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Author

*The author of this computation has been verified*

R Software Module

rwasp_cross.wasp

Title produced by software

Cross Correlation Function

Date of computation

Sun, 21 Dec 2008 14:37:45 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/21/t1229895602vifl5w25bf0hje6.htm/, Retrieved Sat, 18 May 2024 12:23:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35848, Retrieved Sat, 18 May 2024 12:23:59 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

131

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Standard Deviation-Mean Plot] [Paper ] [2008-12-21 17:01:52] [74be16979710d4c4e7c6647856088456]
F RMPD    [Cross Correlation Function] [Paper ] [2008-12-21 21:37:45] [3452c99afdd85d4fde81272403cd85da] [Current]

Feedback Forum

2009-01-08 14:04:01 [Aurélie Van Impe] [reply] 
Je kan moeilijk met de toekomst van x de huidige waarde van y verklaren he! Je moet dit dan beschouwen als het verklaren van de toekomstige waarde van x, door middel van de huidige waarde van Y. Er is inderdaad een negatief verband te zien. Dit kon je ook een beetje waarnemen in de correlation matrix hierboven. De diagonaal liep op het einde dalend, wat wijst op een negatief verband. Uit de tabel op je blog had je ook nog wel het een en ander kunnen halen.

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Dataseries X:

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Histogram

Boxplots

1.8
1.7
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5
4.8
3.2

Dataseries Y:

Download CSV

Histogram

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35848&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35848&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35848&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	1
Degree of non-seasonal differencing (d) of X series	0
Degree of seasonal differencing (D) of X series	0
Seasonal Period (s)	12
Box-Cox transformation parameter (lambda) of Y series	1
Degree of non-seasonal differencing (d) of Y series	0
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-14	0.128880419349632
-13	0.120568325300844
-12	0.104882227304588
-11	0.0791772934930154
-10	0.0557257723940132
-9	0.0432841612593062
-8	0.00219922739036623
-7	-0.0355759145177588
-6	-0.0844311163975321
-5	-0.131038397669575
-4	-0.188506143128344
-3	-0.241329602425488
-2	-0.303779177755222
-1	-0.371895526240381
0	-0.423264338862939
1	-0.456410522856267
2	-0.465611130315552
3	-0.471665117603273
4	-0.479409681984472
5	-0.46011050497488
6	-0.435654587788145
7	-0.411196072180123
8	-0.398218904032695
9	-0.38723568163926
10	-0.373250347568025
11	-0.371174354663277
12	-0.374031334508639
13	-0.361753374610164
14	-0.334813251061988

\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) & 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 & 0.128880419349632 \tabularnewline
-13 & 0.120568325300844 \tabularnewline
-12 & 0.104882227304588 \tabularnewline
-11 & 0.0791772934930154 \tabularnewline
-10 & 0.0557257723940132 \tabularnewline
-9 & 0.0432841612593062 \tabularnewline
-8 & 0.00219922739036623 \tabularnewline
-7 & -0.0355759145177588 \tabularnewline
-6 & -0.0844311163975321 \tabularnewline
-5 & -0.131038397669575 \tabularnewline
-4 & -0.188506143128344 \tabularnewline
-3 & -0.241329602425488 \tabularnewline
-2 & -0.303779177755222 \tabularnewline
-1 & -0.371895526240381 \tabularnewline
0 & -0.423264338862939 \tabularnewline
1 & -0.456410522856267 \tabularnewline
2 & -0.465611130315552 \tabularnewline
3 & -0.471665117603273 \tabularnewline
4 & -0.479409681984472 \tabularnewline
5 & -0.46011050497488 \tabularnewline
6 & -0.435654587788145 \tabularnewline
7 & -0.411196072180123 \tabularnewline
8 & -0.398218904032695 \tabularnewline
9 & -0.38723568163926 \tabularnewline
10 & -0.373250347568025 \tabularnewline
11 & -0.371174354663277 \tabularnewline
12 & -0.374031334508639 \tabularnewline
13 & -0.361753374610164 \tabularnewline
14 & -0.334813251061988 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35848&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]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]0.128880419349632[/C][/ROW]
[ROW][C]-13[/C][C]0.120568325300844[/C][/ROW]
[ROW][C]-12[/C][C]0.104882227304588[/C][/ROW]
[ROW][C]-11[/C][C]0.0791772934930154[/C][/ROW]
[ROW][C]-10[/C][C]0.0557257723940132[/C][/ROW]
[ROW][C]-9[/C][C]0.0432841612593062[/C][/ROW]
[ROW][C]-8[/C][C]0.00219922739036623[/C][/ROW]
[ROW][C]-7[/C][C]-0.0355759145177588[/C][/ROW]
[ROW][C]-6[/C][C]-0.0844311163975321[/C][/ROW]
[ROW][C]-5[/C][C]-0.131038397669575[/C][/ROW]
[ROW][C]-4[/C][C]-0.188506143128344[/C][/ROW]
[ROW][C]-3[/C][C]-0.241329602425488[/C][/ROW]
[ROW][C]-2[/C][C]-0.303779177755222[/C][/ROW]
[ROW][C]-1[/C][C]-0.371895526240381[/C][/ROW]
[ROW][C]0[/C][C]-0.423264338862939[/C][/ROW]
[ROW][C]1[/C][C]-0.456410522856267[/C][/ROW]
[ROW][C]2[/C][C]-0.465611130315552[/C][/ROW]
[ROW][C]3[/C][C]-0.471665117603273[/C][/ROW]
[ROW][C]4[/C][C]-0.479409681984472[/C][/ROW]
[ROW][C]5[/C][C]-0.46011050497488[/C][/ROW]
[ROW][C]6[/C][C]-0.435654587788145[/C][/ROW]
[ROW][C]7[/C][C]-0.411196072180123[/C][/ROW]
[ROW][C]8[/C][C]-0.398218904032695[/C][/ROW]
[ROW][C]9[/C][C]-0.38723568163926[/C][/ROW]
[ROW][C]10[/C][C]-0.373250347568025[/C][/ROW]
[ROW][C]11[/C][C]-0.371174354663277[/C][/ROW]
[ROW][C]12[/C][C]-0.374031334508639[/C][/ROW]
[ROW][C]13[/C][C]-0.361753374610164[/C][/ROW]
[ROW][C]14[/C][C]-0.334813251061988[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35848&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35848&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
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	1
Degree of non-seasonal differencing (d) of X series	0
Degree of seasonal differencing (D) of X series	0
Seasonal Period (s)	12
Box-Cox transformation parameter (lambda) of Y series	1
Degree of non-seasonal differencing (d) of Y series	0
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-14	0.128880419349632
-13	0.120568325300844
-12	0.104882227304588
-11	0.0791772934930154
-10	0.0557257723940132
-9	0.0432841612593062
-8	0.00219922739036623
-7	-0.0355759145177588
-6	-0.0844311163975321
-5	-0.131038397669575
-4	-0.188506143128344
-3	-0.241329602425488
-2	-0.303779177755222
-1	-0.371895526240381
0	-0.423264338862939
1	-0.456410522856267
2	-0.465611130315552
3	-0.471665117603273
4	-0.479409681984472
5	-0.46011050497488
6	-0.435654587788145
7	-0.411196072180123
8	-0.398218904032695
9	-0.38723568163926
10	-0.373250347568025
11	-0.371174354663277
12	-0.374031334508639
13	-0.361753374610164
14	-0.334813251061988

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;

Parameters (R input):

par1 = 1 ; par2 = 0 ; 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) 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code