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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 computationSat, 29 Nov 2008 10:57:22 -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/29/t12279816257f7kjt1x1kjnh7w.htm/, Retrieved Sun, 19 May 2024 07:16:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26350, Retrieved Sun, 19 May 2024 07:16:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196

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]
F RMPD  [Standard Deviation-Mean Plot] [vraag 5] [2008-11-29 13:37:39] [c45c87b96bbf32ffc2144fc37d767b2e]
-    D    [Standard Deviation-Mean Plot] [vraag 7] [2008-11-29 17:31:20] [c45c87b96bbf32ffc2144fc37d767b2e]
F RMPD      [Cross Correlation Function] [vraag 7] [2008-11-29 17:42:06] [c45c87b96bbf32ffc2144fc37d767b2e]
F   P           [Cross Correlation Function] [vraag 7] [2008-11-29 17:57:22] [3dc594a6c62226e1e98766c4d385bfaa] [Current]
Feedback Forum
2008-12-08 19:32:03 [Michaël De Kuyer] [reply] 
Deze vraag heb ik correct beantwoord.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
527
510
514
517
508
493
490
469
478
Dataseries Y:
Download CSV
Histogram 
2.282
2.266
1.878
2.267
2.069
1.746
2.299
2.36
2.214
2.825
2.355
2.333
3.016
2.155
2.172
2.15
2.533
2.058
2.16
2.259
2.498
2.695
2.799
2.945
2.93
2.318
2.54
2.57
2.669
2.45
2.842
3.439
2.677
2.979
2.257
2.842
2.546
2.455
2.293
2.379
2.478
2.054
2.272
2.351
2.271
2.542
2.304
2.194
2.722
2.395
2.146
1.894
2.548
2.087
2.063
2.481
2.476
2.212
2.834
2.148
2.598

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26350&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26350&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26350&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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])
-140.000603933909134389
-13-0.0148662822824279
-12-0.0848645329123625
-110.0338069853227781
-100.111543867038768
-90.145196949542423
-80.243633074543261
-70.232966780446706
-60.324809608300499
-50.337454475035318
-40.206746001015309
-30.200876541691091
-20.170204300996597
-10.0893590986831672
00.0899401030399232
10.176019075742295
20.233047025861083
30.316407358112067
40.392215648032791
50.389571471870314
60.455386158541365
70.380991492970417
80.219720252193849
90.160217160304601
100.0228260662763024
11-0.105319702290556
12-0.162752687233189
13-0.096731055088237
14-0.082936947227521

\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 & 0.000603933909134389 \tabularnewline
-13 & -0.0148662822824279 \tabularnewline
-12 & -0.0848645329123625 \tabularnewline
-11 & 0.0338069853227781 \tabularnewline
-10 & 0.111543867038768 \tabularnewline
-9 & 0.145196949542423 \tabularnewline
-8 & 0.243633074543261 \tabularnewline
-7 & 0.232966780446706 \tabularnewline
-6 & 0.324809608300499 \tabularnewline
-5 & 0.337454475035318 \tabularnewline
-4 & 0.206746001015309 \tabularnewline
-3 & 0.200876541691091 \tabularnewline
-2 & 0.170204300996597 \tabularnewline
-1 & 0.0893590986831672 \tabularnewline
0 & 0.0899401030399232 \tabularnewline
1 & 0.176019075742295 \tabularnewline
2 & 0.233047025861083 \tabularnewline
3 & 0.316407358112067 \tabularnewline
4 & 0.392215648032791 \tabularnewline
5 & 0.389571471870314 \tabularnewline
6 & 0.455386158541365 \tabularnewline
7 & 0.380991492970417 \tabularnewline
8 & 0.219720252193849 \tabularnewline
9 & 0.160217160304601 \tabularnewline
10 & 0.0228260662763024 \tabularnewline
11 & -0.105319702290556 \tabularnewline
12 & -0.162752687233189 \tabularnewline
13 & -0.096731055088237 \tabularnewline
14 & -0.082936947227521 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26350&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]0.000603933909134389[/C][/ROW]
[ROW][C]-13[/C][C]-0.0148662822824279[/C][/ROW]
[ROW][C]-12[/C][C]-0.0848645329123625[/C][/ROW]
[ROW][C]-11[/C][C]0.0338069853227781[/C][/ROW]
[ROW][C]-10[/C][C]0.111543867038768[/C][/ROW]
[ROW][C]-9[/C][C]0.145196949542423[/C][/ROW]
[ROW][C]-8[/C][C]0.243633074543261[/C][/ROW]
[ROW][C]-7[/C][C]0.232966780446706[/C][/ROW]
[ROW][C]-6[/C][C]0.324809608300499[/C][/ROW]
[ROW][C]-5[/C][C]0.337454475035318[/C][/ROW]
[ROW][C]-4[/C][C]0.206746001015309[/C][/ROW]
[ROW][C]-3[/C][C]0.200876541691091[/C][/ROW]
[ROW][C]-2[/C][C]0.170204300996597[/C][/ROW]
[ROW][C]-1[/C][C]0.0893590986831672[/C][/ROW]
[ROW][C]0[/C][C]0.0899401030399232[/C][/ROW]
[ROW][C]1[/C][C]0.176019075742295[/C][/ROW]
[ROW][C]2[/C][C]0.233047025861083[/C][/ROW]
[ROW][C]3[/C][C]0.316407358112067[/C][/ROW]
[ROW][C]4[/C][C]0.392215648032791[/C][/ROW]
[ROW][C]5[/C][C]0.389571471870314[/C][/ROW]
[ROW][C]6[/C][C]0.455386158541365[/C][/ROW]
[ROW][C]7[/C][C]0.380991492970417[/C][/ROW]
[ROW][C]8[/C][C]0.219720252193849[/C][/ROW]
[ROW][C]9[/C][C]0.160217160304601[/C][/ROW]
[ROW][C]10[/C][C]0.0228260662763024[/C][/ROW]
[ROW][C]11[/C][C]-0.105319702290556[/C][/ROW]
[ROW][C]12[/C][C]-0.162752687233189[/C][/ROW]
[ROW][C]13[/C][C]-0.096731055088237[/C][/ROW]
[ROW][C]14[/C][C]-0.082936947227521[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26350&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26350&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])
-140.000603933909134389
-13-0.0148662822824279
-12-0.0848645329123625
-110.0338069853227781
-100.111543867038768
-90.145196949542423
-80.243633074543261
-70.232966780446706
-60.324809608300499
-50.337454475035318
-40.206746001015309
-30.200876541691091
-20.170204300996597
-10.0893590986831672
00.0899401030399232
10.176019075742295
20.233047025861083
30.316407358112067
40.392215648032791
50.389571471870314
60.455386158541365
70.380991492970417
80.219720252193849
90.160217160304601
100.0228260662763024
11-0.105319702290556
12-0.162752687233189
13-0.096731055088237
14-0.082936947227521


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
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')