第四章探索性数据分析4。1常用分布的概率函数图#二项分布n-20p-0。2k-seq(0,n)plot(k,dbinom(k,n,p),type='h',main='Binomialdistribution,n=20,p=0。2',xlab='k')#泊松分布lambda-4。0k-seq(0,20)plot(k,dpois(k,lambda),type='h',main='Poissondistribution,lambda=5。5',xlab='k')#几何分布p-0。5k-seq(0,10)plot(k,dgeom(k,p),type='h',main='Geometricdistribution,p=0。5',xlab='k')#超几何分布N-30M-10n-10k-seq(0,10)plot(k,dhyper(k,N,M,n),type='h',main='Hypergeometricdistribution,N=30,M=10,n=10',xlab='k')#负二项分布n-10p-0。5k-seq(0,40)plot(k,dnbinom(k,n,p),type='h',main='NegativeBinomialdistribution,n=10,p=0。

5',xlab='k')#正态分布curve(dnorm(x,0,1),xlim=c(-5,5),ylim=c(0,。8),col='red',lwd=2,lty=3)curve(dnorm(x,0,2),add=T,col='blue',lwd=2,lty=2)curve(dnorm(x,0,1/2),add=T,lwd=2,lty=1)title(main="Gaussiandistributions")legend(par('usr')[2],par('usr')[4],xjust=1,c('sigma=1','sigma=2','sigma=1/2'),lwd=c(2,2,2),lty=c(3,2,1),【原创】定制代写开发ws数据挖掘和统计分析可视化调研报告程序等服务（附代码数据）,咨询：3有问题到淘宝找“大数据部落”就可以了col=c('red','blue',par("fg")))分布curve(dt(x,1),xlim=c(-3,3),ylim=c(0,。4),col='red',lwd=2,lty=1)curve(dt(x,2),add=T,col='green',lwd=2,lty=2)curve(dt(x,10),add=T,col='orange',lwd=2,lty=3)curve(dnorm(x),add=T,lwd=3,lty=4)title(main="Studentdistributions")legend(par('usr')[2],par('usr')[4],xjust=1,c('df=1','df=2','df=10','Gaussiandistribution'),lwd=c(2,2,2,2),lty=c(1,2,3,4),col=c('red','blue','green',par("fg")))#卡方分布curve(dchisq(x,1),xlim=c(0,10),ylim=c(0,。

6),col='red',lwd=2)curve(dchisq(x,2),add=T,col='green',lwd=2)curve(dchisq(x,3),add=T,col='blue',lwd=2)curve(dchisq(x,5),add=T,col='orange',lwd=2)abline(h=0,lty=3)abline(v=0,lty=3)title(main='ChisquareDistributions')legend(par('usr')[2],par('usr')[4],xjust=1,c('df=1','df=2','df=3','df=5'),lwd=3,lty=1,col=c('red','green','blue','orange')分布curve(df(x,1,1),xlim=c(0,2),ylim=c(0,。8),lty=1)curve(df(x,3,1),add=T,lwd=2,lty=2)curve(df(x,6,1),add=T,lwd=2,lty=3)curve(df(x,3,3),add=T,col='red',lwd=3,lty=4)curve(df(x,3,6),add=T,col='blue',lwd=3,lty=5)title(main="Fisher'slegend(par('usr')[2],par('usr')[4],xjust=1,c('df=(1,1)','df=(3,1)','df=(6,1)','df=(3,3)','df=(3,6)'),lwd=c(1,2,2,3,3),lty=c(1,2,3,4,5),col=c(par("fg"),par("fg"),par("fg"),'red','blue'))#对数正态分布curve(dlnorm(x),xlim=c(-。

2,5),ylim=c(0,1。0),lwd=2)curve(dlnorm(x,0,3/2),add=T,col='blue',lwd=2,lty=2)curve(dlnorm(x,0,1/2),add=T,col='orange',lwd=2,lty=3)title(main="Lognormaldistributions")legend(par('usr')[2],par('usr')[4],xjust=1,c('sigma=1','sigma=2','sigma=1/2'),lwd=c(2,2,2),lty=c(1,2,3),col=c(par("fg"),'blue','orange'#柯西分布curve(dcauchy(x),xlim=c(-5,5),ylim=c(0,。5),lwd=3)curve(dnorm(x),add=T,col='red',lty=2)legend(par('usr')[2],par('usr')[4],xjust=1,c('Cauchydistribution','Gaussiandistribution'),lwd=c(3,1),lty=c(1,2),col=c(par("fg"),'red'))#威布尔分布curve(dexp(x),xlim=c(0,3),ylim=c(0,2))curve(dweibull(x,1),lty=3,lwd=3, add=T) curve(dweibull(x,2), col='red', add=T) curve(dweibull(x,。

8), col='blue', add=T) title(main="Weibull Probability Distribution Function") legend(par('usr')[2], par('usr')[4], xjust=1, c('Exponential', 'Weibull, shape=1', 'Weibull, shape=2', 'Weibull, shape=。8'), lwd=c(1,3,1,1), lty=c(1,3,1,1), col=c(par("fg"), par("fg"), 'red', 'blue')) #珈码分布 curve( dgamma(x,1,1), xlim=c(0,5), lwd=2, lty=1 curve(dgamma(x,2,1), add=T, col='red', lwd=2, lty=2 curve(dgamma(x,3,1), add=T, col='green', lwd=2, lty=3 curve(dgamma(x,4,1), add=T, col='blue', lwd=2, lty=4 curve(dgamma(x,5,1), add=T, col='orange', lwd=2, lty=5 title(main="Gammadistributions") legend(par('usr')[2], par('usr')[4], xjust=1, (Exponentialdistribution)', lwd=c(2,2,2,2,2),lty=c(1,2,3,4,5), col=c(par('fg'), 'red', 'green', 'blue', 'orange') #贝塔分布curve( dbeta(x,1,1), xlim=c(0,1), ylim=c(0,4) curve(dbeta(x,3,1), add=T, col='green' curve(dbeta(x,3,2), add=T, lty=2, lwd=2 curve(dbeta(x,4,2), add=T, lty=2, lwd=2, col='blue' curve(dbeta(x,2,3), add=T, lty=3, lwd=3, col='red' curve(dbeta(x,4,3), add=T, lty=3, lwd=3, col='orange' title(main="Betadistributions") legend(par('usr')[1], par('usr')[4], xjust=0, c('(1,1)', '(3,1)', '(3,2)', '(4,2)', '(2,3)', '(4,3)' lwd=c(1,1,2,2, 3,3), lty=c(1,1, 2,2, 3,3), col=c(par('fg'), 'green', par('fg'), 'blue', 'red', 'orange' 4。

2直方图与密度函数的估计 4。2。1 直方图 4。2。2 核密度估计 rbinom(N,n,p)hist(x, xlim=c(min(x),max(x)), probability=T, nclass=max(x)-min(x)+1, col='lightblue', main='Binomial distribution, n=100, lines(density(x,bw=1),col='red', lwd=3) rnbinom(N,10, 。25) hist(x, xlim=c(min(x),max(x)), probability=T,