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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, 02 Dec 2008 12:52:31 -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/02/t1228247595jiynx23zleqj9w1.htm/, Retrieved Sun, 19 May 2024 09:25:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28292, Retrieved Sun, 19 May 2024 09:25:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsnon stationary time series cross correlation
Estimated Impact174

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD    [Cross Correlation Function] [non stationary ti...] [2008-12-02 19:52:31] [74c7506a1ea162af3aa8be25bcd05d28] [Current]
F   PD      [Cross Correlation Function] [non stationary ti...] [2008-12-02 20:08:18] [47f64d63202c1921bd27f3073f07a153]
F   P         [Cross Correlation Function] [non stat time ser...] [2008-12-03 11:54:56] [c96f3dce3a823a83b6ede18389e1cfd4]
F   P           [Cross Correlation Function] [non stat time ser...] [2008-12-03 13:42:47] [c96f3dce3a823a83b6ede18389e1cfd4]
F   P         [Cross Correlation Function] [non stationary ti...] [2008-12-03 13:42:33] [47f64d63202c1921bd27f3073f07a153]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28292&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]0 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=28292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28292&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 time0 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 series1
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])
-14-0.0384780040817884
-13-0.065429942735084
-120.0581211881817296
-110.0612119921626746
-100.0553201670645378
-9-0.0157523320654252
-8-0.086862573334376
-7-0.0720968676932234
-60.0268967114555676
-50.149227513211778
-40.172095198022298
-30.0331874944183715
-2-0.184903216781832
-1-0.345437166025734
0-0.0955127730649726
10.0745699373428269
20.188039439269017
30.161724639097616
40.0324744451936540
5-0.0752753102002924
6-0.0581237469708134
70.0195787879079959
80.0396616572655227
90.0169449410109530
10-0.0479423252059174
11-0.120289954229364
12-0.00363753191520808
130.0033488152135731
140.0523924858876921

\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 & 1 \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 & -0.0384780040817884 \tabularnewline
-13 & -0.065429942735084 \tabularnewline
-12 & 0.0581211881817296 \tabularnewline
-11 & 0.0612119921626746 \tabularnewline
-10 & 0.0553201670645378 \tabularnewline
-9 & -0.0157523320654252 \tabularnewline
-8 & -0.086862573334376 \tabularnewline
-7 & -0.0720968676932234 \tabularnewline
-6 & 0.0268967114555676 \tabularnewline
-5 & 0.149227513211778 \tabularnewline
-4 & 0.172095198022298 \tabularnewline
-3 & 0.0331874944183715 \tabularnewline
-2 & -0.184903216781832 \tabularnewline
-1 & -0.345437166025734 \tabularnewline
0 & -0.0955127730649726 \tabularnewline
1 & 0.0745699373428269 \tabularnewline
2 & 0.188039439269017 \tabularnewline
3 & 0.161724639097616 \tabularnewline
4 & 0.0324744451936540 \tabularnewline
5 & -0.0752753102002924 \tabularnewline
6 & -0.0581237469708134 \tabularnewline
7 & 0.0195787879079959 \tabularnewline
8 & 0.0396616572655227 \tabularnewline
9 & 0.0169449410109530 \tabularnewline
10 & -0.0479423252059174 \tabularnewline
11 & -0.120289954229364 \tabularnewline
12 & -0.00363753191520808 \tabularnewline
13 & 0.0033488152135731 \tabularnewline
14 & 0.0523924858876921 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28292&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]1[/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]-0.0384780040817884[/C][/ROW]
[ROW][C]-13[/C][C]-0.065429942735084[/C][/ROW]
[ROW][C]-12[/C][C]0.0581211881817296[/C][/ROW]
[ROW][C]-11[/C][C]0.0612119921626746[/C][/ROW]
[ROW][C]-10[/C][C]0.0553201670645378[/C][/ROW]
[ROW][C]-9[/C][C]-0.0157523320654252[/C][/ROW]
[ROW][C]-8[/C][C]-0.086862573334376[/C][/ROW]
[ROW][C]-7[/C][C]-0.0720968676932234[/C][/ROW]
[ROW][C]-6[/C][C]0.0268967114555676[/C][/ROW]
[ROW][C]-5[/C][C]0.149227513211778[/C][/ROW]
[ROW][C]-4[/C][C]0.172095198022298[/C][/ROW]
[ROW][C]-3[/C][C]0.0331874944183715[/C][/ROW]
[ROW][C]-2[/C][C]-0.184903216781832[/C][/ROW]
[ROW][C]-1[/C][C]-0.345437166025734[/C][/ROW]
[ROW][C]0[/C][C]-0.0955127730649726[/C][/ROW]
[ROW][C]1[/C][C]0.0745699373428269[/C][/ROW]
[ROW][C]2[/C][C]0.188039439269017[/C][/ROW]
[ROW][C]3[/C][C]0.161724639097616[/C][/ROW]
[ROW][C]4[/C][C]0.0324744451936540[/C][/ROW]
[ROW][C]5[/C][C]-0.0752753102002924[/C][/ROW]
[ROW][C]6[/C][C]-0.0581237469708134[/C][/ROW]
[ROW][C]7[/C][C]0.0195787879079959[/C][/ROW]
[ROW][C]8[/C][C]0.0396616572655227[/C][/ROW]
[ROW][C]9[/C][C]0.0169449410109530[/C][/ROW]
[ROW][C]10[/C][C]-0.0479423252059174[/C][/ROW]
[ROW][C]11[/C][C]-0.120289954229364[/C][/ROW]
[ROW][C]12[/C][C]-0.00363753191520808[/C][/ROW]
[ROW][C]13[/C][C]0.0033488152135731[/C][/ROW]
[ROW][C]14[/C][C]0.0523924858876921[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28292&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 series1
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])
-14-0.0384780040817884
-13-0.065429942735084
-120.0581211881817296
-110.0612119921626746
-100.0553201670645378
-9-0.0157523320654252
-8-0.086862573334376
-7-0.0720968676932234
-60.0268967114555676
-50.149227513211778
-40.172095198022298
-30.0331874944183715
-2-0.184903216781832
-1-0.345437166025734
0-0.0955127730649726
10.0745699373428269
20.188039439269017
30.161724639097616
40.0324744451936540
5-0.0752753102002924
6-0.0581237469708134
70.0195787879079959
80.0396616572655227
90.0169449410109530
10-0.0479423252059174
11-0.120289954229364
12-0.00363753191520808
130.0033488152135731
140.0523924858876921


Figures (Output of Computation)

Input Parameters & R Code

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