Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
-43.46299021 -80.75309516 -70.74336158 38.9668564 103.8074054 -154.6120618 80.77812389 -8.071755014 98.25849525 -30.58100421 -44.78092348 40.3791734 -132.19098 -76.88100421 -106.2410204 -60.55099614 -2.200632843 -67.52066514 -28.0902534 -21.31993855 204.9200453 -150.9996641 90.49044089 3.190198694 -95.23997084 -53.65976094 -80.03964792 206.0103925 95.62085262 70.15086069 -4.308751793 -9.298856744 138.9711352 77.72149848 281.4313935 108.1314743 118.3119264 -143.9872663 73.21297587 215.4333311 67.37396079 -107.8253934 -100.1751915 -279.1043923 25.05610826 71.32658458 126.5560275 225.3961728 229.2960114 -32.31452952 256.6652767 74.69536553 8.935672307 161.5151556 -242.1946587 -173.2347233 -53.46489282 -290.1749493 -360.6546748 -187.924909
Data Y:
0.002022723 -0.017208098 -0.051656261 -0.072675401 -0.04888664 -0.035594314 -0.043990322 -0.026968066 -0.008756337 0.032209121 0.042033292 0.026096897 0.026430772 0.042472121 0.058426687 0.053742338 0.041398106 0.052385238 0.052190308 0.039393774 0.00733234 0.018657154 0.017944976 0.006882464 0.009761905 0.019803549 0.004696588 -0.014269327 0.004359046 5.42631E-05 -0.004455318 -0.02117114 -0.021005357 -0.011061589 -0.028604411 -0.02249124 -0.030906084 -0.036827378 -0.055456866 -0.045366315 -0.043827384 -0.036552019 -0.067865593 -0.066311103 -0.051684645 -0.045133838 -0.061448816 -0.025835909 0.00011375 0.047607207 0.079794997 0.039112385 0.055018633 0.074915741 0.061521734 0.052521997 0.024700439 0.004811919 0.0048453 -0.007247995
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation