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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 computationMon, 08 Dec 2008 13:02:32 -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/2008/Dec/08/t122876660663o5k3i5sqkirta.htm/, Retrieved Thu, 16 May 2024 05:40:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30896, Retrieved Thu, 16 May 2024 05:40:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact207

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [(Partial) Autocorrelation Function] [Opdracht 1 - Blok...] [2008-12-02 21:26:11] [8094ad203a218aaca2d1cea2c78c2d6e]
- RMPD    [Variance Reduction Matrix] [Verbetering Q8] [2008-12-08 19:35:00] [8094ad203a218aaca2d1cea2c78c2d6e]
- RMPD        [Cross Correlation Function] [Verbetering Q9] [2008-12-08 20:02:32] [1351baa662f198be3bff32f9007a9a6d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-3
-2
0
1
11
14
14
16
14
10
15
18
18
12
8
2
-2
-1
1
-6
-16
-21
-38
-32
-22
-31
-22
-26
-19
-20
-24
-29
-28
-31
-30
-32
-38
-43
-51
-43
-43
-42
-47
-45
-38
-46
-38
-32
-27
-26
-21
-23
-24
-17
-23
-16
-22
-26
-25
-21
-21
-18
-12
-19
-31
-38
-38
-32
-43
-33
-28
-25
-19
-20
-21
-19
-17
-16
-10
-16
-10
-8
-7
-15
-7
-6
-6
2
-4
-4
-8
-10
-16
-14
-30
-33
-40
-38
-39
-46
-50
-55
-66
-63
-56
-66
Dataseries Y:
Download CSV
Histogram 
17
22
29
26
29
42
40
34
46
43
44
40
41
42
35
40
43
47
41
44
38
35
34
31
25
35
36
41
41
38
39
45
46
48
48
48
45
44
45
45
45
42
43
50
46
46
45
49
46
45
49
47
45
48
51
48
49
51
54
52
52
53
51
55
53
51
52
54
58
57
52
50
53
50
50
51
53
49
54
57
58
56
60
55
54
52
55
56
54
53
59
62
63
64
75
77
79
77
82
83
81
78
79
79
73
72

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 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=30896&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]2 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=30896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30896&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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)12
Box-Cox transformation parameter (lambda) of Y series2
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-170.0233111450960611
-16-0.0499271298314701
-150.0132410154923036
-140.0569732696888653
-130.0373606286366824
-12-0.0631084808995035
-11-0.0738327189636983
-100.115502171680521
-90.0793928565839375
-80.0209968729517733
-70.0965303084256519
-60.076761927263841
-50.0239399727519992
-4-0.0135130645591494
-30.000795957069981944
-2-0.00600708153595813
-10.0952207109830301
0-0.190860151468567
10.0848193424425071
20.0355728098325024
3-0.0795276731608315
4-0.111956948691908
5-0.0540428534321936
6-0.0297866117761273
7-0.135502998191549
8-0.033818425539392
90.115125763797833
10-0.096821382807829
11-0.0885071905841476
12-0.0515456621563759
130.148021094842569
14-0.169463876318751
15-0.00900139006475147
160.0472695823264318
17-0.0712998498289714

