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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 computationWed, 17 Dec 2008 08:26:00 -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/17/t1229527644qb64158flrj75kk.htm/, Retrieved Sun, 19 May 2024 08:02:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34404, Retrieved Sun, 19 May 2024 08:02:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact176
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cross Correlation Function] [Cross Correlation...] [2008-12-13 11:42:49] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
-   P   [Cross Correlation Function] [Cross Correlation...] [2008-12-16 11:55:59] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
-   PD    [Cross Correlation Function] [Cross Correlation...] [2008-12-17 15:18:13] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
-   P         [Cross Correlation Function] [Cross Correlation...] [2008-12-17 15:26:00] [b5110a3ab194da7214bdf478e0a05dbd] [Current]
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Dataseries X:
85.0
95.9
108.9
96.2
100.1
105.7
64.5
66.8
110.3
96.1
102.5
97.6
83.6
86.5
96.0
91.1
87.2
84.5
59.2
61.5
98.8
97.9
92.7
84.2
74.5
79.7
86.8
79.8
87.0
91.4
58.7
62.8
87.9
90.4
80.6
73.5
71.4
70.6
78.3
76.0
77.4
80.9
63.4
58.1
88.2
81.2
84.9
76.4
71.5
76.1
82.9
78.0
82.0
84.7
55.7
59.5
83.2
87.6
76.2
76.4
68.3
70.0
76.3
70.9
72.4
80.1
57.4
62.7
82.6
88.9
80.4
72.0
69.4
69.2
77.3
79.4
78.6
76.1
61.8
59.4
78.1
Dataseries Y:
99.5
98.2
108.9
100.0
105.0
108.4
96.7
100.5
115.6
114.9
110.7
107.7
113.5
106.9
119.6
109.4
106.9
118.7
108.9
113.1
125.1
126.5
122.7
127.5
107.1
112.0
122.1
111.5
113.2
128.2
115.1
117.4
132.0
130.8
128.0
132.7
117.0
110.9
123.5
117.4
122.7
123.5
111.5
113.8
131.2
127.0
126.2
121.2
118.8
117.9
135.2
120.7
126.4
129.6
113.4
120.5
135.5
137.6
130.6
133.1
121.5
120.5
136.9
123.7
128.5
135.0
120.9
121.1
132.2
134.5
133.6
136.1
124.5
124.6
133.5
132.3
125.3
135.5
121.2
117.5
135.9




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=34404&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=34404&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34404&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 series-1.3
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.15943985299787
-14-0.0613592420411365
-130.121586995458542
-12-0.245508170348136
-110.144681070426148
-100.0307880744606327
-9-0.111525896260591
-80.102990635952473
-70.0498925394100905
-60.069084440288835
-5-0.203771998925056
-40.161146809340590
-3-0.165378889492002
-20.203134323782652
-1-0.267618196467546
00.286655908724501
1-0.173031821177468
20.0246374094978275
30.180907304829793
4-0.109404131571768
5-0.222047266963258
60.0785794329233095
70.0728420230368168
8-0.00146011078663027
9-0.0559259362358251
100.0490558654221613
110.109486165761547
12-0.201063523572015
130.232706093489748
14-0.163532909088741
15-0.0724630469701385

