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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, 14 Dec 2010 17:53:52 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t12923491083zfefmvb6qpzvt0.htm/, Retrieved Thu, 02 May 2024 18:04:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109956, Retrieved Thu, 02 May 2024 18:04:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Ws4 part 1.1 s090...] [2009-10-27 21:56:53] [e0fc65a5811681d807296d590d5b45de]
-  M D    [Bivariate Explorative Data Analysis] [Paper; bivariate ...] [2009-12-19 19:10:37] [e0fc65a5811681d807296d590d5b45de]
- RMPD      [Cross Correlation Function] [cross correlation...] [2010-12-08 19:50:23] [74be16979710d4c4e7c6647856088456]
-   PD        [Cross Correlation Function] [] [2010-12-09 09:22:26] [b98453cac15ba1066b407e146608df68]
- R PD            [Cross Correlation Function] [CCF 3] [2010-12-14 17:53:52] [de8ccb310fbbdc3d90ae577a3e011cf9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1606
1634
2013
1654
1003
1029
1052
1653
1918
1926
1862
1816
1712
1646
1555
1402
1047
891
940
1372
2012
1879
1667
1856
1771
1721
1773
1507
1033
1011
1111
1736
1865
2078
1947
1428
1500
1950
1591
1613
1077
880
1128
1320
1692
1575
1478
1500
1368
1563
1424
1274
1047
1049
1069
981
1540
1559
1459
1559
Dataseries Y:
Download CSV
Histogram 
16
29
22
30
20
39
18
9,6
10,2
20,2
50
120
19,8
18
3
11
15
27
28
14
5,6
6,5
8,5
87,9
5,8
25,2
7,5
13,7
34
17
9
9,2
5
24
40
86,5
0,54
14
4,8
28
16
5,8
16
9,1
6
17
26
99,6
41
72
23
42
40
18
45
18
2
10
13,6
160

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'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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109956&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109956&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109956&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0488788572488967
-12-0.0998087221778246
-110.0207981266521907
-10-0.103857956893088
-9-0.0768015949673424
-80.0351199803799179
-7-0.149113048330121
-6-0.0886023672034659
-5-0.193016327640973
-4-0.250140282101403
-3-0.180079032630057
-2-0.0940882179006748
-10.0870328758247202
00.0990369345980676
1-0.266545446257949
2-0.2122221350283
3-0.106437579542732
40.034913436337988
50.246431911516473
6-0.0542817744560465
7-0.240141527195017
8-0.0080426654131642
9-0.0613692395681638
10-0.0882018125679415
11-0.0277258864842913
12-0.177837607836941
13-0.00952212788594813

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 0 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0488788572488967 \tabularnewline
-12 & -0.0998087221778246 \tabularnewline
-11 & 0.0207981266521907 \tabularnewline
-10 & -0.103857956893088 \tabularnewline
-9 & -0.0768015949673424 \tabularnewline
-8 & 0.0351199803799179 \tabularnewline
-7 & -0.149113048330121 \tabularnewline
-6 & -0.0886023672034659 \tabularnewline
-5 & -0.193016327640973 \tabularnewline
-4 & -0.250140282101403 \tabularnewline
-3 & -0.180079032630057 \tabularnewline
-2 & -0.0940882179006748 \tabularnewline
-1 & 0.0870328758247202 \tabularnewline
0 & 0.0990369345980676 \tabularnewline
1 & -0.266545446257949 \tabularnewline
2 & -0.2122221350283 \tabularnewline
3 & -0.106437579542732 \tabularnewline
4 & 0.034913436337988 \tabularnewline
5 & 0.246431911516473 \tabularnewline
6 & -0.0542817744560465 \tabularnewline
7 & -0.240141527195017 \tabularnewline
8 & -0.0080426654131642 \tabularnewline
9 & -0.0613692395681638 \tabularnewline
10 & -0.0882018125679415 \tabularnewline
11 & -0.0277258864842913 \tabularnewline
12 & -0.177837607836941 \tabularnewline
13 & -0.00952212788594813 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109956&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]0[/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]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]0[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.0488788572488967[/C][/ROW]
[ROW][C]-12[/C][C]-0.0998087221778246[/C][/ROW]
[ROW][C]-11[/C][C]0.0207981266521907[/C][/ROW]
[ROW][C]-10[/C][C]-0.103857956893088[/C][/ROW]
[ROW][C]-9[/C][C]-0.0768015949673424[/C][/ROW]
[ROW][C]-8[/C][C]0.0351199803799179[/C][/ROW]
[ROW][C]-7[/C][C]-0.149113048330121[/C][/ROW]
[ROW][C]-6[/C][C]-0.0886023672034659[/C][/ROW]
[ROW][C]-5[/C][C]-0.193016327640973[/C][/ROW]
[ROW][C]-4[/C][C]-0.250140282101403[/C][/ROW]
[ROW][C]-3[/C][C]-0.180079032630057[/C][/ROW]
[ROW][C]-2[/C][C]-0.0940882179006748[/C][/ROW]
[ROW][C]-1[/C][C]0.0870328758247202[/C][/ROW]
[ROW][C]0[/C][C]0.0990369345980676[/C][/ROW]
[ROW][C]1[/C][C]-0.266545446257949[/C][/ROW]
[ROW][C]2[/C][C]-0.2122221350283[/C][/ROW]
[ROW][C]3[/C][C]-0.106437579542732[/C][/ROW]
[ROW][C]4[/C][C]0.034913436337988[/C][/ROW]
[ROW][C]5[/C][C]0.246431911516473[/C][/ROW]
[ROW][C]6[/C][C]-0.0542817744560465[/C][/ROW]
[ROW][C]7[/C][C]-0.240141527195017[/C][/ROW]
[ROW][C]8[/C][C]-0.0080426654131642[/C][/ROW]
[ROW][C]9[/C][C]-0.0613692395681638[/C][/ROW]
[ROW][C]10[/C][C]-0.0882018125679415[/C][/ROW]
[ROW][C]11[/C][C]-0.0277258864842913[/C][/ROW]
[ROW][C]12[/C][C]-0.177837607836941[/C][/ROW]
[ROW][C]13[/C][C]-0.00952212788594813[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109956&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109956&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 series0
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0488788572488967
-12-0.0998087221778246
-110.0207981266521907
-10-0.103857956893088
-9-0.0768015949673424
-80.0351199803799179
-7-0.149113048330121
-6-0.0886023672034659
-5-0.193016327640973
-4-0.250140282101403
-3-0.180079032630057
-2-0.0940882179006748
-10.0870328758247202
00.0990369345980676
1-0.266545446257949
2-0.2122221350283
3-0.106437579542732
40.034913436337988
50.246431911516473
6-0.0542817744560465
7-0.240141527195017
8-0.0080426654131642
9-0.0613692395681638
10-0.0882018125679415
11-0.0277258864842913
12-0.177837607836941
13-0.00952212788594813


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ; par2 = none ; par4 = no ;
Parameters (R input):
par1 = 0.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 0.0 ; par6 = 0 ; 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')