Contents

1. Getting Started

The first lessons below will introduce you to using R. These lessons are not focused on spatial data but on the basic operations of R you'll need for working with Spatial Data.

1. About R
2. Installing
3. Introduction To R and R Studio
4. Getting Started with R
5. Writing Scripts
6. Getting Help

2. Exploring Tabular Data

These lessons will show you how to create data in R and use R to explore data.

1. Generating Data
2. Linear Regression
3. Histograms
4. Testing Normality (QQPlots)
5. Testing for Covariance
6. 2D Plots
7. Files and Folders
8. 3D Plots

3. Control Flow

1. Boolean values, comparisons and "if" statements
2. Looping
3. Functions

4. Packages and Libraries

1. Packages and Libraries

5. Exploring Spatial Data

1. Spatial Data as Data Frames
2. Cluster Analysis
3. Reading Raster File Formats

6. Interpolation

1. Variograms & Kriging
2. Spatial Statistics (incomplete)

7. Correlation/Regression Models

1. Polynomial Regression
2. Generalized Additive Models (GAMs)
3. Categorical and Regression Trees (CART)
4. Habitat Suitability Models
5. Presence-Only Example with GAMs

8. Monte Carlo Methods

1. Introduction to Monte Carlo methods
2. Sub-Sampling Data for Cross-Validation
3. Noise Injection
4. Uncertainty in raster covariates
5. Creating Uncertianty Maps

9. Additional Information

1. Tips
2. Applied Spatial Analysis with R
3. R as a GIS

Acknowledgments

The material in this web site was drawn from a large number of web sites, blogs, articles, and books. Special thanks go to Jose Montero for contributing content.