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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 07:08:21 -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/t1196258293g9uu1luomnqxlnh.htm/, Retrieved Thu, 02 May 2024 02:33:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7054, Retrieved Thu, 02 May 2024 02:33:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsgroep MENS
Estimated Impact194

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] [voeding en textie...] [2007-11-28 14:08:21] [82643448f9a1604e63bdcbbe838c35e0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100
100
100
100.1
100
100
99.8
100
99.9
99.2
98.7
98.7
98.9
99.2
99.8
100.5
100.1
100.5
98.4
98.6
99
99.1
98.9
98.5
96.9
96.8
97
97
96.9
97.1
97.2
97.9
98.9
99.2
99.5
99.3
99.9
100
100.3
100.5
100.7
100.9
100.8
100.9
101
100.3
100.1
99.8
99.9
99.9
100.2
99.7
100.4
100.9
101.3
101.4
101.3
100.9
100.9
100.9
101.1
101.1
101.3
101.8
102.9
103.2
103.3
104.5
105
104.9
104.9
105.4
106
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=7054&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=7054&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7054&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])
-15-0.0169219212237035
-14-0.00108397173959903
-13-0.190515417238248
-12-0.00296393907544365
-110.0839022185663806
-10-0.102241868495826
-90.0614253113774145
-80.0279838971303362
-7-0.164012751245268
-60.160017266856324
-50.0567128402315523
-4-0.100150718654855
-30.095495104337301
-2-0.136946685771828
-1-0.00544422591012615
00.113613234156474
10.102560119054252
20.0577473391465246
3-0.0287422343078356
4-0.0226807056904167
5-0.0445794453915703
60.299871773275655
7-0.096564308069548
8-0.0851862968055926
90.00235032836999014
100.160073385284256
110.0234449500708574
120.0158564094932925
130.0493687101756598
140.019734488223792
15-0.0286093222416698

\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 & -0.0169219212237035 \tabularnewline
-14 & -0.00108397173959903 \tabularnewline
-13 & -0.190515417238248 \tabularnewline
-12 & -0.00296393907544365 \tabularnewline
-11 & 0.0839022185663806 \tabularnewline
-10 & -0.102241868495826 \tabularnewline
-9 & 0.0614253113774145 \tabularnewline
-8 & 0.0279838971303362 \tabularnewline
-7 & -0.164012751245268 \tabularnewline
-6 & 0.160017266856324 \tabularnewline
-5 & 0.0567128402315523 \tabularnewline
-4 & -0.100150718654855 \tabularnewline
-3 & 0.095495104337301 \tabularnewline
-2 & -0.136946685771828 \tabularnewline
-1 & -0.00544422591012615 \tabularnewline
0 & 0.113613234156474 \tabularnewline
1 & 0.102560119054252 \tabularnewline
2 & 0.0577473391465246 \tabularnewline
3 & -0.0287422343078356 \tabularnewline
4 & -0.0226807056904167 \tabularnewline
5 & -0.0445794453915703 \tabularnewline
6 & 0.299871773275655 \tabularnewline
7 & -0.096564308069548 \tabularnewline
8 & -0.0851862968055926 \tabularnewline
9 & 0.00235032836999014 \tabularnewline
10 & 0.160073385284256 \tabularnewline
11 & 0.0234449500708574 \tabularnewline
12 & 0.0158564094932925 \tabularnewline
13 & 0.0493687101756598 \tabularnewline
14 & 0.019734488223792 \tabularnewline
15 & -0.0286093222416698 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7054&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]-0.0169219212237035[/C][/ROW]
[ROW][C]-14[/C][C]-0.00108397173959903[/C][/ROW]
[ROW][C]-13[/C][C]-0.190515417238248[/C][/ROW]
[ROW][C]-12[/C][C]-0.00296393907544365[/C][/ROW]
[ROW][C]-11[/C][C]0.0839022185663806[/C][/ROW]
[ROW][C]-10[/C][C]-0.102241868495826[/C][/ROW]
[ROW][C]-9[/C][C]0.0614253113774145[/C][/ROW]
[ROW][C]-8[/C][C]0.0279838971303362[/C][/ROW]
[ROW][C]-7[/C][C]-0.164012751245268[/C][/ROW]
[ROW][C]-6[/C][C]0.160017266856324[/C][/ROW]
[ROW][C]-5[/C][C]0.0567128402315523[/C][/ROW]
[ROW][C]-4[/C][C]-0.100150718654855[/C][/ROW]
[ROW][C]-3[/C][C]0.095495104337301[/C][/ROW]
[ROW][C]-2[/C][C]-0.136946685771828[/C][/ROW]
[ROW][C]-1[/C][C]-0.00544422591012615[/C][/ROW]
[ROW][C]0[/C][C]0.113613234156474[/C][/ROW]
[ROW][C]1[/C][C]0.102560119054252[/C][/ROW]
[ROW][C]2[/C][C]0.0577473391465246[/C][/ROW]
[ROW][C]3[/C][C]-0.0287422343078356[/C][/ROW]
[ROW][C]4[/C][C]-0.0226807056904167[/C][/ROW]
[ROW][C]5[/C][C]-0.0445794453915703[/C][/ROW]
[ROW][C]6[/C][C]0.299871773275655[/C][/ROW]
[ROW][C]7[/C][C]-0.096564308069548[/C][/ROW]
[ROW][C]8[/C][C]-0.0851862968055926[/C][/ROW]
[ROW][C]9[/C][C]0.00235032836999014[/C][/ROW]
[ROW][C]10[/C][C]0.160073385284256[/C][/ROW]
[ROW][C]11[/C][C]0.0234449500708574[/C][/ROW]
[ROW][C]12[/C][C]0.0158564094932925[/C][/ROW]
[ROW][C]13[/C][C]0.0493687101756598[/C][/ROW]
[ROW][C]14[/C][C]0.019734488223792[/C][/ROW]
[ROW][C]15[/C][C]-0.0286093222416698[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7054&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7054&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])
-15-0.0169219212237035
-14-0.00108397173959903
-13-0.190515417238248
-12-0.00296393907544365
-110.0839022185663806
-10-0.102241868495826
-90.0614253113774145
-80.0279838971303362
-7-0.164012751245268
-60.160017266856324
-50.0567128402315523
-4-0.100150718654855
-30.095495104337301
-2-0.136946685771828
-1-0.00544422591012615
00.113613234156474
10.102560119054252
20.0577473391465246
3-0.0287422343078356
4-0.0226807056904167
5-0.0445794453915703
60.299871773275655
7-0.096564308069548
8-0.0851862968055926
90.00235032836999014
100.160073385284256
110.0234449500708574
120.0158564094932925
130.0493687101756598
140.019734488223792
15-0.0286093222416698


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')