Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
-2.225348423 2.257563984 1.740476391 3.706301205 7.959396904 -1.810786388 -1.764228405 -1.270419804 4.26994678 0.614671842 1.706301205 4.797930568 6.99357209 2.027747276 -1.627527662 -3.076264883 -0.444268937 1.268460179 1.670639417 3.325914355 4.085201453 1.936117913 -4.638423857 -9.15551145 -2.385328158 -1.30459499 -5.936590936 -15.08567448 -11.20058283 -4.660216246 -1.464574724 -3.7751246 -3.20058283 -10.00494131 -3.315491184 -1.004941308 3.454692108 3.201596409 6.833592356 4.627054639 6.052512869 1.07579186 3.822696161 2.086688055 -1.740949414 -0.362049167 2.580496656 5.901942727 4.867767541 -0.017324105 3.810313364 4.051026267 0.672126019 -0.293698795 1.855384745 -1.43188614 -3.444268937 3.945527506 3.541861665 7.506199877 0.816749754 1.000008479 -1.770174813 -9.549075061 -2.783250246 -4.981417326 -1.341050742 0.916057116 -3.913759591
Data Y:
453.76 567.15 -1861.46 -7454.68 -11242.01 -11289.29 11715.62 19336.27 20729.84 17062.92 10369.32 11258.72 10721.21 10375.43 8202.51 2834.34 -371.69 -2429.58 19711.67 23745.59 25554.61 21797.03 15266.24 16605.63 14210.92 14714.05 11338.08 10074.50 9246.14 6347.71 25088.21 25798.35 27194.14 13649.64 4755.79 1004.64 4035.07 -1054.60 -10228.63 -11699.39 -18817.18 -29199.23 -6246.90 -4201.96 -10585.42 -15033.13 -22236.31 -18963.19 -17206.41 -20744.05 -28649.59 -29339.61 -40442.91 -39478.68 -18740.10 -18252.00 -20542.69 -23465.13 -23725.81 -15453.46 -6685.61 -3334.80 1292.91 2637.62 -3574.61 1701.23 22560.80 26551.57 24040.85
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
12
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation