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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 16 Jan 2008 13:08:13 -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/Jan/16/t1200513825ek6z4aaiz6rf0fl.htm/, Retrieved Wed, 15 May 2024 23:24:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=8008, Retrieved Wed, 15 May 2024 23:24:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact272

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] [] [2008-01-16 20:08:13] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,88
0,87
0,88
0,89
0,92
0,96
0,99
0,98
0,98
0,98
1,00
1,02
1,06
1,08
1,08
1,08
1,16
1,17
1,14
1,11
1,12
1,17
1,17
1,23
1,26
1,26
1,23
1,20
1,20
1,21
1,23
1,22
1,22
1,25
1,30
1,34
1,31
1,30
1,32
1,29
1,27
1,22
1,20
1,23
1,23
1,20
1,18
1,19
1,21
1,19
1,20
1,23
1,28
1,27
1,27
1,28
1,27
1,26
1,29
1,32
Dataseries Y:
Download CSV
Histogram 
281
295
294
302
314
321
313
310
319
316
319
333
356
358
340
328
355
356
351
359
378
378
389.
407
413
404
406
402
383
392
398
400
405
420
439
441
424
423
434
429
421
430
424
437
456
469
476
510
549
554
557
610
675
596
633
632
596
585
627
629

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8008&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]2 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=8008&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8008&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-13-0.208843319572872
-12-0.358161669688674
-110.211815780407894
-100.327295497175518
-9-0.183008993159873
-8-0.171986351910605
-70.0842398775246167
-60.369254790880872
-5-0.0739724789555818
-4-0.0637180866603044
-3-0.0388917464635345
-2-0.0232430900074442
-10.0793498701126015
00.272034476385529
1-0.130150793566407
2-0.144651206962232
30.169121983756138
40.189448856274538
5-0.129765526646447
6-0.268044889790557
70.0715183357058527
80.157625492316992
9-0.0368764770729027
10-0.0831972664985192
110.200969426896182
120.0650113320969234
13-0.0398120282121261

\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 & 1 \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 & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.208843319572872 \tabularnewline
-12 & -0.358161669688674 \tabularnewline
-11 & 0.211815780407894 \tabularnewline
-10 & 0.327295497175518 \tabularnewline
-9 & -0.183008993159873 \tabularnewline
-8 & -0.171986351910605 \tabularnewline
-7 & 0.0842398775246167 \tabularnewline
-6 & 0.369254790880872 \tabularnewline
-5 & -0.0739724789555818 \tabularnewline
-4 & -0.0637180866603044 \tabularnewline
-3 & -0.0388917464635345 \tabularnewline
-2 & -0.0232430900074442 \tabularnewline
-1 & 0.0793498701126015 \tabularnewline
0 & 0.272034476385529 \tabularnewline
1 & -0.130150793566407 \tabularnewline
2 & -0.144651206962232 \tabularnewline
3 & 0.169121983756138 \tabularnewline
4 & 0.189448856274538 \tabularnewline
5 & -0.129765526646447 \tabularnewline
6 & -0.268044889790557 \tabularnewline
7 & 0.0715183357058527 \tabularnewline
8 & 0.157625492316992 \tabularnewline
9 & -0.0368764770729027 \tabularnewline
10 & -0.0831972664985192 \tabularnewline
11 & 0.200969426896182 \tabularnewline
12 & 0.0650113320969234 \tabularnewline
13 & -0.0398120282121261 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=8008&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]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[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]2[/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]-13[/C][C]-0.208843319572872[/C][/ROW]
[ROW][C]-12[/C][C]-0.358161669688674[/C][/ROW]
[ROW][C]-11[/C][C]0.211815780407894[/C][/ROW]
[ROW][C]-10[/C][C]0.327295497175518[/C][/ROW]
[ROW][C]-9[/C][C]-0.183008993159873[/C][/ROW]
[ROW][C]-8[/C][C]-0.171986351910605[/C][/ROW]
[ROW][C]-7[/C][C]0.0842398775246167[/C][/ROW]
[ROW][C]-6[/C][C]0.369254790880872[/C][/ROW]
[ROW][C]-5[/C][C]-0.0739724789555818[/C][/ROW]
[ROW][C]-4[/C][C]-0.0637180866603044[/C][/ROW]
[ROW][C]-3[/C][C]-0.0388917464635345[/C][/ROW]
[ROW][C]-2[/C][C]-0.0232430900074442[/C][/ROW]
[ROW][C]-1[/C][C]0.0793498701126015[/C][/ROW]
[ROW][C]0[/C][C]0.272034476385529[/C][/ROW]
[ROW][C]1[/C][C]-0.130150793566407[/C][/ROW]
[ROW][C]2[/C][C]-0.144651206962232[/C][/ROW]
[ROW][C]3[/C][C]0.169121983756138[/C][/ROW]
[ROW][C]4[/C][C]0.189448856274538[/C][/ROW]
[ROW][C]5[/C][C]-0.129765526646447[/C][/ROW]
[ROW][C]6[/C][C]-0.268044889790557[/C][/ROW]
[ROW][C]7[/C][C]0.0715183357058527[/C][/ROW]
[ROW][C]8[/C][C]0.157625492316992[/C][/ROW]
[ROW][C]9[/C][C]-0.0368764770729027[/C][/ROW]
[ROW][C]10[/C][C]-0.0831972664985192[/C][/ROW]
[ROW][C]11[/C][C]0.200969426896182[/C][/ROW]
[ROW][C]12[/C][C]0.0650113320969234[/C][/ROW]
[ROW][C]13[/C][C]-0.0398120282121261[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=8008&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=8008&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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-13-0.208843319572872
-12-0.358161669688674
-110.211815780407894
-100.327295497175518
-9-0.183008993159873
-8-0.171986351910605
-70.0842398775246167
-60.369254790880872
-5-0.0739724789555818
-4-0.0637180866603044
-3-0.0388917464635345
-2-0.0232430900074442
-10.0793498701126015
00.272034476385529
1-0.130150793566407
2-0.144651206962232
30.169121983756138
40.189448856274538
5-0.129765526646447
6-0.268044889790557
70.0715183357058527
80.157625492316992
9-0.0368764770729027
10-0.0831972664985192
110.200969426896182
120.0650113320969234
13-0.0398120282121261


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; 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',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')