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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 07:04:13 -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/t1196258086je9jga15rqa5uu7.htm/, Retrieved Wed, 01 May 2024 23:20:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7053, Retrieved Wed, 01 May 2024 23:20:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgroep MENS
Estimated Impact195

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] [voeding en transp...] [2007-11-28 14:04:13] [82643448f9a1604e63bdcbbe838c35e0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100
100
100
100.1
100
100
99.8
100
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
99.1
98.9
98.5
96.9
96.8
97
97
96.9
97.1
97.2
97.9
98.9
99.2
99.5
99.3
99.9
100
100.3
100.5
100.7
100.9
100.8
100.9
101
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
104.9
104.9
105.4
106
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=7053&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=7053&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7053&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])
-15-0.0553926627236485
-14-0.00068607271090496
-130.00566395420605906
-120.109444014754057
-110.0592508581372380
-10-0.213067974488625
-90.0140317286744916
-8-0.0820319410463342
-7-0.125668863498814
-60.145647840448194
-50.0097033036500538
-4-0.130831753365444
-30.187430824844792
-2-0.000616694571602348
-10.0533845510248649
00.0160957283188199
10.00960694512324599
2-0.0258819003019365
3-0.0224611726000820
4-0.0718140828630965
5-0.0327214285351161
60.213349341386919
7-0.0112874378308605
8-0.0215110775257046
90.133315876186681
100.104059500275758
110.0269437712674136
12-0.000936604880620486
130.0389538980493734
14-0.0146426417344832
150.0160436947143418

\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 & -0.0553926627236485 \tabularnewline
-14 & -0.00068607271090496 \tabularnewline
-13 & 0.00566395420605906 \tabularnewline
-12 & 0.109444014754057 \tabularnewline
-11 & 0.0592508581372380 \tabularnewline
-10 & -0.213067974488625 \tabularnewline
-9 & 0.0140317286744916 \tabularnewline
-8 & -0.0820319410463342 \tabularnewline
-7 & -0.125668863498814 \tabularnewline
-6 & 0.145647840448194 \tabularnewline
-5 & 0.0097033036500538 \tabularnewline
-4 & -0.130831753365444 \tabularnewline
-3 & 0.187430824844792 \tabularnewline
-2 & -0.000616694571602348 \tabularnewline
-1 & 0.0533845510248649 \tabularnewline
0 & 0.0160957283188199 \tabularnewline
1 & 0.00960694512324599 \tabularnewline
2 & -0.0258819003019365 \tabularnewline
3 & -0.0224611726000820 \tabularnewline
4 & -0.0718140828630965 \tabularnewline
5 & -0.0327214285351161 \tabularnewline
6 & 0.213349341386919 \tabularnewline
7 & -0.0112874378308605 \tabularnewline
8 & -0.0215110775257046 \tabularnewline
9 & 0.133315876186681 \tabularnewline
10 & 0.104059500275758 \tabularnewline
11 & 0.0269437712674136 \tabularnewline
12 & -0.000936604880620486 \tabularnewline
13 & 0.0389538980493734 \tabularnewline
14 & -0.0146426417344832 \tabularnewline
15 & 0.0160436947143418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7053&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]-0.0553926627236485[/C][/ROW]
[ROW][C]-14[/C][C]-0.00068607271090496[/C][/ROW]
[ROW][C]-13[/C][C]0.00566395420605906[/C][/ROW]
[ROW][C]-12[/C][C]0.109444014754057[/C][/ROW]
[ROW][C]-11[/C][C]0.0592508581372380[/C][/ROW]
[ROW][C]-10[/C][C]-0.213067974488625[/C][/ROW]
[ROW][C]-9[/C][C]0.0140317286744916[/C][/ROW]
[ROW][C]-8[/C][C]-0.0820319410463342[/C][/ROW]
[ROW][C]-7[/C][C]-0.125668863498814[/C][/ROW]
[ROW][C]-6[/C][C]0.145647840448194[/C][/ROW]
[ROW][C]-5[/C][C]0.0097033036500538[/C][/ROW]
[ROW][C]-4[/C][C]-0.130831753365444[/C][/ROW]
[ROW][C]-3[/C][C]0.187430824844792[/C][/ROW]
[ROW][C]-2[/C][C]-0.000616694571602348[/C][/ROW]
[ROW][C]-1[/C][C]0.0533845510248649[/C][/ROW]
[ROW][C]0[/C][C]0.0160957283188199[/C][/ROW]
[ROW][C]1[/C][C]0.00960694512324599[/C][/ROW]
[ROW][C]2[/C][C]-0.0258819003019365[/C][/ROW]
[ROW][C]3[/C][C]-0.0224611726000820[/C][/ROW]
[ROW][C]4[/C][C]-0.0718140828630965[/C][/ROW]
[ROW][C]5[/C][C]-0.0327214285351161[/C][/ROW]
[ROW][C]6[/C][C]0.213349341386919[/C][/ROW]
[ROW][C]7[/C][C]-0.0112874378308605[/C][/ROW]
[ROW][C]8[/C][C]-0.0215110775257046[/C][/ROW]
[ROW][C]9[/C][C]0.133315876186681[/C][/ROW]
[ROW][C]10[/C][C]0.104059500275758[/C][/ROW]
[ROW][C]11[/C][C]0.0269437712674136[/C][/ROW]
[ROW][C]12[/C][C]-0.000936604880620486[/C][/ROW]
[ROW][C]13[/C][C]0.0389538980493734[/C][/ROW]
[ROW][C]14[/C][C]-0.0146426417344832[/C][/ROW]
[ROW][C]15[/C][C]0.0160436947143418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7053&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7053&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])
-15-0.0553926627236485
-14-0.00068607271090496
-130.00566395420605906
-120.109444014754057
-110.0592508581372380
-10-0.213067974488625
-90.0140317286744916
-8-0.0820319410463342
-7-0.125668863498814
-60.145647840448194
-50.0097033036500538
-4-0.130831753365444
-30.187430824844792
-2-0.000616694571602348
-10.0533845510248649
00.0160957283188199
10.00960694512324599
2-0.0258819003019365
3-0.0224611726000820
4-0.0718140828630965
5-0.0327214285351161
60.213349341386919
7-0.0112874378308605
8-0.0215110775257046
90.133315876186681
100.104059500275758
110.0269437712674136
12-0.000936604880620486
130.0389538980493734
14-0.0146426417344832
150.0160436947143418


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')