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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 computationMon, 26 Nov 2007 13:06:54 -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/26/t1196107120t0b54rgag0345u1.htm/, Retrieved Fri, 03 May 2024 01:26:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6666, Retrieved Fri, 03 May 2024 01:26:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

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] [vraag vijf tussen...] [2007-11-26 20:06:54] [e1de87d26bd88c28cdef9ffadea7aeba] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6,1
5,8
6,2
5,8
5,9
6,7
5,9
3,8
1,7
1,4
1,8
3
3,6
4,8
4,3
4,2
2,9
4,9
7,2
8,7
9,1
8,9
9
11,6
9,6
9,1
9,2
10,8
11
8,5
6,5
7,2
7,8
8,7
7,8
7,5
7,7
7,5
8,3
7,9
10,4
11,5
14
11,9
11,9
10,3
11,3
9,9
8,9
9,2
8,8
6,7
7,1
6,6
7,2
5,1
5,3
6,4
8,1
8
Dataseries Y:
Download CSV
Histogram 
12102.8
12989
11610.2
10205.5
11356.2
11307.1
12648.6
11947.2
11714.1
12192.5
11268.8
9097.4
12639.8
13040.1
11687.3
11191.7
11391.9
11793.1
13933.2
12778.1
11810.3
13698.4
11956.6
10723.8
13938.9
13979.8
13807.4
12973.9
12509.8
12934.1
14908.3
13772.1
13012.6
14049.9
11816.5
11593.2
14466.2
13615.9
14733.9
13880.7
13527.5
13584
16170.2
13260.6
14741.9
15486.5
13154.5
12621.2
15031.6
15452.4
15428
13105.9
14716.8
14180
16202.2
15035.9
15914.8
16468
14729.9
13705.2

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=6666&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=6666&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6666&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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-140.351610942974732
-130.387668524202071
-120.394198528056613
-110.394572331653816
-100.411350721951093
-90.395052960378586
-80.458170688221488
-70.477564386552626
-60.437785035788809
-50.400434068550828
-40.426853322796642
-30.447419314004566
-20.439450350247123
-10.394879246266561
00.404171974754718
10.385379025021206
20.393304172568342
30.326032145022905
40.359285612070421
50.334217393328596
60.258276543016064
70.178134929520766
80.134242071667206
90.0949619843321428
100.0648981531241143
110.00270653503177192
12-0.050574683935992
13-0.0648775005256542
14-0.059151909865994

\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 & 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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.351610942974732 \tabularnewline
-13 & 0.387668524202071 \tabularnewline
-12 & 0.394198528056613 \tabularnewline
-11 & 0.394572331653816 \tabularnewline
-10 & 0.411350721951093 \tabularnewline
-9 & 0.395052960378586 \tabularnewline
-8 & 0.458170688221488 \tabularnewline
-7 & 0.477564386552626 \tabularnewline
-6 & 0.437785035788809 \tabularnewline
-5 & 0.400434068550828 \tabularnewline
-4 & 0.426853322796642 \tabularnewline
-3 & 0.447419314004566 \tabularnewline
-2 & 0.439450350247123 \tabularnewline
-1 & 0.394879246266561 \tabularnewline
0 & 0.404171974754718 \tabularnewline
1 & 0.385379025021206 \tabularnewline
2 & 0.393304172568342 \tabularnewline
3 & 0.326032145022905 \tabularnewline
4 & 0.359285612070421 \tabularnewline
5 & 0.334217393328596 \tabularnewline
6 & 0.258276543016064 \tabularnewline
7 & 0.178134929520766 \tabularnewline
8 & 0.134242071667206 \tabularnewline
9 & 0.0949619843321428 \tabularnewline
10 & 0.0648981531241143 \tabularnewline
11 & 0.00270653503177192 \tabularnewline
12 & -0.050574683935992 \tabularnewline
13 & -0.0648775005256542 \tabularnewline
14 & -0.059151909865994 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6666&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]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]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]0.351610942974732[/C][/ROW]
[ROW][C]-13[/C][C]0.387668524202071[/C][/ROW]
[ROW][C]-12[/C][C]0.394198528056613[/C][/ROW]
[ROW][C]-11[/C][C]0.394572331653816[/C][/ROW]
[ROW][C]-10[/C][C]0.411350721951093[/C][/ROW]
[ROW][C]-9[/C][C]0.395052960378586[/C][/ROW]
[ROW][C]-8[/C][C]0.458170688221488[/C][/ROW]
[ROW][C]-7[/C][C]0.477564386552626[/C][/ROW]
[ROW][C]-6[/C][C]0.437785035788809[/C][/ROW]
[ROW][C]-5[/C][C]0.400434068550828[/C][/ROW]
[ROW][C]-4[/C][C]0.426853322796642[/C][/ROW]
[ROW][C]-3[/C][C]0.447419314004566[/C][/ROW]
[ROW][C]-2[/C][C]0.439450350247123[/C][/ROW]
[ROW][C]-1[/C][C]0.394879246266561[/C][/ROW]
[ROW][C]0[/C][C]0.404171974754718[/C][/ROW]
[ROW][C]1[/C][C]0.385379025021206[/C][/ROW]
[ROW][C]2[/C][C]0.393304172568342[/C][/ROW]
[ROW][C]3[/C][C]0.326032145022905[/C][/ROW]
[ROW][C]4[/C][C]0.359285612070421[/C][/ROW]
[ROW][C]5[/C][C]0.334217393328596[/C][/ROW]
[ROW][C]6[/C][C]0.258276543016064[/C][/ROW]
[ROW][C]7[/C][C]0.178134929520766[/C][/ROW]
[ROW][C]8[/C][C]0.134242071667206[/C][/ROW]
[ROW][C]9[/C][C]0.0949619843321428[/C][/ROW]
[ROW][C]10[/C][C]0.0648981531241143[/C][/ROW]
[ROW][C]11[/C][C]0.00270653503177192[/C][/ROW]
[ROW][C]12[/C][C]-0.050574683935992[/C][/ROW]
[ROW][C]13[/C][C]-0.0648775005256542[/C][/ROW]
[ROW][C]14[/C][C]-0.059151909865994[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6666&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6666&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 series0
Seasonal Period (s)12
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])
-140.351610942974732
-130.387668524202071
-120.394198528056613
-110.394572331653816
-100.411350721951093
-90.395052960378586
-80.458170688221488
-70.477564386552626
-60.437785035788809
-50.400434068550828
-40.426853322796642
-30.447419314004566
-20.439450350247123
-10.394879246266561
00.404171974754718
10.385379025021206
20.393304172568342
30.326032145022905
40.359285612070421
50.334217393328596
60.258276543016064
70.178134929520766
80.134242071667206
90.0949619843321428
100.0648981531241143
110.00270653503177192
12-0.050574683935992
13-0.0648775005256542
14-0.059151909865994


Figures (Output of Computation)

Input Parameters & R Code

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