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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 computationSun, 30 Nov 2008 16:03:03 -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/t1228086249btn4k7qa549y6t2.htm/, Retrieved Sun, 05 May 2024 10:14:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26785, Retrieved Sun, 05 May 2024 10:14:01 +0000
QR Codes:

Original text written by user:goede versie
IsPrivate?No (this computation is public)
User-defined keywordsCross correlation function herproductie
Estimated Impact256

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:05:16] [b98453cac15ba1066b407e146608df68]
F RMPD  [Cross Correlation Function] [Cross correlation...] [2008-11-30 19:09:57] [b635de6fc42b001d22cbe6e730fec936]
-   PD    [Cross Correlation Function] [Cross correlation...] [2008-11-30 19:48:56] [b635de6fc42b001d22cbe6e730fec936]
F   P         [Cross Correlation Function] [Cross correlation...] [2008-11-30 23:03:03] [f4b2017b314c03698059f43b95818e67] [Current]
Feedback Forum
2008-12-05 15:48:17 [Kristof Van Esbroeck] [reply] 
Student geeft op deze vraagstelling een correct antwoord door een herberekening uit te voeren van de gegevens uit Q7.

De analyse en interpretatie van student zijn ook correct. In de Cross Correlatie functie noteren we enkel op -4 een waarde buiten het interval.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.5
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.6
8.2
8.1
8
8.6
8.7
8.8
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.1
8.2
8.1
8.1
7.9
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
Dataseries Y:
Download CSV
Histogram 
9.5
9.1
9
9.3
9.9
9.8
9.4
8.3
8
8.5
10.4
11.1
10.9
9.9
9.2
9.2
9.5
9.6
9.5
9.1
8.9
9
10.1
10.3
10.2
9.6
9.2
9.3
9.4
9.4
9.2
9
9
9
9.8
10
9.9
9.3
9
9
9.1
9.1
9.1
9.2
8.8
8.3
8.4
8.1
7.8
7.9
7.9
8
7.9
7.5
7.2
6.9
6.6
6.7
7.3
7.5

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26785&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26785&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26785&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0.7
Degree of non-seasonal differencing (d) of X series2
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0.3
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0663338958940668
-120.166175750921705
-110.109535219729443
-10-0.0847929834936135
-9-0.191211928639638
-80.0665414045242514
-70.137717633065868
-60.140574395714419
-50.00791773510470005
-4-0.327129477254919
-3-0.194290335089616
-2-0.133615243290591
-10.107219020016250
00.671762316306772
10.244672250503900
2-0.143072859028019
3-0.256990844519610
4-0.268330716670096
5-0.145529970423512
60.154443688699042
70.0957900136850466
80.216768165944211
9-0.0352303484119266
10-0.173891899753229
110.0840295745099596
120.0769667926012133
13-0.120753055465474

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.7 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 2 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 0.3 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0663338958940668 \tabularnewline
-12 & 0.166175750921705 \tabularnewline
-11 & 0.109535219729443 \tabularnewline
-10 & -0.0847929834936135 \tabularnewline
-9 & -0.191211928639638 \tabularnewline
-8 & 0.0665414045242514 \tabularnewline
-7 & 0.137717633065868 \tabularnewline
-6 & 0.140574395714419 \tabularnewline
-5 & 0.00791773510470005 \tabularnewline
-4 & -0.327129477254919 \tabularnewline
-3 & -0.194290335089616 \tabularnewline
-2 & -0.133615243290591 \tabularnewline
-1 & 0.107219020016250 \tabularnewline
0 & 0.671762316306772 \tabularnewline
1 & 0.244672250503900 \tabularnewline
2 & -0.143072859028019 \tabularnewline
3 & -0.256990844519610 \tabularnewline
4 & -0.268330716670096 \tabularnewline
5 & -0.145529970423512 \tabularnewline
6 & 0.154443688699042 \tabularnewline
7 & 0.0957900136850466 \tabularnewline
8 & 0.216768165944211 \tabularnewline
9 & -0.0352303484119266 \tabularnewline
10 & -0.173891899753229 \tabularnewline
11 & 0.0840295745099596 \tabularnewline
12 & 0.0769667926012133 \tabularnewline
13 & -0.120753055465474 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26785&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]0.7[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]2[/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]0.3[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]2[/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]-0.0663338958940668[/C][/ROW]
[ROW][C]-12[/C][C]0.166175750921705[/C][/ROW]
[ROW][C]-11[/C][C]0.109535219729443[/C][/ROW]
[ROW][C]-10[/C][C]-0.0847929834936135[/C][/ROW]
[ROW][C]-9[/C][C]-0.191211928639638[/C][/ROW]
[ROW][C]-8[/C][C]0.0665414045242514[/C][/ROW]
[ROW][C]-7[/C][C]0.137717633065868[/C][/ROW]
[ROW][C]-6[/C][C]0.140574395714419[/C][/ROW]
[ROW][C]-5[/C][C]0.00791773510470005[/C][/ROW]
[ROW][C]-4[/C][C]-0.327129477254919[/C][/ROW]
[ROW][C]-3[/C][C]-0.194290335089616[/C][/ROW]
[ROW][C]-2[/C][C]-0.133615243290591[/C][/ROW]
[ROW][C]-1[/C][C]0.107219020016250[/C][/ROW]
[ROW][C]0[/C][C]0.671762316306772[/C][/ROW]
[ROW][C]1[/C][C]0.244672250503900[/C][/ROW]
[ROW][C]2[/C][C]-0.143072859028019[/C][/ROW]
[ROW][C]3[/C][C]-0.256990844519610[/C][/ROW]
[ROW][C]4[/C][C]-0.268330716670096[/C][/ROW]
[ROW][C]5[/C][C]-0.145529970423512[/C][/ROW]
[ROW][C]6[/C][C]0.154443688699042[/C][/ROW]
[ROW][C]7[/C][C]0.0957900136850466[/C][/ROW]
[ROW][C]8[/C][C]0.216768165944211[/C][/ROW]
[ROW][C]9[/C][C]-0.0352303484119266[/C][/ROW]
[ROW][C]10[/C][C]-0.173891899753229[/C][/ROW]
[ROW][C]11[/C][C]0.0840295745099596[/C][/ROW]
[ROW][C]12[/C][C]0.0769667926012133[/C][/ROW]
[ROW][C]13[/C][C]-0.120753055465474[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26785&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26785&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 series0.7
Degree of non-seasonal differencing (d) of X series2
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0.3
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0663338958940668
-120.166175750921705
-110.109535219729443
-10-0.0847929834936135
-9-0.191211928639638
-80.0665414045242514
-70.137717633065868
-60.140574395714419
-50.00791773510470005
-4-0.327129477254919
-3-0.194290335089616
-2-0.133615243290591
-10.107219020016250
00.671762316306772
10.244672250503900
2-0.143072859028019
3-0.256990844519610
4-0.268330716670096
5-0.145529970423512
60.154443688699042
70.0957900136850466
80.216768165944211
9-0.0352303484119266
10-0.173891899753229
110.0840295745099596
120.0769667926012133
13-0.120753055465474


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.7 ; par2 = 2 ; par3 = 1 ; par4 = 12 ; par5 = 0.3 ; par6 = 2 ; par7 = 1 ;
Parameters (R input):
par1 = 0.7 ; par2 = 2 ; par3 = 1 ; par4 = 12 ; par5 = 0.3 ; par6 = 2 ; 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')