A decision-theoretic approach to subset selection

The multiple decision problem of selecting a random non-empty subset of populations, out of k populations, that are close in some sense to the best population is considered in a decision-theoretic framework. Uniformly optimal procedures for non-negative semi-additive loss are derived. A class of likelihood-ratio type of procedures is shown to be admissible for monotone additive loss.     

大力发展广义民族学科推进西部地区小康进程--西部地区全面建设小康社会与民族新学科发展理论研讨会综述

本文对西部地区全面建设小康社会与民族新学科发展理论研讨会进行了综述.     

Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints

Quantitative risk assessment often begins with an estimate of the exposure or dose associated with a particular risk level from which exposure levels posing low risk to populations can be extrapolated. For continuous exposures, this value, the benchmark dose, is often defined by a specified increase (or decrease) from the median or mean response at no exposure. This method of calculating the benchmark dose does not take into account the response distribution and, consequently, cannot be interpreted based upon probability statements of the target population. We investigate quantile regression as an alternative to the use of the median or mean regression. By defining the dose–response quantile relationship and an impairment threshold, we specify a benchmark dose as the dose associated with a specified probability that the population will have a response equal to or more extreme than the specified impairment threshold. In addition, in an effort to minimize model uncertainty, we use Bayesian monotonic semiparametric regression to define the exposure–response quantile relationship, which gives the model flexibility to estimate the quantal dose–response function. We describe this methodology and apply it to both epidemiology and toxicology data.     

含单层吸收媒质的滤光片的全匹配诱导设计分析

本文从导纳匹配的观点出发,分析并介绍了一种确定全匹配状态下诱导滤光片的结构参数的方法,并提出了匹配波长处的透射率的解析表达式。     

关于一类新型的广义双拟变分不等式

本文在局部凸Hausdorff拓扑线性空间中引入了一类新型的广义双拟变分不等式,并研究了其解的存在性问题,本文的结果统一,改进和发展了有关变分不等式问题的许多最新结果。     

Testing retrospective hypotheses

This paper develops a conditional approach to testing hypotheses set up after viewing the data. For example, suppose X_i are estimates of location parameters θ_i, i = 1,…n. We show how to compute p-values for testing whether θ₁ is one of the three largest θ_i after observing that X₁ is one of the three largest X_i, or for testing whether θ₁ > θ₂ > … > θ_n after observing X₁ >X₂> … >X_n.     

Goodness‐of‐Fit Test for Monotone Functions

Abstract. In this article, we develop a test for the null hypothesis that a real‐valued function belongs to a given parametric set against the non‐parametric alternative that it is monotone, say decreasing. The method is described in a general model that covers the monotone density model, the monotone regression and the right‐censoring model with monotone hazard rate. The criterion for testing is an ‐distance between a Grenander‐type non‐parametric estimator and a parametric estimator computed under the null hypothesis. A normalized version of this distance is shown to have an asymptotic normal distribution under the null, whence a test can be developed. Moreover, a bootstrap procedure is shown to be consistent to calibrate the test.     

A class of neutral to the right priors induced by superposition of beta processes

A random distribution function on the positive real line which belongs to the class of neutral to the right priors is defined. It corresponds to the superposition of independent beta processes at the cumulative hazard level. The definition is constructive and starts with a discrete time process with random probability masses obtained from suitably defined products of independent beta random variables. The continuous time version is derived as the corresponding infinitesimal weak limit and is described in terms of completely random measures. It takes the interpretation of the survival distribution resulting from independent competing failure times. We discuss prior specification and illustrate posterior inference on a real data example.     

A “Reverse Order” Elementary Statistics Course

A family of coefficients for measuring monotone association is presented. These include measures of association of ordinal or interval variables such as gamma of Goodman and Kruskal, Somers's d_yx , Kendall's tau, or Spearman's rho as special cases. The article shows how a large number of measures of association can be put into a single general form. These coefficients are used as a basis for defining a variety of data analysis techniques.     

Multivariate Weibull and Pareto Distributions in Hilbert Space

Two general multivariate distributions in a real separable Hilbert space H are introduced in this article, one is multivariate Weibull distribution (denoted by GMW^H), the other is multivariate Pareto distribution (denoted by GMP^H). They are more general than the existing references. Some characterization theorems of the GMW^H and GMP^H via an intensively monotone operator are proved. The limiting behaviors and the interrelationship between the GMW and GMP in Euclidean space are also studied.