Isbn: 9781441977618 - forest analytics with r: an introduction (use r!) (21 resultados)

Soft cover. Condición: Very Good. No Jacket. Very Good copy. (see picture) 339 pages including index. All clean and tight.Bottom of the pages has had light moisture but does nor effect the pages working at all.

guter Zustand. Gewicht in Gramm: 550.

Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Condición: Very Good. 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.…

Paperback. Condición: Very Good. 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.…

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Condición: New.

Paperback. Condición: New. 2011 ed. This book presents techniques that are relevant to solving operational foresty problems including sampling, spatial analysis, inventory analysis, estimation of future forest conditions and basic methods for common optimization problems. The goal is to provide forest biometrics scientists and students with a demonstration of how R can be used efficiently to solve common forest biometrical problems.…

Condición: New.

PF. Condición: New.

Condición: New. In English.

Condición: New. pp. 356.

Condición: New. pp. 356 Illus.

Condición: New.

Paperback. Condición: New. 2011 ed. This book presents techniques that are relevant to solving operational foresty problems including sampling, spatial analysis, inventory analysis, estimation of future forest conditions and basic methods for common optimization problems. The goal is to provide forest biometrics scientists and students with a demonstration of how R can be used efficiently to solve common forest biometrical problems.…

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Condición: gut. Forest Analysis with R In englischer Sprache. pages.

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