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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 09:16:14 -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/t1228061849voxjt97ofjisx7g.htm/, Retrieved Sun, 19 May 2024 12:19:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26594, Retrieved Sun, 19 May 2024 12:19:20 +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)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [Cross Correlation Function] [Taak 7 Q7] [2008-11-30 15:54:53] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P       [Cross Correlation Function] [taak 7 Q 9] [2008-11-30 16:16:14] [bda7fba231d49184c6a1b627868bbb81] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
512927
502831
470984
471067
476049
474605
470439
461251
454724
455626
516847
525192
522975
518585
509239
512238
519164
517009
509933
509127
500857
506971
569323
579714
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
Dataseries Y:
Download CSV
Histogram 
189917
184128
175335
179566
181140
177876
175041
169292
166070
166972
206348
215706
202108
195411
193111
195198
198770
194163
190420
189733
186029
191531
232571
243477
227247
217859
208679
213188
216234
213587
209465
204045
200237
203666
241476
260307
243324
244460
233575
237217
235243
230354
227184
221678
217142
219452
256446
265845
248624
241114
229245
231805
219277
219313
212610
214771
211142
211457
240048
240636
230580

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26594&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26594&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26594&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'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series-1.2
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1.4
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.0442233651274584
-12-0.133337262834037
-11-0.13790581882033
-10-0.0296437246060232
-90.151162029017542
-80.133477102940360
-70.130016302542437
-6-0.0694997633369528
-50.183892596864511
-4-0.0169933465138499
-3-0.0840539162658464
-20.131262984878702
-1-0.0378190303143421
00.486043210639447
10.0508989398424685
20.123150553878182
3-0.129659747199666
4-0.161302259042385
50.0180076308372207
6-0.0102551051927177
70.04700334788489
80.0500039294303351
90.0574874674283744
10-0.0693766658469671
11-0.0699095769741059
12-0.261796910663434
130.0143222840246649

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -1.2 \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) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1.4 \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 & 0.0442233651274584 \tabularnewline
-12 & -0.133337262834037 \tabularnewline
-11 & -0.13790581882033 \tabularnewline
-10 & -0.0296437246060232 \tabularnewline
-9 & 0.151162029017542 \tabularnewline
-8 & 0.133477102940360 \tabularnewline
-7 & 0.130016302542437 \tabularnewline
-6 & -0.0694997633369528 \tabularnewline
-5 & 0.183892596864511 \tabularnewline
-4 & -0.0169933465138499 \tabularnewline
-3 & -0.0840539162658464 \tabularnewline
-2 & 0.131262984878702 \tabularnewline
-1 & -0.0378190303143421 \tabularnewline
0 & 0.486043210639447 \tabularnewline
1 & 0.0508989398424685 \tabularnewline
2 & 0.123150553878182 \tabularnewline
3 & -0.129659747199666 \tabularnewline
4 & -0.161302259042385 \tabularnewline
5 & 0.0180076308372207 \tabularnewline
6 & -0.0102551051927177 \tabularnewline
7 & 0.04700334788489 \tabularnewline
8 & 0.0500039294303351 \tabularnewline
9 & 0.0574874674283744 \tabularnewline
10 & -0.0693766658469671 \tabularnewline
11 & -0.0699095769741059 \tabularnewline
12 & -0.261796910663434 \tabularnewline
13 & 0.0143222840246649 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26594&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]-1.2[/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]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]1.4[/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]0.0442233651274584[/C][/ROW]
[ROW][C]-12[/C][C]-0.133337262834037[/C][/ROW]
[ROW][C]-11[/C][C]-0.13790581882033[/C][/ROW]
[ROW][C]-10[/C][C]-0.0296437246060232[/C][/ROW]
[ROW][C]-9[/C][C]0.151162029017542[/C][/ROW]
[ROW][C]-8[/C][C]0.133477102940360[/C][/ROW]
[ROW][C]-7[/C][C]0.130016302542437[/C][/ROW]
[ROW][C]-6[/C][C]-0.0694997633369528[/C][/ROW]
[ROW][C]-5[/C][C]0.183892596864511[/C][/ROW]
[ROW][C]-4[/C][C]-0.0169933465138499[/C][/ROW]
[ROW][C]-3[/C][C]-0.0840539162658464[/C][/ROW]
[ROW][C]-2[/C][C]0.131262984878702[/C][/ROW]
[ROW][C]-1[/C][C]-0.0378190303143421[/C][/ROW]
[ROW][C]0[/C][C]0.486043210639447[/C][/ROW]
[ROW][C]1[/C][C]0.0508989398424685[/C][/ROW]
[ROW][C]2[/C][C]0.123150553878182[/C][/ROW]
[ROW][C]3[/C][C]-0.129659747199666[/C][/ROW]
[ROW][C]4[/C][C]-0.161302259042385[/C][/ROW]
[ROW][C]5[/C][C]0.0180076308372207[/C][/ROW]
[ROW][C]6[/C][C]-0.0102551051927177[/C][/ROW]
[ROW][C]7[/C][C]0.04700334788489[/C][/ROW]
[ROW][C]8[/C][C]0.0500039294303351[/C][/ROW]
[ROW][C]9[/C][C]0.0574874674283744[/C][/ROW]
[ROW][C]10[/C][C]-0.0693766658469671[/C][/ROW]
[ROW][C]11[/C][C]-0.0699095769741059[/C][/ROW]
[ROW][C]12[/C][C]-0.261796910663434[/C][/ROW]
[ROW][C]13[/C][C]0.0143222840246649[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26594&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26594&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 series-1.2
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1.4
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.0442233651274584
-12-0.133337262834037
-11-0.13790581882033
-10-0.0296437246060232
-90.151162029017542
-80.133477102940360
-70.130016302542437
-6-0.0694997633369528
-50.183892596864511
-4-0.0169933465138499
-3-0.0840539162658464
-20.131262984878702
-1-0.0378190303143421
00.486043210639447
10.0508989398424685
20.123150553878182
3-0.129659747199666
4-0.161302259042385
50.0180076308372207
6-0.0102551051927177
70.04700334788489
80.0500039294303351
90.0574874674283744
10-0.0693766658469671
11-0.0699095769741059
12-0.261796910663434
130.0143222840246649


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = -1.2 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1.4 ; 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')