Nonlinear mixed-effects models with scale mixture of skew-normal distributions

Aiming to avoid the sensitivity in the parameters estimation due to atypical observations or skewness, we develop asymmetric nonlinear regression models with mixed-effects, which provide alternatives to the use of normal distribution and other symmetric distributions. Nonlinear models with mixed-effects are explored in several areas of knowledge, especially when data are correlated, such as longitudinal data, repeated measures and multilevel data, in particular, for their flexibility in dealing with measures of areas such as economics and pharmacokinetics. The random components of the present model are assumed to follow distributions that belong to scale mixtures of skew-normal (SMSN) distribution family, that encompasses distributions with light and heavy tails, such as skew-normal, skew-Student-t, skew-contaminated normal and skew-slash, as well as symmetrical versions of these distributions. For the parameters estimation we obtain a numerical solution via the EM algorithm and its extensions, and the Newton-Raphson algorithm. An application with pharmacokinetic data shows the superiority of the proposed models, for which the skew-contaminated normal distribution has shown to be the most adequate distribution. A brief simulation study points to good properties of the parameter vector estimators obtained by the maximum likelihood method.     

Experimental designs for open pollination in polycross trials

A polycross is the pollination by natural hybridization of a group of genotypes, generally selected, grown in isolation from other compatible genotypes in such a way to promote random open pollination. A particular practical application of the polycross method occurs in the production of a synthetic variety resulting from cross-pollinated plants. Laying out these experiments in appropriate designs, known as polycross designs, would not only save experimental resources but also gather more information from the experiment. Different situations may arise in polycross nurseries where accordingly different polycross designs may be used. For situations in which some genotypes interfere in the growth or production of other genotypes, but have to be grown together, neighbour-restricted design is a better option. Furthermore, when the topography of the nursery is such that a known wind system in a certain direction may prevail, then designs balanced for neighbour effects of genotypes only in the direction of wind are appropriate which may help in saving experimental resources to a great extent. Also, when genotypes are planted in a small area without leaving much space between rows, designs balanced for neighbour effects from all possible eight directions are useful to have equal chance of pollinating and being pollinated by every other genotype. Here, polycross designs have been obtained to match above-mentioned three situations. SAS Macros have also been developed to generate these proposed designs.     

Inference Based on Order Statistics from the Generalized Pareto Distribution and Application

ABSTRACT

In this article, we derive exact explicit expressions for the single, double, triple, and quadruple moments of order statistics from the generalized Pareto distribution (GPD). Also, we obtain the best linear unbiased estimates of the location and scale parameters (BLUE's) of the GPD. We then use these results to determine the mean, variance, and coefficients of skewness and kurtosis of certain linear functions of order statistics. These are then utilized to develop approximate confidence intervals for the generalized Pareto parameters using Edgeworth approximation and compare them with those based on Monte Carlo simulations. To show the usefulness of our results, we also present a numerical example. Finally, we give an application to real data.     

Skewed type III generalized logistic distribution

Abstract

This paper develops a skewed extension of the type III generalized logistic distribution and presents the analytical equations for the computation of its moments, cumulative probabilities and quantile values. It is demonstrated through an example that the distribution provides an excellent fit to data characterized by skewness and excess kurtosis.     

基于交互式迭代算法的中国碳减排目标分配研究

众所周知,温室气体的大量排放会引起气候变化和全球变暖等环境问题。其中,二氧化碳作为影响最大的温室气体,主要产生于人类活动。应对气候变化需要来自于全球各个国家的共同行动与努力。作为经济高速发展的发展中国家,中国已于近几年成为世界最大的能耗国和碳排放国。为积极应对温室效应,中国政府计划采取强有力的政策措施,实现节能减排并逐步建立全国碳交易市场。为确保应对气候变化国家方案的切实贯彻实施,如何将全国碳减排目标在各省份间进行合理分配,至关重要。在效率分析的理论框架下,借助于方向性距离函数评价含有非期望产出（碳排放）的绩效表现,在此基础之上提出一种交互式迭代算法,合理有效地将全国碳减排总目标分摊为各省级目标。结果表明,受到地理环境、经济状况、产业结构等因素的共同影响,不同区域相应承担不同水平的减排任务。绝大部分沿海发达地区的省份和直辖市需要大幅减少碳排放量,而中西部经济区则期望减排比例较小。分摊结果不仅显示了方法的有效性和易操作性,也针对各典型区域如何推进可持续发展提供了启发性建议。     

同步分支线定向耦合器的分解设计方法

定向耦合器是四端口网络,直接设计十分困难。本文采用同步分支线定向耦合器的分解设计方法。文中首先分析了定向耦合器的传输特性,并依据奇、偶模激励原则将其分解为两个二端口网络,即两个带通滤波器。这样,同步分支线定向耦合器的设计即转化为带通滤波器的设计。     

布局装卸路径规划的研究

本文对布局装卸路径与形态操作的关系进行了深入的研究，进而提出了计算形态操作及装卸路径可行域的定理与算法，这些算法具有较广泛的适应范围。本文还根据八叉树这种数据结构的特点及一评价函数，提出了一种定向搜索算法来求解布局物体的装卸路径。走向搜索法可用较短的时间求得较佳的装卸路径，具有广泛的应用范围。