Description Usage Format Examples
Data for the capital punishment example used in chapters 4, 5, and 6
1 |
A data frame with 17 rows and 7 variables:
The number of times that capital punishment is implemented on a state level in the United States for the year 1997
Median per capita income in dollars
Percent of the population classified as living in poverty
Percent of Black citizens in the population
Rate of violent crimes per 100,000 residents for the year before (1996)
Dummy variable to indicate whether the state is in the South
Proportion of the population with a college degree
...
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 | data(dp)
attach(dp)
## Table 4.2
dp
## Table 5.1
dp.out <- glm(EXECUTIONS ~ INCOME+PERPOVERTY+PERBLACK+log(VC100k96)+
SOUTH+PROPDEGREE, family=poisson)
dp.cis <- round(glm.summary(dp.out, alpha = 0.05),4)
round(cbind(summary(dp.out)$coef[,1:2], dp.cis),4)
round(dp.out$null.deviance,4);round(dp.out$df.null,4)
round(dp.out$deviance,4);round(dp.out$df.residual,4)
round(logLik(dp.out),4)
round(dp.out$aic,4)
round(vcov(dp.out),4) # variance covariance matrix
## Table 5.2
k <- 200
b5 <- seq(0.1, 5.4,length=k)
w <- rep(0,k)
for(i in 1:k){
mm <- glm(EXECUTIONS ~ INCOME+PERPOVERTY+PERBLACK+log(VC100k96)+PROPDEGREE,
offset=b5[i]*SOUTH,family=poisson)
w[i] <- logLik(mm)
}
f <- function(b5,x,y,maxloglik){
mm <- glm(EXECUTIONS ~ INCOME+PERPOVERTY+PERBLACK+log(VC100k96)+PROPDEGREE,
offset=b5*x,family=poisson)
logLik(mm) - maxloglik + qchisq(.95,1)/2
}
low.pll <- uniroot(f,interval=c(1.5,2), x=SOUTH, y=EXECUTIONS, maxloglik=logLik(dp.out))$root
high.pll <- uniroot(f,interval=c(3,4), x=SOUTH, y=EXECUTIONS, maxloglik=logLik(dp.out))$root
w[which.min(abs(w-low.pll))]
round(c(low.pll, high.pll),4)
cbind(round(dp.cis[,3:4],4),
round(confint(dp.out),4))
## Table 6.2
resp <- resid(dp.out,type="response")
pears <- resid(dp.out,type="pearson")
working <- resid(dp.out,type="working")
devs <- resid(dp.out,type="deviance")
dp.mat <- cbind(rep(1,nrow(dp)), as.matrix(dp[,2:4]), as.matrix(log(dp[,5])),
as.matrix(dp[,6]), as.matrix(dp[,7]))
dp.resid.mat <- cbind(resp,pears,working,devs)
dimnames(dp.resid.mat)[[2]] <- c("response","pearson","working","deviance")
dimnames(dp.resid.mat)[[1]] <- rownames(dp)
dp.resid.mat2 <- round(dp.resid.mat,4)
resid.df <- data.frame(cbind(dp.resid.mat2[,1], dp.resid.mat2[,2],
dp.resid.mat2[,3], dp.resid.mat2[,4]))
colnames(resid.df) <- dimnames(dp.resid.mat)[[2]]
resid.df
## Figure 5.1
dp.mat.0 <- cbind(dp.mat[,1:5],rep(0,length=nrow(dp.mat)),dp.mat[,7])
dimnames(dp.mat.0)[[2]] <- names(dp.out$coefficients)
dp.mat.1 <- cbind(dp.mat[,1:5],rep(1,length=nrow(dp.mat)),dp.mat[,7])
dimnames(dp.mat.1)[[2]] <- names(dp.out$coefficients)
tcks = list(seq(0,140,20), seq(0,12,2), seq(0,30,5), seq(0,10,2), seq(0,30,5))
layout(matrix(c(1,1,2,2,3,3,4,4,5,6,6,7,8,8,8,8), ncol=4, byrow = TRUE),
heights = c(0.3,0.3,0.3,0.1))
par(mar=c(3,3,2,4),oma=c(2,1,1,3))
for (i in 2:(ncol(dp.mat.0)-1)) {
j = i-1
if (i==6){
