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SHw WS6

*The author of this computation has been verified*
R Software Module: /rwasp_edabi.wasp (opens new window with default values)
Title produced by software: Bivariate Explorative Data Analysis
Date of computation: Fri, 13 Nov 2009 03:47:41 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0.htm/, Retrieved Fri, 13 Nov 2009 11:48:49 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0.htm/},
    year = {2009},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2009},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
100 108 125 109 92 126 63 51 129 115 96 101 106 93 120 96 99 129 62 56 119 92 90 105 102 99 107 90 90 108 62 53 97 96 103 88 100 95 109 92 96 100 62 64 110 119 93 84 101 92 91 110 85 120 74 59 121 124 100 121
 
Dataseries Y:
» Textbox « » Textfile « » CSV «
100 109 173 91 124 130 82 82 196 116 146 102 153 119 153 137 147 152 84 76 161 129 104 144 171 140 120 130 247 154 38 57 172 163 130 163 110 133 156 157 127 167 89 53 187 202 137 151 128 140 203 160 161 210 154 70 269 176 156 210
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Model: Y[t] = c + b X[t] + e[t]
c-0.316574888656738
b1.45197352876693


Descriptive Statistics about e[t]
# observations60
minimum-66.9485397469382
Q1-18.5587382811863
median-2.96268533872010
mean-7.97394557790672e-17
Q322.3932352475807
maximum116.638957299633
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/11kwm1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/11kwm1258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/21r331258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/21r331258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/3j61r1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/3j61r1258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/46lto1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/46lto1258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/5b3ic1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/5b3ic1258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/6iyen1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/6iyen1258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/75qlz1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/75qlz1258109258.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/82jgi1258109258.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Nov/13/t125810932097k663nznt57dp0/82jgi1258109258.ps (open in new window)


 
Parameters (Session):
par1 = red ; par2 = blue ; par3 = TRUE ; par4 = Faill_brussel ; par5 = Faill_waalsgewest ;
 
Parameters (R input):
par1 = 0 ; par2 = 36 ; par3 = TRUE ; par4 = Faill_brussel ; par5 = Faill_waalsgewest ;
 
R code (references can be found in the software module):
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')
 





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