Isbn: 9781108716789 - joint species distribution modelling: with applications in r (14 risultati)

Condizione: New.

Paperback or Softback. Condizione: New. Joint Species Distribution Modelling: With Applications in R. Book.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. pp. 371.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback. Condizione: Brand New. 372 pages. 8.75x5.75x0.75 inches. In Stock.

Paperback. Condizione: new. Paperback. Joint species distribution modelling (JSDM) is a fast-developing field and promises to revolutionise how data on ecological communities are analysed and interpreted. Written for both readers with a limited statistical background, and those with statistical expertise, this book provides a comprehensive account of JSDM. It enables readers to integrate data on species abundances, environmental covariates, species traits, phylogenetic relationships, and the spatio-temporal context in which the data have been acquired. Step-by-step coverage of the full technical detail of statistical methods is provided, as well as advice on interpreting results of statistical analyses in the broader context of modern community ecology theory. With the advantage of numerous example R-scripts, this is an ideal guide to help graduate students and researchers learn how to conduct and interpret statistical analyses in practice with the R-package HMSC-R, providing a fast starting point for applying joint species distribution modelling to their own data. Joint Species Distribution Modelling is for graduate students and researchers interested in analysing data on community ecology and placing their results in the context of modern ecological theory. With the help of example R-scripts, readers will learn how to conduct and interpret statistical analyses. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condizione: New. Print on Demand pp. 371.

Condizione: New. PRINT ON DEMAND pp. 371.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Paperback. Condizione: new. Paperback. Joint species distribution modelling (JSDM) is a fast-developing field and promises to revolutionise how data on ecological communities are analysed and interpreted. Written for both readers with a limited statistical background, and those with statistical expertise, this book provides a comprehensive account of JSDM. It enables readers to integrate data on species abundances, environmental covariates, species traits, phylogenetic relationships, and the spatio-temporal context in which the data have been acquired. Step-by-step coverage of the full technical detail of statistical methods is provided, as well as advice on interpreting results of statistical analyses in the broader context of modern community ecology theory. With the advantage of numerous example R-scripts, this is an ideal guide to help graduate students and researchers learn how to conduct and interpret statistical analyses in practice with the R-package HMSC-R, providing a fast starting point for applying joint species distribution modelling to their own data. Joint Species Distribution Modelling is for graduate students and researchers interested in analysing data on community ecology and placing their results in the context of modern ecological theory. With the help of example R-scripts, readers will learn how to conduct and interpret statistical analyses. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Joint Species Distribution Modelling is for graduate students and researchers interested in analysing data on community ecology and placing their results in the context of modern ecological theory. With the help of example R-scripts, readers will learn how .…