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Description of Statistical Computation

Author's title

cross correlation function: dollarkoers (x) en export (y) MET stationaire t...

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 24 Dec 2007 00:47:07 -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/Dec/24/t11984813206b3sp91151f31zs.htm/, Retrieved Sun, 05 May 2024 16:23:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4844, Retrieved Sun, 05 May 2024 16:23:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact313

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] [cross correlation...] [2007-12-24 07:47:07] [cb51ec34031fa6f7825ad77351c1efd8] [Current]
-   PD    [Cross Correlation Function] [] [2008-12-24 11:43:21] [0e3da40906c04c6abfe5eb434331b3f1]
-   PD    [Cross Correlation Function] [] [2008-12-24 11:47:14] [0e3da40906c04c6abfe5eb434331b3f1]
-    D    [Cross Correlation Function] [Nick Mulkens] [2008-12-24 14:20:58] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.1608
1.1208
1.0883
1.0704
1.0628
1.0378
1.0353
1.0604
1.0501
1.0706
1.0338
1.011
1.0137
0.9834
0.9643
0.947
0.906
0.9492
0.9397
0.9041
0.8721
0.8552
0.8564
0.8973
0.9383
0.9217
0.9095
0.892
0.8742
0.8532
0.8607
0.9005
0.9111
0.9059
0.8883
0.8924
0.8833
0.87
0.8758
0.8858
0.917
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
Dataseries Y:
Download CSV
Histogram 
544.5
619.8
777.6
640.4
633
722
860.1
495.1
692.8
766.7
648.5
640
681.6
752.5
1031.7
685.5
887.6
655.4
944.2
626.6
1221.8
939.6
886.6
811.3
774.7
910.6
911.6
697.7
829.8
824.3
885.6
538.9
686
878.7
812.7
640.4
773.9
795.9
836.3
876.1
851.7
692.4
877.3
536.8
705.9
951
755.7
695.5
744.8
672.1
666.6
760.8
756
604.4
883.9
527.9
756.2
812.9
655.6
707.6

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4844&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4844&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4844&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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 series1
krho(Y[t],X[t+k])
-13-0.222078144641432
-120.440043771645331
-11-0.259625295136365
-100.133998975323397
-9-0.096480124590862
-8-0.00762908537548982
-70.00447989836608505
-60.0408147275999966
-50.0051553846530869
-4-0.0987889612405047
-30.155211449432002
-2-0.120196280710158
-10.244517977483025
0-0.430125540732291
10.144074965809524
20.0380365228468239
30.0868080519446673
4-0.111967943772517
50.0625615593834013
6-0.124988938227648
70.184281713820381
8-0.0705555720141715
9-0.0438369170065942
100.0467414293201815
110.0156200952654027
12-0.12789416213436
130.197032340334894

\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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.222078144641432 \tabularnewline
-12 & 0.440043771645331 \tabularnewline
-11 & -0.259625295136365 \tabularnewline
-10 & 0.133998975323397 \tabularnewline
-9 & -0.096480124590862 \tabularnewline
-8 & -0.00762908537548982 \tabularnewline
-7 & 0.00447989836608505 \tabularnewline
-6 & 0.0408147275999966 \tabularnewline
-5 & 0.0051553846530869 \tabularnewline
-4 & -0.0987889612405047 \tabularnewline
-3 & 0.155211449432002 \tabularnewline
-2 & -0.120196280710158 \tabularnewline
-1 & 0.244517977483025 \tabularnewline
0 & -0.430125540732291 \tabularnewline
1 & 0.144074965809524 \tabularnewline
2 & 0.0380365228468239 \tabularnewline
3 & 0.0868080519446673 \tabularnewline
4 & -0.111967943772517 \tabularnewline
5 & 0.0625615593834013 \tabularnewline
6 & -0.124988938227648 \tabularnewline
7 & 0.184281713820381 \tabularnewline
8 & -0.0705555720141715 \tabularnewline
9 & -0.0438369170065942 \tabularnewline
10 & 0.0467414293201815 \tabularnewline
11 & 0.0156200952654027 \tabularnewline
12 & -0.12789416213436 \tabularnewline
13 & 0.197032340334894 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4844&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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.222078144641432[/C][/ROW]
[ROW][C]-12[/C][C]0.440043771645331[/C][/ROW]
[ROW][C]-11[/C][C]-0.259625295136365[/C][/ROW]
[ROW][C]-10[/C][C]0.133998975323397[/C][/ROW]
[ROW][C]-9[/C][C]-0.096480124590862[/C][/ROW]
[ROW][C]-8[/C][C]-0.00762908537548982[/C][/ROW]
[ROW][C]-7[/C][C]0.00447989836608505[/C][/ROW]
[ROW][C]-6[/C][C]0.0408147275999966[/C][/ROW]
[ROW][C]-5[/C][C]0.0051553846530869[/C][/ROW]
[ROW][C]-4[/C][C]-0.0987889612405047[/C][/ROW]
[ROW][C]-3[/C][C]0.155211449432002[/C][/ROW]
[ROW][C]-2[/C][C]-0.120196280710158[/C][/ROW]
[ROW][C]-1[/C][C]0.244517977483025[/C][/ROW]
[ROW][C]0[/C][C]-0.430125540732291[/C][/ROW]
[ROW][C]1[/C][C]0.144074965809524[/C][/ROW]
[ROW][C]2[/C][C]0.0380365228468239[/C][/ROW]
[ROW][C]3[/C][C]0.0868080519446673[/C][/ROW]
[ROW][C]4[/C][C]-0.111967943772517[/C][/ROW]
[ROW][C]5[/C][C]0.0625615593834013[/C][/ROW]
[ROW][C]6[/C][C]-0.124988938227648[/C][/ROW]
[ROW][C]7[/C][C]0.184281713820381[/C][/ROW]
[ROW][C]8[/C][C]-0.0705555720141715[/C][/ROW]
[ROW][C]9[/C][C]-0.0438369170065942[/C][/ROW]
[ROW][C]10[/C][C]0.0467414293201815[/C][/ROW]
[ROW][C]11[/C][C]0.0156200952654027[/C][/ROW]
[ROW][C]12[/C][C]-0.12789416213436[/C][/ROW]
[ROW][C]13[/C][C]0.197032340334894[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4844&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4844&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 series1
krho(Y[t],X[t+k])
-13-0.222078144641432
-120.440043771645331
-11-0.259625295136365
-100.133998975323397
-9-0.096480124590862
-8-0.00762908537548982
-70.00447989836608505
-60.0408147275999966
-50.0051553846530869
-4-0.0987889612405047
-30.155211449432002
-2-0.120196280710158
-10.244517977483025
0-0.430125540732291
10.144074965809524
20.0380365228468239
30.0868080519446673
4-0.111967943772517
50.0625615593834013
6-0.124988938227648
70.184281713820381
8-0.0705555720141715
9-0.0438369170065942
100.0467414293201815
110.0156200952654027
12-0.12789416213436
130.197032340334894


Figures (Output of Computation)

Input Parameters & R Code

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