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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 computationTue, 27 Nov 2007 03:55:03 -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/27/t11961603396gkhc0zq8rv9cnw.htm/, Retrieved Sun, 05 May 2024 17:04:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6845, Retrieved Sun, 05 May 2024 17:04:36 +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] [68ccea1ea79fa519d33f2664ba3973dd] [Current]
-   PD    [Cross Correlation Function] [voeding en transp...] [2007-11-28 14:04:13] [066f1eb6d7ef1bdf47c03bb1fc313ae5]
-   PD    [Cross Correlation Function] [voeding en textie...] [2007-11-28 14:08:21] [066f1eb6d7ef1bdf47c03bb1fc313ae5]
-   PD    [Cross Correlation Function] [energie en transp...] [2007-11-28 14:10:24] [066f1eb6d7ef1bdf47c03bb1fc313ae5]
-   PD    [Cross Correlation Function] [energie en textie...] [2007-11-28 14:12:18] [066f1eb6d7ef1bdf47c03bb1fc313ae5]
-   PD    [Cross Correlation Function] [transport en text...] [2007-11-28 14:14:20] [066f1eb6d7ef1bdf47c03bb1fc313ae5]
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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
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
109,0
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
131,0
131,0
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 
100,0
100,0
100,0
100,1
100,0
100,0
99,8
100,0
99,9
99,2
98,7
98,7
98,9
99,2
99,8
100,5
100,1
100,5
98,4
98,6
99,0
99,1
98,9
98,5
96,9
96,8
97,0
97,0
96,9
97,1
97,2
97,9
98,9
99,2
99,5
99,3
99,9
100,0
100,3
100,5
100,7
100,9
100,8
100,9
101,0
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
105,0
104,9
104,9
105,4
106,0

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6845&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6845&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'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])
-15-0.0130596930913995
-14-0.0153549340671163
-130.0097232030952581
-12-0.0717410023022272
-110.0471455363104826
-10-0.114539434578766
-9-0.121123573121442
-80.0145325549780840
-70.208505435995252
-6-0.0857391470279228
-5-0.0460460808230784
-40.0821984238143081
-30.0502321810039133
-20.0998326005884353
-1-0.105966745275280
00.0270323086649096
10.0237662791287992
2-0.0646384517758616
3-0.143866984219393
40.093843801874696
50.139007595198287
60.082792061699765
70.116077651095044
80.159015302348164
90.0254546070599204
100.120933295840497
11-0.0194957625514101
12-0.0285824387855386
13-0.0270857496901464
14-0.08839894429683
15-0.116528325728273

\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 & -0.0130596930913995 \tabularnewline
-14 & -0.0153549340671163 \tabularnewline
-13 & 0.0097232030952581 \tabularnewline
-12 & -0.0717410023022272 \tabularnewline
-11 & 0.0471455363104826 \tabularnewline
-10 & -0.114539434578766 \tabularnewline
-9 & -0.121123573121442 \tabularnewline
-8 & 0.0145325549780840 \tabularnewline
-7 & 0.208505435995252 \tabularnewline
-6 & -0.0857391470279228 \tabularnewline
-5 & -0.0460460808230784 \tabularnewline
-4 & 0.0821984238143081 \tabularnewline
-3 & 0.0502321810039133 \tabularnewline
-2 & 0.0998326005884353 \tabularnewline
-1 & -0.105966745275280 \tabularnewline
0 & 0.0270323086649096 \tabularnewline
1 & 0.0237662791287992 \tabularnewline
2 & -0.0646384517758616 \tabularnewline
3 & -0.143866984219393 \tabularnewline
4 & 0.093843801874696 \tabularnewline
5 & 0.139007595198287 \tabularnewline
6 & 0.082792061699765 \tabularnewline
7 & 0.116077651095044 \tabularnewline
8 & 0.159015302348164 \tabularnewline
9 & 0.0254546070599204 \tabularnewline
10 & 0.120933295840497 \tabularnewline
11 & -0.0194957625514101 \tabularnewline
12 & -0.0285824387855386 \tabularnewline
13 & -0.0270857496901464 \tabularnewline
14 & -0.08839894429683 \tabularnewline
15 & -0.116528325728273 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6845&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]-0.0130596930913995[/C][/ROW]
[ROW][C]-14[/C][C]-0.0153549340671163[/C][/ROW]
[ROW][C]-13[/C][C]0.0097232030952581[/C][/ROW]
[ROW][C]-12[/C][C]-0.0717410023022272[/C][/ROW]
[ROW][C]-11[/C][C]0.0471455363104826[/C][/ROW]
[ROW][C]-10[/C][C]-0.114539434578766[/C][/ROW]
[ROW][C]-9[/C][C]-0.121123573121442[/C][/ROW]
[ROW][C]-8[/C][C]0.0145325549780840[/C][/ROW]
[ROW][C]-7[/C][C]0.208505435995252[/C][/ROW]
[ROW][C]-6[/C][C]-0.0857391470279228[/C][/ROW]
[ROW][C]-5[/C][C]-0.0460460808230784[/C][/ROW]
[ROW][C]-4[/C][C]0.0821984238143081[/C][/ROW]
[ROW][C]-3[/C][C]0.0502321810039133[/C][/ROW]
[ROW][C]-2[/C][C]0.0998326005884353[/C][/ROW]
[ROW][C]-1[/C][C]-0.105966745275280[/C][/ROW]
[ROW][C]0[/C][C]0.0270323086649096[/C][/ROW]
[ROW][C]1[/C][C]0.0237662791287992[/C][/ROW]
[ROW][C]2[/C][C]-0.0646384517758616[/C][/ROW]
[ROW][C]3[/C][C]-0.143866984219393[/C][/ROW]
[ROW][C]4[/C][C]0.093843801874696[/C][/ROW]
[ROW][C]5[/C][C]0.139007595198287[/C][/ROW]
[ROW][C]6[/C][C]0.082792061699765[/C][/ROW]
[ROW][C]7[/C][C]0.116077651095044[/C][/ROW]
[ROW][C]8[/C][C]0.159015302348164[/C][/ROW]
[ROW][C]9[/C][C]0.0254546070599204[/C][/ROW]
[ROW][C]10[/C][C]0.120933295840497[/C][/ROW]
[ROW][C]11[/C][C]-0.0194957625514101[/C][/ROW]
[ROW][C]12[/C][C]-0.0285824387855386[/C][/ROW]
[ROW][C]13[/C][C]-0.0270857496901464[/C][/ROW]
[ROW][C]14[/C][C]-0.08839894429683[/C][/ROW]
[ROW][C]15[/C][C]-0.116528325728273[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6845&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])
-15-0.0130596930913995
-14-0.0153549340671163
-130.0097232030952581
-12-0.0717410023022272
-110.0471455363104826
-10-0.114539434578766
-9-0.121123573121442
-80.0145325549780840
-70.208505435995252
-6-0.0857391470279228
-5-0.0460460808230784
-40.0821984238143081
-30.0502321810039133
-20.0998326005884353
-1-0.105966745275280
00.0270323086649096
10.0237662791287992
2-0.0646384517758616
3-0.143866984219393
40.093843801874696
50.139007595198287
60.082792061699765
70.116077651095044
80.159015302348164
90.0254546070599204
100.120933295840497
11-0.0194957625514101
12-0.0285824387855386
13-0.0270857496901464
14-0.08839894429683
15-0.116528325728273


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
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')