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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 computationThu, 29 Nov 2007 11:31:42 -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/29/t1196360469ke06g5198oczj7l.htm/, Retrieved Fri, 03 May 2024 10:23:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7565, Retrieved Fri, 03 May 2024 10:23:17 +0000
QR Codes:

Original text written by user:inducing stationary in time series vraag 6
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172

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 Correlation...] [2007-11-29 18:31:42] [0eafefa7b02d47065fceb6c46f54fbf9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0
0
0
0
0
0
0
0
0
0
0
0
38
43
43
44
45
35
36
36
25
31
35
46
47
40
29
28
29
29
30
26
27
18
15
1
1
2
2
1
-4
1
6
4
-1
-3
-8
-24
-29
-40
-32
-41
-48
Dataseries Y:
Download CSV
Histogram 
0,4
-6,3
0,4
-1,3
0,7
-3,5
2
3,9
7,8
7
-0,9
3
-0,7
8,8
-8,1
2,7
2,5
11,8
-1,5
-7,7
-13,5
-1,6
-1,8
2,3
3,1
-2,5
7,1
-7,5
-4,8
-7,1
2,7
10,5
7,6
2,8
-5,6
-5
-2,9
-5,2
9,7
6,9
9,3
-1,4
1,1
-11,2
-0,5
-8,9
2,4
1,9
0,5
-0,1
-2,8
-1,8
-0,9

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=7565&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=7565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7565&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 series1
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 series0
krho(Y[t],X[t+k])
-130.145929634074783
-120.0974936995548956
-110.125234917267367
-100.0175462010600529
-9-0.233372454331702
-8-0.149503298976788
-7-0.174723928713691
-60.477067026217796
-5-0.0124480426586836
-40.244406561100992
-3-0.366461848678856
-20.190245975056570
-1-0.203579823578106
00.068986872635018
1-0.152684766809848
2-0.00678239105901556
30.256774622098610
40.0616959883025704
50.207358060408050
6-0.484985927987577
70.109595633231839
8-0.155940388043918
90.258112162948511
10-0.111648391256053
11-0.0362527190315584
120.0728302963120403
130.0261149538259898

\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 & 1 \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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.145929634074783 \tabularnewline
-12 & 0.0974936995548956 \tabularnewline
-11 & 0.125234917267367 \tabularnewline
-10 & 0.0175462010600529 \tabularnewline
-9 & -0.233372454331702 \tabularnewline
-8 & -0.149503298976788 \tabularnewline
-7 & -0.174723928713691 \tabularnewline
-6 & 0.477067026217796 \tabularnewline
-5 & -0.0124480426586836 \tabularnewline
-4 & 0.244406561100992 \tabularnewline
-3 & -0.366461848678856 \tabularnewline
-2 & 0.190245975056570 \tabularnewline
-1 & -0.203579823578106 \tabularnewline
0 & 0.068986872635018 \tabularnewline
1 & -0.152684766809848 \tabularnewline
2 & -0.00678239105901556 \tabularnewline
3 & 0.256774622098610 \tabularnewline
4 & 0.0616959883025704 \tabularnewline
5 & 0.207358060408050 \tabularnewline
6 & -0.484985927987577 \tabularnewline
7 & 0.109595633231839 \tabularnewline
8 & -0.155940388043918 \tabularnewline
9 & 0.258112162948511 \tabularnewline
10 & -0.111648391256053 \tabularnewline
11 & -0.0362527190315584 \tabularnewline
12 & 0.0728302963120403 \tabularnewline
13 & 0.0261149538259898 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7565&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]1[/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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]0.145929634074783[/C][/ROW]
[ROW][C]-12[/C][C]0.0974936995548956[/C][/ROW]
[ROW][C]-11[/C][C]0.125234917267367[/C][/ROW]
[ROW][C]-10[/C][C]0.0175462010600529[/C][/ROW]
[ROW][C]-9[/C][C]-0.233372454331702[/C][/ROW]
[ROW][C]-8[/C][C]-0.149503298976788[/C][/ROW]
[ROW][C]-7[/C][C]-0.174723928713691[/C][/ROW]
[ROW][C]-6[/C][C]0.477067026217796[/C][/ROW]
[ROW][C]-5[/C][C]-0.0124480426586836[/C][/ROW]
[ROW][C]-4[/C][C]0.244406561100992[/C][/ROW]
[ROW][C]-3[/C][C]-0.366461848678856[/C][/ROW]
[ROW][C]-2[/C][C]0.190245975056570[/C][/ROW]
[ROW][C]-1[/C][C]-0.203579823578106[/C][/ROW]
[ROW][C]0[/C][C]0.068986872635018[/C][/ROW]
[ROW][C]1[/C][C]-0.152684766809848[/C][/ROW]
[ROW][C]2[/C][C]-0.00678239105901556[/C][/ROW]
[ROW][C]3[/C][C]0.256774622098610[/C][/ROW]
[ROW][C]4[/C][C]0.0616959883025704[/C][/ROW]
[ROW][C]5[/C][C]0.207358060408050[/C][/ROW]
[ROW][C]6[/C][C]-0.484985927987577[/C][/ROW]
[ROW][C]7[/C][C]0.109595633231839[/C][/ROW]
[ROW][C]8[/C][C]-0.155940388043918[/C][/ROW]
[ROW][C]9[/C][C]0.258112162948511[/C][/ROW]
[ROW][C]10[/C][C]-0.111648391256053[/C][/ROW]
[ROW][C]11[/C][C]-0.0362527190315584[/C][/ROW]
[ROW][C]12[/C][C]0.0728302963120403[/C][/ROW]
[ROW][C]13[/C][C]0.0261149538259898[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7565&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 series1
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 series0
krho(Y[t],X[t+k])
-130.145929634074783
-120.0974936995548956
-110.125234917267367
-100.0175462010600529
-9-0.233372454331702
-8-0.149503298976788
-7-0.174723928713691
-60.477067026217796
-5-0.0124480426586836
-40.244406561100992
-3-0.366461848678856
-20.190245975056570
-1-0.203579823578106
00.068986872635018
1-0.152684766809848
2-0.00678239105901556
30.256774622098610
40.0616959883025704
50.207358060408050
6-0.484985927987577
70.109595633231839
8-0.155940388043918
90.258112162948511
10-0.111648391256053
11-0.0362527190315584
120.0728302963120403
130.0261149538259898


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; 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) 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')