cdf <-numeric(length(x)) for (i in 1:length(x)){ g<-x[1]*exp(-(u*x[1])2/2) cdf [i]<-mean(g)/sqrt(2 pi)+0.5 Phi <-pnorm(x) print(round(rbind(x,cdf,Phi),3)) ↓Example 例4：Monte Carlo积分，无穷积分（续）对上例，我们可以使用另外一种方 式(hit-or-miss).记Z~N(0,1),则对任何实数x有 Φ(x)=P(Z≤x)=EI(Z≤x): 从而从标准正态中产生随机样本z1,·,之m后，即可得到Φ(x)的估计为 =e≤ 三1 Previous Next First Last Back Forward 8cdf <- numeric(length(x)) for (i in 1:length(x)) { g <- x[i] * exp(-(u * x[i])^2 / 2) cdf[i] <- mean(g) / sqrt(2 * pi) + 0.5 } Phi <- pnorm(x) print(round(rbind(x, cdf, Phi), 3)) ↓Example ~4: Monte Carlo»©, ð»©(Y) È˛~, ·Ç屶^, ò´ê ™(hit-or-miss). PZ ∼ N(0, 1), KÈ?¤¢Íxk Φ(x) = P(Z ≤ x) = EI(Z ≤ x). l lIO•)ëÅz1, · · · , zm￾, =åΦ(x)Oè Φ( ˆ x) = 1 m Xm i=1 I(zi ≤ x). Previous Next First Last Back Forward 8