A Constrained Interval-Valued Linear Regression Model: A New Heteroscedasticity Estimation Method

Linear regression models for interval-valued data have been widely studied. Most literatures are to split an interval into two real numbers, i.e., the left- and right-endpoints or the center and radius of this interval, and fit two separate real-valued or two dimension linear regression models. This paper is focused on the bias-corrected and heteroscedasticity-adjusted modeling by imposing order constraint to the endpoints of the response interval and weighted linear least squares with estimated covariance matrix, based on a generalized linear model for interval-valued data. A three step estimation method is proposed. Theoretical conclusions and numerical evaluations show that the proposed estimator has higher efficiency than previous estimators.

     

两种耐寒性不同的小麦低温处理后ATPase同工酶的变化

正常温度条件下（２５±１℃）培养的冬小麦京农Ｓ５１００、临远７０６９和春小麦津春４号、津春９号幼苗叶片内均显示出６条ＡＴＰａｓｅ同工酶谱带，芽鞘内则为９－１０条，表明ＡＴＰａｓｅ同工酶不能反映出两种类型小麦在耐寒性上的差异。１－４℃低温处理１－４周后，冬小麦和春小麦幼苗叶片及芽鞘内ＡＴＰａｓｅ同工酶谱均有所减少，叶片中由６条减至１条（ＡＴＰａｓｅ５），芽鞘由９－１０条减至２条（ＡＴＰａｓｅ６，ＡＴＰａｓｅ７），将１－４℃低温处理１－４周后的小麦幼苗转入正常条件下再培养１周，使其幼苗生长恢复正常，检测叶片及芽鞘内的ＡＴＰａｓｅ同工酶，发现各自均基本恢复到低温处理前的水平。     

Estimation in Partially Observed Functional Linear Quantile Regression

Currently, working with partially observed functional data has attracted a greatly increasing attention, since there are many applications in which each functional curve may be observed only on a subset of a common domain, and the incompleteness makes most existing methods for functional data analysis ineffective. In this paper, motivated by the appealing characteristics of conditional quantile regression, the authors consider the functional linear quantile regression, assuming the explanatory f...     

低温胁迫下植物体内POD,COD,ATPase同工酶的变化

０～４℃低温对绿豆（武清绿豆）红豆（京农２号），黄豆（鲁豆７６０５）三种作物幼苗生长的抑制作用是明显的，这三种作物对低温处理的反应都很敏感，其中绿豆和红豆比黄豆更为敏感，绿豆，红豆，黄豆胚轴子ＰＯＤ，ＣＯＤ，ＡＴＰａｓｅ三种同工酶的变化表明，植物的生长受抑与ＰＯＤ，ＣＯＤ，ＡＴＰａｓｅ同工酶变化相关。     

基于改进PSO算法的岩石蠕变模型参数辨识

微粒群优化(PSO)算法是一类随机全局优化技术,具有收敛速度快、规则简单、易于实现的优点.针对岩石蠕变本构模型参数的辨识问题,本文利用FLAC软件自带的fish语言实现了改进PSO算法对本构模型参数的辨识.该方法从岩石本构模型参数的随机值出发,以蠕变过程中试件变形的实验值与计算值的误差大小作为适应度函数来评价参数的品质,利用改进PSO算法规则实现模型参数的进化,搜索出全局最优的模型参数值,从而实现了岩石蠕变本构模型参数的自适应辨识.利用该方法对页岩蠕变实验进行了仿真研究,实验结果表明:改进的PSO算法用于岩石蠕变模型的参数辨识是有效的.     

Semiparametric analysis of isotonic errors-in-variables regression models with randomly right censored response

This paper considers the estimation of a semiparametric isotonic regression model when the covariates are measured with additive errors and the response is randomly right censored by a censoring time. The authors show that the proposed estimator of the regression parameter is rootn consistent and asymptotically normal. The authors also show that the isotonic estimator of the functional component, at a fixed point, is cubic root-n consistent and converges in distribution to the slope at zero of the greatest convex minorant of the sum of a two-sided standard Brownian motion and the square of the time parameter. A simulation study is carried out to investigate the performance of the estimators proposed in this article.     

小麦F2代白粉病抗、感病特性RAPD标记的比较研究

用２０个随机引物,以抗白粉病（７９２０１－１１－７、临远７０６９）和感白粉病（中麦２号、郑８３１）的高产小麦品种为亲本,杂交获得的Ｆ２群体接种白粉病菌１５号小种,并进行ＤＮＡ随机扩增多态性（ＲＡＰＤ）分析．从中选育高产、抗病个体和研究抗感特性在分子水平上的差异．