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Description of Statistical Computation

Author's title

Cross Correlation Function: Duurzame en niet-duurzame consumptiegoederen: p...

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationTue, 16 Dec 2008 04:54:18 -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/16/t12294284997w37pivdoquzmje.htm/, Retrieved Wed, 15 May 2024 06:11:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33925, Retrieved Wed, 15 May 2024 06:11:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

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...] [2008-12-13 11:42:49] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
-         [Cross Correlation Function] [Cross Correlation...] [2008-12-16 11:54:18] [b5110a3ab194da7214bdf478e0a05dbd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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:
Download CSV
Histogram 
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

Tables (Output of Computation)





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=33925&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=33925&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33925&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 time1 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)1
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])
-16-0.306541503964386
-15-0.243242340196610
-14-0.393451474290727
-13-0.158482065707786
-120.115894120233263
-11-0.195107616741167
-10-0.331674811511929
-9-0.195532314203291
-8-0.34231372420834
-7-0.236528278575672
-6-0.0574064151467752
-5-0.341539137114509
-4-0.454411162736847
-3-0.454016536548061
-2-0.572315467811114
-1-0.356477027434842
0-0.0470199819066042
1-0.388851005153903
2-0.544148172824011
3-0.348047449944521
4-0.478486512579204
5-0.34391441076759
6-0.0631816688683962
7-0.309067409152922
8-0.457868340700153
9-0.388069987504484
10-0.426698771041001
11-0.176730304630667
120.105356193608298
13-0.119225900415645
14-0.275583719070124
15-0.126215433227636
16-0.184660234484858

\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) & 1 \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 & -0.306541503964386 \tabularnewline
-15 & -0.243242340196610 \tabularnewline
-14 & -0.393451474290727 \tabularnewline
-13 & -0.158482065707786 \tabularnewline
-12 & 0.115894120233263 \tabularnewline
-11 & -0.195107616741167 \tabularnewline
-10 & -0.331674811511929 \tabularnewline
-9 & -0.195532314203291 \tabularnewline
-8 & -0.34231372420834 \tabularnewline
-7 & -0.236528278575672 \tabularnewline
-6 & -0.0574064151467752 \tabularnewline
-5 & -0.341539137114509 \tabularnewline
-4 & -0.454411162736847 \tabularnewline
-3 & -0.454016536548061 \tabularnewline
-2 & -0.572315467811114 \tabularnewline
-1 & -0.356477027434842 \tabularnewline
0 & -0.0470199819066042 \tabularnewline
1 & -0.388851005153903 \tabularnewline
2 & -0.544148172824011 \tabularnewline
3 & -0.348047449944521 \tabularnewline
4 & -0.478486512579204 \tabularnewline
5 & -0.34391441076759 \tabularnewline
6 & -0.0631816688683962 \tabularnewline
7 & -0.309067409152922 \tabularnewline
8 & -0.457868340700153 \tabularnewline
9 & -0.388069987504484 \tabularnewline
10 & -0.426698771041001 \tabularnewline
11 & -0.176730304630667 \tabularnewline
12 & 0.105356193608298 \tabularnewline
13 & -0.119225900415645 \tabularnewline
14 & -0.275583719070124 \tabularnewline
15 & -0.126215433227636 \tabularnewline
16 & -0.184660234484858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33925&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]1[/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]-0.306541503964386[/C][/ROW]
[ROW][C]-15[/C][C]-0.243242340196610[/C][/ROW]
[ROW][C]-14[/C][C]-0.393451474290727[/C][/ROW]
[ROW][C]-13[/C][C]-0.158482065707786[/C][/ROW]
[ROW][C]-12[/C][C]0.115894120233263[/C][/ROW]
[ROW][C]-11[/C][C]-0.195107616741167[/C][/ROW]
[ROW][C]-10[/C][C]-0.331674811511929[/C][/ROW]
[ROW][C]-9[/C][C]-0.195532314203291[/C][/ROW]
[ROW][C]-8[/C][C]-0.34231372420834[/C][/ROW]
[ROW][C]-7[/C][C]-0.236528278575672[/C][/ROW]
[ROW][C]-6[/C][C]-0.0574064151467752[/C][/ROW]
[ROW][C]-5[/C][C]-0.341539137114509[/C][/ROW]
[ROW][C]-4[/C][C]-0.454411162736847[/C][/ROW]
[ROW][C]-3[/C][C]-0.454016536548061[/C][/ROW]
[ROW][C]-2[/C][C]-0.572315467811114[/C][/ROW]
[ROW][C]-1[/C][C]-0.356477027434842[/C][/ROW]
[ROW][C]0[/C][C]-0.0470199819066042[/C][/ROW]
[ROW][C]1[/C][C]-0.388851005153903[/C][/ROW]
[ROW][C]2[/C][C]-0.544148172824011[/C][/ROW]
[ROW][C]3[/C][C]-0.348047449944521[/C][/ROW]
[ROW][C]4[/C][C]-0.478486512579204[/C][/ROW]
[ROW][C]5[/C][C]-0.34391441076759[/C][/ROW]
[ROW][C]6[/C][C]-0.0631816688683962[/C][/ROW]
[ROW][C]7[/C][C]-0.309067409152922[/C][/ROW]
[ROW][C]8[/C][C]-0.457868340700153[/C][/ROW]
[ROW][C]9[/C][C]-0.388069987504484[/C][/ROW]
[ROW][C]10[/C][C]-0.426698771041001[/C][/ROW]
[ROW][C]11[/C][C]-0.176730304630667[/C][/ROW]
[ROW][C]12[/C][C]0.105356193608298[/C][/ROW]
[ROW][C]13[/C][C]-0.119225900415645[/C][/ROW]
[ROW][C]14[/C][C]-0.275583719070124[/C][/ROW]
[ROW][C]15[/C][C]-0.126215433227636[/C][/ROW]
[ROW][C]16[/C][C]-0.184660234484858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33925&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33925&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)1
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])
-16-0.306541503964386
-15-0.243242340196610
-14-0.393451474290727
-13-0.158482065707786
-120.115894120233263
-11-0.195107616741167
-10-0.331674811511929
-9-0.195532314203291
-8-0.34231372420834
-7-0.236528278575672
-6-0.0574064151467752
-5-0.341539137114509
-4-0.454411162736847
-3-0.454016536548061
-2-0.572315467811114
-1-0.356477027434842
0-0.0470199819066042
1-0.388851005153903
2-0.544148172824011
3-0.348047449944521
4-0.478486512579204
5-0.34391441076759
6-0.0631816688683962
7-0.309067409152922
8-0.457868340700153
9-0.388069987504484
10-0.426698771041001
11-0.176730304630667
120.105356193608298
13-0.119225900415645
14-0.275583719070124
15-0.126215433227636
16-0.184660234484858


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')