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Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 26 Nov 2007 11:42:10 -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/t1196101950px72hcixy3au2a1.htm/, Retrieved Thu, 02 May 2024 17:10:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6622, Retrieved Thu, 02 May 2024 17:10:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Opdracht 4 Questi...] [2007-11-26 18:42:10] [cb172450b25aceeff04d58e88e905157] [Current]
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Dataseries X:
2,9
2,6
2,7
1,8
1,3
0,9
1,3
1,3
1,3
1,3
1,1
1,4
1,2
1,7
1,8
1,5
1
1,6
1,5
1,8
1,8
1,6
1,9
1,7
1,6
1,3
1,1
1,9
2,6
2,3
2,4
2,2
2
2,9
2,6
2,3
2,3
2,6
3,1
2,8
2,5
2,9
3,1
3,1
3,2
2,5
2,6
2,9
2,6
2,4
1,7
2
2,2
1,9
1,6
1,6
1,2
1,2
1,5
1,6
Dataseries Y:
20538.6
20667.5
20554.9
19982.3
19636.6
19587.9
19861.1
20164.6
20146.9
20192.8
20361.8
20639.7
21251.5
21313.1
21300.0
20477.3
20128.3
20079.5
20235.9
20444.8
20319.9
20384.9
20506.7
20796.5
21760.2
21971.6
21652.7
20702.7
20379.9
20240.1
20376.5
20680.4
20532.0
20749.2
20900.7
21141.8
21770.2
21792.6
21670.1
20810.5
20647.0
20312.9
20014.2
20491.2
20302.7
20641.0
20475.6
20703.0
21158.6
20866.8
20595.2
19373.1
18675.4
18737.5
18587.6
18798.3
18429.5
18485.1
18597.5
18615.1




Summary of compuational 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 compuational 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=6622&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]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=6622&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6622&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 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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0708282675350151
-120.237489082880797
-11-0.0739429649483029
-100.0637244574318397
-90.0216350490815133
-8-0.0409867322326197
-7-0.057855838899127
-6-0.164356056618760
-50.0749182579134201
-40.0107292825131925
-30.0889733807397064
-20.217368342183527
-10.0590465505003333
0-0.0867092187978307
10.0308394538043219
2-0.0515874509822210
30.0826994540948169
4-0.0809663530122904
5-0.0103112715806802
6-0.098221419291631
7-0.0275189156828362
80.0520328426407585
90.0458141111256454
100.131224025791271
110.0649507936925976
12-0.0136391469807710
13-0.0472799946884978

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0708282675350151 \tabularnewline
-12 & 0.237489082880797 \tabularnewline
-11 & -0.0739429649483029 \tabularnewline
-10 & 0.0637244574318397 \tabularnewline
-9 & 0.0216350490815133 \tabularnewline
-8 & -0.0409867322326197 \tabularnewline
-7 & -0.057855838899127 \tabularnewline
-6 & -0.164356056618760 \tabularnewline
-5 & 0.0749182579134201 \tabularnewline
-4 & 0.0107292825131925 \tabularnewline
-3 & 0.0889733807397064 \tabularnewline
-2 & 0.217368342183527 \tabularnewline
-1 & 0.0590465505003333 \tabularnewline
0 & -0.0867092187978307 \tabularnewline
1 & 0.0308394538043219 \tabularnewline
2 & -0.0515874509822210 \tabularnewline
3 & 0.0826994540948169 \tabularnewline
4 & -0.0809663530122904 \tabularnewline
5 & -0.0103112715806802 \tabularnewline
6 & -0.098221419291631 \tabularnewline
7 & -0.0275189156828362 \tabularnewline
8 & 0.0520328426407585 \tabularnewline
9 & 0.0458141111256454 \tabularnewline
10 & 0.131224025791271 \tabularnewline
11 & 0.0649507936925976 \tabularnewline
12 & -0.0136391469807710 \tabularnewline
13 & -0.0472799946884978 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6622&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]1[/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]-0.0708282675350151[/C][/ROW]
[ROW][C]-12[/C][C]0.237489082880797[/C][/ROW]
[ROW][C]-11[/C][C]-0.0739429649483029[/C][/ROW]
[ROW][C]-10[/C][C]0.0637244574318397[/C][/ROW]
[ROW][C]-9[/C][C]0.0216350490815133[/C][/ROW]
[ROW][C]-8[/C][C]-0.0409867322326197[/C][/ROW]
[ROW][C]-7[/C][C]-0.057855838899127[/C][/ROW]
[ROW][C]-6[/C][C]-0.164356056618760[/C][/ROW]
[ROW][C]-5[/C][C]0.0749182579134201[/C][/ROW]
[ROW][C]-4[/C][C]0.0107292825131925[/C][/ROW]
[ROW][C]-3[/C][C]0.0889733807397064[/C][/ROW]
[ROW][C]-2[/C][C]0.217368342183527[/C][/ROW]
[ROW][C]-1[/C][C]0.0590465505003333[/C][/ROW]
[ROW][C]0[/C][C]-0.0867092187978307[/C][/ROW]
[ROW][C]1[/C][C]0.0308394538043219[/C][/ROW]
[ROW][C]2[/C][C]-0.0515874509822210[/C][/ROW]
[ROW][C]3[/C][C]0.0826994540948169[/C][/ROW]
[ROW][C]4[/C][C]-0.0809663530122904[/C][/ROW]
[ROW][C]5[/C][C]-0.0103112715806802[/C][/ROW]
[ROW][C]6[/C][C]-0.098221419291631[/C][/ROW]
[ROW][C]7[/C][C]-0.0275189156828362[/C][/ROW]
[ROW][C]8[/C][C]0.0520328426407585[/C][/ROW]
[ROW][C]9[/C][C]0.0458141111256454[/C][/ROW]
[ROW][C]10[/C][C]0.131224025791271[/C][/ROW]
[ROW][C]11[/C][C]0.0649507936925976[/C][/ROW]
[ROW][C]12[/C][C]-0.0136391469807710[/C][/ROW]
[ROW][C]13[/C][C]-0.0472799946884978[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6622&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6622&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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0708282675350151
-120.237489082880797
-11-0.0739429649483029
-100.0637244574318397
-90.0216350490815133
-8-0.0409867322326197
-7-0.057855838899127
-6-0.164356056618760
-50.0749182579134201
-40.0107292825131925
-30.0889733807397064
-20.217368342183527
-10.0590465505003333
0-0.0867092187978307
10.0308394538043219
2-0.0515874509822210
30.0826994540948169
4-0.0809663530122904
5-0.0103112715806802
6-0.098221419291631
7-0.0275189156828362
80.0520328426407585
90.0458141111256454
100.131224025791271
110.0649507936925976
12-0.0136391469807710
13-0.0472799946884978



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