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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationThu, 22 Nov 2007 07:09:01 -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/Nov/22/t1195740080lx47wl8277hj4rt.htm/, Retrieved Thu, 02 May 2024 14:29:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6007, Retrieved Thu, 02 May 2024 14:29:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Cross Correlation...] [2007-11-22 14:09:01] [2cdb7403ed3391afb545b8c0d20da37e] [Current]
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Dataseries X:
373
371
354
357
363
364
363
358
357
357
380
378
376
380
379
384
392
394
392
396
392
396
419
421
420
418
410
418
426
428
430
424
423
427
441
449
452
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418
Dataseries Y:
513
503
471
471
476
475
470
461
455
456
517
525
523
519
509
512
519
517
510
509
501
507
569
580
578
565
547
555
562
561
555
544
537
543
594
611
613
611
594
595
591
589
584
573
567
569
621
629
628
612
595
597
593
590
580
574
573
573
620
626
620
588
566
557
561
549
532
526
511
499
555
565
542




Summary of compuational 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 compuational 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=6007&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]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=6007&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6007&T=0

As an alternative you can also use a 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 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)1
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])
-150.156051899770592
-140.222583114153788
-130.29257119635674
-120.350700748461432
-110.361500177399916
-100.367829586587810
-90.412427895303792
-80.474779515876163
-70.558941872741916
-60.623075567899054
-50.661396822945241
-40.694473990460946
-30.747974023910327
-20.81750265731223
-10.885308111400979
00.93501969008317
10.888527537131272
20.832374589160898
30.790178069030812
40.758390248186241
50.74322808084695
60.713521846600412
70.660586025474263
80.600325077573426
90.563680367294468
100.546188005249644
110.542189557062638
120.524587833723497
130.457185341521014
140.383394682822178
150.323757170928483

\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) & 1 \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
-15 & 0.156051899770592 \tabularnewline
-14 & 0.222583114153788 \tabularnewline
-13 & 0.29257119635674 \tabularnewline
-12 & 0.350700748461432 \tabularnewline
-11 & 0.361500177399916 \tabularnewline
-10 & 0.367829586587810 \tabularnewline
-9 & 0.412427895303792 \tabularnewline
-8 & 0.474779515876163 \tabularnewline
-7 & 0.558941872741916 \tabularnewline
-6 & 0.623075567899054 \tabularnewline
-5 & 0.661396822945241 \tabularnewline
-4 & 0.694473990460946 \tabularnewline
-3 & 0.747974023910327 \tabularnewline
-2 & 0.81750265731223 \tabularnewline
-1 & 0.885308111400979 \tabularnewline
0 & 0.93501969008317 \tabularnewline
1 & 0.888527537131272 \tabularnewline
2 & 0.832374589160898 \tabularnewline
3 & 0.790178069030812 \tabularnewline
4 & 0.758390248186241 \tabularnewline
5 & 0.74322808084695 \tabularnewline
6 & 0.713521846600412 \tabularnewline
7 & 0.660586025474263 \tabularnewline
8 & 0.600325077573426 \tabularnewline
9 & 0.563680367294468 \tabularnewline
10 & 0.546188005249644 \tabularnewline
11 & 0.542189557062638 \tabularnewline
12 & 0.524587833723497 \tabularnewline
13 & 0.457185341521014 \tabularnewline
14 & 0.383394682822178 \tabularnewline
15 & 0.323757170928483 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6007&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]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]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]-15[/C][C]0.156051899770592[/C][/ROW]
[ROW][C]-14[/C][C]0.222583114153788[/C][/ROW]
[ROW][C]-13[/C][C]0.29257119635674[/C][/ROW]
[ROW][C]-12[/C][C]0.350700748461432[/C][/ROW]
[ROW][C]-11[/C][C]0.361500177399916[/C][/ROW]
[ROW][C]-10[/C][C]0.367829586587810[/C][/ROW]
[ROW][C]-9[/C][C]0.412427895303792[/C][/ROW]
[ROW][C]-8[/C][C]0.474779515876163[/C][/ROW]
[ROW][C]-7[/C][C]0.558941872741916[/C][/ROW]
[ROW][C]-6[/C][C]0.623075567899054[/C][/ROW]
[ROW][C]-5[/C][C]0.661396822945241[/C][/ROW]
[ROW][C]-4[/C][C]0.694473990460946[/C][/ROW]
[ROW][C]-3[/C][C]0.747974023910327[/C][/ROW]
[ROW][C]-2[/C][C]0.81750265731223[/C][/ROW]
[ROW][C]-1[/C][C]0.885308111400979[/C][/ROW]
[ROW][C]0[/C][C]0.93501969008317[/C][/ROW]
[ROW][C]1[/C][C]0.888527537131272[/C][/ROW]
[ROW][C]2[/C][C]0.832374589160898[/C][/ROW]
[ROW][C]3[/C][C]0.790178069030812[/C][/ROW]
[ROW][C]4[/C][C]0.758390248186241[/C][/ROW]
[ROW][C]5[/C][C]0.74322808084695[/C][/ROW]
[ROW][C]6[/C][C]0.713521846600412[/C][/ROW]
[ROW][C]7[/C][C]0.660586025474263[/C][/ROW]
[ROW][C]8[/C][C]0.600325077573426[/C][/ROW]
[ROW][C]9[/C][C]0.563680367294468[/C][/ROW]
[ROW][C]10[/C][C]0.546188005249644[/C][/ROW]
[ROW][C]11[/C][C]0.542189557062638[/C][/ROW]
[ROW][C]12[/C][C]0.524587833723497[/C][/ROW]
[ROW][C]13[/C][C]0.457185341521014[/C][/ROW]
[ROW][C]14[/C][C]0.383394682822178[/C][/ROW]
[ROW][C]15[/C][C]0.323757170928483[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6007&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6007&T=1

As an alternative you can also use a 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)1
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])
-150.156051899770592
-140.222583114153788
-130.29257119635674
-120.350700748461432
-110.361500177399916
-100.367829586587810
-90.412427895303792
-80.474779515876163
-70.558941872741916
-60.623075567899054
-50.661396822945241
-40.694473990460946
-30.747974023910327
-20.81750265731223
-10.885308111400979
00.93501969008317
10.888527537131272
20.832374589160898
30.790178069030812
40.758390248186241
50.74322808084695
60.713521846600412
70.660586025474263
80.600325077573426
90.563680367294468
100.546188005249644
110.542189557062638
120.524587833723497
130.457185341521014
140.383394682822178
150.323757170928483



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')