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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 computationWed, 28 Nov 2007 12:30:10 -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/28/t1196277647nodqpm3m3k89cc8.htm/, Retrieved Thu, 02 May 2024 05:13:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7249, Retrieved Thu, 02 May 2024 05:13:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsYannick Leroy, Nick Vandewalle, Jeroen Goetschalckx, Nick Van Hove, Jef Jacobs, Michiel Van den Broeck
Estimated Impact200

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] [Workshop 4: Q6] [2007-11-28 19:30:10] [9ec4fcc2bfe8b6d942eac6074e595603] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.409
-0.625
-0.211
-0.676
0.274
0.893
-0.544
-0.161
-0.296
0.742
0.495
-0.178
0.313
-0.66
-0.103
-0.463
-0.149
0.865
0.243
-1.022
-0.236
0.72
-0.171
0.576
0.019
0.005
-0.106
-0.667
0.102
0.702
0.066
-0.604
-0.123
0.552
0.083
0.254
0.307
-0.581
0.277
-0.7
0.089
0.245
-0.017
-0.329
-0.167
0.237
0.727
-0.167
0.282
-0.585
-0.057
-0.502
-0.01
0.633
-0.28
-0.311
0.13
1.168
0.09
0.55
Dataseries Y:
Download CSV
Histogram 
7
4
-4
2
2
-2
3
-5
-9
6
1
9
-2
0
-5
2
-11
11
-3
9
0
5
-2
4
3
2
3
4
0
-3
2
-3
6
-1
4
-5
-11
-1
-6
-3
2
-1
-8
-8
-20
-17
24
8
5
0
1
0
-2
-8
5
0
0
-2
-9
-4

Tables (Output of Computation)





Summary of compuational 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 compuational 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=7249&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]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=7249&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7249&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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)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])
-130.03541671990738
-120.0968264799187226
-11-0.0616405819919066
-10-0.0843103751512544
-90.00822790656480326
-80.0641826857670314
-70.0158160729888579
-60.246631187850979
-5-0.0645205632484409
-4-0.00114732661473419
-3-0.00607523326053983
-2-0.0116552484536879
-10.0983805692563056
0-0.105801949207230
1-0.0394652271387970
20.138731845967624
3-0.188192444625995
4-0.116226683844070
50.0428964424753641
6-0.226349866500896
70.117552157354598
8-0.123300347376101
9-0.0394778047496027
10-0.0448678498392193
110.0428031373968160
12-0.171411661280907
130.204518082019571

\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) & 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
-13 & 0.03541671990738 \tabularnewline
-12 & 0.0968264799187226 \tabularnewline
-11 & -0.0616405819919066 \tabularnewline
-10 & -0.0843103751512544 \tabularnewline
-9 & 0.00822790656480326 \tabularnewline
-8 & 0.0641826857670314 \tabularnewline
-7 & 0.0158160729888579 \tabularnewline
-6 & 0.246631187850979 \tabularnewline
-5 & -0.0645205632484409 \tabularnewline
-4 & -0.00114732661473419 \tabularnewline
-3 & -0.00607523326053983 \tabularnewline
-2 & -0.0116552484536879 \tabularnewline
-1 & 0.0983805692563056 \tabularnewline
0 & -0.105801949207230 \tabularnewline
1 & -0.0394652271387970 \tabularnewline
2 & 0.138731845967624 \tabularnewline
3 & -0.188192444625995 \tabularnewline
4 & -0.116226683844070 \tabularnewline
5 & 0.0428964424753641 \tabularnewline
6 & -0.226349866500896 \tabularnewline
7 & 0.117552157354598 \tabularnewline
8 & -0.123300347376101 \tabularnewline
9 & -0.0394778047496027 \tabularnewline
10 & -0.0448678498392193 \tabularnewline
11 & 0.0428031373968160 \tabularnewline
12 & -0.171411661280907 \tabularnewline
13 & 0.204518082019571 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7249&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]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]-13[/C][C]0.03541671990738[/C][/ROW]
[ROW][C]-12[/C][C]0.0968264799187226[/C][/ROW]
[ROW][C]-11[/C][C]-0.0616405819919066[/C][/ROW]
[ROW][C]-10[/C][C]-0.0843103751512544[/C][/ROW]
[ROW][C]-9[/C][C]0.00822790656480326[/C][/ROW]
[ROW][C]-8[/C][C]0.0641826857670314[/C][/ROW]
[ROW][C]-7[/C][C]0.0158160729888579[/C][/ROW]
[ROW][C]-6[/C][C]0.246631187850979[/C][/ROW]
[ROW][C]-5[/C][C]-0.0645205632484409[/C][/ROW]
[ROW][C]-4[/C][C]-0.00114732661473419[/C][/ROW]
[ROW][C]-3[/C][C]-0.00607523326053983[/C][/ROW]
[ROW][C]-2[/C][C]-0.0116552484536879[/C][/ROW]
[ROW][C]-1[/C][C]0.0983805692563056[/C][/ROW]
[ROW][C]0[/C][C]-0.105801949207230[/C][/ROW]
[ROW][C]1[/C][C]-0.0394652271387970[/C][/ROW]
[ROW][C]2[/C][C]0.138731845967624[/C][/ROW]
[ROW][C]3[/C][C]-0.188192444625995[/C][/ROW]
[ROW][C]4[/C][C]-0.116226683844070[/C][/ROW]
[ROW][C]5[/C][C]0.0428964424753641[/C][/ROW]
[ROW][C]6[/C][C]-0.226349866500896[/C][/ROW]
[ROW][C]7[/C][C]0.117552157354598[/C][/ROW]
[ROW][C]8[/C][C]-0.123300347376101[/C][/ROW]
[ROW][C]9[/C][C]-0.0394778047496027[/C][/ROW]
[ROW][C]10[/C][C]-0.0448678498392193[/C][/ROW]
[ROW][C]11[/C][C]0.0428031373968160[/C][/ROW]
[ROW][C]12[/C][C]-0.171411661280907[/C][/ROW]
[ROW][C]13[/C][C]0.204518082019571[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7249&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7249&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)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])
-130.03541671990738
-120.0968264799187226
-11-0.0616405819919066
-10-0.0843103751512544
-90.00822790656480326
-80.0641826857670314
-70.0158160729888579
-60.246631187850979
-5-0.0645205632484409
-4-0.00114732661473419
-3-0.00607523326053983
-2-0.0116552484536879
-10.0983805692563056
0-0.105801949207230
1-0.0394652271387970
20.138731845967624
3-0.188192444625995
4-0.116226683844070
50.0428964424753641
6-0.226349866500896
70.117552157354598
8-0.123300347376101
9-0.0394778047496027
10-0.0448678498392193
110.0428031373968160
12-0.171411661280907
130.204518082019571


Figures (Output of Computation)

Input Parameters & R Code

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