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.Rhistory
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source("code.R")
gridX
gridY
list(gridX,gridY)
data
H
plot(fhat)
fhat<-kde(data,H,eval.points=list(gridX,gridY))
kde
fhat<-kde(data,H)
grid=list(gridX,gridY)
fhat<-kde(data,H,eval.points=grid)
fhat<-kde(x=data,H,eval.points=grid)
fhat<-kde(x=data,H=H,eval.points=grid)
grid
grid[[1]]
list.grid
is.list(grid)
? kde
? plot.kde
fhat<-kde(x=data,H=H,eval.points=grid)
fhat<-kde(x=data,H=H,eval.points=as.list(grid))
data <- subset(data0,F2==2.00e+09,select = c("ADF","ASI"))/10e6
data
fhat<-kde(x=data,H=H,eval.points=grid)
grid=list(gridX,gridY)
t(data)
data
data[1,]
kde
predict
predict(fhat
_
)
predict(fhat, c(1,2))
predict(fhat, x=c(1,2))
predict(fhat, x=c(2,2))
kde
kdde
kdde
kdde
fhat<-kde(x=data,H=H)
fhat$eval.points
grid
as.numeric(grid)
grid
q()
source("code.R")
6007/58023
fhat$eval.points
fhat$estimate
plot(fhat)
list(gridX,gridY)
fhat$eval.points
kde
fhat<-kde.points(x = x, H = H, eval.points = eval.points)
kde
kde
fhat<-kde(x = x, H = H)
fhat<-kde(x = data, H = H)
fhat<-kde(x = data, H = H,eval.points=fhat$eval.points)
fhat<-kde(x = data, H = H,fhat$eval.points)
fhat<-kde(x = data, H = H, list(gridX,gridY))
plot(fhat)
list(gridX,gridY)
data(iris)
ir <- iris[,1:4][iris[,5]=="setosa",]
H.scv <- Hscv(ir)
ir
ir[1,]
fhat <- kde(ir, H.scv, eval.points=ir)
plot(fhat)
ir <- iris[,1:2][iris[,5]=="setosa",]
H.scv <- Hscv(ir)
fhat <- kde(ir, H.scv, eval.points=ir)
plot(fhat)
ir
fhat <- kde(ir, H.scv, eval.points=ir)
plot(fhat)
fhat$eval.points[[1]]
grid
gridX<-seq(from=minADF, to=maxADF,by=(maxADF-minADF)/150);
gridY<-seq(from=minASI, to=maxASI,by=(maxASI-minASI)/150);
grid<-expand.grid(gridY,gridX)[2,1]
grid
grid<-expand.grid(gridY,gridX)[,2:1]
grid
grid<-expand.grid(gridY,gridX)
grid
grid<-expand.grid(gridY,gridX)[,2:1]
grid
fhat <- kde(data,H,eval.points=grid)
plot(fhat)
fhat$eval.points
plot(fhat)
grid[,1]
151*151
grid[[1]]
fhat <- kde(data,H,eval.points=list(gridX,gridY))
fhat <- kde(data,H,eval.points = list(gridX,gridY))
fhat <- kde(data,H,eval.points = as.data.frame(list(gridX,gridY)))
plot(fhat)
fhat <- kde(data,H,eval.points = list(gridX,gridY))
q
kde
H
fhat <- kde(data,H,eval.points = list(gridX,gridY))
kde
fhat <- kde(data,H,eval.points = list(gridX,gridY))
fhat <- kde(data,H)
plot(fhat)
grid<-fhat$eval.points
fhat <- kde(data,H,eval.points=grid)
224/18
224/18*16
224/18*16/60
q()
source("code.R")
source("code.R")
q()
source("code.R")
source("code.R")
plot(fhat)
plot(fhat)
plot(fhat,contours)
plot(fhat,contour)
plot(fhat,contour=filled.contour)
plot(fhat,display="filled.contour2")
plot(fhat,display="filled.contour")
plot(fhat,display="filled.contour3")
plot(fhat,display="filled.contour2")
min(fhat$eval.points[[1]])
minADF
max(fhat$eval.points[[1]])
maxADF
source("code.R")
plot(fhat,display="filled.contour3")
plot(fhat,display="filled.contour2")
plot(fhat,display="filled.contour2")
q()
batchlist=readLines("list1.txt")
batchlist
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
dim(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
