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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 computationThu, 02 Dec 2010 12:14:54 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/02/t1291291979a1fitsjjt0gp35h.htm/, Retrieved Sun, 05 May 2024 15:57:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104228, Retrieved Sun, 05 May 2024 15:57:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

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] [appelen] [2009-12-17 16:17:08] [7773f496f69461f4a67891f0ef752622]
-    D    [Cross Correlation Function] [Appelen Jonagold ...] [2010-12-02 12:14:54] [2fa539864aa87c5da4977c85c6885fac] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.25 
1.23 
1.2 
1.15 
1.13 
1.17 
1.22 
1.21 
1.15 
1.24 
1.16 
1.3 
1.3 
1.26 
1.29 
1.29 
1.35 
1.35 
1.45 
1.43 
1.43 
1.41 
1.46 
1.78 
1.79 
1.66 
1.56 
1.53 
1.47 
1.47 
1.45 
1.41 
1.45 
1.46 
1.38 
1.45 
1.48 
1.48 
1.51 
1.45 
1.42 
1.43 
1.43 
1.44 
1.41 
1.35 
1.43 
1.72 
1.63 
1.57 
1.47 
1.39 
1.34 
1.28 
1.26 
1.26
Dataseries Y:
Download CSV
Histogram 
1.89 
1.84 
1.83 
1.8 
1.77 
1.75 
1.73 
1.71 
1.73 
1.75 
1.78 
1.99 
1.98 
1.94 
1.95 
1.91 
1.90 
1.86 
1.90 
1.88 
1.87 
1.89 
1.97 
2.14 
2.15 
2.06 
1.95 
1.94 
1.92 
1.89 
1.87 
1.87 
1.88 
1.92 
1.94 
2.14 
2.10 
2.02 
1.96 
1.93 
1.87 
1.85 
1.87 
1.88 
1.90 
1.90 
2.00 
2.21 
2.07 
1.96 
1.92 
1.82 
1.75 
1.70 
1.70 
1.73

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104228&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104228&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104228&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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])
-14-0.0609021951123717
-130.0220286974167309
-120.116118111084721
-110.0987214761789366
-100.0781768726338735
-90.065168643036225
-8-0.00113328931540061
-7-0.0134996650553267
-60.00983617856041736
-50.0668765615476844
-40.138629100374880
-30.240388307050598
-20.383871620398819
-10.583971492286922
00.787626801836342
10.726962468697328
20.574098353040878
30.415765858871866
40.277577839849854
50.185671811074286
60.108182252653627
70.0798323765144957
80.0914523267007784
90.145041586156897
100.180960031962631
110.251812636047097
120.307697063932656
130.206204695377565
140.06547991124933

\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 & -0.0609021951123717 \tabularnewline
-13 & 0.0220286974167309 \tabularnewline
-12 & 0.116118111084721 \tabularnewline
-11 & 0.0987214761789366 \tabularnewline
-10 & 0.0781768726338735 \tabularnewline
-9 & 0.065168643036225 \tabularnewline
-8 & -0.00113328931540061 \tabularnewline
-7 & -0.0134996650553267 \tabularnewline
-6 & 0.00983617856041736 \tabularnewline
-5 & 0.0668765615476844 \tabularnewline
-4 & 0.138629100374880 \tabularnewline
-3 & 0.240388307050598 \tabularnewline
-2 & 0.383871620398819 \tabularnewline
-1 & 0.583971492286922 \tabularnewline
0 & 0.787626801836342 \tabularnewline
1 & 0.726962468697328 \tabularnewline
2 & 0.574098353040878 \tabularnewline
3 & 0.415765858871866 \tabularnewline
4 & 0.277577839849854 \tabularnewline
5 & 0.185671811074286 \tabularnewline
6 & 0.108182252653627 \tabularnewline
7 & 0.0798323765144957 \tabularnewline
8 & 0.0914523267007784 \tabularnewline
9 & 0.145041586156897 \tabularnewline
10 & 0.180960031962631 \tabularnewline
11 & 0.251812636047097 \tabularnewline
12 & 0.307697063932656 \tabularnewline
13 & 0.206204695377565 \tabularnewline
14 & 0.06547991124933 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104228&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]-0.0609021951123717[/C][/ROW]
[ROW][C]-13[/C][C]0.0220286974167309[/C][/ROW]
[ROW][C]-12[/C][C]0.116118111084721[/C][/ROW]
[ROW][C]-11[/C][C]0.0987214761789366[/C][/ROW]
[ROW][C]-10[/C][C]0.0781768726338735[/C][/ROW]
[ROW][C]-9[/C][C]0.065168643036225[/C][/ROW]
[ROW][C]-8[/C][C]-0.00113328931540061[/C][/ROW]
[ROW][C]-7[/C][C]-0.0134996650553267[/C][/ROW]
[ROW][C]-6[/C][C]0.00983617856041736[/C][/ROW]
[ROW][C]-5[/C][C]0.0668765615476844[/C][/ROW]
[ROW][C]-4[/C][C]0.138629100374880[/C][/ROW]
[ROW][C]-3[/C][C]0.240388307050598[/C][/ROW]
[ROW][C]-2[/C][C]0.383871620398819[/C][/ROW]
[ROW][C]-1[/C][C]0.583971492286922[/C][/ROW]
[ROW][C]0[/C][C]0.787626801836342[/C][/ROW]
[ROW][C]1[/C][C]0.726962468697328[/C][/ROW]
[ROW][C]2[/C][C]0.574098353040878[/C][/ROW]
[ROW][C]3[/C][C]0.415765858871866[/C][/ROW]
[ROW][C]4[/C][C]0.277577839849854[/C][/ROW]
[ROW][C]5[/C][C]0.185671811074286[/C][/ROW]
[ROW][C]6[/C][C]0.108182252653627[/C][/ROW]
[ROW][C]7[/C][C]0.0798323765144957[/C][/ROW]
[ROW][C]8[/C][C]0.0914523267007784[/C][/ROW]
[ROW][C]9[/C][C]0.145041586156897[/C][/ROW]
[ROW][C]10[/C][C]0.180960031962631[/C][/ROW]
[ROW][C]11[/C][C]0.251812636047097[/C][/ROW]
[ROW][C]12[/C][C]0.307697063932656[/C][/ROW]
[ROW][C]13[/C][C]0.206204695377565[/C][/ROW]
[ROW][C]14[/C][C]0.06547991124933[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104228&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104228&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 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])
-14-0.0609021951123717
-130.0220286974167309
-120.116118111084721
-110.0987214761789366
-100.0781768726338735
-90.065168643036225
-8-0.00113328931540061
-7-0.0134996650553267
-60.00983617856041736
-50.0668765615476844
-40.138629100374880
-30.240388307050598
-20.383871620398819
-10.583971492286922
00.787626801836342
10.726962468697328
20.574098353040878
30.415765858871866
40.277577839849854
50.185671811074286
60.108182252653627
70.0798323765144957
80.0914523267007784
90.145041586156897
100.180960031962631
110.251812636047097
120.307697063932656
130.206204695377565
140.06547991124933


Figures (Output of Computation)

Input Parameters & R Code

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')