遗传算法中的逐级进化策略研究

基于反馈控制原理，通过对遗传算法寻优规律的分析，提出了一种逐级进化策略．计算结果表明，该方法可有效地改善遗传算法的寻优性能．     

Jaynes-Cummings模型中的Schrdinger Cat态

本文采用两个量子态的密度算符之间的距离来检验某些文献关于Jaynes-Cummings模型(JCM)中的Schrdinger Cat态的推论是否正确。     

The foundation of experimental design and observation

Summary Despite a very large literature on experimental design there are few papers which discuss the fundamentals, certainly compared to work on statistical inference. This paper tries to address some of the issues in a way which draws together some different fields such as search, group-testing and entropy based methods. An important philosophical distinction is between active and passive observation and examples introduce this subject. There are close connections with the approach tof Taguchi in engineering. This paper, the following discussion, the contribution of R. Fontana and the reply of H. P. Wynn are a result of the seminar hold in Rome, on the 6th October 1993. The Editorial Board wishes to thank Prof. Alessandra Giovagnoli for the organization of the meeting.     

Testing for structural changes in linear regressions with time-varying variance

Abstract

This article proposes a nonparametric test for structural changes in linear regression models that allows for serial correlation, autoregressive conditional heteroskedasticity and time-varying variance in error terms. The test requires no trimming of the boundary region near the end points of the sample period, and requires no prior information on the alternative, what it requires is the transformed OLS residuals under the null hypothesis. We show that the test has a limiting standard normal distribution under the null hypothesis, and is powerful against single break, multiple breaks and smooth structural changes. The Monte Carlo experiment is conducted to highlight the merits of the proposed test relative to other popular tests for structural changes.     

The entropic measure transform

We introduce the entropic measure transform (EMT) problem for a general process and prove the existence of a unique optimal measure characterizing the solution. The density process of the optimal measure is characterized using a semimartingale BSDE under general conditions. The EMT is used to reinterpret the conditional entropic risk-measure and to obtain a convenient formula for the conditional expectation of a process that admits an affine representation under a related measure. The EMT is then used to provide a new characterization of defaultable bond prices, forward prices and futures prices when a jump-diffusion drives the asset. The characterization of these pricing problems in terms of the EMT provides economic interpretations as maximizing the returns subject to a penalty for removing financial risk as expressed through the aggregate relative entropy. The EMT is shown to extend the optimal stochastic control characterization of default-free bond prices of Gombani & Runggaldier (2013). These methods are illustrated numerically with an example in the defaultable bond setting. The Canadian Journal of Statistics 48: 97–129; 2020 © 2020 Statistical Society of Canada     

城市福利水平结构性差异的测度及其对人口迁移的影响

文章在将城市福利分为户籍福利和非户籍福利的基础上,基于熵值法构建了城市福利水平评价指标体系,对全国288个地级以上城市的福利水平进行了测算。结果发现,户籍福利和非户籍福利都随城市规模的增大而增大,不同规模城市的福利差距很大,少数特大城市的非户籍福利水平高于其他城市户籍福利和非户籍福利的总和。城市福利的这种结构性差异对人口迁移产生了重要影响:农业转移人口宁愿到特大城市作非户籍居民,也不愿意到中小城市作户籍居民,特大城市即使严控户籍,也无法改变人口膨胀的态势。因此,特大城市人口疏解不应靠户籍管制,而应致力于缩小不同规模城市之间的福利水平差距。     

Maximum entropy estimation of income share function from generalized Gini index

Following Sir Anthony and Atkinson who started thinking about the insensitivity of the Gini index to income shares of the lower and the upper income groups, a generalization of the classical Gini index was introduced by Kakwani, Donaldson, Weymark and Yitzhaki which is sensitive to both high and low incomes. In this paper, the maximum entropy method is used to estimate the underlying true income share function based on the limited information of the generalized Gini index about the income shares of a population's percentiles. The income share function is estimated through maximizing both the Shannon entropy and the second-order entropy. In the end, through parametric bootstrap and analyzing a real dataset, the results are compared with the estimator of the share function, which is obtained based on the total information. In contrast to the classic Gini index, the derived share function based on the generalized Gini index provides more accurate approximations for income shares of the lower and the upper percentiles.     

Measures of discrimination for latent group-based trajectory models

In clinical research, patient care decisions are often easier to make if patients are classified into a manageable number of groups based on homogeneous risk patterns. Investigators can use latent group-based trajectory modeling to estimate the posterior probabilities that an individual will be classified into a particular group of risk patterns. Although this method is increasingly used in clinical research, there is currently no measure that can be used to determine whether an individual's group assignment has a high level of discrimination. In this study, we propose a discrimination index and provide confidence intervals of the probability of the assigned group for each individual. We also propose a modified form of entropy to measure discrimination. The two proposed measures were applied to assess the group assignments of the longitudinal patterns of conduct disorders among young adolescent girls.