\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) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 2 \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
-17 & 0.0233111450960611 \tabularnewline
-16 & -0.0499271298314701 \tabularnewline
-15 & 0.0132410154923036 \tabularnewline
-14 & 0.0569732696888653 \tabularnewline
-13 & 0.0373606286366824 \tabularnewline
-12 & -0.0631084808995035 \tabularnewline
-11 & -0.0738327189636983 \tabularnewline
-10 & 0.115502171680521 \tabularnewline
-9 & 0.0793928565839375 \tabularnewline
-8 & 0.0209968729517733 \tabularnewline
-7 & 0.0965303084256519 \tabularnewline
-6 & 0.076761927263841 \tabularnewline
-5 & 0.0239399727519992 \tabularnewline
-4 & -0.0135130645591494 \tabularnewline
-3 & 0.000795957069981944 \tabularnewline
-2 & -0.00600708153595813 \tabularnewline
-1 & 0.0952207109830301 \tabularnewline
0 & -0.190860151468567 \tabularnewline
1 & 0.0848193424425071 \tabularnewline
2 & 0.0355728098325024 \tabularnewline
3 & -0.0795276731608315 \tabularnewline
4 & -0.111956948691908 \tabularnewline
5 & -0.0540428534321936 \tabularnewline
6 & -0.0297866117761273 \tabularnewline
7 & -0.135502998191549 \tabularnewline
8 & -0.033818425539392 \tabularnewline
9 & 0.115125763797833 \tabularnewline
10 & -0.096821382807829 \tabularnewline
11 & -0.0885071905841476 \tabularnewline
12 & -0.0515456621563759 \tabularnewline
13 & 0.148021094842569 \tabularnewline
14 & -0.169463876318751 \tabularnewline
15 & -0.00900139006475147 \tabularnewline
16 & 0.0472695823264318 \tabularnewline
17 & -0.0712998498289714 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30896&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]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]2[/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]-17[/C][C]0.0233111450960611[/C][/ROW]
[ROW][C]-16[/C][C]-0.0499271298314701[/C][/ROW]
[ROW][C]-15[/C][C]0.0132410154923036[/C][/ROW]
[ROW][C]-14[/C][C]0.0569732696888653[/C][/ROW]
[ROW][C]-13[/C][C]0.0373606286366824[/C][/ROW]
[ROW][C]-12[/C][C]-0.0631084808995035[/C][/ROW]
[ROW][C]-11[/C][C]-0.0738327189636983[/C][/ROW]
[ROW][C]-10[/C][C]0.115502171680521[/C][/ROW]
[ROW][C]-9[/C][C]0.0793928565839375[/C][/ROW]
[ROW][C]-8[/C][C]0.0209968729517733[/C][/ROW]
[ROW][C]-7[/C][C]0.0965303084256519[/C][/ROW]
[ROW][C]-6[/C][C]0.076761927263841[/C][/ROW]
[ROW][C]-5[/C][C]0.0239399727519992[/C][/ROW]
[ROW][C]-4[/C][C]-0.0135130645591494[/C][/ROW]
[ROW][C]-3[/C][C]0.000795957069981944[/C][/ROW]
[ROW][C]-2[/C][C]-0.00600708153595813[/C][/ROW]
[ROW][C]-1[/C][C]0.0952207109830301[/C][/ROW]
[ROW][C]0[/C][C]-0.190860151468567[/C][/ROW]
[ROW][C]1[/C][C]0.0848193424425071[/C][/ROW]
[ROW][C]2[/C][C]0.0355728098325024[/C][/ROW]
[ROW][C]3[/C][C]-0.0795276731608315[/C][/ROW]
[ROW][C]4[/C][C]-0.111956948691908[/C][/ROW]
[ROW][C]5[/C][C]-0.0540428534321936[/C][/ROW]
[ROW][C]6[/C][C]-0.0297866117761273[/C][/ROW]
[ROW][C]7[/C][C]-0.135502998191549[/C][/ROW]
[ROW][C]8[/C][C]-0.033818425539392[/C][/ROW]
[ROW][C]9[/C][C]0.115125763797833[/C][/ROW]
[ROW][C]10[/C][C]-0.096821382807829[/C][/ROW]
[ROW][C]11[/C][C]-0.0885071905841476[/C][/ROW]
[ROW][C]12[/C][C]-0.0515456621563759[/C][/ROW]
[ROW][C]13[/C][C]0.148021094842569[/C][/ROW]
[ROW][C]14[/C][C]-0.169463876318751[/C][/ROW]
[ROW][C]15[/C][C]-0.00900139006475147[/C][/ROW]
[ROW][C]16[/C][C]0.0472695823264318[/C][/ROW]
[ROW][C]17[/C][C]-0.0712998498289714[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30896&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)12
Box-Cox transformation parameter (lambda) of Y series2
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-170.0233111450960611
-16-0.0499271298314701
-150.0132410154923036
-140.0569732696888653
-130.0373606286366824
-12-0.0631084808995035
-11-0.0738327189636983
-100.115502171680521
-90.0793928565839375
-80.0209968729517733
-70.0965303084256519
-60.076761927263841
-50.0239399727519992
-4-0.0135130645591494
-30.000795957069981944
-2-0.00600708153595813
-10.0952207109830301
0-0.190860151468567
10.0848193424425071
20.0355728098325024
3-0.0795276731608315
4-0.111956948691908
5-0.0540428534321936
6-0.0297866117761273
7-0.135502998191549
8-0.033818425539392
90.115125763797833
10-0.096821382807829
11-0.0885071905841476
12-0.0515456621563759
130.148021094842569
14-0.169463876318751
15-0.00900139006475147
160.0472695823264318
17-0.0712998498289714


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 2.0 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 2.0 ; 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')