乱数001 - waseda2bun_r @ ウィキ

 ・平均10、分散1.5の正規分布

標本数を増やすと理論値に近づく（と思う）。

ywhite <- rnorm(10,sd=sqrt(1.5)) plot(ywhite,type="l") abline(h=0,col="red") mean(ywhite);var(ywhite) ywhite1 <- rnorm(10,m=10,sd=sqrt(1.5)) ywhite2 <- rnorm(100,m=10,sd=sqrt(1.5)) ywhite3 <- rnorm(1000,m=10,sd=sqrt(1.5)) ywhite4 <- rnorm(10000,m=10,sd=sqrt(1.5)) ywhite5 <- rnorm(100000,m=10,sd=sqrt(1.5)) ywhite6 <- rnorm(1000000,m=10,sd=sqrt(1.5)) mean(ywhite1);var(ywhite1) mean(ywhite2);var(ywhite2) mean(ywhite3);var(ywhite3) mean(ywhite4);var(ywhite4) mean(ywhite5);var(ywhite5) mean(ywhite6);var(ywhite6)

・グラフ化

par(mfrow=c(2,2)) hist(ywhite3,prob=TRUE,ylim=c(0,0.4)) y3 <- density(ywhite3);lines(y3,col=2) hist(ywhite4,prob=TRUE,ylim=c(0,0.4)) y4 <- density(ywhite4);lines(y4,col=2) hist(ywhite1,prob=TRUE,ylim=c(0,0.4)) y1 <- density(ywhite1);lines(y1,col=2) hist(ywhite2,prob=TRUE,ylim=c(0,0.4)) y2 <- density(ywhite2);lines(y2,col=2) hist(ywhite5,prob=TRUE,ylim=c(0,0.4)) y5 <- density(ywhite5);lines(y5,col=2) hist(ywhite6,prob=TRUE,ylim=c(0,0.4)) y6 <- density(ywhite3);lines(y6,col=2) ttl1 = "デフォルト" ttl2 = "相対頻度" ttl3 = "区間を４に指定" ttl4 = "kukanで区間指定" kukan <- seq(4,20,by=0.0001) par(mfrow=c(2,2)) hist1 <- hist(ywhite6,main=ttl1) hist2 <- hist(ywhite6,prob=TRUE,main=ttl2) hist3 <- hist(ywhite6,breaks=4,main=ttl3) hist4 <- hist(ywhite6,breaks=kukan,right=TRUE,main=ttl4) write.csv(ywhite5,"ywhite5.csv")

・ACFの計算

理論値では0

par(mfrow=c(2,2)) ywhite1_acf30 <- acf(ywhite1,lag.max=30) ywhite2_acf30 <- acf(ywhite2,lag.max=30) ywhite3_acf30 <- acf(ywhite3,lag.max=30) ywhite4_acf30 <- acf(ywhite4,lag.max=30) ywhite5_acf30 <- acf(ywhite5,lag.max=30) ywhite6_acf30 <- acf(ywhite6,lag.max=30) ywhite1_acf30;ywhite2_acf30;ywhite3_acf30;ywhite4_acf30;ywhite5_acf30;ywhite6_acf30