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*Unverified author*

R Software Module

rwasp_cross.wasp

Title produced by software

Cross Correlation Function

Date of computation

Thu, 13 Dec 2007 07:41:47 -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/2007/Dec/13/t1197555986icno8l24g11e5nm.htm/, Retrieved Sun, 05 May 2024 12:42:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3577, Retrieved Sun, 05 May 2024 12:42:08 +0000

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No (this computation is public)

User-defined keywords

bridome

Estimated Impact

180

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

-       [Cross Correlation Function] [paper w3] [2007-12-13 14:41:47] [9cd804c1ac16035a4cb2da1c6dfdb61e] [Current]

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Dataseries Y:

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Summary of compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3577&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3577&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3577&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 compuational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	1
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	1
Degree of non-seasonal differencing (d) of Y series	1
Degree of seasonal differencing (D) of Y series	1
k	rho(Y[t],X[t+k])
-16	0.0389980355577857
-15	0.0647774124671742
-14	-0.0158734096559784
-13	-0.0214863333613837
-12	0.0612904263009091
-11	-0.0704396432460332
-10	0.0895503153820217
-9	-0.0874934580875952
-8	-0.0518597702859247
-7	-0.0408471207315729
-6	0.000751520346439315
-5	-0.0435156877880968
-4	0.0265248562303791
-3	0.137425330191796
-2	-0.0280214643498634
-1	-0.0303163827953036
0	-0.154168899221775
1	-0.0417468979108980
2	0.120473793267205
3	-0.0437133076298571
4	-0.0437298085789993
5	-0.073640435831668
6	0.00821898292916192
7	-0.00100678163935554
8	-0.00968113482942047
9	-0.00339888787847214
10	0.00481156489901458
11	0.0118038840495740
12	-0.100794173998337
13	-0.116316952468899
14	-0.00826202523548362
15	-0.0615738231104983
16	-0.0243310410580727

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1 \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 & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.0389980355577857 \tabularnewline
-15 & 0.0647774124671742 \tabularnewline
-14 & -0.0158734096559784 \tabularnewline
-13 & -0.0214863333613837 \tabularnewline
-12 & 0.0612904263009091 \tabularnewline
-11 & -0.0704396432460332 \tabularnewline
-10 & 0.0895503153820217 \tabularnewline
-9 & -0.0874934580875952 \tabularnewline
-8 & -0.0518597702859247 \tabularnewline
-7 & -0.0408471207315729 \tabularnewline
-6 & 0.000751520346439315 \tabularnewline
-5 & -0.0435156877880968 \tabularnewline
-4 & 0.0265248562303791 \tabularnewline
-3 & 0.137425330191796 \tabularnewline
-2 & -0.0280214643498634 \tabularnewline
-1 & -0.0303163827953036 \tabularnewline
0 & -0.154168899221775 \tabularnewline
1 & -0.0417468979108980 \tabularnewline
2 & 0.120473793267205 \tabularnewline
3 & -0.0437133076298571 \tabularnewline
4 & -0.0437298085789993 \tabularnewline
5 & -0.073640435831668 \tabularnewline
6 & 0.00821898292916192 \tabularnewline
7 & -0.00100678163935554 \tabularnewline
8 & -0.00968113482942047 \tabularnewline
9 & -0.00339888787847214 \tabularnewline
10 & 0.00481156489901458 \tabularnewline
11 & 0.0118038840495740 \tabularnewline
12 & -0.100794173998337 \tabularnewline
13 & -0.116316952468899 \tabularnewline
14 & -0.00826202523548362 \tabularnewline
15 & -0.0615738231104983 \tabularnewline
16 & -0.0243310410580727 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3577&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]1[/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]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]0.0389980355577857[/C][/ROW]
[ROW][C]-15[/C][C]0.0647774124671742[/C][/ROW]
[ROW][C]-14[/C][C]-0.0158734096559784[/C][/ROW]
[ROW][C]-13[/C][C]-0.0214863333613837[/C][/ROW]
[ROW][C]-12[/C][C]0.0612904263009091[/C][/ROW]
[ROW][C]-11[/C][C]-0.0704396432460332[/C][/ROW]
[ROW][C]-10[/C][C]0.0895503153820217[/C][/ROW]
[ROW][C]-9[/C][C]-0.0874934580875952[/C][/ROW]
[ROW][C]-8[/C][C]-0.0518597702859247[/C][/ROW]
[ROW][C]-7[/C][C]-0.0408471207315729[/C][/ROW]
[ROW][C]-6[/C][C]0.000751520346439315[/C][/ROW]
[ROW][C]-5[/C][C]-0.0435156877880968[/C][/ROW]
[ROW][C]-4[/C][C]0.0265248562303791[/C][/ROW]
[ROW][C]-3[/C][C]0.137425330191796[/C][/ROW]
[ROW][C]-2[/C][C]-0.0280214643498634[/C][/ROW]
[ROW][C]-1[/C][C]-0.0303163827953036[/C][/ROW]
[ROW][C]0[/C][C]-0.154168899221775[/C][/ROW]
[ROW][C]1[/C][C]-0.0417468979108980[/C][/ROW]
[ROW][C]2[/C][C]0.120473793267205[/C][/ROW]
[ROW][C]3[/C][C]-0.0437133076298571[/C][/ROW]
[ROW][C]4[/C][C]-0.0437298085789993[/C][/ROW]
[ROW][C]5[/C][C]-0.073640435831668[/C][/ROW]
[ROW][C]6[/C][C]0.00821898292916192[/C][/ROW]
[ROW][C]7[/C][C]-0.00100678163935554[/C][/ROW]
[ROW][C]8[/C][C]-0.00968113482942047[/C][/ROW]
[ROW][C]9[/C][C]-0.00339888787847214[/C][/ROW]
[ROW][C]10[/C][C]0.00481156489901458[/C][/ROW]
[ROW][C]11[/C][C]0.0118038840495740[/C][/ROW]
[ROW][C]12[/C][C]-0.100794173998337[/C][/ROW]
[ROW][C]13[/C][C]-0.116316952468899[/C][/ROW]
[ROW][C]14[/C][C]-0.00826202523548362[/C][/ROW]
[ROW][C]15[/C][C]-0.0615738231104983[/C][/ROW]
[ROW][C]16[/C][C]-0.0243310410580727[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3577&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3577&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	1
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	1
Degree of non-seasonal differencing (d) of Y series	1
Degree of seasonal differencing (D) of Y series	1
k	rho(Y[t],X[t+k])
-16	0.0389980355577857
-15	0.0647774124671742
-14	-0.0158734096559784
-13	-0.0214863333613837
-12	0.0612904263009091
-11	-0.0704396432460332
-10	0.0895503153820217
-9	-0.0874934580875952
-8	-0.0518597702859247
-7	-0.0408471207315729
-6	0.000751520346439315
-5	-0.0435156877880968
-4	0.0265248562303791
-3	0.137425330191796
-2	-0.0280214643498634
-1	-0.0303163827953036
0	-0.154168899221775
1	-0.0417468979108980
2	0.120473793267205
3	-0.0437133076298571
4	-0.0437298085789993
5	-0.073640435831668
6	0.00821898292916192
7	-0.00100678163935554
8	-0.00968113482942047
9	-0.00339888787847214
10	0.00481156489901458
11	0.0118038840495740
12	-0.100794173998337
13	-0.116316952468899
14	-0.00826202523548362
15	-0.0615738231104983
16	-0.0243310410580727

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

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

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) x <- 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

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Figures (Output of Computation)

Input Parameters & R Code