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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 computationTue, 02 Dec 2008 09:22:32 -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/02/t1228235056kbpyi2rc7ob9lif.htm/, Retrieved Sun, 19 May 2024 09:39:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28029, Retrieved Sun, 19 May 2024 09:39:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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] [] [2008-12-02 16:22:32] [cdc575afe547a0c8f1ab59a46ec2fd93] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.5
7.2
6.9
6.7
6.4
6.3
6.8
7.3
7.1
7.1
6.8
6.5
6.3
6.1
6.1
6.3
6.3
6
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8.0
8.1
8.2
8.3
8.2
8.0
7.9
7.6
7.6
8.2
8.3
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
8.0
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
8.0
8.0
7.9
8.0
7.7
7.2
7.5
7.3
7.0
7.0
7.0
7.2
7.3
7.1
6.8
6.6
6.2
6.2
6.8
6.9
6.8
Dataseries Y:
Download CSV
Histogram 
15.9
15.5
15.3
14.5
14.4
14.7
19.1
21.6
20.2
17.9
15.7
14.5
14.1
13.9
14.2
15.3
15.4
15.2
16.5
18.2
18.6
21.0
19.2
18.7
18.4
17.8
17.2
16.2
15.5
15.3
18.3
19.2
19.0
18.7
18.1
18.5
21.1
21.0
20.4
19.5
18.6
18.8
23.7
24.8
25.0
23.6
22.3
21.8
20.8
19.7
18.3
17.4
17.0
18.1
23.9
25.6
25.3
23.6
21.9
21.4
20.6
20.5
20.2
20.6
19.7
19.3
22.8
23.5
23.8
22.6
22.0
21.7
20.7
20.2
19.1
19.5
18.7
18.6
22.2
23.2
23.5
21.3
20.0
18.7
18.9
18.3
18.4
19.9
19.2
18.5
20.9
20.5
19.4
18.1
17.0
17.0
17.3
16.7
15.5
15.3
13.7
14.1
17.3
18.1
18.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28029&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]1 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=28029&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28029&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 time1 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)1
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])
-170.0802595590891862
-160.0815222800198594
-150.0338866381101685
-14-0.0377228764581296
-13-0.215934016716655
-12-0.0590631939919997
-110.00501528095555678
-10-0.00986691211348864
-9-0.000156746737861351
-8-0.0587946176859704
-7-0.0661517380256587
-60.0429690600346504
-50.153636559556805
-40.169622164175928
-30.0965896453029976
-2-0.0951824045608657
-1-0.354484336322804
0-0.139891744874372
10.00232936659532597
20.0505591444569853
30.0712492599548629
4-0.0226811376023325
5-0.0487027698429024
60.0232817321704906
70.0892557211353638
80.111229559886839
90.0917112813369131
10-0.0347125088327709
11-0.211299879222503
12-0.0572788381493667
130.0124235974124493
140.0386401512569971
150.0167287710120120
16-0.0877051709812938
17-0.0971893698965003

