一种实用自适应PID控制器

本文介绍了一种实用自适应PID控制器,它是以MCS-51系列单片微机为核心,采用PID控制规律结合参数辨识的控制算法,实现了PID参数完全在线自动整定。该控制器适用于被控制对象未知或慢时变的场合,既可替代常规PID控制器,也可作为分布式系统的低级智能控制器。     

挠性转子动不平衡量的极大似然估计

本文提出利用模态参数识别技术进行挠性转子动平衡的方法。为了计及平衡过程中测试数据的误差,对动不平衡量采用极大似然估计。本文给出计算机模拟的几个实例以论证此种方法,并提出加速收敛的措施。计算结果表明此法效果是鸿意的。     

主流叶片气动有限元计算及试验研究

为了减少蒸汽透平高压级中存在的严重流动损失,本文提出一种新的由主、分流叶片组成的多分流喷嘴叶栅结构,文章着重讨论了主流叶片的气动设计原理,试验表明,这些原则是成功的。     

网上CAI

用好现代先进技术,开展网络建设,是教育信息化的第一步。本文基于这一思想,介绍了网上CAI的设计思路,描述了该系统的功能,以及实现系统所采用的技术措施。     

浙江流通产业演进动力研究

 本文分析了生产方式变革和消费需求升级及其矛盾对流通产业演进的影响,指出“生产方式引致的大量化”和“消费需求引致的大量化”在时间、空间、集散等方面发生的矛盾是推动流通不断演化与发展的动力。通过构建浙江流通演进的动力模型,实证分析“生产方式引致的大量化”和“消费需求的大量化”的相关系数为0.741,两者对浙江流通演进均具有正向促进作用,路径系数分别为0.68和0.42,前者的作用大于后者。     

On distribution-weighted partial least squares with diverging number of highly correlated predictors

Summary.  Because highly correlated data arise from many scientific fields, we investigate parameter estimation in a semiparametric regression model with diverging number of predictors that are highly correlated. For this, we first develop a distribution-weighted least squares estimator that can recover directions in the central subspace, then use the distribution-weighted least squares estimator as a seed vector and project it onto a Krylov space by partial least squares to avoid computing the inverse of the covariance of predictors. Thus, distrbution-weighted partial least squares can handle the cases with high dimensional and highly correlated predictors. Furthermore, we also suggest an iterative algorithm for obtaining a better initial value before implementing partial least squares. For theoretical investigation, we obtain strong consistency and asymptotic normality when the dimension p of predictors is of convergence rate O { n ^1/2/ log ( n )} and o ( n ^1/3) respectively where n is the sample size. When there are no other constraints on the covariance of predictors, the rates n ^1/2 and n ^1/3 are optimal. We also propose a Bayesian information criterion type of criterion to estimate the dimension of the Krylov space in the partial least squares procedure. Illustrative examples with a real data set and comprehensive simulations demonstrate that the method is robust to non-ellipticity and works well even in 'small n –large p ' problems.     

Parallel tempering for dynamic generalized linear models

ABSTRACT

Markov chain Monte Carlo (MCMC) methods can be used for statistical inference. The methods are time-consuming due to time-vary. To resolve these problems, parallel tempering (PT), as a parallel MCMC method, is tried, for dynamic generalized linear models (DGLMs), as well as the several optimal properties of our proposed method. In PT, two or more samples are drawn at the same time, and samples can exchange information with each other. We also present some simulations of the DGLMs in the case and provide two applications of Poisson-type DGLMs in financial research.     

Estimation on semi-functional linear errors-in-variables models

Abstract

Semi-functional linear regression models are important in practice. In this paper, their estimation is discussed when function-valued and real-valued random variables are all measured with additive error. By means of functional principal component analysis and kernel smoothing techniques, the estimators of the slope function and the non parametric component are obtained. To account for errors in variables, deconvolution is involved in the construction of a new class of kernel estimators. The convergence rates of the estimators of the unknown slope function and non parametric component are established under suitable norm and conditions. Simulation studies are conducted to illustrate the finite sample performance of our method.     

Testing the proportional odds model for interval-censored data

This paper discusses the goodness-of-fit test for the proportional odds model for K-sample interval-censored failure time data, which frequently occur in, for example, periodic follow-up survival studies. The proportional odds model has a feature that allows the ratio of two hazard functions to be monotonic and converge to one and provides an important tool for the modeling of survival data. To test the model, a procedure is proposed, which is a generalization of the method given in Dauxois and Kirmani [Dauxois JY, Kirmani SNUA (2003) Biometrika 90:913–922]. The asymptotic distribution of the procedure is established and its properties are evaluated by simulation studies     

平行数据模型中的异方差问题的处理

一、引言平行数据 (PanelData)指在时间序列上取多个截面 ,在这些截面上同时选取样本观测值所构成的样本数据。也就是把截面和时间序列数据融合在一起的数据。平行数据模型是一类线性经济模型 ,这些模型可以看作协变量的双向设计。如 :yit =∑pk =1xitkyk uit,i=1 ,2 ,L,N ,t =1 ,2 ,L,T其中N是横截面的个数 ,T是每一横截面上时间序列的长度 ,P是外生的或自变量的个数。近 2 0年来 ,平行数据模型在计量经济学理论方法方面取得了重要发展 ,新方法、新观点层出不穷。在经济分析中 ,平行数据模型起着只利用截面数据或只利用时间序列数据模…