Andreas Beger andybega

## add-countries-to-cshapes
# Example of how to add missing countries/territories to cshapes using another source for
# the map data/polygon
#

library(cshapes)
library(rgdal)  # need this for projection transform (spTransform)

# this returns all polygons, with start and end dates for indepdence
# we'll have to manually subset for dates below
all <- cshp()

## runme.R
#
# copy and run this code in R to setup and source `wikipedia-terrorism.R` from this gist
#
packs <- c("dplyr", "rvest", "httr", "XML", "stringr", "purrr", "xml2", "tibble", "devtools")
need <- packs[!packs %in% rownames(installed.packages())]
install.packages(need)

devtools::source_gist("https://gist.github.com/andybega/0f16b6a0de0185c157e2a280b5e05074",
                      filename = "wikipedia-terrorism.R")

## us48-spatial-lag.R
library("splm")
data("usaww")
?usaww

# Only Alabama has this policy
policy_x <- c(1, rep(0, 47))
names(policy_x) <- rownames(usaww)

head(policy_x)

## line-segment-colors.R
plot(c(1, 2), c(1, 1), col = c("blue", "red"), pch= 19, cex=4)
lines(c(1, 2), c(1, 1), col = c("blue", "red"), lwd=3)

## plot-yemen.R
library(cshapes)
library(sf)

states <- cshp(as.Date("2016-01-01"), useGW = TRUE)
states <- st_as_sf(states)

yemen <- states[states$CNTRY_NAME=="Yemen", ]
plot(yemen[, 1])

## chart-model.R
library("tidyverse")

arima_qs <- readr::read_csv("/path/to/forecast_rct_a_subset.csv",
  col_types = cols(user_id = col_integer())) %>%
  mutate(Forecaster = factor(Forecaster))

# Add # of questions to each Data source label
arima_qs <- arima_qs %>%
  group_by(Data_source) %>%
  mutate(by_Data_source_n_ifps = length(unique(ifp_id))) %>%

## example.R
library("ggplot2")

df <- structure(list(date = structure(c(17532, 17897, 18262, 18993,
19358, 19723, 20089), class = "Date"), id = c("9991", "9991",
"9991", "9992", "9992", "9992", "9992"), cowcode = c(999, 999,
999, 999, 999, 999, 999), y = c(1, 1, 1, 2, 2, 2, 2)), row.names = c(NA,
-7L), class = "data.frame")

ggplot(df, aes(x = date, y = y, group = cowcode)) + geom_line()

## dot-density-map.R
# Dot density map
# Eventually should be like http://www.radicalcartography.net/index.html?frenchkisses

library(maptools)

nc_SP <- readShapePoly(system.file("shapes/sids.shp", package="maptools")[1],
 proj4string=CRS("+proj=longlat  +ellps=clrk66"))

## Not run:
pls <- slot(nc_SP, "polygons")

## predict-ebma.r
# EBMA ensemble prediction
#
# Aggregate a set of predictions into an ensemble prediction using a fitted
# EBMA model. Recreates the functionality used to calculate test predictions
# during a EBMA calibration call.
#
# ebma - A fitted EBMA object; only works with logit EBMA.
# inputs - Matrix or data frame in which each column is a series of
#   probabilities.
# outcome - Vector of observed outcomes. Lenght must match rows in inputs.

## archigos-polity.r
# Archigos transitions and tenure by regime type
#
# Andreas Beger
# 15 December 2014

setwd("~/Desktop/archigos-polity")

library(foreign)
library(gdata)
	# Example of how to add missing countries/territories to cshapes using another source for
	# the map data/polygon
	#

	library(cshapes)
	library(rgdal) # need this for projection transform (spTransform)

	# this returns all polygons, with start and end dates for indepdence
	# we'll have to manually subset for dates below
	all <- cshp()
	#
	# copy and run this code in R to setup and source `wikipedia-terrorism.R` from this gist
	#
	packs <- c("dplyr", "rvest", "httr", "XML", "stringr", "purrr", "xml2", "tibble", "devtools")
	need <- packs[!packs %in% rownames(installed.packages())]
	install.packages(need)

	devtools::source_gist("https://gist.github.com/andybega/0f16b6a0de0185c157e2a280b5e05074",
	filename = "wikipedia-terrorism.R")
	library("splm")
	data("usaww")
	?usaww

	# Only Alabama has this policy
	policy_x <- c(1, rep(0, 47))
	names(policy_x) <- rownames(usaww)

	head(policy_x)
	plot(c(1, 2), c(1, 1), col = c("blue", "red"), pch= 19, cex=4)
	lines(c(1, 2), c(1, 1), col = c("blue", "red"), lwd=3)
	library(cshapes)
	library(sf)

	states <- cshp(as.Date("2016-01-01"), useGW = TRUE)
	states <- st_as_sf(states)

	yemen <- states[states$CNTRY_NAME=="Yemen", ]
	plot(yemen[, 1])
	library("tidyverse")

	arima_qs <- readr::read_csv("/path/to/forecast_rct_a_subset.csv",
	col_types = cols(user_id = col_integer())) %>%
	mutate(Forecaster = factor(Forecaster))

	# Add # of questions to each Data source label
	arima_qs <- arima_qs %>%
	group_by(Data_source) %>%
	mutate(by_Data_source_n_ifps = length(unique(ifp_id))) %>%
	library("ggplot2")

	df <- structure(list(date = structure(c(17532, 17897, 18262, 18993,
	19358, 19723, 20089), class = "Date"), id = c("9991", "9991",
	"9991", "9992", "9992", "9992", "9992"), cowcode = c(999, 999,
	999, 999, 999, 999, 999), y = c(1, 1, 1, 2, 2, 2, 2)), row.names = c(NA,
	-7L), class = "data.frame")

	ggplot(df, aes(x = date, y = y, group = cowcode)) + geom_line()
	# Dot density map
	# Eventually should be like http://www.radicalcartography.net/index.html?frenchkisses

	library(maptools)

	nc_SP <- readShapePoly(system.file("shapes/sids.shp", package="maptools")[1],
	proj4string=CRS("+proj=longlat +ellps=clrk66"))

	## Not run:
	pls <- slot(nc_SP, "polygons")
	# EBMA ensemble prediction
	#
	# Aggregate a set of predictions into an ensemble prediction using a fitted
	# EBMA model. Recreates the functionality used to calculate test predictions
	# during a EBMA calibration call.
	#
	# ebma - A fitted EBMA object; only works with logit EBMA.
	# inputs - Matrix or data frame in which each column is a series of
	# probabilities.
	# outcome - Vector of observed outcomes. Lenght must match rows in inputs.
	# Archigos transitions and tenure by regime type
	#
	# Andreas Beger
	# 15 December 2014

	setwd("~/Desktop/archigos-polity")

	library(foreign)
	library(gdata)