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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 30 Nov 2008 06:27:08 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/30/t1228051687wycihm734lgkefc.htm/, Retrieved Thu, 28 May 2026 17:26:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26500, Retrieved Thu, 28 May 2026 17:26:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact430

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [tijdreeks verkoop...] [2008-10-13 20:55:30] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   PD  [Univariate Data Series] [totale werkloosheid] [2008-10-19 15:02:07] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMPD    [Cross Correlation Function] [] [2008-11-28 11:47:25] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   P       [Cross Correlation Function] [Non Stationary Ti...] [2008-11-28 12:34:34] [063e4b67ad7d3a8a83eccec794cd5aa7]
-   P           [Cross Correlation Function] [Non Stationary Ti...] [2008-11-30 13:27:08] [6797a1f4a60918966297e9d9220cabc2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.4
7.2
7.1
6.9
6.8
6.8
6.8
6.9
6.7
6.6
6.5
6.4
6.3
6.3
6.3
6.5
6.6
6.5
6.4
6.5
6.7
7.1
7.1
7.2
7.2
7.3
7.3
7.3
7.3
7.4
7.6
7.6
7.6
7.7
7.8
7.9
8.1
8.1
8.1
8.2
8.2
8.2
8.2
8.2
8.2
8.3
8.3
8.4
8.4
8.4
8.3
8
8
8.2
8.6
8.7
8.7
8.5
8.4
8.4
8.4
8.5
8.5
8.5
8.5
8.5
8.4
8.4
8.4
8.5
8.6
8.6
8.6
8.6
8.5
8.4
8.4
8.3
8.2
8.1
8.2
8.1
8
7.9
7.8
7.7
7.7
7.9
7.8
7.6
7.4
7.3
7.1
7.1
7
7
7
6.9
6.8
6.7
6.6
6.6
Dataseries Y:
Download CSV
Histogram 
6.2
6.1
5.9
5.6
5.5
5.5
5.6
5.7
5.6
5.4
5.3
5.3
5.4
5.5
5.6
5.7
5.8
5.8
5.7
5.9
6.1
6.4
6.4
6.3
6.2
6.2
6.3
6.5
6.6
6.6
6.7
6.6
6.7
7
7.2
7.3
7.5
7.6
7.7
7.8
7.8
7.7
7.6
7.6
7.7
7.8
7.8
7.8
7.7
7.6
7.4
7.1
7.1
7.3
7.6
7.8
7.7
7.6
7.5
7.5
7.5
7.6
7.6
7.7
7.8
7.7
7.6
7.6
7.6
7.7
7.8
7.8
7.9
7.9
7.8
7.8
7.7
7.5
7.1
6.9
7.1
7.1
7.1
7
6.9
6.8
6.7
6.8
6.8
6.7
6.8
6.7
6.6
6.4
6.4
6.4
6.5
6.5
6.4
6.3
6.2
6.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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=26500&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=26500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26500&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.0208860023605408
-15-0.0679408116603103
-14-0.0412975651575063
-130.164993021710337
-120.00519218129126349
-11-0.0212058492573343
-10-0.107042094793175
-9-0.0530785925226922
-8-0.0522896368439364
-7-0.0528333765684841
-60.0661656613831124
-50.059491522803378
-40.133312186583054
-3-0.0126286216416844
-2-0.124718966622567
-1-0.358351132384543
0-0.318780740469716
10.272946680159371
20.306141457264804
30.145962131351192
40.0064395841887528
5-0.0929688313343116
6-0.166789495113987
7-0.0467029777132972
8-0.0280345805038501
9-0.0142971562866187
100.165494115181979
110.106466370378949
120.125268037128726
13-0.100746441707979
14-0.180164426181521
15-0.0876647036291715
160.079066152887071

