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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 26 Nov 2007 12:26:54 -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/26/t1196104667rtau5o6nxy9w6cd.htm/, Retrieved Thu, 02 May 2024 22:48:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6644, Retrieved Thu, 02 May 2024 22:48:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [opdr 7 q 5 cross ...] [2007-11-26 19:26:54] [0c12eff582f43eaf43ae2f09e879befe] [Current]
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Dataseries X:
112,6
113,8
107,8
103,2
103,3
101,2
107,7
110,4
101,9
115,9
89,9
88,6
117,2
123,9
100
103,6
94,1
98,7
119,5
112,7
104,4
124,7
89,1
97
121,6
118,8
114
111,5
97,2
102,5
113,4
109,8
104,9
126,1
80
96,8
117,2
112,3
117,3
111,1
102,2
104,3
122,9
107,6
121,3
131,5
89
104,4
128,9
135,9
133,3
121,3
120,5
120,4
137,9
126,1
133,2
146,6
103,4
117,2
Dataseries Y:
105,1
113,3
99,1
100,3
93,5
98,8
106,2
98,3
102,1
117,1
101,5
80,5
105,9
109,5
97,2
114,5
93,5
100,9
121,1
116,5
109,3
118,1
108,3
105,4
116,2
111,2
105,8
122,7
99,5
107,9
124,6
115
110,3
132,7
99,7
96,5
118,7
112,9
130,5
137,9
115
116,8
140,9
120,7
134,2
147,3
112,4
107,1
128,4
137,7
135
151
137,4
132,4
161,3
139,8
146
154,6
142,1
120,5




Summary of compuational 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 compuational 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=6644&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]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=6644&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6644&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 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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.0242069834133049
-130.075925170901397
-120.274040443458284
-11-0.0839709152038067
-10-0.103112831465645
-90.226956265376582
-80.0846310238704992
-70.216820080016448
-60.481004291542944
-50.185418209509718
-40.174632226344121
-30.386750588699828
-20.301961733751354
-10.520155767102704
00.775758457594566
10.26529879172083
20.215405695197027
30.490531582300052
40.241854109242590
50.363571317670225
60.550231091128387
70.163150852083361
80.161930319423272
90.244139805661086
100.0655472125786575
110.280474359510570
120.43742706764676
130.0358402715607329
140.0537774425731114

\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) & 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
-14 & -0.0242069834133049 \tabularnewline
-13 & 0.075925170901397 \tabularnewline
-12 & 0.274040443458284 \tabularnewline
-11 & -0.0839709152038067 \tabularnewline
-10 & -0.103112831465645 \tabularnewline
-9 & 0.226956265376582 \tabularnewline
-8 & 0.0846310238704992 \tabularnewline
-7 & 0.216820080016448 \tabularnewline
-6 & 0.481004291542944 \tabularnewline
-5 & 0.185418209509718 \tabularnewline
-4 & 0.174632226344121 \tabularnewline
-3 & 0.386750588699828 \tabularnewline
-2 & 0.301961733751354 \tabularnewline
-1 & 0.520155767102704 \tabularnewline
0 & 0.775758457594566 \tabularnewline
1 & 0.26529879172083 \tabularnewline
2 & 0.215405695197027 \tabularnewline
3 & 0.490531582300052 \tabularnewline
4 & 0.241854109242590 \tabularnewline
5 & 0.363571317670225 \tabularnewline
6 & 0.550231091128387 \tabularnewline
7 & 0.163150852083361 \tabularnewline
8 & 0.161930319423272 \tabularnewline
9 & 0.244139805661086 \tabularnewline
10 & 0.0655472125786575 \tabularnewline
11 & 0.280474359510570 \tabularnewline
12 & 0.43742706764676 \tabularnewline
13 & 0.0358402715607329 \tabularnewline
14 & 0.0537774425731114 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6644&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]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]-14[/C][C]-0.0242069834133049[/C][/ROW]
[ROW][C]-13[/C][C]0.075925170901397[/C][/ROW]
[ROW][C]-12[/C][C]0.274040443458284[/C][/ROW]
[ROW][C]-11[/C][C]-0.0839709152038067[/C][/ROW]
[ROW][C]-10[/C][C]-0.103112831465645[/C][/ROW]
[ROW][C]-9[/C][C]0.226956265376582[/C][/ROW]
[ROW][C]-8[/C][C]0.0846310238704992[/C][/ROW]
[ROW][C]-7[/C][C]0.216820080016448[/C][/ROW]
[ROW][C]-6[/C][C]0.481004291542944[/C][/ROW]
[ROW][C]-5[/C][C]0.185418209509718[/C][/ROW]
[ROW][C]-4[/C][C]0.174632226344121[/C][/ROW]
[ROW][C]-3[/C][C]0.386750588699828[/C][/ROW]
[ROW][C]-2[/C][C]0.301961733751354[/C][/ROW]
[ROW][C]-1[/C][C]0.520155767102704[/C][/ROW]
[ROW][C]0[/C][C]0.775758457594566[/C][/ROW]
[ROW][C]1[/C][C]0.26529879172083[/C][/ROW]
[ROW][C]2[/C][C]0.215405695197027[/C][/ROW]
[ROW][C]3[/C][C]0.490531582300052[/C][/ROW]
[ROW][C]4[/C][C]0.241854109242590[/C][/ROW]
[ROW][C]5[/C][C]0.363571317670225[/C][/ROW]
[ROW][C]6[/C][C]0.550231091128387[/C][/ROW]
[ROW][C]7[/C][C]0.163150852083361[/C][/ROW]
[ROW][C]8[/C][C]0.161930319423272[/C][/ROW]
[ROW][C]9[/C][C]0.244139805661086[/C][/ROW]
[ROW][C]10[/C][C]0.0655472125786575[/C][/ROW]
[ROW][C]11[/C][C]0.280474359510570[/C][/ROW]
[ROW][C]12[/C][C]0.43742706764676[/C][/ROW]
[ROW][C]13[/C][C]0.0358402715607329[/C][/ROW]
[ROW][C]14[/C][C]0.0537774425731114[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6644&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6644&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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.0242069834133049
-130.075925170901397
-120.274040443458284
-11-0.0839709152038067
-10-0.103112831465645
-90.226956265376582
-80.0846310238704992
-70.216820080016448
-60.481004291542944
-50.185418209509718
-40.174632226344121
-30.386750588699828
-20.301961733751354
-10.520155767102704
00.775758457594566
10.26529879172083
20.215405695197027
30.490531582300052
40.241854109242590
50.363571317670225
60.550231091128387
70.163150852083361
80.161930319423272
90.244139805661086
100.0655472125786575
110.280474359510570
120.43742706764676
130.0358402715607329
140.0537774425731114



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