Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
89.28 89.47 89.53 90.72 90.91 91.38 91.49 90.9 90.93 90.57 91.28 90.83 91.5 91.58 92.49 94.16 95.46 95.8 95.32 95.41 95.35 95.68 95.59 94.96 96.92 96.06 96.59 96.67 97.27 96.38 96.47 96.05 96.76 96.51 96.55 95.97 97 97.46 97.9 98.42 98.54 99 98.94 99.02 100.07 98.72 98.73 98.04 99.08 99.22 99.57 100.44 100.84 100.75 100.49 99.98 99.96 99.76 100.11 99.79 100.29 101.12 102.65 102.71 103.39 102.8 102.07 102.15 101.21 101.27 101.86 101.65 101.94 102.62 102.71 103.39 104.51 104.09 104.29 104.57 105.39 105.15 106.13 105.46 106.47 106.62 106.52 108.04 107.15 107.32 107.76 107.26 107.89
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
0
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Chart options
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) library(lattice) bitmap(file='pic1.png') plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(x) grid() dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1) } else { densityplot(~x,col='black',main='Density Plot') } dev.off() bitmap(file='pic4.png') qqnorm(x) grid() dev.off() if (par2 > 0) { bitmap(file='lagplot.png') dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main=paste('Lag plot, lowess, and regression line')) lines(lowess(z)) abline(lm(z)) dev.off() bitmap(file='pic5.png') acf(x,lag.max=par2,main='Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(x,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(x)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,quantile(x,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation