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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 computationFri, 19 Dec 2008 08:32:52 -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/19/t1229702213pny850kpn7dxc8s.htm/, Retrieved Wed, 15 May 2024 01:40:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35197, Retrieved Wed, 15 May 2024 01:40:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [] [2008-12-19 15:32:52] [e02910eed3830f1815f587e12f46cbdb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
8.1
8.2
8.3
8.2
8
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
8.6
8.7
8.8
8.5
8.4
8.5
8.7
Dataseries Y:
Download CSV
Histogram 
101.7
101.9
102
102.2
102.4
102.6
102.6
102.5
102.5
102.6
102.7
102.9
103.1
103.2
103.2
103
102.8
102.6
102.4
102.2
101.9
101.6
101.3
101.2
111.7
111.4
111.1
111.1
111.3
111.9
112.4
112.9
113
113
112.7
112.4
112.3
112.5
112.8
113.2
114
114.9
115.6
115.5
115
114.9
115.2
115.4
115
114.6
114.5
114.4
113.9
113.2
112.7
112.6
112.5
112.3
112
111.7
119.2

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35197&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35197&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35197&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'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 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 series0
krho(Y[t],X[t+k])
-13-0.0102223696915182
-120.0910488963501366
-110.110859652695032
-10-0.00413088978663381
-90.0614151893365225
-8-0.0486168873375172
-70.0464283351712503
-6-0.0584681876306023
-5-0.0260562174287218
-4-0.068533857686048
-3-0.0696474542323647
-20.0130016037573301
-10.126007284182075
00.141586567826478
10.0125404369225454
2-0.168019679918916
3-0.376112330586946
4-0.0386432564735195
50.135979361641998
60.367596375271894
70.254078071502374
80.0134012169556428
9-0.248787177222681
10-0.232462647973262
11-0.0629289816076783
12-0.0750317469320726
130.067071910275895

\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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0102223696915182 \tabularnewline
-12 & 0.0910488963501366 \tabularnewline
-11 & 0.110859652695032 \tabularnewline
-10 & -0.00413088978663381 \tabularnewline
-9 & 0.0614151893365225 \tabularnewline
-8 & -0.0486168873375172 \tabularnewline
-7 & 0.0464283351712503 \tabularnewline
-6 & -0.0584681876306023 \tabularnewline
-5 & -0.0260562174287218 \tabularnewline
-4 & -0.068533857686048 \tabularnewline
-3 & -0.0696474542323647 \tabularnewline
-2 & 0.0130016037573301 \tabularnewline
-1 & 0.126007284182075 \tabularnewline
0 & 0.141586567826478 \tabularnewline
1 & 0.0125404369225454 \tabularnewline
2 & -0.168019679918916 \tabularnewline
3 & -0.376112330586946 \tabularnewline
4 & -0.0386432564735195 \tabularnewline
5 & 0.135979361641998 \tabularnewline
6 & 0.367596375271894 \tabularnewline
7 & 0.254078071502374 \tabularnewline
8 & 0.0134012169556428 \tabularnewline
9 & -0.248787177222681 \tabularnewline
10 & -0.232462647973262 \tabularnewline
11 & -0.0629289816076783 \tabularnewline
12 & -0.0750317469320726 \tabularnewline
13 & 0.067071910275895 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35197&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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.0102223696915182[/C][/ROW]
[ROW][C]-12[/C][C]0.0910488963501366[/C][/ROW]
[ROW][C]-11[/C][C]0.110859652695032[/C][/ROW]
[ROW][C]-10[/C][C]-0.00413088978663381[/C][/ROW]
[ROW][C]-9[/C][C]0.0614151893365225[/C][/ROW]
[ROW][C]-8[/C][C]-0.0486168873375172[/C][/ROW]
[ROW][C]-7[/C][C]0.0464283351712503[/C][/ROW]
[ROW][C]-6[/C][C]-0.0584681876306023[/C][/ROW]
[ROW][C]-5[/C][C]-0.0260562174287218[/C][/ROW]
[ROW][C]-4[/C][C]-0.068533857686048[/C][/ROW]
[ROW][C]-3[/C][C]-0.0696474542323647[/C][/ROW]
[ROW][C]-2[/C][C]0.0130016037573301[/C][/ROW]
[ROW][C]-1[/C][C]0.126007284182075[/C][/ROW]
[ROW][C]0[/C][C]0.141586567826478[/C][/ROW]
[ROW][C]1[/C][C]0.0125404369225454[/C][/ROW]
[ROW][C]2[/C][C]-0.168019679918916[/C][/ROW]
[ROW][C]3[/C][C]-0.376112330586946[/C][/ROW]
[ROW][C]4[/C][C]-0.0386432564735195[/C][/ROW]
[ROW][C]5[/C][C]0.135979361641998[/C][/ROW]
[ROW][C]6[/C][C]0.367596375271894[/C][/ROW]
[ROW][C]7[/C][C]0.254078071502374[/C][/ROW]
[ROW][C]8[/C][C]0.0134012169556428[/C][/ROW]
[ROW][C]9[/C][C]-0.248787177222681[/C][/ROW]
[ROW][C]10[/C][C]-0.232462647973262[/C][/ROW]
[ROW][C]11[/C][C]-0.0629289816076783[/C][/ROW]
[ROW][C]12[/C][C]-0.0750317469320726[/C][/ROW]
[ROW][C]13[/C][C]0.067071910275895[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35197&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35197&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 series0
krho(Y[t],X[t+k])
-13-0.0102223696915182
-120.0910488963501366
-110.110859652695032
-10-0.00413088978663381
-90.0614151893365225
-8-0.0486168873375172
-70.0464283351712503
-6-0.0584681876306023
-5-0.0260562174287218
-4-0.068533857686048
-3-0.0696474542323647
-20.0130016037573301
-10.126007284182075
00.141586567826478
10.0125404369225454
2-0.168019679918916
3-0.376112330586946
4-0.0386432564735195
50.135979361641998
60.367596375271894
70.254078071502374
80.0134012169556428
9-0.248787177222681
10-0.232462647973262
11-0.0629289816076783
12-0.0750317469320726
130.067071910275895


Figures (Output of Computation)

Input Parameters & R Code

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