wilbert.rspatial1

---
title: "Wilbert Rspatial Notebook"
output:
  pdf_document: default
  html_document:
    df_print: paged
---

This is an [R Markdown](http://rmarkdown.rstudio.com) Notebook. When you execute code within the notebook, the results appear beneath the code. 

Add a new chunk by clicking the *Insert Chunk* button on the toolbar or by pressing *Ctrl+Alt+I*.

When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the *Preview* button or press *Ctrl+Shift+K* to preview the HTML file).

The preview shows you a rendered HTML copy of the contents of the editor. Consequently, unlike *Knit*, *Preview* does not run any R code chunks. Instead, the output of the chunk when it was last run in the editor is displayed.
#################################################################################################################################################################

Book: Applied Spatial Data Analysis with R, Roger S. Bivand, Edzer J. Pebesma, Virgilio Gómez-Rubio
Book URL: http://gis.humboldt.edu/OLM/r/Spatial%20Analysis%20With%20R.pdf

Additional, more in-depth books: 
https://www.amazon.com/Statistical-Spatio-Temporal-Monographs-Statistics-Probability/dp/1466560231/ref=sr_1_3?ie=UTF8&qid=1532636251&sr=8-3&keywords=diggle%2C+statistics
https://www.amazon.com/Handbook-Spatial-Statistics-Handbooks-Statistical-ebook/dp/B008GXJOXC/ref=sr_1_2?ie=UTF8&qid=1532636251&sr=8-2&keywords=diggle%2C+statistics

Good R-based tutorial on spatial analysis (without musch stats background): http://www.rspatial.org/index.html

GitHub repository: wgvanpanhuis/rspatial: https://github.com/wgvanpanhuis/rspatial.git
Steps in RStudio to add the Git repository:
- File -> New Project -> From version control repository -> Git -> copy Git repo URL and assign a folder on your computer to copy the repository
- The local repository folder is the working directory for the notebook

Steps to create an R Notebook:
- File -> New File -> R Notebook -> save as your name.Rmd, if problems, install required packages until it works

Install packages for Spatial Data Analysis: "ctv"
library(ctv)
install.views("Spatial") ## This will install any packages needed to do texamples for the book, OK if some don't work ##

```{r}
class(cars)
```
```{r}
summary(cars)
```
```{r}
str(cars)
```
```{r}
plot(cars$dist, cars$speed)
```

Stop at 2.3: Spatial Objects

```{r}
library(sp)
getClass("Spatial")
```

```{r}
m <- matrix(c(0,0,1,1), ncol = 2, dimnames = list(NULL, c("min", "max")))
crs <- CRS(projargs = as.character(NA))
crs
S <- Spatial(bbox = m, proj4string = crs)
S

```


```{r}
save.image("~/rspatial")
```

```{r}
load()
```