Titlebook: Applied Multidimensional Scaling; Ingwer Borg,Patrick J. F. Groenen,Patrick Mair Book 20131st edition The Author(s) 2013 Data analysis.MDS

方面

書目名稱Applied Multidimensional Scaling影響因子(影響力)




書目名稱Applied Multidimensional Scaling影響因子(影響力)學(xué)科排名




書目名稱Applied Multidimensional Scaling網(wǎng)絡(luò)公開度




書目名稱Applied Multidimensional Scaling網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Applied Multidimensional Scaling被引頻次




書目名稱Applied Multidimensional Scaling被引頻次學(xué)科排名




書目名稱Applied Multidimensional Scaling年度引用




書目名稱Applied Multidimensional Scaling年度引用學(xué)科排名




書目名稱Applied Multidimensional Scaling讀者反饋




書目名稱Applied Multidimensional Scaling讀者反饋學(xué)科排名

Camouflage

Book 20131st editionpresenting ways to enforce theoretical expectations on the MDS solution, and by discussing typical mistakes that MDS users tend to make.? The primary audience of this book are psychologists, social scientists, and market researchers. No particular background knowledge is required, beyond a basic knowledge of statistics.

哀求

Book 20131st editione two MDS programs, Proxscal (a module of SPSS) and Smacof (an R-package). The book is unique in its orientation on the applied researcher, whose primary interest is in using MDS as a tool to build substantive theories. This is done by emphasizing practical issues (such as evaluating model fit), by

創(chuàng)作

https://doi.org/10.1007/978-3-642-31848-1Data analysis; MDS; Multidimensional scaling; R package Smacof

Eulogy

Applied Multidimensional Scaling978-3-642-31848-1Series ISSN 2191-544X Series E-ISSN 2191-5458

amplitude

Entwicklung ostdeutscher Unternehmen applications, iterative methods are needed, because they admit many types of data and distances. They use a two-phase optimization algorithm, moving the points in MDS space in small steps while holding the data or their transforms fixed, and vice versa, until convergence is reached.

修正案

系列

https://doi.org/10.1007/978-3-663-20381-0The different purposes of MDS are explained: MDS as a psychological model of similarity judgments; MDS for visualizing proximity data; and MDS for testing structural hypotheses.

可卡

按等級(jí)

Beurteilung der Versuchsergebnisse,The data for MDS, proximities, are discussed. Proximities can be collected directly as judgments of similarity; proximities can be derived from data vectors; proximities may result from converting other indices; and co-occurrence data are yet another popular form of proximities.