\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 & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.0208860023605408 \tabularnewline
-15 & -0.0679408116603103 \tabularnewline
-14 & -0.0412975651575063 \tabularnewline
-13 & 0.164993021710337 \tabularnewline
-12 & 0.00519218129126349 \tabularnewline
-11 & -0.0212058492573343 \tabularnewline
-10 & -0.107042094793175 \tabularnewline
-9 & -0.0530785925226922 \tabularnewline
-8 & -0.0522896368439364 \tabularnewline
-7 & -0.0528333765684841 \tabularnewline
-6 & 0.0661656613831124 \tabularnewline
-5 & 0.059491522803378 \tabularnewline
-4 & 0.133312186583054 \tabularnewline
-3 & -0.0126286216416844 \tabularnewline
-2 & -0.124718966622567 \tabularnewline
-1 & -0.358351132384543 \tabularnewline
0 & -0.318780740469716 \tabularnewline
1 & 0.272946680159371 \tabularnewline
2 & 0.306141457264804 \tabularnewline
3 & 0.145962131351192 \tabularnewline
4 & 0.0064395841887528 \tabularnewline
5 & -0.0929688313343116 \tabularnewline
6 & -0.166789495113987 \tabularnewline
7 & -0.0467029777132972 \tabularnewline
8 & -0.0280345805038501 \tabularnewline
9 & -0.0142971562866187 \tabularnewline
10 & 0.165494115181979 \tabularnewline
11 & 0.106466370378949 \tabularnewline
12 & 0.125268037128726 \tabularnewline
13 & -0.100746441707979 \tabularnewline
14 & -0.180164426181521 \tabularnewline
15 & -0.0876647036291715 \tabularnewline
16 & 0.079066152887071 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26500&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]2[/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]-0.0208860023605408[/C][/ROW]
[ROW][C]-15[/C][C]-0.0679408116603103[/C][/ROW]
[ROW][C]-14[/C][C]-0.0412975651575063[/C][/ROW]
[ROW][C]-13[/C][C]0.164993021710337[/C][/ROW]
[ROW][C]-12[/C][C]0.00519218129126349[/C][/ROW]
[ROW][C]-11[/C][C]-0.0212058492573343[/C][/ROW]
[ROW][C]-10[/C][C]-0.107042094793175[/C][/ROW]
[ROW][C]-9[/C][C]-0.0530785925226922[/C][/ROW]
[ROW][C]-8[/C][C]-0.0522896368439364[/C][/ROW]
[ROW][C]-7[/C][C]-0.0528333765684841[/C][/ROW]
[ROW][C]-6[/C][C]0.0661656613831124[/C][/ROW]
[ROW][C]-5[/C][C]0.059491522803378[/C][/ROW]
[ROW][C]-4[/C][C]0.133312186583054[/C][/ROW]
[ROW][C]-3[/C][C]-0.0126286216416844[/C][/ROW]
[ROW][C]-2[/C][C]-0.124718966622567[/C][/ROW]
[ROW][C]-1[/C][C]-0.358351132384543[/C][/ROW]
[ROW][C]0[/C][C]-0.318780740469716[/C][/ROW]
[ROW][C]1[/C][C]0.272946680159371[/C][/ROW]
[ROW][C]2[/C][C]0.306141457264804[/C][/ROW]
[ROW][C]3[/C][C]0.145962131351192[/C][/ROW]
[ROW][C]4[/C][C]0.0064395841887528[/C][/ROW]
[ROW][C]5[/C][C]-0.0929688313343116[/C][/ROW]
[ROW][C]6[/C][C]-0.166789495113987[/C][/ROW]
[ROW][C]7[/C][C]-0.0467029777132972[/C][/ROW]
[ROW][C]8[/C][C]-0.0280345805038501[/C][/ROW]
[ROW][C]9[/C][C]-0.0142971562866187[/C][/ROW]
[ROW][C]10[/C][C]0.165494115181979[/C][/ROW]
[ROW][C]11[/C][C]0.106466370378949[/C][/ROW]
[ROW][C]12[/C][C]0.125268037128726[/C][/ROW]
[ROW][C]13[/C][C]-0.100746441707979[/C][/ROW]
[ROW][C]14[/C][C]-0.180164426181521[/C][/ROW]
[ROW][C]15[/C][C]-0.0876647036291715[/C][/ROW]
[ROW][C]16[/C][C]0.079066152887071[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26500&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.0208860023605408
-15-0.0679408116603103
-14-0.0412975651575063
-130.164993021710337
-120.00519218129126349
-11-0.0212058492573343
-10-0.107042094793175
-9-0.0530785925226922
-8-0.0522896368439364
-7-0.0528333765684841
-60.0661656613831124
-50.059491522803378
-40.133312186583054
-3-0.0126286216416844
-2-0.124718966622567
-1-0.358351132384543
0-0.318780740469716
10.272946680159371
20.306141457264804
30.145962131351192
40.0064395841887528
5-0.0929688313343116
6-0.166789495113987
7-0.0467029777132972
8-0.0280345805038501
9-0.0142971562866187
100.165494115181979
110.106466370378949
120.125268037128726
13-0.100746441707979
14-0.180164426181521
15-0.0876647036291715
160.079066152887071


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; 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')