rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
#Data Set   ----------------------------------------------
Q<-c(0,0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
R<-c(1,0,-1,-2,-3,-4,-5,-6,-7,-8,-9)
#---------------------------------------------------------
difD<-(Q-R)
adifD<-abs(difD)
aorderD<-rank(adifD)  #rank: tie
negD<-aorderD[(difD<=0)==TRUE]
posD<-aorderD[(difD>0)==TRUE]
negS<-sum(negD)
posS<-sum(posD)
nsample<-length(posD)
ST<-min(negS,posS)
if(negS==ST){
nsample<-length(negD)
}
nsample
ntotal<-length(difD)
sortdata<-sort(aorderD)
sampleMatrix<-combn(x=sortdata,m=nsample)
critdata<-sort(apply(sampleMatrix,2,sum))
cset<-which(critdata==ST)
p<-max(cset)/length(critdata)
p  #<----Wilcoxon順位和検定の結果
difD
adifD
aordifD
aorderD
negD
negS
ST
nsample
sortdata
sampleMatrix
critdata
p
A<-c(8.5,8.6,9.48,8.65,8.16,8.83,7.76,8.63)
B<-c(8.27,8.20,8.25,8.14,9.00,8.10,7.20,8.32,7.70)
median(A)
median(B)
wilcox.test(A,B,alternative="greater",paired=FALSE)
t.test(A,B)
A<-c(8.50,8.60,9.48,8.65,8.16,8.83,7.76,8.63)
B<-c(8.27,8.20,8.25,8.14,9.00,8.10,7.20,8.32,7.70)
na<-length(A)
classdataA<-rep(c("A"),na)
dataA<-data.frame(classdataA,A)
colnames(dataA)<-c("Class","time")
nb<-length(B)
classdataB<-rep(c("B"),nb)
dataB<-data.frame(classdataB,B)
colnames(dataB)<-c("Class","time")
mergeAB<-rbind(dataA,dataB)
#------------------------------------------------
odata<-order(mergeAB[,2])
oclasslist<-tapply(odata,mergeAB[,1],list)
boxplot(oclasslist$A,oclasslist$B,names=c("A", "B"),las=1,horizontal=TRUE,main=c("rank distribution"))
tclasslist<-tapply(mergeAB[,2],mergeAB[,1],list)
boxplot(tclasslist$A,tclasslist$B,names=c("A", "B"),las=1,horizontal=TRUE,main=c("Time distribution"))
data12<-c(474,404,467,446,397,397,451,389,357,450,420,426)
av<-mean(data12)
AccData1<-matrix(c(data12,rep(av,12)),nrow=12,ncol=2)
rownames(AccData1)<-c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
chisq.test(AccData1)
matrix
AccData1
data12<-c(474,404,467,446,397,397,451,389,357,450,420,426)
av<-mean(data12)
AccData1<-matrix(c(data12,rep(av,12)),nrow=12,ncol=2)
rownames(AccData1)<-c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
chisq.test(AccData1)
data12<-c(474,404,467,446,397,397,451,389,357,450,420,426)
av<-mean(data12)
av
AccData1<-matrix(c(data12,rep(av,12)),nrow=12,ncol=2)
rownames(AccData1)<-c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
chisq.test(AccData1)
data12<-c(423,423,423,423,423,423,423,423,423,423,423,423)
av<-mean(data12)
av
AccData1<-matrix(c(data12,rep(av,12)),nrow=12,ncol=2)
rownames(AccData1)<-c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
chisq.test(AccData1)
#[A]-------------------------------------
cholera<-c(1263,98)
noncholera<-c(38783,26009)
crossdataA<-data.frame(cholera,noncholera)
chisq.test(crossdataA)
#[B]-------------------------------------
#[A]-------------------------------------
cholera<-c(98,98)
noncholera<-c(26009,26009)
crossdataA<-data.frame(cholera,noncholera)
chisq.test(crossdataA)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
install.packages("multcomp")
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
install.packages("zoo")
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
library(zoo)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
plot(tks)
install.packages("zoo")
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
library(zoo)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
