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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 computationSun, 25 Nov 2007 04:22:44 -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/2007/Nov/25/t1195989362q9qqo0iuzop24pn.htm/, Retrieved Sat, 04 May 2024 12:56:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6409, Retrieved Sat, 04 May 2024 12:56:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordscross correlationQ5, Seizoenale differentiatie
Estimated Impact204

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 correllation] [2007-11-25 11:22:44] [374a040e40dd748baa758ef078993f27] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
88,74
88,92
88,77
89,17
89,61
89,52
89,74
89,40
89,36
89,38
89,36
89,29
89,59
89,79
89,86
90,21
90,37
90,19
90,33
90,22
90,42
90,54
90,73
91,02
91,19
91,53
91,88
92,06
92,32
92,67
92,85
92,82
93,46
93,23
93,54
93,29
93,20
93,60
93,81
94,62
95,22
95,38
95,31
95,30
95,57
95,42
95,53
95,33
95,90
96,06
96,31
96,34
96,49
96,22
96,53
96,50
96,77
96,66
96,58
96,63
97,06
97,73
98,01
97,76
97,49
97,77
97,96
98,23
98,51
98,19
98,37
98,31
98,60
98,97
99,11
99,64
100,03
99,98
100,32
100,44
100,51
101,00
100,88
100,55
100,83
101,51
102,16
102,39
102,54
102,85
103,47
103,57
103,69
103,50
103,47
103,45
103,48
103,93
103,89
104,40
104,79
104,77
105,13
105,26
104,96
104,75
105,01
105,15
105,20
105,77
105,78
106,26
106,13
106,12
106,57
106,44
106,54
Dataseries Y:
Download CSV
Histogram 
88,95
88,81
88,90
90,15
90,92
90,78
90,81
89,46
89,22
88,89
89,41
89,59
90,25
90,20
90,27
90,71
91,18
90,66
89,72
88,72
88,91
89,15
89,15
89,08
89,28
89,47
89,53
90,72
90,91
91,38
91,49
90,90
90,93
90,57
91,28
90,83
91,50
91,58
92,49
94,16
95,46
95,80
95,32
95,41
95,35
95,68
95,59
94,96
96,92
96,06
96,59
96,67
97,27
96,38
96,47
96,05
96,76
96,51
96,55
95,97
97,00
97,46
97,90
98,42
98,54
99,00
98,94
99,02
100,07
98,72
98,73
98,04
99,08
99,22
99,57
100,44
100,84
100,75
100,49
99,98
99,96
99,76
100,11
99,79
100,29
101,12
102,65
102,71
103,39
102,80
102,07
102,15
101,21
101,27
101,86
101,65
101,94
102,62
102,71
103,39
104,51
104,09
104,29
104,57
105,39
105,15
106,13
105,46
106,47
106,62
106,52
108,04
107,15
107,32
107,76
107,26
107,89

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6409&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]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=6409&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6409&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 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 series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-170.0454084296893758
-160.0743933466092723
-150.080131833417052
-140.0710793657887826
-130.0777844254455968
-120.0588253707654626
-110.0370140563869829
-100.0517455505382748
-90.0332073169884923
-80.0610173300273235
-70.0779646423926745
-60.0825944093572206
-50.129212915918921
-40.115200013608249
-30.127545115656648
-20.114359312439105
-10.106153770943015
00.00967736052020256
10.0128824772750227
2-0.0091267463991754
30.0243088368880854
40.0504360371026458
50.0560092464860477
60.0652333168138284
70.052961951066636
80.0500735703413403
90.0430972239516172
100.0425663514172597
110.0309378838282633
120.00370492506423922
130.00237265074849346
14-0.0103585704165388
150.0153866154899153
160.0244904464391107
170.0247960700252306

