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Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 13 Dec 2009 08:33:46 -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/2009/Dec/13/t1260718524w72n4b9e33na88c.htm/, Retrieved Sat, 27 Apr 2024 21:19:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67330, Retrieved Sat, 27 Apr 2024 21:19:29 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsETP(37)
Estimated Impact89
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Cross Correlation...] [2009-12-13 15:33:46] [af31b947d6acaef3c71f428c4bb503e9] [Current]
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Dataseries X:
1,43
1,43
1,43
1,43
1,43
1,43
1,44
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,57
1,58
1,58
1,58
1,58
1,59
1,6
1,6
1,61
1,61
1,61
1,62
1,63
1,63
1,64
1,64
1,64
1,64
1,64
1,65
1,65
1,65
1,65
Dataseries Y:
0,51
0,51
0,51
0,51
0,52
0,52
0,52
0,53
0,53
0,52
0,52
0,52
0,52
0,52
0,52
0,52
0,52
0,52
0,52
0,53
0,53
0,53
0,54
0,54
0,54
0,54
0,54
0,54
0,54
0,54
0,54
0,54
0,53
0,53
0,53
0,53
0,53
0,54
0,55
0,55
0,55
0,55
0,55
0,55
0,55
0,55
0,56
0,56
0,56
0,56
0,56
0,55
0,56
0,55
0,55
0,56
0,55
0,55
0,55
0,55




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=67330&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=67330&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67330&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 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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-140.113692523526232
-130.173364046529449
-120.233035569532667
-110.287212377950411
-100.346336915791274
-90.403969675916624
-80.435695229715898
-70.470404338946199
-60.518067051339537
-50.565729763732875
-40.616376031557239
-30.68044829882122
-20.7445205660852
-10.817543499642259
00.872665100613162
10.846931520637864
20.81821438523154
30.786513694394191
40.74884589269479
50.689820806701628
60.659611893579791
70.633405917327915
80.60334618197763
90.590168397774566
100.558616884708768
110.525573593927457
120.491038525430633
130.455011679218296
140.418984833005959

\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 & 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
-14 & 0.113692523526232 \tabularnewline
-13 & 0.173364046529449 \tabularnewline
-12 & 0.233035569532667 \tabularnewline
-11 & 0.287212377950411 \tabularnewline
-10 & 0.346336915791274 \tabularnewline
-9 & 0.403969675916624 \tabularnewline
-8 & 0.435695229715898 \tabularnewline
-7 & 0.470404338946199 \tabularnewline
-6 & 0.518067051339537 \tabularnewline
-5 & 0.565729763732875 \tabularnewline
-4 & 0.616376031557239 \tabularnewline
-3 & 0.68044829882122 \tabularnewline
-2 & 0.7445205660852 \tabularnewline
-1 & 0.817543499642259 \tabularnewline
0 & 0.872665100613162 \tabularnewline
1 & 0.846931520637864 \tabularnewline
2 & 0.81821438523154 \tabularnewline
3 & 0.786513694394191 \tabularnewline
4 & 0.74884589269479 \tabularnewline
5 & 0.689820806701628 \tabularnewline
6 & 0.659611893579791 \tabularnewline
7 & 0.633405917327915 \tabularnewline
8 & 0.60334618197763 \tabularnewline
9 & 0.590168397774566 \tabularnewline
10 & 0.558616884708768 \tabularnewline
11 & 0.525573593927457 \tabularnewline
12 & 0.491038525430633 \tabularnewline
13 & 0.455011679218296 \tabularnewline
14 & 0.418984833005959 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67330&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]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]-14[/C][C]0.113692523526232[/C][/ROW]
[ROW][C]-13[/C][C]0.173364046529449[/C][/ROW]
[ROW][C]-12[/C][C]0.233035569532667[/C][/ROW]
[ROW][C]-11[/C][C]0.287212377950411[/C][/ROW]
[ROW][C]-10[/C][C]0.346336915791274[/C][/ROW]
[ROW][C]-9[/C][C]0.403969675916624[/C][/ROW]
[ROW][C]-8[/C][C]0.435695229715898[/C][/ROW]
[ROW][C]-7[/C][C]0.470404338946199[/C][/ROW]
[ROW][C]-6[/C][C]0.518067051339537[/C][/ROW]
[ROW][C]-5[/C][C]0.565729763732875[/C][/ROW]
[ROW][C]-4[/C][C]0.616376031557239[/C][/ROW]
[ROW][C]-3[/C][C]0.68044829882122[/C][/ROW]
[ROW][C]-2[/C][C]0.7445205660852[/C][/ROW]
[ROW][C]-1[/C][C]0.817543499642259[/C][/ROW]
[ROW][C]0[/C][C]0.872665100613162[/C][/ROW]
[ROW][C]1[/C][C]0.846931520637864[/C][/ROW]
[ROW][C]2[/C][C]0.81821438523154[/C][/ROW]
[ROW][C]3[/C][C]0.786513694394191[/C][/ROW]
[ROW][C]4[/C][C]0.74884589269479[/C][/ROW]
[ROW][C]5[/C][C]0.689820806701628[/C][/ROW]
[ROW][C]6[/C][C]0.659611893579791[/C][/ROW]
[ROW][C]7[/C][C]0.633405917327915[/C][/ROW]
[ROW][C]8[/C][C]0.60334618197763[/C][/ROW]
[ROW][C]9[/C][C]0.590168397774566[/C][/ROW]
[ROW][C]10[/C][C]0.558616884708768[/C][/ROW]
[ROW][C]11[/C][C]0.525573593927457[/C][/ROW]
[ROW][C]12[/C][C]0.491038525430633[/C][/ROW]
[ROW][C]13[/C][C]0.455011679218296[/C][/ROW]
[ROW][C]14[/C][C]0.418984833005959[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67330&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67330&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 series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-140.113692523526232
-130.173364046529449
-120.233035569532667
-110.287212377950411
-100.346336915791274
-90.403969675916624
-80.435695229715898
-70.470404338946199
-60.518067051339537
-50.565729763732875
-40.616376031557239
-30.68044829882122
-20.7445205660852
-10.817543499642259
00.872665100613162
10.846931520637864
20.81821438523154
30.786513694394191
40.74884589269479
50.689820806701628
60.659611893579791
70.633405917327915
80.60334618197763
90.590168397774566
100.558616884708768
110.525573593927457
120.491038525430633
130.455011679218296
140.418984833005959



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