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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationTue, 02 Dec 2008 06:49:03 -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/t1228225792vbid7fclz3jv8w9.htm/, Retrieved Sun, 19 May 2024 11:37:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27787, Retrieved Sun, 19 May 2024 11:37:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cross Correlation Function] [] [2008-12-02 13:40:49] [74be16979710d4c4e7c6647856088456]
F   P   [Cross Correlation Function] [] [2008-12-02 13:44:21] [74be16979710d4c4e7c6647856088456]
-   P       [Cross Correlation Function] [] [2008-12-02 13:49:03] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
4.56
4.41
4.33
4.20
4.25
4.25
4.19
4.17
4.21
4.21
4.17
4.16
4.19
4.08
4.06
3.98
3.82
3.82
3.72
3.56
3.57
3.49
3.32
3.23
3.04
3.00
2.82
2.73
2.59
2.58
2.53
2.31
2.31
2.30
2.07
2.07
2.06
2.06
2.05
2.05
2.05
2.05
2.05
2.06
2.07
2.08
2.05
2.03
2.02
2.02
2.01
2.01
2.01
2.01
2.01
2.01
2.03
2.04
2.03
2.05
2.08
2.06
2.09
2.19
2.56
2.54
2.63
2.78
2.84
3.02
3.28
3.29
3.29
3.29
3.32
3.34
3.32
3.30
3.30
3.30
3.31
3.35
3.48
3.76
4.06
4.51
4.52
4.53
4.63
4.79
4.77
4.77
4.77
4.81
4.83
4.76
4.61
Dataseries Y:
5.1
4.9
5.2
5.1
4.6
3.7
3.9
3.1
2.8
2.6
2.2
1.8
1.3
1.2
1.4
1.3
1.3
1.9
1.9
2.1
2.0
1.9
1.9
1.9
1.8
1.7
1.6
1.7
1.9
1.7
1.3
2.0
2.0
2.3
2.0
1.7
2.3
2.4
2.4
2.3
2.1
2.1
2.5
2.0
1.8
1.7
1.9
2.1
1.4
1.6
1.7
1.6
1.9
1.6
1.1
1.3
1.6
1.6
1.7
1.6
1.7
1.6
1.5
1.6
1.1
1.5
1.4
1.3
0.9
1.2
0.9
1.1
1.3
1.3
1.4
1.2
1.7
2.0
3.0
3.1
3.2
2.7
2.8
3.0
2.8
3.1
3.1
3.2
3.1
2.7
2.2
2.2
2.1
2.3
2.5
2.3
2.6




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=27787&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=27787&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27787&T=0

As an alternative you can also use a 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 series-0.5
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.0108070076577080
-15-0.0455467805711560
-140.109879304421038
-130.0664833888508641
-120.0703480612950768
-110.0429726826152915
-100.0916290443959148
-90.139545683999101
-80.114124223349849
-70.0638294274322133
-6-0.00815235967795531
-5-0.0167315972120066
-4-0.093098497719009
-30.00605877439768973
-20.0584441027616006
-1-0.0148619675992000
0-0.162081659068235
10.0541310596489284
2-0.0862462299354433
3-0.0718258524021504
40.094314188354494
50.0653677743915024
60.126288325295815
70.183011919270843
80.145878609845236
90.128941433198905
10-0.0340457705071162
110.151730466495693
120.183216734609487
130.103977225836308
140.096689724179535
15-0.0183909200339855
16-0.0636850139860025

