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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 computationSun, 06 Jan 2008 14:31:20 -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/Jan/06/t1199655028g0ccicrs7ibtn3k.htm/, Retrieved Sat, 04 May 2024 20:25:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7908, Retrieved Sat, 04 May 2024 20:25:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing time series Q5 WL-EA2
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [WS2 - Robustness ...] [2007-10-20 13:06:37] [5343e105a400b9e32bf6f011133bbaf4]
- RM D    [Cross Correlation Function] [CVWS7Q5WL-EA2] [2008-01-06 21:31:20] [b523c8d839cc24a05ea912c062a47207] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.3
7.2
7.1
6.9
6.8
6.7
6.8
6.8
6.7
6.8
6.8
6.7
6.3
6.2
6.2
6.5
6.5
6.4
6.2
6.2
6.3
7.5
7.4
7.4
7.4
7.4
7.4
7.2
7.2
7.2
7.5
7.4
7.5
8.0
8.0
8.0
8.1
8.1
8.1
7.9
7.9
8.0
8.2
8.1
8.2
8.5
8.5
8.6
8.4
8.4
8.4
7.7
7.8
7.9
8.8
8.8
8.9
8.5
8.5
8.5
8.4
8.5
8.4
8.3
8.4
8.4
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.3
8.3
8.3
8.2
8.1
8.1
8.2
8.0
7.9
7.9
7.8
7.7
7.9
7.7
7.6
Dataseries Y:
Download CSV
Histogram 
13.5
16.2
17.6
15.8
17.6
15.2
15.9
12.0
13.3
14.8
16.1
16.9
17.6
13.9
10.0
7.6
7.1
8.1
8.1
7.7
4.0
1.4
0.3
-1.0
-1.9
-1.5
-0.2
3.4
3.0
4.1
3.4
3.2
6.1
5.8
6.2
5.8
5.9
6.7
5.9
3.8
1.7
1.4
1.8
3.0
3.6
4.8
4.3
4.2
2.9
4.9
7.2
8.7
9.1
8.9
9.0
11.6
9.6
9.1
9.2
10.8
11.0
8.5
6.5
7.2
7.8
8.7
7.8
7.5
7.7
7.5
8.3
7.9
10.4
11.5
14.0
11.9
11.9
10.3
11.3
9.9
8.9
9.2
8.8
6.7
7.1
6.6
7.2
5.0
5.3
6.3

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=7908&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=7908&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7908&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)1
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])
-160.0278796165086335
-15-0.0913916196636354
-14-0.0576184963009675
-130.0650340186249908
-120.0751564878076825
-110.211958593127207
-100.116924541529704
-90.0237192989892488
-80.0228361264162853
-7-0.135739932298769
-60.0978615464366755
-50.125011612297927
-40.0608050153632336
-30.0107297935924547
-20.0474319258831416
-10.0765747378683067
0-0.153871330961131
1-0.153490898726559
2-0.137948109329778
30.118487449166934
40.138926492294135
50.104450261066906
6-0.109427767001504
7-0.149528861145228
8-0.251434229497717
90.114726229375877
10-0.0552713104611991
110.125119307284924
12-0.0082692639978409
130.0689940095513058
14-0.223777821185244
15-0.0140351823781122
16-0.169384034529161

