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Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 26 Nov 2007 13:15:08 -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/2007/Nov/26/t1196107535j74p53iwn6nifpe.htm/, Retrieved Fri, 03 May 2024 03:04:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6673, Retrieved Fri, 03 May 2024 03:04:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [relatie import ec...] [2007-11-26 20:15:08] [e1de87d26bd88c28cdef9ffadea7aeba] [Current]
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Dataseries X:
6.1
5.8
6.2
5.8
5.9
6.7
5.9
3.8
1.7
1.4
1.8
3
3.6
4.8
4.3
4.2
2.9
4.9
7.2
8.7
9.1
8.9
9
11.6
9.6
9.1
9.2
10.8
11
8.5
6.5
7.2
7.8
8.7
7.8
7.5
7.7
7.5
8.3
7.9
10.4
11.5
14
11.9
11.9
10.3
11.3
9.9
8.9
9.2
8.8
6.7
7.1
6.6
7.2
5.1
5.3
6.4
8.1
8
Dataseries Y:
10837.3
11624.1
10509
10984.9
10649.1
10855.7
11677.4
10760.2
10046.2
10772.8
9987.7
8638.7
11063.7
11855.7
10684.5
11337.4
10478
11123.9
12909.3
11339.9
10462.2
12733.5
10519.2
10414.9
12476.8
12384.6
12266.7
12919.9
11497.3
12142
13919.4
12656.8
12034.1
13199.7
10881.3
11301.2
13643.9
12517
13981.1
14275.7
13435
13565.7
16216.3
12970
14079.9
14235
12213.4
12581
14130.4
14210.8
14378.5
13142.8
13714.7
13621.9
15379.8
14441.8
15354.8
15537.8
14552.7
14587.9




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 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=6673&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]2 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=6673&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6673&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 time2 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 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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.219403494379112
-120.370542466908157
-110.122156819298668
-100.387165206486301
-90.249803559224921
-80.108805680328946
-70.254600100527834
-60.0811321730896998
-5-0.0964632809725958
-40.0524044107038533
-3-0.137988951304196
-2-0.168523140426295
-10.0283765736257232
0-0.199782456669833
1-0.0430981389708262
20.136188444929186
3-0.0624534578268142
40.00402628214584195
50.173186033243661
6-0.0578631998375725
70.0275997782119931
80.0346791010242281
9-0.195131994334309
10-0.0826277756423792
11-0.0419712609206176
12-0.240077441082863
13-0.0567535953186282

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.219403494379112 \tabularnewline
-12 & 0.370542466908157 \tabularnewline
-11 & 0.122156819298668 \tabularnewline
-10 & 0.387165206486301 \tabularnewline
-9 & 0.249803559224921 \tabularnewline
-8 & 0.108805680328946 \tabularnewline
-7 & 0.254600100527834 \tabularnewline
-6 & 0.0811321730896998 \tabularnewline
-5 & -0.0964632809725958 \tabularnewline
-4 & 0.0524044107038533 \tabularnewline
-3 & -0.137988951304196 \tabularnewline
-2 & -0.168523140426295 \tabularnewline
-1 & 0.0283765736257232 \tabularnewline
0 & -0.199782456669833 \tabularnewline
1 & -0.0430981389708262 \tabularnewline
2 & 0.136188444929186 \tabularnewline
3 & -0.0624534578268142 \tabularnewline
4 & 0.00402628214584195 \tabularnewline
5 & 0.173186033243661 \tabularnewline
6 & -0.0578631998375725 \tabularnewline
7 & 0.0275997782119931 \tabularnewline
8 & 0.0346791010242281 \tabularnewline
9 & -0.195131994334309 \tabularnewline
10 & -0.0826277756423792 \tabularnewline
11 & -0.0419712609206176 \tabularnewline
12 & -0.240077441082863 \tabularnewline
13 & -0.0567535953186282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6673&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]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]-13[/C][C]0.219403494379112[/C][/ROW]
[ROW][C]-12[/C][C]0.370542466908157[/C][/ROW]
[ROW][C]-11[/C][C]0.122156819298668[/C][/ROW]
[ROW][C]-10[/C][C]0.387165206486301[/C][/ROW]
[ROW][C]-9[/C][C]0.249803559224921[/C][/ROW]
[ROW][C]-8[/C][C]0.108805680328946[/C][/ROW]
[ROW][C]-7[/C][C]0.254600100527834[/C][/ROW]
[ROW][C]-6[/C][C]0.0811321730896998[/C][/ROW]
[ROW][C]-5[/C][C]-0.0964632809725958[/C][/ROW]
[ROW][C]-4[/C][C]0.0524044107038533[/C][/ROW]
[ROW][C]-3[/C][C]-0.137988951304196[/C][/ROW]
[ROW][C]-2[/C][C]-0.168523140426295[/C][/ROW]
[ROW][C]-1[/C][C]0.0283765736257232[/C][/ROW]
[ROW][C]0[/C][C]-0.199782456669833[/C][/ROW]
[ROW][C]1[/C][C]-0.0430981389708262[/C][/ROW]
[ROW][C]2[/C][C]0.136188444929186[/C][/ROW]
[ROW][C]3[/C][C]-0.0624534578268142[/C][/ROW]
[ROW][C]4[/C][C]0.00402628214584195[/C][/ROW]
[ROW][C]5[/C][C]0.173186033243661[/C][/ROW]
[ROW][C]6[/C][C]-0.0578631998375725[/C][/ROW]
[ROW][C]7[/C][C]0.0275997782119931[/C][/ROW]
[ROW][C]8[/C][C]0.0346791010242281[/C][/ROW]
[ROW][C]9[/C][C]-0.195131994334309[/C][/ROW]
[ROW][C]10[/C][C]-0.0826277756423792[/C][/ROW]
[ROW][C]11[/C][C]-0.0419712609206176[/C][/ROW]
[ROW][C]12[/C][C]-0.240077441082863[/C][/ROW]
[ROW][C]13[/C][C]-0.0567535953186282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6673&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6673&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 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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.219403494379112
-120.370542466908157
-110.122156819298668
-100.387165206486301
-90.249803559224921
-80.108805680328946
-70.254600100527834
-60.0811321730896998
-5-0.0964632809725958
-40.0524044107038533
-3-0.137988951304196
-2-0.168523140426295
-10.0283765736257232
0-0.199782456669833
1-0.0430981389708262
20.136188444929186
3-0.0624534578268142
40.00402628214584195
50.173186033243661
6-0.0578631998375725
70.0275997782119931
80.0346791010242281
9-0.195131994334309
10-0.0826277756423792
11-0.0419712609206176
12-0.240077441082863
13-0.0567535953186282



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