Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
561278.953403 531688.863508 530476.739984 516554.039015 529717.931445 516329.925670 498702.735525 485559.950110 484415.489208 585513.012854 591640.832901 591184.538059 562076.281333 530999.465840 532933.809615 518188.961997 533223.711085 511609.605386 506174.094115 496165.453587 496047.989229 579981.128842 586091.473023 574269.182369 514907.874461 476875.512441 457465.603353 455610.427846 455500.237443 418876.375959 412242.387427 379690.136583 355843.920372 462294.800073 474151.341638 429638.357104 404162.558230 376383.480981 379651.991480 377545.637891 378910.852584 349587.403733 345057.419945 308009.944364 317241.810145 413015.475329 416106.506654 384505.026884 365277.427820 359238.927542 378922.695756 397396.594516 419572.566945 425088.005901 429181.353756 403454.736163 421312.533750 517493.790015 532462.390475 500425.214996
Data Y:
-728.6536239 -142.7511303 -787.4949964 -451.4486862 -608.6620624 -296.7188762 552.6397207 292.2142193 1109.976956 676.0328384 -795.667833 6.748639935 337.1910648 -28.2329969 -301.334858 959.2260214 975.7066251 338.5370335 1429.849533 239.3427171 703.4676389 668.1531457 -323.5548664 -180.6756105 268.5288785 671.1955607 -437.4322114 24.26534452 196.6884971 -230.2832497 696.8676478 -136.156074 -155.3059685 529.5866478 -321.7732118 76.40069887 -616.1635797 1191.089993 -111.028839 -541.98817 71.06336825 581.3435659 176.8095 446.251913 -59.83651764 361.9772745 -545.3283088 -584.3486789 89.33123317 -271.0948937 -267.8957385 356.7999528 -1291.339839 -888.6439591 -571.7600768 -228.9650974 -610.0780403 -549.9429329 -611.468584 -351.2567187
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