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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, 02 Dec 2008 07:59:47 -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/02/t1228235246gv64zkf559iayd6.htm/, Retrieved Fri, 17 May 2024 03:19:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28036, Retrieved Fri, 17 May 2024 03:19:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Cross Correlation Function] [Laura_Reussens_cr...] [2008-12-02 14:59:47] [72f421f2574380e5d56d79ce560242da] [Current]
Feedback Forum
2008-12-08 14:40:25 [Jessica Alves Pires] [reply] 
Je hebt een goede algemene uitleg gegeven. Jouw uitleg over de grafiek van je tijdreeks is ook goed.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5,5
5,3
5,2
5,3
5,3
5
4,8
4,9
5,3
6
6,2
6,4
6,4
6,4
6,2
6,1
6
5,9
6,2
6,2
6,4
6,8
6,9
7
7
6,9
6,7
6,6
6,5
6,4
6,5
6,5
6,6
6,7
6,8
7,2
7,6
7,6
7,3
6,4
6,1
6,3
7,1
7,5
7,4
7,1
6,8
6,9
7,2
7,4
7,3
6,9
6,9
6,8
7,1
7,2
7,1
7
6,9
7
7,4
7,5
7,5
7,4
7,3
7
6,7
6,5
6,5
6,5
6,6
6,8
6,9
6,9
6,8
6,8
6,5
6,1
6
5,9
5,8
5,9
5,9
6,2
6,3
6,2
6
5,8
5,5
5,5
5,7
5,8
Dataseries Y:
Download CSV
Histogram 
25
27
25
23
24
24
26
25
24
24
22
22
22
27
24
24
22
23
25
23
21
21
22
20
22
22
20
21
20
21
21
21
19
21
21
22
19
24
22
22
22
24
22
23
24
21
20
22
23
23
22
20
21
21
20
20
17
18
19
19
20
21
20
21
19
22
20
18
16
17
18
19
18
20
21
18
19
19
19
21
19
19
17
16
16
17
16
15
16
16
16
18

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28036&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28036&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28036&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'George Udny Yule' @ 72.249.76.132






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)12
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])
-16-0.241321220702978
-15-0.278384188111643
-14-0.310510888196503
-13-0.336513697501965
-12-0.327518106090937
-11-0.300349885378966
-10-0.279756719664159
-9-0.276148559794702
-8-0.277615997375125
-7-0.250202290250546
-6-0.206394071624459
-5-0.173347446545699
-4-0.16255383303151
-3-0.152841686686381
-2-0.147906573235256
-1-0.144417839188149
0-0.141506329949067
1-0.131420328855711
2-0.125222301756643
3-0.110949762113124
4-0.0998685458335173
5-0.0563831230895796
6-0.0204679705290575
70.0370367168052016
80.086519969738278
90.114081949502201
100.135732351059792
110.161881125259239
120.170660077074652
130.172618487480291
140.148435912327073
150.134908774434648
160.145326513923421

