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ws5 bivariate Xt Zt

*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: Wed, 04 Nov 2009 08:39:05 -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/04/t1257349339ij0mm5l1uoelw36.htm/, Retrieved Fri, 24 May 2013 18:00:31 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

System-generated keywords (parent):

(pk = 0)

Estimated Impact

Dataseries X:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

Dataseries Y:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

Output produced by software:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Model: Y[t] = c + b X[t] + e[t]
c	2575.16729040097
b	428.101458080194

Descriptive Statistics about e[t]
# observations	60
minimum	-1952.04702916160
Q1	-273.656977521266
median	137.231251518834
mean	-1.37989157137734e-14
Q3	561.4914990887
maximum	944.513699878493

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/1n8g51257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/1n8g51257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/27avl1257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/27avl1257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/3eed21257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/3eed21257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/4gpy41257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/4gpy41257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/53rt31257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/53rt31257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/6a0o31257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/6a0o31257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/7px1w1257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/7px1w1257349139.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/8v81u1257349139.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Nov/04/t1257349339ij0mm5l1uoelw36/8v81u1257349139.ps (opens in new window)

Click here to open pdf file.

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')