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*Unverified author*

R Software Module

rwasp_cross.wasp

Title produced by software

Cross Correlation Function

Date of computation

Wed, 26 Nov 2008 12:12:49 -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/Nov/26/t1227726841gdqh84lf3zqm6c7.htm/, Retrieved Sat, 18 May 2024 16:05:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=25700, Retrieved Sat, 18 May 2024 16:05:38 +0000

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IsPrivate?

No (this computation is public)

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Estimated Impact

128

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

-       [Cross Correlation Function] [Q7 ] [2008-11-26 19:12:49] [fb0ffb935e9c1a725d69519be28b148f] [Current]

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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=25700&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=25700&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25700&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	-2
Degree of non-seasonal differencing (d) of X series	0
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	0
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-16	0.235893161017297
-15	0.342950428969147
-14	0.370036037827385
-13	0.332628814101364
-12	0.489472668096657
-11	0.434934072789499
-10	0.395578466415155
-9	0.515906286719524
-8	0.439878078806431
-7	0.447153905438169
-6	0.508642526708794
-5	0.512435910450268
-4	0.486953864570776
-3	0.586723940728935
-2	0.562149847984471
-1	0.593094248521912
0	0.912339646013153
1	0.622237909347791
2	0.564609883983152
3	0.590424246581245
4	0.529157761579938
5	0.511398170946628
6	0.525986269551063
7	0.492668911360594
8	0.402076433070086
9	0.513458906596972
10	0.457849821456807
11	0.459247723586902
12	0.519846903902967
13	0.392952887871441
14	0.389597163901541
15	0.390285854517179
16	0.308107359943462

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -2 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.235893161017297 \tabularnewline
-15 & 0.342950428969147 \tabularnewline
-14 & 0.370036037827385 \tabularnewline
-13 & 0.332628814101364 \tabularnewline
-12 & 0.489472668096657 \tabularnewline
-11 & 0.434934072789499 \tabularnewline
-10 & 0.395578466415155 \tabularnewline
-9 & 0.515906286719524 \tabularnewline
-8 & 0.439878078806431 \tabularnewline
-7 & 0.447153905438169 \tabularnewline
-6 & 0.508642526708794 \tabularnewline
-5 & 0.512435910450268 \tabularnewline
-4 & 0.486953864570776 \tabularnewline
-3 & 0.586723940728935 \tabularnewline
-2 & 0.562149847984471 \tabularnewline
-1 & 0.593094248521912 \tabularnewline
0 & 0.912339646013153 \tabularnewline
1 & 0.622237909347791 \tabularnewline
2 & 0.564609883983152 \tabularnewline
3 & 0.590424246581245 \tabularnewline
4 & 0.529157761579938 \tabularnewline
5 & 0.511398170946628 \tabularnewline
6 & 0.525986269551063 \tabularnewline
7 & 0.492668911360594 \tabularnewline
8 & 0.402076433070086 \tabularnewline
9 & 0.513458906596972 \tabularnewline
10 & 0.457849821456807 \tabularnewline
11 & 0.459247723586902 \tabularnewline
12 & 0.519846903902967 \tabularnewline
13 & 0.392952887871441 \tabularnewline
14 & 0.389597163901541 \tabularnewline
15 & 0.390285854517179 \tabularnewline
16 & 0.308107359943462 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25700&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]-2[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]0[/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]0[/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]-16[/C][C]0.235893161017297[/C][/ROW]
[ROW][C]-15[/C][C]0.342950428969147[/C][/ROW]
[ROW][C]-14[/C][C]0.370036037827385[/C][/ROW]
[ROW][C]-13[/C][C]0.332628814101364[/C][/ROW]
[ROW][C]-12[/C][C]0.489472668096657[/C][/ROW]
[ROW][C]-11[/C][C]0.434934072789499[/C][/ROW]
[ROW][C]-10[/C][C]0.395578466415155[/C][/ROW]
[ROW][C]-9[/C][C]0.515906286719524[/C][/ROW]
[ROW][C]-8[/C][C]0.439878078806431[/C][/ROW]
[ROW][C]-7[/C][C]0.447153905438169[/C][/ROW]
[ROW][C]-6[/C][C]0.508642526708794[/C][/ROW]
[ROW][C]-5[/C][C]0.512435910450268[/C][/ROW]
[ROW][C]-4[/C][C]0.486953864570776[/C][/ROW]
[ROW][C]-3[/C][C]0.586723940728935[/C][/ROW]
[ROW][C]-2[/C][C]0.562149847984471[/C][/ROW]
[ROW][C]-1[/C][C]0.593094248521912[/C][/ROW]
[ROW][C]0[/C][C]0.912339646013153[/C][/ROW]
[ROW][C]1[/C][C]0.622237909347791[/C][/ROW]
[ROW][C]2[/C][C]0.564609883983152[/C][/ROW]
[ROW][C]3[/C][C]0.590424246581245[/C][/ROW]
[ROW][C]4[/C][C]0.529157761579938[/C][/ROW]
[ROW][C]5[/C][C]0.511398170946628[/C][/ROW]
[ROW][C]6[/C][C]0.525986269551063[/C][/ROW]
[ROW][C]7[/C][C]0.492668911360594[/C][/ROW]
[ROW][C]8[/C][C]0.402076433070086[/C][/ROW]
[ROW][C]9[/C][C]0.513458906596972[/C][/ROW]
[ROW][C]10[/C][C]0.457849821456807[/C][/ROW]
[ROW][C]11[/C][C]0.459247723586902[/C][/ROW]
[ROW][C]12[/C][C]0.519846903902967[/C][/ROW]
[ROW][C]13[/C][C]0.392952887871441[/C][/ROW]
[ROW][C]14[/C][C]0.389597163901541[/C][/ROW]
[ROW][C]15[/C][C]0.390285854517179[/C][/ROW]
[ROW][C]16[/C][C]0.308107359943462[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25700&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25700&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	-2
Degree of non-seasonal differencing (d) of X series	0
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	0
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-16	0.235893161017297
-15	0.342950428969147
-14	0.370036037827385
-13	0.332628814101364
-12	0.489472668096657
-11	0.434934072789499
-10	0.395578466415155
-9	0.515906286719524
-8	0.439878078806431
-7	0.447153905438169
-6	0.508642526708794
-5	0.512435910450268
-4	0.486953864570776
-3	0.586723940728935
-2	0.562149847984471
-1	0.593094248521912
0	0.912339646013153
1	0.622237909347791
2	0.564609883983152
3	0.590424246581245
4	0.529157761579938
5	0.511398170946628
6	0.525986269551063
7	0.492668911360594
8	0.402076433070086
9	0.513458906596972
10	0.457849821456807
11	0.459247723586902
12	0.519846903902967
13	0.392952887871441
14	0.389597163901541
15	0.390285854517179
16	0.308107359943462

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = -2.0 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;

Parameters (R input):

par1 = -2.0 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; 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