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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, 28 Dec 2008 06:52:27 -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/28/t1230472397679p80lue88otnf.htm/, Retrieved Sat, 18 May 2024 06:28:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36702, Retrieved Sat, 18 May 2024 06:28:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper - Cross correlation - Prodcuten van metaal (X) / Machines (Y)
Estimated Impact267

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] [Paper - Cross cor...] [2007-12-18 20:54:04] [5343e105a400b9e32bf6f011133bbaf4]
-    D    [Cross Correlation Function] [Paper - Cross cor...] [2008-12-28 13:52:27] [3efbb18563b4564408d69b3c9a8e9a6e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.65
-1.53
-3.36
10.51
-1.02
-2.68
-9.75
3.64
9.5
-0.33
-0.99
3.16
4.27
-2.97
-7.49
0.33
-2.57
4.07
5.31
-8.09
5.29
7.38
-6.12
-3.38
-8.61
2.58
10.02
7.08
-2.75
3.42
-1.6
0.65
2.86
-3.52
5.65
4.31
-4.39
-5.85
-5.47
-2.3
-0.14
8.08
-7.43
0.02
-2.47
-2.11
7.87
4.66
3.6
-3.64
7.26
-7.62
13.83
1.28
-0.32
-2.9
4.92
11.99
10.06
-2.22
3.97
0.56
3.34
-2.86
4.38
1.43
-0.49
-1.23
Dataseries Y:
Download CSV
Histogram 
-0.36
3.69
0.68
7.63
-1.52
5.71
13.19
-5.5
1.77
1.97
-5.61
-7.32
-1.09
-0.1
-9.4
-6.39
-2.03
0.9
7.57
-2.19
3.59
-1.69
-1.54
13.36
-3.66
0.61
9.25
11.03
-3.5
-6.56
5.55
16.5
-0.09
-10.19
-1.56
3.62
-3.46
-0.84
-1.75
-5.59
-4.31
8.29
-14.07
-4.08
3.96
-2.54
24.36
11.73
3.82
-2.98
7.46
-6.39
11.7
2.36
-7.48
-2.54
-2.31
10.86
-2.11
3.41
11.2
-1.21
5.82
-2.61
-1.54
-5.42
11.6
-9.07

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=36702&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=36702&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36702&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 series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
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])
-15-0.0320496071754534
-140.169024880073458
-13-0.138650845338077
-120.00803478053337927
-11-0.0570801408116196
-100.0472120213695721
-90.0221650688343053
-8-0.225106230968944
-7-0.221851301646007
-60.0965544595254764
-50.262774589032676
-4-0.135938014597329
-3-0.06184856210442
-20.00490496775885789
-1-0.0284063177262118
00.4271293682949
1-0.136690266542864
20.0950817639876442
30.0217956980546414
40.0848961567275228
50.0252025040284434
60.0856161004146707
7-0.108509370937613
8-0.00838227028484783
90.146820818925243
10-0.0696815036681196
110.0674241329841451
120.106657664578695
13-0.170446854443652
14-0.0240755962628515
15-0.0316565652036593

