Spatial Predictive Modelling with R
暫譯: 使用 R 進行空間預測建模
Li, Jin
- 出版商: CRC
- 出版日期: 2022-02-23
- 售價: $4,880
- 貴賓價: 9.5 折 $4,636
- 語言: 英文
- 頁數: 416
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367550547
- ISBN-13: 9780367550547
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相關分類:
Machine Learning
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相關主題
商品描述
Spatial predictive modeling (SPM) is an emerging discipline in applied sciences, playing a key role in the generation of spatial predictions in various disciplines. SPM refers to preparing relevant data, developing optimal predictive models based on point data, and then generating spatial predictions. This book aims to systematically introduce the entire process of SPM as a discipline. The process contains data acquisition, spatial predictive methods and variable selection, parameter optimization, accuracy assessment, and the generation and visualization of spatial predictions, where spatial predictive methods are from geostatistics, modern statistics, and machine learning.
The key features of this book are:
-Systematically introducing major components of SPM process.
-Novel hybrid methods (228 hybrids plus numerous variants) of modern statistical methods or machine learning methods with mathematical and/or univariate geostatistical methods.
-Novel predictive accuracy-based variable selection techniques for spatial predictive methods.
-Predictive accuracy-based parameter/model optimization.
-Reproducible examples for SPM of various data types in R.
This book provides guidelines, recommendations, and reproducible examples for developing optimal predictive models by considering various components and associated factors for quality-improved spatial predictions. It provides valuable tools for researchers, modelers, and university students not only in SPM field but also in other predictive modeling fields.
Dr Li has produced over 100 various publications in spatial predictive modelling, statistical computing, ecological and environmental modelling, and ecology, developed a number of hybrid methods for SPM, and published four R packages for variable selections as well as SPM.
商品描述(中文翻譯)
空間預測建模（Spatial Predictive Modeling, SPM）是一個新興的應用科學領域，在各個學科中扮演著生成空間預測的關鍵角色。SPM指的是準備相關數據、基於點數據開發最佳預測模型，然後生成空間預測。本書旨在系統性地介紹SPM作為一個學科的整個過程。該過程包括數據獲取、空間預測方法和變數選擇、參數優化、準確性評估，以及空間預測的生成和可視化，其中空間預測方法來自地質統計學、現代統計學和機器學習。
本書的主要特點包括：
- 系統性介紹SPM過程的主要組成部分。
- 現代統計方法或機器學習方法與數學和/或單變量地質統計方法的創新混合方法（228種混合方法及眾多變體）。
- 基於預測準確性的空間預測方法的變數選擇技術。
- 基於預測準確性的參數/模型優化。
- 在R中針對各種數據類型的SPM可重現示例。
本書提供了指導方針、建議和可重現的示例，以考慮各種組件和相關因素來開發最佳預測模型，以提高空間預測的質量。它為研究人員、建模者和大學學生提供了有價值的工具，不僅在SPM領域，也在其他預測建模領域。
李博士在空間預測建模、統計計算、生態和環境建模以及生態學方面發表了超過100篇各類出版物，開發了多種SPM的混合方法，並發布了四個用於變數選擇及SPM的R套件。
作者簡介
Dr Jin Li works at Data2action, Australia as a Founder. He has research experience in spatial predictive modelling, statistical computing, ecological and environmental modelling, and ecology. As a scientist, he worked in the Chinese Academy of Sciences, University of New England, CSIRO, and Geoscience Australia. He was an Associate Editor (Jul 2008-Dec 2015) and an editorial board member (Jan 2016-April 2020) of Acta Oecologica, and a Guest Academic Editor (Mar 2018) and an Academic Editor (May 2018-Apr 2020) of PLOS ONE. He has produced over 100 various publications, developed a number of hybrid methods for spatial predictive modeling, and published four R packages for variable selections and spatial predictive modelling.
For further information see https: //www.researchgate.net/profile/Jin-Li-74, https: //scholar.google.com/citations?user=Jeot53EAAAAJ&hl=en and https: //www.linkedin.com/in/jin-li-01421a68/.
作者簡介(中文翻譯)
金利博士在澳洲的Data2action擔任創辦人。他在空間預測建模、統計計算、生態與環境建模以及生態學方面擁有研究經驗。作為一名科學家，他曾在中國科學院、新英格蘭大學、澳洲科學與工業研究組織（CSIRO）以及澳洲地質科學局工作。他曾擔任《Acta Oecologica》的副編輯（2008年7月-2015年12月）及編輯委員會成員（2016年1月-2020年4月），並於2018年3月擔任《PLOS ONE》的客座學術編輯，及於2018年5月-2020年4月擔任學術編輯。他已發表超過100篇各類出版物，開發了多種混合方法以進行空間預測建模，並發佈了四個用於變數選擇和空間預測建模的R套件。
欲了解更多資訊，請參見 https://www.researchgate.net/profile/Jin-Li-74、https://scholar.google.com/citations?user=Jeot53EAAAAJ&hl=en 及 https://www.linkedin.com/in/jin-li-01421a68/。
