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Description of Statistical Computation

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 computationTue, 16 Dec 2008 13:27:23 -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/16/t1229459283ko3wht17sc5uwjc.htm/, Retrieved Wed, 15 May 2024 09:19:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34182, Retrieved Wed, 15 May 2024 09:19:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

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] [paper cross corr ...] [2007-12-01 14:01:57] [22f18fc6a98517db16300404be421f9a]
-   PD    [Cross Correlation Function] [cross correlation...] [2008-12-16 20:27:23] [e8f764b122b426f433a1e1038b457077] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,5
7,6
7,9
7,9
8,1
8,2
8
7,5
6,8
6,5
6,6
7,6
8
8
7,7
7,5
7,6
7,7
7,9
7,8
7,5
7,5
7,1
7,5
7,5
7,6
7,7
7,7
7,9
8,1
8,2
8,2
8,1
7,9
7,3
6,9
6,6
6,7
6,9
7
7,1
7,2
7,1
6,9
7
6,8
6,4
6,7
6,7
6,4
6,3
6,2
6,5
6,8
6,8
6,5
6,3
5,9
5,9
6,4
Dataseries Y:
Download CSV
Histogram 
9,4
9,5
9,1
9
9,3
9,9
9,8
9,4
8,3
8
8,5
10,4
11,1
10,9
9,9
9,2
9,2
9,5
9,6
9,5
9,1
8,9
9
10,1
10,3
10,2
9,6
9,2
9,3
9,4
9,4
9,2
9
9
9
9,8
10
9,9
9,3
9
9
9,1
9,1
9,1
9,2
8,8
8,3
8,4
8,1
7,8
7,9
7,9
8
7,9
7,5
7,2
6,9
6,6
6,7
7,3

Tables (Output of Computation)





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=34182&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=34182&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34182&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 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 series1
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])
-130.102226558395027
-120.225519677031276
-110.334334909624196
-100.284828493057326
-90.139845415968636
-8-0.00310624281107846
-7-0.00556759092089453
-60.123336111616333
-50.341106303987446
-40.470945103841503
-30.444977343870692
-20.246339027637014
-10.021711454942483
0-0.116725940928399
1-0.0585134458944938
20.120649050361075
30.26724436420292
40.254099260542199
50.122777202875240
6-0.00573956284123052
7-0.0405531284643507
8-0.00104257976703997
90.0350177822785199
100.00358991383702485
11-0.0651128683374065
12-0.113694935832468
13-0.0830516892775075

\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 & 1 \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 & 0.102226558395027 \tabularnewline
-12 & 0.225519677031276 \tabularnewline
-11 & 0.334334909624196 \tabularnewline
-10 & 0.284828493057326 \tabularnewline
-9 & 0.139845415968636 \tabularnewline
-8 & -0.00310624281107846 \tabularnewline
-7 & -0.00556759092089453 \tabularnewline
-6 & 0.123336111616333 \tabularnewline
-5 & 0.341106303987446 \tabularnewline
-4 & 0.470945103841503 \tabularnewline
-3 & 0.444977343870692 \tabularnewline
-2 & 0.246339027637014 \tabularnewline
-1 & 0.021711454942483 \tabularnewline
0 & -0.116725940928399 \tabularnewline
1 & -0.0585134458944938 \tabularnewline
2 & 0.120649050361075 \tabularnewline
3 & 0.26724436420292 \tabularnewline
4 & 0.254099260542199 \tabularnewline
5 & 0.122777202875240 \tabularnewline
6 & -0.00573956284123052 \tabularnewline
7 & -0.0405531284643507 \tabularnewline
8 & -0.00104257976703997 \tabularnewline
9 & 0.0350177822785199 \tabularnewline
10 & 0.00358991383702485 \tabularnewline
11 & -0.0651128683374065 \tabularnewline
12 & -0.113694935832468 \tabularnewline
13 & -0.0830516892775075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34182&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]1[/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]0.102226558395027[/C][/ROW]
[ROW][C]-12[/C][C]0.225519677031276[/C][/ROW]
[ROW][C]-11[/C][C]0.334334909624196[/C][/ROW]
[ROW][C]-10[/C][C]0.284828493057326[/C][/ROW]
[ROW][C]-9[/C][C]0.139845415968636[/C][/ROW]
[ROW][C]-8[/C][C]-0.00310624281107846[/C][/ROW]
[ROW][C]-7[/C][C]-0.00556759092089453[/C][/ROW]
[ROW][C]-6[/C][C]0.123336111616333[/C][/ROW]
[ROW][C]-5[/C][C]0.341106303987446[/C][/ROW]
[ROW][C]-4[/C][C]0.470945103841503[/C][/ROW]
[ROW][C]-3[/C][C]0.444977343870692[/C][/ROW]
[ROW][C]-2[/C][C]0.246339027637014[/C][/ROW]
[ROW][C]-1[/C][C]0.021711454942483[/C][/ROW]
[ROW][C]0[/C][C]-0.116725940928399[/C][/ROW]
[ROW][C]1[/C][C]-0.0585134458944938[/C][/ROW]
[ROW][C]2[/C][C]0.120649050361075[/C][/ROW]
[ROW][C]3[/C][C]0.26724436420292[/C][/ROW]
[ROW][C]4[/C][C]0.254099260542199[/C][/ROW]
[ROW][C]5[/C][C]0.122777202875240[/C][/ROW]
[ROW][C]6[/C][C]-0.00573956284123052[/C][/ROW]
[ROW][C]7[/C][C]-0.0405531284643507[/C][/ROW]
[ROW][C]8[/C][C]-0.00104257976703997[/C][/ROW]
[ROW][C]9[/C][C]0.0350177822785199[/C][/ROW]
[ROW][C]10[/C][C]0.00358991383702485[/C][/ROW]
[ROW][C]11[/C][C]-0.0651128683374065[/C][/ROW]
[ROW][C]12[/C][C]-0.113694935832468[/C][/ROW]
[ROW][C]13[/C][C]-0.0830516892775075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34182&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34182&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 series0
Degree of seasonal differencing (D) of X series1
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])
-130.102226558395027
-120.225519677031276
-110.334334909624196
-100.284828493057326
-90.139845415968636
-8-0.00310624281107846
-7-0.00556759092089453
-60.123336111616333
-50.341106303987446
-40.470945103841503
-30.444977343870692
-20.246339027637014
-10.021711454942483
0-0.116725940928399
1-0.0585134458944938
20.120649050361075
30.26724436420292
40.254099260542199
50.122777202875240
6-0.00573956284123052
7-0.0405531284643507
8-0.00104257976703997
90.0350177822785199
100.00358991383702485
11-0.0651128683374065
12-0.113694935832468
13-0.0830516892775075


Figures (Output of Computation)

Input Parameters & R Code

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