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Hands-On Geospatial Analysis with R and QGIS

You're reading from   Hands-On Geospatial Analysis with R and QGIS A beginner's guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788991674
Length 354 pages
Edition 1st Edition
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Authors (2):
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Brad Hamson Brad Hamson
Author Profile Icon Brad Hamson
Brad Hamson
Shammunul Islam Shammunul Islam
Author Profile Icon Shammunul Islam
Shammunul Islam
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Table of Contents (12) Chapters Close

Preface 1. Setting Up R and QGIS Environments for Geospatial Tasks FREE CHAPTER 2. Fundamentals of GIS Using R and QGIS 3. Creating Geospatial Data 4. Working with Geospatial Data 5. Remote Sensing Using R and QGIS 6. Point Pattern Analysis 7. Spatial Analysis 8. GRASS, Graphical Modelers, and Web Mapping 9. Classification of Remote Sensing Images 10. Landslide Susceptibility Mapping 11. Other Books You May Enjoy

Generalized linear model

The observed variable might not always be amenable to the assumptions of normal distribution and, in those cases, using a linear model is not a good idea. Instead, we can use a GLM, which allows the observed variable to have an error distribution different to the normal distribution.

Modeling count data using Poisson GLM

Suppose we have the migration rates for each of the areas we have considered so far. This is the count data, and if it can be assumed that the migration rate is constant, we can use the Poisson model to get the probability of a specified rate of migration. In a Poisson model, the mean and variance are the same.

Using the glm() function, we can fit a different GLM model. Here we model...

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