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Description of Statistical Computation

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, 10 Dec 2008 11:56:01 -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/10/t1228935723i7w197oklr69rog.htm/, Retrieved Fri, 17 May 2024 02:40:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32077, Retrieved Fri, 17 May 2024 02:40:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Cross Correlation...] [2008-12-10 18:56:01] [1fa440a634ec541bd583650ead0404df] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,8
103,4
104,9
105,1
105,6
104,5
105,5
105,1
106,9
106,6
106,6
106,5
109,7
109,5
109,2
109,1
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109,2
113,3
112,3
112,3
116,3
118,3
119,4
119,4
119,4
120,1
121,7
123,7
123,7
128,5
127,1
122,6
119,8
122,7
123,4
123,8
121,8
121,2
121,2
121,2
121,2
129,6
131
131
129,8
129,8
134,9
131,2
127,1
130,5
130,5
131,7
131,7
131,7
131,7
128,7
125
124,5
123
122,8
123,1
124,8
126,9
131,7
136,8
143,7
150,1
152,7
152,6
150,5
154,9
158
158,1
160,6
160,6
Dataseries Y:
Download CSV
Histogram 
100
100
100
100,1
100
100
99,8
100
99,9
99,2
98,7
98,7
98,9
99,2
99,8
100,5
100,1
100,5
98,4
98,6
99
99,1
98,9
98,5
96,9
96,8
97
97
96,9
97,1
97,2
97,9
98,9
99,2
99,5
99,3
99,9
100
100,3
100,5
100,7
100,9
100,8
100,9
101
100,3
100,1
99,8
99,9
99,9
100,2
99,7
100,4
100,9
101,3
101,4
101,3
100,9
100,9
100,9
101,1
101,1
101,3
101,8
102,9
103,2
103,3
104,5
105
104,9
104,9
105,4
106
105,7
105,9
106,2
106,4
106,9
107,3
107,9
109,2
110,2
110,2
110,5
110,6
110,8
111,3
111,1
111,2
111,2
111,1
111,5
112,1
111,4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32077&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32077&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32077&T=0

As an alternative you can also use a QR Code:  
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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132






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)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 series0
krho(Y[t],X[t+k])
-160.000747319851865263
-150.0355163315821631
-14-0.0812043368725296
-13-0.0623417415616555
-12-0.0528048250672953
-11-0.0220723011829492
-10-0.0939966943367864
-9-0.122416358822108
-8-0.0555302401090026
-70.133039640516804
-6-0.113978337691874
-5-0.122995670061198
-4-0.0593950647110732
-3-0.0386161896850371
-20.0712826399318765
-1-0.074007428465396
00.0482889540384547
10.0957128046854497
20.0285385966232682
30.0140879763998341
40.239470120797476
50.238944898098737
60.150924674216229
70.0575731788964422
80.107839079526395
90.0761516527434485
100.0762090826608045
11-0.0311616819940509
120.00982709420406038
130.0223727118597457
14-0.0058479318574314
15-0.000433334830967797
160.119009616124486

