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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 25 Nov 2007 07:30:07 -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/2007/Nov/25/t1196000450y3n4oceneph08na.htm/, Retrieved Sat, 04 May 2024 07:00:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6468, Retrieved Sat, 04 May 2024 07:00:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact220

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] [ws7] [2007-11-25 14:30:07] [e2f7a6e26aa7cf06a3d27eb5298a4843] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8.1
8.2
8
8.1
8.3
8.2
8.1
7.7
7.6
7.7
8.2
8.4
8.4
8.6
8.4
8.5
8.7
8.7
8.6
7.4
7.3
7.4
9
9.2
9.2
8.5
8.3
8.3
8.6
8.6
8.5
8.1
8.1
8
8.6
8.7
8.7
8.6
8.4
8.4
8.7
8.7
8.5
8.3
8.3
8.3
8.1
8.2
8.1
8.1
7.9
7.7
8.1
8
7.7
7.8
7.6
7.4
7.7
7.9
7.6
Dataseries Y:
Download CSV
Histogram 
8,5
8,6
8,5
8,5
9
9
8,8
8
7,9
8,1
9,3
9,4
9,4
9,3
9
9,1
9,7
9,7
9,6
8,3
8,2
8,4
10,6
10,9
10,9
9,6
9,3
9,3
9,6
9,5
9,5
9
8,9
9
10,1
10,2
10,2
9,5
9,3
9,3
9,4
9,3
9,1
9
8,9
9
9,8
10
9,8
9,4
9
8,9
9,3
9,1
8,8
8,9
8,7
8,6
9,1
9,3
8,9

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6468&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6468&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6468&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series-2
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series-1.6
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0243905427885047
-120.110594716330403
-111.43163123735188e-05
-100.0186052096519491
-9-0.182778332628273
-8-0.0695365104306901
-7-0.0259379552531047
-6-0.0331989011711534
-50.000268236944965649
-40.0848731044119511
-30.395547738983791
-20.0272268729997312
-1-0.0914840364444777
0-0.429095180010325
1-0.0215197846391307
20.031200905026586
30.167136847223344
40.0216130441736031
5-0.0392142870648466
6-0.150018557127262
7-0.0141408355388146
80.0418501249809962
90.388596414707641
100.0818462908147988
11-0.0469083163714065
12-0.541369274369879
13-0.0434982069157661

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -2 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & -1.6 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0243905427885047 \tabularnewline
-12 & 0.110594716330403 \tabularnewline
-11 & 1.43163123735188e-05 \tabularnewline
-10 & 0.0186052096519491 \tabularnewline
-9 & -0.182778332628273 \tabularnewline
-8 & -0.0695365104306901 \tabularnewline
-7 & -0.0259379552531047 \tabularnewline
-6 & -0.0331989011711534 \tabularnewline
-5 & 0.000268236944965649 \tabularnewline
-4 & 0.0848731044119511 \tabularnewline
-3 & 0.395547738983791 \tabularnewline
-2 & 0.0272268729997312 \tabularnewline
-1 & -0.0914840364444777 \tabularnewline
0 & -0.429095180010325 \tabularnewline
1 & -0.0215197846391307 \tabularnewline
2 & 0.031200905026586 \tabularnewline
3 & 0.167136847223344 \tabularnewline
4 & 0.0216130441736031 \tabularnewline
5 & -0.0392142870648466 \tabularnewline
6 & -0.150018557127262 \tabularnewline
7 & -0.0141408355388146 \tabularnewline
8 & 0.0418501249809962 \tabularnewline
9 & 0.388596414707641 \tabularnewline
10 & 0.0818462908147988 \tabularnewline
11 & -0.0469083163714065 \tabularnewline
12 & -0.541369274369879 \tabularnewline
13 & -0.0434982069157661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6468&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]-2[/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]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]-1.6[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.0243905427885047[/C][/ROW]
[ROW][C]-12[/C][C]0.110594716330403[/C][/ROW]
[ROW][C]-11[/C][C]1.43163123735188e-05[/C][/ROW]
[ROW][C]-10[/C][C]0.0186052096519491[/C][/ROW]
[ROW][C]-9[/C][C]-0.182778332628273[/C][/ROW]
[ROW][C]-8[/C][C]-0.0695365104306901[/C][/ROW]
[ROW][C]-7[/C][C]-0.0259379552531047[/C][/ROW]
[ROW][C]-6[/C][C]-0.0331989011711534[/C][/ROW]
[ROW][C]-5[/C][C]0.000268236944965649[/C][/ROW]
[ROW][C]-4[/C][C]0.0848731044119511[/C][/ROW]
[ROW][C]-3[/C][C]0.395547738983791[/C][/ROW]
[ROW][C]-2[/C][C]0.0272268729997312[/C][/ROW]
[ROW][C]-1[/C][C]-0.0914840364444777[/C][/ROW]
[ROW][C]0[/C][C]-0.429095180010325[/C][/ROW]
[ROW][C]1[/C][C]-0.0215197846391307[/C][/ROW]
[ROW][C]2[/C][C]0.031200905026586[/C][/ROW]
[ROW][C]3[/C][C]0.167136847223344[/C][/ROW]
[ROW][C]4[/C][C]0.0216130441736031[/C][/ROW]
[ROW][C]5[/C][C]-0.0392142870648466[/C][/ROW]
[ROW][C]6[/C][C]-0.150018557127262[/C][/ROW]
[ROW][C]7[/C][C]-0.0141408355388146[/C][/ROW]
[ROW][C]8[/C][C]0.0418501249809962[/C][/ROW]
[ROW][C]9[/C][C]0.388596414707641[/C][/ROW]
[ROW][C]10[/C][C]0.0818462908147988[/C][/ROW]
[ROW][C]11[/C][C]-0.0469083163714065[/C][/ROW]
[ROW][C]12[/C][C]-0.541369274369879[/C][/ROW]
[ROW][C]13[/C][C]-0.0434982069157661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6468&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6468&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 series-2
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series-1.6
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0243905427885047
-120.110594716330403
-111.43163123735188e-05
-100.0186052096519491
-9-0.182778332628273
-8-0.0695365104306901
-7-0.0259379552531047
-6-0.0331989011711534
-50.000268236944965649
-40.0848731044119511
-30.395547738983791
-20.0272268729997312
-1-0.0914840364444777
0-0.429095180010325
1-0.0215197846391307
20.031200905026586
30.167136847223344
40.0216130441736031
5-0.0392142870648466
6-0.150018557127262
7-0.0141408355388146
80.0418501249809962
90.388596414707641
100.0818462908147988
11-0.0469083163714065
12-0.541369274369879
13-0.0434982069157661


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = -2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -1.6 ; par6 = 1 ; par7 = 1 ;
Parameters (R input):
par1 = -2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -1.6 ; par6 = 1 ; par7 = 1 ;
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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')