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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 computationMon, 26 Nov 2007 11:31:19 -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/26/t11961013117jxyypldgjsdqx7.htm/, Retrieved Thu, 02 May 2024 15:03:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6616, Retrieved Thu, 02 May 2024 15:03:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184

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] [Opdracht 4 Questi...] [2007-11-26 18:31:19] [cb172450b25aceeff04d58e88e905157] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2.9
2.6
2.7
1.8
1.3
0.9
1.3
1.3
1.3
1.3
1.1
1.4
1.2
1.7
1.8
1.5
1
1.6
1.5
1.8
1.8
1.6
1.9
1.7
1.6
1.3
1.1
1.9
2.6
2.3
2.4
2.2
2
2.9
2.6
2.3
2.3
2.6
3.1
2.8
2.5
2.9
3.1
3.1
3.2
2.5
2.6
2.9
2.6
2.4
1.7
2
2.2
1.9
1.6
1.6
1.2
1.2
1.5
1.6
Dataseries Y:
Download CSV
Histogram 
0.0
0.2
0.5
0.4
0.2
0.0
-0.1
0.1
0.3
0.3
-0.1
0.4
-0.2
0.4
0.6
0.1
-0.1
0.1
-0.1
0.2
0.4
0.1
0.1
0.3
-0.2
0.2
0.6
0.4
0.3
0.0
-0.2
0.2
0.2
0.3
-0.1
0.4
-0.6
0.3
0.6
0.4
0.3
0.1
-0.1
0.3
0.5
0.2
-0.2
0.3
-0.5
0.3
0.5
0.7
0.3
0.1
-0.1
0.1
0.0
0.1
0.1
0.4

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=6616&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=6616&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6616&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 series0
Degree of seasonal differencing (D) of X series0
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])
-14-0.0153840522984341
-130.0536500696310776
-120.0375169314130393
-110.0791268908621234
-100.00276216615929409
-90.0122079844276299
-80.0184543170732490
-70.0544948015494563
-60.0295080602590330
-50.0190121109953047
-4-0.0135924532063486
-3-0.0156241547909325
-20.0251224513948789
-10.0267642333030437
00.108697868695571
10.0245804574018244
20.0300486435441409
30.0027263341774524
40.0156938437634908
5-0.0238508392518821
6-0.0538817078758968
7-0.0720964867398262
80.0110227076109603
90.0479609666243354
100.0282564801688767
110.0124116906551080
12-0.111013686860585
13-0.0915964205430388
140.00518406956188658

\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 & 0 \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
-14 & -0.0153840522984341 \tabularnewline
-13 & 0.0536500696310776 \tabularnewline
-12 & 0.0375169314130393 \tabularnewline
-11 & 0.0791268908621234 \tabularnewline
-10 & 0.00276216615929409 \tabularnewline
-9 & 0.0122079844276299 \tabularnewline
-8 & 0.0184543170732490 \tabularnewline
-7 & 0.0544948015494563 \tabularnewline
-6 & 0.0295080602590330 \tabularnewline
-5 & 0.0190121109953047 \tabularnewline
-4 & -0.0135924532063486 \tabularnewline
-3 & -0.0156241547909325 \tabularnewline
-2 & 0.0251224513948789 \tabularnewline
-1 & 0.0267642333030437 \tabularnewline
0 & 0.108697868695571 \tabularnewline
1 & 0.0245804574018244 \tabularnewline
2 & 0.0300486435441409 \tabularnewline
3 & 0.0027263341774524 \tabularnewline
4 & 0.0156938437634908 \tabularnewline
5 & -0.0238508392518821 \tabularnewline
6 & -0.0538817078758968 \tabularnewline
7 & -0.0720964867398262 \tabularnewline
8 & 0.0110227076109603 \tabularnewline
9 & 0.0479609666243354 \tabularnewline
10 & 0.0282564801688767 \tabularnewline
11 & 0.0124116906551080 \tabularnewline
12 & -0.111013686860585 \tabularnewline
13 & -0.0915964205430388 \tabularnewline
14 & 0.00518406956188658 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6616&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]0[/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]-14[/C][C]-0.0153840522984341[/C][/ROW]
[ROW][C]-13[/C][C]0.0536500696310776[/C][/ROW]
[ROW][C]-12[/C][C]0.0375169314130393[/C][/ROW]
[ROW][C]-11[/C][C]0.0791268908621234[/C][/ROW]
[ROW][C]-10[/C][C]0.00276216615929409[/C][/ROW]
[ROW][C]-9[/C][C]0.0122079844276299[/C][/ROW]
[ROW][C]-8[/C][C]0.0184543170732490[/C][/ROW]
[ROW][C]-7[/C][C]0.0544948015494563[/C][/ROW]
[ROW][C]-6[/C][C]0.0295080602590330[/C][/ROW]
[ROW][C]-5[/C][C]0.0190121109953047[/C][/ROW]
[ROW][C]-4[/C][C]-0.0135924532063486[/C][/ROW]
[ROW][C]-3[/C][C]-0.0156241547909325[/C][/ROW]
[ROW][C]-2[/C][C]0.0251224513948789[/C][/ROW]
[ROW][C]-1[/C][C]0.0267642333030437[/C][/ROW]
[ROW][C]0[/C][C]0.108697868695571[/C][/ROW]
[ROW][C]1[/C][C]0.0245804574018244[/C][/ROW]
[ROW][C]2[/C][C]0.0300486435441409[/C][/ROW]
[ROW][C]3[/C][C]0.0027263341774524[/C][/ROW]
[ROW][C]4[/C][C]0.0156938437634908[/C][/ROW]
[ROW][C]5[/C][C]-0.0238508392518821[/C][/ROW]
[ROW][C]6[/C][C]-0.0538817078758968[/C][/ROW]
[ROW][C]7[/C][C]-0.0720964867398262[/C][/ROW]
[ROW][C]8[/C][C]0.0110227076109603[/C][/ROW]
[ROW][C]9[/C][C]0.0479609666243354[/C][/ROW]
[ROW][C]10[/C][C]0.0282564801688767[/C][/ROW]
[ROW][C]11[/C][C]0.0124116906551080[/C][/ROW]
[ROW][C]12[/C][C]-0.111013686860585[/C][/ROW]
[ROW][C]13[/C][C]-0.0915964205430388[/C][/ROW]
[ROW][C]14[/C][C]0.00518406956188658[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6616&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6616&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 series0
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])
-14-0.0153840522984341
-130.0536500696310776
-120.0375169314130393
-110.0791268908621234
-100.00276216615929409
-90.0122079844276299
-80.0184543170732490
-70.0544948015494563
-60.0295080602590330
-50.0190121109953047
-4-0.0135924532063486
-3-0.0156241547909325
-20.0251224513948789
-10.0267642333030437
00.108697868695571
10.0245804574018244
20.0300486435441409
30.0027263341774524
40.0156938437634908
5-0.0238508392518821
6-0.0538817078758968
7-0.0720964867398262
80.0110227076109603
90.0479609666243354
100.0282564801688767
110.0124116906551080
12-0.111013686860585
13-0.0915964205430388
140.00518406956188658


Figures (Output of Computation)

Input Parameters & R Code

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