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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationThu, 29 Nov 2007 14:25:41 -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/2007/Nov/29/t1196370904dt79mti1h9nz0oi.htm/, Retrieved Fri, 03 May 2024 08:06:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7608, Retrieved Fri, 03 May 2024 08:06:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Broodprijs & Infl...] [2007-11-29 21:25:41] [5a8e7c1f041681f87e3014e302618e0c] [Current]
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Dataseries X:
1,43
1,43
1,43
1,43
1,43
1,43
1,44
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,48
1,57
1,58
1,58
1,58
1,58
1,59
1,6
1,6
1,61
1,61
1,61
1,62
1,63
1,63
1,64
1,64
1,64
1,64
1,64
1,65
1,65
1,65
1,65
Dataseries Y:
1,6
1,6
1,4
1,7
1,8
1,9
2,2
2,1
2,4
2,6
2,8
2,7
2,6
2,9
2,8
2,2
2,2
2,2
2
2
1,7
1,4
1,3
1,4
1,3
1,3
1,4
2
1,7
1,8
1,7
1,6
1,7
1,9
1,8
1,7
1,6
1,8
1,6
1,5
1,5
1,3
1,4
1,4
1,3
1,3
1,2
1,1
1,4
1,2
1,5
1,1
1,3
1,5
1,1
1,4
1,3
1,5
1,6
1,7




Summary of compuational 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 compuational 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=7608&T=0

[TABLE]
[ROW][C]Summary of compuational 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=7608&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7608&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 compuational 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)1
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])
-14-0.265610802878841
-130.114243881854836
-12-0.0782995494032162
-110.115790601076960
-100.0437685983097447
-9-0.0969579611689572
-8-0.126393628020350
-7-0.0156929776709092
-60.0609176254552742
-50.0416565265443618
-4-0.0967623989684587
-30.0308259363131182
-20.00537618267552225
-1-0.0332900200393997
00.0719562227543206
10.0742247442801023
2-0.0906004118145702
30.0129942193040306
40.140609222158403
5-0.00722335655113906
6-0.0225767671284556
7-0.104222207998382
80.0674476251137376
9-0.164613593350497
100.30023064588163
110.09135065952921
120.0115932828131865
13-0.065017320312997
140.0440317183613246

\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) & 1 \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 & -0.265610802878841 \tabularnewline
-13 & 0.114243881854836 \tabularnewline
-12 & -0.0782995494032162 \tabularnewline
-11 & 0.115790601076960 \tabularnewline
-10 & 0.0437685983097447 \tabularnewline
-9 & -0.0969579611689572 \tabularnewline
-8 & -0.126393628020350 \tabularnewline
-7 & -0.0156929776709092 \tabularnewline
-6 & 0.0609176254552742 \tabularnewline
-5 & 0.0416565265443618 \tabularnewline
-4 & -0.0967623989684587 \tabularnewline
-3 & 0.0308259363131182 \tabularnewline
-2 & 0.00537618267552225 \tabularnewline
-1 & -0.0332900200393997 \tabularnewline
0 & 0.0719562227543206 \tabularnewline
1 & 0.0742247442801023 \tabularnewline
2 & -0.0906004118145702 \tabularnewline
3 & 0.0129942193040306 \tabularnewline
4 & 0.140609222158403 \tabularnewline
5 & -0.00722335655113906 \tabularnewline
6 & -0.0225767671284556 \tabularnewline
7 & -0.104222207998382 \tabularnewline
8 & 0.0674476251137376 \tabularnewline
9 & -0.164613593350497 \tabularnewline
10 & 0.30023064588163 \tabularnewline
11 & 0.09135065952921 \tabularnewline
12 & 0.0115932828131865 \tabularnewline
13 & -0.065017320312997 \tabularnewline
14 & 0.0440317183613246 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7608&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]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]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]-0.265610802878841[/C][/ROW]
[ROW][C]-13[/C][C]0.114243881854836[/C][/ROW]
[ROW][C]-12[/C][C]-0.0782995494032162[/C][/ROW]
[ROW][C]-11[/C][C]0.115790601076960[/C][/ROW]
[ROW][C]-10[/C][C]0.0437685983097447[/C][/ROW]
[ROW][C]-9[/C][C]-0.0969579611689572[/C][/ROW]
[ROW][C]-8[/C][C]-0.126393628020350[/C][/ROW]
[ROW][C]-7[/C][C]-0.0156929776709092[/C][/ROW]
[ROW][C]-6[/C][C]0.0609176254552742[/C][/ROW]
[ROW][C]-5[/C][C]0.0416565265443618[/C][/ROW]
[ROW][C]-4[/C][C]-0.0967623989684587[/C][/ROW]
[ROW][C]-3[/C][C]0.0308259363131182[/C][/ROW]
[ROW][C]-2[/C][C]0.00537618267552225[/C][/ROW]
[ROW][C]-1[/C][C]-0.0332900200393997[/C][/ROW]
[ROW][C]0[/C][C]0.0719562227543206[/C][/ROW]
[ROW][C]1[/C][C]0.0742247442801023[/C][/ROW]
[ROW][C]2[/C][C]-0.0906004118145702[/C][/ROW]
[ROW][C]3[/C][C]0.0129942193040306[/C][/ROW]
[ROW][C]4[/C][C]0.140609222158403[/C][/ROW]
[ROW][C]5[/C][C]-0.00722335655113906[/C][/ROW]
[ROW][C]6[/C][C]-0.0225767671284556[/C][/ROW]
[ROW][C]7[/C][C]-0.104222207998382[/C][/ROW]
[ROW][C]8[/C][C]0.0674476251137376[/C][/ROW]
[ROW][C]9[/C][C]-0.164613593350497[/C][/ROW]
[ROW][C]10[/C][C]0.30023064588163[/C][/ROW]
[ROW][C]11[/C][C]0.09135065952921[/C][/ROW]
[ROW][C]12[/C][C]0.0115932828131865[/C][/ROW]
[ROW][C]13[/C][C]-0.065017320312997[/C][/ROW]
[ROW][C]14[/C][C]0.0440317183613246[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7608&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7608&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)1
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])
-14-0.265610802878841
-130.114243881854836
-12-0.0782995494032162
-110.115790601076960
-100.0437685983097447
-9-0.0969579611689572
-8-0.126393628020350
-7-0.0156929776709092
-60.0609176254552742
-50.0416565265443618
-4-0.0967623989684587
-30.0308259363131182
-20.00537618267552225
-1-0.0332900200393997
00.0719562227543206
10.0742247442801023
2-0.0906004118145702
30.0129942193040306
40.140609222158403
5-0.00722335655113906
6-0.0225767671284556
7-0.104222207998382
80.0674476251137376
9-0.164613593350497
100.30023064588163
110.09135065952921
120.0115932828131865
13-0.065017320312997
140.0440317183613246



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')