elliottmorris

library(tidyverse)

bayes_update_normal = function(
    data_mu,
    data_se,
    prior_mu = 0,
    prior_se = 3){
  
  if(all(data_mu == 0)){
    return(c(0,0))

elliottmorris

elliottmorris

elliottmorris

#' Description
#' This file runs a live election-night forecast based on The Economist's pre-election forecasting model
#' available at projects.economist.com/us-2020-forecast/president.
#' It is resampling model based on https://pkremp.github.io/update_prob.html.
#' This script does not input any real election results! You will have to enter your picks/constraints manually (scroll to the bottom of the script).
#' 
#' Licence
#' This software is published by *[The Economist](https://www.economist.com)* under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by *The Economist* are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).
#' The licences include only the data and the software authored by *The Economist*, and do not cover any *Economist* content or third-party data or content made available using the software. More information about licensing, syndication and the copyright of *Economist* content can be fou

elliottmorris

library(tidyverse)
library(lubridate)
library(pbapply)

url<- 'https://docs.google.com/spreadsheets/d/e/2PACX-1vQ56fySJKLL18Lipu1_i3ID9JE06voJEz2EXm6JW4Vh11zmndyTwejMavuNntzIWLY0RyhA1UsVEen0/pub?gid=0&single=true&output=csv'

all_polls <- read_csv(url)

# remove any polls if biden or trump blank
all_polls <- all_polls %>% filter(!is.na(biden),!is.na(trump))#, include == "TRUE")

elliottmorris

library(pbapply)
library(tidyverse)

mod <- read_csv('~/Downloads/output/site_data/electoral_college_simulations.csv')
mod <- mod %>% gather(state,vote,4:ncol(.))
evs <- read_csv('data/prior/state_evs.csv')
mod <- mod %>% left_join(evs)

tp <- pblapply(1:max(mod$draw),
               cl = 12,

elliottmorris

library(tidyverse)
library(janitor)
library(lubridate)
library(zoo)
library(politicaldata)

RUN_DATE <- Sys.Date()
start_date <- ymd("2020-02-01")
election_day <- ymd('2020-11-03')

elliottmorris

library(tidyverse)
library(zoo)

trump_approve <- read_csv("https://projects.fivethirtyeight.com/polls-page/president_approval_polls.csv")

trump_approve <- trump_approve %>% 
  mutate("date" = mdy(end_date)) %>% 
  dplyr::select(pollster,
                date, 
                "approve" = yes,

elliottmorris

library(tidyverse)
library(politicaldata)
library(lubridate)
library(zoo)
library(gghighlight)

today_2020_time_difference <- as.numeric(difftime(ymd('2020-11-03'),Sys.Date(),units = 'days'))

# wrangle -----------------------------------------------------------------
# historical

elliottmorris

rm(list = ls()) #reset the environment
library(tidyverse)
library(lubridate)
library(mgcv)

exponent_weight <- function(i) {
  exp(-0.04*i)
}

TODAY_DAY <- difftime(Sys.Date(),as.Date("2017-01-21"))