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -1.3 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.15943985299787 \tabularnewline
-14 & -0.0613592420411365 \tabularnewline
-13 & 0.121586995458542 \tabularnewline
-12 & -0.245508170348136 \tabularnewline
-11 & 0.144681070426148 \tabularnewline
-10 & 0.0307880744606327 \tabularnewline
-9 & -0.111525896260591 \tabularnewline
-8 & 0.102990635952473 \tabularnewline
-7 & 0.0498925394100905 \tabularnewline
-6 & 0.069084440288835 \tabularnewline
-5 & -0.203771998925056 \tabularnewline
-4 & 0.161146809340590 \tabularnewline
-3 & -0.165378889492002 \tabularnewline
-2 & 0.203134323782652 \tabularnewline
-1 & -0.267618196467546 \tabularnewline
0 & 0.286655908724501 \tabularnewline
1 & -0.173031821177468 \tabularnewline
2 & 0.0246374094978275 \tabularnewline
3 & 0.180907304829793 \tabularnewline
4 & -0.109404131571768 \tabularnewline
5 & -0.222047266963258 \tabularnewline
6 & 0.0785794329233095 \tabularnewline
7 & 0.0728420230368168 \tabularnewline
8 & -0.00146011078663027 \tabularnewline
9 & -0.0559259362358251 \tabularnewline
10 & 0.0490558654221613 \tabularnewline
11 & 0.109486165761547 \tabularnewline
12 & -0.201063523572015 \tabularnewline
13 & 0.232706093489748 \tabularnewline
14 & -0.163532909088741 \tabularnewline
15 & -0.0724630469701385 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34404&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]-1.3[/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]1[/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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]0.15943985299787[/C][/ROW]
[ROW][C]-14[/C][C]-0.0613592420411365[/C][/ROW]
[ROW][C]-13[/C][C]0.121586995458542[/C][/ROW]
[ROW][C]-12[/C][C]-0.245508170348136[/C][/ROW]
[ROW][C]-11[/C][C]0.144681070426148[/C][/ROW]
[ROW][C]-10[/C][C]0.0307880744606327[/C][/ROW]
[ROW][C]-9[/C][C]-0.111525896260591[/C][/ROW]
[ROW][C]-8[/C][C]0.102990635952473[/C][/ROW]
[ROW][C]-7[/C][C]0.0498925394100905[/C][/ROW]
[ROW][C]-6[/C][C]0.069084440288835[/C][/ROW]
[ROW][C]-5[/C][C]-0.203771998925056[/C][/ROW]
[ROW][C]-4[/C][C]0.161146809340590[/C][/ROW]
[ROW][C]-3[/C][C]-0.165378889492002[/C][/ROW]
[ROW][C]-2[/C][C]0.203134323782652[/C][/ROW]
[ROW][C]-1[/C][C]-0.267618196467546[/C][/ROW]
[ROW][C]0[/C][C]0.286655908724501[/C][/ROW]
[ROW][C]1[/C][C]-0.173031821177468[/C][/ROW]
[ROW][C]2[/C][C]0.0246374094978275[/C][/ROW]
[ROW][C]3[/C][C]0.180907304829793[/C][/ROW]
[ROW][C]4[/C][C]-0.109404131571768[/C][/ROW]
[ROW][C]5[/C][C]-0.222047266963258[/C][/ROW]
[ROW][C]6[/C][C]0.0785794329233095[/C][/ROW]
[ROW][C]7[/C][C]0.0728420230368168[/C][/ROW]
[ROW][C]8[/C][C]-0.00146011078663027[/C][/ROW]
[ROW][C]9[/C][C]-0.0559259362358251[/C][/ROW]
[ROW][C]10[/C][C]0.0490558654221613[/C][/ROW]
[ROW][C]11[/C][C]0.109486165761547[/C][/ROW]
[ROW][C]12[/C][C]-0.201063523572015[/C][/ROW]
[ROW][C]13[/C][C]0.232706093489748[/C][/ROW]
[ROW][C]14[/C][C]-0.163532909088741[/C][/ROW]
[ROW][C]15[/C][C]-0.0724630469701385[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34404&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34404&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 series-1.3
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.15943985299787
-14-0.0613592420411365
-130.121586995458542
-12-0.245508170348136
-110.144681070426148
-100.0307880744606327
-9-0.111525896260591
-80.102990635952473
-70.0498925394100905
-60.069084440288835
-5-0.203771998925056
-40.161146809340590
-3-0.165378889492002
-20.203134323782652
-1-0.267618196467546
00.286655908724501
1-0.173031821177468
20.0246374094978275
30.180907304829793
4-0.109404131571768
5-0.222047266963258
60.0785794329233095
70.0728420230368168
8-0.00146011078663027
9-0.0559259362358251
100.0490558654221613
110.109486165761547
12-0.201063523572015
130.232706093489748
14-0.163532909088741
15-0.0724630469701385



Parameters (Session):
par1 = -1.3 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 1 ;
Parameters (R input):
par1 = -1.3 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 1 ;
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')