i <- i+1
plot(0,0, type = "n", axes=FALSE, xlab = "", ylab="")
}
ruler <- seq(min(dp.mat.0[,i]),max(dp.mat.0[,i]),length=1000)
xbeta0 <- exp(dp.out$coefficients[-i]%*%apply(dp.mat.0[,-i],2,mean)
+ dp.out$coefficients[i]*ruler)
xbeta1 <- exp(dp.out$coefficients[-i]%*%apply(dp.mat.1[,-i],2,mean)
+ dp.out$coefficients[i]*ruler)
plot(ruler,xbeta0,type="l", xlab="",ylab="", yaxt="n", xaxt="n",
ylim=c(min(xbeta0,xbeta1)-2,max(xbeta0,xbeta1)), lwd=3)
lines(ruler,xbeta1,lty=4, lwd=2)
axis(1, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1)
axis(2, at=tcks[[j]],
tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = paste("Levels of",dimnames(dp.mat.0)[[2]][i]), ylab="Expected executions",
line = 1.7, cex.lab=1.2)
}
plot(0,0, type = "n", axes=FALSE, xlab = "", ylab="")
par(mar=c(0,1.5,1,1))
plot(0,0, type="n", axes = FALSE, xlab = "", ylab = "")
legend("center", ncol = 2,
legend = c("South State", "Non-South State"),
cex=1.1, lty=c(2,1), bty="n", lwd=c(2,3))
dev.off()
## Figure 5.2
par(mar=c(3,3,1,0),oma=c(1,1,1,1))
plot(b5,w,type="l",lwd=3, xaxt="n", yaxt="n", xlab="", ylab="")
abline(h=logLik(dp.out)-qchisq(.95,1)/2,lty=3, col="gray40")
segments(dp.cis[6,3], -45, dp.cis[6,4], -45, lty=6, col="black", lwd=2)
segments(dp.cis[6,3:4], c(-45,-45), dp.cis[6,3:4], c(-55,-55), lty=3, col="gray40")
text(3.5, y=-45, "Wald Test", cex=0.9)
segments(low.pll, -42.5, high.pll, -42.5, lty=2, lwd=2, col="black")
segments(c(low.pll, high.pll), c(-55,-55), c(low.pll, high.pll),
rep(logLik(dp.out)-qchisq(.95,1)/2,2), lty=3, col="gray40")
text(3.25, y=-42.5, "Profile log-likelihood", cex=0.9, pos=4)
axis(1, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1)
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
title(xlab = 'Coefficient of SOUTH', ylab="Profile log-likelihood",
line = 1.7, cex.lab=1.2)
dev.off()
## Figure 6.1
coef.vector <- NULL
for (i in 1:length(EXECUTIONS)) {
dp.temp <- glm(EXECUTIONS[-i] ~ INCOME[-i]+PERPOVERTY[-i]+PERBLACK[-i]+log(VC100k96)[-i]+
SOUTH[-i]+PROPDEGREE[-i], family=poisson)
coef.vector <- rbind(coef.vector,dp.temp$coefficients)
}
layout(matrix(c(1,2,3,4,5,6), ncol=2, byrow = TRUE), heights = c(0.33,0.33,0.33))
par(mar=c(3,4.5,2,4),oma=c(2,1,1,3))
for(i in 2:ncol(coef.vector)) {
x=plot(coef.vector[,i],type="b",xlab="",ylab="", yaxt="n", xaxt="n", lwd=2,
ylim=c(min(coef.vector[,i])-abs(min(coef.vector[,i]))*0.25,
max(coef.vector[,i])+abs(max(coef.vector[,i]))*0.25))
abline(h=dp.out$coefficients[i])
axis(1, at =seq(2,16,2), tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1)
if(i==2){
axis(2, at = seq(5,35,5)/100000, labels = as.expression(paste(seq(5,35,5), "e(-5)", sep="")),
tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
}
else{
axis(2, tck=0.03, cex.axis=0.9, mgp=c(0.3, 0.3, 0), lty=1, lwd=0, lwd.ticks = 1, las=2)
}
title(xlab = "Index number",
line = 1.7, cex.lab=1.2)
title(ylab=dimnames(dp.mat.0)[[2]][i],
line = 3.25, cex.lab=1.2)
}
dev.off()
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