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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 computationSun, 30 Nov 2008 13:45:08 -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/30/t1228077975wu9yix39uqo3v7m.htm/, Retrieved Sun, 19 May 2024 04:52:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26722, Retrieved Sun, 19 May 2024 04:52:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

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] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RM D    [Cross Correlation Function] [Q7 Non Stationary...] [2008-11-30 20:45:08] [5e9e099b83e50415d7642e10d74756e4] [Current]
-           [Cross Correlation Function] [Q9 Non Stationary...] [2008-11-30 22:18:27] [deb3c14ac9e4607a6d84fc9d0e0e6cc2]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590
517945
Dataseries Y:
Download CSV
Histogram 
308347
298427
289231
291975
294912
293488
290555
284736
281818
287854
316263
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
301631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976

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=26722&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=26722&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26722&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])
-140.0924447832364622
-130.256075348511005
-120.40068663128135
-110.393966073414268
-100.323278291261986
-90.263194394081351
-80.26206506350102
-70.327067829993085
-60.393970318050335
-50.429587447687863
-40.471212147714612
-30.556906806950626
-20.67854929372961
-10.857556565961622
00.994341115296594
10.894287213793011
20.736100705289081
30.611527392755986
40.520792139976764
50.472504785281279
60.428600310665485
70.356545306022307
80.283402154780801
90.273789005078066
100.326094113085812
110.408999393896262
120.444671897268653
130.330820625725394
140.186665439686746

\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 & 0.0924447832364622 \tabularnewline
-13 & 0.256075348511005 \tabularnewline
-12 & 0.40068663128135 \tabularnewline
-11 & 0.393966073414268 \tabularnewline
-10 & 0.323278291261986 \tabularnewline
-9 & 0.263194394081351 \tabularnewline
-8 & 0.26206506350102 \tabularnewline
-7 & 0.327067829993085 \tabularnewline
-6 & 0.393970318050335 \tabularnewline
-5 & 0.429587447687863 \tabularnewline
-4 & 0.471212147714612 \tabularnewline
-3 & 0.556906806950626 \tabularnewline
-2 & 0.67854929372961 \tabularnewline
-1 & 0.857556565961622 \tabularnewline
0 & 0.994341115296594 \tabularnewline
1 & 0.894287213793011 \tabularnewline
2 & 0.736100705289081 \tabularnewline
3 & 0.611527392755986 \tabularnewline
4 & 0.520792139976764 \tabularnewline
5 & 0.472504785281279 \tabularnewline
6 & 0.428600310665485 \tabularnewline
7 & 0.356545306022307 \tabularnewline
8 & 0.283402154780801 \tabularnewline
9 & 0.273789005078066 \tabularnewline
10 & 0.326094113085812 \tabularnewline
11 & 0.408999393896262 \tabularnewline
12 & 0.444671897268653 \tabularnewline
13 & 0.330820625725394 \tabularnewline
14 & 0.186665439686746 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26722&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]0.0924447832364622[/C][/ROW]
[ROW][C]-13[/C][C]0.256075348511005[/C][/ROW]
[ROW][C]-12[/C][C]0.40068663128135[/C][/ROW]
[ROW][C]-11[/C][C]0.393966073414268[/C][/ROW]
[ROW][C]-10[/C][C]0.323278291261986[/C][/ROW]
[ROW][C]-9[/C][C]0.263194394081351[/C][/ROW]
[ROW][C]-8[/C][C]0.26206506350102[/C][/ROW]
[ROW][C]-7[/C][C]0.327067829993085[/C][/ROW]
[ROW][C]-6[/C][C]0.393970318050335[/C][/ROW]
[ROW][C]-5[/C][C]0.429587447687863[/C][/ROW]
[ROW][C]-4[/C][C]0.471212147714612[/C][/ROW]
[ROW][C]-3[/C][C]0.556906806950626[/C][/ROW]
[ROW][C]-2[/C][C]0.67854929372961[/C][/ROW]
[ROW][C]-1[/C][C]0.857556565961622[/C][/ROW]
[ROW][C]0[/C][C]0.994341115296594[/C][/ROW]
[ROW][C]1[/C][C]0.894287213793011[/C][/ROW]
[ROW][C]2[/C][C]0.736100705289081[/C][/ROW]
[ROW][C]3[/C][C]0.611527392755986[/C][/ROW]
[ROW][C]4[/C][C]0.520792139976764[/C][/ROW]
[ROW][C]5[/C][C]0.472504785281279[/C][/ROW]
[ROW][C]6[/C][C]0.428600310665485[/C][/ROW]
[ROW][C]7[/C][C]0.356545306022307[/C][/ROW]
[ROW][C]8[/C][C]0.283402154780801[/C][/ROW]
[ROW][C]9[/C][C]0.273789005078066[/C][/ROW]
[ROW][C]10[/C][C]0.326094113085812[/C][/ROW]
[ROW][C]11[/C][C]0.408999393896262[/C][/ROW]
[ROW][C]12[/C][C]0.444671897268653[/C][/ROW]
[ROW][C]13[/C][C]0.330820625725394[/C][/ROW]
[ROW][C]14[/C][C]0.186665439686746[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26722&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26722&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])
-140.0924447832364622
-130.256075348511005
-120.40068663128135
-110.393966073414268
-100.323278291261986
-90.263194394081351
-80.26206506350102
-70.327067829993085
-60.393970318050335
-50.429587447687863
-40.471212147714612
-30.556906806950626
-20.67854929372961
-10.857556565961622
00.994341115296594
10.894287213793011
20.736100705289081
30.611527392755986
40.520792139976764
50.472504785281279
60.428600310665485
70.356545306022307
80.283402154780801
90.273789005078066
100.326094113085812
110.408999393896262
120.444671897268653
130.330820625725394
140.186665439686746


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')