Handbook for Applied Modeling: Non-Gaussian and Correlated Data

Jamie D Riggs (u. a.)

ISBN 10: 1316601056 / ISBN 13: 9781316601051

Verlag: Cambridge University Press, 2017

Beschreibung

Handbook for Applied Modeling: Non-Gaussian and Correlated Data | Jamie D Riggs (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2017 | Cambridge University Press | EAN 9781316601051 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Bestandsnummer des Verkäufers 109297855

Bibliografische Details

• Titel: Handbook for Applied Modeling: Non-Gaussian and Correlated Data
• Verlag: Cambridge University Press
• Erscheinungsjahr: 2017
• Sprache: Englisch
• ISBN-10: 1316601056
• ISBN-13: 9781316601051
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 258B x 179 H x 13 T Millimeter Breite: 258 mm, Höhe: 179 mm, Tiefe: 13 mm
• Gewicht: 481 Gramm
• Verkäuferkataloge:
  • Bücher

Über diesen Titel

Inhaltsangabe

This compact, entry-level Handbook equips applied practitioners to choose and use core models for real-world data - with R and SAS.

Über die Autorinnen und Autoren

Jamie D. Riggs is an adjunct lecturer in the Predictive Analytics program at Northwestern University, Illinois. She specializes in the statistical issues of solar system cratering processes, solar physics, and galactic dynamics, and has collaborated with researchers at the Los Alamos National Laboratory, New Mexico and the Southwest Research Institute, Texas. She has held technical and managerial positions at Sun Microsystems, Inc., National Oceanic and Atmospheric Administration, and the Boeing Company, where she applied advanced statistical designs and analyses to manufacturing and business problems. She is the Solar System and Planetary Sciences Section Head of the International Astrostatistics Association.

Trent L. Lalonde is Associate Professor of Applied Statistics at the University of Northern Colorado, and Director of the University's Research Consulting Lab. He has spent a number of years designing and teaching graduate courses covering statistical methods for students in diverse areas such as special education, psychological sciences, and public health. In addition, he has helped direct dissertations in these areas, and has consulted with numerous faculty on publications and funding proposals. He has received awards for both instruction and advising, and has Chaired the Applied Public Health Statistics section of the American Public Health Association.