xmin= 0
xmax= 5
curve(df(x,3,15), xmin,xmax, col=1)
xmin= 0
xmax= 5
curve(df(x,3,15), xmin,xmax, col="red")
curve(pf(x,3,15), xmin,xmax, col="blue",add=TRUE)
xmin= 0
xmax= 5
curve(pf(x,3,15), xmin,xmax, col="blue")
curve(df(x,3,15), xmin,xmax, col="red",add=TRUE)
summary(anova)
install.packages("zoo")
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
library(zoo)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
if(!require(zoo)){
install.packages("zoo")
library(zoo)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
if(!require(multcomp)){
install.packages("multcomp")
library(multcomp)
}
ifdata<-"DataBrandy.csv"
df<-read.delim(ifdata,row.names=1,header=T,sep=",",as.is=TRUE,strip.white=FALSE)
#------- cnames: classnames
rnames<-rownames(df)
cnames<-substr(rnames, 1, 2)
#-------
selectdata<-data.frame(Class=factor(cnames),SelectValue=df[,1])
plot(SelectValue~Class,data=selectdata)
anova<-aov(SelectValue~Class,data=selectdata)
summary(anova)
tks<-glht(anova,linfct=mcp(Class="Tukey"))
summary(tks)
plot(tks)
setwd("~/JACI/テキスト/20200408プログラム/RprogrammingLectureCourse")
install.packages("som")
#[1]
ifname <- "DataBrandy.csv"
df <- read.delim(ifname, header=T,sep=",",row.names=1,as.is=TRUE,strip.white=FALSE)
ld<-rownames(df)
groupdata<-as.factor(substring(ld,1,2))
mdata<-scale(df)
head(mdata)
groupdata
#[1]
ifname <- "DataBrandy.csv"
df <- read.delim(ifname, header=T,sep=",",row.names=1,as.is=TRUE,strip.white=FALSE)
ld<-rownames(df)
groupdata<-as.factor(substring(ld,1,2))
mdata<-scale(df)
groupdata
head(mdata)
ld
groupdata
head(mdata)
ld
groupdata
head(mdata)
#[2]
xsize<-10
ysize<-10
brandy.som<-som(mdata, xdim=xsize, ydim=ysize,init="linear",alpha=0.5,alphaType="linear",neigh="gaussian")
#------------------------
setwd("~/JACI/テキスト/20200408プログラム/RprogrammingLectureCourse/mol")
if(!require(som)){
install.packages("som")
library(som)
}
#[1]
ifname <- "DataBrandy.csv"
df <- read.delim(ifname, header=T,sep=",",row.names=1,as.is=TRUE,strip.white=FALSE)
ld<-rownames(df)
groupdata<-as.factor(substring(ld,1,2))
mdata<-scale(df)
ld
groupdata
head(mdata)
#[2]
xsize<-10
ysize<-10
brandy.som<-som(mdata, xdim=xsize, ydim=ysize,init="linear",alpha=0.5,alphaType="linear",neigh="gaussian")
View(brandy.som)
summary(brandy.som)
if(!require(som)){
install.packages("som")
library(som)
}
#[1]
ifname <- "DataBrandy.csv"
df <- read.delim(ifname, header=T,sep=",",row.names=1,as.is=TRUE,strip.white=FALSE)
ld<-rownames(df)
groupdata<-as.factor(substring(ld,1,2))
mdata<-scale(df)
ld
groupdata
head(mdata)
#[2]
xsize<-10
ysize<-10
brandy.som<-som(mdata, xdim=xsize, ydim=ysize,init="linear",alpha=0.5,alphaType="linear",neigh="gaussian")
#------------------------
out.new<-data.frame(groupdata,brandy.som$visual[,1:2])
group<-unique(out.new[,1])
ng<-length(group)
for(i in 1:ng){
gdataset<-out.new[out.new[,1]==group[i],2:3]
namedata<-rownames(mdata[as.integer(rownames(gdataset)),])
ns<-dim(gdataset)[1]
rdata<-runif(ns,min=-0.4,max=0.4)
plot(gdataset[,1]+rdata,gdataset[,2]+rdata,col=i,pch=16,xlim=c(-0.5,xsize+1),ylim=c(-0.5,ysize-0.5),xlab="X",ylab="Y")
text(gdataset[,1]+rdata,gdataset[,2]+rdata-0.1,labels=namedata,cex=0.7)
par(new=T)
}
legend("topright", legend = group, col = 1:ng, pch = 16)
#-------------------------------------------------
for(i in 0:xsize){
segments(-0.5, i-0.5, xsize-0.5, i-0.5)
}
for(i in 0:(ysize)){
segments(i-0.5, -0.5, i-0.5, ysize-0.5)
}
out.new
group
ng
