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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 computationWed, 28 Nov 2007 07:14:20 -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/28/t1196258645qmbk9mlbv6uq957.htm/, Retrieved Thu, 02 May 2024 05:20:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7057, Retrieved Thu, 02 May 2024 05:20:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgroep MENS
Estimated Impact181

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] [voeding en energi...] [2007-11-27 10:55:03] [75d515ccfbd49ab2c9a93737926697f5]
-   PD    [Cross Correlation Function] [transport en text...] [2007-11-28 14:14:20] [82643448f9a1604e63bdcbbe838c35e0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.9
99.9
99.9
99.9
99.9
99.7
99.6
99.5
100.6
100.2
100.1
100.2
99.1
99.5
99.5
99.6
99.5
99.6
99.8
99.9
100.5
100.5
100.5
100.5
99.5
99.9
100.4
99.6
99.5
99.6
98.4
99.9
100.3
100.3
101.3
101
99.7
99.4
99.9
100.7
99.8
98.8
99.6
99.1
100.3
100.5
100.8
100.6
99.1
98.8
99
99.9
99.5
99.2
99.6
100.1
99.8
101.6
101.7
101.9
100
102
102
102.9
102.7
102.7
102.7
102.7
102.6
102.6
102.5
102.5
102.1
Dataseries Y:
Download CSV
Histogram 
99.7
99.8
99.8
99.9
99.9
99.9
100
99.9
99.6
99.6
98.9
99.3
99.4
100.1
99.5
99.8
100
99.8
99.7
99.6
100.3
100.2
100.4
100.4
99.6
99.9
100.5
100.3
100.5
99.7
98.8
99.8
99.8
99.7
99.5
99.6
99.6
100.3
99
99.2
99.5
98.1
100.2
100.3
100
97.3
96.9
96.9
96.9
96.6
96.9
97
97.3
97.6
96.5
97
96.7
96.5
99.3
99.2
97
101.2
101.3
101
100.5
100.5
100.5
101.5
101.2
101
101.1
100.7
101

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=7057&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=7057&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7057&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 series0
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])
-15-0.0235532523144783
-14-0.0247222163494053
-13-0.152345378728987
-12-0.030083762158706
-110.144526047798267
-10-0.0908332192951045
-9-0.0137294463647992
-80.130341502419795
-7-0.130488282585172
-60.0075418708009197
-50.0577937285776496
-40.258160640023227
-3-0.0854177378126013
-2-0.0462524784138235
-1-0.207602341754978
00.396457788408498
1-0.230477507272544
20.092879018163182
30.155766492540908
4-0.0203567363058851
5-0.0162607557372454
6-0.036009172783696
70.0288521862311728
80.0311546044133706
9-0.0412511298781210
10-0.107825371383536
110.0302210610946353
12-0.0804162103857783
130.0148584282340234
14-0.0274206100295488
150.137345715954360

