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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 01 Dec 2008 15:54:30 -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/2008/Dec/01/t122817209977hx7431qstcd7q.htm/, Retrieved Sun, 05 May 2024 19:01:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27499, Retrieved Sun, 05 May 2024 19:01:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Q7] [2008-12-01 22:54:30] [95d95b0e883740fcbc85e18ec42dcafb] [Current]
-   P     [Cross Correlation Function] [Q8] [2008-12-01 23:06:45] [7173087adebe3e3a714c80ea2417b3eb]
-   P     [Cross Correlation Function] [Q8] [2008-12-01 23:15:57] [7173087adebe3e3a714c80ea2417b3eb]
-   P     [Cross Correlation Function] [Q8] [2008-12-01 23:23:16] [7173087adebe3e3a714c80ea2417b3eb]
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Dataseries X:
5014
6153
6441
5584
6427
6062
5589
6216
5809
4989
6706
7174
6122
8075
6292
6337
8576
6077
5931
6288
7167
6054
6468
6401
6927
7914
7728
8699
8522
6481
7502
7778
7424
6941
8574
9169
7701
9035
7158
8195
8124
7073
7017
7390
7776
6197
6889
7087
6485
7654
6501
6313
7826
6589
6729
5684
8105
6391
5901
6758
Dataseries Y:
2400
4700
3700
2900
2800
3000
3100
3700
3000
2000
1900
1900
1800
3400
3800
2800
3100
2100
2000
2500
2400
2500
3300
3100
3700
5600
3700
2900
4000
2900
2400
3300
3800
4400
4000
3100
2700
5200
4600
3700
3200
2400
2200
3200
3100
2300
2500
2900
2700
5000
3500
3000
3800
2800
2400
2700
2800
2700
2600
3100




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=27499&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=27499&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27499&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)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 series0
krho(Y[t],X[t+k])
-14-0.0616699052974327
-130.0458805484166633
-120.358116792038818
-110.079463074547824
-100.165462405796512
-90.319358018280782
-80.0586495769771034
-70.00813914541747888
-60.150337523661727
-50.0601693163859885
-40.033021594971134
-30.313874629003936
-20.121093842956822
-10.121425746092842
00.430047968023864
10.155984369957477
20.286577409330962
30.351328781529036
40.0480675342927629
50.0357040784236293
60.132964281823602
70.0146888740810288
8-0.115121342708297
90.163767540189427
100.092277261201719
110.0834655331713632
120.238353419526874
13-0.0206951590492552
14-0.00632340714380368

\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) & 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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & -0.0616699052974327 \tabularnewline
-13 & 0.0458805484166633 \tabularnewline
-12 & 0.358116792038818 \tabularnewline
-11 & 0.079463074547824 \tabularnewline
-10 & 0.165462405796512 \tabularnewline
-9 & 0.319358018280782 \tabularnewline
-8 & 0.0586495769771034 \tabularnewline
-7 & 0.00813914541747888 \tabularnewline
-6 & 0.150337523661727 \tabularnewline
-5 & 0.0601693163859885 \tabularnewline
-4 & 0.033021594971134 \tabularnewline
-3 & 0.313874629003936 \tabularnewline
-2 & 0.121093842956822 \tabularnewline
-1 & 0.121425746092842 \tabularnewline
0 & 0.430047968023864 \tabularnewline
1 & 0.155984369957477 \tabularnewline
2 & 0.286577409330962 \tabularnewline
3 & 0.351328781529036 \tabularnewline
4 & 0.0480675342927629 \tabularnewline
5 & 0.0357040784236293 \tabularnewline
6 & 0.132964281823602 \tabularnewline
7 & 0.0146888740810288 \tabularnewline
8 & -0.115121342708297 \tabularnewline
9 & 0.163767540189427 \tabularnewline
10 & 0.092277261201719 \tabularnewline
11 & 0.0834655331713632 \tabularnewline
12 & 0.238353419526874 \tabularnewline
13 & -0.0206951590492552 \tabularnewline
14 & -0.00632340714380368 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27499&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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]-0.0616699052974327[/C][/ROW]
[ROW][C]-13[/C][C]0.0458805484166633[/C][/ROW]
[ROW][C]-12[/C][C]0.358116792038818[/C][/ROW]
[ROW][C]-11[/C][C]0.079463074547824[/C][/ROW]
[ROW][C]-10[/C][C]0.165462405796512[/C][/ROW]
[ROW][C]-9[/C][C]0.319358018280782[/C][/ROW]
[ROW][C]-8[/C][C]0.0586495769771034[/C][/ROW]
[ROW][C]-7[/C][C]0.00813914541747888[/C][/ROW]
[ROW][C]-6[/C][C]0.150337523661727[/C][/ROW]
[ROW][C]-5[/C][C]0.0601693163859885[/C][/ROW]
[ROW][C]-4[/C][C]0.033021594971134[/C][/ROW]
[ROW][C]-3[/C][C]0.313874629003936[/C][/ROW]
[ROW][C]-2[/C][C]0.121093842956822[/C][/ROW]
[ROW][C]-1[/C][C]0.121425746092842[/C][/ROW]
[ROW][C]0[/C][C]0.430047968023864[/C][/ROW]
[ROW][C]1[/C][C]0.155984369957477[/C][/ROW]
[ROW][C]2[/C][C]0.286577409330962[/C][/ROW]
[ROW][C]3[/C][C]0.351328781529036[/C][/ROW]
[ROW][C]4[/C][C]0.0480675342927629[/C][/ROW]
[ROW][C]5[/C][C]0.0357040784236293[/C][/ROW]
[ROW][C]6[/C][C]0.132964281823602[/C][/ROW]
[ROW][C]7[/C][C]0.0146888740810288[/C][/ROW]
[ROW][C]8[/C][C]-0.115121342708297[/C][/ROW]
[ROW][C]9[/C][C]0.163767540189427[/C][/ROW]
[ROW][C]10[/C][C]0.092277261201719[/C][/ROW]
[ROW][C]11[/C][C]0.0834655331713632[/C][/ROW]
[ROW][C]12[/C][C]0.238353419526874[/C][/ROW]
[ROW][C]13[/C][C]-0.0206951590492552[/C][/ROW]
[ROW][C]14[/C][C]-0.00632340714380368[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27499&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27499&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)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 series0
krho(Y[t],X[t+k])
-14-0.0616699052974327
-130.0458805484166633
-120.358116792038818
-110.079463074547824
-100.165462405796512
-90.319358018280782
-80.0586495769771034
-70.00813914541747888
-60.150337523661727
-50.0601693163859885
-40.033021594971134
-30.313874629003936
-20.121093842956822
-10.121425746092842
00.430047968023864
10.155984369957477
20.286577409330962
30.351328781529036
40.0480675342927629
50.0357040784236293
60.132964281823602
70.0146888740810288
8-0.115121342708297
90.163767540189427
100.092277261201719
110.0834655331713632
120.238353419526874
13-0.0206951590492552
14-0.00632340714380368



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