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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 computationTue, 14 Dec 2010 15:11:40 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t12923394086mv20ndto2amw9o.htm/, Retrieved Fri, 03 May 2024 01:12:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109721, Retrieved Fri, 03 May 2024 01:12:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

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] [appelen] [2009-12-17 16:17:08] [7773f496f69461f4a67891f0ef752622]
-   P   [Cross Correlation Function] [Appelen kruiscorr...] [2009-12-17 16:28:57] [7773f496f69461f4a67891f0ef752622]
- R  D      [Cross Correlation Function] [biefstuk 2 D=1] [2010-12-14 15:11:40] [6e52d1bada9435d33ddf990b22ee4b00] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10.92
10.98
11.15
11.19
11.33
11.38
11.4
11.45
11.56
11.61
11.82
11.77
11.85
11.82
11.92
11.86
11.87
11.94
11.86
11.92
11.83
11.91
11.93
11.99
11.96
12.12
11.85
12.01
12.1
12.21
12.31
12.31
12.39
12.35
12.41
12.51
12.27
12.51
12.44
12.47
12.51
12.58
12.5
12.52
12.59
12.51
12.67
12.64
12.54
12.66
12.67
12.62
12.72
12.85
12.85
12.82
Dataseries Y:
Download CSV
Histogram 
15.13
15.25
15.33
15.36
15.4
15.4
15.41
15.47
15.54
15.55
15.59
15.65
15.75
15.86
15.89
15.94
15.93
15.95
15.99
15.99
16.06
16.08
16.07
16.11
16.15
16.15
16.18
16.3
16.42
16.49
16.5
16.58
16.64
16.66
16.81
16.91
16.92
16.95
17.11
17.16
17.16
17.27
17.34
17.39
17.43
17.45
17.5
17.56
17.62
17.7
17.72
17.71
17.74
17.75
17.78
17.8

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'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109721&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109721&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109721&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'RServer@AstonUniversity' @ vre.aston.ac.uk






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 series1
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 series1
krho(Y[t],X[t+k])
-14-0.0454396126457156
-13-0.00270971572057371
-12-0.187974181642406
-110.0525557748121662
-100.121521447144329
-90.00306345651257879
-8-0.131329714559015
-70.0456869249310449
-60.0960812056829483
-5-0.099189071212708
-40.218607981095479
-30.0765841157963512
-2-0.184540905210904
-10.0174902617137854
00.0855294700668951
10.0421089363573642
2-0.0152759362365577
30.150608587723286
4-0.119197630469591
5-0.0427421476884982
60.00536353733331561
7-0.125666799196092
80.000497687261475228
9-0.0188516277921075
100.00220130904115583
110.0146465532689704
120.0933423943994016
13-0.250404071722294
14-0.0285358562277687

\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 & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & -0.0454396126457156 \tabularnewline
-13 & -0.00270971572057371 \tabularnewline
-12 & -0.187974181642406 \tabularnewline
-11 & 0.0525557748121662 \tabularnewline
-10 & 0.121521447144329 \tabularnewline
-9 & 0.00306345651257879 \tabularnewline
-8 & -0.131329714559015 \tabularnewline
-7 & 0.0456869249310449 \tabularnewline
-6 & 0.0960812056829483 \tabularnewline
-5 & -0.099189071212708 \tabularnewline
-4 & 0.218607981095479 \tabularnewline
-3 & 0.0765841157963512 \tabularnewline
-2 & -0.184540905210904 \tabularnewline
-1 & 0.0174902617137854 \tabularnewline
0 & 0.0855294700668951 \tabularnewline
1 & 0.0421089363573642 \tabularnewline
2 & -0.0152759362365577 \tabularnewline
3 & 0.150608587723286 \tabularnewline
4 & -0.119197630469591 \tabularnewline
5 & -0.0427421476884982 \tabularnewline
6 & 0.00536353733331561 \tabularnewline
7 & -0.125666799196092 \tabularnewline
8 & 0.000497687261475228 \tabularnewline
9 & -0.0188516277921075 \tabularnewline
10 & 0.00220130904115583 \tabularnewline
11 & 0.0146465532689704 \tabularnewline
12 & 0.0933423943994016 \tabularnewline
13 & -0.250404071722294 \tabularnewline
14 & -0.0285358562277687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109721&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]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]-0.0454396126457156[/C][/ROW]
[ROW][C]-13[/C][C]-0.00270971572057371[/C][/ROW]
[ROW][C]-12[/C][C]-0.187974181642406[/C][/ROW]
[ROW][C]-11[/C][C]0.0525557748121662[/C][/ROW]
[ROW][C]-10[/C][C]0.121521447144329[/C][/ROW]
[ROW][C]-9[/C][C]0.00306345651257879[/C][/ROW]
[ROW][C]-8[/C][C]-0.131329714559015[/C][/ROW]
[ROW][C]-7[/C][C]0.0456869249310449[/C][/ROW]
[ROW][C]-6[/C][C]0.0960812056829483[/C][/ROW]
[ROW][C]-5[/C][C]-0.099189071212708[/C][/ROW]
[ROW][C]-4[/C][C]0.218607981095479[/C][/ROW]
[ROW][C]-3[/C][C]0.0765841157963512[/C][/ROW]
[ROW][C]-2[/C][C]-0.184540905210904[/C][/ROW]
[ROW][C]-1[/C][C]0.0174902617137854[/C][/ROW]
[ROW][C]0[/C][C]0.0855294700668951[/C][/ROW]
[ROW][C]1[/C][C]0.0421089363573642[/C][/ROW]
[ROW][C]2[/C][C]-0.0152759362365577[/C][/ROW]
[ROW][C]3[/C][C]0.150608587723286[/C][/ROW]
[ROW][C]4[/C][C]-0.119197630469591[/C][/ROW]
[ROW][C]5[/C][C]-0.0427421476884982[/C][/ROW]
[ROW][C]6[/C][C]0.00536353733331561[/C][/ROW]
[ROW][C]7[/C][C]-0.125666799196092[/C][/ROW]
[ROW][C]8[/C][C]0.000497687261475228[/C][/ROW]
[ROW][C]9[/C][C]-0.0188516277921075[/C][/ROW]
[ROW][C]10[/C][C]0.00220130904115583[/C][/ROW]
[ROW][C]11[/C][C]0.0146465532689704[/C][/ROW]
[ROW][C]12[/C][C]0.0933423943994016[/C][/ROW]
[ROW][C]13[/C][C]-0.250404071722294[/C][/ROW]
[ROW][C]14[/C][C]-0.0285358562277687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109721&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109721&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 series1
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 series1
krho(Y[t],X[t+k])
-14-0.0454396126457156
-13-0.00270971572057371
-12-0.187974181642406
-110.0525557748121662
-100.121521447144329
-90.00306345651257879
-8-0.131329714559015
-70.0456869249310449
-60.0960812056829483
-5-0.099189071212708
-40.218607981095479
-30.0765841157963512
-2-0.184540905210904
-10.0174902617137854
00.0855294700668951
10.0421089363573642
2-0.0152759362365577
30.150608587723286
4-0.119197630469591
5-0.0427421476884982
60.00536353733331561
7-0.125666799196092
80.000497687261475228
9-0.0188516277921075
100.00220130904115583
110.0146465532689704
120.0933423943994016
13-0.250404071722294
14-0.0285358562277687


Figures (Output of Computation)

Input Parameters & R Code

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