\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) & 1 \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 & 0.0802595590891862 \tabularnewline
-16 & 0.0815222800198594 \tabularnewline
-15 & 0.0338866381101685 \tabularnewline
-14 & -0.0377228764581296 \tabularnewline
-13 & -0.215934016716655 \tabularnewline
-12 & -0.0590631939919997 \tabularnewline
-11 & 0.00501528095555678 \tabularnewline
-10 & -0.00986691211348864 \tabularnewline
-9 & -0.000156746737861351 \tabularnewline
-8 & -0.0587946176859704 \tabularnewline
-7 & -0.0661517380256587 \tabularnewline
-6 & 0.0429690600346504 \tabularnewline
-5 & 0.153636559556805 \tabularnewline
-4 & 0.169622164175928 \tabularnewline
-3 & 0.0965896453029976 \tabularnewline
-2 & -0.0951824045608657 \tabularnewline
-1 & -0.354484336322804 \tabularnewline
0 & -0.139891744874372 \tabularnewline
1 & 0.00232936659532597 \tabularnewline
2 & 0.0505591444569853 \tabularnewline
3 & 0.0712492599548629 \tabularnewline
4 & -0.0226811376023325 \tabularnewline
5 & -0.0487027698429024 \tabularnewline
6 & 0.0232817321704906 \tabularnewline
7 & 0.0892557211353638 \tabularnewline
8 & 0.111229559886839 \tabularnewline
9 & 0.0917112813369131 \tabularnewline
10 & -0.0347125088327709 \tabularnewline
11 & -0.211299879222503 \tabularnewline
12 & -0.0572788381493667 \tabularnewline
13 & 0.0124235974124493 \tabularnewline
14 & 0.0386401512569971 \tabularnewline
15 & 0.0167287710120120 \tabularnewline
16 & -0.0877051709812938 \tabularnewline
17 & -0.0971893698965003 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28029&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]1[/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]0.0802595590891862[/C][/ROW]
[ROW][C]-16[/C][C]0.0815222800198594[/C][/ROW]
[ROW][C]-15[/C][C]0.0338866381101685[/C][/ROW]
[ROW][C]-14[/C][C]-0.0377228764581296[/C][/ROW]
[ROW][C]-13[/C][C]-0.215934016716655[/C][/ROW]
[ROW][C]-12[/C][C]-0.0590631939919997[/C][/ROW]
[ROW][C]-11[/C][C]0.00501528095555678[/C][/ROW]
[ROW][C]-10[/C][C]-0.00986691211348864[/C][/ROW]
[ROW][C]-9[/C][C]-0.000156746737861351[/C][/ROW]
[ROW][C]-8[/C][C]-0.0587946176859704[/C][/ROW]
[ROW][C]-7[/C][C]-0.0661517380256587[/C][/ROW]
[ROW][C]-6[/C][C]0.0429690600346504[/C][/ROW]
[ROW][C]-5[/C][C]0.153636559556805[/C][/ROW]
[ROW][C]-4[/C][C]0.169622164175928[/C][/ROW]
[ROW][C]-3[/C][C]0.0965896453029976[/C][/ROW]
[ROW][C]-2[/C][C]-0.0951824045608657[/C][/ROW]
[ROW][C]-1[/C][C]-0.354484336322804[/C][/ROW]
[ROW][C]0[/C][C]-0.139891744874372[/C][/ROW]
[ROW][C]1[/C][C]0.00232936659532597[/C][/ROW]
[ROW][C]2[/C][C]0.0505591444569853[/C][/ROW]
[ROW][C]3[/C][C]0.0712492599548629[/C][/ROW]
[ROW][C]4[/C][C]-0.0226811376023325[/C][/ROW]
[ROW][C]5[/C][C]-0.0487027698429024[/C][/ROW]
[ROW][C]6[/C][C]0.0232817321704906[/C][/ROW]
[ROW][C]7[/C][C]0.0892557211353638[/C][/ROW]
[ROW][C]8[/C][C]0.111229559886839[/C][/ROW]
[ROW][C]9[/C][C]0.0917112813369131[/C][/ROW]
[ROW][C]10[/C][C]-0.0347125088327709[/C][/ROW]
[ROW][C]11[/C][C]-0.211299879222503[/C][/ROW]
[ROW][C]12[/C][C]-0.0572788381493667[/C][/ROW]
[ROW][C]13[/C][C]0.0124235974124493[/C][/ROW]
[ROW][C]14[/C][C]0.0386401512569971[/C][/ROW]
[ROW][C]15[/C][C]0.0167287710120120[/C][/ROW]
[ROW][C]16[/C][C]-0.0877051709812938[/C][/ROW]
[ROW][C]17[/C][C]-0.0971893698965003[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28029&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28029&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)1
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])
-170.0802595590891862
-160.0815222800198594
-150.0338866381101685
-14-0.0377228764581296
-13-0.215934016716655
-12-0.0590631939919997
-110.00501528095555678
-10-0.00986691211348864
-9-0.000156746737861351
-8-0.0587946176859704
-7-0.0661517380256587
-60.0429690600346504
-50.153636559556805
-40.169622164175928
-30.0965896453029976
-2-0.0951824045608657
-1-0.354484336322804
0-0.139891744874372
10.00232936659532597
20.0505591444569853
30.0712492599548629
4-0.0226811376023325
5-0.0487027698429024
60.0232817321704906
70.0892557211353638
80.111229559886839
90.0917112813369131
10-0.0347125088327709
11-0.211299879222503
12-0.0572788381493667
130.0124235974124493
140.0386401512569971
150.0167287710120120
16-0.0877051709812938
17-0.0971893698965003


Figures (Output of Computation)

Input Parameters & R Code

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