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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 computationFri, 24 Dec 2010 15:16:47 +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/24/t1293203662rzopialq7jbtv01.htm/, Retrieved Tue, 30 Apr 2024 01:12:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115094, Retrieved Tue, 30 Apr 2024 01:12:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact106

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] [paperCCF1] [2010-12-19 14:45:22] [7e261c986c934df955dd3ac53e9d45c6]
-   PD  [Cross Correlation Function] [paperCCF2] [2010-12-19 14:48:27] [7e261c986c934df955dd3ac53e9d45c6]
-   P     [Cross Correlation Function] [paperCCF2] [2010-12-22 14:53:54] [7e261c986c934df955dd3ac53e9d45c6]
-   P         [Cross Correlation Function] [Kristof Nagels] [2010-12-24 15:16:47] [fff0a1ca5ad3b1801f382406d5a383a7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15
14.4
13
13.7
13.6
15.2
12.9
14
14.1
13.2
11.3
13.3
14.4
13.3
11.6
13.2
13.1
14.6
14
14.3
13.8
13.7
11
14.4
15.6
13.7
12.6
13.2
13.3
14.3
14
13.4
13.9
13.7
10.5
14.5
15
13.5
13.5
13.2
13.8
16.2
14.7
13.9
16
14.4
12.3
15.9
15.9
15.5
15.1
14.5
15.1
17.4
16.2
15.6
17.2
14.9
13.8
17.5
16.2
17.5
16.6
16.2
16.6
19.6
15.9
18
18.3
16.3
14.9
18.2
18.4
18.5
16
17.4
17.2
19.6
17.2
18.3
19.3
18.1
16.2
18.4
20.5
19
16.5
18.7
19
19.2
20.5
19.3
20.6
20.1
16.1
20.4
19.7
15.6
14.4
13.7
14.1
15
14.2
13.6
15.4
14.8
12.5
16.2
16.1
16
15.8
15.2
15.7
18.9
17.4
17
19.8
17.7
16
19.6
19.7
Dataseries Y:
Download CSV
Histogram 
6.7
6.7
6.5
6.3
6.3
6.3
6.5
6.6
6.5
6.3
6.3
6.5
7
7.1
7.3
7.3
7.4
7.4
7.3
7.4
7.5
7.7
7.7
7.7
7.7
7.7
7.8
8
8.1
8.1
8.2
8.2
8.2
8.1
8.1
8.2
8.3
8.3
8.4
8.5
8.5
8.4
8
7.9
8.1
8.5
8.8
8.8
8.6
8.3
8.3
8.3
8.4
8.4
8.5
8.6
8.6
8.6
8.6
8.6
8.5
8.4
8.4
8.4
8.5
8.5
8.6
8.6
8.4
8.2
8
8
8
8
7.9
7.9
7.8
7.8
8
7.8
7.4
7.2
7
7
7.2
7.2
7.2
7
6.9
6.8
6.8
6.8
6.9
7.2
7.2
7.2
7.1
7.2
7.3
7.5
7.6
7.7
7.7
7.7
7.8
8
8.1
8.1
8
8.1
8.2
8.3
8.4
8.4
8.4
8.5
8.5
8.6
8.6
8.5
8.5

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'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=115094&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=115094&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115094&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'George Udny Yule' @ 72.249.76.132






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 series2
Seasonal Period (s)12
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])
-160.00967754406469997
-15-0.00200541113996878
-14-0.0149856890710449
-130.0658602803662067
-12-0.0254025459316951
-110.0219628276780574
-100.032414937873664
-9-0.0191143582135517
-80.0733833420459784
-70.132916152406519
-6-0.0435026153366335
-50.00835101143218357
-40.0925974168355507
-3-0.124151166098128
-20.0485871534755395
-1-0.0117736066374139
0-0.0619814062828229
10.0499096571554886
20.01562226357655
3-0.0369082272234377
40.0113415014746582
5-0.178423171644980
6-0.0730670692695093
70.0715632627240686
8-0.0274210511675047
9-0.0393961054332427
10-0.0103967120978179
11-0.0461184127904247
12-0.0420018305056178
130.0386809663526912
14-0.0919789726165948
15-0.109038565021239
16-0.0289842847633013

