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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 computationThu, 18 Dec 2008 04:54:21 -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/18/t12296013739zz16pa82zdboxt.htm/, Retrieved Sat, 11 May 2024 04:24:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34683, Retrieved Sat, 11 May 2024 04:24:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137

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...] [2008-12-18 11:54:21] [9e8e8f1cf6738240aaa61f66e2e3fd45] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
124
118.63
121.86
119.97
125.03
130.09
126.65
121.7
119.24
122.63
116.66
114.12
113.11
112.61
113.4
115.18
121.01
119.44
116.68
117.07
117.41
119.58
120.92
117.09
116.77
119.39
122.49
124.08
118.29
112.94
113.79
114.43
118.7
120.36
118.27
118.34
117.82
117.65
118.18
121.02
124.78
131.16
130.14
131.75
134.73
135.35
140.32
136.35
131.6
128.9
133.89
138.25
146.23
144.76
149.3
156.8
159.08
165.12
163.14
153.43
151.01
Dataseries Y:
Download CSV
Histogram 
104.89
105.15
105.24
105.57
105.62
106.17
106.27
106.41
106.94
107.16
107.32
107.32
107.35
107.55
107.87
108.37
108.38
107.92
108.03
108.14
108.3
108.64
108.66
109.04
109.03
109.03
109.54
109.75
109.83
109.65
109.82
109.95
110.12
110.15
110.21
109.99
110.14
110.14
110.81
110.97
110.99
109.73
109.81
110.02
110.18
110.21
110.25
110.36
110.51
110.6
110.95
111.18
111.19
111.69
111.7
111.83
111.77
111.73
112.01
111.86
112.04

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34683&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34683&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34683&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'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 series0
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 series0
krho(Y[t],X[t+k])
-14-0.0537349466526106
-130.00722954618774656
-120.204055044086553
-110.0888911121290896
-100.0824564832461619
-9-0.119980910835507
-8-0.136178975734455
-70.0906724236493511
-60.143624759344514
-50.000285875628217602
-4-0.0796103969880041
-3-0.0497806016649849
-2-0.257492301486735
-1-0.0342576589940808
0-0.0803565300078772
10.156592517161658
2-0.00770663594090608
3-0.0841883605561752
40.01017851538697
5-0.192771137149621
60.0941515817337196
70.152272897728841
80.0247801643027039
9-0.279796538974604
10-0.219232667600047
11-0.120007287948406
120.174130052303691
13-0.0187195920686183
14-0.103280765734249

\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 & 1 \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
-14 & -0.0537349466526106 \tabularnewline
-13 & 0.00722954618774656 \tabularnewline
-12 & 0.204055044086553 \tabularnewline
-11 & 0.0888911121290896 \tabularnewline
-10 & 0.0824564832461619 \tabularnewline
-9 & -0.119980910835507 \tabularnewline
-8 & -0.136178975734455 \tabularnewline
-7 & 0.0906724236493511 \tabularnewline
-6 & 0.143624759344514 \tabularnewline
-5 & 0.000285875628217602 \tabularnewline
-4 & -0.0796103969880041 \tabularnewline
-3 & -0.0497806016649849 \tabularnewline
-2 & -0.257492301486735 \tabularnewline
-1 & -0.0342576589940808 \tabularnewline
0 & -0.0803565300078772 \tabularnewline
1 & 0.156592517161658 \tabularnewline
2 & -0.00770663594090608 \tabularnewline
3 & -0.0841883605561752 \tabularnewline
4 & 0.01017851538697 \tabularnewline
5 & -0.192771137149621 \tabularnewline
6 & 0.0941515817337196 \tabularnewline
7 & 0.152272897728841 \tabularnewline
8 & 0.0247801643027039 \tabularnewline
9 & -0.279796538974604 \tabularnewline
10 & -0.219232667600047 \tabularnewline
11 & -0.120007287948406 \tabularnewline
12 & 0.174130052303691 \tabularnewline
13 & -0.0187195920686183 \tabularnewline
14 & -0.103280765734249 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34683&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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]-0.0537349466526106[/C][/ROW]
[ROW][C]-13[/C][C]0.00722954618774656[/C][/ROW]
[ROW][C]-12[/C][C]0.204055044086553[/C][/ROW]
[ROW][C]-11[/C][C]0.0888911121290896[/C][/ROW]
[ROW][C]-10[/C][C]0.0824564832461619[/C][/ROW]
[ROW][C]-9[/C][C]-0.119980910835507[/C][/ROW]
[ROW][C]-8[/C][C]-0.136178975734455[/C][/ROW]
[ROW][C]-7[/C][C]0.0906724236493511[/C][/ROW]
[ROW][C]-6[/C][C]0.143624759344514[/C][/ROW]
[ROW][C]-5[/C][C]0.000285875628217602[/C][/ROW]
[ROW][C]-4[/C][C]-0.0796103969880041[/C][/ROW]
[ROW][C]-3[/C][C]-0.0497806016649849[/C][/ROW]
[ROW][C]-2[/C][C]-0.257492301486735[/C][/ROW]
[ROW][C]-1[/C][C]-0.0342576589940808[/C][/ROW]
[ROW][C]0[/C][C]-0.0803565300078772[/C][/ROW]
[ROW][C]1[/C][C]0.156592517161658[/C][/ROW]
[ROW][C]2[/C][C]-0.00770663594090608[/C][/ROW]
[ROW][C]3[/C][C]-0.0841883605561752[/C][/ROW]
[ROW][C]4[/C][C]0.01017851538697[/C][/ROW]
[ROW][C]5[/C][C]-0.192771137149621[/C][/ROW]
[ROW][C]6[/C][C]0.0941515817337196[/C][/ROW]
[ROW][C]7[/C][C]0.152272897728841[/C][/ROW]
[ROW][C]8[/C][C]0.0247801643027039[/C][/ROW]
[ROW][C]9[/C][C]-0.279796538974604[/C][/ROW]
[ROW][C]10[/C][C]-0.219232667600047[/C][/ROW]
[ROW][C]11[/C][C]-0.120007287948406[/C][/ROW]
[ROW][C]12[/C][C]0.174130052303691[/C][/ROW]
[ROW][C]13[/C][C]-0.0187195920686183[/C][/ROW]
[ROW][C]14[/C][C]-0.103280765734249[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34683&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34683&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 series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.0537349466526106
-130.00722954618774656
-120.204055044086553
-110.0888911121290896
-100.0824564832461619
-9-0.119980910835507
-8-0.136178975734455
-70.0906724236493511
-60.143624759344514
-50.000285875628217602
-4-0.0796103969880041
-3-0.0497806016649849
-2-0.257492301486735
-1-0.0342576589940808
0-0.0803565300078772
10.156592517161658
2-0.00770663594090608
3-0.0841883605561752
40.01017851538697
5-0.192771137149621
60.0941515817337196
70.152272897728841
80.0247801643027039
9-0.279796538974604
10-0.219232667600047
11-0.120007287948406
120.174130052303691
13-0.0187195920686183
14-0.103280765734249


Figures (Output of Computation)

Input Parameters & R Code

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