\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 & -0.5 \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
-16 & -0.0108070076577080 \tabularnewline
-15 & -0.0455467805711560 \tabularnewline
-14 & 0.109879304421038 \tabularnewline
-13 & 0.0664833888508641 \tabularnewline
-12 & 0.0703480612950768 \tabularnewline
-11 & 0.0429726826152915 \tabularnewline
-10 & 0.0916290443959148 \tabularnewline
-9 & 0.139545683999101 \tabularnewline
-8 & 0.114124223349849 \tabularnewline
-7 & 0.0638294274322133 \tabularnewline
-6 & -0.00815235967795531 \tabularnewline
-5 & -0.0167315972120066 \tabularnewline
-4 & -0.093098497719009 \tabularnewline
-3 & 0.00605877439768973 \tabularnewline
-2 & 0.0584441027616006 \tabularnewline
-1 & -0.0148619675992000 \tabularnewline
0 & -0.162081659068235 \tabularnewline
1 & 0.0541310596489284 \tabularnewline
2 & -0.0862462299354433 \tabularnewline
3 & -0.0718258524021504 \tabularnewline
4 & 0.094314188354494 \tabularnewline
5 & 0.0653677743915024 \tabularnewline
6 & 0.126288325295815 \tabularnewline
7 & 0.183011919270843 \tabularnewline
8 & 0.145878609845236 \tabularnewline
9 & 0.128941433198905 \tabularnewline
10 & -0.0340457705071162 \tabularnewline
11 & 0.151730466495693 \tabularnewline
12 & 0.183216734609487 \tabularnewline
13 & 0.103977225836308 \tabularnewline
14 & 0.096689724179535 \tabularnewline
15 & -0.0183909200339855 \tabularnewline
16 & -0.0636850139860025 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27787&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]-0.5[/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]-16[/C][C]-0.0108070076577080[/C][/ROW]
[ROW][C]-15[/C][C]-0.0455467805711560[/C][/ROW]
[ROW][C]-14[/C][C]0.109879304421038[/C][/ROW]
[ROW][C]-13[/C][C]0.0664833888508641[/C][/ROW]
[ROW][C]-12[/C][C]0.0703480612950768[/C][/ROW]
[ROW][C]-11[/C][C]0.0429726826152915[/C][/ROW]
[ROW][C]-10[/C][C]0.0916290443959148[/C][/ROW]
[ROW][C]-9[/C][C]0.139545683999101[/C][/ROW]
[ROW][C]-8[/C][C]0.114124223349849[/C][/ROW]
[ROW][C]-7[/C][C]0.0638294274322133[/C][/ROW]
[ROW][C]-6[/C][C]-0.00815235967795531[/C][/ROW]
[ROW][C]-5[/C][C]-0.0167315972120066[/C][/ROW]
[ROW][C]-4[/C][C]-0.093098497719009[/C][/ROW]
[ROW][C]-3[/C][C]0.00605877439768973[/C][/ROW]
[ROW][C]-2[/C][C]0.0584441027616006[/C][/ROW]
[ROW][C]-1[/C][C]-0.0148619675992000[/C][/ROW]
[ROW][C]0[/C][C]-0.162081659068235[/C][/ROW]
[ROW][C]1[/C][C]0.0541310596489284[/C][/ROW]
[ROW][C]2[/C][C]-0.0862462299354433[/C][/ROW]
[ROW][C]3[/C][C]-0.0718258524021504[/C][/ROW]
[ROW][C]4[/C][C]0.094314188354494[/C][/ROW]
[ROW][C]5[/C][C]0.0653677743915024[/C][/ROW]
[ROW][C]6[/C][C]0.126288325295815[/C][/ROW]
[ROW][C]7[/C][C]0.183011919270843[/C][/ROW]
[ROW][C]8[/C][C]0.145878609845236[/C][/ROW]
[ROW][C]9[/C][C]0.128941433198905[/C][/ROW]
[ROW][C]10[/C][C]-0.0340457705071162[/C][/ROW]
[ROW][C]11[/C][C]0.151730466495693[/C][/ROW]
[ROW][C]12[/C][C]0.183216734609487[/C][/ROW]
[ROW][C]13[/C][C]0.103977225836308[/C][/ROW]
[ROW][C]14[/C][C]0.096689724179535[/C][/ROW]
[ROW][C]15[/C][C]-0.0183909200339855[/C][/ROW]
[ROW][C]16[/C][C]-0.0636850139860025[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27787&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27787&T=1

As an alternative you can also use a 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 series-0.5
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.0108070076577080
-15-0.0455467805711560
-140.109879304421038
-130.0664833888508641
-120.0703480612950768
-110.0429726826152915
-100.0916290443959148
-90.139545683999101
-80.114124223349849
-70.0638294274322133
-6-0.00815235967795531
-5-0.0167315972120066
-4-0.093098497719009
-30.00605877439768973
-20.0584441027616006
-1-0.0148619675992000
0-0.162081659068235
10.0541310596489284
2-0.0862462299354433
3-0.0718258524021504
40.094314188354494
50.0653677743915024
60.126288325295815
70.183011919270843
80.145878609845236
90.128941433198905
10-0.0340457705071162
110.151730466495693
120.183216734609487
130.103977225836308
140.096689724179535
15-0.0183909200339855
16-0.0636850139860025



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = -0.5 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = -0.5 ; 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')