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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 computationTue, 02 Dec 2008 15:03:42 -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/02/t12282555072pvtk10qq94gnvd.htm/, Retrieved Tue, 14 May 2024 06:56:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28504, Retrieved Tue, 14 May 2024 06:56:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact208

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]
- RM D  [Cross Correlation Function] [Opdracht 1 - Blok...] [2008-11-26 22:16:36] [8094ad203a218aaca2d1cea2c78c2d6e]
F    D    [Cross Correlation Function] [Opdracht 1 - Blok...] [2008-12-02 21:57:15] [8094ad203a218aaca2d1cea2c78c2d6e]
-             [Cross Correlation Function] [Opdracht 1 - Blok...] [2008-12-02 22:03:42] [1351baa662f198be3bff32f9007a9a6d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.1
101.1
111.1
93.3
100
108
70.4
75.4
105.5
112.3
102.5
93.5
86.7
95.2
103.8
97
95.5
101
67.5
64
106.7
100.6
101.2
93.1
84.2
85.8
91.8
92.4
80.3
79.7
62.5
57.1
100.8
100.7
86.2
83.2
71.7
77.5
89.8
80.3
78.7
93.8
57.6
60.6
91
85.3
77.4
77.3
68.3
69.9
81.7
75.1
69.9
84
54.3
60
89.9
77
85.3
77.6
69.2
Dataseries Y:
Download CSV
Histogram 
13
8
7
3
3
4
4
0
-4
-14
-18
-8
-1
1
2
0
1
0
-1
-3
-3
-3
-4
-8
-9
-13
-18
-11
-9
-10
-13
-11
-5
-15
-6
-6
-3
-1
-3
-4
-6
0
-4
-2
-2
-6
-7
-6
-6
-3
-2
-5
-11
-11
-11
-10
-14
-8
-9
-5
-1

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=28504&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=28504&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28504&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 series0.1
Degree of non-seasonal differencing (d) of X series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-130.143983969005892
-120.158561105404322
-110.167482895500105
-100.232807301162556
-90.249917045659208
-80.185603525149838
-70.0712392712425267
-60.0762600947180473
-5-0.0260433415871085
-4-0.0610294833841149
-30.104077552431218
-2-0.0488335887914835
-1-0.0542019961014644
0-0.146653646976641
1-0.150523462543484
2-0.112428587649964
3-0.0786192281596693
4-0.0369103793327347
5-0.0178738429244351
60.084554435355347
70.221773295002607
80.204802278135704
90.0651973051613259
100.0246652928928834
11-0.0627707650354874
12-0.0276455698771507
13-0.108085439633669

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.143983969005892 \tabularnewline
-12 & 0.158561105404322 \tabularnewline
-11 & 0.167482895500105 \tabularnewline
-10 & 0.232807301162556 \tabularnewline
-9 & 0.249917045659208 \tabularnewline
-8 & 0.185603525149838 \tabularnewline
-7 & 0.0712392712425267 \tabularnewline
-6 & 0.0762600947180473 \tabularnewline
-5 & -0.0260433415871085 \tabularnewline
-4 & -0.0610294833841149 \tabularnewline
-3 & 0.104077552431218 \tabularnewline
-2 & -0.0488335887914835 \tabularnewline
-1 & -0.0542019961014644 \tabularnewline
0 & -0.146653646976641 \tabularnewline
1 & -0.150523462543484 \tabularnewline
2 & -0.112428587649964 \tabularnewline
3 & -0.0786192281596693 \tabularnewline
4 & -0.0369103793327347 \tabularnewline
5 & -0.0178738429244351 \tabularnewline
6 & 0.084554435355347 \tabularnewline
7 & 0.221773295002607 \tabularnewline
8 & 0.204802278135704 \tabularnewline
9 & 0.0651973051613259 \tabularnewline
10 & 0.0246652928928834 \tabularnewline
11 & -0.0627707650354874 \tabularnewline
12 & -0.0276455698771507 \tabularnewline
13 & -0.108085439633669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28504&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]0.1[/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]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]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]-13[/C][C]0.143983969005892[/C][/ROW]
[ROW][C]-12[/C][C]0.158561105404322[/C][/ROW]
[ROW][C]-11[/C][C]0.167482895500105[/C][/ROW]
[ROW][C]-10[/C][C]0.232807301162556[/C][/ROW]
[ROW][C]-9[/C][C]0.249917045659208[/C][/ROW]
[ROW][C]-8[/C][C]0.185603525149838[/C][/ROW]
[ROW][C]-7[/C][C]0.0712392712425267[/C][/ROW]
[ROW][C]-6[/C][C]0.0762600947180473[/C][/ROW]
[ROW][C]-5[/C][C]-0.0260433415871085[/C][/ROW]
[ROW][C]-4[/C][C]-0.0610294833841149[/C][/ROW]
[ROW][C]-3[/C][C]0.104077552431218[/C][/ROW]
[ROW][C]-2[/C][C]-0.0488335887914835[/C][/ROW]
[ROW][C]-1[/C][C]-0.0542019961014644[/C][/ROW]
[ROW][C]0[/C][C]-0.146653646976641[/C][/ROW]
[ROW][C]1[/C][C]-0.150523462543484[/C][/ROW]
[ROW][C]2[/C][C]-0.112428587649964[/C][/ROW]
[ROW][C]3[/C][C]-0.0786192281596693[/C][/ROW]
[ROW][C]4[/C][C]-0.0369103793327347[/C][/ROW]
[ROW][C]5[/C][C]-0.0178738429244351[/C][/ROW]
[ROW][C]6[/C][C]0.084554435355347[/C][/ROW]
[ROW][C]7[/C][C]0.221773295002607[/C][/ROW]
[ROW][C]8[/C][C]0.204802278135704[/C][/ROW]
[ROW][C]9[/C][C]0.0651973051613259[/C][/ROW]
[ROW][C]10[/C][C]0.0246652928928834[/C][/ROW]
[ROW][C]11[/C][C]-0.0627707650354874[/C][/ROW]
[ROW][C]12[/C][C]-0.0276455698771507[/C][/ROW]
[ROW][C]13[/C][C]-0.108085439633669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28504&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28504&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 series0.1
Degree of non-seasonal differencing (d) of X series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-130.143983969005892
-120.158561105404322
-110.167482895500105
-100.232807301162556
-90.249917045659208
-80.185603525149838
-70.0712392712425267
-60.0762600947180473
-5-0.0260433415871085
-4-0.0610294833841149
-30.104077552431218
-2-0.0488335887914835
-1-0.0542019961014644
0-0.146653646976641
1-0.150523462543484
2-0.112428587649964
3-0.0786192281596693
4-0.0369103793327347
5-0.0178738429244351
60.084554435355347
70.221773295002607
80.204802278135704
90.0651973051613259
100.0246652928928834
11-0.0627707650354874
12-0.0276455698771507
13-0.108085439633669


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Airline ; par2 = Box-Jenkins ; par3 = Airline Passengers ;
Parameters (R input):
par1 = 0.1 ; par2 = 0 ; par3 = 1 ; 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) 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')