\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 & 1 \tabularnewline
Seasonal Period (s) & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-17 & 0.0454084296893758 \tabularnewline
-16 & 0.0743933466092723 \tabularnewline
-15 & 0.080131833417052 \tabularnewline
-14 & 0.0710793657887826 \tabularnewline
-13 & 0.0777844254455968 \tabularnewline
-12 & 0.0588253707654626 \tabularnewline
-11 & 0.0370140563869829 \tabularnewline
-10 & 0.0517455505382748 \tabularnewline
-9 & 0.0332073169884923 \tabularnewline
-8 & 0.0610173300273235 \tabularnewline
-7 & 0.0779646423926745 \tabularnewline
-6 & 0.0825944093572206 \tabularnewline
-5 & 0.129212915918921 \tabularnewline
-4 & 0.115200013608249 \tabularnewline
-3 & 0.127545115656648 \tabularnewline
-2 & 0.114359312439105 \tabularnewline
-1 & 0.106153770943015 \tabularnewline
0 & 0.00967736052020256 \tabularnewline
1 & 0.0128824772750227 \tabularnewline
2 & -0.0091267463991754 \tabularnewline
3 & 0.0243088368880854 \tabularnewline
4 & 0.0504360371026458 \tabularnewline
5 & 0.0560092464860477 \tabularnewline
6 & 0.0652333168138284 \tabularnewline
7 & 0.052961951066636 \tabularnewline
8 & 0.0500735703413403 \tabularnewline
9 & 0.0430972239516172 \tabularnewline
10 & 0.0425663514172597 \tabularnewline
11 & 0.0309378838282633 \tabularnewline
12 & 0.00370492506423922 \tabularnewline
13 & 0.00237265074849346 \tabularnewline
14 & -0.0103585704165388 \tabularnewline
15 & 0.0153866154899153 \tabularnewline
16 & 0.0244904464391107 \tabularnewline
17 & 0.0247960700252306 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6409&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]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-17[/C][C]0.0454084296893758[/C][/ROW]
[ROW][C]-16[/C][C]0.0743933466092723[/C][/ROW]
[ROW][C]-15[/C][C]0.080131833417052[/C][/ROW]
[ROW][C]-14[/C][C]0.0710793657887826[/C][/ROW]
[ROW][C]-13[/C][C]0.0777844254455968[/C][/ROW]
[ROW][C]-12[/C][C]0.0588253707654626[/C][/ROW]
[ROW][C]-11[/C][C]0.0370140563869829[/C][/ROW]
[ROW][C]-10[/C][C]0.0517455505382748[/C][/ROW]
[ROW][C]-9[/C][C]0.0332073169884923[/C][/ROW]
[ROW][C]-8[/C][C]0.0610173300273235[/C][/ROW]
[ROW][C]-7[/C][C]0.0779646423926745[/C][/ROW]
[ROW][C]-6[/C][C]0.0825944093572206[/C][/ROW]
[ROW][C]-5[/C][C]0.129212915918921[/C][/ROW]
[ROW][C]-4[/C][C]0.115200013608249[/C][/ROW]
[ROW][C]-3[/C][C]0.127545115656648[/C][/ROW]
[ROW][C]-2[/C][C]0.114359312439105[/C][/ROW]
[ROW][C]-1[/C][C]0.106153770943015[/C][/ROW]
[ROW][C]0[/C][C]0.00967736052020256[/C][/ROW]
[ROW][C]1[/C][C]0.0128824772750227[/C][/ROW]
[ROW][C]2[/C][C]-0.0091267463991754[/C][/ROW]
[ROW][C]3[/C][C]0.0243088368880854[/C][/ROW]
[ROW][C]4[/C][C]0.0504360371026458[/C][/ROW]
[ROW][C]5[/C][C]0.0560092464860477[/C][/ROW]
[ROW][C]6[/C][C]0.0652333168138284[/C][/ROW]
[ROW][C]7[/C][C]0.052961951066636[/C][/ROW]
[ROW][C]8[/C][C]0.0500735703413403[/C][/ROW]
[ROW][C]9[/C][C]0.0430972239516172[/C][/ROW]
[ROW][C]10[/C][C]0.0425663514172597[/C][/ROW]
[ROW][C]11[/C][C]0.0309378838282633[/C][/ROW]
[ROW][C]12[/C][C]0.00370492506423922[/C][/ROW]
[ROW][C]13[/C][C]0.00237265074849346[/C][/ROW]
[ROW][C]14[/C][C]-0.0103585704165388[/C][/ROW]
[ROW][C]15[/C][C]0.0153866154899153[/C][/ROW]
[ROW][C]16[/C][C]0.0244904464391107[/C][/ROW]
[ROW][C]17[/C][C]0.0247960700252306[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6409&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6409&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 series1
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-170.0454084296893758
-160.0743933466092723
-150.080131833417052
-140.0710793657887826
-130.0777844254455968
-120.0588253707654626
-110.0370140563869829
-100.0517455505382748
-90.0332073169884923
-80.0610173300273235
-70.0779646423926745
-60.0825944093572206
-50.129212915918921
-40.115200013608249
-30.127545115656648
-20.114359312439105
-10.106153770943015
00.00967736052020256
10.0128824772750227
2-0.0091267463991754
30.0243088368880854
40.0504360371026458
50.0560092464860477
60.0652333168138284
70.052961951066636
80.0500735703413403
90.0430972239516172
100.0425663514172597
110.0309378838282633
120.00370492506423922
130.00237265074849346
14-0.0103585704165388
150.0153866154899153
160.0244904464391107
170.0247960700252306


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 1 ; par5 = 1 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')