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Author

*The author of this computation has been verified*

R Software Module

rwasp_cross.wasp

Title produced by software

Cross Correlation Function

Date of computation

Sun, 21 Dec 2008 10:56:34 -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/t1229882416yzrehr6m0syygtv.htm/, Retrieved Fri, 17 May 2024 07:01:05 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35718, Retrieved Fri, 17 May 2024 07:01:05 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

131

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

-       [Cross Correlation Function] [Paper Cross Corre...] [2008-12-21 17:56:34] [0da3c04827d8ef68db874351a2e09488] [Current]

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Dataseries X:

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Dataseries Y:

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Histogram

1.7
1.4
1.8
1.7
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5

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	'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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35718&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]0 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=35718&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35718&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	0 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	-0.2
Degree of non-seasonal differencing (d) of X series	1
Degree of seasonal differencing (D) of X series	0
Seasonal Period (s)	12
Box-Cox transformation parameter (lambda) of Y series	-0.4
Degree of non-seasonal differencing (d) of Y series	1
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-14	-0.125592909748007
-13	-0.189243084457390
-12	-0.229278680842559
-11	0.105790092604088
-10	0.143016345856294
-9	-0.144949942576707
-8	0.0928322159605901
-7	0.111986508806801
-6	0.0490210441272331
-5	0.0736882404638944
-4	0.123749769160360
-3	-0.0409736402807841
-2	-0.132845019803438
-1	0.0126333294152817
0	0.455377076014475
1	0.0647995685393124
2	-0.252917005000933
3	0.0894553871125675
4	0.0719354319065444
5	0.0911994389579708
6	0.0151216026970155
7	-0.184797377009304
8	-0.0107506243375257
9	-0.133858118639693
10	-0.0055785921076508
11	0.134938069348679
12	-0.289352917311313
13	-0.173213616005077
14	0.145054314774574

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -0.2 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & -0.4 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & -0.125592909748007 \tabularnewline
-13 & -0.189243084457390 \tabularnewline
-12 & -0.229278680842559 \tabularnewline
-11 & 0.105790092604088 \tabularnewline
-10 & 0.143016345856294 \tabularnewline
-9 & -0.144949942576707 \tabularnewline
-8 & 0.0928322159605901 \tabularnewline
-7 & 0.111986508806801 \tabularnewline
-6 & 0.0490210441272331 \tabularnewline
-5 & 0.0736882404638944 \tabularnewline
-4 & 0.123749769160360 \tabularnewline
-3 & -0.0409736402807841 \tabularnewline
-2 & -0.132845019803438 \tabularnewline
-1 & 0.0126333294152817 \tabularnewline
0 & 0.455377076014475 \tabularnewline
1 & 0.0647995685393124 \tabularnewline
2 & -0.252917005000933 \tabularnewline
3 & 0.0894553871125675 \tabularnewline
4 & 0.0719354319065444 \tabularnewline
5 & 0.0911994389579708 \tabularnewline
6 & 0.0151216026970155 \tabularnewline
7 & -0.184797377009304 \tabularnewline
8 & -0.0107506243375257 \tabularnewline
9 & -0.133858118639693 \tabularnewline
10 & -0.0055785921076508 \tabularnewline
11 & 0.134938069348679 \tabularnewline
12 & -0.289352917311313 \tabularnewline
13 & -0.173213616005077 \tabularnewline
14 & 0.145054314774574 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35718&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]-0.2[/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]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]-0.4[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]-0.125592909748007[/C][/ROW]
[ROW][C]-13[/C][C]-0.189243084457390[/C][/ROW]
[ROW][C]-12[/C][C]-0.229278680842559[/C][/ROW]
[ROW][C]-11[/C][C]0.105790092604088[/C][/ROW]
[ROW][C]-10[/C][C]0.143016345856294[/C][/ROW]
[ROW][C]-9[/C][C]-0.144949942576707[/C][/ROW]
[ROW][C]-8[/C][C]0.0928322159605901[/C][/ROW]
[ROW][C]-7[/C][C]0.111986508806801[/C][/ROW]
[ROW][C]-6[/C][C]0.0490210441272331[/C][/ROW]
[ROW][C]-5[/C][C]0.0736882404638944[/C][/ROW]
[ROW][C]-4[/C][C]0.123749769160360[/C][/ROW]
[ROW][C]-3[/C][C]-0.0409736402807841[/C][/ROW]
[ROW][C]-2[/C][C]-0.132845019803438[/C][/ROW]
[ROW][C]-1[/C][C]0.0126333294152817[/C][/ROW]
[ROW][C]0[/C][C]0.455377076014475[/C][/ROW]
[ROW][C]1[/C][C]0.0647995685393124[/C][/ROW]
[ROW][C]2[/C][C]-0.252917005000933[/C][/ROW]
[ROW][C]3[/C][C]0.0894553871125675[/C][/ROW]
[ROW][C]4[/C][C]0.0719354319065444[/C][/ROW]
[ROW][C]5[/C][C]0.0911994389579708[/C][/ROW]
[ROW][C]6[/C][C]0.0151216026970155[/C][/ROW]
[ROW][C]7[/C][C]-0.184797377009304[/C][/ROW]
[ROW][C]8[/C][C]-0.0107506243375257[/C][/ROW]
[ROW][C]9[/C][C]-0.133858118639693[/C][/ROW]
[ROW][C]10[/C][C]-0.0055785921076508[/C][/ROW]
[ROW][C]11[/C][C]0.134938069348679[/C][/ROW]
[ROW][C]12[/C][C]-0.289352917311313[/C][/ROW]
[ROW][C]13[/C][C]-0.173213616005077[/C][/ROW]
[ROW][C]14[/C][C]0.145054314774574[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35718&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35718&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	-0.2
Degree of non-seasonal differencing (d) of X series	1
Degree of seasonal differencing (D) of X series	0
Seasonal Period (s)	12
Box-Cox transformation parameter (lambda) of Y series	-0.4
Degree of non-seasonal differencing (d) of Y series	1
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-14	-0.125592909748007
-13	-0.189243084457390
-12	-0.229278680842559
-11	0.105790092604088
-10	0.143016345856294
-9	-0.144949942576707
-8	0.0928322159605901
-7	0.111986508806801
-6	0.0490210441272331
-5	0.0736882404638944
-4	0.123749769160360
-3	-0.0409736402807841
-2	-0.132845019803438
-1	0.0126333294152817
0	0.455377076014475
1	0.0647995685393124
2	-0.252917005000933
3	0.0894553871125675
4	0.0719354319065444
5	0.0911994389579708
6	0.0151216026970155
7	-0.184797377009304
8	-0.0107506243375257
9	-0.133858118639693
10	-0.0055785921076508
11	0.134938069348679
12	-0.289352917311313
13	-0.173213616005077
14	0.145054314774574

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = -0.2 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = -0.4 ; par6 = 1 ; par7 = 0 ;

Parameters (R input):

par1 = -0.2 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = -0.4 ; par6 = 1 ; par7 = 0 ;

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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code