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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 17 Dec 2008 06:42:00 -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/Dec/17/t1229521435kgyuew4jau0k6f5.htm/, Retrieved Sun, 19 May 2024 07:08:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34345, Retrieved Sun, 19 May 2024 07:08:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Werkloosheid -25 ...] [2008-11-28 13:09:39] [6743688719638b0cb1c0a6e0bf433315]
-   P   [Univariate Data Series] [Unemployment unde...] [2008-12-02 17:58:48] [6743688719638b0cb1c0a6e0bf433315]
- RMPD      [Cross Correlation Function] ['under 25' compa...] [2008-12-17 13:42:00] [9b05d7ef5dbcfba4217d280d9092f628] [Current]
-    D        [Cross Correlation Function] [-25 compared to 50+] [2008-12-19 11:44:43] [6743688719638b0cb1c0a6e0bf433315]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
150739
159129
157928
147768
137507
136919
136151
133001
125554
119647
114158
116193
152803
161761
160942
149470
139208
134588
130322
126611
122401
117352
112135
112879
148729
157230
157221
146681
136524
132111
125326
122716
116615
113719
110737
112093
143565
149946
149147
134339
122683
115614
116566
111272
104609
101802
94542
93051
124129
130374
123946
114971
105531
104919
104782
101281
94545
93248
84031
87486
115867
Dataseries Y:
Download CSV
Histogram 
374556
375021
375787
372720
364431
370490
376974
377632
378205
370861
369167
371551
382842
381903
384502
392058
384359
388884
386586
387495
385705
378670
377367
376911
389827
387820
387267
380575
372402
376740
377795
376126
370804
367980
367866
366121
379421
378519
372423
355072
344693
342892
344178
337606
327103
323953
316532
306307
327225
329573
313761
307836
300074
304198
306122
300414
292133
290616
280244
285179
305486

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 5 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=34345&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]5 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=34345&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34345&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 time5 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 series1
Seasonal Period (s)1
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])
-14-0.169408221902146
-13-0.090385494852375
-120.600872983964648
-11-0.113277096121669
-10-0.0861710755172945
-9-0.103908284327075
-8-0.164273331078745
-70.0190064356817306
-60.129113499463664
-50.256006047720717
-4-0.235177936457392
-3-0.00486572360417626
-2-0.228165822252837
-1-0.146790956465329
00.775287270959866
1-0.135924344931664
2-0.0134653060480759
3-0.177323459811879
4-0.102928435434834
5-0.0230528890423123
60.126863427623332
70.287276766769822
8-0.261284053787167
90.00746179233940761
10-0.199956692260683
11-0.108157115727134
120.498300159803236
13-0.0917668240390096
140.0278118596140788

\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 & 1 \tabularnewline
Seasonal Period (s) & 1 \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
-14 & -0.169408221902146 \tabularnewline
-13 & -0.090385494852375 \tabularnewline
-12 & 0.600872983964648 \tabularnewline
-11 & -0.113277096121669 \tabularnewline
-10 & -0.0861710755172945 \tabularnewline
-9 & -0.103908284327075 \tabularnewline
-8 & -0.164273331078745 \tabularnewline
-7 & 0.0190064356817306 \tabularnewline
-6 & 0.129113499463664 \tabularnewline
-5 & 0.256006047720717 \tabularnewline
-4 & -0.235177936457392 \tabularnewline
-3 & -0.00486572360417626 \tabularnewline
-2 & -0.228165822252837 \tabularnewline
-1 & -0.146790956465329 \tabularnewline
0 & 0.775287270959866 \tabularnewline
1 & -0.135924344931664 \tabularnewline
2 & -0.0134653060480759 \tabularnewline
3 & -0.177323459811879 \tabularnewline
4 & -0.102928435434834 \tabularnewline
5 & -0.0230528890423123 \tabularnewline
6 & 0.126863427623332 \tabularnewline
7 & 0.287276766769822 \tabularnewline
8 & -0.261284053787167 \tabularnewline
9 & 0.00746179233940761 \tabularnewline
10 & -0.199956692260683 \tabularnewline
11 & -0.108157115727134 \tabularnewline
12 & 0.498300159803236 \tabularnewline
13 & -0.0917668240390096 \tabularnewline
14 & 0.0278118596140788 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34345&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]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/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]-14[/C][C]-0.169408221902146[/C][/ROW]
[ROW][C]-13[/C][C]-0.090385494852375[/C][/ROW]
[ROW][C]-12[/C][C]0.600872983964648[/C][/ROW]
[ROW][C]-11[/C][C]-0.113277096121669[/C][/ROW]
[ROW][C]-10[/C][C]-0.0861710755172945[/C][/ROW]
[ROW][C]-9[/C][C]-0.103908284327075[/C][/ROW]
[ROW][C]-8[/C][C]-0.164273331078745[/C][/ROW]
[ROW][C]-7[/C][C]0.0190064356817306[/C][/ROW]
[ROW][C]-6[/C][C]0.129113499463664[/C][/ROW]
[ROW][C]-5[/C][C]0.256006047720717[/C][/ROW]
[ROW][C]-4[/C][C]-0.235177936457392[/C][/ROW]
[ROW][C]-3[/C][C]-0.00486572360417626[/C][/ROW]
[ROW][C]-2[/C][C]-0.228165822252837[/C][/ROW]
[ROW][C]-1[/C][C]-0.146790956465329[/C][/ROW]
[ROW][C]0[/C][C]0.775287270959866[/C][/ROW]
[ROW][C]1[/C][C]-0.135924344931664[/C][/ROW]
[ROW][C]2[/C][C]-0.0134653060480759[/C][/ROW]
[ROW][C]3[/C][C]-0.177323459811879[/C][/ROW]
[ROW][C]4[/C][C]-0.102928435434834[/C][/ROW]
[ROW][C]5[/C][C]-0.0230528890423123[/C][/ROW]
[ROW][C]6[/C][C]0.126863427623332[/C][/ROW]
[ROW][C]7[/C][C]0.287276766769822[/C][/ROW]
[ROW][C]8[/C][C]-0.261284053787167[/C][/ROW]
[ROW][C]9[/C][C]0.00746179233940761[/C][/ROW]
[ROW][C]10[/C][C]-0.199956692260683[/C][/ROW]
[ROW][C]11[/C][C]-0.108157115727134[/C][/ROW]
[ROW][C]12[/C][C]0.498300159803236[/C][/ROW]
[ROW][C]13[/C][C]-0.0917668240390096[/C][/ROW]
[ROW][C]14[/C][C]0.0278118596140788[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34345&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34345&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 series1
Seasonal Period (s)1
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])
-14-0.169408221902146
-13-0.090385494852375
-120.600872983964648
-11-0.113277096121669
-10-0.0861710755172945
-9-0.103908284327075
-8-0.164273331078745
-70.0190064356817306
-60.129113499463664
-50.256006047720717
-4-0.235177936457392
-3-0.00486572360417626
-2-0.228165822252837
-1-0.146790956465329
00.775287270959866
1-0.135924344931664
2-0.0134653060480759
3-0.177323459811879
4-0.102928435434834
5-0.0230528890423123
60.126863427623332
70.287276766769822
8-0.261284053787167
90.00746179233940761
10-0.199956692260683
11-0.108157115727134
120.498300159803236
13-0.0917668240390096
140.0278118596140788


Figures (Output of Computation)

Input Parameters & R Code

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