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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 computationThu, 02 Dec 2010 12:18:28 +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/02/t1291292201ydj027nlzkgwtvo.htm/, Retrieved Sun, 05 May 2024 12:30:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104230, Retrieved Sun, 05 May 2024 12:30:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

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]
-    D      [Cross Correlation Function] [Seizoenale differ...] [2010-12-02 12:18:28] [2fa539864aa87c5da4977c85c6885fac] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.25 
1.23 
1.2 
1.15 
1.13 
1.17 
1.22 
1.21 
1.15 
1.24 
1.16 
1.3 
1.3 
1.26 
1.29 
1.29 
1.35 
1.35 
1.45 
1.43 
1.43 
1.41 
1.46 
1.78 
1.79 
1.66 
1.56 
1.53 
1.47 
1.47 
1.45 
1.41 
1.45 
1.46 
1.38 
1.45 
1.48 
1.48 
1.51 
1.45 
1.42 
1.43 
1.43 
1.44 
1.41 
1.35 
1.43 
1.72 
1.63 
1.57 
1.47 
1.39 
1.34 
1.28 
1.26 
1.26
Dataseries Y:
Download CSV
Histogram 
1.89 
1.84 
1.83 
1.8 
1.77 
1.75 
1.73 
1.71 
1.73 
1.75 
1.78 
1.99 
1.98 
1.94 
1.95 
1.91 
1.90 
1.86 
1.90 
1.88 
1.87 
1.89 
1.97 
2.14 
2.15 
2.06 
1.95 
1.94 
1.92 
1.89 
1.87 
1.87 
1.88 
1.92 
1.94 
2.14 
2.10 
2.02 
1.96 
1.93 
1.87 
1.85 
1.87 
1.88 
1.90 
1.90 
2.00 
2.21 
2.07 
1.96 
1.92 
1.82 
1.75 
1.70 
1.70 
1.73

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104230&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104230&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104230&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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])
-14-0.0524298209454563
-13-0.05721579448537
-120.365317448483023
-110.140135634732776
-10-0.05263928495485
-90.0213533234794488
-8-0.107858905333608
-7-0.0857694564516155
-6-0.0582817546176369
-5-0.0101393639137192
-4-0.0799997708394332
-3-0.111985525347724
-2-0.172097799528596
-1-0.034021209698615
00.756687944099187
10.277768443096903
20.0168236774402208
3-0.0429492840014528
4-0.115754508470991
5-0.000860392637879995
6-0.136098845186238
7-0.0793633751588077
8-0.0741082401498913
9-0.0305382518390549
10-0.154615295118659
110.0514757013249919
120.487606412619597
130.118128960466863
140.0353555028102350

\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 & -0.0524298209454563 \tabularnewline
-13 & -0.05721579448537 \tabularnewline
-12 & 0.365317448483023 \tabularnewline
-11 & 0.140135634732776 \tabularnewline
-10 & -0.05263928495485 \tabularnewline
-9 & 0.0213533234794488 \tabularnewline
-8 & -0.107858905333608 \tabularnewline
-7 & -0.0857694564516155 \tabularnewline
-6 & -0.0582817546176369 \tabularnewline
-5 & -0.0101393639137192 \tabularnewline
-4 & -0.0799997708394332 \tabularnewline
-3 & -0.111985525347724 \tabularnewline
-2 & -0.172097799528596 \tabularnewline
-1 & -0.034021209698615 \tabularnewline
0 & 0.756687944099187 \tabularnewline
1 & 0.277768443096903 \tabularnewline
2 & 0.0168236774402208 \tabularnewline
3 & -0.0429492840014528 \tabularnewline
4 & -0.115754508470991 \tabularnewline
5 & -0.000860392637879995 \tabularnewline
6 & -0.136098845186238 \tabularnewline
7 & -0.0793633751588077 \tabularnewline
8 & -0.0741082401498913 \tabularnewline
9 & -0.0305382518390549 \tabularnewline
10 & -0.154615295118659 \tabularnewline
11 & 0.0514757013249919 \tabularnewline
12 & 0.487606412619597 \tabularnewline
13 & 0.118128960466863 \tabularnewline
14 & 0.0353555028102350 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104230&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]-0.0524298209454563[/C][/ROW]
[ROW][C]-13[/C][C]-0.05721579448537[/C][/ROW]
[ROW][C]-12[/C][C]0.365317448483023[/C][/ROW]
[ROW][C]-11[/C][C]0.140135634732776[/C][/ROW]
[ROW][C]-10[/C][C]-0.05263928495485[/C][/ROW]
[ROW][C]-9[/C][C]0.0213533234794488[/C][/ROW]
[ROW][C]-8[/C][C]-0.107858905333608[/C][/ROW]
[ROW][C]-7[/C][C]-0.0857694564516155[/C][/ROW]
[ROW][C]-6[/C][C]-0.0582817546176369[/C][/ROW]
[ROW][C]-5[/C][C]-0.0101393639137192[/C][/ROW]
[ROW][C]-4[/C][C]-0.0799997708394332[/C][/ROW]
[ROW][C]-3[/C][C]-0.111985525347724[/C][/ROW]
[ROW][C]-2[/C][C]-0.172097799528596[/C][/ROW]
[ROW][C]-1[/C][C]-0.034021209698615[/C][/ROW]
[ROW][C]0[/C][C]0.756687944099187[/C][/ROW]
[ROW][C]1[/C][C]0.277768443096903[/C][/ROW]
[ROW][C]2[/C][C]0.0168236774402208[/C][/ROW]
[ROW][C]3[/C][C]-0.0429492840014528[/C][/ROW]
[ROW][C]4[/C][C]-0.115754508470991[/C][/ROW]
[ROW][C]5[/C][C]-0.000860392637879995[/C][/ROW]
[ROW][C]6[/C][C]-0.136098845186238[/C][/ROW]
[ROW][C]7[/C][C]-0.0793633751588077[/C][/ROW]
[ROW][C]8[/C][C]-0.0741082401498913[/C][/ROW]
[ROW][C]9[/C][C]-0.0305382518390549[/C][/ROW]
[ROW][C]10[/C][C]-0.154615295118659[/C][/ROW]
[ROW][C]11[/C][C]0.0514757013249919[/C][/ROW]
[ROW][C]12[/C][C]0.487606412619597[/C][/ROW]
[ROW][C]13[/C][C]0.118128960466863[/C][/ROW]
[ROW][C]14[/C][C]0.0353555028102350[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104230&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104230&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])
-14-0.0524298209454563
-13-0.05721579448537
-120.365317448483023
-110.140135634732776
-10-0.05263928495485
-90.0213533234794488
-8-0.107858905333608
-7-0.0857694564516155
-6-0.0582817546176369
-5-0.0101393639137192
-4-0.0799997708394332
-3-0.111985525347724
-2-0.172097799528596
-1-0.034021209698615
00.756687944099187
10.277768443096903
20.0168236774402208
3-0.0429492840014528
4-0.115754508470991
5-0.000860392637879995
6-0.136098845186238
7-0.0793633751588077
8-0.0741082401498913
9-0.0305382518390549
10-0.154615295118659
110.0514757013249919
120.487606412619597
130.118128960466863
140.0353555028102350


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')