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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 computationSun, 06 Dec 2009 17:02:29 -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/07/t1260144182ytv8hme0zpq0mgg.htm/, Retrieved Sat, 04 May 2024 22:46:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64529, Retrieved Sat, 04 May 2024 22:46:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

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...] [2007-12-17 15:16:15] [0089dec2868056b990fdbd23bf9edb23]
- RMPD    [Cross Correlation Function] [PAPER] [2009-12-07 00:02:29] [2d9a0b3c2f25bb8f387fafb994d0d852] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
526
511
499
555
565
542
527
510
514
517
508
493
490
469
478
528
534
518
506
502
516
528
533
536
537
524
536
587
597
581
564
564
Dataseries Y:
Download CSV
Histogram 
100.00
100.83
101.51
102.16
102.39
102.54
102.85
103.47
103.57
103.69
103.50
103.47
103.45
103.48
103.93
103.89
104.40
104.79
104.77
105.13
105.26
104.96
104.75
105.01
105.15
105.20
105.77
105.78
106.26
106.13
106.12
106.57
106.44
106.54
107.10
108.10
108.40
108.84
109.62
110.42
110.67
111.66
112.28
112.87
112.18
112.36
112.16
111.49
111.25
111.36
111.74
111.10
111.33
111.25
111.04
110.97
111.31
111.02
111.07
111.36

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=64529&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=64529&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64529&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 series1
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 series1
krho(Y[t],X[t+k])
-130.193907424874974
-120.553747372728244
-110.168616732349363
-100.191670698901587
-90.270631024878299
-80.213290442497275
-7-0.078291577017273
-6-0.0208814111321334
-50.206541119857116
-4-0.0748392916790544
-3-0.250033045064622
-2-0.198747131832934
-1-0.153946936081663
0-0.767117977230843
1-0.328453253244164
2-0.214098661317200
3-0.111776658103322
4-0.231666310025118
50.0442873175947135
60.0310129493365817
7-0.0512033667980661
8-0.0740329966107622
90.119299554971947
100.109332299185051
11-0.00578272915436415
120.0804227141927136
130.135209185705431

\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 & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.193907424874974 \tabularnewline
-12 & 0.553747372728244 \tabularnewline
-11 & 0.168616732349363 \tabularnewline
-10 & 0.191670698901587 \tabularnewline
-9 & 0.270631024878299 \tabularnewline
-8 & 0.213290442497275 \tabularnewline
-7 & -0.078291577017273 \tabularnewline
-6 & -0.0208814111321334 \tabularnewline
-5 & 0.206541119857116 \tabularnewline
-4 & -0.0748392916790544 \tabularnewline
-3 & -0.250033045064622 \tabularnewline
-2 & -0.198747131832934 \tabularnewline
-1 & -0.153946936081663 \tabularnewline
0 & -0.767117977230843 \tabularnewline
1 & -0.328453253244164 \tabularnewline
2 & -0.214098661317200 \tabularnewline
3 & -0.111776658103322 \tabularnewline
4 & -0.231666310025118 \tabularnewline
5 & 0.0442873175947135 \tabularnewline
6 & 0.0310129493365817 \tabularnewline
7 & -0.0512033667980661 \tabularnewline
8 & -0.0740329966107622 \tabularnewline
9 & 0.119299554971947 \tabularnewline
10 & 0.109332299185051 \tabularnewline
11 & -0.00578272915436415 \tabularnewline
12 & 0.0804227141927136 \tabularnewline
13 & 0.135209185705431 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64529&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]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[/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]0.193907424874974[/C][/ROW]
[ROW][C]-12[/C][C]0.553747372728244[/C][/ROW]
[ROW][C]-11[/C][C]0.168616732349363[/C][/ROW]
[ROW][C]-10[/C][C]0.191670698901587[/C][/ROW]
[ROW][C]-9[/C][C]0.270631024878299[/C][/ROW]
[ROW][C]-8[/C][C]0.213290442497275[/C][/ROW]
[ROW][C]-7[/C][C]-0.078291577017273[/C][/ROW]
[ROW][C]-6[/C][C]-0.0208814111321334[/C][/ROW]
[ROW][C]-5[/C][C]0.206541119857116[/C][/ROW]
[ROW][C]-4[/C][C]-0.0748392916790544[/C][/ROW]
[ROW][C]-3[/C][C]-0.250033045064622[/C][/ROW]
[ROW][C]-2[/C][C]-0.198747131832934[/C][/ROW]
[ROW][C]-1[/C][C]-0.153946936081663[/C][/ROW]
[ROW][C]0[/C][C]-0.767117977230843[/C][/ROW]
[ROW][C]1[/C][C]-0.328453253244164[/C][/ROW]
[ROW][C]2[/C][C]-0.214098661317200[/C][/ROW]
[ROW][C]3[/C][C]-0.111776658103322[/C][/ROW]
[ROW][C]4[/C][C]-0.231666310025118[/C][/ROW]
[ROW][C]5[/C][C]0.0442873175947135[/C][/ROW]
[ROW][C]6[/C][C]0.0310129493365817[/C][/ROW]
[ROW][C]7[/C][C]-0.0512033667980661[/C][/ROW]
[ROW][C]8[/C][C]-0.0740329966107622[/C][/ROW]
[ROW][C]9[/C][C]0.119299554971947[/C][/ROW]
[ROW][C]10[/C][C]0.109332299185051[/C][/ROW]
[ROW][C]11[/C][C]-0.00578272915436415[/C][/ROW]
[ROW][C]12[/C][C]0.0804227141927136[/C][/ROW]
[ROW][C]13[/C][C]0.135209185705431[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64529&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64529&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 series1
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 series1
krho(Y[t],X[t+k])
-130.193907424874974
-120.553747372728244
-110.168616732349363
-100.191670698901587
-90.270631024878299
-80.213290442497275
-7-0.078291577017273
-6-0.0208814111321334
-50.206541119857116
-4-0.0748392916790544
-3-0.250033045064622
-2-0.198747131832934
-1-0.153946936081663
0-0.767117977230843
1-0.328453253244164
2-0.214098661317200
3-0.111776658103322
4-0.231666310025118
50.0442873175947135
60.0310129493365817
7-0.0512033667980661
8-0.0740329966107622
90.119299554971947
100.109332299185051
11-0.00578272915436415
120.0804227141927136
130.135209185705431


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; 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',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')