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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, 15 Dec 2009 03:43:00 -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/2009/Dec/15/t1260876465e6i0wl7hp0hwsvj.htm/, Retrieved Wed, 08 May 2024 20:26:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67842, Retrieved Wed, 08 May 2024 20:26:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Yen/Euro] [2009-11-02 16:45:36] [74be16979710d4c4e7c6647856088456]
- RMPD    [Cross Correlation Function] [kruiscorrelatiefu...] [2009-12-15 10:43:00] [5c2088b06970f9a7d6fea063ee8d5871] [Current]
-   P       [Cross Correlation Function] [Kruiscorrealtie t...] [2009-12-15 11:30:46] [7773f496f69461f4a67891f0ef752622]
- RMPD      [Variance Reduction Matrix] [variantie reducti...] [2009-12-15 11:45:38] [7773f496f69461f4a67891f0ef752622]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8.32
8.27
8.28
8.32
8.3
8.26
8.29
8.17
8.04
8
7.98
7.97
7.92
7.96
7.99
7.93
7.97
7.95
7.96
7.97
7.9
7.76
7.74
7.72
7.68
7.72
7.71
7.71
7.68
7.7
7.69
7.66
7.61
7.33
7.24
7.14
Dataseries Y:
Download CSV
Histogram 
1.56
1.57
1.56
1.56
1.56
1.56
1.55
1.56
1.55
1.54
1.54
1.53
1.53
1.53
1.53
1.52
1.52
1.52
1.52
1.52
1.51
1.51
1.51
1.52
1.51
1.5
1.5
1.5
1.5
1.5
1.5
1.49
1.47
1.45
1.45
1.44

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=67842&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=67842&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67842&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 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])
-120.0911526411549828
-110.148466263860353
-100.198355615225594
-90.239941937470401
-80.289379590911187
-70.355168709217237
-60.397190304007428
-50.458273551209612
-40.519282884205977
-30.57869074274291
-20.694766159075085
-10.83591491655927
00.968374648514852
10.848283226999797
20.729924682976742
30.584045416320084
40.465826488019132
50.389607254002944
60.340522746212187
70.277172796698193
80.228310031524895
90.188932922765149
100.139306377465046
110.092685676534951
120.0672126511588775

\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
-12 & 0.0911526411549828 \tabularnewline
-11 & 0.148466263860353 \tabularnewline
-10 & 0.198355615225594 \tabularnewline
-9 & 0.239941937470401 \tabularnewline
-8 & 0.289379590911187 \tabularnewline
-7 & 0.355168709217237 \tabularnewline
-6 & 0.397190304007428 \tabularnewline
-5 & 0.458273551209612 \tabularnewline
-4 & 0.519282884205977 \tabularnewline
-3 & 0.57869074274291 \tabularnewline
-2 & 0.694766159075085 \tabularnewline
-1 & 0.83591491655927 \tabularnewline
0 & 0.968374648514852 \tabularnewline
1 & 0.848283226999797 \tabularnewline
2 & 0.729924682976742 \tabularnewline
3 & 0.584045416320084 \tabularnewline
4 & 0.465826488019132 \tabularnewline
5 & 0.389607254002944 \tabularnewline
6 & 0.340522746212187 \tabularnewline
7 & 0.277172796698193 \tabularnewline
8 & 0.228310031524895 \tabularnewline
9 & 0.188932922765149 \tabularnewline
10 & 0.139306377465046 \tabularnewline
11 & 0.092685676534951 \tabularnewline
12 & 0.0672126511588775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67842&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]-12[/C][C]0.0911526411549828[/C][/ROW]
[ROW][C]-11[/C][C]0.148466263860353[/C][/ROW]
[ROW][C]-10[/C][C]0.198355615225594[/C][/ROW]
[ROW][C]-9[/C][C]0.239941937470401[/C][/ROW]
[ROW][C]-8[/C][C]0.289379590911187[/C][/ROW]
[ROW][C]-7[/C][C]0.355168709217237[/C][/ROW]
[ROW][C]-6[/C][C]0.397190304007428[/C][/ROW]
[ROW][C]-5[/C][C]0.458273551209612[/C][/ROW]
[ROW][C]-4[/C][C]0.519282884205977[/C][/ROW]
[ROW][C]-3[/C][C]0.57869074274291[/C][/ROW]
[ROW][C]-2[/C][C]0.694766159075085[/C][/ROW]
[ROW][C]-1[/C][C]0.83591491655927[/C][/ROW]
[ROW][C]0[/C][C]0.968374648514852[/C][/ROW]
[ROW][C]1[/C][C]0.848283226999797[/C][/ROW]
[ROW][C]2[/C][C]0.729924682976742[/C][/ROW]
[ROW][C]3[/C][C]0.584045416320084[/C][/ROW]
[ROW][C]4[/C][C]0.465826488019132[/C][/ROW]
[ROW][C]5[/C][C]0.389607254002944[/C][/ROW]
[ROW][C]6[/C][C]0.340522746212187[/C][/ROW]
[ROW][C]7[/C][C]0.277172796698193[/C][/ROW]
[ROW][C]8[/C][C]0.228310031524895[/C][/ROW]
[ROW][C]9[/C][C]0.188932922765149[/C][/ROW]
[ROW][C]10[/C][C]0.139306377465046[/C][/ROW]
[ROW][C]11[/C][C]0.092685676534951[/C][/ROW]
[ROW][C]12[/C][C]0.0672126511588775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67842&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67842&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])
-120.0911526411549828
-110.148466263860353
-100.198355615225594
-90.239941937470401
-80.289379590911187
-70.355168709217237
-60.397190304007428
-50.458273551209612
-40.519282884205977
-30.57869074274291
-20.694766159075085
-10.83591491655927
00.968374648514852
10.848283226999797
20.729924682976742
30.584045416320084
40.465826488019132
50.389607254002944
60.340522746212187
70.277172796698193
80.228310031524895
90.188932922765149
100.139306377465046
110.092685676534951
120.0672126511588775


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')