你好! Shipping to Taiwan with premium packaging for just NT$300 

Ship to
Taiwan
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Entropy Measures for Environmental Data: Description, Sampling and Inference for Data with Dependence Structures
Type
Physical Book
Author
Publisher
Language
English
Pages
212
Format
Hardcover
ISBN13
9789819725458
Categories

Entropy Measures for Environmental Data: Description, Sampling and Inference for Data with Dependence Structures

Daniela Cocchi (Author) · Linda Altieri (Author) · Springer · Hardcover

Entropy Measures for Environmental Data: Description, Sampling and Inference for Data with Dependence Structures - Altieri, Linda ; Cocchi, Daniela

Cheaper New Book Imported to Taiwan
Delivery: 25 Sep - 08 Oct Shipping: 16 to 20 business days.
NT$ 5,078
Faster New Book Imported to Taiwan
Delivery: 21 Sep - 30 Sep Shipping: 12 to 14 business days.
NT$ 5,418
NT$ 5,078

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Entropy Measures for Environmental Data: Description, Sampling and Inference for Data with Dependence Structures"

This book shows how to successfully adapt entropy measures to the complexity of environmental data. It also provides a unified framework that covers all main entropy and spatial entropy measures in the literature, with suggestions for their potential use in the analysis of environmental data such as biodiversity, land use and other phenomena occurring over space or time, or both. First, recent literature reviews about including spatial information in traditional entropy measures are presented, highlighting the advantages and disadvantages of past approaches and the difference in interpretation of their proposals. A consistent notation applicable to all approaches is introduced, and the authors' own proposal is presented. Second, the use of entropy in spatial sampling is focused on, and a method with an outstanding performance when data show a negative or complex spatial correlation is proposed. The last part of the book covers estimating entropy and proposes a model-based approach that differs from all existing estimators, working with data presenting any departure from independence: presence of covariates, temporal or spatial correlation, or both. The theoretical parts are supported by environmental examples covering point data about biodiversity and lattice data about land use. Moreover, a practical section is provided for all parts of the book; in particular, the R package SpatEntropy covers not only the authors' novel proposals, but also all the main entropy and spatial entropy indices available in the literature. R codes are supplemented to reproduce all the examples. This book is a valuable resource for students and researchers in applied sciences where the use of entropy measures is of interest and where data present dependence on space, time or covariates, such as geography, ecology, biology and landscape analysis.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Hardcover.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews