Change-of-variance problem for linear processes with long memory

In this paper we investigate the asymptotic properties of the test statistics for detecting change-points in the variance of infinite moving average sequences with long memory. This research is partly supported by NSFC Grants and SRF for ROCS, SEM.     

试论性质命题主、谓项周延性的量词方法

性质命题主、谓项周延性“含糊”的问题如何解决,产生过表解法、图例法、与欧拉圈分析法等等.文章在诸多方法之外,提出了性质命题的量词方法,并阐述了量词方法的特征、规则及运用方式.     

Riemann积分与Lebesgue积分的联系

研究Riemann积分与Lebesgue积分的关系.证明了广义Riemann积分与Lebesgue积分、柯西主值积分与Lebesgue积分关系的若干结论.     

p-半单BCI-代数的导群列

引入了p-半单BCI-代数的导群和广义a-结合BCI-代数的导半群的概念,并给出了p-半单BCI-代数的一个导群列和广义a-结合BCI-代数的导半群列.     

Poverty statics and dynamics: does the accounting period matter?

Any public policy aimed at reducing the effects of deprivation should be aware of the consequences of the use of different income accounting periods on eligibility and subsequent policy evaluation. This study aims to throw some light on the relev-ance of choosing a specific accounting period for public policy evaluation in a European country, in contrast to the existing evidence for the United States. Our analysis indicates that there are some significant differences in the results on poverty when using different income accounting periods. Researchers and decision-makers using an annual income measure, whatever the economic and social welfare context, should be aware that the use of quarterly data instead of yearly data will lead to a significantly larger number of poor households and a lower level of inequality and mobility in the distribution.     

Modelling the effects of repellent chemicals on foraging bees

Summary.  Many pesticide sprays that are used for crop protection are harmful to honey-bees. It can therefore be beneficial to add to the spray chemical compounds that are repellent to bees, to discourage them from feeding on recently sprayed crops. Experiments were conducted using an artificial feeding station to assess the repellent effects of various compounds. In this system, bees arrive at the feeding station, choose between feeding dishes to which different chemicals have been added, feed for a variable period and then depart. The number of bees at each feeding dish is recorded at intervals of 1 min. We discuss the analysis of data from this type of experiment, based on a queuing theory model.     

Estimation of Polygons and Areas

Abstract.  In forestry the problem of estimating areas is central. This paper addresses area estimation through fitting of a polygon to observed coordinate data. Coordinates of corners and points along the sides of a simple closed polygon are measured with independent random errors. This paper focuses on procedures to adjust the coordinates for estimation of the polygon and its area. Different new techniques that consider different amounts of prior information are described and compared. The different techniques use restricted least squares, maximum likelihood and the expectation maximization algorithm. In a simulation study it is shown that the root mean square errors of the estimates are decreased when coordinates are adjusted before estimation. Minor further improvement is achieved by using prior information about the order and the distribution of the points along the sides of the polygon. This paper has its origin in forestry but there are also other applications.     

Conservative prior distributions for variance parameters in hierarchical models

Bayesian hierarchical models typically involve specifying prior distributions for one or more variance components. This is rather removed from the observed data, so specification based on expert knowledge can be difficult. While there are suggestions for “default” priors in the literature, often a conditionally conjugate inverse‐gamma specification is used, despite documented drawbacks of this choice. The authors suggest “conservative” prior distributions for variance components, which deliberately give more weight to smaller values. These are appropriate for investigators who are skeptical about the presence of variability in the second‐stage parameters (random effects) and want to particularly guard against inferring more structure than is really present. The suggested priors readily adapt to various hierarchical modelling settings, such as fitting smooth curves, modelling spatial variation and combining data from multiple sites.     

A hierarchical model for extreme wind speeds

Summary.  A typical extreme value analysis is often carried out on the basis of simplistic inferential procedures, though the data being analysed may be structurally complex. Here we develop a hierarchical model for hourly gust maximum wind speed data, which attempts to identify site and seasonal effects for the marginal densities of hourly maxima, as well as for the serial dependence at each location. A Gaussian model for the random effects exploits the meteorological structure in the data, enabling increased precision for inferences at individual sites and in individual seasons. The Bayesian framework that is adopted is also exploited to obtain predictive return level estimates at each site, which incorporate uncertainty due to model estimation, as well as the randomness that is inherent in the processes that are involved.     

Acceptance sampling based on truncated life tests for generalized Rayleigh distribution

This paper considers the problem of an acceptance sampling plan for a truncated life test when the lifetime follows the generalized Rayleigh distribution. For different acceptance numbers, confidence levels, and values of the ratio of the fixed experiment time to the specified mean life, the minimum sample sizes necessary to ensure the specified mean life are found. The operating characteristic values of the sampling plans and producer's risk are discussed. Some tables are presented and the use of the tables is illustrated by a numerical example.