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Description of Statistical Computation

Author's title

Non Stationary Time Series Q7 totaal werkloosheid en totaal werkloosheid ma...

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationFri, 28 Nov 2008 05:34:34 -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/Nov/28/t122787576253ufaxfmroi120v.htm/, Retrieved Sun, 19 May 2024 12:39:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26042, Retrieved Sun, 19 May 2024 12:39:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [tijdreeks verkoop...] [2008-10-13 20:55:30] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   PD  [Univariate Data Series] [totale werkloosheid] [2008-10-19 15:02:07] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMPD    [Cross Correlation Function] [] [2008-11-28 11:47:25] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-   P         [Cross Correlation Function] [Non Stationary Ti...] [2008-11-28 12:34:34] [6797a1f4a60918966297e9d9220cabc2] [Current]
-   P           [Cross Correlation Function] [Non Stationary Ti...] [2008-11-30 13:27:08] [063e4b67ad7d3a8a83eccec794cd5aa7]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.4
7.2
7.1
6.9
6.8
6.8
6.8
6.9
6.7
6.6
6.5
6.4
6.3
6.3
6.3
6.5
6.6
6.5
6.4
6.5
6.7
7.1
7.1
7.2
7.2
7.3
7.3
7.3
7.3
7.4
7.6
7.6
7.6
7.7
7.8
7.9
8.1
8.1
8.1
8.2
8.2
8.2
8.2
8.2
8.2
8.3
8.3
8.4
8.4
8.4
8.3
8
8
8.2
8.6
8.7
8.7
8.5
8.4
8.4
8.4
8.5
8.5
8.5
8.5
8.5
8.4
8.4
8.4
8.5
8.6
8.6
8.6
8.6
8.5
8.4
8.4
8.3
8.2
8.1
8.2
8.1
8
7.9
7.8
7.7
7.7
7.9
7.8
7.6
7.4
7.3
7.1
7.1
7
7
7
6.9
6.8
6.7
6.6
6.6
Dataseries Y:
Download CSV
Histogram 
6.2
6.1
5.9
5.6
5.5
5.5
5.6
5.7
5.6
5.4
5.3
5.3
5.4
5.5
5.6
5.7
5.8
5.8
5.7
5.9
6.1
6.4
6.4
6.3
6.2
6.2
6.3
6.5
6.6
6.6
6.7
6.6
6.7
7
7.2
7.3
7.5
7.6
7.7
7.8
7.8
7.7
7.6
7.6
7.7
7.8
7.8
7.8
7.7
7.6
7.4
7.1
7.1
7.3
7.6
7.8
7.7
7.6
7.5
7.5
7.5
7.6
7.6
7.7
7.8
7.7
7.6
7.6
7.6
7.7
7.8
7.8
7.9
7.9
7.8
7.8
7.7
7.5
7.1
6.9
7.1
7.1
7.1
7
6.9
6.8
6.7
6.8
6.8
6.7
6.8
6.7
6.6
6.4
6.4
6.4
6.5
6.5
6.4
6.3
6.2
6.3

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26042&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26042&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26042&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'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])
-170.211815419727356
-160.260382120522913
-150.308888520857359
-140.353716593064068
-130.396363798593948
-120.442227028716385
-110.491818837350821
-100.543561362431529
-90.595394338203902
-80.643930888768904
-70.689211214433941
-60.729989105669396
-50.767973075540067
-40.805203289646857
-30.84481537196751
-20.88573396427889
-10.925335996522692
00.954063845612906
10.95102399295575
20.93263767294598
30.911698633415866
40.891181697113527
50.872554175259315
60.852730694259746
70.825620907542662
80.792802677173788
90.750557474717978
100.703478185296479
110.654187878967596
120.605591027941484
130.557466530527404
140.512015353555887
150.462805447841818
160.407706197092628
170.351109484892527

