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R Software Module

rwasp_cross.wasp

Title produced by software

Cross Correlation Function

Date of computation

Sun, 21 Dec 2008 07:41:38 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/21/t1229870538xjimk9heqhaptvk.htm/, Retrieved Fri, 17 May 2024 05:46:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35608, Retrieved Fri, 17 May 2024 05:46:25 +0000

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No (this computation is public)

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Estimated Impact

184

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Kendall tau Correlation Matrix] [Kendall tau matri...] [2007-12-13 16:32:12] [707a919fab5d6f3020ea3c395672cd86]
- RMPD  [Cross Correlation Function] [Stefan Temmerman] [2008-12-11 13:49:31] [4c0c0466a42d9212e91e81695c3ab4a9]
-           [Cross Correlation Function] [] [2008-12-21 14:41:38] [75a00449045803b2332dacf227dc78d5] [Current]

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Dataseries X:

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Dataseries Y:

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7.3
7.1
7.1
6.8
6.5
6.3
6.1
6.1
6.3
6.3
6
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8
8.1
8.2
8.3
8.2
8
7.9
7.6
7.6
8.2
8.3
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35608&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35608&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35608&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	-0.6
Degree of non-seasonal differencing (d) of X series	1
Degree of seasonal differencing (D) of X series	2
Seasonal Period (s)	12
Box-Cox transformation parameter (lambda) of Y series	1
Degree of non-seasonal differencing (d) of Y series	2
Degree of seasonal differencing (D) of Y series	1
k	rho(Y[t],X[t+k])
-15	0.0304057392382176
-14	0.122205061018990
-13	-0.132081294099040
-12	0.0924560036048447
-11	0.0258745410366296
-10	-0.0440096671868219
-9	0.0110235572195794
-8	-0.0811831359582591
-7	-0.023975307166323
-6	0.0844228821754183
-5	0.0630759319844917
-4	-0.100795213160667
-3	-0.0192779003262279
-2	0.0233634069054486
-1	-0.00648367112787924
0	-0.0437108591805704
1	0.149731868525346
2	-0.229225521122701
3	0.126142246284520
4	-0.0717870431805463
5	0.0346802013191776
6	0.0707767154389678
7	-0.0173166285068989
8	0.0455159559506086
9	0.0736861418293399
10	-0.0953694075927833
11	-0.0197514228621139
12	-0.0107969776524840
13	-0.0793361319830858
14	0.0888010845325091
15	0.0646688723477729

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -0.6 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 2 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.0304057392382176 \tabularnewline
-14 & 0.122205061018990 \tabularnewline
-13 & -0.132081294099040 \tabularnewline
-12 & 0.0924560036048447 \tabularnewline
-11 & 0.0258745410366296 \tabularnewline
-10 & -0.0440096671868219 \tabularnewline
-9 & 0.0110235572195794 \tabularnewline
-8 & -0.0811831359582591 \tabularnewline
-7 & -0.023975307166323 \tabularnewline
-6 & 0.0844228821754183 \tabularnewline
-5 & 0.0630759319844917 \tabularnewline
-4 & -0.100795213160667 \tabularnewline
-3 & -0.0192779003262279 \tabularnewline
-2 & 0.0233634069054486 \tabularnewline
-1 & -0.00648367112787924 \tabularnewline
0 & -0.0437108591805704 \tabularnewline
1 & 0.149731868525346 \tabularnewline
2 & -0.229225521122701 \tabularnewline
3 & 0.126142246284520 \tabularnewline
4 & -0.0717870431805463 \tabularnewline
5 & 0.0346802013191776 \tabularnewline
6 & 0.0707767154389678 \tabularnewline
7 & -0.0173166285068989 \tabularnewline
8 & 0.0455159559506086 \tabularnewline
9 & 0.0736861418293399 \tabularnewline
10 & -0.0953694075927833 \tabularnewline
11 & -0.0197514228621139 \tabularnewline
12 & -0.0107969776524840 \tabularnewline
13 & -0.0793361319830858 \tabularnewline
14 & 0.0888010845325091 \tabularnewline
15 & 0.0646688723477729 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35608&T=1

