margingaussianmodelprop: Title

In balexanderstats/bayesurvey: Bayesian Conjugate Prior Analysis of Survey Data

Description

Title

Usage

margingaussianmodelprop(
  poll_data,
  stateloc,
  marginloc,
  nloc,
  proploc = NULL,
  npolls = NULL,
  dateloc = NULL,
  normalize = F,
  invgamma = F,
  v0 = NULL,
  a0 = NULL,
  b0 = NULL,
  election_data,
  cutoffs = c(-0.2, -0.1, -0.025, 0.025, 0.1, 0.2),
  groupnames = c("Strong Red", "Red", "Lean Red", "Competitive", "Lean Blue", "Blue",
    "Strong Blue")
)

Arguments

poll_data
stateloc
marginloc
npolls	the number of polls to include, default is all polls
dateloc	the location of the date used to determine the last npolls
normalize	whether or not to normalize poll date before margin is calculated
invgamma
v0
a0
b0
election_data
cutoffs
groupnames

Examples

require(politicaldata)
elect2008  = subset(pres_results , year == 2008)
elect2008$margin = elect2008$dem - elect2008$rep
elect2012 = subset(pres_results , year == 2012)
elect2012$margin = elect2012$dem - elect2012$rep
electdata = data.frame("state" = elect2008$state, "2008" =  elect2008$margin, "2012" = elect2012$margin)
data(polls2016)
polls = polls2016[ complete.cases(polls2016[, c(2, 3, 12)]), ]
stateloc  = which(colnames(polls) == "State")
polls2016$margin = polls2016$Trump - polls2016$Clinton
marginloc = which(colnames(polls2016) == "margin")
margingaussianmodelprop(polls2016, stateloc = stateloc, marginloc = marginloc, election_data = electdata)

balexanderstats/bayesurvey documentation built on Sept. 20, 2020, 11:40 a.m.