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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 computationTue, 15 Dec 2009 11:50:56 -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/2009/Dec/15/t1260903107qt6bbl5wm8jiv3s.htm/, Retrieved Wed, 08 May 2024 07:04:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68074, Retrieved Wed, 08 May 2024 07:04:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110

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] [workshop paper] [2007-12-18 13:41:49] [74be16979710d4c4e7c6647856088456]
- R  D  [Cross Correlation Function] [Cross correlation...] [2008-12-22 10:18:58] [072df11bdb18ed8d65d8164df87f26f2]
- RMPD      [Cross Correlation Function] [] [2009-12-15 18:50:56] [66ffaa9e54a90d3ae4874684602d24e9] [Current]
-   P         [Cross Correlation Function] [] [2009-12-15 19:08:51] [a9a33b1951d9ae87ed6d7d9055d41c93]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
412
404
409
412
406
398
397
385
390
413
413
401
397
397
409
419
424
428
430
424
433
456
459
446
Dataseries Y:
Download CSV
Histogram 
17823.2
17872
17420.4
16704.4
15991.2
16583.6
19123.5
17838.7
17209.4
18586.5
16258.1
15141.6
19202.1
17746.5
19090.1
18040.3
17515.5
17751.8
21072.4
17170
19439.5
19795.4
17574.9
16165.4
19464.6
19932.1
19961.2
17343.4
18924.2
18574.1
21350.6
18594.6
19823.1
20844.4
19640.2
17735.4
19813.6
22160
20664.3
17877.4
20906.5
21164.1
21374.4
22952.3
21343.5
23899.3
22392.9
18274.1
22786.7
22321.5
17842.2
16373.5
15993.8
16446.1
17729
16643
16196.7
18252.1
17570.4
15836.8

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68074&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68074&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68074&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'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 series2
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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.202397047078211
-12-0.350831242606504
-110.373426007128021
-10-0.072244781503292
-9-0.3798621399352
-80.617762168232233
-7-0.391201319981327
-6-0.0318707428000392
-50.265953545814698
-4-0.194407628735053
-3-0.0921799147960894
-20.281947884395629
-1-0.373415199875469
00.252024612061428
1-0.0567560937078252
2-0.119399364007826
30.13221983384935
40.163363823537853
5-0.313065036239981
60.232672330230701
70.0310780042500854
8-0.123221902149030
90.139619956553638
10-0.0844530720161654
11-0.0231622429101256
120.206896661089038
13-0.240910069281144

\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 & 2 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.202397047078211 \tabularnewline
-12 & -0.350831242606504 \tabularnewline
-11 & 0.373426007128021 \tabularnewline
-10 & -0.072244781503292 \tabularnewline
-9 & -0.3798621399352 \tabularnewline
-8 & 0.617762168232233 \tabularnewline
-7 & -0.391201319981327 \tabularnewline
-6 & -0.0318707428000392 \tabularnewline
-5 & 0.265953545814698 \tabularnewline
-4 & -0.194407628735053 \tabularnewline
-3 & -0.0921799147960894 \tabularnewline
-2 & 0.281947884395629 \tabularnewline
-1 & -0.373415199875469 \tabularnewline
0 & 0.252024612061428 \tabularnewline
1 & -0.0567560937078252 \tabularnewline
2 & -0.119399364007826 \tabularnewline
3 & 0.13221983384935 \tabularnewline
4 & 0.163363823537853 \tabularnewline
5 & -0.313065036239981 \tabularnewline
6 & 0.232672330230701 \tabularnewline
7 & 0.0310780042500854 \tabularnewline
8 & -0.123221902149030 \tabularnewline
9 & 0.139619956553638 \tabularnewline
10 & -0.0844530720161654 \tabularnewline
11 & -0.0231622429101256 \tabularnewline
12 & 0.206896661089038 \tabularnewline
13 & -0.240910069281144 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68074&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]2[/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]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]0.202397047078211[/C][/ROW]
[ROW][C]-12[/C][C]-0.350831242606504[/C][/ROW]
[ROW][C]-11[/C][C]0.373426007128021[/C][/ROW]
[ROW][C]-10[/C][C]-0.072244781503292[/C][/ROW]
[ROW][C]-9[/C][C]-0.3798621399352[/C][/ROW]
[ROW][C]-8[/C][C]0.617762168232233[/C][/ROW]
[ROW][C]-7[/C][C]-0.391201319981327[/C][/ROW]
[ROW][C]-6[/C][C]-0.0318707428000392[/C][/ROW]
[ROW][C]-5[/C][C]0.265953545814698[/C][/ROW]
[ROW][C]-4[/C][C]-0.194407628735053[/C][/ROW]
[ROW][C]-3[/C][C]-0.0921799147960894[/C][/ROW]
[ROW][C]-2[/C][C]0.281947884395629[/C][/ROW]
[ROW][C]-1[/C][C]-0.373415199875469[/C][/ROW]
[ROW][C]0[/C][C]0.252024612061428[/C][/ROW]
[ROW][C]1[/C][C]-0.0567560937078252[/C][/ROW]
[ROW][C]2[/C][C]-0.119399364007826[/C][/ROW]
[ROW][C]3[/C][C]0.13221983384935[/C][/ROW]
[ROW][C]4[/C][C]0.163363823537853[/C][/ROW]
[ROW][C]5[/C][C]-0.313065036239981[/C][/ROW]
[ROW][C]6[/C][C]0.232672330230701[/C][/ROW]
[ROW][C]7[/C][C]0.0310780042500854[/C][/ROW]
[ROW][C]8[/C][C]-0.123221902149030[/C][/ROW]
[ROW][C]9[/C][C]0.139619956553638[/C][/ROW]
[ROW][C]10[/C][C]-0.0844530720161654[/C][/ROW]
[ROW][C]11[/C][C]-0.0231622429101256[/C][/ROW]
[ROW][C]12[/C][C]0.206896661089038[/C][/ROW]
[ROW][C]13[/C][C]-0.240910069281144[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68074&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68074&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 series2
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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.202397047078211
-12-0.350831242606504
-110.373426007128021
-10-0.072244781503292
-9-0.3798621399352
-80.617762168232233
-7-0.391201319981327
-6-0.0318707428000392
-50.265953545814698
-4-0.194407628735053
-3-0.0921799147960894
-20.281947884395629
-1-0.373415199875469
00.252024612061428
1-0.0567560937078252
2-0.119399364007826
30.13221983384935
40.163363823537853
5-0.313065036239981
60.232672330230701
70.0310780042500854
8-0.123221902149030
90.139619956553638
10-0.0844530720161654
11-0.0231622429101256
120.206896661089038
13-0.240910069281144


Figures (Output of Computation)

Input Parameters & R Code

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