\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) & 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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.000747319851865263 \tabularnewline
-15 & 0.0355163315821631 \tabularnewline
-14 & -0.0812043368725296 \tabularnewline
-13 & -0.0623417415616555 \tabularnewline
-12 & -0.0528048250672953 \tabularnewline
-11 & -0.0220723011829492 \tabularnewline
-10 & -0.0939966943367864 \tabularnewline
-9 & -0.122416358822108 \tabularnewline
-8 & -0.0555302401090026 \tabularnewline
-7 & 0.133039640516804 \tabularnewline
-6 & -0.113978337691874 \tabularnewline
-5 & -0.122995670061198 \tabularnewline
-4 & -0.0593950647110732 \tabularnewline
-3 & -0.0386161896850371 \tabularnewline
-2 & 0.0712826399318765 \tabularnewline
-1 & -0.074007428465396 \tabularnewline
0 & 0.0482889540384547 \tabularnewline
1 & 0.0957128046854497 \tabularnewline
2 & 0.0285385966232682 \tabularnewline
3 & 0.0140879763998341 \tabularnewline
4 & 0.239470120797476 \tabularnewline
5 & 0.238944898098737 \tabularnewline
6 & 0.150924674216229 \tabularnewline
7 & 0.0575731788964422 \tabularnewline
8 & 0.107839079526395 \tabularnewline
9 & 0.0761516527434485 \tabularnewline
10 & 0.0762090826608045 \tabularnewline
11 & -0.0311616819940509 \tabularnewline
12 & 0.00982709420406038 \tabularnewline
13 & 0.0223727118597457 \tabularnewline
14 & -0.0058479318574314 \tabularnewline
15 & -0.000433334830967797 \tabularnewline
16 & 0.119009616124486 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32077&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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]0.000747319851865263[/C][/ROW]
[ROW][C]-15[/C][C]0.0355163315821631[/C][/ROW]
[ROW][C]-14[/C][C]-0.0812043368725296[/C][/ROW]
[ROW][C]-13[/C][C]-0.0623417415616555[/C][/ROW]
[ROW][C]-12[/C][C]-0.0528048250672953[/C][/ROW]
[ROW][C]-11[/C][C]-0.0220723011829492[/C][/ROW]
[ROW][C]-10[/C][C]-0.0939966943367864[/C][/ROW]
[ROW][C]-9[/C][C]-0.122416358822108[/C][/ROW]
[ROW][C]-8[/C][C]-0.0555302401090026[/C][/ROW]
[ROW][C]-7[/C][C]0.133039640516804[/C][/ROW]
[ROW][C]-6[/C][C]-0.113978337691874[/C][/ROW]
[ROW][C]-5[/C][C]-0.122995670061198[/C][/ROW]
[ROW][C]-4[/C][C]-0.0593950647110732[/C][/ROW]
[ROW][C]-3[/C][C]-0.0386161896850371[/C][/ROW]
[ROW][C]-2[/C][C]0.0712826399318765[/C][/ROW]
[ROW][C]-1[/C][C]-0.074007428465396[/C][/ROW]
[ROW][C]0[/C][C]0.0482889540384547[/C][/ROW]
[ROW][C]1[/C][C]0.0957128046854497[/C][/ROW]
[ROW][C]2[/C][C]0.0285385966232682[/C][/ROW]
[ROW][C]3[/C][C]0.0140879763998341[/C][/ROW]
[ROW][C]4[/C][C]0.239470120797476[/C][/ROW]
[ROW][C]5[/C][C]0.238944898098737[/C][/ROW]
[ROW][C]6[/C][C]0.150924674216229[/C][/ROW]
[ROW][C]7[/C][C]0.0575731788964422[/C][/ROW]
[ROW][C]8[/C][C]0.107839079526395[/C][/ROW]
[ROW][C]9[/C][C]0.0761516527434485[/C][/ROW]
[ROW][C]10[/C][C]0.0762090826608045[/C][/ROW]
[ROW][C]11[/C][C]-0.0311616819940509[/C][/ROW]
[ROW][C]12[/C][C]0.00982709420406038[/C][/ROW]
[ROW][C]13[/C][C]0.0223727118597457[/C][/ROW]
[ROW][C]14[/C][C]-0.0058479318574314[/C][/ROW]
[ROW][C]15[/C][C]-0.000433334830967797[/C][/ROW]
[ROW][C]16[/C][C]0.119009616124486[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32077&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32077&T=1

As an alternative you can also use a QR Code:  
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)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 series0
krho(Y[t],X[t+k])
-160.000747319851865263
-150.0355163315821631
-14-0.0812043368725296
-13-0.0623417415616555
-12-0.0528048250672953
-11-0.0220723011829492
-10-0.0939966943367864
-9-0.122416358822108
-8-0.0555302401090026
-70.133039640516804
-6-0.113978337691874
-5-0.122995670061198
-4-0.0593950647110732
-3-0.0386161896850371
-20.0712826399318765
-1-0.074007428465396
00.0482889540384547
10.0957128046854497
20.0285385966232682
30.0140879763998341
40.239470120797476
50.238944898098737
60.150924674216229
70.0575731788964422
80.107839079526395
90.0761516527434485
100.0762090826608045
11-0.0311616819940509
120.00982709420406038
130.0223727118597457
14-0.0058479318574314
15-0.000433334830967797
160.119009616124486


Figures (Output of Computation)

Input Parameters & R Code

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