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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, 24 Dec 2010 15:15:56 +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/24/t1293203616zljh9swnyyxpbfh.htm/, Retrieved Tue, 30 Apr 2024 04:06:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115092, Retrieved Tue, 30 Apr 2024 04:06:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97

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] [paperCCF1] [2010-12-19 14:45:22] [7e261c986c934df955dd3ac53e9d45c6]
-   P     [Cross Correlation Function] [Kristof Nagels] [2010-12-24 15:15:56] [fff0a1ca5ad3b1801f382406d5a383a7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15
14,4
13
13,7
13,6
15,2
12,9
14
14,1
13,2
11,3
13,3
14,4
13,3
11,6
13,2
13,1
14,6
14
14,3
13,8
13,7
11
14,4
15,6
13,7
12,6
13,2
13,3
14,3
14
13,4
13,9
13,7
10,5
14,5
15
13,5
13,5
13,2
13,8
16,2
14,7
13,9
16
14,4
12,3
15,9
15,9
15,5
15,1
14,5
15,1
17,4
16,2
15,6
17,2
14,9
13,8
17,5
16,2
17,5
16,6
16,2
16,6
19,6
15,9
18
18,3
16,3
14,9
18,2
18,4
18,5
16
17,4
17,2
19,6
17,2
18,3
19,3
18,1
16,2
18,4
20,5
19
16,5
18,7
19
19,2
20,5
19,3
20,6
20,1
16,1
20,4
19,7
15,6
14,4
13,7
14,1
15
14,2
13,6
15,4
14,8
12,5
16,2
16,1
16
15,8
15,2
15,7
18,9
17,4
17
19,8
17,7
16
19,6
19,7
Dataseries Y:
Download CSV
Histogram 
6,7
6,7
6,5
6,3
6,3
6,3
6,5
6,6
6,5
6,3
6,3
6,5
7
7,1
7,3
7,3
7,4
7,4
7,3
7,4
7,5
7,7
7,7
7,7
7,7
7,7
7,8
8
8,1
8,1
8,2
8,2
8,2
8,1
8,1
8,2
8,3
8,3
8,4
8,5
8,5
8,4
8
7,9
8,1
8,5
8,8
8,8
8,6
8,3
8,3
8,3
8,4
8,4
8,5
8,6
8,6
8,6
8,6
8,6
8,5
8,4
8,4
8,4
8,5
8,5
8,6
8,6
8,4
8,2
8
8
8
8
7,9
7,9
7,8
7,8
8
7,8
7,4
7,2
7
7
7,2
7,2
7,2
7
6,9
6,8
6,8
6,8
6,9
7,2
7,2
7,2
7,1
7,2
7,3
7,5
7,6
7,7
7,7
7,7
7,8
8
8,1
8,1
8
8,1
8,2
8,3
8,4
8,4
8,4
8,5
8,5
8,6
8,6
8,5
8,5

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115092&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115092&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115092&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'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 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])
-17-0.304400974409538
-16-0.304643946065195
-15-0.313852894310171
-14-0.325282594130842
-13-0.321584045038900
-12-0.314221839231891
-11-0.290924152766133
-10-0.272586965879553
-9-0.263015676193393
-8-0.248519322154600
-7-0.215655853069739
-6-0.181717227355119
-5-0.143076952069853
-4-0.0958086312581583
-3-0.0585408227960881
-2-0.0293345283726595
-10.0195072029249475
00.0726945029801302
10.111178133992929
20.144414326518929
30.164352369942216
40.186970094338627
50.215806700993418
60.254958847804543
70.277917096085298
80.307297330971695
90.336305928116295
100.346688992343205
110.360097879207401
120.380810311971736
130.403229685526885
140.422478038443301
150.423416318385647
160.431680615347403
170.445736411164472

