ADE-4: A multivariate analysis and graphical display software

被引:1385
作者
Thioulouse, J
Chessel, D
Doledec, S
Olivier, JM
机构
[1] UNIV LYON 1, LAB BIOMETRIE GENET & BIOL POPULAT, UMR CNRS 5558, F-69622 VILLEURBANNE, FRANCE
[2] UNIV LYON 1, LAB ECOL EAUX DOUCES & GRANDS FLEUVES, ESA CNRS 5023, F-69622 VILLEURBANNE, FRANCE
关键词
multivariate analysis; principal component analysis; correspondence analysis; instrumental variables; canonical correspondence analysis; partial least squares regression; coinertia analysis; graphics; multivariate graphics; interactive graphics; Macintosh; Hyper-Card; Windows; 95;
D O I
10.1023/A:1018513530268
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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 nonspecialists in statistics, data analysis or computer science.
引用
收藏
页码:75 / 83
页数:9
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