Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
6.39170155 4.14280265 1.85518345 0.9440078 -0.2987007 -0.47934055 0.22863585 0.1541864 -0.87734645 0.27333845 0.84342695 2.60229635 4.2090676 2.93881445 2.2050794 1.20827865 -0.0947125 -0.23862615 0.32024325 -1.23862615 -0.79392355 -0.3623907 0.7565967 2.84301075 3.8559724 2.41205875 0.58152295 -1.519266 -1.352004 -1.61627485 -0.1767656 -0.04282245 -0.44901285 -0.5236704 -0.09151325 0.3827281 -0.25520325 -0.3462298 -2.28175085 -3.402897 -2.12047115 -2.5276586 -4.3031051 -4.61448885 -6.26737595 -3.74303055 1.229841 3.1787399 3.2396034 0.43860635 -3.9579863 -3.72624535 -1.5292365 0.0727576 1.28173105 -0.44460845 -2.1557841 -0.65499515 1.3995133 2.49631405
Data Y:
-302.8565274 -296.2381342 -283.8545246 -280.1276024 -267.9674044 -270.2000126 -285.6899758 -281.7807792 -273.7475034 -302.1976646 -242.5853026 -269.1411498 -300.3416448 -287.1431526 -293.1466632 -281.3836222 -274.962386 -278.0127198 -304.568567 -278.6127198 -294.7204086 -302.9536844 -250.8597156 -278.053857 -303.8125472 -307.262881 -301.0033506 -281.145328 -288.222584 -287.3665642 -311.4898032 -288.7020154 -294.4438202 -309.1189008 -264.799345 -285.7928188 -300.785625 -318.3493336 -301.2210762 -276.6567 -295.6558598 -299.0239192 -293.5409772 -306.1983322 -291.7849574 -302.9862926 -266.579444 -273.2978372 -304.3011752 -302.2274298 -273.6801116 -266.1291102 -260.707874 -265.2553648 -283.2190734 -268.3702474 -264.1433252 -284.6013478 -249.3356364 -261.6986774
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