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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 computationWed, 05 Dec 2007 10:31:25 -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/Dec/05/t11968751688v8pe8xs0fzj2w6.htm/, Retrieved Fri, 03 May 2024 01:58:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2494, Retrieved Fri, 03 May 2024 01:58:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact250

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] [Cross Correlation...] [2007-12-05 17:31:25] [89d26cd0a44959d9c8b169f34617598a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
Dataseries Y:
Download CSV
Histogram 
-11,8
-11,4
-17,7
-17,3
-18,6
-17,9
-21,4
-19,4
-15,5
-7,7
-0,7
-1,6
1,4
0,7
9,5
1,4
4,1
6,6
18,4
16,9
9,2
-4,3
-5,9
-7,7
-5,4
-2,3
-4,8
2,3
-5,2
-10
-17,1
-14,4
-3,9
3,7
6,5
0,9
-4,1
-7
-12,2
-2,5
4,4
13,7
12,3
13,4
2,2
1,7
-7,2
-4,8
-2,9
-2,4
-2,5
-5,3
-7,1
-8

Tables (Output of Computation)





Summary of compuational 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 compuational 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=2494&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]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=2494&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2494&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 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)12
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])
-14-0.253552162180945
-13-0.270403117738396
-12-0.252523334583301
-11-0.191973207604486
-10-0.104186417739449
-9-0.021202345219375
-80.0458259850706998
-70.085723770010002
-60.127508865076393
-50.17164559869217
-40.217797024568586
-30.260978494910261
-20.284078377352751
-10.309024889821616
00.340245280550425
10.341531885755964
20.351821325977712
30.34555612248672
40.352883106283202
50.321102131439244
60.276219595977035
70.181634503826429
80.104337016294114
90.0637767415328223
100.0782328102519974
110.138795355847416
120.170808278033299
130.191386290999901
140.165694387594712

\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) & 12 \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 & -0.253552162180945 \tabularnewline
-13 & -0.270403117738396 \tabularnewline
-12 & -0.252523334583301 \tabularnewline
-11 & -0.191973207604486 \tabularnewline
-10 & -0.104186417739449 \tabularnewline
-9 & -0.021202345219375 \tabularnewline
-8 & 0.0458259850706998 \tabularnewline
-7 & 0.085723770010002 \tabularnewline
-6 & 0.127508865076393 \tabularnewline
-5 & 0.17164559869217 \tabularnewline
-4 & 0.217797024568586 \tabularnewline
-3 & 0.260978494910261 \tabularnewline
-2 & 0.284078377352751 \tabularnewline
-1 & 0.309024889821616 \tabularnewline
0 & 0.340245280550425 \tabularnewline
1 & 0.341531885755964 \tabularnewline
2 & 0.351821325977712 \tabularnewline
3 & 0.34555612248672 \tabularnewline
4 & 0.352883106283202 \tabularnewline
5 & 0.321102131439244 \tabularnewline
6 & 0.276219595977035 \tabularnewline
7 & 0.181634503826429 \tabularnewline
8 & 0.104337016294114 \tabularnewline
9 & 0.0637767415328223 \tabularnewline
10 & 0.0782328102519974 \tabularnewline
11 & 0.138795355847416 \tabularnewline
12 & 0.170808278033299 \tabularnewline
13 & 0.191386290999901 \tabularnewline
14 & 0.165694387594712 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2494&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]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]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]-0.253552162180945[/C][/ROW]
[ROW][C]-13[/C][C]-0.270403117738396[/C][/ROW]
[ROW][C]-12[/C][C]-0.252523334583301[/C][/ROW]
[ROW][C]-11[/C][C]-0.191973207604486[/C][/ROW]
[ROW][C]-10[/C][C]-0.104186417739449[/C][/ROW]
[ROW][C]-9[/C][C]-0.021202345219375[/C][/ROW]
[ROW][C]-8[/C][C]0.0458259850706998[/C][/ROW]
[ROW][C]-7[/C][C]0.085723770010002[/C][/ROW]
[ROW][C]-6[/C][C]0.127508865076393[/C][/ROW]
[ROW][C]-5[/C][C]0.17164559869217[/C][/ROW]
[ROW][C]-4[/C][C]0.217797024568586[/C][/ROW]
[ROW][C]-3[/C][C]0.260978494910261[/C][/ROW]
[ROW][C]-2[/C][C]0.284078377352751[/C][/ROW]
[ROW][C]-1[/C][C]0.309024889821616[/C][/ROW]
[ROW][C]0[/C][C]0.340245280550425[/C][/ROW]
[ROW][C]1[/C][C]0.341531885755964[/C][/ROW]
[ROW][C]2[/C][C]0.351821325977712[/C][/ROW]
[ROW][C]3[/C][C]0.34555612248672[/C][/ROW]
[ROW][C]4[/C][C]0.352883106283202[/C][/ROW]
[ROW][C]5[/C][C]0.321102131439244[/C][/ROW]
[ROW][C]6[/C][C]0.276219595977035[/C][/ROW]
[ROW][C]7[/C][C]0.181634503826429[/C][/ROW]
[ROW][C]8[/C][C]0.104337016294114[/C][/ROW]
[ROW][C]9[/C][C]0.0637767415328223[/C][/ROW]
[ROW][C]10[/C][C]0.0782328102519974[/C][/ROW]
[ROW][C]11[/C][C]0.138795355847416[/C][/ROW]
[ROW][C]12[/C][C]0.170808278033299[/C][/ROW]
[ROW][C]13[/C][C]0.191386290999901[/C][/ROW]
[ROW][C]14[/C][C]0.165694387594712[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2494&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2494&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)12
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])
-14-0.253552162180945
-13-0.270403117738396
-12-0.252523334583301
-11-0.191973207604486
-10-0.104186417739449
-9-0.021202345219375
-80.0458259850706998
-70.085723770010002
-60.127508865076393
-50.17164559869217
-40.217797024568586
-30.260978494910261
-20.284078377352751
-10.309024889821616
00.340245280550425
10.341531885755964
20.351821325977712
30.34555612248672
40.352883106283202
50.321102131439244
60.276219595977035
70.181634503826429
80.104337016294114
90.0637767415328223
100.0782328102519974
110.138795355847416
120.170808278033299
130.191386290999901
140.165694387594712


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; 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) x <- 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')