\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) & 12 \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 & -0.241321220702978 \tabularnewline
-15 & -0.278384188111643 \tabularnewline
-14 & -0.310510888196503 \tabularnewline
-13 & -0.336513697501965 \tabularnewline
-12 & -0.327518106090937 \tabularnewline
-11 & -0.300349885378966 \tabularnewline
-10 & -0.279756719664159 \tabularnewline
-9 & -0.276148559794702 \tabularnewline
-8 & -0.277615997375125 \tabularnewline
-7 & -0.250202290250546 \tabularnewline
-6 & -0.206394071624459 \tabularnewline
-5 & -0.173347446545699 \tabularnewline
-4 & -0.16255383303151 \tabularnewline
-3 & -0.152841686686381 \tabularnewline
-2 & -0.147906573235256 \tabularnewline
-1 & -0.144417839188149 \tabularnewline
0 & -0.141506329949067 \tabularnewline
1 & -0.131420328855711 \tabularnewline
2 & -0.125222301756643 \tabularnewline
3 & -0.110949762113124 \tabularnewline
4 & -0.0998685458335173 \tabularnewline
5 & -0.0563831230895796 \tabularnewline
6 & -0.0204679705290575 \tabularnewline
7 & 0.0370367168052016 \tabularnewline
8 & 0.086519969738278 \tabularnewline
9 & 0.114081949502201 \tabularnewline
10 & 0.135732351059792 \tabularnewline
11 & 0.161881125259239 \tabularnewline
12 & 0.170660077074652 \tabularnewline
13 & 0.172618487480291 \tabularnewline
14 & 0.148435912327073 \tabularnewline
15 & 0.134908774434648 \tabularnewline
16 & 0.145326513923421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28036&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]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]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]-0.241321220702978[/C][/ROW]
[ROW][C]-15[/C][C]-0.278384188111643[/C][/ROW]
[ROW][C]-14[/C][C]-0.310510888196503[/C][/ROW]
[ROW][C]-13[/C][C]-0.336513697501965[/C][/ROW]
[ROW][C]-12[/C][C]-0.327518106090937[/C][/ROW]
[ROW][C]-11[/C][C]-0.300349885378966[/C][/ROW]
[ROW][C]-10[/C][C]-0.279756719664159[/C][/ROW]
[ROW][C]-9[/C][C]-0.276148559794702[/C][/ROW]
[ROW][C]-8[/C][C]-0.277615997375125[/C][/ROW]
[ROW][C]-7[/C][C]-0.250202290250546[/C][/ROW]
[ROW][C]-6[/C][C]-0.206394071624459[/C][/ROW]
[ROW][C]-5[/C][C]-0.173347446545699[/C][/ROW]
[ROW][C]-4[/C][C]-0.16255383303151[/C][/ROW]
[ROW][C]-3[/C][C]-0.152841686686381[/C][/ROW]
[ROW][C]-2[/C][C]-0.147906573235256[/C][/ROW]
[ROW][C]-1[/C][C]-0.144417839188149[/C][/ROW]
[ROW][C]0[/C][C]-0.141506329949067[/C][/ROW]
[ROW][C]1[/C][C]-0.131420328855711[/C][/ROW]
[ROW][C]2[/C][C]-0.125222301756643[/C][/ROW]
[ROW][C]3[/C][C]-0.110949762113124[/C][/ROW]
[ROW][C]4[/C][C]-0.0998685458335173[/C][/ROW]
[ROW][C]5[/C][C]-0.0563831230895796[/C][/ROW]
[ROW][C]6[/C][C]-0.0204679705290575[/C][/ROW]
[ROW][C]7[/C][C]0.0370367168052016[/C][/ROW]
[ROW][C]8[/C][C]0.086519969738278[/C][/ROW]
[ROW][C]9[/C][C]0.114081949502201[/C][/ROW]
[ROW][C]10[/C][C]0.135732351059792[/C][/ROW]
[ROW][C]11[/C][C]0.161881125259239[/C][/ROW]
[ROW][C]12[/C][C]0.170660077074652[/C][/ROW]
[ROW][C]13[/C][C]0.172618487480291[/C][/ROW]
[ROW][C]14[/C][C]0.148435912327073[/C][/ROW]
[ROW][C]15[/C][C]0.134908774434648[/C][/ROW]
[ROW][C]16[/C][C]0.145326513923421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28036&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28036&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)12
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])
-16-0.241321220702978
-15-0.278384188111643
-14-0.310510888196503
-13-0.336513697501965
-12-0.327518106090937
-11-0.300349885378966
-10-0.279756719664159
-9-0.276148559794702
-8-0.277615997375125
-7-0.250202290250546
-6-0.206394071624459
-5-0.173347446545699
-4-0.16255383303151
-3-0.152841686686381
-2-0.147906573235256
-1-0.144417839188149
0-0.141506329949067
1-0.131420328855711
2-0.125222301756643
3-0.110949762113124
4-0.0998685458335173
5-0.0563831230895796
6-0.0204679705290575
70.0370367168052016
80.086519969738278
90.114081949502201
100.135732351059792
110.161881125259239
120.170660077074652
130.172618487480291
140.148435912327073
150.134908774434648
160.145326513923421


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; 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) 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')