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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, 07 Dec 2008 02:06:03 -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/07/t1228640787psbvd9zopk9645k.htm/, Retrieved Sat, 18 May 2024 09:22:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29823, Retrieved Sat, 18 May 2024 09:22:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cross Correlation Function] [Cross Correlation...] [2008-12-04 16:34:44] [c94d7012e41b73cfa20d93e879679ede]
-   P     [Cross Correlation Function] [Cross Correlation...] [2008-12-07 09:06:03] [32a7b12f2bdf14b45f7a9a96ba1ab98d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
345
334
345
333
336
324
320
330
313
301
288
294
302
294
293
290
283
286
293
334
329
411
416
418
408
402
401
400
389
371
364
350
332
323
316
312
315
314
313
314
317
308
312
306
304
297
284
278
273
265
259
252
245
235
232
229
219
218
215
211
Dataseries Y:
Download CSV
Histogram 
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
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258

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'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 & 2 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=29823&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29823&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29823&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'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 series0
Seasonal Period (s)12
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])
-13-0.104918372090072
-12-0.187965417735962
-11-0.00752159354628973
-10-0.00422670331617477
-90.111413575530212
-80.0788230186006325
-70.116769381342317
-60.182837674159737
-50.0537072874652473
-4-0.0313750975316961
-30.160914536589086
-2-0.0223605270234933
-1-0.00174432273071821
0-0.271281718974683
1-0.140759198752276
2-0.104727945700716
30.0986827217083474
4-0.0564647333619394
50.0548610107075111
60.0310025719893045
7-0.041635860014294
80.0508991093210656
9-0.110872775976170
100.0942434523734573
110.122197753391653
120.319999037457292
130.100933885042478

\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 & 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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.104918372090072 \tabularnewline
-12 & -0.187965417735962 \tabularnewline
-11 & -0.00752159354628973 \tabularnewline
-10 & -0.00422670331617477 \tabularnewline
-9 & 0.111413575530212 \tabularnewline
-8 & 0.0788230186006325 \tabularnewline
-7 & 0.116769381342317 \tabularnewline
-6 & 0.182837674159737 \tabularnewline
-5 & 0.0537072874652473 \tabularnewline
-4 & -0.0313750975316961 \tabularnewline
-3 & 0.160914536589086 \tabularnewline
-2 & -0.0223605270234933 \tabularnewline
-1 & -0.00174432273071821 \tabularnewline
0 & -0.271281718974683 \tabularnewline
1 & -0.140759198752276 \tabularnewline
2 & -0.104727945700716 \tabularnewline
3 & 0.0986827217083474 \tabularnewline
4 & -0.0564647333619394 \tabularnewline
5 & 0.0548610107075111 \tabularnewline
6 & 0.0310025719893045 \tabularnewline
7 & -0.041635860014294 \tabularnewline
8 & 0.0508991093210656 \tabularnewline
9 & -0.110872775976170 \tabularnewline
10 & 0.0942434523734573 \tabularnewline
11 & 0.122197753391653 \tabularnewline
12 & 0.319999037457292 \tabularnewline
13 & 0.100933885042478 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29823&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]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]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]-0.104918372090072[/C][/ROW]
[ROW][C]-12[/C][C]-0.187965417735962[/C][/ROW]
[ROW][C]-11[/C][C]-0.00752159354628973[/C][/ROW]
[ROW][C]-10[/C][C]-0.00422670331617477[/C][/ROW]
[ROW][C]-9[/C][C]0.111413575530212[/C][/ROW]
[ROW][C]-8[/C][C]0.0788230186006325[/C][/ROW]
[ROW][C]-7[/C][C]0.116769381342317[/C][/ROW]
[ROW][C]-6[/C][C]0.182837674159737[/C][/ROW]
[ROW][C]-5[/C][C]0.0537072874652473[/C][/ROW]
[ROW][C]-4[/C][C]-0.0313750975316961[/C][/ROW]
[ROW][C]-3[/C][C]0.160914536589086[/C][/ROW]
[ROW][C]-2[/C][C]-0.0223605270234933[/C][/ROW]
[ROW][C]-1[/C][C]-0.00174432273071821[/C][/ROW]
[ROW][C]0[/C][C]-0.271281718974683[/C][/ROW]
[ROW][C]1[/C][C]-0.140759198752276[/C][/ROW]
[ROW][C]2[/C][C]-0.104727945700716[/C][/ROW]
[ROW][C]3[/C][C]0.0986827217083474[/C][/ROW]
[ROW][C]4[/C][C]-0.0564647333619394[/C][/ROW]
[ROW][C]5[/C][C]0.0548610107075111[/C][/ROW]
[ROW][C]6[/C][C]0.0310025719893045[/C][/ROW]
[ROW][C]7[/C][C]-0.041635860014294[/C][/ROW]
[ROW][C]8[/C][C]0.0508991093210656[/C][/ROW]
[ROW][C]9[/C][C]-0.110872775976170[/C][/ROW]
[ROW][C]10[/C][C]0.0942434523734573[/C][/ROW]
[ROW][C]11[/C][C]0.122197753391653[/C][/ROW]
[ROW][C]12[/C][C]0.319999037457292[/C][/ROW]
[ROW][C]13[/C][C]0.100933885042478[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29823&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29823&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 series0
Seasonal Period (s)12
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])
-13-0.104918372090072
-12-0.187965417735962
-11-0.00752159354628973
-10-0.00422670331617477
-90.111413575530212
-80.0788230186006325
-70.116769381342317
-60.182837674159737
-50.0537072874652473
-4-0.0313750975316961
-30.160914536589086
-2-0.0223605270234933
-1-0.00174432273071821
0-0.271281718974683
1-0.140759198752276
2-0.104727945700716
30.0986827217083474
4-0.0564647333619394
50.0548610107075111
60.0310025719893045
7-0.041635860014294
80.0508991093210656
9-0.110872775976170
100.0942434523734573
110.122197753391653
120.319999037457292
130.100933885042478


Figures (Output of Computation)

Input Parameters & R Code

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