\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 & 2 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.00967754406469997 \tabularnewline
-15 & -0.00200541113996878 \tabularnewline
-14 & -0.0149856890710449 \tabularnewline
-13 & 0.0658602803662067 \tabularnewline
-12 & -0.0254025459316951 \tabularnewline
-11 & 0.0219628276780574 \tabularnewline
-10 & 0.032414937873664 \tabularnewline
-9 & -0.0191143582135517 \tabularnewline
-8 & 0.0733833420459784 \tabularnewline
-7 & 0.132916152406519 \tabularnewline
-6 & -0.0435026153366335 \tabularnewline
-5 & 0.00835101143218357 \tabularnewline
-4 & 0.0925974168355507 \tabularnewline
-3 & -0.124151166098128 \tabularnewline
-2 & 0.0485871534755395 \tabularnewline
-1 & -0.0117736066374139 \tabularnewline
0 & -0.0619814062828229 \tabularnewline
1 & 0.0499096571554886 \tabularnewline
2 & 0.01562226357655 \tabularnewline
3 & -0.0369082272234377 \tabularnewline
4 & 0.0113415014746582 \tabularnewline
5 & -0.178423171644980 \tabularnewline
6 & -0.0730670692695093 \tabularnewline
7 & 0.0715632627240686 \tabularnewline
8 & -0.0274210511675047 \tabularnewline
9 & -0.0393961054332427 \tabularnewline
10 & -0.0103967120978179 \tabularnewline
11 & -0.0461184127904247 \tabularnewline
12 & -0.0420018305056178 \tabularnewline
13 & 0.0386809663526912 \tabularnewline
14 & -0.0919789726165948 \tabularnewline
15 & -0.109038565021239 \tabularnewline
16 & -0.0289842847633013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115094&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]2[/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]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]-16[/C][C]0.00967754406469997[/C][/ROW]
[ROW][C]-15[/C][C]-0.00200541113996878[/C][/ROW]
[ROW][C]-14[/C][C]-0.0149856890710449[/C][/ROW]
[ROW][C]-13[/C][C]0.0658602803662067[/C][/ROW]
[ROW][C]-12[/C][C]-0.0254025459316951[/C][/ROW]
[ROW][C]-11[/C][C]0.0219628276780574[/C][/ROW]
[ROW][C]-10[/C][C]0.032414937873664[/C][/ROW]
[ROW][C]-9[/C][C]-0.0191143582135517[/C][/ROW]
[ROW][C]-8[/C][C]0.0733833420459784[/C][/ROW]
[ROW][C]-7[/C][C]0.132916152406519[/C][/ROW]
[ROW][C]-6[/C][C]-0.0435026153366335[/C][/ROW]
[ROW][C]-5[/C][C]0.00835101143218357[/C][/ROW]
[ROW][C]-4[/C][C]0.0925974168355507[/C][/ROW]
[ROW][C]-3[/C][C]-0.124151166098128[/C][/ROW]
[ROW][C]-2[/C][C]0.0485871534755395[/C][/ROW]
[ROW][C]-1[/C][C]-0.0117736066374139[/C][/ROW]
[ROW][C]0[/C][C]-0.0619814062828229[/C][/ROW]
[ROW][C]1[/C][C]0.0499096571554886[/C][/ROW]
[ROW][C]2[/C][C]0.01562226357655[/C][/ROW]
[ROW][C]3[/C][C]-0.0369082272234377[/C][/ROW]
[ROW][C]4[/C][C]0.0113415014746582[/C][/ROW]
[ROW][C]5[/C][C]-0.178423171644980[/C][/ROW]
[ROW][C]6[/C][C]-0.0730670692695093[/C][/ROW]
[ROW][C]7[/C][C]0.0715632627240686[/C][/ROW]
[ROW][C]8[/C][C]-0.0274210511675047[/C][/ROW]
[ROW][C]9[/C][C]-0.0393961054332427[/C][/ROW]
[ROW][C]10[/C][C]-0.0103967120978179[/C][/ROW]
[ROW][C]11[/C][C]-0.0461184127904247[/C][/ROW]
[ROW][C]12[/C][C]-0.0420018305056178[/C][/ROW]
[ROW][C]13[/C][C]0.0386809663526912[/C][/ROW]
[ROW][C]14[/C][C]-0.0919789726165948[/C][/ROW]
[ROW][C]15[/C][C]-0.109038565021239[/C][/ROW]
[ROW][C]16[/C][C]-0.0289842847633013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115094&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115094&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 series2
Seasonal Period (s)12
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])
-160.00967754406469997
-15-0.00200541113996878
-14-0.0149856890710449
-130.0658602803662067
-12-0.0254025459316951
-110.0219628276780574
-100.032414937873664
-9-0.0191143582135517
-80.0733833420459784
-70.132916152406519
-6-0.0435026153366335
-50.00835101143218357
-40.0925974168355507
-3-0.124151166098128
-20.0485871534755395
-1-0.0117736066374139
0-0.0619814062828229
10.0499096571554886
20.01562226357655
3-0.0369082272234377
40.0113415014746582
5-0.178423171644980
6-0.0730670692695093
70.0715632627240686
8-0.0274210511675047
9-0.0393961054332427
10-0.0103967120978179
11-0.0461184127904247
12-0.0420018305056178
130.0386809663526912
14-0.0919789726165948
15-0.109038565021239
16-0.0289842847633013


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')