dmarcelinobr

require(MCMCpack)

## the more recent polls, the better they are.
##http://es.wikipedia.org/wiki/Elecciones_presidenciales_de_Uruguay_de_2014
 
polls = NULL
polls <- data.frame( rbind(
  Factum = c(52,37, 1004),
  Cifra = c(52, 35, 1000),
  Equipos  =  c(52, 39, 600),

dmarcelinobr

# caTools is handy because it provides write.gif function
library(caTools) 
cols <- colorRampPalette(c("#00007F", "brown", "blue", "#007FFF", "green", "#7FFF7F", "yellow", "#FF7F00", "red", "#7F0000", "magenta"))
m <- 1200 # define size
C <- complex( real=rep(seq(-1.8,0.6, length.out=m), each=m ),
              imag=rep(seq(-1.2,1.2, length.out=m), m ) )
C <- matrix(C,m,m) # reshape as square matrix
Z <- 0 # initialize Z to zero
X <- array(0, c(m,m,20)) # initialize output 3D array
for (k in 1:20) { # loop with 20 iterations

dmarcelinobr

#Comments 
1. All code is written with the original, vague priors. 
2. Runs were made with the logicals compiled.
3. Note that inprod() could be used, but is much slower (in versions of BUGS up to 3.0.1): with no missing covariate information it should be more efficient.
4. Parameters that I monitored are highlighted in this fetching shade .
5. Initial valus are given: the burn-in was not our main interest, so they were set to make this small.
6. Comments on the no selection, fixed effect, apply to all models. Similarly, comments on fixed effect models also apply to the corresponding random effect model

Data for all models in here 

dmarcelinobr

# The original R code is Bradley Boehmke
# https://rpubs.com/bradleyboehmke/weather_graphic
# Packages
library(dplyr)
library(tidyr)
library(magrittr)
library(ggplot2)
"http://academic.udayton.edu/kissock/http/Weather/gsod95-current/BZBRSLIA.txt" %>%
  read.table() %>% data.frame %>% tbl_df -> data
names(data) <- c("month", "day", "year", "temp")

dmarcelinobr

## Exported as an SVG of 1200 width and 525 height 
poly_coords<- function(shapefile){

if (nrow(data.frame(shapefile$ID))< 1) 

	{

	print ("No ID field in SpatialPolygon")

	}else{

dmarcelinobr

require(dplyr)
require(RCurl)
require(reshape2)
require(rvest)
require(pipeR)


getGoogleResults <- function (search.term, show = 10){
	Trim <- function (x) gsub("^\\s+|\\s+$", "", x)
	packages = c('rvest','dplyr','pipeR','reshape2')

dmarcelinobr

library(rvest)

'http://espn.go.com/sportsnation/teamrankings#table' %>>%
	html %>>%
	html_table() %>>% data.frame %>>% tbl_df -> data

names(data) %<>% tolower()
c('rank','team') -> names(data)[1:2]
data$rank  %>>% (gsub('\\.','',.)) %>>% as.numeric -> data$rank
data[!is.na(data$rank),] -> data

dmarcelinobr

##################################################################################
#######################    SQLite Speed      #####################################
##################################################################################
install.packages("sqldf")
require(sqldf)
#DataPath<-"C:/Data/NewTables/"
#Datatbl<-list.files(DataPath)
#Cwd<-getwd()
#setwd(DataPath)
#dat = lapply(Datatbl,read.csv, header = TRUE)

dmarcelinobr

# written by http://hannes.muehleisen.org/

# from http://stackoverflow.com/questions/16474696/read-system-tmp-dir-in-r
gettmpdir <- 
	function() {
		tm <- Sys.getenv(c('TMPDIR', 'TMP', 'TEMP'))
		d <- which(file.info(tm)$isdir & file.access(tm, 2) == 0)
		if (length(d) > 0)
		  tm[[d[1]]]
		else if (.Platform$OS.type == 'windows')

dmarcelinobr

library(ggplot2)
#install.packages("lme4")
library(lme4)
library(doBy)
library(mice)

############### ############### 
# MI adjustments for final estimates
############### ############### 
finalMI <- function(var,beta,m){