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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 07 Dec 2008 08:28:13 -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/2008/Dec/07/t1228663725zmc6o7ghtn42701.htm/, Retrieved Sat, 18 May 2024 19:32:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30089, Retrieved Sat, 18 May 2024 19:32:11 +0000
QR Codes:

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

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [Spectral Analysis] [Q6 non statistica...] [2008-12-01 11:41:39] [7d3039e6253bb5fb3b26df1537d500b4]
F RMPD    [Cross Correlation Function] [Q9 Cross Correlat...] [2008-12-01 20:56:24] [7d3039e6253bb5fb3b26df1537d500b4]
-   P         [Cross Correlation Function] [Q9 Cross Correlat...] [2008-12-07 15:28:13] [35348cd8592af0baf5f138bd59921307] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.8
7.6
7.5
7.6
7.5
7.3
7.6
7.5
7.6
7.9
7.9
8.1
8.2
8.0
7.5
6.8
6.5
6.6
7.6
8.0
8.0
7.7
7.5
7.6
7.7
7.9
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.1
7.9
7.3
6.9
6.6
6.7
6.9
7.0
7.1
7.2
7.1
6.9
7.0
6.8
6.4
6.7
6.7
6.4
6.3
6.2
6.5
6.8
6.8
6.5
6.3
5.9
5.9
6.4
6.4
Dataseries Y:
Download CSV
Histogram 
9.0
9.1
8.7
8.2
7.9
7.9
9.1
9.4
9.5
9.1
9.0
9.3
9.9
9.8
9.4
8.3
8.0
8.5
10.4
11.1
10.9
9.9
9.2
9.2
9.5
9.6
9.5
9.1
8.9
9.0
10.1
10.3
10.2
9.6
9.2
9.3
9.4
9.4
9.2
9.0
9.0
9.0
9.8
10.0
9.9
9.3
9.0
9.0
9.1
9.1
9.1
9.2
8.8
8.3
8.4
8.1
7.8
7.9
7.9
8.0
7.9
7.5
7.2
6.9
6.6
6.7
7.3
7.5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30089&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]0 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=30089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30089&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series2
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 series0
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.110057814571407
-140.116671332550931
-13-0.0441681441674287
-120.159273575982235
-11-0.359580948853264
-100.0156072383526667
-90.0908147209468547
-80.115940209734335
-70.0495421523714426
-6-0.115143952540041
-5-0.178973443939134
-4-0.071486882134705
-30.180570199420459
-20.196436036766416
-10.0489240372271348
00.160699895219598
1-0.544471074212441
2-0.0149019957950327
30.0684710003047538
40.179342067563901
50.15899635319047
6-0.0831870538963207
7-0.183995338496553
8-0.089617482791365
90.0558159696249978
100.221136483979364
110.0378282133102222
120.124536576003209
13-0.393535409560518
140.00103927569949829
15-0.0200475919473735

