Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data:
1412 1811 1115 126 1613 1810 1412 1414 1512 159 1710 1912 1012 1611 1815 1412 1410 1712 1411 1612 1811 1112 1413 1211 1712 913 1610 1414 1512 1110 1612 138 1710 1512 1412 167 99 1512 1710 1310 1510 1612 1615 1210 1510 1112 1513 1511 1711 1312 1614 1410 1112 1213 125 156 1612 1512 1211 1210 87 1312 1114 1411 1512 1013 1114 1211 1512 1512 148 1611 1514 1514 1312 129 1713 1311 1512 1312 1512 1512 1612 1511 1410 159 1412 1312 712 179 1315 1512 1412 1312 1610 1213 149 1712 1510 1714 1211 1615 1111 1511 912 1612 1512 1011 107 1512 1114 1311 1411 1810 1613 1413 148 1411 1412 1211 1413 1512 1514 1513 1315 1710 1711 199 1511 1310 911 158 1511 1512 1612 119 1411 1110 158 139 158 169 1415 1511 168 1613 1112 1212 99 167 1313 169 126 98 138 1315 146 199 1311 128 138 1010 148 1614 1010 118 1411 1212 912 912 115 1612 910 137 1612 1311 98 129 1610 119 1412 136 1515 1412 1612 1312 1411 157 137 115 1112 1412 153 1111 1510 1212 149 1412 89 1312 912 1510 179 1312 158 1511 1411 1612 1310 1610 912 1612 1111 108 1112 1510 1711 1410 88 1512 1112 1610 1012 159 99 166 1910 129 89 119 146 910 156 1314 1610 1110 126 1312 1012 117 128 811 123 126 1510 118 139 149 108 129 157 137 136 139 1210 1211 912 98 1511 103 1411 1512 77 149
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) qqline(x) grid() dev.off() if (par2 > 0) { bitmap(file='lagplot1.png') dum <- cbind(lag(x,k=1),x) dum dum1 <- dum[2:length(x),] dum1 z <- as.data.frame(dum1) z plot(z,main='Lag plot (k=1), lowess, and regression line') lines(lowess(z)) abline(lm(z)) dev.off() if (par2 > 1) { bitmap(file='lagplotpar2.png') dum <- cbind(lag(x,k=par2),x) dum dum1 <- dum[(par2+1):length(x),] dum1 z <- as.data.frame(dum1) z mylagtitle <- 'Lag plot (k=' mylagtitle <- paste(mylagtitle,par2,sep='') mylagtitle <- paste(mylagtitle,'), and lowess',sep='') plot(z,main=mylagtitle) lines(lowess(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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation