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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 28 Nov 2007 12:12:11 -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/2007/Nov/28/t1196276769f0g25uah67u2i8b.htm/, Retrieved Thu, 02 May 2024 04:15:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7237, Retrieved Thu, 02 May 2024 04:15:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsYannick Leroy, Nick Vandewalle, Jeroen Goetschalckx, Nick Van Hove, Jef Jacobs, Michiel Van den Broeck
Estimated Impact179
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Workshop 4: Q5] [2007-11-28 19:12:11] [9ec4fcc2bfe8b6d942eac6074e595603] [Current]
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Dataseries X:
21
14
10
14
12
10
12
9
14
23
17
16
7
9
9
14
12
23
12
15
6
6
1
3
-1
-4
-6
-9
-13
-13
-10
-12
-9
-15
-14
-18
-13
-2
-1
5
8
6
7
15
23
43
60
36
28
23
23
22
22
24
32
27
27
27
29
38
Dataseries Y:
106,7
110,2
125,9
100,1
106,4
114,8
81,3
87,0
104,2
108,0
105,0
94,5
92,0
95,9
108,8
103,4
102,1
110,1
83,2
82,7
106,8
113,7
102,5
96,6
92,1
95,6
102,3
98,6
98,2
104,5
84,0
73,8
103,9
106,0
97,2
102,6
89,0
93,8
116,7
106,8
98,5
118,7
90,0
91,9
113,3
113,1
104,1
108,7
96,7
101,0
116,9
105,8
99,0
129,4
83,0
88,9
115,9
104,2
113,4
112,2




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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=7237&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=7237&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7237&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-140.212653825907176
-130.414174246048791
-12-0.416416665885096
-11-0.240336197745657
-100.225491898030608
-9-0.0356252741481044
-80.0861168713394363
-70.255725211278776
-6-0.237696947153784
-5-0.165802123951401
-40.203256772887867
-3-0.288633075289773
-20.237912790799561
-10.683843004835062
0-0.673896221643855
1-0.239317081174733
20.291954309760295
3-0.215422827686756
40.144104882563159
50.260964573354814
6-0.247706085865900
7-0.0739269005826023
80.0509548437868219
9-0.228767614218501
100.234038279688702
110.428063489328244
12-0.40617127225651
13-0.197100607954882
140.205340725384309

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \tabularnewline
Seasonal Period (s) & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.212653825907176 \tabularnewline
-13 & 0.414174246048791 \tabularnewline
-12 & -0.416416665885096 \tabularnewline
-11 & -0.240336197745657 \tabularnewline
-10 & 0.225491898030608 \tabularnewline
-9 & -0.0356252741481044 \tabularnewline
-8 & 0.0861168713394363 \tabularnewline
-7 & 0.255725211278776 \tabularnewline
-6 & -0.237696947153784 \tabularnewline
-5 & -0.165802123951401 \tabularnewline
-4 & 0.203256772887867 \tabularnewline
-3 & -0.288633075289773 \tabularnewline
-2 & 0.237912790799561 \tabularnewline
-1 & 0.683843004835062 \tabularnewline
0 & -0.673896221643855 \tabularnewline
1 & -0.239317081174733 \tabularnewline
2 & 0.291954309760295 \tabularnewline
3 & -0.215422827686756 \tabularnewline
4 & 0.144104882563159 \tabularnewline
5 & 0.260964573354814 \tabularnewline
6 & -0.247706085865900 \tabularnewline
7 & -0.0739269005826023 \tabularnewline
8 & 0.0509548437868219 \tabularnewline
9 & -0.228767614218501 \tabularnewline
10 & 0.234038279688702 \tabularnewline
11 & 0.428063489328244 \tabularnewline
12 & -0.40617127225651 \tabularnewline
13 & -0.197100607954882 \tabularnewline
14 & 0.205340725384309 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7237&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]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]0.212653825907176[/C][/ROW]
[ROW][C]-13[/C][C]0.414174246048791[/C][/ROW]
[ROW][C]-12[/C][C]-0.416416665885096[/C][/ROW]
[ROW][C]-11[/C][C]-0.240336197745657[/C][/ROW]
[ROW][C]-10[/C][C]0.225491898030608[/C][/ROW]
[ROW][C]-9[/C][C]-0.0356252741481044[/C][/ROW]
[ROW][C]-8[/C][C]0.0861168713394363[/C][/ROW]
[ROW][C]-7[/C][C]0.255725211278776[/C][/ROW]
[ROW][C]-6[/C][C]-0.237696947153784[/C][/ROW]
[ROW][C]-5[/C][C]-0.165802123951401[/C][/ROW]
[ROW][C]-4[/C][C]0.203256772887867[/C][/ROW]
[ROW][C]-3[/C][C]-0.288633075289773[/C][/ROW]
[ROW][C]-2[/C][C]0.237912790799561[/C][/ROW]
[ROW][C]-1[/C][C]0.683843004835062[/C][/ROW]
[ROW][C]0[/C][C]-0.673896221643855[/C][/ROW]
[ROW][C]1[/C][C]-0.239317081174733[/C][/ROW]
[ROW][C]2[/C][C]0.291954309760295[/C][/ROW]
[ROW][C]3[/C][C]-0.215422827686756[/C][/ROW]
[ROW][C]4[/C][C]0.144104882563159[/C][/ROW]
[ROW][C]5[/C][C]0.260964573354814[/C][/ROW]
[ROW][C]6[/C][C]-0.247706085865900[/C][/ROW]
[ROW][C]7[/C][C]-0.0739269005826023[/C][/ROW]
[ROW][C]8[/C][C]0.0509548437868219[/C][/ROW]
[ROW][C]9[/C][C]-0.228767614218501[/C][/ROW]
[ROW][C]10[/C][C]0.234038279688702[/C][/ROW]
[ROW][C]11[/C][C]0.428063489328244[/C][/ROW]
[ROW][C]12[/C][C]-0.40617127225651[/C][/ROW]
[ROW][C]13[/C][C]-0.197100607954882[/C][/ROW]
[ROW][C]14[/C][C]0.205340725384309[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7237&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7237&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
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-140.212653825907176
-130.414174246048791
-12-0.416416665885096
-11-0.240336197745657
-100.225491898030608
-9-0.0356252741481044
-80.0861168713394363
-70.255725211278776
-6-0.237696947153784
-5-0.165802123951401
-40.203256772887867
-3-0.288633075289773
-20.237912790799561
-10.683843004835062
0-0.673896221643855
1-0.239317081174733
20.291954309760295
3-0.215422827686756
40.144104882563159
50.260964573354814
6-0.247706085865900
7-0.0739269005826023
80.0509548437868219
9-0.228767614218501
100.234038279688702
110.428063489328244
12-0.40617127225651
13-0.197100607954882
140.205340725384309



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