro eight data sets from known distributions. Computer simulation results are discussed, comparing the estimation methods with squared-error-based bandwidth selection for right-censored data.     

Random balanced resampling: A new method for estimating variance components in unbalanced designs

Variance components in factorial designs with balanced data are commonly estimated by equating mean squares to expected mean squares. For unbalanced data, the usual extensions of this approach are the Henderson methods, which require formulas that are rather involved. Alternatively, maximum likelihood estimation based on normality has been proposed. Although the algorithm for maximum likelihood is computationally complex, programs exist in some statistical packages. This article introduces a simpler method, that of creating a balanced data set by resampling from the original one. Revised formulas for expected mean squares are presented for the two-way case; they are easily generalized to larger factorial designs. The results of a number of simulation studies indicate that, in certain types of designs, the proposed method has performance advantages over both the Henderson Method I and maximum likelihood estimators.     

Generating pseudo-random variables from mixture models by exemplary sampling

Generating samples from a two-stage distribution is an important part of the study of mixture models. These samples are used to examine estimation procedures, and other properties of the mixture model. In this paper we present an exemplary sampling method for generating data from the mixed distribution. This method uses the order statistic spacings of the mixing distribution and random sampling from the distribution conditional on the mixing variable to produce samples from the mixed distribution. We show that this exemplary procedure often produces data with an empirical distribution function closer to the mixed distribution than the Method of Composition. We illustrate the method with an example.     

Moderate deviations for the random weighted sums of WUOD random variables with consistently varying tails

Abstract

In this paper, we investigate the moderate deviations for random weighted sums of widely upper orthant dependent (WUOD) random variables with consistently varying tails, which are not necessarily identically distributed. In the end, we obtain the asymptotic relations for random weighted sums of random variables.     

Degradation modeling based on gamma process models with random effects

The random effects in a gamma process are introduced in terms of its scale parameter. However, the scale parameter affects both its mean and variance. Hence, the variation of the degradation rates and the within degradation increments are expected to be large. For some products, the random effects affect just the rate or just the volatility of the process. Thus, two modifications of the parameters' structure of the gamma process are proposed. One implies that the random effects affect just the volatility and the second just the rate. A Bayesian estimation approach is provided and implemented in two case studies.     

Inverse Gaussian process models for bivariate degradation analysis: A Bayesian perspective

This article conducts a Bayesian analysis for bivariate degradation models based on the inverse Gaussian (IG) process. Assume that a product has two quality characteristics (QCs) and each of the QCs is governed by an IG process. The dependence of the QCs is described by a copula function. A bivariate simple IG process model and three bivariate IG process models with random effects are investigated by using Bayesian method. In addition, a simulation example is given to illustrate the effectiveness of the proposed methods. Finally, an example about heavy machine tools is presented to validate the proposed models.     

甘肃退耕还林还草中的生物多样性和生物入侵问题

本文论述退耕还林还草问题时 ,结合甘肃植被生境和物种多样性的具体特点 ,及多样性退化濒危丧失的情况 ,提出以下意见因地制宜恢复和重建林草植被 ;按生境种植适宜的树和草 ;突出三大流域和六大植物区域的重点林草 ;培育、引进和筛选丰产和高 WU E相结合的植被 ;防止生物入侵 ;保护和改善生态环境和生物多样性。     

RANDOM PATHS ORIGINATING WITHIN A CONVEX REGION AND TERMINATING ON ITS SURFACE

A ray is defined as a straight line originating within an arbitrary convex body K in n -dimensional Euclidean space and terminating on the surface of K. The distributions of ray length are derived for three types of randomness. The results are expressed as functions of the overlap volume and overlap surface content of K with its translated self.     

The Paradoxes of Modernity: Scientific Advances,Environmental Problems,and Risks to the Social Fabric?

Recent reviews have contrasted U.S. sociologists' empirical work on technological risks with the theoretical risk work of Giddens and Beck, but the reality is more complex. Most U.S. sociologists are less likely than Giddens or Beck to see risks as transcending socioeconomic and other divisions, but the United States–based work tends to interpret the trustworthiness of scientific–technical expertise in ways that lie between the arguments of Beck and Giddens. An examination of early nuclear technologies indicates that the United States–based perspectives provide a better fit, for theoretical as well as empirical reasons. The development of nuclear technologies was mixed, rather than high or low, in its competence and trustworthiness, and it created social and environmental risks that did not so much transcend social divisions as to reinforce them.