FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 20 Dec 2009 10:12:28 -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/2009/Dec/20/t1261329893lifrrb8uy44w00c.htm/, Retrieved Sat, 27 Apr 2024 10:35:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69958, Retrieved Sat, 27 Apr 2024 10:35:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [] [2009-12-20 17:12:28] [e24e91da8d334fb8882bf413603fde71] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,8
1,1
1,3
1,2
1,3
1,1
1,3
1,2
1,6
1,7
1,5
0,9
1,5
1,4
1,6
1,7
1,4
1,8
1,7
1,4
1,2
1
1,7
2,4
2
2,1
2
1,8
2,7
2,3
1,9
2
2,3
2,8
2,4
2,3
2,7
2,7
2,9
3
2,2
2,3
2,8
2,8
2,8
2,2
2,6
2,8
2,5
2,4
2,3
1,9
1,7
2
2,1
1,7
1,8
1,8
1,8
1,3
1,3
1,3
1,2
1,4
2,2
2,9
3,1
3,5
3,6
4,4
4,1
5,1
5,8
5,9
5,4
5,5
4,8
3,2
2,7
2,1
1,9
0,6
0,7
-0,2
-1
-1,7
-0,7
Dataseries Y:
Download CSV
Histogram 
6,8
7,5
7,6
7,8
8
8,1
8,2
8,3
8,2
8
7,9
7,6
7,6
8,3
8,4
8,4
8,4
8,4
8,6
8,9
8,8
8,3
7,5
7,2
7,4
8,8
9,3
9,3
8,7
8,2
8,3
8,5
8,6
8,5
8,2
8,1
7,9
8,6
8,7
8,7
8,5
8,4
8,5
8,7
8,7
8,6
8,5
8,3
8
8,2
8,1
8,1
8
7,9
7,9
8
8
7,9
8
7,7
7,2
7,5
7,3
7
7
7
7,2
7,3
7,1
6,8
6,4
6,1
6,5
7,7
7,9
7,5
6,9
6,6
6,9
7,7
8
8
7,7
7,3
7,4
8,1
8,3

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=69958&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=69958&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69958&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])
-160.0266426414991037
-150.0555329627382918
-140.00609908734674021
-130.0272882585261464
-12-0.0144046881379590
-11-0.043965141164494
-100.0125952213018865
-90.066363121298243
-80.0434377500380908
-7-0.0155111826587287
-6-0.100698124546831
-5-0.0627860014814108
-4-0.034070706379945
-3-0.0184107700058582
-20.0272343260534759
-10.0185894964847585
0-0.0228409109727632
10.0149298590596553
2-0.0143821160567725
3-0.0741247719362865
4-0.214451052769865
5-0.117155484444791
6-0.0416347587990799
70.135798913402219
80.0381869659064212
90.0160749296372065
10-0.0768351793406874
11-0.0699724340833246
12-0.0557585910416239
130.0930583076420755
140.062465459426861
15-0.0233958696409431
160.0238342675620139

