On an adaptive version of the Metropolis–Hastings algorithm with independent proposal distribution

In this paper, we present a general formulation of an algorithm, the adaptive independent chain (AIC), that was introduced in a special context in Gåsemyr et al . [ Methodol. Comput. Appl. Probab. 3 (2001)]. The algorithm aims at producing samples from a specific target distribution Π, and is an adaptive, non-Markovian version of the Metropolis–Hastings independent chain. A certain parametric class of possible proposal distributions is fixed, and the parameters of the proposal distribution are updated periodically on the basis of the recent history of the chain, thereby obtaining proposals that get ever closer to Π. We show that under certain conditions, the algorithm produces an exact sample from Π in a finite number of iterations, and hence that it converges to Π. We also present another adaptive algorithm, the componentwise adaptive independent chain (CAIC), which may be an alternative in particular in high dimensions. The CAIC may be regarded as an adaptive approximation to the Gibbs sampler updating parametric approximations to the conditionals of Π.     

Optimal scaling of Metropolis algorithms: Heading toward general target distributions

The authors provide an overview of optimal scaling results for the Metropolis algorithm with Gaussian proposal distribution. They address in more depth the case of high‐dimensional target distributions formed of independent, but not identically distributed components. They attempt to give an intuitive explanation as to why the well‐known optimal acceptance rate of 0.234 is not always suitable. They show how to find the asymptotically optimal acceptance rate when needed, and they explain why it is sometimes necessary to turn to inhomogeneous proposal distributions. Their results are illustrated with a simple example.     

银行个人住房抵押贷款预警系统构想

在分析银行住房抵押贷款的各种风险因素的基础之上，提出模糊预警模型，给出预警结果。     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.     

我国城镇住房制度改革的历程与进展

我国城镇住房制度改革是国家整个经济体制改革的重要组成部分 ,二十多年来 ,这一改革取得了重要成就和积极进展 ,本文在对我国城镇住房制度改革的必要性、进程、目标和特点进行分析的基础上 ,概括了新的城镇住房制度的基本内涵     

台湾的金融改革及其启示

要本文在分析台湾实行金融改革动因的基础上，概述了台湾金融改革的内容，评述了台湾实行金融自由化的目的－建立区域金融中心的构想，并就这一改革给大陆带来的启示作出了思考。     

引导与干预:不同汇率制度中的央行行为分析

广义汇率目标区制包括介于浮动汇率制与固定汇率制之间的所有的汇率安排,中央银行外汇市场干预的不同,决定了汇率目标区制中类型的不同。在中央银行强有力的干预下,中心汇率和目标区公开是最具吸引力的一种目标区制,其根本特性就在于其汇率形成机制的内在稳定性,从而也是构建未来人民币汇率目标区制的较好选择。     

改进的OBS长度自适应门限组装算法

现有OBS长度自适应组装算法的突发数据长度门限的选择虽然随着业务流的变化而变化,克服了固定长度门限算法输出的突发数据的突发性,但仍然没有考虑业务流的自相似特性,因此不能有效降低输出突发数据的自相似程度和分组阻塞率。针对这一问题,该文提出了一种改进的OBS长度自适应门限组装算法,能根据到达的网络业务流的自相似特性自适应地调整长度门限值。仿真结果表明:在相同的调度算法下,更能降低业务流的自相似性,分组阻塞率降低一个数量级。     

四川省高等教育与区域经济发展关系研究

在对四川省经济发展和高等教育发展现状进行考查的基础上,从理论层次上论述二者发生关系的可能性,运用模糊统计方法得出四川省高等教育发展与经济发展呈强相关关系,并通过对四川省经济发展特点和劳动力人才市场供求状况的分析,指出四川省高等教育在适应经济发展过程中所存在的问题,进而提出针对性的发展对策,供四川省高等教育改革与发展决策参考。     

房价上涨对我国人口出生率的影响——基于省级面板数据的实证分析

人口数量和结构是影响我国可持续发展的关键因素,住房是人民群众安居乐业的刚需。近年来,我国人口出生率持续下降。为了实现经济高质量发展,缓解人口危机是当前亟待解决的重要问题。为了探究房价上涨对于我国人口出生率的影响,利用31个省级行政区2010—2019年的面板数据和加权最小二乘法进行实证分析,结果表明：房价上涨对人口出生率产生显著的负向影响,住房价格平均上涨1%将导致人口出生率下降0.13%~0.22%;房价上涨对人口出生率的影响在东部省份以挤出效应为主、在中西部省份是以财富效应为主。当前,通过遏制住房投资投机性需求、给予“刚需”人群购房贷款优惠、适量增加东部省份土地供给等手段,可以助力解决我国当前的人口问题。