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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 28 Nov 2007 12:10:46 -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/2007/Nov/28/t1196276450lojvzroj1mt8zir.htm/, Retrieved Thu, 02 May 2024 00:45:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7230, Retrieved Thu, 02 May 2024 00:45:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsExogene variabele: Gemiddelde consumptieprijs van aardappelen; Endogene variabele: Prijsindexcijfers grondstoffen, algemeen indexcijfer (inclusief energie)
Estimated Impact180

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...] [2007-11-28 19:10:46] [bebbf4ab6ac77d61a56e6916ab0650f9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,58
0,57
0,57
0,56
0,56
0,88
0,84
0,69
0,59
0,54
0,52
0,52
0,51
0,52
0,51
0,51
0,53
0,95
0,98
0,88
0,81
0,77
0,76
0,75
0,73
0,74
0,73
0,75
0,77
1,09
1,03
0,9
0,76
0,66
0,63
0,61
0,61
0,61
0,61
0,61
0,62
0,76
0,83
0,81
0,77
0,75
0,76
0,76
1,77
1,75
1,78
1,8
1,78
1,79
1,8
1,8
1,81
1,8
1,81
1,81
1,81
1,8
1,79
1,79
1,79
1,79
1,8
Dataseries Y:
Download CSV
Histogram 
75,9
77,7
86,9
90,7
91,0
89,5
92,5
94,1
98,5
96,8
91,2
97,1
104,9
110,9
104,8
94,1
95,8
99,3
101,1
104,0
99,0
105,4
107,1
110,7
117,1
118,7
126,5
127,5
134,6
131,8
135,9
142,7
141,7
153,4
145,0
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179,0
190,6
190,0
181,6
174,8
180,5
196,8
193,8
197,0
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244,0

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7230&T=0

[TABLE]
[ROW][C]Summary of compuational 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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7230&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7230&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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])
-150.0961236153760467
-140.150744905259922
-130.196209205676935
-120.232983692893667
-110.279761012929613
-100.323885135559499
-90.367426414573803
-80.412390245454781
-70.469967781558931
-60.524698558711798
-50.573955260279065
-40.630573651564019
-30.683979507721165
-20.728094112847921
-10.770414110898224
00.812981033280674
10.781754818592656
20.753074535991871
30.735621578656928
40.720861202120014
50.710086095605853
60.7077751619035
70.706171644957883
80.68638713324562
90.67157572382094
100.656389425525342
110.62528801786797
120.580380365443558
130.527619441566078
140.485382807127783
150.4476236001756

\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
-15 & 0.0961236153760467 \tabularnewline
-14 & 0.150744905259922 \tabularnewline
-13 & 0.196209205676935 \tabularnewline
-12 & 0.232983692893667 \tabularnewline
-11 & 0.279761012929613 \tabularnewline
-10 & 0.323885135559499 \tabularnewline
-9 & 0.367426414573803 \tabularnewline
-8 & 0.412390245454781 \tabularnewline
-7 & 0.469967781558931 \tabularnewline
-6 & 0.524698558711798 \tabularnewline
-5 & 0.573955260279065 \tabularnewline
-4 & 0.630573651564019 \tabularnewline
-3 & 0.683979507721165 \tabularnewline
-2 & 0.728094112847921 \tabularnewline
-1 & 0.770414110898224 \tabularnewline
0 & 0.812981033280674 \tabularnewline
1 & 0.781754818592656 \tabularnewline
2 & 0.753074535991871 \tabularnewline
3 & 0.735621578656928 \tabularnewline
4 & 0.720861202120014 \tabularnewline
5 & 0.710086095605853 \tabularnewline
6 & 0.7077751619035 \tabularnewline
7 & 0.706171644957883 \tabularnewline
8 & 0.68638713324562 \tabularnewline
9 & 0.67157572382094 \tabularnewline
10 & 0.656389425525342 \tabularnewline
11 & 0.62528801786797 \tabularnewline
12 & 0.580380365443558 \tabularnewline
13 & 0.527619441566078 \tabularnewline
14 & 0.485382807127783 \tabularnewline
15 & 0.4476236001756 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7230&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]-15[/C][C]0.0961236153760467[/C][/ROW]
[ROW][C]-14[/C][C]0.150744905259922[/C][/ROW]
[ROW][C]-13[/C][C]0.196209205676935[/C][/ROW]
[ROW][C]-12[/C][C]0.232983692893667[/C][/ROW]
[ROW][C]-11[/C][C]0.279761012929613[/C][/ROW]
[ROW][C]-10[/C][C]0.323885135559499[/C][/ROW]
[ROW][C]-9[/C][C]0.367426414573803[/C][/ROW]
[ROW][C]-8[/C][C]0.412390245454781[/C][/ROW]
[ROW][C]-7[/C][C]0.469967781558931[/C][/ROW]
[ROW][C]-6[/C][C]0.524698558711798[/C][/ROW]
[ROW][C]-5[/C][C]0.573955260279065[/C][/ROW]
[ROW][C]-4[/C][C]0.630573651564019[/C][/ROW]
[ROW][C]-3[/C][C]0.683979507721165[/C][/ROW]
[ROW][C]-2[/C][C]0.728094112847921[/C][/ROW]
[ROW][C]-1[/C][C]0.770414110898224[/C][/ROW]
[ROW][C]0[/C][C]0.812981033280674[/C][/ROW]
[ROW][C]1[/C][C]0.781754818592656[/C][/ROW]
[ROW][C]2[/C][C]0.753074535991871[/C][/ROW]
[ROW][C]3[/C][C]0.735621578656928[/C][/ROW]
[ROW][C]4[/C][C]0.720861202120014[/C][/ROW]
[ROW][C]5[/C][C]0.710086095605853[/C][/ROW]
[ROW][C]6[/C][C]0.7077751619035[/C][/ROW]
[ROW][C]7[/C][C]0.706171644957883[/C][/ROW]
[ROW][C]8[/C][C]0.68638713324562[/C][/ROW]
[ROW][C]9[/C][C]0.67157572382094[/C][/ROW]
[ROW][C]10[/C][C]0.656389425525342[/C][/ROW]
[ROW][C]11[/C][C]0.62528801786797[/C][/ROW]
[ROW][C]12[/C][C]0.580380365443558[/C][/ROW]
[ROW][C]13[/C][C]0.527619441566078[/C][/ROW]
[ROW][C]14[/C][C]0.485382807127783[/C][/ROW]
[ROW][C]15[/C][C]0.4476236001756[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7230&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7230&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])
-150.0961236153760467
-140.150744905259922
-130.196209205676935
-120.232983692893667
-110.279761012929613
-100.323885135559499
-90.367426414573803
-80.412390245454781
-70.469967781558931
-60.524698558711798
-50.573955260279065
-40.630573651564019
-30.683979507721165
-20.728094112847921
-10.770414110898224
00.812981033280674
10.781754818592656
20.753074535991871
30.735621578656928
40.720861202120014
50.710086095605853
60.7077751619035
70.706171644957883
80.68638713324562
90.67157572382094
100.656389425525342
110.62528801786797
120.580380365443558
130.527619441566078
140.485382807127783
150.4476236001756


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 ;
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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')