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Pakillo / simulate.gamm.R
Created Mar 3, 2017 — forked from gavinsimpson/simulate.gamm.R
S3 method for simulate() for "gamm" objects from package mgcv
View simulate.gamm.R
`simulate.gamm` <- function(object, nsim = 1, seed = NULL, newdata,
freq = FALSE, unconditional = FALSE, ...) {
if (!exists(".Random.seed", envir = .GlobalEnv, inherits = FALSE))
if (is.null(seed))
RNGstate <- get(".Random.seed", envir = .GlobalEnv)
else {
R.seed <- get(".Random.seed", envir = .GlobalEnv)
RNGstate <- structure(seed, kind = as.list(RNGkind()))
Pakillo / ShinyPerspectivePlot.R
Created Dec 19, 2016 — forked from leeper/ShinyPerspectivePlot.R
Shiny App for 3D Interaction plots
View ShinyPerspectivePlot.R
ui <- shinyUI(pageWithSidebar(
titlePanel("", "3D Perspective Plot for Interaction Effects"),
Pakillo / beamer_two_col.Rmd
Created Nov 7, 2016 — forked from jhollist/beamer_two_col.Rmd
This .Rmd shows how to use two (or more) columns in a Beamer Presentation from RStudio
View beamer_two_col.Rmd
title: "Untitled"
author: "Jeff W. Hollister"
date: "2/2/2016"
output: beamer_presentation
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
Pakillo /
Created Jan 11, 2016 — forked from jesperronn/
Convert a Word Document into MD

Converting a Word Document to Markdown in One Move

The Problem

A lot of important government documents are created and saved in Microsoft Word (*.docx). But Microsoft Word is a proprietary format, and it's not really useful for presenting documents on the web. So, I wanted to find a way to convert a .docx file into markdown.

Installing Pandoc

On a mac you can use homebrew by running the command brew install pandoc.

The Solution

Pakillo / tables.Rmd
Created Sep 30, 2015 — forked from benmarwick/tables.Rmd
Methods for tables with rmarkdown
View tables.Rmd
title: "A few methods for making tables in rmarkdown"
output: html_document
Packages that have appeared since my original look into this, and seem great:
View base_r_plotting_tutorial_koontz_d-rug.r
### Title: Back to basics: High quality plots using base R graphics
### An interactive tutorial for the Davis R Users Group meeting on April 24, 2015
### Date created: 20150418
### Last updated: 20150423
### Author: Michael Koontz
### Email:
### Twitter: @michaeljkoontz
View iwanthue.R
swatch <- function(x) {
# x: a vector of colours (hex, numeric, or string)
par(mai=c(0.2, max(strwidth(x, "inch") + 0.4, na.rm = TRUE), 0.2, 0.4))
barplot(rep(1, length(x)), col=rev(x), space = 0.1, axes=FALSE,
names.arg=rev(x), cex.names=0.8, horiz=T, las=1)
# Example:
# swatch(colours()[1:10])
# swatch(iwanthue(5))
View gdal_project.R
## Function to use GDAL to project coordinate reference system
# See for additional details
# `resampling` can be 'near' (nearest neighbour), 'bilinear', 'cubic', or
# 'lanczos' (Lanczos windowed sinc resampling).
# `extent` should be a bbox object or a vector of c(xmin, ymin, xmax, ymax)
# `of` is the output format (use GDAL short name as given by the name field of
# gdalDrivers(), or at
# `extension` is the output extension corresponding to the primary file
# `ot` is the output type (see
View polygonizer.R
polygonizer <- function(x, outshape=NULL, gdalformat = 'ESRI Shapefile',
pypath=NULL, readpoly=TRUE, quietish=TRUE) {
# x: an R Raster layer, or the file path to a raster file recognised by GDAL
# outshape: the path to the output shapefile (if NULL, a temporary file will be created)
# gdalformat: the desired OGR vector format
# pypath: the path to (if NULL, an attempt will be made to determine the location
# readpoly: should the polygon shapefile be read back into R, and returned by this function? (logical)
# quietish: should (some) messages be suppressed? (logical)
if (isTRUE(readpoly)) require(rgdal)
if (is.null(pypath)) {
Pakillo /
Last active Sep 13, 2016 — forked from hadley/
R programming syllabus by Hadley Wickham


  • I've tried to break up in to separate pieces, but it's not always possible: e.g. knowledge of data structures and subsetting are tidy intertwined.

  • Level of Bloom's taxonomy listed in square brackets, e.g. Few categories currently assess components higher in the taxonomy.

Programming R curriculum

Data structures

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