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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 computationSun, 21 Dec 2008 10:36:39 -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/Dec/21/t12298810619gzbwj0r7xbrnw7.htm/, Retrieved Fri, 17 May 2024 03:19:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35705, Retrieved Fri, 17 May 2024 03:19:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

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] [] [2008-12-21 17:36:39] [a2d5a6282476ec2b5afae6fb53d308f8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
87,0
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
110,3
109,8
117,3
118,8
131,3
125,9
133,1
147,0
145,8
164,4
149,8
137,7
151,7
156,8
180,0
180,4
170,4
191,6
199,5
218,2
217,5
205,0
194,0
199,3
219,3
211,1
215,2
240,2
242,2
240,7
255,4
253,0
218,2
203,7
205,6
215,6
188,5
202,9
214,0
230,3
230,0
241,0
259,6
247,8
270,3
289,7
Dataseries Y:
Download CSV
Histogram 
106,7
101,1
97,8
113,8
107,1
117,5
113,7
106,6
109,8
108,8
102,0
114,5
116,5
108,6
113,9
109,3
112,5
123,4
115,2
110,8
120,4
117,6
111,2
131,1
118,9
115,7
119,6
113,1
106,4
115,5
111,8
109,6
121,5
109,5
109,0
113,4
112,7
114,4
109,2
116,2
113,8
123,6
112,6
117,7
113,3
110,7
114,7
116,9
120,6
111,6
111,9
116,1
111,9
125,1
115,1
116,7
115,8
116,8
113,0
106,5

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35705&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35705&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35705&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'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.124397661854944
-13-0.0618983236660903
-12-0.0527643995521543
-110.028916619683026
-100.109290093354189
-9-0.101596986158044
-8-0.286115110278497
-70.0189639736450329
-60.0379031170731859
-50.0973486479379197
-40.140749449299455
-3-0.0258090772900421
-2-0.16261192716132
-10.0149599514564018
0-0.0600575602608532
10.0143900368778686
20.218791971075371
30.0308990463928186
40.0930694915537627
50.035040801727661
6-0.190675404438580
70.162171016926939
80.048050651073734
90.00367373596962881
100.0083940985260694
110.0720369200707482
12-0.18370763218031
13-0.0318423537201642
140.146054262094497

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0 \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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & -0.124397661854944 \tabularnewline
-13 & -0.0618983236660903 \tabularnewline
-12 & -0.0527643995521543 \tabularnewline
-11 & 0.028916619683026 \tabularnewline
-10 & 0.109290093354189 \tabularnewline
-9 & -0.101596986158044 \tabularnewline
-8 & -0.286115110278497 \tabularnewline
-7 & 0.0189639736450329 \tabularnewline
-6 & 0.0379031170731859 \tabularnewline
-5 & 0.0973486479379197 \tabularnewline
-4 & 0.140749449299455 \tabularnewline
-3 & -0.0258090772900421 \tabularnewline
-2 & -0.16261192716132 \tabularnewline
-1 & 0.0149599514564018 \tabularnewline
0 & -0.0600575602608532 \tabularnewline
1 & 0.0143900368778686 \tabularnewline
2 & 0.218791971075371 \tabularnewline
3 & 0.0308990463928186 \tabularnewline
4 & 0.0930694915537627 \tabularnewline
5 & 0.035040801727661 \tabularnewline
6 & -0.190675404438580 \tabularnewline
7 & 0.162171016926939 \tabularnewline
8 & 0.048050651073734 \tabularnewline
9 & 0.00367373596962881 \tabularnewline
10 & 0.0083940985260694 \tabularnewline
11 & 0.0720369200707482 \tabularnewline
12 & -0.18370763218031 \tabularnewline
13 & -0.0318423537201642 \tabularnewline
14 & 0.146054262094497 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35705&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]0[/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]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]-0.124397661854944[/C][/ROW]
[ROW][C]-13[/C][C]-0.0618983236660903[/C][/ROW]
[ROW][C]-12[/C][C]-0.0527643995521543[/C][/ROW]
[ROW][C]-11[/C][C]0.028916619683026[/C][/ROW]
[ROW][C]-10[/C][C]0.109290093354189[/C][/ROW]
[ROW][C]-9[/C][C]-0.101596986158044[/C][/ROW]
[ROW][C]-8[/C][C]-0.286115110278497[/C][/ROW]
[ROW][C]-7[/C][C]0.0189639736450329[/C][/ROW]
[ROW][C]-6[/C][C]0.0379031170731859[/C][/ROW]
[ROW][C]-5[/C][C]0.0973486479379197[/C][/ROW]
[ROW][C]-4[/C][C]0.140749449299455[/C][/ROW]
[ROW][C]-3[/C][C]-0.0258090772900421[/C][/ROW]
[ROW][C]-2[/C][C]-0.16261192716132[/C][/ROW]
[ROW][C]-1[/C][C]0.0149599514564018[/C][/ROW]
[ROW][C]0[/C][C]-0.0600575602608532[/C][/ROW]
[ROW][C]1[/C][C]0.0143900368778686[/C][/ROW]
[ROW][C]2[/C][C]0.218791971075371[/C][/ROW]
[ROW][C]3[/C][C]0.0308990463928186[/C][/ROW]
[ROW][C]4[/C][C]0.0930694915537627[/C][/ROW]
[ROW][C]5[/C][C]0.035040801727661[/C][/ROW]
[ROW][C]6[/C][C]-0.190675404438580[/C][/ROW]
[ROW][C]7[/C][C]0.162171016926939[/C][/ROW]
[ROW][C]8[/C][C]0.048050651073734[/C][/ROW]
[ROW][C]9[/C][C]0.00367373596962881[/C][/ROW]
[ROW][C]10[/C][C]0.0083940985260694[/C][/ROW]
[ROW][C]11[/C][C]0.0720369200707482[/C][/ROW]
[ROW][C]12[/C][C]-0.18370763218031[/C][/ROW]
[ROW][C]13[/C][C]-0.0318423537201642[/C][/ROW]
[ROW][C]14[/C][C]0.146054262094497[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35705&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35705&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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.124397661854944
-13-0.0618983236660903
-12-0.0527643995521543
-110.028916619683026
-100.109290093354189
-9-0.101596986158044
-8-0.286115110278497
-70.0189639736450329
-60.0379031170731859
-50.0973486479379197
-40.140749449299455
-3-0.0258090772900421
-2-0.16261192716132
-10.0149599514564018
0-0.0600575602608532
10.0143900368778686
20.218791971075371
30.0308990463928186
40.0930694915537627
50.035040801727661
6-0.190675404438580
70.162171016926939
80.048050651073734
90.00367373596962881
100.0083940985260694
110.0720369200707482
12-0.18370763218031
13-0.0318423537201642
140.146054262094497


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.0 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 0.0 ; par2 = 1 ; 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')