\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) & 1 \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
-15 & -0.0320496071754534 \tabularnewline
-14 & 0.169024880073458 \tabularnewline
-13 & -0.138650845338077 \tabularnewline
-12 & 0.00803478053337927 \tabularnewline
-11 & -0.0570801408116196 \tabularnewline
-10 & 0.0472120213695721 \tabularnewline
-9 & 0.0221650688343053 \tabularnewline
-8 & -0.225106230968944 \tabularnewline
-7 & -0.221851301646007 \tabularnewline
-6 & 0.0965544595254764 \tabularnewline
-5 & 0.262774589032676 \tabularnewline
-4 & -0.135938014597329 \tabularnewline
-3 & -0.06184856210442 \tabularnewline
-2 & 0.00490496775885789 \tabularnewline
-1 & -0.0284063177262118 \tabularnewline
0 & 0.4271293682949 \tabularnewline
1 & -0.136690266542864 \tabularnewline
2 & 0.0950817639876442 \tabularnewline
3 & 0.0217956980546414 \tabularnewline
4 & 0.0848961567275228 \tabularnewline
5 & 0.0252025040284434 \tabularnewline
6 & 0.0856161004146707 \tabularnewline
7 & -0.108509370937613 \tabularnewline
8 & -0.00838227028484783 \tabularnewline
9 & 0.146820818925243 \tabularnewline
10 & -0.0696815036681196 \tabularnewline
11 & 0.0674241329841451 \tabularnewline
12 & 0.106657664578695 \tabularnewline
13 & -0.170446854443652 \tabularnewline
14 & -0.0240755962628515 \tabularnewline
15 & -0.0316565652036593 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36702&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]1[/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]-15[/C][C]-0.0320496071754534[/C][/ROW]
[ROW][C]-14[/C][C]0.169024880073458[/C][/ROW]
[ROW][C]-13[/C][C]-0.138650845338077[/C][/ROW]
[ROW][C]-12[/C][C]0.00803478053337927[/C][/ROW]
[ROW][C]-11[/C][C]-0.0570801408116196[/C][/ROW]
[ROW][C]-10[/C][C]0.0472120213695721[/C][/ROW]
[ROW][C]-9[/C][C]0.0221650688343053[/C][/ROW]
[ROW][C]-8[/C][C]-0.225106230968944[/C][/ROW]
[ROW][C]-7[/C][C]-0.221851301646007[/C][/ROW]
[ROW][C]-6[/C][C]0.0965544595254764[/C][/ROW]
[ROW][C]-5[/C][C]0.262774589032676[/C][/ROW]
[ROW][C]-4[/C][C]-0.135938014597329[/C][/ROW]
[ROW][C]-3[/C][C]-0.06184856210442[/C][/ROW]
[ROW][C]-2[/C][C]0.00490496775885789[/C][/ROW]
[ROW][C]-1[/C][C]-0.0284063177262118[/C][/ROW]
[ROW][C]0[/C][C]0.4271293682949[/C][/ROW]
[ROW][C]1[/C][C]-0.136690266542864[/C][/ROW]
[ROW][C]2[/C][C]0.0950817639876442[/C][/ROW]
[ROW][C]3[/C][C]0.0217956980546414[/C][/ROW]
[ROW][C]4[/C][C]0.0848961567275228[/C][/ROW]
[ROW][C]5[/C][C]0.0252025040284434[/C][/ROW]
[ROW][C]6[/C][C]0.0856161004146707[/C][/ROW]
[ROW][C]7[/C][C]-0.108509370937613[/C][/ROW]
[ROW][C]8[/C][C]-0.00838227028484783[/C][/ROW]
[ROW][C]9[/C][C]0.146820818925243[/C][/ROW]
[ROW][C]10[/C][C]-0.0696815036681196[/C][/ROW]
[ROW][C]11[/C][C]0.0674241329841451[/C][/ROW]
[ROW][C]12[/C][C]0.106657664578695[/C][/ROW]
[ROW][C]13[/C][C]-0.170446854443652[/C][/ROW]
[ROW][C]14[/C][C]-0.0240755962628515[/C][/ROW]
[ROW][C]15[/C][C]-0.0316565652036593[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36702&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36702&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)1
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])
-15-0.0320496071754534
-140.169024880073458
-13-0.138650845338077
-120.00803478053337927
-11-0.0570801408116196
-100.0472120213695721
-90.0221650688343053
-8-0.225106230968944
-7-0.221851301646007
-60.0965544595254764
-50.262774589032676
-4-0.135938014597329
-3-0.06184856210442
-20.00490496775885789
-1-0.0284063177262118
00.4271293682949
1-0.136690266542864
20.0950817639876442
30.0217956980546414
40.0848961567275228
50.0252025040284434
60.0856161004146707
7-0.108509370937613
8-0.00838227028484783
90.146820818925243
10-0.0696815036681196
110.0674241329841451
120.106657664578695
13-0.170446854443652
14-0.0240755962628515
15-0.0316565652036593


Figures (Output of Computation)

Input Parameters & R Code

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