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Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 28 Nov 2007 13:46:06 -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/t1196282148jvdt8echgqdlce9.htm/, Retrieved Thu, 02 May 2024 08:26:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7277, Retrieved Thu, 02 May 2024 08:26:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [cross correlation...] [2007-11-28 20:46:06] [cb51ec34031fa6f7825ad77351c1efd8] [Current]
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Dataseries X:
40,3
38,4
46,9
56,1
57,4
58,5
66,6
71,8
80,7
78,2
85,0
87,6
88,6
95,0
96,3
83,3
96,9
103,4
99,3
103,8
113,4
111,5
114,2
90,6
90,8
96,4
90,0
92,1
97,2
95,1
88,5
91,0
90,5
75,0
66,3
66,0
68,4
70,6
83,9
90,1
90,6
87,1
90,8
94,1
99,8
96,8
87,0
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
Dataseries Y:
544.5
619.8
777.6
640.4
633.0
722.0
860.1
495.1
692.8
766.7
648.5
640.0
681.6
752.5
1031.7
685.5
887.6
655.4
944.2
626.6
1221.8
939.6
886.6
811.3
774.7
910.6
911.6
697.7
829.8
824.3
885.6
538.9
686.0
878.7
812.7
640.4
773.9
795.9
836.3
876.1
851.7
692.4
877.3
536.8
705.9
951.0
755.7
695.5
744.8
672.1
666.6
760.8
756.0
604.4
883.9
527.9
756.2
812.9
655.6
707.6




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=7277&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=7277&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7277&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 series0
krho(Y[t],X[t+k])
-140.0801832172778907
-130.0997887296222577
-12-0.141494852114224
-110.0952545742377858
-100.0716652104987874
-90.115181624878456
-8-0.0522214487920906
-7-0.0635207667853468
-6-0.177973759474449
-50.104116009150649
-4-0.114676076228186
-30.0455380206695241
-20.00539887968728061
-1-0.0622346922357944
0-0.182696788974005
10.056807559047559
2-0.173228452784005
3-0.0589644099332136
4-0.169457642863588
5-0.142480255941367
6-0.105101509088042
70.0207820794579947
8-0.250723850821163
9-0.0560548323098697
100.013421114849688
11-0.182679253222098
12-0.172805299741973
130.0522710445933236
140.116275688623868

\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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.0801832172778907 \tabularnewline
-13 & 0.0997887296222577 \tabularnewline
-12 & -0.141494852114224 \tabularnewline
-11 & 0.0952545742377858 \tabularnewline
-10 & 0.0716652104987874 \tabularnewline
-9 & 0.115181624878456 \tabularnewline
-8 & -0.0522214487920906 \tabularnewline
-7 & -0.0635207667853468 \tabularnewline
-6 & -0.177973759474449 \tabularnewline
-5 & 0.104116009150649 \tabularnewline
-4 & -0.114676076228186 \tabularnewline
-3 & 0.0455380206695241 \tabularnewline
-2 & 0.00539887968728061 \tabularnewline
-1 & -0.0622346922357944 \tabularnewline
0 & -0.182696788974005 \tabularnewline
1 & 0.056807559047559 \tabularnewline
2 & -0.173228452784005 \tabularnewline
3 & -0.0589644099332136 \tabularnewline
4 & -0.169457642863588 \tabularnewline
5 & -0.142480255941367 \tabularnewline
6 & -0.105101509088042 \tabularnewline
7 & 0.0207820794579947 \tabularnewline
8 & -0.250723850821163 \tabularnewline
9 & -0.0560548323098697 \tabularnewline
10 & 0.013421114849688 \tabularnewline
11 & -0.182679253222098 \tabularnewline
12 & -0.172805299741973 \tabularnewline
13 & 0.0522710445933236 \tabularnewline
14 & 0.116275688623868 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7277&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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]0.0801832172778907[/C][/ROW]
[ROW][C]-13[/C][C]0.0997887296222577[/C][/ROW]
[ROW][C]-12[/C][C]-0.141494852114224[/C][/ROW]
[ROW][C]-11[/C][C]0.0952545742377858[/C][/ROW]
[ROW][C]-10[/C][C]0.0716652104987874[/C][/ROW]
[ROW][C]-9[/C][C]0.115181624878456[/C][/ROW]
[ROW][C]-8[/C][C]-0.0522214487920906[/C][/ROW]
[ROW][C]-7[/C][C]-0.0635207667853468[/C][/ROW]
[ROW][C]-6[/C][C]-0.177973759474449[/C][/ROW]
[ROW][C]-5[/C][C]0.104116009150649[/C][/ROW]
[ROW][C]-4[/C][C]-0.114676076228186[/C][/ROW]
[ROW][C]-3[/C][C]0.0455380206695241[/C][/ROW]
[ROW][C]-2[/C][C]0.00539887968728061[/C][/ROW]
[ROW][C]-1[/C][C]-0.0622346922357944[/C][/ROW]
[ROW][C]0[/C][C]-0.182696788974005[/C][/ROW]
[ROW][C]1[/C][C]0.056807559047559[/C][/ROW]
[ROW][C]2[/C][C]-0.173228452784005[/C][/ROW]
[ROW][C]3[/C][C]-0.0589644099332136[/C][/ROW]
[ROW][C]4[/C][C]-0.169457642863588[/C][/ROW]
[ROW][C]5[/C][C]-0.142480255941367[/C][/ROW]
[ROW][C]6[/C][C]-0.105101509088042[/C][/ROW]
[ROW][C]7[/C][C]0.0207820794579947[/C][/ROW]
[ROW][C]8[/C][C]-0.250723850821163[/C][/ROW]
[ROW][C]9[/C][C]-0.0560548323098697[/C][/ROW]
[ROW][C]10[/C][C]0.013421114849688[/C][/ROW]
[ROW][C]11[/C][C]-0.182679253222098[/C][/ROW]
[ROW][C]12[/C][C]-0.172805299741973[/C][/ROW]
[ROW][C]13[/C][C]0.0522710445933236[/C][/ROW]
[ROW][C]14[/C][C]0.116275688623868[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7277&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7277&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 series0
krho(Y[t],X[t+k])
-140.0801832172778907
-130.0997887296222577
-12-0.141494852114224
-110.0952545742377858
-100.0716652104987874
-90.115181624878456
-8-0.0522214487920906
-7-0.0635207667853468
-6-0.177973759474449
-50.104116009150649
-4-0.114676076228186
-30.0455380206695241
-20.00539887968728061
-1-0.0622346922357944
0-0.182696788974005
10.056807559047559
2-0.173228452784005
3-0.0589644099332136
4-0.169457642863588
5-0.142480255941367
6-0.105101509088042
70.0207820794579947
8-0.250723850821163
9-0.0560548323098697
100.013421114849688
11-0.182679253222098
12-0.172805299741973
130.0522710445933236
140.116275688623868



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; 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) 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')