\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) & 1 \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
-16 & 0.0278796165086335 \tabularnewline
-15 & -0.0913916196636354 \tabularnewline
-14 & -0.0576184963009675 \tabularnewline
-13 & 0.0650340186249908 \tabularnewline
-12 & 0.0751564878076825 \tabularnewline
-11 & 0.211958593127207 \tabularnewline
-10 & 0.116924541529704 \tabularnewline
-9 & 0.0237192989892488 \tabularnewline
-8 & 0.0228361264162853 \tabularnewline
-7 & -0.135739932298769 \tabularnewline
-6 & 0.0978615464366755 \tabularnewline
-5 & 0.125011612297927 \tabularnewline
-4 & 0.0608050153632336 \tabularnewline
-3 & 0.0107297935924547 \tabularnewline
-2 & 0.0474319258831416 \tabularnewline
-1 & 0.0765747378683067 \tabularnewline
0 & -0.153871330961131 \tabularnewline
1 & -0.153490898726559 \tabularnewline
2 & -0.137948109329778 \tabularnewline
3 & 0.118487449166934 \tabularnewline
4 & 0.138926492294135 \tabularnewline
5 & 0.104450261066906 \tabularnewline
6 & -0.109427767001504 \tabularnewline
7 & -0.149528861145228 \tabularnewline
8 & -0.251434229497717 \tabularnewline
9 & 0.114726229375877 \tabularnewline
10 & -0.0552713104611991 \tabularnewline
11 & 0.125119307284924 \tabularnewline
12 & -0.0082692639978409 \tabularnewline
13 & 0.0689940095513058 \tabularnewline
14 & -0.223777821185244 \tabularnewline
15 & -0.0140351823781122 \tabularnewline
16 & -0.169384034529161 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7908&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]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]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]-16[/C][C]0.0278796165086335[/C][/ROW]
[ROW][C]-15[/C][C]-0.0913916196636354[/C][/ROW]
[ROW][C]-14[/C][C]-0.0576184963009675[/C][/ROW]
[ROW][C]-13[/C][C]0.0650340186249908[/C][/ROW]
[ROW][C]-12[/C][C]0.0751564878076825[/C][/ROW]
[ROW][C]-11[/C][C]0.211958593127207[/C][/ROW]
[ROW][C]-10[/C][C]0.116924541529704[/C][/ROW]
[ROW][C]-9[/C][C]0.0237192989892488[/C][/ROW]
[ROW][C]-8[/C][C]0.0228361264162853[/C][/ROW]
[ROW][C]-7[/C][C]-0.135739932298769[/C][/ROW]
[ROW][C]-6[/C][C]0.0978615464366755[/C][/ROW]
[ROW][C]-5[/C][C]0.125011612297927[/C][/ROW]
[ROW][C]-4[/C][C]0.0608050153632336[/C][/ROW]
[ROW][C]-3[/C][C]0.0107297935924547[/C][/ROW]
[ROW][C]-2[/C][C]0.0474319258831416[/C][/ROW]
[ROW][C]-1[/C][C]0.0765747378683067[/C][/ROW]
[ROW][C]0[/C][C]-0.153871330961131[/C][/ROW]
[ROW][C]1[/C][C]-0.153490898726559[/C][/ROW]
[ROW][C]2[/C][C]-0.137948109329778[/C][/ROW]
[ROW][C]3[/C][C]0.118487449166934[/C][/ROW]
[ROW][C]4[/C][C]0.138926492294135[/C][/ROW]
[ROW][C]5[/C][C]0.104450261066906[/C][/ROW]
[ROW][C]6[/C][C]-0.109427767001504[/C][/ROW]
[ROW][C]7[/C][C]-0.149528861145228[/C][/ROW]
[ROW][C]8[/C][C]-0.251434229497717[/C][/ROW]
[ROW][C]9[/C][C]0.114726229375877[/C][/ROW]
[ROW][C]10[/C][C]-0.0552713104611991[/C][/ROW]
[ROW][C]11[/C][C]0.125119307284924[/C][/ROW]
[ROW][C]12[/C][C]-0.0082692639978409[/C][/ROW]
[ROW][C]13[/C][C]0.0689940095513058[/C][/ROW]
[ROW][C]14[/C][C]-0.223777821185244[/C][/ROW]
[ROW][C]15[/C][C]-0.0140351823781122[/C][/ROW]
[ROW][C]16[/C][C]-0.169384034529161[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7908&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7908&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)1
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])
-160.0278796165086335
-15-0.0913916196636354
-14-0.0576184963009675
-130.0650340186249908
-120.0751564878076825
-110.211958593127207
-100.116924541529704
-90.0237192989892488
-80.0228361264162853
-7-0.135739932298769
-60.0978615464366755
-50.125011612297927
-40.0608050153632336
-30.0107297935924547
-20.0474319258831416
-10.0765747378683067
0-0.153871330961131
1-0.153490898726559
2-0.137948109329778
30.118487449166934
40.138926492294135
50.104450261066906
6-0.109427767001504
7-0.149528861145228
8-0.251434229497717
90.114726229375877
10-0.0552713104611991
110.125119307284924
12-0.0082692639978409
130.0689940095513058
14-0.223777821185244
15-0.0140351823781122
16-0.169384034529161


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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',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')