[TABLE]
[ROW][C]Cross Correlation Function[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of X series[/C][C]-0.6[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]2[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]2[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]0.0304057392382176[/C][/ROW]
[ROW][C]-14[/C][C]0.122205061018990[/C][/ROW]
[ROW][C]-13[/C][C]-0.132081294099040[/C][/ROW]
[ROW][C]-12[/C][C]0.0924560036048447[/C][/ROW]
[ROW][C]-11[/C][C]0.0258745410366296[/C][/ROW]
[ROW][C]-10[/C][C]-0.0440096671868219[/C][/ROW]
[ROW][C]-9[/C][C]0.0110235572195794[/C][/ROW]
[ROW][C]-8[/C][C]-0.0811831359582591[/C][/ROW]
[ROW][C]-7[/C][C]-0.023975307166323[/C][/ROW]
[ROW][C]-6[/C][C]0.0844228821754183[/C][/ROW]
[ROW][C]-5[/C][C]0.0630759319844917[/C][/ROW]
[ROW][C]-4[/C][C]-0.100795213160667[/C][/ROW]
[ROW][C]-3[/C][C]-0.0192779003262279[/C][/ROW]
[ROW][C]-2[/C][C]0.0233634069054486[/C][/ROW]
[ROW][C]-1[/C][C]-0.00648367112787924[/C][/ROW]
[ROW][C]0[/C][C]-0.0437108591805704[/C][/ROW]
[ROW][C]1[/C][C]0.149731868525346[/C][/ROW]
[ROW][C]2[/C][C]-0.229225521122701[/C][/ROW]
[ROW][C]3[/C][C]0.126142246284520[/C][/ROW]
[ROW][C]4[/C][C]-0.0717870431805463[/C][/ROW]
[ROW][C]5[/C][C]0.0346802013191776[/C][/ROW]
[ROW][C]6[/C][C]0.0707767154389678[/C][/ROW]
[ROW][C]7[/C][C]-0.0173166285068989[/C][/ROW]
[ROW][C]8[/C][C]0.0455159559506086[/C][/ROW]
[ROW][C]9[/C][C]0.0736861418293399[/C][/ROW]
[ROW][C]10[/C][C]-0.0953694075927833[/C][/ROW]
[ROW][C]11[/C][C]-0.0197514228621139[/C][/ROW]
[ROW][C]12[/C][C]-0.0107969776524840[/C][/ROW]
[ROW][C]13[/C][C]-0.0793361319830858[/C][/ROW]
[ROW][C]14[/C][C]0.0888010845325091[/C][/ROW]
[ROW][C]15[/C][C]0.0646688723477729[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35608&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35608&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	-0.6
Degree of non-seasonal differencing (d) of X series	1
Degree of seasonal differencing (D) of X series	2
Seasonal Period (s)	12
Box-Cox transformation parameter (lambda) of Y series	1
Degree of non-seasonal differencing (d) of Y series	2
Degree of seasonal differencing (D) of Y series	1
k	rho(Y[t],X[t+k])
-15	0.0304057392382176
-14	0.122205061018990
-13	-0.132081294099040
-12	0.0924560036048447
-11	0.0258745410366296
-10	-0.0440096671868219
-9	0.0110235572195794
-8	-0.0811831359582591
-7	-0.023975307166323
-6	0.0844228821754183
-5	0.0630759319844917
-4	-0.100795213160667
-3	-0.0192779003262279
-2	0.0233634069054486
-1	-0.00648367112787924
0	-0.0437108591805704
1	0.149731868525346
2	-0.229225521122701
3	0.126142246284520
4	-0.0717870431805463
5	0.0346802013191776
6	0.0707767154389678
7	-0.0173166285068989
8	0.0455159559506086
9	0.0736861418293399
10	-0.0953694075927833
11	-0.0197514228621139
12	-0.0107969776524840
13	-0.0793361319830858
14	0.0888010845325091
15	0.0646688723477729

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = -0.6 ; par2 = 1 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 1 ;

Parameters (R input):

par1 = -0.6 ; par2 = 1 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 1 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',xlab='Lag (k)'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Cross Correlation Function',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
a<-table.element(a,par7)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'k',header=TRUE)
a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
a<-table.row.end(a)
mylength <- length(r$acf)
myhalf <- floor((mylength-1)/2)
for (i in 1:mylength) {
a<-table.row.start(a)
a<-table.element(a,i-myhalf-1,header=TRUE)
a<-table.element(a,r$acf[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

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