\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) & 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
-15 & -0.0235532523144783 \tabularnewline
-14 & -0.0247222163494053 \tabularnewline
-13 & -0.152345378728987 \tabularnewline
-12 & -0.030083762158706 \tabularnewline
-11 & 0.144526047798267 \tabularnewline
-10 & -0.0908332192951045 \tabularnewline
-9 & -0.0137294463647992 \tabularnewline
-8 & 0.130341502419795 \tabularnewline
-7 & -0.130488282585172 \tabularnewline
-6 & 0.0075418708009197 \tabularnewline
-5 & 0.0577937285776496 \tabularnewline
-4 & 0.258160640023227 \tabularnewline
-3 & -0.0854177378126013 \tabularnewline
-2 & -0.0462524784138235 \tabularnewline
-1 & -0.207602341754978 \tabularnewline
0 & 0.396457788408498 \tabularnewline
1 & -0.230477507272544 \tabularnewline
2 & 0.092879018163182 \tabularnewline
3 & 0.155766492540908 \tabularnewline
4 & -0.0203567363058851 \tabularnewline
5 & -0.0162607557372454 \tabularnewline
6 & -0.036009172783696 \tabularnewline
7 & 0.0288521862311728 \tabularnewline
8 & 0.0311546044133706 \tabularnewline
9 & -0.0412511298781210 \tabularnewline
10 & -0.107825371383536 \tabularnewline
11 & 0.0302210610946353 \tabularnewline
12 & -0.0804162103857783 \tabularnewline
13 & 0.0148584282340234 \tabularnewline
14 & -0.0274206100295488 \tabularnewline
15 & 0.137345715954360 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7057&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]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]-15[/C][C]-0.0235532523144783[/C][/ROW]
[ROW][C]-14[/C][C]-0.0247222163494053[/C][/ROW]
[ROW][C]-13[/C][C]-0.152345378728987[/C][/ROW]
[ROW][C]-12[/C][C]-0.030083762158706[/C][/ROW]
[ROW][C]-11[/C][C]0.144526047798267[/C][/ROW]
[ROW][C]-10[/C][C]-0.0908332192951045[/C][/ROW]
[ROW][C]-9[/C][C]-0.0137294463647992[/C][/ROW]
[ROW][C]-8[/C][C]0.130341502419795[/C][/ROW]
[ROW][C]-7[/C][C]-0.130488282585172[/C][/ROW]
[ROW][C]-6[/C][C]0.0075418708009197[/C][/ROW]
[ROW][C]-5[/C][C]0.0577937285776496[/C][/ROW]
[ROW][C]-4[/C][C]0.258160640023227[/C][/ROW]
[ROW][C]-3[/C][C]-0.0854177378126013[/C][/ROW]
[ROW][C]-2[/C][C]-0.0462524784138235[/C][/ROW]
[ROW][C]-1[/C][C]-0.207602341754978[/C][/ROW]
[ROW][C]0[/C][C]0.396457788408498[/C][/ROW]
[ROW][C]1[/C][C]-0.230477507272544[/C][/ROW]
[ROW][C]2[/C][C]0.092879018163182[/C][/ROW]
[ROW][C]3[/C][C]0.155766492540908[/C][/ROW]
[ROW][C]4[/C][C]-0.0203567363058851[/C][/ROW]
[ROW][C]5[/C][C]-0.0162607557372454[/C][/ROW]
[ROW][C]6[/C][C]-0.036009172783696[/C][/ROW]
[ROW][C]7[/C][C]0.0288521862311728[/C][/ROW]
[ROW][C]8[/C][C]0.0311546044133706[/C][/ROW]
[ROW][C]9[/C][C]-0.0412511298781210[/C][/ROW]
[ROW][C]10[/C][C]-0.107825371383536[/C][/ROW]
[ROW][C]11[/C][C]0.0302210610946353[/C][/ROW]
[ROW][C]12[/C][C]-0.0804162103857783[/C][/ROW]
[ROW][C]13[/C][C]0.0148584282340234[/C][/ROW]
[ROW][C]14[/C][C]-0.0274206100295488[/C][/ROW]
[ROW][C]15[/C][C]0.137345715954360[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7057&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7057&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)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])
-15-0.0235532523144783
-14-0.0247222163494053
-13-0.152345378728987
-12-0.030083762158706
-110.144526047798267
-10-0.0908332192951045
-9-0.0137294463647992
-80.130341502419795
-7-0.130488282585172
-60.0075418708009197
-50.0577937285776496
-40.258160640023227
-3-0.0854177378126013
-2-0.0462524784138235
-1-0.207602341754978
00.396457788408498
1-0.230477507272544
20.092879018163182
30.155766492540908
4-0.0203567363058851
5-0.0162607557372454
6-0.036009172783696
70.0288521862311728
80.0311546044133706
9-0.0412511298781210
10-0.107825371383536
110.0302210610946353
12-0.0804162103857783
130.0148584282340234
14-0.0274206100295488
150.137345715954360


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; 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')