Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
0.82 0.82 1.00 1.02 1.02 0.97 0.94 0.73 0.84 0.77 0.80 0.88 1.04 1.02 1.08 1.07 0.99 0.87 0.95 1.16 1.04 1.00 0.93 0.99 0.88 0.92 0.84 0.88 0.94 1.02 1.00 0.89 0.90 0.75 0.69 0.62 0.63 0.60 0.55 0.54 0.32 0.24 0.17 0.25 0.17 0.20 0.39 0.38 0.67 0.63 0.71 0.71 0.64 0.59 0.65 0.65 0.68 0.90 0.86 0.93 0.84 0.68 0.38 0.23 0.46 0.55 0.64 0.62 0.48 0.26 0.35 0.14 -0.87 -0.30 0.02 0.41 0.62 0.46 0.03 -0.82 -0.20 -0.15 -0.54 -0.53 -0.05 -0.02 0.21 0.16 -0.17 -0.30 -0.43 -0.09 0.17 0.26 0.43 0.66 0.58 0.67 0.82 0.71 0.77 1.01 1.03 1.06 1.21 1.09 1.13 0.91 0.79 0.81 0.74 1.03 1.14 1.08 0.97 0.98 0.82 0.85 0.76 0.78 1.06 0.97 0.98 0.59 0.29 -0.13 0.25 0.23 0.23 0.25 0.10 0.31 0.19 0.55 0.57 0.39 0.04 0.48 0.40 0.58 0.59 0.46 0.62 0.55 0.46 0.23 0.12 0.65 0.96 0.82 0.88 0.82 0.71 1.05 0.94 0.82 0.82 0.94 1.12 1.02 0.92 1.05 1.14 1.13 1.15 0.90 0.94 1.06 0.97 0.87 0.52 0.67 0.78 0.63 0.47 0.49 0.20 0.19 0.40 0.49
Data Y:
6.9 6.8 6.7 6.6 6.5 6.5 7.0 7.5 7.6 7.6 7.6 7.8 8.0 8.0 8.0 7.9 7.9 8.0 8.5 9.2 9.4 9.5 9.5 9.6 9.7 9.7 9.6 9.5 9.4 9.3 9.6 10.2 10.2 10.1 9.9 9.8 9.8 9.7 9.5 9.3 9.1 9.0 9.5 10.0 10.2 10.1 10.0 9.9 10.0 9.9 9.7 9.5 9.2 9.0 9.3 9.8 9.8 9.6 9.4 9.3 9.2 9.2 9.0 8.8 8.7 8.7 9.1 9.7 9.8 9.6 9.4 9.4 9.5 9.4 9.3 9.2 9.0 8.9 9.2 9.8 9.9 9.6 9.2 9.1 9.1 9.0 8.9 8.7 8.5 8.3 8.5 8.7 8.4 8.1 7.8 7.7 7.5 7.2 6.8 6.7 6.4 6.3 6.8 7.3 7.1 7.0 6.8 6.6 6.3 6.1 6.1 6.3 6.3 6.0 6.2 6.4 6.8 7.5 7.5 7.6 7.6 7.4 7.3 7.1 6.9 6.8 7.5 7.6 7.8 8.0 8.1 8.2 8.3 8.2 8.0 7.9 7.6 7.6 8.3 8.4 8.4 8.4 8.4 8.6 8.9 8.8 8.3 7.5 7.2 7.4 8.8 9.3 9.3 8.7 8.2 8.3 8.5 8.6 8.5 8.2 8.1 7.9 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 8.5 8.3 8.0 8.2 8.1 8.1 8.0 7.9 7.9
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
36
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
Label y-axis:
Label x-axis:
R Code
par1 <- as.numeric(par1) par2 <- as.numeric(par2) x <- as.ts(x) y <- as.ts(y) mylm <- lm(y~x) cbind(mylm$resid) library(lattice) bitmap(file='pic1.png') plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic1a.png') plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic1b.png') plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]') grid() dev.off() bitmap(file='pic1c.png') plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value') grid() dev.off() bitmap(file='pic2.png') hist(mylm$resid,main='Histogram of e[t]') dev.off() bitmap(file='pic3.png') if (par1 > 0) { densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1) } else { densityplot(~mylm$resid,col='black',main='Density Plot of e[t]') } dev.off() bitmap(file='pic4.png') qqnorm(mylm$resid,main='QQ plot of e[t]') qqline(mylm$resid) grid() dev.off() if (par2 > 0) { bitmap(file='pic5.png') acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function') grid() dev.off() } summary(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'c',1,TRUE) a<-table.element(a,mylm$coeff[[1]]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'b',1,TRUE) a<-table.element(a,mylm$coeff[[2]]) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'# observations',header=TRUE) a<-table.element(a,length(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'minimum',header=TRUE) a<-table.element(a,min(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q1',header=TRUE) a<-table.element(a,quantile(mylm$resid,0.25)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'median',header=TRUE) a<-table.element(a,median(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'mean',header=TRUE) a<-table.element(a,mean(mylm$resid)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Q3',header=TRUE) a<-table.element(a,quantile(mylm$resid,0.75)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'maximum',header=TRUE) a<-table.element(a,max(mylm$resid)) 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