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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 computationMon, 01 Dec 2008 13:56:55 -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/01/t1228165056nsl6ujw7a13om3q.htm/, Retrieved Sun, 05 May 2024 15:48:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27399, Retrieved Sun, 05 May 2024 15:48:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

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] [Cross Corr] [2008-12-01 19:38:27] [bc937651ef42bf891200cf0e0edc7238]
F   PD    [Cross Correlation Function] [Task 7: Q9] [2008-12-01 20:56:55] [96c9291ce335a5c9abba7b920811c2df] [Current]
Feedback Forum
2008-12-08 19:10:00 [8e2cc0b2ef568da46d009b2f601285b2] [reply] 
De foutieve correlatie veroorzaakt doordat beide reeksen een trend (termijn/seizoenaal) vertonen is weggehaald door het stationair maken van beide reeksen. Nu blijkt dat er geen echte significante correlatie tussen beide is in tegenstelling tot het berekenen van CCF op niet stationaire reeksen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6
4
2
0
4
4
4
7
4
6
5
8
9
8
9
10
11
11
10
11
12
10
12
12
9
11
11
11
9
11
11
12
12
11
10
10
6
8
9
9
8
9
11
12
12
11
10
13
11
12
11
12
11
12
12
12
12
12
11
9
Dataseries Y:
Download CSV
Histogram 
59
44
41
35
34
36
39
40
30
33
30
32
41
40
41
40
39
34
34
46
45
44
40
39
37
39
35
26
26
33
27
30
26
27
18
19
13
14
41
21
16
17
9
14
14
16
11
10
6
9
5
7
2
0
8
13
11
19
23
23

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27399&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27399&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27399&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'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])
-14-0.0845795924108032
-130.0385195861113345
-120.12539036144944
-11-0.116118578110739
-10-0.120187930312325
-9-0.0225716738788804
-80.0878133857899931
-70.0666278219708945
-60.135234013666031
-5-0.0860690466843367
-4-0.078217203574045
-30.118623864297025
-2-0.114846471084961
-1-0.039814864485487
00.333656757777166
1-0.0692350620900294
20.0121580064922684
3-0.19972126647406
40.0978938491869751
5-0.125879276900149
60.123258133971989
7-0.0443541316321144
8-0.167590021109664
90.158132866983964
10-0.062167800835709
11-0.000297056686165188
12-0.0677001919736813
130.0897315100084608
14-0.0761581975574583

\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
-14 & -0.0845795924108032 \tabularnewline
-13 & 0.0385195861113345 \tabularnewline
-12 & 0.12539036144944 \tabularnewline
-11 & -0.116118578110739 \tabularnewline
-10 & -0.120187930312325 \tabularnewline
-9 & -0.0225716738788804 \tabularnewline
-8 & 0.0878133857899931 \tabularnewline
-7 & 0.0666278219708945 \tabularnewline
-6 & 0.135234013666031 \tabularnewline
-5 & -0.0860690466843367 \tabularnewline
-4 & -0.078217203574045 \tabularnewline
-3 & 0.118623864297025 \tabularnewline
-2 & -0.114846471084961 \tabularnewline
-1 & -0.039814864485487 \tabularnewline
0 & 0.333656757777166 \tabularnewline
1 & -0.0692350620900294 \tabularnewline
2 & 0.0121580064922684 \tabularnewline
3 & -0.19972126647406 \tabularnewline
4 & 0.0978938491869751 \tabularnewline
5 & -0.125879276900149 \tabularnewline
6 & 0.123258133971989 \tabularnewline
7 & -0.0443541316321144 \tabularnewline
8 & -0.167590021109664 \tabularnewline
9 & 0.158132866983964 \tabularnewline
10 & -0.062167800835709 \tabularnewline
11 & -0.000297056686165188 \tabularnewline
12 & -0.0677001919736813 \tabularnewline
13 & 0.0897315100084608 \tabularnewline
14 & -0.0761581975574583 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27399&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]-14[/C][C]-0.0845795924108032[/C][/ROW]
[ROW][C]-13[/C][C]0.0385195861113345[/C][/ROW]
[ROW][C]-12[/C][C]0.12539036144944[/C][/ROW]
[ROW][C]-11[/C][C]-0.116118578110739[/C][/ROW]
[ROW][C]-10[/C][C]-0.120187930312325[/C][/ROW]
[ROW][C]-9[/C][C]-0.0225716738788804[/C][/ROW]
[ROW][C]-8[/C][C]0.0878133857899931[/C][/ROW]
[ROW][C]-7[/C][C]0.0666278219708945[/C][/ROW]
[ROW][C]-6[/C][C]0.135234013666031[/C][/ROW]
[ROW][C]-5[/C][C]-0.0860690466843367[/C][/ROW]
[ROW][C]-4[/C][C]-0.078217203574045[/C][/ROW]
[ROW][C]-3[/C][C]0.118623864297025[/C][/ROW]
[ROW][C]-2[/C][C]-0.114846471084961[/C][/ROW]
[ROW][C]-1[/C][C]-0.039814864485487[/C][/ROW]
[ROW][C]0[/C][C]0.333656757777166[/C][/ROW]
[ROW][C]1[/C][C]-0.0692350620900294[/C][/ROW]
[ROW][C]2[/C][C]0.0121580064922684[/C][/ROW]
[ROW][C]3[/C][C]-0.19972126647406[/C][/ROW]
[ROW][C]4[/C][C]0.0978938491869751[/C][/ROW]
[ROW][C]5[/C][C]-0.125879276900149[/C][/ROW]
[ROW][C]6[/C][C]0.123258133971989[/C][/ROW]
[ROW][C]7[/C][C]-0.0443541316321144[/C][/ROW]
[ROW][C]8[/C][C]-0.167590021109664[/C][/ROW]
[ROW][C]9[/C][C]0.158132866983964[/C][/ROW]
[ROW][C]10[/C][C]-0.062167800835709[/C][/ROW]
[ROW][C]11[/C][C]-0.000297056686165188[/C][/ROW]
[ROW][C]12[/C][C]-0.0677001919736813[/C][/ROW]
[ROW][C]13[/C][C]0.0897315100084608[/C][/ROW]
[ROW][C]14[/C][C]-0.0761581975574583[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27399&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27399&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])
-14-0.0845795924108032
-130.0385195861113345
-120.12539036144944
-11-0.116118578110739
-10-0.120187930312325
-9-0.0225716738788804
-80.0878133857899931
-70.0666278219708945
-60.135234013666031
-5-0.0860690466843367
-4-0.078217203574045
-30.118623864297025
-2-0.114846471084961
-1-0.039814864485487
00.333656757777166
1-0.0692350620900294
20.0121580064922684
3-0.19972126647406
40.0978938491869751
5-0.125879276900149
60.123258133971989
7-0.0443541316321144
8-0.167590021109664
90.158132866983964
10-0.062167800835709
11-0.000297056686165188
12-0.0677001919736813
130.0897315100084608
14-0.0761581975574583


Figures (Output of Computation)

Input Parameters & R Code

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