Forest Analytics with R: An Introduction (Use R!) - Taschenbuch

EAN (ISBN-13): 9781441977618
ISBN (ISBN-10): 1441977619
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2011
Herausgeber: Springer
339 Seiten
Gewicht: 0,517 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2007-01-17T10:46:18+01:00 (Berlin)
Detailseite zuletzt geändert am 2024-04-09T15:43:02+02:00 (Berlin)
ISBN/EAN: 9781441977618

ISBN - alternative Schreibweisen:
1-4419-7761-9, 978-1-4419-7761-8
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: hamann, andrews, robinson andrew
Titel des Buches: forest analytics with, fores

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Daten vom Verlag:

Autor/in: Andrew P. Robinson; Jeff D. Hamann
Titel: Use R! Forest Analytics with R - An Introduction
Verlag: Springer; Springer US
354 Seiten
Erscheinungsjahr: 2010-12-01
New York; NY; US
Gedruckt / Hergestellt in Niederlande.
Sprache: Englisch
74,89 € (DE)
76,99 € (AT)
83,00 CHF (CH)
POD
XIV, 354 p.

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; forest biometrics; forest informatics; forest management; forest statistics; natural resources management; Biostatistics; Forestry; Mathematical Applications in Environmental Science; Ökologie, Biosphäre; Forstwirtschaft und Waldbau: Praxis und Techniken; Umwelt; Angewandte Mathematik; EA

Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt a problem-driven approach, in which statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, which provide compelling examples of practical applications. The modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximum likelihood, fitting allometric functions using both linear and non-linear least-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and using forest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class in forest biometrics or applied statistics for natural resources management. The text assumes no programming background, some introductory statistics, and very basic applied mathematics. Andrew Robinson has been associate professor of forest mensuration and forest biometrics at the University of Idaho, and is currently senior lecturer in applied statistics at the University of Melbourne. He received his PhD in forestry from the University of Minnesota. Robinson is author of the popular and freely-available "icebreakeR" document. Jeff Hamann has been a software developer, forester, and financial analyst. He is currently a consultant specializing in forestry, operations research, and geographic information sciences. He received his PhD in forestry from Oregon State University. Both authors have presented numerous R workshops to forestry professionals and scientists, and others.
Use of real datasets provides detailed and realistic examples of forestry data handling and analysis Guided by forestry problems, not by statistical tools, so all material is driven by context instead of convenience Combines practical, down-to-earth forestry data analysis solutions with state-of-the-art statistical functionality