beenswax<-read.table("E:\\文档\\102-大学\\003-大三\\非参数统计\\2016.10.12-第四次非参作业\\beenswax.txt",header=T)#导入数据
plot(ecdf(beenswax$MeltingPoint))#MeltingPoint的经验累积分布
hist(beenswax$MeltingPoint,main="Histogram of MeltingPoint",xlab='MeltingPoint')#MeltingPoint的直方图
qqnorm(beenswax$MeltingPoint)#MeltingPoint的Q-Q图
plot(ecdf(beenswax$Hydrocarbon))#Hydrocarbon的经验累积分布
hist(beenswax$Hydrocarbon,main="Histogram of Hydrocarbon",xlab='Hydrocarbon')#Hydrocarbon的直方图
qqnorm(beenswax$Hydrocarbon)#Hydrocarbon的Q-Q图
#######MeltingPoint#########
#联想到经验分布函数,按照分位数定义来做
MeltingPoint<-beenswax$MeltingPoint
MeltingPoint_sort <- sort(MeltingPoint)
MeltingPoint_rank <- rank(MeltingPoint_sort,ties.method = "max")
MeltingPoint_cdf <- MeltingPoint_rank/length(MeltingPoint_rank)
MeltingPoint_sort[length(MeltingPoint_cdf[MeltingPoint_cdf<=0.90])]#0.90分位数
## [1] 63.93
MeltingPoint_sort[length(MeltingPoint_cdf[MeltingPoint_cdf<=0.75])]#0.75分位数
## [1] 63.83
MeltingPoint_sort[length(MeltingPoint_cdf[MeltingPoint_cdf<=0.50])]#0.50分位数
## [1] 63.51
MeltingPoint_sort[length(MeltingPoint_cdf[MeltingPoint_cdf<=0.25])]#0.25分位数
## [1] 63.34
MeltingPoint_sort[length(MeltingPoint_cdf[MeltingPoint_cdf<=0.10])]#0.10分位数
## [1] 63.1
#######Hydrocarbon#########
#同理
Hydrocarbon<-beenswax$Hydrocarbon
Hydrocarbon_sort <- sort(Hydrocarbon)
Hydrocarbon_rank <- rank(Hydrocarbon_sort,ties.method = "max")
Hydrocarbon_cdf <- Hydrocarbon_rank/length(Hydrocarbon_rank)
Hydrocarbon_sort[length(Hydrocarbon_cdf[Hydrocarbon_cdf<=0.90])]#0.90分位数
## [1] 15.4
Hydrocarbon_sort[length(Hydrocarbon_cdf[Hydrocarbon_cdf<=0.75])]#0.75分位数
## [1] 15.1
Hydrocarbon_sort[length(Hydrocarbon_cdf[Hydrocarbon_cdf<=0.50])]#0.50分位数
## [1] 14.56
Hydrocarbon_sort[length(Hydrocarbon_cdf[Hydrocarbon_cdf<=0.25])]#0.25分位数
## [1] 14.01
Hydrocarbon_sort[length(Hydrocarbon_cdf[Hydrocarbon_cdf<=0.10])]#0.10分位数
## [1] 13.65
MeltingPoint
hist(beenswax$MeltingPoint,main="Histogram of MeltingPoint",xlab='MeltingPoint')
qqnorm(beenswax$MeltingPoint)
* 从图像上看好像很难直接看出结论。
* 然后,由于总体均值和方差未知,Liliefor提出用样本均值和标准差代替总体均值和标准差,然后使用Kolmogorov-Smirnov正态性检验法。我们不妨试一下这一种正态性检验的方法。
library(nortest)
lillie.test(MeltingPoint)
##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: MeltingPoint
## D = 0.085842, p-value = 0.3447
* 从Liliefor检验来看,我们没有足够的证据说明Hydrocarbon不服从正态分布。
Hydrocarbon
hist(beenswax$Hydrocarbon,main="Histogram of Hydrocarbon",xlab='Hydrocarbon')
qqnorm(beenswax$Hydrocarbon)
* 从图像上看,Hydrocarbon好像有点像正态分布,然而并不能贸然看图就下定结论。
* 同理运用Liliefor检验来进行正态性检验。
library(nortest)
lillie.test(Hydrocarbon)
##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: Hydrocarbon
## D = 0.062161, p-value = 0.8261
* 从Liliefor检验来看,我们没有足够的证据说明Hydrocarbon不服从正态分布。
#输入数据
participant<-c("BG","JF","BS","SI","BW","TS","GM","SS","MU","OS")
nodrug<-c(174,224,260,255,165,237,191,100,115,189)
placebo<-c(263,213,231,291,168,121,137,102,89,433)
I.Papaverine<-c(105,103,145,103,144,94,35,133,83,237)
II.Aminophylline<-c(141,168,78,164,127,114,96,222,165,168)
III.Morphine<-c(199,143,113,225,176,144,87,120,100,173)
IV.Pentobarbital<-c(108,341,159,135,239,136,140,134,185,188)
VI.Tripelinnamine<-c(144,184,125,227,196,155,121,129,76,317)
research<-data.frame(participant,nodrug,placebo,I.Papaverine,II.Aminophylline,III.Morphine,IV.Pentobarbital,VI.Tripelinnamine)
n=length(nodrug)
plot(sort(nodrug,decreasing=T),1:n/n,type="l",lty=1,lwd=2,xlab="duration",ylab="proportion of suffering participant")
lines(sort(placebo,decreasing=T),1:n/n,lty=1)
lines(sort(I.Papaverine,decreasing=T),1:n/n,lty=2)
lines(sort(II.Aminophylline,decreasing=T),1:n/n,lty=3)
lines(sort(III.Morphine,decreasing=T),1:n/n,lty=4)
lines(sort(IV.Pentobarbital,decreasing=T),1:n/n,lty=5)
lines(sort(VI.Tripelinnamine,decreasing=T),1:n/n,lty=6)
legend(205,1.03,title="Drug Use",legend=c("nodrug","placebo","I.Papaverine","II.Aminophylline","III.Morphine","IV.Pentobarbital","VI.Tripelinnamine"),lty=c(1,1:6),lwd=c(2,1,1,1,1,1,1))
生存函数如上图所示
实线对应于对照组,其中粗实线是nodrug,细实线是placebo(安慰剂),其他虚线分别代表5个实验组,图中的经验生存函数直观地描述人皮肤瘙痒的持续时间。可以看出:I.Papaverine明显低于对照组,而其他4个实验组的生存函数曲线或多或少靠近于对照组。从图中可以看出I.Papaverine与其他四组有明显差别,而II.Aminophylline、III.Morphine、IV.Pentobarbital、VI.Tripelinnamine从图像上看不出有明显差异。