Regression technique for analyzing electrocapillary curves

Based on the Nelder-Mead simplex technique, a program for the regression analysis of electrocapillary curves (ECC), which is aimed at determination of adsorption parameters of simple organic substances, is developed. This method is tested by the example of theoretically calculated ECC strictly corresponding to the model of two parallel capacitors. Then, the method is used for the regression analysis of ECC on a mercury electrode in 0.916 M NaF solutions with different additions of 5-chlor-1-penthanol. The adsorption parameters found for this system are in a good agreement with those obtained earlier by the regression analysis of differential capacitance curves.Translated from Elektrokhimiya, Vol. 41, No. 3, 2005, pp. 285–290.Original Russian Text Copyright © 2005 by Damaskin, Safonov.     

催化动力学光度法同时测定痕量铅和镉

在十六烷基三甲基溴化铵（CTAB）存在下，痕量的Pb(Ⅱ）和Cd(Ⅱ）在硼酸－氯化钾－氢氧化钠缓冲体系中，能同时催化过硫酸铵氧化焦锫酚红（PR）而发生褪色指示反应，通过研究该反应的最佳反应条件以及将多元线性回归（MIR）用于数据处理，建立了同时测定铅和镉的新方法，方法已用于废水及铜混中铅和镉的同时测定。     

氨基酸结构描述子矢量VHSE及其在肽QSAR中的应用

从20种天然氨基酸的50个物化性质出发，按照疏水、立体和电性特征将其分类后分别进行主成分分析，并将产生的得分矢量即VHSE(principal component score vector of hydrophilicity,steric，and electronic properties)作为氨基酸结构描述子用于肽的定量构效关系研究。与已有方法相比，VHSE描述子具有物化意义明确、结果更易解释等特点。应用该描述子并结合逐步回归变量筛选和偏最小二乘建模方法，在对苦味二肽和血管舒缓激肽促进剂等体系的定量构效关系研究中，均取得了优于已有文献的结果。     

一种半参数ROC曲面估计方法

ROC曲面是诊断医学统计学里评估有多类诊断结果的诊断测试方法准确性的一个重要工具,也是近年来的一个研究热点.本文提出一种半参数的ROC曲面估计方法.该方法可以借助于许多统计软件里的逻辑斯蒂回归程序进行计算,所以它的实施较为方便.相关统计模拟显示,本文提出的方法与传统的非参数方法相比,有效性得到了显著提高.而与参数方法相比,当参数模型假设是正确时仍比参数方法有略高的有效性；而当参数模型假设不正确时,本文提出的半参数方法明显优于参数方法.     

Solving bilinear tensor least squares problems and application to Hammerstein identification

Bilinear tensor least squares problems occur in applications such as Hammerstein system identification and social network analysis. A linearly constrained problem of medium size is considered, and nonlinear least squares solvers of Gauss–Newton‐type are applied to numerically solve it. The problem is separable, and the variable projection method can be used. Perturbation theory is presented and used to motivate the choice of constraint. Numerical experiments with Hammerstein models and random tensors are performed, comparing the different methods and showing that a variable projection method performs best.     

Fast and efficient nested simulation for large variable annuity portfolios: A surrogate modeling approach

The nested-simulation is commonly used for calculating the predictive distribution of the total variable annuity (VA) liabilities of large VA portfolios. Due to the large numbers of policies, inner-loops and outer-loops, running the nested-simulation for a large VA portfolio is extremely time consuming and often prohibitive. In this paper, the use of surrogate models is incorporated into the nested-simulation algorithm so that the relationship between the inputs and the outputs of a simulation model is approximated by various statistical models. As a result, the nested-simulation algorithm can be run with much smaller numbers of different inputs. Specifically, a spline regression model is used to reduce the number of outer-loops and a model-assisted finite population estimation framework is adapted to reduce the number of policies in use for the nested-simulation. From simulation studies, our proposed algorithm is able to accurately approximate the predictive distribution of the total VA liability at a significantly reduced running time.     

基于ANP-SVR的高校新专业设置优化分析

随着新专业的设置问题越来越多地成为各个高校普遍面对的发展问题,人们逐渐意识到决策过程中的滞后性、盲目性、片面性问题给专业设置工作乃至于该专业的生命力和竞争力带来的负面影响.运用ANP-SVR算法深入分析了高校新专业设置过程中的主要问题及其内部包含的各种因素,利用10个专业进行建模分析,并利用SVR,算法对3个拟建专业进行回归分析,得到了理想结果.方法将主观决策数字化,为高校的决策者提供了一种解决问题的新方法.     

Use of Chemometrics: Principal Component Analysis (PCA) and Principal Component Regression (PCR) for the Authentication of Orange Juice

ABSTRACT

Principal Component Analysis (PCA) was applied to a set of physico-chemical variables obtained from 41 samples of summer orange juice, in order to reduce the number of variables. Working with the covariance matrix, three components (which explained 98.27% of the variance) were taken. With the correlation matrix, four components which explained: 85.65% of the variance were taken. With the scores corresponding to both matrixes a principal component regression (PCR) was carried out against the dependent variable of Brix grades, so as to obtain two statistical models that would allow the detection of adulterations in pure orange juice, based on dilution and later masking by the addition of sugar. The models were tested with simulated dilutions of 41 samples of juice, to assess the effectiveness of each for the detection of adulterations. Both models turned out to be equally effective, detecting adulterations starting from about 15 % of dilution.     

人口老龄化与区域产业结构——基于分位数回归的实证研究

基于2005-2016年的省级面板数据,运用分位数回归实证分析了人口老龄化背景下,产业结构优化升级的影响因素.结果表明:全部样本的老年抚养比对产业结构优化升级的阻碍作用十分明显,东部对产业结构的影响不显著,中部的阻碍作用与全国趋势相反,西部的阻碍作用与全国趋势相同,具有明显的区域差异性;全部样本和东中西部的人均GDP都是正向推动产业结构合理化和高度化;全部样本和西部的政府行为对产业结构调整的抑制作用在增强,而东中部对产业结构调整的促进作用在增强;全部样本和东部的创新效率对产业结构调整有不断增强地推动作用,中部对产业结构调整的促进作用在减弱,而西部对产业结构调整的阻碍作用在增强.     

Bias analysis for misclassification in a multicategorical exposure in a logistic regression model

We derive the expressions of asymptotic biases when ignoring the misclassification in a multicategory exposure. For a model with a misclassified exposure variable only, we provide a general conclusion on the direction of the biases under nondifferential misclassification assumption. To better understand the bias formulas, we use a numerical example.