FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationFri, 28 Nov 2008 06:48:15 -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/Nov/28/t12278802151i9tglmdmkuloxl.htm/, Retrieved Sun, 19 May 2024 09:25:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26110, Retrieved Sun, 19 May 2024 09:25:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

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  [(Partial) Autocorrelation Function] [Non stationary ti...] [2008-11-28 13:32:29] [a57f5cc542637534b8bb5bcb4d37eab1]
- RMPD      [Cross Correlation Function] [Non stationary ti...] [2008-11-28 13:48:15] [0f30549460cf4ec26d9cf94b1fcf7789] [Current]
-   PD        [Cross Correlation Function] [Non stationary ti...] [2008-12-01 19:40:01] [a57f5cc542637534b8bb5bcb4d37eab1]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,33
0,33
0,32
0,33
0,34
0,36
0,34
0,33
0,35
0,31
0,28
0,26
0,26
0,26
0,29
0,30
0,30
0,28
0,29
0,29
0,32
0,33
0,29
0,31
0,33
0,36
0,39
0,30
0,27
0,28
0,29
0,30
0,30
0,30
0,31
0,30
0,31
0,29
0,32
0,33
0,35
0,35
0,36
0,40
0,40
0,47
0,43
0,38
0,38
0,40
0,45
0,47
0,45
0,50
0,54
0,55
0,59
0,51
0,50
0,50
Dataseries Y:
Download CSV
Histogram 
1,00
1,04
1,02
1,07
1,12
1,08
1,02
1,01
1,04
0,98
0,95
0,94
0,94
0,96
0,97
1,03
1,01
0,99
1,00
1,00
1,02
1,01
0,99
0,98
1,01
1,03
1,03
1,00
0,96
0,97
0,98
1,02
1,04
1,01
1,01
1,00
1,01
1,02
1,03
1,06
1,12
1,12
1,13
1,13
1,13
1,17
1,14
1,08
1,07
1,12
1,14
1,21
1,20
1,23
1,29
1,31
1,37
1,35
1,26
1,26

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=26110&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=26110&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26110&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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-140.129063651511139
-130.182606604945456
-120.233168827592458
-110.281141996771638
-100.297741148799704
-90.322977117652484
-80.362446241979658
-70.409629417921219
-60.484807564308452
-50.541171922162833
-40.603238836245062
-30.704168106739185
-20.7905057374326
-10.893327008537825
00.958587088563703
10.89495346520351
20.819569522258578
30.720173768049243
40.630171630909062
50.553586101611115
60.455438403945243
70.383473339297566
80.341428438699840
90.316019866282538
100.312505392164933
110.294830787157925
120.260041874868739
130.234732881430969
140.183652848090402

\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) & 1 \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
-14 & 0.129063651511139 \tabularnewline
-13 & 0.182606604945456 \tabularnewline
-12 & 0.233168827592458 \tabularnewline
-11 & 0.281141996771638 \tabularnewline
-10 & 0.297741148799704 \tabularnewline
-9 & 0.322977117652484 \tabularnewline
-8 & 0.362446241979658 \tabularnewline
-7 & 0.409629417921219 \tabularnewline
-6 & 0.484807564308452 \tabularnewline
-5 & 0.541171922162833 \tabularnewline
-4 & 0.603238836245062 \tabularnewline
-3 & 0.704168106739185 \tabularnewline
-2 & 0.7905057374326 \tabularnewline
-1 & 0.893327008537825 \tabularnewline
0 & 0.958587088563703 \tabularnewline
1 & 0.89495346520351 \tabularnewline
2 & 0.819569522258578 \tabularnewline
3 & 0.720173768049243 \tabularnewline
4 & 0.630171630909062 \tabularnewline
5 & 0.553586101611115 \tabularnewline
6 & 0.455438403945243 \tabularnewline
7 & 0.383473339297566 \tabularnewline
8 & 0.341428438699840 \tabularnewline
9 & 0.316019866282538 \tabularnewline
10 & 0.312505392164933 \tabularnewline
11 & 0.294830787157925 \tabularnewline
12 & 0.260041874868739 \tabularnewline
13 & 0.234732881430969 \tabularnewline
14 & 0.183652848090402 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26110&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]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]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]-14[/C][C]0.129063651511139[/C][/ROW]
[ROW][C]-13[/C][C]0.182606604945456[/C][/ROW]
[ROW][C]-12[/C][C]0.233168827592458[/C][/ROW]
[ROW][C]-11[/C][C]0.281141996771638[/C][/ROW]
[ROW][C]-10[/C][C]0.297741148799704[/C][/ROW]
[ROW][C]-9[/C][C]0.322977117652484[/C][/ROW]
[ROW][C]-8[/C][C]0.362446241979658[/C][/ROW]
[ROW][C]-7[/C][C]0.409629417921219[/C][/ROW]
[ROW][C]-6[/C][C]0.484807564308452[/C][/ROW]
[ROW][C]-5[/C][C]0.541171922162833[/C][/ROW]
[ROW][C]-4[/C][C]0.603238836245062[/C][/ROW]
[ROW][C]-3[/C][C]0.704168106739185[/C][/ROW]
[ROW][C]-2[/C][C]0.7905057374326[/C][/ROW]
[ROW][C]-1[/C][C]0.893327008537825[/C][/ROW]
[ROW][C]0[/C][C]0.958587088563703[/C][/ROW]
[ROW][C]1[/C][C]0.89495346520351[/C][/ROW]
[ROW][C]2[/C][C]0.819569522258578[/C][/ROW]
[ROW][C]3[/C][C]0.720173768049243[/C][/ROW]
[ROW][C]4[/C][C]0.630171630909062[/C][/ROW]
[ROW][C]5[/C][C]0.553586101611115[/C][/ROW]
[ROW][C]6[/C][C]0.455438403945243[/C][/ROW]
[ROW][C]7[/C][C]0.383473339297566[/C][/ROW]
[ROW][C]8[/C][C]0.341428438699840[/C][/ROW]
[ROW][C]9[/C][C]0.316019866282538[/C][/ROW]
[ROW][C]10[/C][C]0.312505392164933[/C][/ROW]
[ROW][C]11[/C][C]0.294830787157925[/C][/ROW]
[ROW][C]12[/C][C]0.260041874868739[/C][/ROW]
[ROW][C]13[/C][C]0.234732881430969[/C][/ROW]
[ROW][C]14[/C][C]0.183652848090402[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26110&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26110&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)1
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])
-140.129063651511139
-130.182606604945456
-120.233168827592458
-110.281141996771638
-100.297741148799704
-90.322977117652484
-80.362446241979658
-70.409629417921219
-60.484807564308452
-50.541171922162833
-40.603238836245062
-30.704168106739185
-20.7905057374326
-10.893327008537825
00.958587088563703
10.89495346520351
20.819569522258578
30.720173768049243
40.630171630909062
50.553586101611115
60.455438403945243
70.383473339297566
80.341428438699840
90.316019866282538
100.312505392164933
110.294830787157925
120.260041874868739
130.234732881430969
140.183652848090402


Figures (Output of Computation)

Input Parameters & R Code

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