Matthew Blackwell mattblackwell

## beamer-overlay.Rmd
---
title: 'Beamer Overlay Test'
output:
  beamer_presentation:
    incremental: true
    theme: CambridgeUS
---


```{r, echo = FALSE}

## clinton-rust-belt.R
group.mean <- function(x, group) {
  out <- tapply(x, group, mean, na.rm = TRUE)
  out[group]
}

data(state.fips, package = "maps")
state.fips <- unique(state.fips[,c("fips","abb")])
state.fips$abb <- as.character(state.fips$abb)
state.fips <- rbind(state.fips, c(2, "AK"))
state.fips <- rbind(state.fips, c(15, "HI"))

## sc-primary.csv

          
            fips
            county_name.x
            trump.share
            blkprop2010
            blkprop40
            w.med.income2014

            
              45001
              Abbeville
              0.369
              0.282763504740921
              0.424796127512974
              39287

            
              45003
              Aiken
              0.316
              0.245810404812023
              0.41912412853594
              52247

            
              45007
              Anderson
              0.3195
              0.160426664386563
              0.26353819100009
              45788

            
              45009
              Bamberg
              0.401
              0.615312441358604
              0.606340181301293
              44127

            
              45011
              Barnwell
              0.427
              0.442730206445338
              0.626576621312941
              44781

            
              45013
              Beaufort
              0.301
              0.192870747628411
              0.670735581068204
              65475

            
              45015
              Berkeley
              0.3398
              0.250299421399774
              0.64711736950752
              58645

            
              45019
              Charleston
              0.264
              0.297647975922949
              0.491911977209859
              64441

            
              45021
              Cherokee
              0.42
              0.203787358606483
              0.234154400720937
              38562

## rmdrender
#! /bin/sh

if [ -r "$1" ]; then
    mdfile="$1"
    Rscript -e "rmarkdown::render('${mdfile}', 'all')"
else
    exit 0
fi

## gist:7587294
library(Amelia)
data(africa)
a.out <- amelia(africa, ts = "year", cs = "country")

overimpute(a.out, "gdp_pc")
overimpute(a.out, "gdp_pc", subset = country == "Burkina Faso")
overimpute(a.out, "gdp_pc", subset = gdp_pc >=500)

## gist:6985383
## Function to implment the MCMC sampler
polling.gibbs.kal.fixedS <- function(y, size, dates, states, big, ## data
                              F, X=NULL, XL = NULL, Z=NULL,     ## covariates
                              m.0, C.0, b = NULL, B = NULL,  ## hyper-parameters
                              starts, phi, sigma.a, nu, beta, k,         ## starting values
                              tune, A,
                              iters = 10000, thin = 1, burnin = 0) { ## mcmc stuff

  aa <- proc.time()
  ## pre-gibbs cleaning (calculate variances, setup times, etc)

## attenuation.R
### Create plots for MO talk

library(tikzDevice)

x <- rnorm(200,0,.4)

y <- x + rnorm(200, 0, .4)

night <- rgb(26,31,30, max=255)
beach <- rgb(227,223,186, max=255)

## gist:1203787
## Function to implment the MCMC sampler
polling.gibbs.kal <- function(y, size, dates, states, big, ## data
                              F, X=NULL, XL = NULL, Z=NULL,     ## covariates
                              m.0, C.0, b = NULL, B = NULL,  ## hyper-parameters
                              c.0, d.0, e.0, f.0, g.0, h.0,
                              starts, phi, sigma.a, nu, beta,          ## starting values
                              tune, A, tune.phi,
                              iters = 10000, thin = 1, burnin = 0) { ## mcmc stuff

  aa <- proc.time()
	---
	title: 'Beamer Overlay Test'
	output:
	beamer_presentation:
	incremental: true
	theme: CambridgeUS
	---


	```{r, echo = FALSE}
	group.mean <- function(x, group) {
	out <- tapply(x, group, mean, na.rm = TRUE)
	out[group]
	}

	data(state.fips, package = "maps")
	state.fips <- unique(state.fips[,c("fips","abb")])
	state.fips$abb <- as.character(state.fips$abb)
	state.fips <- rbind(state.fips, c(2, "AK"))
	state.fips <- rbind(state.fips, c(15, "HI"))
fips	county_name.x	trump.share	blkprop2010	blkprop40	w.med.income2014
45001	Abbeville	0.369	0.282763504740921	0.424796127512974	39287
45003	Aiken	0.316	0.245810404812023	0.41912412853594	52247
45007	Anderson	0.3195	0.160426664386563	0.26353819100009	45788
45009	Bamberg	0.401	0.615312441358604	0.606340181301293	44127
45011	Barnwell	0.427	0.442730206445338	0.626576621312941	44781
45013	Beaufort	0.301	0.192870747628411	0.670735581068204	65475
45015	Berkeley	0.3398	0.250299421399774	0.64711736950752	58645
45019	Charleston	0.264	0.297647975922949	0.491911977209859	64441
45021	Cherokee	0.42	0.203787358606483	0.234154400720937	38562
	#! /bin/sh

	if [ -r "$1" ]; then
	mdfile="$1"
	Rscript -e "rmarkdown::render('${mdfile}', 'all')"
	else
	exit 0
	fi
	library(Amelia)
	data(africa)
	a.out <- amelia(africa, ts = "year", cs = "country")

	overimpute(a.out, "gdp_pc")
	overimpute(a.out, "gdp_pc", subset = country == "Burkina Faso")
	overimpute(a.out, "gdp_pc", subset = gdp_pc >=500)
	## Function to implment the MCMC sampler
	polling.gibbs.kal.fixedS <- function(y, size, dates, states, big, ## data
	F, X=NULL, XL = NULL, Z=NULL, ## covariates
	m.0, C.0, b = NULL, B = NULL, ## hyper-parameters
	starts, phi, sigma.a, nu, beta, k, ## starting values
	tune, A,
	iters = 10000, thin = 1, burnin = 0) { ## mcmc stuff

	aa <- proc.time()
	## pre-gibbs cleaning (calculate variances, setup times, etc)
	### Create plots for MO talk

	library(tikzDevice)

	x <- rnorm(200,0,.4)

	y <- x + rnorm(200, 0, .4)

	night <- rgb(26,31,30, max=255)
	beach <- rgb(227,223,186, max=255)
	## Function to implment the MCMC sampler
	polling.gibbs.kal <- function(y, size, dates, states, big, ## data
	F, X=NULL, XL = NULL, Z=NULL, ## covariates
	m.0, C.0, b = NULL, B = NULL, ## hyper-parameters
	c.0, d.0, e.0, f.0, g.0, h.0,
	starts, phi, sigma.a, nu, beta, ## starting values
	tune, A, tune.phi,
	iters = 10000, thin = 1, burnin = 0) { ## mcmc stuff

	aa <- proc.time()