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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 computationMon, 01 Dec 2008 12:15:28 -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/2008/Dec/01/t12281589674vk0166mim1qtrd.htm/, Retrieved Thu, 01 May 2025 08:06:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27203, Retrieved Thu, 01 May 2025 08:06:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact345

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RM D  [Standard Deviation-Mean Plot] [Opdracht 1 - Blok...] [2008-11-26 22:10:36] [8094ad203a218aaca2d1cea2c78c2d6e]
-   P     [Standard Deviation-Mean Plot] [Q5- Airline] [2008-11-28 13:14:59] [e5d91604aae608e98a8ea24759233f66]
F RMPD      [Cross Correlation Function] [Q7-random walk (1)] [2008-12-01 19:13:02] [e5d91604aae608e98a8ea24759233f66]
F   PD          [Cross Correlation Function] [Q7-random walk (2)] [2008-12-01 19:15:28] [55ca0ca4a201c9689dcf5fae352c92eb] [Current]
Feedback Forum
2008-12-07 13:07:22 [Kevin Neelen] [reply] 
De studente heeft niet exact ingegeven wat er moest ingegeven worden. Hierbij wordt het volgende ingegeven:
Tijdreeks X: Lambda = -1,7, d = 1 en D = 1
Tijdreeks Y: Lambda = -2, d = 0 en D = 1
Seasonal periode = 12
Hierbij onze eigen link voor de berekening: http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/28/t1227908760k5m0pln7wljyewd.htm
Wanneer we de ideale waarden uit Q8 voor Lambda, d en D in de mate van het mogelijke invoeren bij de parameterwaarden zien we dat de bekomen cross correlatiewaarden in veel grotere mate binnen het betrouwbaarheidsinterval vallen in vergelijking met Q7. Slechts 3 waarnemingen vallen hierbuiten, tegenover 13 in Q7. Een fikse verbetering dus.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.21
1.74
1.76
1.48
1.04
1.62
1.49
1.79
1.8
1.58
1.86
1.74
1.59
1.26
1.13
1.92
2.61
2.26
2.41
2.26
2.03
2.86
2.55
2.27
2.26
2.57
3.07
2.76
2.51
2.87
3.14
3.11
3.16
2.47
2.57
2.89
2.63
2.38
1.69
1.96
2.19
1.87
1.6
1.63
1.22
1.21
1.49
1.64
1.66
1.77
1.82
1.78
1.28
1.29
1.37
1.12
1.51
2.24
2.94
3.09
Dataseries Y:
Download CSV
Histogram 
99.29
98.69
107.92
101.03
97.55
103.02
94.08
94.12
115.08
116.48
103.42
112.51
95.55
97.53
119.26
100.94
97.73
115.25
92.8
99.2
118.69
110.12
110.26
112.9
102.17
99.38
116.1
103.77
101.81
113.74
89.67
99.5
122.89
108.61
114.37
110.5
104.08
103.64
121.61
101.14
115.97
120.12
95.97
105.01
124.68
123.89
123.61
114.76
108.75
106.09
123.17
106.16
115.18
120.6
109.48
114.44
121.44
129.48
124.32
112.59

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27203&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27203&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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132






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 series1
krho(Y[t],X[t+k])
-13-0.0735790223161942
-12-0.114527045810392
-110.148468940032901
-10-0.0890355517402608
-9-0.0255894015761481
-80.117036349187308
-7-0.191870547725082
-60.184807429527481
-5-0.0133563806197859
-4-0.0189445820447751
-3-0.0768682728237631
-2-0.10616256791008
-10.215143743648665
0-0.192130415320227
1-0.119569169011108
20.150612399096791
3-0.00432646494811070
40.0642714269912816
50.0176624094909594
6-0.215561157510063
70.104999966840133
80.0550786528933386
90.0265869950809415
10-0.0485780802829517
11-0.192963616043081
120.245854302732223
130.107083978886196