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 2 \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 & 0 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.110057814571407 \tabularnewline
-14 & 0.116671332550931 \tabularnewline
-13 & -0.0441681441674287 \tabularnewline
-12 & 0.159273575982235 \tabularnewline
-11 & -0.359580948853264 \tabularnewline
-10 & 0.0156072383526667 \tabularnewline
-9 & 0.0908147209468547 \tabularnewline
-8 & 0.115940209734335 \tabularnewline
-7 & 0.0495421523714426 \tabularnewline
-6 & -0.115143952540041 \tabularnewline
-5 & -0.178973443939134 \tabularnewline
-4 & -0.071486882134705 \tabularnewline
-3 & 0.180570199420459 \tabularnewline
-2 & 0.196436036766416 \tabularnewline
-1 & 0.0489240372271348 \tabularnewline
0 & 0.160699895219598 \tabularnewline
1 & -0.544471074212441 \tabularnewline
2 & -0.0149019957950327 \tabularnewline
3 & 0.0684710003047538 \tabularnewline
4 & 0.179342067563901 \tabularnewline
5 & 0.15899635319047 \tabularnewline
6 & -0.0831870538963207 \tabularnewline
7 & -0.183995338496553 \tabularnewline
8 & -0.089617482791365 \tabularnewline
9 & 0.0558159696249978 \tabularnewline
10 & 0.221136483979364 \tabularnewline
11 & 0.0378282133102222 \tabularnewline
12 & 0.124536576003209 \tabularnewline
13 & -0.393535409560518 \tabularnewline
14 & 0.00103927569949829 \tabularnewline
15 & -0.0200475919473735 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30089&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]2[/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]0[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]2[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]0.110057814571407[/C][/ROW]
[ROW][C]-14[/C][C]0.116671332550931[/C][/ROW]
[ROW][C]-13[/C][C]-0.0441681441674287[/C][/ROW]
[ROW][C]-12[/C][C]0.159273575982235[/C][/ROW]
[ROW][C]-11[/C][C]-0.359580948853264[/C][/ROW]
[ROW][C]-10[/C][C]0.0156072383526667[/C][/ROW]
[ROW][C]-9[/C][C]0.0908147209468547[/C][/ROW]
[ROW][C]-8[/C][C]0.115940209734335[/C][/ROW]
[ROW][C]-7[/C][C]0.0495421523714426[/C][/ROW]
[ROW][C]-6[/C][C]-0.115143952540041[/C][/ROW]
[ROW][C]-5[/C][C]-0.178973443939134[/C][/ROW]
[ROW][C]-4[/C][C]-0.071486882134705[/C][/ROW]
[ROW][C]-3[/C][C]0.180570199420459[/C][/ROW]
[ROW][C]-2[/C][C]0.196436036766416[/C][/ROW]
[ROW][C]-1[/C][C]0.0489240372271348[/C][/ROW]
[ROW][C]0[/C][C]0.160699895219598[/C][/ROW]
[ROW][C]1[/C][C]-0.544471074212441[/C][/ROW]
[ROW][C]2[/C][C]-0.0149019957950327[/C][/ROW]
[ROW][C]3[/C][C]0.0684710003047538[/C][/ROW]
[ROW][C]4[/C][C]0.179342067563901[/C][/ROW]
[ROW][C]5[/C][C]0.15899635319047[/C][/ROW]
[ROW][C]6[/C][C]-0.0831870538963207[/C][/ROW]
[ROW][C]7[/C][C]-0.183995338496553[/C][/ROW]
[ROW][C]8[/C][C]-0.089617482791365[/C][/ROW]
[ROW][C]9[/C][C]0.0558159696249978[/C][/ROW]
[ROW][C]10[/C][C]0.221136483979364[/C][/ROW]
[ROW][C]11[/C][C]0.0378282133102222[/C][/ROW]
[ROW][C]12[/C][C]0.124536576003209[/C][/ROW]
[ROW][C]13[/C][C]-0.393535409560518[/C][/ROW]
[ROW][C]14[/C][C]0.00103927569949829[/C][/ROW]
[ROW][C]15[/C][C]-0.0200475919473735[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30089&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 series2
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 series0
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.110057814571407
-140.116671332550931
-13-0.0441681441674287
-120.159273575982235
-11-0.359580948853264
-100.0156072383526667
-90.0908147209468547
-80.115940209734335
-70.0495421523714426
-6-0.115143952540041
-5-0.178973443939134
-4-0.071486882134705
-30.180570199420459
-20.196436036766416
-10.0489240372271348
00.160699895219598
1-0.544471074212441
2-0.0149019957950327
30.0684710003047538
40.179342067563901
50.15899635319047
6-0.0831870538963207
7-0.183995338496553
8-0.089617482791365
90.0558159696249978
100.221136483979364
110.0378282133102222
120.124536576003209
13-0.393535409560518
140.00103927569949829
15-0.0200475919473735


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2.0 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 0.0 ; par6 = 2 ; par7 = 1 ;
Parameters (R input):
par1 = 2.0 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 0.0 ; par6 = 2 ; par7 = 1 ;
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')