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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationThu, 29 Nov 2007 11:12:41 -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/2007/Nov/29/t119635938214a86vk1vgbhlbj.htm/, Retrieved Fri, 03 May 2024 10:33:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7561, Retrieved Fri, 03 May 2024 10:33:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordss0650062 s0650550
Estimated Impact183

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] [inducing stationa...] [2007-11-29 12:22:08] [b0cf4683dcfcadeba529c2088f15e82b]
-   PD  [Cross Correlation Function] [inducing stationa...] [2007-11-29 13:19:42] [74be16979710d4c4e7c6647856088456]
-   PD      [Cross Correlation Function] [inducing stationa...] [2007-11-29 18:12:41] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8.0
8.1
8.3
8.2
8.1
7.7
7.6
7.7
8.2
8.4
8.4
8.6
8.4
8.5
8.7
8.7
8.6
7.4
7.3
7.4
9.0
9.2
9.2
8.5
8.3
8.3
8.6
8.6
8.5
8.1
8.1
8.0
8.6
8.7
8.7
8.6
8.4
8.4
8.7
8.7
8.5
8.3
8.3
8.3
8.1
8.2
8.1
8.1
7.9
7.7
8.1
8.0
7.7
7.8
7.6
7.4
7.7
7.8
7.5
7.2
Dataseries Y:
Download CSV
Histogram 
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
1.0
1.7
2.4
2.0
2.1
2.0
1.8
2.7
2.3
1.9
2.0
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3.0
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
2.0
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2

Tables (Output of Computation)





Summary of compuational 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 compuational 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=7561&T=0

[TABLE]
[ROW][C]Summary of compuational 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=7561&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7561&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 compuational 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 series1
Seasonal Period (s)12
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])
-13-0.0663053663252781
-12-0.313289390296339
-110.00438681426080966
-100.218886702335363
-90.185046401990060
-80.0192107405315391
-7-0.293788200266843
-6-0.0357839649149642
-5-0.000851545119010192
-40.131465804200277
-30.00930685272620251
-2-0.163940405138518
-10.137326869700716
00.247340484718553
1-0.00931932151778138
2-0.268323260570962
3-0.055363634985575
4-0.187715456846286
50.254348679044258
60.0185792329109816
70.188586071881829
80.00890345064570686
9-0.201666567706488
100.0235997551673339
11-0.022570713132905
12-0.0391637408911908
130.0744460203096839

\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 & 1 \tabularnewline
Seasonal Period (s) & 12 \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
-13 & -0.0663053663252781 \tabularnewline
-12 & -0.313289390296339 \tabularnewline
-11 & 0.00438681426080966 \tabularnewline
-10 & 0.218886702335363 \tabularnewline
-9 & 0.185046401990060 \tabularnewline
-8 & 0.0192107405315391 \tabularnewline
-7 & -0.293788200266843 \tabularnewline
-6 & -0.0357839649149642 \tabularnewline
-5 & -0.000851545119010192 \tabularnewline
-4 & 0.131465804200277 \tabularnewline
-3 & 0.00930685272620251 \tabularnewline
-2 & -0.163940405138518 \tabularnewline
-1 & 0.137326869700716 \tabularnewline
0 & 0.247340484718553 \tabularnewline
1 & -0.00931932151778138 \tabularnewline
2 & -0.268323260570962 \tabularnewline
3 & -0.055363634985575 \tabularnewline
4 & -0.187715456846286 \tabularnewline
5 & 0.254348679044258 \tabularnewline
6 & 0.0185792329109816 \tabularnewline
7 & 0.188586071881829 \tabularnewline
8 & 0.00890345064570686 \tabularnewline
9 & -0.201666567706488 \tabularnewline
10 & 0.0235997551673339 \tabularnewline
11 & -0.022570713132905 \tabularnewline
12 & -0.0391637408911908 \tabularnewline
13 & 0.0744460203096839 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7561&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]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/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]-13[/C][C]-0.0663053663252781[/C][/ROW]
[ROW][C]-12[/C][C]-0.313289390296339[/C][/ROW]
[ROW][C]-11[/C][C]0.00438681426080966[/C][/ROW]
[ROW][C]-10[/C][C]0.218886702335363[/C][/ROW]
[ROW][C]-9[/C][C]0.185046401990060[/C][/ROW]
[ROW][C]-8[/C][C]0.0192107405315391[/C][/ROW]
[ROW][C]-7[/C][C]-0.293788200266843[/C][/ROW]
[ROW][C]-6[/C][C]-0.0357839649149642[/C][/ROW]
[ROW][C]-5[/C][C]-0.000851545119010192[/C][/ROW]
[ROW][C]-4[/C][C]0.131465804200277[/C][/ROW]
[ROW][C]-3[/C][C]0.00930685272620251[/C][/ROW]
[ROW][C]-2[/C][C]-0.163940405138518[/C][/ROW]
[ROW][C]-1[/C][C]0.137326869700716[/C][/ROW]
[ROW][C]0[/C][C]0.247340484718553[/C][/ROW]
[ROW][C]1[/C][C]-0.00931932151778138[/C][/ROW]
[ROW][C]2[/C][C]-0.268323260570962[/C][/ROW]
[ROW][C]3[/C][C]-0.055363634985575[/C][/ROW]
[ROW][C]4[/C][C]-0.187715456846286[/C][/ROW]
[ROW][C]5[/C][C]0.254348679044258[/C][/ROW]
[ROW][C]6[/C][C]0.0185792329109816[/C][/ROW]
[ROW][C]7[/C][C]0.188586071881829[/C][/ROW]
[ROW][C]8[/C][C]0.00890345064570686[/C][/ROW]
[ROW][C]9[/C][C]-0.201666567706488[/C][/ROW]
[ROW][C]10[/C][C]0.0235997551673339[/C][/ROW]
[ROW][C]11[/C][C]-0.022570713132905[/C][/ROW]
[ROW][C]12[/C][C]-0.0391637408911908[/C][/ROW]
[ROW][C]13[/C][C]0.0744460203096839[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7561&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7561&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 series1
Seasonal Period (s)12
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])
-13-0.0663053663252781
-12-0.313289390296339
-110.00438681426080966
-100.218886702335363
-90.185046401990060
-80.0192107405315391
-7-0.293788200266843
-6-0.0357839649149642
-5-0.000851545119010192
-40.131465804200277
-30.00930685272620251
-2-0.163940405138518
-10.137326869700716
00.247340484718553
1-0.00931932151778138
2-0.268323260570962
3-0.055363634985575
4-0.187715456846286
50.254348679044258
60.0185792329109816
70.188586071881829
80.00890345064570686
9-0.201666567706488
100.0235997551673339
11-0.022570713132905
12-0.0391637408911908
130.0744460203096839


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')