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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 computationSat, 13 Dec 2008 02:22:40 -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/13/t1229160230imiert8w7gs0o5o.htm/, Retrieved Sun, 19 May 2024 05:10:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32898, Retrieved Sun, 19 May 2024 05:10:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210

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] [CFF zonder transf...] [2008-12-13 09:22:40] [e7b1048c2c3a353441b9143db4404b91] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7
117,5
120,6
127,5
112,3
124,5
115,2
Dataseries Y:
Download CSV
Histogram 
6,4
6,8
7,5
7,5
7,6
7,6
7,4
7,3
7,1
6,9
6,8
7,5
7,6
7,8
8
8,1
8,2
8,3
8,2
8
7,9
7,6
7,6
8,2
8,3
8,4
8,4
8,4
8,6
8,9
8,8
8,3
7,5
7,2
7,5
8,8
9,3
9,3
8,7
8,2
8,3
8,5
8,6
8,6
8,2
8,1
8
8,6
8,7
8,8
8,5
8,4
8,5
8,7
8,7
8,6
8,5
8,3
8,1
8,2
8,1
8,1
7,9
7,9
7,9
8
8
7,9
8
7,7
7,2
7,5
7,3
7
7
7
7,2
7,3
7,1
6,8
6,6
6,2
6,2
6,8

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'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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32898&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32898&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32898&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'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])
-16-0.193321299595615
-15-0.222751537582552
-14-0.236305455031454
-13-0.232056110663299
-12-0.210178046260606
-11-0.109918027558537
-10-0.0512643269275399
-9-0.153408036814989
-8-0.275355574695872
-7-0.283170558335511
-6-0.214365507633140
-5-0.101841231245118
-40.0126296620410478
-30.00346594644557142
-2-0.00445630105314359
-10.0259597126530449
00.0439629494837897
10.0938862968307674
20.165546760424112
30.143675042995329
40.0663453716346735
50.0564979962780531
60.089757363624787
70.153126140502337
80.279885319304258
90.256937789797759
100.227985388275177
110.265622898224907
120.238747226565619
130.271816184695058
140.321139108310166
150.252291532882600
160.132331776559218

\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
-16 & -0.193321299595615 \tabularnewline
-15 & -0.222751537582552 \tabularnewline
-14 & -0.236305455031454 \tabularnewline
-13 & -0.232056110663299 \tabularnewline
-12 & -0.210178046260606 \tabularnewline
-11 & -0.109918027558537 \tabularnewline
-10 & -0.0512643269275399 \tabularnewline
-9 & -0.153408036814989 \tabularnewline
-8 & -0.275355574695872 \tabularnewline
-7 & -0.283170558335511 \tabularnewline
-6 & -0.214365507633140 \tabularnewline
-5 & -0.101841231245118 \tabularnewline
-4 & 0.0126296620410478 \tabularnewline
-3 & 0.00346594644557142 \tabularnewline
-2 & -0.00445630105314359 \tabularnewline
-1 & 0.0259597126530449 \tabularnewline
0 & 0.0439629494837897 \tabularnewline
1 & 0.0938862968307674 \tabularnewline
2 & 0.165546760424112 \tabularnewline
3 & 0.143675042995329 \tabularnewline
4 & 0.0663453716346735 \tabularnewline
5 & 0.0564979962780531 \tabularnewline
6 & 0.089757363624787 \tabularnewline
7 & 0.153126140502337 \tabularnewline
8 & 0.279885319304258 \tabularnewline
9 & 0.256937789797759 \tabularnewline
10 & 0.227985388275177 \tabularnewline
11 & 0.265622898224907 \tabularnewline
12 & 0.238747226565619 \tabularnewline
13 & 0.271816184695058 \tabularnewline
14 & 0.321139108310166 \tabularnewline
15 & 0.252291532882600 \tabularnewline
16 & 0.132331776559218 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32898&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]-16[/C][C]-0.193321299595615[/C][/ROW]
[ROW][C]-15[/C][C]-0.222751537582552[/C][/ROW]
[ROW][C]-14[/C][C]-0.236305455031454[/C][/ROW]
[ROW][C]-13[/C][C]-0.232056110663299[/C][/ROW]
[ROW][C]-12[/C][C]-0.210178046260606[/C][/ROW]
[ROW][C]-11[/C][C]-0.109918027558537[/C][/ROW]
[ROW][C]-10[/C][C]-0.0512643269275399[/C][/ROW]
[ROW][C]-9[/C][C]-0.153408036814989[/C][/ROW]
[ROW][C]-8[/C][C]-0.275355574695872[/C][/ROW]
[ROW][C]-7[/C][C]-0.283170558335511[/C][/ROW]
[ROW][C]-6[/C][C]-0.214365507633140[/C][/ROW]
[ROW][C]-5[/C][C]-0.101841231245118[/C][/ROW]
[ROW][C]-4[/C][C]0.0126296620410478[/C][/ROW]
[ROW][C]-3[/C][C]0.00346594644557142[/C][/ROW]
[ROW][C]-2[/C][C]-0.00445630105314359[/C][/ROW]
[ROW][C]-1[/C][C]0.0259597126530449[/C][/ROW]
[ROW][C]0[/C][C]0.0439629494837897[/C][/ROW]
[ROW][C]1[/C][C]0.0938862968307674[/C][/ROW]
[ROW][C]2[/C][C]0.165546760424112[/C][/ROW]
[ROW][C]3[/C][C]0.143675042995329[/C][/ROW]
[ROW][C]4[/C][C]0.0663453716346735[/C][/ROW]
[ROW][C]5[/C][C]0.0564979962780531[/C][/ROW]
[ROW][C]6[/C][C]0.089757363624787[/C][/ROW]
[ROW][C]7[/C][C]0.153126140502337[/C][/ROW]
[ROW][C]8[/C][C]0.279885319304258[/C][/ROW]
[ROW][C]9[/C][C]0.256937789797759[/C][/ROW]
[ROW][C]10[/C][C]0.227985388275177[/C][/ROW]
[ROW][C]11[/C][C]0.265622898224907[/C][/ROW]
[ROW][C]12[/C][C]0.238747226565619[/C][/ROW]
[ROW][C]13[/C][C]0.271816184695058[/C][/ROW]
[ROW][C]14[/C][C]0.321139108310166[/C][/ROW]
[ROW][C]15[/C][C]0.252291532882600[/C][/ROW]
[ROW][C]16[/C][C]0.132331776559218[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32898&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32898&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 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])
-16-0.193321299595615
-15-0.222751537582552
-14-0.236305455031454
-13-0.232056110663299
-12-0.210178046260606
-11-0.109918027558537
-10-0.0512643269275399
-9-0.153408036814989
-8-0.275355574695872
-7-0.283170558335511
-6-0.214365507633140
-5-0.101841231245118
-40.0126296620410478
-30.00346594644557142
-2-0.00445630105314359
-10.0259597126530449
00.0439629494837897
10.0938862968307674
20.165546760424112
30.143675042995329
40.0663453716346735
50.0564979962780531
60.089757363624787
70.153126140502337
80.279885319304258
90.256937789797759
100.227985388275177
110.265622898224907
120.238747226565619
130.271816184695058
140.321139108310166
150.252291532882600
160.132331776559218


Figures (Output of Computation)

Input Parameters & R Code

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')