Li J. Spatial Predictive Modelling with R 2022 torrent

Textbook in PDF format

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.
Data acquisition,data quality control, and spatial reference systems
Predictive variables and exploratory analysis
Model evaluation and validation
Mathematical spatial interpolation methods
Univariate geostatistical methods
Multivariate geostatistical methods
Modern statistical methods
Tree-based machine learning methods
Support vector machines
Hybrids of modern statistical methods with geostatistical methods
Hybrids of machine learning methods with geostatistical methods
Applications and comparisons of spatial predictive methods
Appendix