\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
-17 & 0.211815419727356 \tabularnewline
-16 & 0.260382120522913 \tabularnewline
-15 & 0.308888520857359 \tabularnewline
-14 & 0.353716593064068 \tabularnewline
-13 & 0.396363798593948 \tabularnewline
-12 & 0.442227028716385 \tabularnewline
-11 & 0.491818837350821 \tabularnewline
-10 & 0.543561362431529 \tabularnewline
-9 & 0.595394338203902 \tabularnewline
-8 & 0.643930888768904 \tabularnewline
-7 & 0.689211214433941 \tabularnewline
-6 & 0.729989105669396 \tabularnewline
-5 & 0.767973075540067 \tabularnewline
-4 & 0.805203289646857 \tabularnewline
-3 & 0.84481537196751 \tabularnewline
-2 & 0.88573396427889 \tabularnewline
-1 & 0.925335996522692 \tabularnewline
0 & 0.954063845612906 \tabularnewline
1 & 0.95102399295575 \tabularnewline
2 & 0.93263767294598 \tabularnewline
3 & 0.911698633415866 \tabularnewline
4 & 0.891181697113527 \tabularnewline
5 & 0.872554175259315 \tabularnewline
6 & 0.852730694259746 \tabularnewline
7 & 0.825620907542662 \tabularnewline
8 & 0.792802677173788 \tabularnewline
9 & 0.750557474717978 \tabularnewline
10 & 0.703478185296479 \tabularnewline
11 & 0.654187878967596 \tabularnewline
12 & 0.605591027941484 \tabularnewline
13 & 0.557466530527404 \tabularnewline
14 & 0.512015353555887 \tabularnewline
15 & 0.462805447841818 \tabularnewline
16 & 0.407706197092628 \tabularnewline
17 & 0.351109484892527 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26042&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]-17[/C][C]0.211815419727356[/C][/ROW]
[ROW][C]-16[/C][C]0.260382120522913[/C][/ROW]
[ROW][C]-15[/C][C]0.308888520857359[/C][/ROW]
[ROW][C]-14[/C][C]0.353716593064068[/C][/ROW]
[ROW][C]-13[/C][C]0.396363798593948[/C][/ROW]
[ROW][C]-12[/C][C]0.442227028716385[/C][/ROW]
[ROW][C]-11[/C][C]0.491818837350821[/C][/ROW]
[ROW][C]-10[/C][C]0.543561362431529[/C][/ROW]
[ROW][C]-9[/C][C]0.595394338203902[/C][/ROW]
[ROW][C]-8[/C][C]0.643930888768904[/C][/ROW]
[ROW][C]-7[/C][C]0.689211214433941[/C][/ROW]
[ROW][C]-6[/C][C]0.729989105669396[/C][/ROW]
[ROW][C]-5[/C][C]0.767973075540067[/C][/ROW]
[ROW][C]-4[/C][C]0.805203289646857[/C][/ROW]
[ROW][C]-3[/C][C]0.84481537196751[/C][/ROW]
[ROW][C]-2[/C][C]0.88573396427889[/C][/ROW]
[ROW][C]-1[/C][C]0.925335996522692[/C][/ROW]
[ROW][C]0[/C][C]0.954063845612906[/C][/ROW]
[ROW][C]1[/C][C]0.95102399295575[/C][/ROW]
[ROW][C]2[/C][C]0.93263767294598[/C][/ROW]
[ROW][C]3[/C][C]0.911698633415866[/C][/ROW]
[ROW][C]4[/C][C]0.891181697113527[/C][/ROW]
[ROW][C]5[/C][C]0.872554175259315[/C][/ROW]
[ROW][C]6[/C][C]0.852730694259746[/C][/ROW]
[ROW][C]7[/C][C]0.825620907542662[/C][/ROW]
[ROW][C]8[/C][C]0.792802677173788[/C][/ROW]
[ROW][C]9[/C][C]0.750557474717978[/C][/ROW]
[ROW][C]10[/C][C]0.703478185296479[/C][/ROW]
[ROW][C]11[/C][C]0.654187878967596[/C][/ROW]
[ROW][C]12[/C][C]0.605591027941484[/C][/ROW]
[ROW][C]13[/C][C]0.557466530527404[/C][/ROW]
[ROW][C]14[/C][C]0.512015353555887[/C][/ROW]
[ROW][C]15[/C][C]0.462805447841818[/C][/ROW]
[ROW][C]16[/C][C]0.407706197092628[/C][/ROW]
[ROW][C]17[/C][C]0.351109484892527[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26042&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26042&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])
-170.211815419727356
-160.260382120522913
-150.308888520857359
-140.353716593064068
-130.396363798593948
-120.442227028716385
-110.491818837350821
-100.543561362431529
-90.595394338203902
-80.643930888768904
-70.689211214433941
-60.729989105669396
-50.767973075540067
-40.805203289646857
-30.84481537196751
-20.88573396427889
-10.925335996522692
00.954063845612906
10.95102399295575
20.93263767294598
30.911698633415866
40.891181697113527
50.872554175259315
60.852730694259746
70.825620907542662
80.792802677173788
90.750557474717978
100.703478185296479
110.654187878967596
120.605591027941484
130.557466530527404
140.512015353555887
150.462805447841818
160.407706197092628
170.351109484892527


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Airline ; par2 = Box-Jenkins ; par3 = Airline Passengers ;
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) 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')