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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 computationFri, 10 Dec 2010 14:13:23 +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/10/t1291990577un8ae7kuxwxcjib.htm/, Retrieved Mon, 29 Apr 2024 12:05:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107712, Retrieved Mon, 29 Apr 2024 12:05:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135

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 09:25:48] [b98453cac15ba1066b407e146608df68]
- R  D            [Cross Correlation Function] [Paper/ Cross Corr...] [2010-12-10 14:13:23] [f38914513f1f4d866974b642cdd0baea] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
65,03
61,94
62,68
69,8
70,81
70,9
74,52
73,18
64,33
59,44
59,36
62,16
54,37
59,11
60,55
64,04
63,75
67,29
73,73
72,39
78,86
85,16
94,71
91,29
92,56
94,84
105,12
111,67
125,45
133,69
134,08
117
103,88
77,6
57,55
42,78
41,43
39,15
47,48
49,7
58,79
69,59
64,27
71
69,27
75,47
77,97
74,61
79,55
77,3
81,1
84,65
74,22
75,4
76,03
76,67
Dataseries Y:
Download CSV
Histogram 
1,28
1,28
1,27
1,35
1,37
1,37
1,4
1,4
1,28
1,23
1,23
1,25
1,21
1,22
1,29
1,32
1,36
1,36
1,37
1,32
1,33
1,36
1,42
1,39
1,42
1,4
1,42
1,44
1,49
1,54
1,55
1,47
1,47
1,35
1,2
1,12
1,11
1,15
1,17
1,2
1,24
1,32
1,29
1,34
1,3
1,26
1,31
1,31
1,33
1,32
1,39
1,42
1,44
1,41
1,39
1,38

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=107712&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=107712&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107712&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])
-14-0.472172787344934
-13-0.450133345300848
-12-0.404564463837094
-11-0.365057381864755
-10-0.35385848926046
-9-0.343597018049233
-8-0.323080499543240
-7-0.274606946429378
-6-0.187121370421201
-5-0.0204580249455016
-40.201295096630334
-30.443562820088749
-20.663940484650641
-10.824750624334763
00.89408826177417
10.816536106644442
20.6802857767562
30.503377178986529
40.327616921627024
50.150359717390068
60.0173104256149850
7-0.0726428853737322
8-0.137611952458991
9-0.205410373212643
10-0.238238650277694
11-0.254715598968404
12-0.262641304917106
13-0.269433577969045
14-0.264890677931338

\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 & -0.472172787344934 \tabularnewline
-13 & -0.450133345300848 \tabularnewline
-12 & -0.404564463837094 \tabularnewline
-11 & -0.365057381864755 \tabularnewline
-10 & -0.35385848926046 \tabularnewline
-9 & -0.343597018049233 \tabularnewline
-8 & -0.323080499543240 \tabularnewline
-7 & -0.274606946429378 \tabularnewline
-6 & -0.187121370421201 \tabularnewline
-5 & -0.0204580249455016 \tabularnewline
-4 & 0.201295096630334 \tabularnewline
-3 & 0.443562820088749 \tabularnewline
-2 & 0.663940484650641 \tabularnewline
-1 & 0.824750624334763 \tabularnewline
0 & 0.89408826177417 \tabularnewline
1 & 0.816536106644442 \tabularnewline
2 & 0.6802857767562 \tabularnewline
3 & 0.503377178986529 \tabularnewline
4 & 0.327616921627024 \tabularnewline
5 & 0.150359717390068 \tabularnewline
6 & 0.0173104256149850 \tabularnewline
7 & -0.0726428853737322 \tabularnewline
8 & -0.137611952458991 \tabularnewline
9 & -0.205410373212643 \tabularnewline
10 & -0.238238650277694 \tabularnewline
11 & -0.254715598968404 \tabularnewline
12 & -0.262641304917106 \tabularnewline
13 & -0.269433577969045 \tabularnewline
14 & -0.264890677931338 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107712&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]-0.472172787344934[/C][/ROW]
[ROW][C]-13[/C][C]-0.450133345300848[/C][/ROW]
[ROW][C]-12[/C][C]-0.404564463837094[/C][/ROW]
[ROW][C]-11[/C][C]-0.365057381864755[/C][/ROW]
[ROW][C]-10[/C][C]-0.35385848926046[/C][/ROW]
[ROW][C]-9[/C][C]-0.343597018049233[/C][/ROW]
[ROW][C]-8[/C][C]-0.323080499543240[/C][/ROW]
[ROW][C]-7[/C][C]-0.274606946429378[/C][/ROW]
[ROW][C]-6[/C][C]-0.187121370421201[/C][/ROW]
[ROW][C]-5[/C][C]-0.0204580249455016[/C][/ROW]
[ROW][C]-4[/C][C]0.201295096630334[/C][/ROW]
[ROW][C]-3[/C][C]0.443562820088749[/C][/ROW]
[ROW][C]-2[/C][C]0.663940484650641[/C][/ROW]
[ROW][C]-1[/C][C]0.824750624334763[/C][/ROW]
[ROW][C]0[/C][C]0.89408826177417[/C][/ROW]
[ROW][C]1[/C][C]0.816536106644442[/C][/ROW]
[ROW][C]2[/C][C]0.6802857767562[/C][/ROW]
[ROW][C]3[/C][C]0.503377178986529[/C][/ROW]
[ROW][C]4[/C][C]0.327616921627024[/C][/ROW]
[ROW][C]5[/C][C]0.150359717390068[/C][/ROW]
[ROW][C]6[/C][C]0.0173104256149850[/C][/ROW]
[ROW][C]7[/C][C]-0.0726428853737322[/C][/ROW]
[ROW][C]8[/C][C]-0.137611952458991[/C][/ROW]
[ROW][C]9[/C][C]-0.205410373212643[/C][/ROW]
[ROW][C]10[/C][C]-0.238238650277694[/C][/ROW]
[ROW][C]11[/C][C]-0.254715598968404[/C][/ROW]
[ROW][C]12[/C][C]-0.262641304917106[/C][/ROW]
[ROW][C]13[/C][C]-0.269433577969045[/C][/ROW]
[ROW][C]14[/C][C]-0.264890677931338[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107712&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107712&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])
-14-0.472172787344934
-13-0.450133345300848
-12-0.404564463837094
-11-0.365057381864755
-10-0.35385848926046
-9-0.343597018049233
-8-0.323080499543240
-7-0.274606946429378
-6-0.187121370421201
-5-0.0204580249455016
-40.201295096630334
-30.443562820088749
-20.663940484650641
-10.824750624334763
00.89408826177417
10.816536106644442
20.6802857767562
30.503377178986529
40.327616921627024
50.150359717390068
60.0173104256149850
7-0.0726428853737322
8-0.137611952458991
9-0.205410373212643
10-0.238238650277694
11-0.254715598968404
12-0.262641304917106
13-0.269433577969045
14-0.264890677931338


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')