FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 04:30:46 -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/t1260876724tcgefnmuuuwkhmq.htm/, Retrieved Wed, 08 May 2024 19:15:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67843, Retrieved Wed, 08 May 2024 19:15:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact113

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] [7773f496f69461f4a67891f0ef752622]
-   P       [Cross Correlation Function] [Kruiscorrealtie t...] [2009-12-15 11:30:46] [5c2088b06970f9a7d6fea063ee8d5871] [Current]
Feedback Forum

Post a new message

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 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=67843&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=67843&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67843&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 series0
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-120.173993815923822
-110.0783223681981702
-100.0667272289518478
-9-0.0476278428803204
-8-0.0929972257038132
-7-0.0568054032930832
-6-0.237810711120617
-5-0.0212500559892808
-40.111593591126316
-30.0137663406191430
-2-0.0393280021714671
-10.147410714482161
00.292650227591504
10.329935349984286
20.320511412110783
30.032629614957455
4-0.0788356545747245
5-0.156885980993324
60.0620255257426257
7-0.145732268030834
80.00706795340513035
90.197055772822335
10-0.139151936683428
11-0.0664757186273362
120.0336869848931512

\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 & 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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-12 & 0.173993815923822 \tabularnewline
-11 & 0.0783223681981702 \tabularnewline
-10 & 0.0667272289518478 \tabularnewline
-9 & -0.0476278428803204 \tabularnewline
-8 & -0.0929972257038132 \tabularnewline
-7 & -0.0568054032930832 \tabularnewline
-6 & -0.237810711120617 \tabularnewline
-5 & -0.0212500559892808 \tabularnewline
-4 & 0.111593591126316 \tabularnewline
-3 & 0.0137663406191430 \tabularnewline
-2 & -0.0393280021714671 \tabularnewline
-1 & 0.147410714482161 \tabularnewline
0 & 0.292650227591504 \tabularnewline
1 & 0.329935349984286 \tabularnewline
2 & 0.320511412110783 \tabularnewline
3 & 0.032629614957455 \tabularnewline
4 & -0.0788356545747245 \tabularnewline
5 & -0.156885980993324 \tabularnewline
6 & 0.0620255257426257 \tabularnewline
7 & -0.145732268030834 \tabularnewline
8 & 0.00706795340513035 \tabularnewline
9 & 0.197055772822335 \tabularnewline
10 & -0.139151936683428 \tabularnewline
11 & -0.0664757186273362 \tabularnewline
12 & 0.0336869848931512 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67843&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]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]1[/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]0.173993815923822[/C][/ROW]
[ROW][C]-11[/C][C]0.0783223681981702[/C][/ROW]
[ROW][C]-10[/C][C]0.0667272289518478[/C][/ROW]
[ROW][C]-9[/C][C]-0.0476278428803204[/C][/ROW]
[ROW][C]-8[/C][C]-0.0929972257038132[/C][/ROW]
[ROW][C]-7[/C][C]-0.0568054032930832[/C][/ROW]
[ROW][C]-6[/C][C]-0.237810711120617[/C][/ROW]
[ROW][C]-5[/C][C]-0.0212500559892808[/C][/ROW]
[ROW][C]-4[/C][C]0.111593591126316[/C][/ROW]
[ROW][C]-3[/C][C]0.0137663406191430[/C][/ROW]
[ROW][C]-2[/C][C]-0.0393280021714671[/C][/ROW]
[ROW][C]-1[/C][C]0.147410714482161[/C][/ROW]
[ROW][C]0[/C][C]0.292650227591504[/C][/ROW]
[ROW][C]1[/C][C]0.329935349984286[/C][/ROW]
[ROW][C]2[/C][C]0.320511412110783[/C][/ROW]
[ROW][C]3[/C][C]0.032629614957455[/C][/ROW]
[ROW][C]4[/C][C]-0.0788356545747245[/C][/ROW]
[ROW][C]5[/C][C]-0.156885980993324[/C][/ROW]
[ROW][C]6[/C][C]0.0620255257426257[/C][/ROW]
[ROW][C]7[/C][C]-0.145732268030834[/C][/ROW]
[ROW][C]8[/C][C]0.00706795340513035[/C][/ROW]
[ROW][C]9[/C][C]0.197055772822335[/C][/ROW]
[ROW][C]10[/C][C]-0.139151936683428[/C][/ROW]
[ROW][C]11[/C][C]-0.0664757186273362[/C][/ROW]
[ROW][C]12[/C][C]0.0336869848931512[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67843&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67843&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 series0
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-120.173993815923822
-110.0783223681981702
-100.0667272289518478
-9-0.0476278428803204
-8-0.0929972257038132
-7-0.0568054032930832
-6-0.237810711120617
-5-0.0212500559892808
-40.111593591126316
-30.0137663406191430
-2-0.0393280021714671
-10.147410714482161
00.292650227591504
10.329935349984286
20.320511412110783
30.032629614957455
4-0.0788356545747245
5-0.156885980993324
60.0620255257426257
7-0.145732268030834
80.00706795340513035
90.197055772822335
10-0.139151936683428
11-0.0664757186273362
120.0336869848931512


Figures (Output of Computation)

Input Parameters & R Code

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