\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
-17 & -0.304400974409538 \tabularnewline
-16 & -0.304643946065195 \tabularnewline
-15 & -0.313852894310171 \tabularnewline
-14 & -0.325282594130842 \tabularnewline
-13 & -0.321584045038900 \tabularnewline
-12 & -0.314221839231891 \tabularnewline
-11 & -0.290924152766133 \tabularnewline
-10 & -0.272586965879553 \tabularnewline
-9 & -0.263015676193393 \tabularnewline
-8 & -0.248519322154600 \tabularnewline
-7 & -0.215655853069739 \tabularnewline
-6 & -0.181717227355119 \tabularnewline
-5 & -0.143076952069853 \tabularnewline
-4 & -0.0958086312581583 \tabularnewline
-3 & -0.0585408227960881 \tabularnewline
-2 & -0.0293345283726595 \tabularnewline
-1 & 0.0195072029249475 \tabularnewline
0 & 0.0726945029801302 \tabularnewline
1 & 0.111178133992929 \tabularnewline
2 & 0.144414326518929 \tabularnewline
3 & 0.164352369942216 \tabularnewline
4 & 0.186970094338627 \tabularnewline
5 & 0.215806700993418 \tabularnewline
6 & 0.254958847804543 \tabularnewline
7 & 0.277917096085298 \tabularnewline
8 & 0.307297330971695 \tabularnewline
9 & 0.336305928116295 \tabularnewline
10 & 0.346688992343205 \tabularnewline
11 & 0.360097879207401 \tabularnewline
12 & 0.380810311971736 \tabularnewline
13 & 0.403229685526885 \tabularnewline
14 & 0.422478038443301 \tabularnewline
15 & 0.423416318385647 \tabularnewline
16 & 0.431680615347403 \tabularnewline
17 & 0.445736411164472 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115092&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]-17[/C][C]-0.304400974409538[/C][/ROW]
[ROW][C]-16[/C][C]-0.304643946065195[/C][/ROW]
[ROW][C]-15[/C][C]-0.313852894310171[/C][/ROW]
[ROW][C]-14[/C][C]-0.325282594130842[/C][/ROW]
[ROW][C]-13[/C][C]-0.321584045038900[/C][/ROW]
[ROW][C]-12[/C][C]-0.314221839231891[/C][/ROW]
[ROW][C]-11[/C][C]-0.290924152766133[/C][/ROW]
[ROW][C]-10[/C][C]-0.272586965879553[/C][/ROW]
[ROW][C]-9[/C][C]-0.263015676193393[/C][/ROW]
[ROW][C]-8[/C][C]-0.248519322154600[/C][/ROW]
[ROW][C]-7[/C][C]-0.215655853069739[/C][/ROW]
[ROW][C]-6[/C][C]-0.181717227355119[/C][/ROW]
[ROW][C]-5[/C][C]-0.143076952069853[/C][/ROW]
[ROW][C]-4[/C][C]-0.0958086312581583[/C][/ROW]
[ROW][C]-3[/C][C]-0.0585408227960881[/C][/ROW]
[ROW][C]-2[/C][C]-0.0293345283726595[/C][/ROW]
[ROW][C]-1[/C][C]0.0195072029249475[/C][/ROW]
[ROW][C]0[/C][C]0.0726945029801302[/C][/ROW]
[ROW][C]1[/C][C]0.111178133992929[/C][/ROW]
[ROW][C]2[/C][C]0.144414326518929[/C][/ROW]
[ROW][C]3[/C][C]0.164352369942216[/C][/ROW]
[ROW][C]4[/C][C]0.186970094338627[/C][/ROW]
[ROW][C]5[/C][C]0.215806700993418[/C][/ROW]
[ROW][C]6[/C][C]0.254958847804543[/C][/ROW]
[ROW][C]7[/C][C]0.277917096085298[/C][/ROW]
[ROW][C]8[/C][C]0.307297330971695[/C][/ROW]
[ROW][C]9[/C][C]0.336305928116295[/C][/ROW]
[ROW][C]10[/C][C]0.346688992343205[/C][/ROW]
[ROW][C]11[/C][C]0.360097879207401[/C][/ROW]
[ROW][C]12[/C][C]0.380810311971736[/C][/ROW]
[ROW][C]13[/C][C]0.403229685526885[/C][/ROW]
[ROW][C]14[/C][C]0.422478038443301[/C][/ROW]
[ROW][C]15[/C][C]0.423416318385647[/C][/ROW]
[ROW][C]16[/C][C]0.431680615347403[/C][/ROW]
[ROW][C]17[/C][C]0.445736411164472[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115092&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115092&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])
-17-0.304400974409538
-16-0.304643946065195
-15-0.313852894310171
-14-0.325282594130842
-13-0.321584045038900
-12-0.314221839231891
-11-0.290924152766133
-10-0.272586965879553
-9-0.263015676193393
-8-0.248519322154600
-7-0.215655853069739
-6-0.181717227355119
-5-0.143076952069853
-4-0.0958086312581583
-3-0.0585408227960881
-2-0.0293345283726595
-10.0195072029249475
00.0726945029801302
10.111178133992929
20.144414326518929
30.164352369942216
40.186970094338627
50.215806700993418
60.254958847804543
70.277917096085298
80.307297330971695
90.336305928116295
100.346688992343205
110.360097879207401
120.380810311971736
130.403229685526885
140.422478038443301
150.423416318385647
160.431680615347403
170.445736411164472


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')