\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 & 0.0266426414991037 \tabularnewline
-15 & 0.0555329627382918 \tabularnewline
-14 & 0.00609908734674021 \tabularnewline
-13 & 0.0272882585261464 \tabularnewline
-12 & -0.0144046881379590 \tabularnewline
-11 & -0.043965141164494 \tabularnewline
-10 & 0.0125952213018865 \tabularnewline
-9 & 0.066363121298243 \tabularnewline
-8 & 0.0434377500380908 \tabularnewline
-7 & -0.0155111826587287 \tabularnewline
-6 & -0.100698124546831 \tabularnewline
-5 & -0.0627860014814108 \tabularnewline
-4 & -0.034070706379945 \tabularnewline
-3 & -0.0184107700058582 \tabularnewline
-2 & 0.0272343260534759 \tabularnewline
-1 & 0.0185894964847585 \tabularnewline
0 & -0.0228409109727632 \tabularnewline
1 & 0.0149298590596553 \tabularnewline
2 & -0.0143821160567725 \tabularnewline
3 & -0.0741247719362865 \tabularnewline
4 & -0.214451052769865 \tabularnewline
5 & -0.117155484444791 \tabularnewline
6 & -0.0416347587990799 \tabularnewline
7 & 0.135798913402219 \tabularnewline
8 & 0.0381869659064212 \tabularnewline
9 & 0.0160749296372065 \tabularnewline
10 & -0.0768351793406874 \tabularnewline
11 & -0.0699724340833246 \tabularnewline
12 & -0.0557585910416239 \tabularnewline
13 & 0.0930583076420755 \tabularnewline
14 & 0.062465459426861 \tabularnewline
15 & -0.0233958696409431 \tabularnewline
16 & 0.0238342675620139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69958&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]0.0266426414991037[/C][/ROW]
[ROW][C]-15[/C][C]0.0555329627382918[/C][/ROW]
[ROW][C]-14[/C][C]0.00609908734674021[/C][/ROW]
[ROW][C]-13[/C][C]0.0272882585261464[/C][/ROW]
[ROW][C]-12[/C][C]-0.0144046881379590[/C][/ROW]
[ROW][C]-11[/C][C]-0.043965141164494[/C][/ROW]
[ROW][C]-10[/C][C]0.0125952213018865[/C][/ROW]
[ROW][C]-9[/C][C]0.066363121298243[/C][/ROW]
[ROW][C]-8[/C][C]0.0434377500380908[/C][/ROW]
[ROW][C]-7[/C][C]-0.0155111826587287[/C][/ROW]
[ROW][C]-6[/C][C]-0.100698124546831[/C][/ROW]
[ROW][C]-5[/C][C]-0.0627860014814108[/C][/ROW]
[ROW][C]-4[/C][C]-0.034070706379945[/C][/ROW]
[ROW][C]-3[/C][C]-0.0184107700058582[/C][/ROW]
[ROW][C]-2[/C][C]0.0272343260534759[/C][/ROW]
[ROW][C]-1[/C][C]0.0185894964847585[/C][/ROW]
[ROW][C]0[/C][C]-0.0228409109727632[/C][/ROW]
[ROW][C]1[/C][C]0.0149298590596553[/C][/ROW]
[ROW][C]2[/C][C]-0.0143821160567725[/C][/ROW]
[ROW][C]3[/C][C]-0.0741247719362865[/C][/ROW]
[ROW][C]4[/C][C]-0.214451052769865[/C][/ROW]
[ROW][C]5[/C][C]-0.117155484444791[/C][/ROW]
[ROW][C]6[/C][C]-0.0416347587990799[/C][/ROW]
[ROW][C]7[/C][C]0.135798913402219[/C][/ROW]
[ROW][C]8[/C][C]0.0381869659064212[/C][/ROW]
[ROW][C]9[/C][C]0.0160749296372065[/C][/ROW]
[ROW][C]10[/C][C]-0.0768351793406874[/C][/ROW]
[ROW][C]11[/C][C]-0.0699724340833246[/C][/ROW]
[ROW][C]12[/C][C]-0.0557585910416239[/C][/ROW]
[ROW][C]13[/C][C]0.0930583076420755[/C][/ROW]
[ROW][C]14[/C][C]0.062465459426861[/C][/ROW]
[ROW][C]15[/C][C]-0.0233958696409431[/C][/ROW]
[ROW][C]16[/C][C]0.0238342675620139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69958&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69958&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])
-160.0266426414991037
-150.0555329627382918
-140.00609908734674021
-130.0272882585261464
-12-0.0144046881379590
-11-0.043965141164494
-100.0125952213018865
-90.066363121298243
-80.0434377500380908
-7-0.0155111826587287
-6-0.100698124546831
-5-0.0627860014814108
-4-0.034070706379945
-3-0.0184107700058582
-20.0272343260534759
-10.0185894964847585
0-0.0228409109727632
10.0149298590596553
2-0.0143821160567725
3-0.0741247719362865
4-0.214451052769865
5-0.117155484444791
6-0.0416347587990799
70.135798913402219
80.0381869659064212
90.0160749296372065
10-0.0768351793406874
11-0.0699724340833246
12-0.0557585910416239
130.0930583076420755
140.062465459426861
15-0.0233958696409431
160.0238342675620139


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')