Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
0.585202358 0.182976571 0.338460824 0.120814956 0.038781686 0.06119999 -0.145477372 -0.203187412 -0.06312324 1.328134042 1.632585617 1.008101956 0.670263571 0.339262979 0.457069277 -0.129575998 -0.020512418 -0.238318717 -0.055964585 -0.078062027 -0.082513602 0.988711593 1.017646829 0.613195254 -0.095707895 -0.437837424 -0.51557955 -0.562160654 -0.741968137 -1.093161246 -1.215258689 -1.468677585 -1.382032309 -0.08854924 -0.095226602 -0.886323453 -1.07948566 -1.114777396 -0.801262241 -0.910004959 -0.818587247 -0.782814218 -0.844975833 -0.986944931 -0.693461862 0.44008538 0.364408609 0.024504868 -0.144334109 -0.288849856 0.144536954 0.491278489 0.658052109 0.606698569 0.528956443 0.382214908 0.57982869 1.575377115 1.715441288 1.170925541
Data Y:
0.665330703 0.238621255 0.365170272 0.127492318 0.078845858 0.123522036 -0.025284855 -0.091898044 0.077101364 1.51510018 1.837358053 1.264067501 0.921777542 0.51510018 0.610648605 0.017325967 0.117486398 -0.091416751 0.122098404 0.10890411 0.104452536 1.184580881 1.213516116 0.746742495 9.61045E-07 -0.342128568 -0.410967545 -0.499838608 -0.672968729 -0.970742941 -1.063905148 -1.292840384 -1.195066171 0.10509426 0.076159024 -0.701583102 -0.876939011 -0.854360275 -0.587586654 -0.689652011 -0.616040597 -0.537977609 -0.582332925 -0.661979977 -0.323981161 0.807340293 0.653760966 0.293825138 0.049309391 -0.199818362 0.146762742 0.471246402 0.655826322 0.613375931 0.56456904 0.446762742 0.700021207 1.684440696 1.860117466 1.295569632
Sample Range:
(leave blank to include all observations)
From:
To:
bandwidth of density plot
(?)
# lags (autocorrelation function)
(?)
1
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