Functional analysis of high-content high-throughput imaging data

High-content automated imaging platforms allow the multiplexing of several targets simultaneously to generate multi-parametric single-cell data sets over extended periods of time. Typically, standard simple measures such as mean value of all cells at every time point are calculated to summarize the temporal process, resulting in loss of time dynamics of the single cells. Multiple experiments are performed but observation time points are not necessarily identical, leading to difficulties when integrating summary measures from different experiments. We used functional data analysis to analyze continuous curve data, where the temporal process of a response variable for each single cell can be described using a smooth curve. This allows analyses to be performed on continuous functions, rather than on original discrete data points. Functional regression models were applied to determine common temporal characteristics of a set of single cell curves and random effects were employed in the models to explain variation between experiments. The aim of the multiplexing approach is to simultaneously analyze the effect of a large number of compounds in comparison to control to discriminate between their mode of action. Functional principal component analysis based on T-statistic curves for pairwise comparison to control was used to study time-dependent compound effects.     

A small but practically useful modification to the Hodrick–Prescott filtering: A note

The Hodrick–Prescott (HP) filtering is widely applied to decompose macroeconomic time series, such as real Gross Domestic Product, into cyclical and trend components. This paper presents a small but practically useful modification to this approach. The reason why this modified filtering is of practical use is that it provides not only identical trend estimates as the HP filtering but also extrapolations of the trend. We provide a proof based on a ridge regression representation of the modified HP filtering. This is mainly because it enhances our understanding of the approach.     

电力企业上市公司基本面综合评价

本文采用主成分分析的方法,以上海股市25家电力企业上市公司2004年中报公布的财务报告为基础,以95%的精度用2个新指标来代替原来的11个财务指标对这25家上市公司进行综合评价,同时在主成分分析的基础上对25家电力上市公司进行了综合评价和比较。     

香蕉假茎营养成分的分析

目的 :分析香蕉假茎的主要营养成分 ,以探讨香蕉假茎的开发利用价值 .方法 :取三种香蕉假茎的老茎与嫩茎部分进行水分、蛋白质、脂肪、碳水化合物、灰分和无机元素含量测定 .结果 :碳水化合物是构成香蕉假茎干物质的最主要成分 ,占香蕉假茎的 4 .50 %～7.6 1 % ,其中粗纤维占 3.2 0 %～ 4 .4 0 % ;香蕉假茎中无机元素含量丰富 ,尤其是K、Ca、Mg、P和S元素含量较高 .结论 :香蕉假茎含有丰富的蛋白质、碳水化合物和无机元素等营养物质 ,具有较高的开发价值     

关于高等学校依法治校的几点思考

在明确几个前提之后 ,阐释了理解高等学校依法治校应处理好的两对关系 ,即治校权与教师权、学生权的关系 ,治校权与法的关系 ;分析了高等学校依法治校的构成要素 ;并还在探索了高等学校依法治校与自由、民主、效率、公正、秩序等的关系后 ,指出高等学校实行依法治校不仅是现代高校管理的基本要求 ,也是一个重大的价值选择。     

科技期刊的综合评价方法研究——主成分分析法

文章首先简要介绍了期刊评价的理论基础和目的,通过对各种期刊评价方法的对比,分析了期刊评价中单指标的局限性和主观因素的影响。文章采用中国科技期刊引证报告数据,利用主成分分析法对科技期刊进行综合评价,并给出了相关的评价结果,最后指出主成分分析法应用中应注意的问题和内容。     

基于顾客满意度陷阱的市场细分方法研究

提出了基于顾客满意度陷阱的市场细分方法,企业可以根据该细分结果对不同满意程度的顾客采取不同的营销战略,将投向满意顾客的部分资源转向不满意顾客和非常满意顾客,能够更有效地提升顾客忠诚度,并拉动企业的业绩表现。以某个电视制造企业为例,采用了聚类分析、主成分回归分析、多重对应分析等统计分析方法,验证了顾客满意度陷阱的存在,同时表明顾客的人口统计特征与顾客满意作用于顾客忠诚的方式存在对应关系,从而佐证了方法的合理性。     

ADE-4: a multivariate analysis and graphical display software

We present ADE-4, a multivariate analysis and graphical display software. Multivariate analysis methods available in ADE-4 include usual one-table methods like principal component analysis and correspondence analysis, spatial data analysis methods (using a total variance decomposition into local and global components, analogous to Moran and Geary indices), discriminant analysis and within/between groups analyses, many linear regression methods including lowess and polynomial regression, multiple and PLS (partial least squares) regression and orthogonal regression (principal component regression), projection methods like principal component analysis on instrumental variables, canonical correspondence analysis and many other variants, coinertia analysis and the RLQ method, and several three-way table (k-table) analysis methods. Graphical display techniques include an automatic collection of elementary graphics corresponding to groups of rows or to columns in the data table, thus providing a very efficient way for automatic k-table graphics and geographical mapping options. A dynamic graphic module allows interactive operations like searching, zooming, selection of points, and display of data values on factor maps. The user interface is simple and homogeneous among all the programs; this contributes to making the use of ADE-4 very easy for non- specialists in statistics, data analysis or computer science.     

我国少数民族构成要素的因子分析

本文用总人口、自治地方本民族人口、自治地方少数民族人口、人均GDP、农业人口、识字人口、在校生、母语人、单语人、双语人人数等 10项指标作为民族的地区、经济、教育和语言构成要素 ,对这些要素在我国现有少数民族中的构成情况作了描述、相关和因子提取等统计分析 ,以说明目前我国少数民族构成的基本社会状况 ,以及这些要素对少数民族整体和个体的构成的作用或代表的信息量有多大。文章还依据已有的经验知识对统计分析结果作了相应的说明和解释。结论是 ,目前我国少数民族之间的区别特征主要在于经济发展水平、人口的教育水平、居住地区、使用语言等方面的社会差别 ;但是从发展趋势看 ,传统意义上的各民族构成要素的作用将逐渐减弱 ,民族间的差别将逐渐缩小     

粮食综合生产能力影响因素的系统分析及其政策建议

以系统科学视角从理论和实证角度将粮食综合生产能力分解为四个因子。通过主成分回归发现,水资源禀赋等自然生产力因子是影响粮食综合生产能力的基本因素;机械化率等技术生产力因子和耕作制度等管理生产力因子是主要促进因素;政策生产力因子影响不太显著,却是保障粮食综合生产能力的稳定因素。在目前生产条件下,稳定农业生产资料价格,改善农业基础条件,提高技术投入,选择良性生产模式,改革耕作制度,发展多熟制的间作套种,是今后提高粮食综合生产能力的主要方向。