Tekijä: Wolfgang Karl Härdle; Marlene Müller; Stefan Sperlich; Axel Werwatz Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2004) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Wolfgang Karl Hardle; Nikolaus Hautsch; Ludger Overbeck Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2010) Saatavuus: Loppuunmyyty.
Tekijä: Wolfgang Karl Härdle; Vladimir Spokoiny; Vladimir Panov; Weining Wang Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2013) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Wolfgang Karl Härdle; Marlene Müller; Stefan Sperlich; Axel Werwatz Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2012) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Wolfgang Karl Hardle; Henry Horng-Shing Lu; Xiaotong Shen Kustantaja: Springer International Publishing AG (2018) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Wolfgang Karl Härdle; Vladimir Spokoiny; Vladimir Panov; Weining Wang Kustantaja: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2016) Saatavuus: Noin 17-20 arkipäivää
Springer Sivumäärä: 516 sivua Asu: Pehmeäkantinen kirja Painos: 3rd ed. 2012 Julkaisuvuosi: 2012, 05.01.2012 (lisätietoa) Kieli: Englanti
Most of the observable phenomena in the empirical sciences are of a multivariate nature. In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices. In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication. In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior. The underlying data structure of these and many other quantitative studies of applied sciences is multivariate. Focusing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data. The book surveys the basic principles of multivariate statistical data analysis and emphasizes both exploratory and inferential statistics. All chapters have exercises that highlight applications in different fields.
The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features
A new Chapter on Regression Models has been added
All numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.
