کتاب دانلود کتب لاتین علوم مهندسیآمار و احتمال
تجزیه و تحلیل فضایی با R - آمار، تجسم و روش های محاسباتی
تجزیه و تحلیل فضایی با R - آمار، تجسم و روش های محاسباتی

Spatial Analysis with R: Statistics, Visualization, and Computational Methods
نویسنده:
سال انتشار: 2021
تعداد صفحات: 355
زبان فایل: انگلیسی
فرمت فایل: pdf
حجم فایل: 11MB
رمز فایل: www.ketabdownload.com
قیمت: 250,000ريال

افزودن به سبد دانلود

Publisher: CRC Press

ISBN-10: 0367860856

ISBN-13: 978-0367860851

ASIN: B08GJ8XJYV

2nd Edition

In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.

New in the Second Edition:

Includes new practical exercises and worked-out examples using R

Presents a wide range of hands-on spatial analysis worktables and lab exercises

All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences

Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods

Explains big data, data management, and data mining

This second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.