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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 07:10:24 -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/t1196258417yd5lbf0bluy3id0.htm/, Retrieved Thu, 02 May 2024 08:25:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7055, Retrieved Thu, 02 May 2024 08:25:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgroep MENS
Estimated Impact183

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] [voeding en energi...] [2007-11-27 10:55:03] [75d515ccfbd49ab2c9a93737926697f5]
-   PD    [Cross Correlation Function] [energie en transp...] [2007-11-28 14:10:24] [82643448f9a1604e63bdcbbe838c35e0] [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
Dataseries Y:
Download CSV
Histogram 
99.9
99.9
99.9
99.9
99.9
99.7
99.6
99.5
100.6
100.2
100.1
100.2
99.1
99.5
99.5
99.6
99.5
99.6
99.8
99.9
100.5
100.5
100.5
100.5
99.5
99.9
100.4
99.6
99.5
99.6
98.4
99.9
100.3
100.3
101.3
101
99.7
99.4
99.9
100.7
99.8
98.8
99.6
99.1
100.3
100.5
100.8
100.6
99.1
98.8
99
99.9
99.5
99.2
99.6
100.1
99.8
101.6
101.7
101.9
100
102
102
102.9
102.7
102.7
102.7
102.7
102.6
102.6
102.5
102.5
102.1

Tables (Output of Computation)





Summary of compuational 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 compuational 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=7055&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]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=7055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7055&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 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 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])
-150.0896929238139872
-14-0.0234755209685644
-130.0540377512689325
-12-0.233030032556035
-110.0119997532061160
-100.0314634539266087
-90.160471284312171
-8-0.125432747139328
-7-0.114744689316745
-6-0.00522674243076587
-50.0911693026931169
-4-0.132393820364202
-30.176611174000283
-2-0.0418842824715362
-10.0497365185382428
0-0.344390546133954
10.0491249547909596
20.222296412574558
30.127945840372415
40.0445039622935353
5-0.169223259627089
6-0.0629052194409249
70.164259004710831
80.0178646544904880
9-0.0118991453620373
100.0750017458478831
11-0.0287286111093158
12-0.411922819282579
13-0.00203314433756767
140.313795948146043
150.069968508586075

\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
-15 & 0.0896929238139872 \tabularnewline
-14 & -0.0234755209685644 \tabularnewline
-13 & 0.0540377512689325 \tabularnewline
-12 & -0.233030032556035 \tabularnewline
-11 & 0.0119997532061160 \tabularnewline
-10 & 0.0314634539266087 \tabularnewline
-9 & 0.160471284312171 \tabularnewline
-8 & -0.125432747139328 \tabularnewline
-7 & -0.114744689316745 \tabularnewline
-6 & -0.00522674243076587 \tabularnewline
-5 & 0.0911693026931169 \tabularnewline
-4 & -0.132393820364202 \tabularnewline
-3 & 0.176611174000283 \tabularnewline
-2 & -0.0418842824715362 \tabularnewline
-1 & 0.0497365185382428 \tabularnewline
0 & -0.344390546133954 \tabularnewline
1 & 0.0491249547909596 \tabularnewline
2 & 0.222296412574558 \tabularnewline
3 & 0.127945840372415 \tabularnewline
4 & 0.0445039622935353 \tabularnewline
5 & -0.169223259627089 \tabularnewline
6 & -0.0629052194409249 \tabularnewline
7 & 0.164259004710831 \tabularnewline
8 & 0.0178646544904880 \tabularnewline
9 & -0.0118991453620373 \tabularnewline
10 & 0.0750017458478831 \tabularnewline
11 & -0.0287286111093158 \tabularnewline
12 & -0.411922819282579 \tabularnewline
13 & -0.00203314433756767 \tabularnewline
14 & 0.313795948146043 \tabularnewline
15 & 0.069968508586075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7055&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]-15[/C][C]0.0896929238139872[/C][/ROW]
[ROW][C]-14[/C][C]-0.0234755209685644[/C][/ROW]
[ROW][C]-13[/C][C]0.0540377512689325[/C][/ROW]
[ROW][C]-12[/C][C]-0.233030032556035[/C][/ROW]
[ROW][C]-11[/C][C]0.0119997532061160[/C][/ROW]
[ROW][C]-10[/C][C]0.0314634539266087[/C][/ROW]
[ROW][C]-9[/C][C]0.160471284312171[/C][/ROW]
[ROW][C]-8[/C][C]-0.125432747139328[/C][/ROW]
[ROW][C]-7[/C][C]-0.114744689316745[/C][/ROW]
[ROW][C]-6[/C][C]-0.00522674243076587[/C][/ROW]
[ROW][C]-5[/C][C]0.0911693026931169[/C][/ROW]
[ROW][C]-4[/C][C]-0.132393820364202[/C][/ROW]
[ROW][C]-3[/C][C]0.176611174000283[/C][/ROW]
[ROW][C]-2[/C][C]-0.0418842824715362[/C][/ROW]
[ROW][C]-1[/C][C]0.0497365185382428[/C][/ROW]
[ROW][C]0[/C][C]-0.344390546133954[/C][/ROW]
[ROW][C]1[/C][C]0.0491249547909596[/C][/ROW]
[ROW][C]2[/C][C]0.222296412574558[/C][/ROW]
[ROW][C]3[/C][C]0.127945840372415[/C][/ROW]
[ROW][C]4[/C][C]0.0445039622935353[/C][/ROW]
[ROW][C]5[/C][C]-0.169223259627089[/C][/ROW]
[ROW][C]6[/C][C]-0.0629052194409249[/C][/ROW]
[ROW][C]7[/C][C]0.164259004710831[/C][/ROW]
[ROW][C]8[/C][C]0.0178646544904880[/C][/ROW]
[ROW][C]9[/C][C]-0.0118991453620373[/C][/ROW]
[ROW][C]10[/C][C]0.0750017458478831[/C][/ROW]
[ROW][C]11[/C][C]-0.0287286111093158[/C][/ROW]
[ROW][C]12[/C][C]-0.411922819282579[/C][/ROW]
[ROW][C]13[/C][C]-0.00203314433756767[/C][/ROW]
[ROW][C]14[/C][C]0.313795948146043[/C][/ROW]
[ROW][C]15[/C][C]0.069968508586075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7055&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])
-150.0896929238139872
-14-0.0234755209685644
-130.0540377512689325
-12-0.233030032556035
-110.0119997532061160
-100.0314634539266087
-90.160471284312171
-8-0.125432747139328
-7-0.114744689316745
-6-0.00522674243076587
-50.0911693026931169
-4-0.132393820364202
-30.176611174000283
-2-0.0418842824715362
-10.0497365185382428
0-0.344390546133954
10.0491249547909596
20.222296412574558
30.127945840372415
40.0445039622935353
5-0.169223259627089
6-0.0629052194409249
70.164259004710831
80.0178646544904880
9-0.0118991453620373
100.0750017458478831
11-0.0287286111093158
12-0.411922819282579
13-0.00203314433756767
140.313795948146043
150.069968508586075


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) 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')