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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 28 Nov 2007 09:39:04 -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/t11962695815te5c53q67oegs8.htm/, Retrieved Thu, 02 May 2024 06:34:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7161, Retrieved Thu, 02 May 2024 06:34:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [vraag 6] [2007-11-28 16:39:04] [a04e235f237a7727ba8ea7d6bf8ed02e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,22
0,07
1,38
0,22
0,54
0,13
-0,68
0,03
-0,42
0,83
-0,52
0,77
0,09
1,07
1,93
1,51
0,40
-0,56
0,10
-0,07
0,39
-0,11
-0,73
2,27
-0,99
0,61
0,10
0,69
-1,03
0,10
-0,48
0,82
-0,29
0,05
-0,68
1,20
0,53
0,51
0,61
0,67
0,00
-0,07
0,09
1,22
-1,57
0,02
-0,80
1,20
0,16
0,41
1,01
0,47
-0,11
-0,30
-0,59
-0,03
-0,23
0,41
-0,37
0,58
0,96
1,78
0,07
0,79
Dataseries Y:
Download CSV
Histogram 
-1584,2
-168,6
74,6
-1147,9
1613,8
-512,3
-625,9
-1409,0
450,7
-378,0
-502,8
790,1
14,5
-156,5
1900,3
-961,2
-582,0
993,6
-892,5
1395,5
111,5
-754,8
469,5
-306,7
42,0
-381,1
-27,0
-653,4
904,9
-285,0
-457,5
901,6
-738,8
115,1
1302,8
-1387,0
766,3
1325,1
-897,0
-545,4
1937,4
-1589,8
1351,8
-623,2
-394,1
1306,0
-608,1
-435,5
-130,1
-58,2
239,7
329,8

Tables (Output of Computation)





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=7161&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=7161&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7161&T=0

As an alternative you can also use a QR Code:  
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])
-120.457460920326676
-11-0.283995072147547
-10-0.090751430423519
-90.335917714949153
-8-0.389029596076946
-70.188187990896334
-60.182773858237241
-5-0.458973756572809
-40.44440964083747
-3-0.160478261810919
-2-0.188090849394688
-10.53132094644134
0-0.631719033041673
10.199794774425105
20.229658233996433
3-0.310095195360616
40.119146006165091
50.104013049483338
6-0.115121763275565
7-0.0422292170928779
80.216978645826350
9-0.216492163926904
10-0.0598898235574963
110.306324034517133
12-0.299648730831443

\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
-12 & 0.457460920326676 \tabularnewline
-11 & -0.283995072147547 \tabularnewline
-10 & -0.090751430423519 \tabularnewline
-9 & 0.335917714949153 \tabularnewline
-8 & -0.389029596076946 \tabularnewline
-7 & 0.188187990896334 \tabularnewline
-6 & 0.182773858237241 \tabularnewline
-5 & -0.458973756572809 \tabularnewline
-4 & 0.44440964083747 \tabularnewline
-3 & -0.160478261810919 \tabularnewline
-2 & -0.188090849394688 \tabularnewline
-1 & 0.53132094644134 \tabularnewline
0 & -0.631719033041673 \tabularnewline
1 & 0.199794774425105 \tabularnewline
2 & 0.229658233996433 \tabularnewline
3 & -0.310095195360616 \tabularnewline
4 & 0.119146006165091 \tabularnewline
5 & 0.104013049483338 \tabularnewline
6 & -0.115121763275565 \tabularnewline
7 & -0.0422292170928779 \tabularnewline
8 & 0.216978645826350 \tabularnewline
9 & -0.216492163926904 \tabularnewline
10 & -0.0598898235574963 \tabularnewline
11 & 0.306324034517133 \tabularnewline
12 & -0.299648730831443 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7161&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]-12[/C][C]0.457460920326676[/C][/ROW]
[ROW][C]-11[/C][C]-0.283995072147547[/C][/ROW]
[ROW][C]-10[/C][C]-0.090751430423519[/C][/ROW]
[ROW][C]-9[/C][C]0.335917714949153[/C][/ROW]
[ROW][C]-8[/C][C]-0.389029596076946[/C][/ROW]
[ROW][C]-7[/C][C]0.188187990896334[/C][/ROW]
[ROW][C]-6[/C][C]0.182773858237241[/C][/ROW]
[ROW][C]-5[/C][C]-0.458973756572809[/C][/ROW]
[ROW][C]-4[/C][C]0.44440964083747[/C][/ROW]
[ROW][C]-3[/C][C]-0.160478261810919[/C][/ROW]
[ROW][C]-2[/C][C]-0.188090849394688[/C][/ROW]
[ROW][C]-1[/C][C]0.53132094644134[/C][/ROW]
[ROW][C]0[/C][C]-0.631719033041673[/C][/ROW]
[ROW][C]1[/C][C]0.199794774425105[/C][/ROW]
[ROW][C]2[/C][C]0.229658233996433[/C][/ROW]
[ROW][C]3[/C][C]-0.310095195360616[/C][/ROW]
[ROW][C]4[/C][C]0.119146006165091[/C][/ROW]
[ROW][C]5[/C][C]0.104013049483338[/C][/ROW]
[ROW][C]6[/C][C]-0.115121763275565[/C][/ROW]
[ROW][C]7[/C][C]-0.0422292170928779[/C][/ROW]
[ROW][C]8[/C][C]0.216978645826350[/C][/ROW]
[ROW][C]9[/C][C]-0.216492163926904[/C][/ROW]
[ROW][C]10[/C][C]-0.0598898235574963[/C][/ROW]
[ROW][C]11[/C][C]0.306324034517133[/C][/ROW]
[ROW][C]12[/C][C]-0.299648730831443[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7161&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7161&T=1

As an alternative you can also use a QR Code:  
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])
-120.457460920326676
-11-0.283995072147547
-10-0.090751430423519
-90.335917714949153
-8-0.389029596076946
-70.188187990896334
-60.182773858237241
-5-0.458973756572809
-40.44440964083747
-3-0.160478261810919
-2-0.188090849394688
-10.53132094644134
0-0.631719033041673
10.199794774425105
20.229658233996433
3-0.310095195360616
40.119146006165091
50.104013049483338
6-0.115121763275565
7-0.0422292170928779
80.216978645826350
9-0.216492163926904
10-0.0598898235574963
110.306324034517133
12-0.299648730831443


Figures (Output of Computation)

Input Parameters & R Code

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')