Nothing
print.nash.eq <-
function(x,...){
digits <- 3
dots <- list(...)
idx <- which(names(dots)=="digits")
if(length(idx)==1)
digits = dots[[idx]]
pos <- NULL
if(!is.null(x$position))
pos <- x$position
idd <- which(names(dots) == "pos")
if(length(idd)==1)
pos <- dots[[idd]]
# print(str(pos))
votes <- NULL
if(!is.null(x$votes))
votes <- x$votes
ide <- which(names(dots) == "votes")
if(length(ide)==1)
votes <- dots[[ide]]
# print(str(votes))
if(!is.null(pos) & !is.null(votes)){
cat("\n\n================\nExternal\n================")
if(!is.null(pos)){
idx <- match( names(x$basic$est) , names(pos))
tpos <- unlist(pos)[idx]
cat("\nParty positions:\n")
print(round(tpos,digits=digits))
}
if(!is.null(votes)){
idx <- match( names(x$basic$mP) , names(votes))
tvotes <- unlist(votes)[idx]
cat("\nParty vote-shares:\n")
print(round(tvotes,digits=digits))
}
}
cat("\n\n================\nNash equilibrium\n================")
cat("\nParty positions:\n")
print(round(x$basic$est,digits=digits))
if(!is.null(pos)){
emn <- x$basic$est
idx <- match( names(emn) , names(pos))
tpos <- unlist(pos)[idx]
mm <- rbind(emn, tpos)
avg <- mean(abs(mm[1,]-mm[2,]))
cat(sprintf("\nCorrelation External/Nash: %.2f\nAverage Absolute Distance: %.2f\n", cor(emn, tpos), avg))
}
cat("\nParty vote-shares:\n")
print(round(x$basic$mP,digits=digits))
if(!is.null(votes)){
mP <- x$basic$mP
idx <- match( names(mP) , names(votes))
tvotes <- unlist(votes)[idx]
mm <- rbind(mP, tvotes)*100
avg <- mean(abs(mm[1,]-mm[2,]))
cat(sprintf("\nCorrelation External/Nash: %.2f\nAverage Absolute Distance: %.2f%%\n", cor(mP, tvotes), avg))
}
if(!is.null(x$MC)){
cat("\n================\nMonte Carlo\n================")
cat("\nParty positions:\n")
tmp <- as.table(rbind(x$MC$est.LB, x$MC$est.mean, x$MC$est.UB))
colnames(tmp) <- names(x$MC$est.mean)
rownames(tmp) <- c(
sprintf("%.1f%% lower bound", 100*(1-x$MC$conf.level)/2),
"mean estimate",
sprintf("%.1f%% upper bound", 100*(1-(1-x$MC$conf.level)/2))
)
print(round(tmp,digits=digits))
if(!is.null(pos)){
emn <- x$MC$est.mean
idx <- match( names(emn) , names(pos))
tpos <- unlist(pos)[idx]
mm <- rbind(emn, tpos)
avg <- mean(abs(mm[1,]-mm[2,]))
cat(sprintf("\nCorrelation External/Nash: %.2f\nAverage Absolute Distance: %.2f\n", cor(emn, tpos), avg))
}
cat("\nParty vote-shares:\n")
tmp <- as.table(rbind(x$MC$mP.LB, x$MC$mP.mean, x$MC$mP.UB))
colnames(tmp) <- names(x$MC$mP.mean)
rownames(tmp) <- c(
sprintf("%.1f%% lower bound", 100*(1-x$MC$conf.level)/2),
"mean estimate",
sprintf("%.1f%% upper bound", 100*(1-(1-x$MC$conf.level)/2))
)
print(round(tmp,digits=digits))
if(!is.null(votes)){
mP <- x$MC$mP.mean
idx <- match( names(mP) , names(votes))
tvotes <- unlist(votes)[idx]
mm <- rbind(mP, tvotes)*100
avg <- mean(abs(mm[1,]-mm[2,]))
cat(sprintf("\nCorrelation External/Monte Carlo: %.2f\nAverage Absolute Distance: %.2f%%\n", cor(mP, tvotes), avg))
}
cat(sprintf("\nMonte Carlo replications: %d\n", x$boot$replications))
}
if(!is.null(x$boot)){
cat("\n================\nBootstrap\n================")
cat("\nParty positions:\n")
tmp <- as.table(rbind(x$boot$est.LB, x$boot$est.mean, x$boot$est.UB))
colnames(tmp) <- names(x$boot$est.mean)
rownames(tmp) <- c(
sprintf("%.1f%% lower bound", 100*(1-x$boot$conf.level)/2),
"mean estimate",
sprintf("%.1f%% upper bound", 100*(1-(1-x$boot$conf.level)/2))
)
print(round(tmp,digits=digits))
if(!is.null(pos)){
emn <- x$boot$est.mean
idx <- match( names(emn) , names(pos))
tpos <- unlist(pos)[idx]
mm <- rbind(emn, tpos)
avg <- mean(abs(mm[1,]-mm[2,]))
cat(sprintf("\nCorrelation External/Bootstrap: %.2f\nAverage Absolute Distance: %.2f\n", cor(emn, tpos), avg))
}
cat("\nParty vote-shares:\n")
tmp <- as.table(rbind(x$boot$mP.LB, x$boot$mP.mean, x$boot$mP.UB))
colnames(tmp) <- names(x$boot$mP.mean)
rownames(tmp) <- c(
sprintf("%.1f%% lower bound", 100*(1-x$boot$conf.level)/2),
"mean estimate",
sprintf("%.1f%% upper bound", 100*(1-(1-x$boot$conf.level)/2))
)
print(round(tmp,digits=digits))
if(!is.null(votes)){
mP <- x$boot$mP.mean
idx <- match( names(mP) , names(votes))
tvotes <- unlist(votes)[idx]
mm <- rbind(mP, tvotes)*100
avg <- mean(abs(mm[1,]-mm[2,]))
cat(sprintf("\nCorrelation External/Monte Carlo: %.2f\nAverage Absolute Distance: %.2f%%\n", cor(mP, tvotes), avg))
}
cat(sprintf("\nBootstrap replications: %d\n", x$boot$replications))
}
}
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