Statistical Methods for Spatial Data Analysis - Info and Reading Options
Texts in Statistical Science
By Oliver Schabenberger and Carol A. Gotway
"Statistical Methods for Spatial Data Analysis" was published by Taylor & Francis Group in 2023, the book is classified in Spatial analysis (Statistics) genre and the language of the book is English.
“Statistical Methods for Spatial Data Analysis” Metadata:
- Title: ➤ Statistical Methods for Spatial Data Analysis
- Authors: Oliver SchabenbergerCarol A. Gotway
- Language: English
- Is Family Friendly: Yes - No Mature Content
- Publisher: Taylor & Francis Group
- Publish Date: 2023
- Genres: Spatial analysis (Statistics)
“Statistical Methods for Spatial Data Analysis” Subjects and Themes:
- Subjects: ➤ Spatial analysis (Statistics) - Probability & statistics - Probability & Statistics - General - Computers - Mathematics - Computer Books: General - Biostatistics - Mathematics / Statistics - Information Technology - Spatial analysis (statistics) - Analyse spatiale (Statistique) - Spatial analysis - SCIENCE - Research & Methodology - Datenanalyse - Raumdaten - Statistische Analyse - Räumliche Statistik - Qa278.2 .s32 2005 - 001.4/22
Edition Specifications:
- Pagination: 506
Edition Identifiers:
- Google Books ID: GsKPzwEACAAJ
- The Open Library ID: OL46071042M - OL8948439W
- ISBN-13: 9781032477916
- ISBN-10: 1032477911
- All ISBNs: 9781032477916 - 1032477911
AI-generated Review of “Statistical Methods for Spatial Data Analysis”:
Snippets and Summary:
Statistical Methods for Spatial Data Analysis is a comprehensive treatment of statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain.
"Statistical Methods for Spatial Data Analysis" Description:
Google Books:
Statistical Methods for Spatial Data Analysis is a comprehensive treatment of statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. The authors deliver an outstanding treatment of semivariogram estimation and modeling, spatial analysis in the s
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