Add grids to graphs

ch04.r

@@ -10,12 +10,13 @@ x = seq(-5, 10, (5+10)/1000)
 x = sort(x)
 f = dnormMix(x, 0, 1, 5, 1, p.mix=c(0.7))
 plot(x,f, xlim=c(-5,10), ylim=c(0,0.4), type="n")
-grid()
 lines(x, f, lwd=4, col="blue")
 polygon(c(min(x), x[x<=0.8]), c(f[x<=0.8], 0), col="lightblue")
+grid()
 
 F = pnormMix(x, 0, 1, 5, 1, p.mix=c(0.7))
 plot(x, F, xlim=c(-5,10), ylim=c(0,0.4), type="n")
+grid()
 
 ## CDF of a Uniform random variable
 
@@ -25,8 +26,10 @@ f = dunif(x, -3, 4)
 F = punif(x, -3, 4)
 plot(x, f, type="n")
 lines(x, f, lwd=5)
+grid()
 plot(x, F, type="n")
 lines(x, F, lwd=5)
+grid()
 
 ## CDF of an exponential random variable
 
@@ -36,8 +39,10 @@ f = dexp(x, 1/2)
 F = pexp(x, 1/2)
 plot(x, f, type="n")
 lines(x, f, lwd=5)
+grid()
 plot(x, F, type="n")
 lines(x, F, lwd=5)
+grid()
 
 #############
 # Chapter 4.5
@@ -48,6 +53,7 @@ lines(x, F, lwd=5)
 a = 0; b = 1;
 X = runif(1000, a, b)
 hist(X)
+grid()
 
 ## Mean, variance, median, mode of a uniform random variable
 
@@ -92,13 +98,15 @@ plot(x, f2, type="n")
 lines(x, f1, lwd=4, col="blue")
 lines(x, f2, lwd=4, col="red")
 legend(0, 1, legend=c(expression(paste(lambda, "=5")), expression(paste(lambda, "=2"))), col=c("red", "blue"), lty=1:1)
+grid()
 
 F1 = pexp(x, 1/lambda1)
 F2 = pexp(x, 1/lambda2)
 plot(x, F2, type="n")
 lines(x, F1, lwd=4, col="blue")
 lines(x, F2, lwd=4, col="red")
 legend(0, 1, legend=c(expression(paste(lambda, "=5")), expression(paste(lambda, "=2"))), col=c("red", "blue"), lty=1:1)
+grid()
 
 #############
 # Chapter 4.6
@@ -111,6 +119,7 @@ mu = 0; sigma = 1;
 f = dnorm(x, mu, sigma)
 plot(x, f, type="n")
 lines(x, f, lwd=4, col="blue")
+grid()
 
 ## PDF and CDF of a Gaussian random variable
 
@@ -120,8 +129,10 @@ f = dnorm(x)
 F = pnorm(x)
 plot(x, f, type = "n")
 lines(x, f, lwd=6)
+grid()
 plot(x, F, type = "n")
 lines(x, F, lwd=6)
+grid()
 
 ## Verify standardised gaussian (not on "Code and Data" section on website, but written in textbook p.45)
 
@@ -143,6 +154,7 @@ lines(x, dgamma(x, 10, theta), lwd = 4, col = "#666666")
 lines(x, dgamma(x, 15, theta), lwd = 4, col = "#999999")
 lines(x, dgamma(x, 20, theta), lwd = 4, col = "#CCCCCC")
 legend(23, 0.36, legend=c("k = 2", "k = 5", "k = 10", "k = 15", "k = 20"), col=c("1", "#333333", "#666666", "#999999", "#CCCCCC"), lwd = 4,lty=1:1)
+grid()
 
 # R code to compute skewness and kurtosis
 library(e1071)
@@ -159,6 +171,7 @@ X2 = runif(N, 1, 6)
 X3 = runif(N, 1, 6)
 Z = X1 + X2 + X3
 hist(Z, breaks=seq(2.5,18.5))
+grid()
 
 #############
 # Chapter 4.8
@@ -172,7 +185,9 @@ sigma = 2
 U = runif(10000, 0, 1)
 gU = sigma * inverseCDF(U, pnorm) + mu;
 hist(U)
+grid()
 hist(gU)
+grid()
 
 ## Generating exponential random variables from uniform random nums (not in "code" section, but in textbook p.63)
 
@@ -191,5 +206,6 @@ gU[U > 0.1 & U <= 0.6] = 2
 gU[U > 0.6 & U <= 0.9] = 3
 gU[U > 0.9 & U <= 1] = 4
 hist(gU)
+grid()
 
 #############