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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 computationMon, 01 Dec 2008 04:34:58 -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/01/t1228131386bc1q90y61h45hka.htm/, Retrieved Sun, 05 May 2024 13:17:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26881, Retrieved Sun, 05 May 2024 13:17:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cross Correlation Function] [Q7 Cross correlat...] [2008-11-30 17:52:44] [2d4aec5ed1856c4828162be37be304d9]
-   PD    [Cross Correlation Function] [Q7 CCF] [2008-12-01 11:34:58] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
-   P       [Cross Correlation Function] [Q9 CCF] [2008-12-01 12:16:39] [2d4aec5ed1856c4828162be37be304d9]
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Dataseries X:
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
97.6
Dataseries Y:
148.8
146.7
118.8
99.4
97.6
110.2
146.6
136.4
126.2
154.9
109
128.5
144.9
136.3
134.8
103.4
106.6
119.2
149.3
150.2
142.9
163.6
98.2
138.2
143.7
132.8
149.4
128.8
98.9
106.2
140.7
133
156.4
157.7
107.9
133.6
148.1
205.6
193.1
117.5
116.4
129.5
157.1
157
158.4
161.7
116.9
161.1
155.7
160.8
145.4
111
144.8
149.2
156.6
182.5
171.3
172.7
133
148.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26881&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26881&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26881&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







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])
-14-0.00206772237903045
-130.0750364409039927
-120.49290708980921
-110.143436963756166
-10-0.156063910370619
-9-0.109592858540782
-80.0848315861859909
-70.27993753000781
-60.36058521908469
-50.354180484301104
-4-0.15531534475761
-3-0.122406616757393
-20.0277697862116949
-10.154298392920497
00.76407022610296
10.162178408961916
2-0.131427607364959
3-0.0470236807822819
4-0.0472832862347211
50.268948791557268
60.343133196218471
70.319691935844252
8-0.0651765854357191
9-0.160182635100297
10-0.0914495763985416
110.0869935580145928
120.532284855384542
130.0430084763153712
14-0.128176438282243

\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 & -0.00206772237903045 \tabularnewline
-13 & 0.0750364409039927 \tabularnewline
-12 & 0.49290708980921 \tabularnewline
-11 & 0.143436963756166 \tabularnewline
-10 & -0.156063910370619 \tabularnewline
-9 & -0.109592858540782 \tabularnewline
-8 & 0.0848315861859909 \tabularnewline
-7 & 0.27993753000781 \tabularnewline
-6 & 0.36058521908469 \tabularnewline
-5 & 0.354180484301104 \tabularnewline
-4 & -0.15531534475761 \tabularnewline
-3 & -0.122406616757393 \tabularnewline
-2 & 0.0277697862116949 \tabularnewline
-1 & 0.154298392920497 \tabularnewline
0 & 0.76407022610296 \tabularnewline
1 & 0.162178408961916 \tabularnewline
2 & -0.131427607364959 \tabularnewline
3 & -0.0470236807822819 \tabularnewline
4 & -0.0472832862347211 \tabularnewline
5 & 0.268948791557268 \tabularnewline
6 & 0.343133196218471 \tabularnewline
7 & 0.319691935844252 \tabularnewline
8 & -0.0651765854357191 \tabularnewline
9 & -0.160182635100297 \tabularnewline
10 & -0.0914495763985416 \tabularnewline
11 & 0.0869935580145928 \tabularnewline
12 & 0.532284855384542 \tabularnewline
13 & 0.0430084763153712 \tabularnewline
14 & -0.128176438282243 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26881&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]-0.00206772237903045[/C][/ROW]
[ROW][C]-13[/C][C]0.0750364409039927[/C][/ROW]
[ROW][C]-12[/C][C]0.49290708980921[/C][/ROW]
[ROW][C]-11[/C][C]0.143436963756166[/C][/ROW]
[ROW][C]-10[/C][C]-0.156063910370619[/C][/ROW]
[ROW][C]-9[/C][C]-0.109592858540782[/C][/ROW]
[ROW][C]-8[/C][C]0.0848315861859909[/C][/ROW]
[ROW][C]-7[/C][C]0.27993753000781[/C][/ROW]
[ROW][C]-6[/C][C]0.36058521908469[/C][/ROW]
[ROW][C]-5[/C][C]0.354180484301104[/C][/ROW]
[ROW][C]-4[/C][C]-0.15531534475761[/C][/ROW]
[ROW][C]-3[/C][C]-0.122406616757393[/C][/ROW]
[ROW][C]-2[/C][C]0.0277697862116949[/C][/ROW]
[ROW][C]-1[/C][C]0.154298392920497[/C][/ROW]
[ROW][C]0[/C][C]0.76407022610296[/C][/ROW]
[ROW][C]1[/C][C]0.162178408961916[/C][/ROW]
[ROW][C]2[/C][C]-0.131427607364959[/C][/ROW]
[ROW][C]3[/C][C]-0.0470236807822819[/C][/ROW]
[ROW][C]4[/C][C]-0.0472832862347211[/C][/ROW]
[ROW][C]5[/C][C]0.268948791557268[/C][/ROW]
[ROW][C]6[/C][C]0.343133196218471[/C][/ROW]
[ROW][C]7[/C][C]0.319691935844252[/C][/ROW]
[ROW][C]8[/C][C]-0.0651765854357191[/C][/ROW]
[ROW][C]9[/C][C]-0.160182635100297[/C][/ROW]
[ROW][C]10[/C][C]-0.0914495763985416[/C][/ROW]
[ROW][C]11[/C][C]0.0869935580145928[/C][/ROW]
[ROW][C]12[/C][C]0.532284855384542[/C][/ROW]
[ROW][C]13[/C][C]0.0430084763153712[/C][/ROW]
[ROW][C]14[/C][C]-0.128176438282243[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26881&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26881&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])
-14-0.00206772237903045
-130.0750364409039927
-120.49290708980921
-110.143436963756166
-10-0.156063910370619
-9-0.109592858540782
-80.0848315861859909
-70.27993753000781
-60.36058521908469
-50.354180484301104
-4-0.15531534475761
-3-0.122406616757393
-20.0277697862116949
-10.154298392920497
00.76407022610296
10.162178408961916
2-0.131427607364959
3-0.0470236807822819
4-0.0472832862347211
50.268948791557268
60.343133196218471
70.319691935844252
8-0.0651765854357191
9-0.160182635100297
10-0.0914495763985416
110.0869935580145928
120.532284855384542
130.0430084763153712
14-0.128176438282243



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) 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')