matr[1,1]
minADF
matr[50,50]
matr[50,49]
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
matr<-read.table("pdf_50/pdf12_QL196_1_GS100.dat",header=F)
sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
1/sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q/sum(matr)
1/sum(matr)
q()
matr<-read.table("pdf_50/pdf12_QL196_1_GS50.dat",header=F)
sum(matr)
q
.q
q()
mydata <- read.table("/home/diana/workspace/data/data-June_WT/Gfile.dat", header=FALSE);
GT="QL196"
T2=2-
T2=20
GS=20
data0 <- subset(mydata,V3==GT & V6==T2 & V4==6);
print(nrow(data0))
names(data0)<-c("B","BD","GT","Day","F2","T2","ADF","ASI","NSM");
minADF=min(data0$ADF)/1e6;
maxADF=max(data0$ADF)/1e6;
minASI=min(data0$ASI)/1e6;
maxASI=max(data0$ASI)/1e6;
minNSM=min(data0$NSM)/1e6;
maxNSM=max(data0$NSM)/1e6;
data <- subset(data0,(F2==Food|Food==0),select = c("ADF","ASI","NSM"))/1e6;
print(nrow(data))
data
Food=1
fhat<-kde(x=data,H=H3d,xmin=c(minADF,minASI,minNSM),xmax=c(maxADF,maxASI,maxNSM),binned=BinTrue,bgridsize=c(GS,GS,GS),gridsize=GS);
data <- subset(data0,(F2==Food|Food==0),select = c("ADF","ASI","NSM"))/1e6;
data
H3d<-Hpiag(x=data);
library(ks)
H3d<-Hpi.diag(x=data);
fhat<-kde(x=data,H=H3d,xmin=c(minADF,minASI,minNSM),xmax=c(maxADF,maxASI,maxNSM),binned=BinTrue,bgridsize=c(GS,GS,GS),gridsize=GS);
fhat<-kde(x=data,H=H3d,xmin=c(minADF,minASI,minNSM),xmax=c(maxADF,maxASI,maxNSM),binned=T,bgridsize=c(GS,GS,GS),gridsize=GS);
plot(fhat)
q()
q
q()
rnorm()
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
rnorm(1)
require(trmvnorm)
library(trmvnorm)
library(tmvnorm)
library(mvtnorm)
rmvnorm(n=2)
rmvnorm(n=2,mean=c(1,1))
rmvnorm(n=4,mean=c(1,1))
q()
mydata <- read.table("/home/diana/workspace/data/dataset-add-2/expression5.dat", header=FALSE);
write.table(file="dates.txt",names(table(mydata$V2)))
mydata <- read.table("/home/diana/workspace/data/dataset-add-2/expression5.dat", header=FALSE);
mydata
mydata[c("ADF","ASI","NSM)][,1]
mydata[,c("ADF","ASI","NSM)][,1]
mydata[,c("ADF","ASI","NSM)]
mydata(,c("ADF","ASI","NSM))
mydata[,1]
mydata[1,]
mydata(,c("ADF","ASI","NSM))[1,]
mydata[,c(7,8,9)][1,]
tp=mydata[,c(7,8,9)]
tp
plot(tp)
plot3d(tp)
plot3D(tp)
plot(tp)
points(tp)
points(tp)
library(scatterplot3d)
library(rgl)
library(scatter3D)
library("scatter3D")
library("scatterplot3D")
download.packages("scatterplot3D")
download.packages(scatterplot3D)
mydata <- read.table("/home/diana/workspace/data/dataset-add-2/expression5.dat", header=FALSE);
library(ks);
mydata <- read.table("/home/diana/workspace/data/lifespan/lifespan-ee.dat", header=FALSE);
GT="QL101"
food="1.00e00"
T2="20"
GS=30
names(mydata)<-c("B","day0","GT","Strain","TT0","TT1","TT2",
"TSD","F0","F1","F2","FSD",
"egg5","FUDR","AB","age","num","ce","CAUSE");
data0 <- subset(mydata,Strain==GT & TT2==T2);
data0 <- subset(mydata,GT==:data0 <- subset(mydata,Strain==GT & TT2==T2) & TT2==T2);
data0[1,]
data0 <- subset(mydata,GT=="QL101" & TT2==T2);
data0[1,]
mydata[1,]
mydata[120,]
mydata[520,]
data0 <- subset(mydata,Strain=="QL101" & TT2==T2);
data0[1,]
GT
T2
data0 <- subset(mydata,Strain==GT & TT2==T2);