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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSat, 22 Dec 2007 06:33:32 -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/Dec/22/t1198329328inwv9mgvnzi5hdr.htm/, Retrieved Sun, 05 May 2024 07:36:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4824, Retrieved Sun, 05 May 2024 07:36:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsniet-gedifferentieerd
Estimated Impact297
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Cross Correlation...] [2007-12-22 13:33:32] [0eafefa7b02d47065fceb6c46f54fbf9] [Current]
- R PD    [Cross Correlation Function] [] [2008-12-23 18:13:17] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
97,5
97,1
97,5
98,5
100,5
102,8
105,2
107,4
108,0
107,6
107,0
105,8
104,3
103,8
104,4
106,2
108,5
109,8
110,3
109,7
108,7
108,9
109,7
110,4
111,4
112,6
113,6
113,8
113,2
113,6
113,9
113,4
113,8
116,0
118,3
120,5
121,9
121,2
120,2
120,6
110,2
109,2
108,7
109,9
112,2
114,5
114,7
113,2
112,1
112,6
113,6
114,0
114,5
115,0
114,9
114,8
114,3
113,7
114,5
116,0
116,6
116,2
115,7
115,6
115,2
115,0
115,7
115,9
115,6
115,9
117,0
117,9
118,8
119,9
Dataseries Y:
104,3
103,9
103,9
103,9
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,0
108,2
112,3
111,3
111,3
115,3
117,2
118,3
118,3
118,3
119,0
120,6
122,6
122,6
127,4
125,9
121,5
118,8
121,6
122,3
122,7
120,8
120,1
120,1
120,1
120,1
128,4
129,8
129,8
128,6
128,6
133,7
130,0
125,9
129,4
129,4
130,6
130,6
130,6
130,8
129,7
125,8
126,0
125,6
125,4
124,7
126,9
129,1




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=4824&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=4824&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4824&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 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])
-150.479296310598718
-140.486327952693519
-130.496500068688681
-120.507043189088047
-110.534562373686748
-100.557886857081597
-90.578606471525812
-80.600282336758324
-70.621502284606799
-60.632830523481254
-50.641097976021039
-40.648940863661648
-30.679968454868763
-20.703848985880835
-10.710740389158211
00.707758831400152
10.640294250834775
20.573109794835723
30.515684364659663
40.46406846519212
50.419805147106986
60.37752964011445
70.337944797723690
80.298258483439355
90.263943612439923
100.240518080833728
110.216914885146647
120.18606665274933
130.159684913705043
140.126064669718199
150.0969439309913067

\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
-15 & 0.479296310598718 \tabularnewline
-14 & 0.486327952693519 \tabularnewline
-13 & 0.496500068688681 \tabularnewline
-12 & 0.507043189088047 \tabularnewline
-11 & 0.534562373686748 \tabularnewline
-10 & 0.557886857081597 \tabularnewline
-9 & 0.578606471525812 \tabularnewline
-8 & 0.600282336758324 \tabularnewline
-7 & 0.621502284606799 \tabularnewline
-6 & 0.632830523481254 \tabularnewline
-5 & 0.641097976021039 \tabularnewline
-4 & 0.648940863661648 \tabularnewline
-3 & 0.679968454868763 \tabularnewline
-2 & 0.703848985880835 \tabularnewline
-1 & 0.710740389158211 \tabularnewline
0 & 0.707758831400152 \tabularnewline
1 & 0.640294250834775 \tabularnewline
2 & 0.573109794835723 \tabularnewline
3 & 0.515684364659663 \tabularnewline
4 & 0.46406846519212 \tabularnewline
5 & 0.419805147106986 \tabularnewline
6 & 0.37752964011445 \tabularnewline
7 & 0.337944797723690 \tabularnewline
8 & 0.298258483439355 \tabularnewline
9 & 0.263943612439923 \tabularnewline
10 & 0.240518080833728 \tabularnewline
11 & 0.216914885146647 \tabularnewline
12 & 0.18606665274933 \tabularnewline
13 & 0.159684913705043 \tabularnewline
14 & 0.126064669718199 \tabularnewline
15 & 0.0969439309913067 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4824&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]-15[/C][C]0.479296310598718[/C][/ROW]
[ROW][C]-14[/C][C]0.486327952693519[/C][/ROW]
[ROW][C]-13[/C][C]0.496500068688681[/C][/ROW]
[ROW][C]-12[/C][C]0.507043189088047[/C][/ROW]
[ROW][C]-11[/C][C]0.534562373686748[/C][/ROW]
[ROW][C]-10[/C][C]0.557886857081597[/C][/ROW]
[ROW][C]-9[/C][C]0.578606471525812[/C][/ROW]
[ROW][C]-8[/C][C]0.600282336758324[/C][/ROW]
[ROW][C]-7[/C][C]0.621502284606799[/C][/ROW]
[ROW][C]-6[/C][C]0.632830523481254[/C][/ROW]
[ROW][C]-5[/C][C]0.641097976021039[/C][/ROW]
[ROW][C]-4[/C][C]0.648940863661648[/C][/ROW]
[ROW][C]-3[/C][C]0.679968454868763[/C][/ROW]
[ROW][C]-2[/C][C]0.703848985880835[/C][/ROW]
[ROW][C]-1[/C][C]0.710740389158211[/C][/ROW]
[ROW][C]0[/C][C]0.707758831400152[/C][/ROW]
[ROW][C]1[/C][C]0.640294250834775[/C][/ROW]
[ROW][C]2[/C][C]0.573109794835723[/C][/ROW]
[ROW][C]3[/C][C]0.515684364659663[/C][/ROW]
[ROW][C]4[/C][C]0.46406846519212[/C][/ROW]
[ROW][C]5[/C][C]0.419805147106986[/C][/ROW]
[ROW][C]6[/C][C]0.37752964011445[/C][/ROW]
[ROW][C]7[/C][C]0.337944797723690[/C][/ROW]
[ROW][C]8[/C][C]0.298258483439355[/C][/ROW]
[ROW][C]9[/C][C]0.263943612439923[/C][/ROW]
[ROW][C]10[/C][C]0.240518080833728[/C][/ROW]
[ROW][C]11[/C][C]0.216914885146647[/C][/ROW]
[ROW][C]12[/C][C]0.18606665274933[/C][/ROW]
[ROW][C]13[/C][C]0.159684913705043[/C][/ROW]
[ROW][C]14[/C][C]0.126064669718199[/C][/ROW]
[ROW][C]15[/C][C]0.0969439309913067[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4824&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4824&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])
-150.479296310598718
-140.486327952693519
-130.496500068688681
-120.507043189088047
-110.534562373686748
-100.557886857081597
-90.578606471525812
-80.600282336758324
-70.621502284606799
-60.632830523481254
-50.641097976021039
-40.648940863661648
-30.679968454868763
-20.703848985880835
-10.710740389158211
00.707758831400152
10.640294250834775
20.573109794835723
30.515684364659663
40.46406846519212
50.419805147106986
60.37752964011445
70.337944797723690
80.298258483439355
90.263943612439923
100.240518080833728
110.216914885146647
120.18606665274933
130.159684913705043
140.126064669718199
150.0969439309913067



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',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')