| workshop 5 | *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: Thu, 05 Nov 2009 15:08:10 -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/05/t1257459037diq5lad4z1rptf9.htm/, Retrieved Thu, 05 Nov 2009 23:10:37 +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/05/t1257459037diq5lad4z1rptf9.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 « | 14836,78129
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3,631100644 | | Dataseries Y: | » Textbox « » Textfile « » CSV « | 523,5658454
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11306,30872 | | Output produced by software: |
Model: Y[t] = c + b X[t] + e[t] | c | 4.81007752170208e-07 | b | 0.527784017182103 |
Descriptive Statistics about e[t] | # observations | 72 | minimum | -20040.7743225510 | Q1 | -4118.77861685935 | median | -132.941533286339 | mean | -2.45186587082773e-13 | Q3 | 4297.27903536547 | maximum | 15791.6505585368 |
| Charts produced by software: | | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/1zokn1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/1zokn1257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/29jmm1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/29jmm1257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/39jxj1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/39jxj1257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/4uapp1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/4uapp1257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/5lka81257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/5lka81257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/6efbz1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/6efbz1257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/71wpz1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/71wpz1257458884.ps (open in new window) |
| http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/8l2pb1257458884.png (open in new window) | http://www.freestatistics.org/blog/date/2009/Nov/05/t1257459037diq5lad4z1rptf9/8l2pb1257458884.ps (open in new window) |
| | Parameters (Session): | par1 = 0 ; par2 = 36 ; | | Parameters (R input): | par1 = 0 ; par2 = 36 ; | | 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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