Produktbild: Forest Analytics with R

Forest Analytics with R An Introduction

Aus der Reihe Use R!

Fr. 101.00

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.12.2010

Verlag

Springer Us

Seitenzahl

354

Maße (L/B/H)

23.7/15.9/2.2 cm

Gewicht

517 g

Auflage

2011

Sprache

Englisch

ISBN

978-1-4419-7761-8

Beschreibung

Rezension

From the reviews:

“The material presented in this text is more than sufficient for a dedicated module of an applied statistics course … . The authors develop, and demonstrate, solutions to common forestry data handling and analysis challenges … . Whilst much of the text may be regarded as standard for the topic, the last chapter addresses an area harvest strategy which is well worth reading on its own … . The text is well written, easy to read and I recommend it to anyone interested in biometrics.” (Carl M. O’Brien, International Statistical Review, Vol. 80 (1), 2012)

Zitat

From the reviews:"The material presented in this text is more than sufficient for a dedicated module of an applied statistics course ... . The authors develop, and demonstrate, solutions to common forestry data handling and analysis challenges ... . Whilst much of the text may be regarded as standard for the topic, the last chapter addresses an area harvest strategy which is well worth reading on its own ... . The text is well written, easy to read and I recommend it to anyone interested in biometrics." (Carl M. O'Brien, International Statistical Review, Vol. 80 (1), 2012)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.12.2010

Verlag

Springer Us

Seitenzahl

354

Maße (L/B/H)

23.7/15.9/2.2 cm

Gewicht

517 g

Auflage

2011

Sprache

Englisch

ISBN

978-1-4419-7761-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Forest Analytics with R
  • Introduction.- Forest data management.- Data analysis for common inventory methods.- Imputation and Interpolation.- Fitting dimensional distributions.- Linear and non-linear models.- Fitting linear hierarchical models.- Simulations.- Forest estate planning and optimization.