\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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0735790223161942 \tabularnewline
-12 & -0.114527045810392 \tabularnewline
-11 & 0.148468940032901 \tabularnewline
-10 & -0.0890355517402608 \tabularnewline
-9 & -0.0255894015761481 \tabularnewline
-8 & 0.117036349187308 \tabularnewline
-7 & -0.191870547725082 \tabularnewline
-6 & 0.184807429527481 \tabularnewline
-5 & -0.0133563806197859 \tabularnewline
-4 & -0.0189445820447751 \tabularnewline
-3 & -0.0768682728237631 \tabularnewline
-2 & -0.10616256791008 \tabularnewline
-1 & 0.215143743648665 \tabularnewline
0 & -0.192130415320227 \tabularnewline
1 & -0.119569169011108 \tabularnewline
2 & 0.150612399096791 \tabularnewline
3 & -0.00432646494811070 \tabularnewline
4 & 0.0642714269912816 \tabularnewline
5 & 0.0176624094909594 \tabularnewline
6 & -0.215561157510063 \tabularnewline
7 & 0.104999966840133 \tabularnewline
8 & 0.0550786528933386 \tabularnewline
9 & 0.0265869950809415 \tabularnewline
10 & -0.0485780802829517 \tabularnewline
11 & -0.192963616043081 \tabularnewline
12 & 0.245854302732223 \tabularnewline
13 & 0.107083978886196 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27203&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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.0735790223161942[/C][/ROW]
[ROW][C]-12[/C][C]-0.114527045810392[/C][/ROW]
[ROW][C]-11[/C][C]0.148468940032901[/C][/ROW]
[ROW][C]-10[/C][C]-0.0890355517402608[/C][/ROW]
[ROW][C]-9[/C][C]-0.0255894015761481[/C][/ROW]
[ROW][C]-8[/C][C]0.117036349187308[/C][/ROW]
[ROW][C]-7[/C][C]-0.191870547725082[/C][/ROW]
[ROW][C]-6[/C][C]0.184807429527481[/C][/ROW]
[ROW][C]-5[/C][C]-0.0133563806197859[/C][/ROW]
[ROW][C]-4[/C][C]-0.0189445820447751[/C][/ROW]
[ROW][C]-3[/C][C]-0.0768682728237631[/C][/ROW]
[ROW][C]-2[/C][C]-0.10616256791008[/C][/ROW]
[ROW][C]-1[/C][C]0.215143743648665[/C][/ROW]
[ROW][C]0[/C][C]-0.192130415320227[/C][/ROW]
[ROW][C]1[/C][C]-0.119569169011108[/C][/ROW]
[ROW][C]2[/C][C]0.150612399096791[/C][/ROW]
[ROW][C]3[/C][C]-0.00432646494811070[/C][/ROW]
[ROW][C]4[/C][C]0.0642714269912816[/C][/ROW]
[ROW][C]5[/C][C]0.0176624094909594[/C][/ROW]
[ROW][C]6[/C][C]-0.215561157510063[/C][/ROW]
[ROW][C]7[/C][C]0.104999966840133[/C][/ROW]
[ROW][C]8[/C][C]0.0550786528933386[/C][/ROW]
[ROW][C]9[/C][C]0.0265869950809415[/C][/ROW]
[ROW][C]10[/C][C]-0.0485780802829517[/C][/ROW]
[ROW][C]11[/C][C]-0.192963616043081[/C][/ROW]
[ROW][C]12[/C][C]0.245854302732223[/C][/ROW]
[ROW][C]13[/C][C]0.107083978886196[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27203&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 series1
krho(Y[t],X[t+k])
-13-0.0735790223161942
-12-0.114527045810392
-110.148468940032901
-10-0.0890355517402608
-9-0.0255894015761481
-80.117036349187308
-7-0.191870547725082
-60.184807429527481
-5-0.0133563806197859
-4-0.0189445820447751
-3-0.0768682728237631
-2-0.10616256791008
-10.215143743648665
0-0.192130415320227
1-0.119569169011108
20.150612399096791
3-0.00432646494811070
40.0642714269912816
50.0176624094909594
6-0.215561157510063
70.104999966840133
80.0550786528933386
90.0265869950809415
10-0.0485780802829517
11-0.192963616043081
120.245854302732223
130.107083978886196


Figures (Output of Computation)

Input Parameters & R Code

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