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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 computationSun, 25 Nov 2007 07:21:40 -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/25/t1195999941cnmbbhc3bzcdr94.htm/, Retrieved Sat, 04 May 2024 09:31:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6463, Retrieved Sat, 04 May 2024 09:31:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact257

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] [WS10Q3-a] [2007-11-25 14:21:40] [f15e5fe6fe718a2cea2c195ef11f432f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.3
7
6.6
6.4
6.3
6.4
6.3
6
5.3
5.2
5.1
5.4
5.8
5.6
5.6
5.4
5.4
5.5
5.5
5.3
5.7
5.6
5.5
5.6
5.9
6
7
6.6
6.6
6.3
6.3
6.3
6.3
6.2
6.2
6.3
6.4
6.4
7.8
7.7
7.7
7.7
7.7
7.6
7.5
7.4
7.4
7.5
7.6
7.6
8.1
7.8
8
7.9
7.9
7.8
6.7
6.6
6.6
7.7
7.9
8
7.7
7.5
7.6
7.8
7.8
7.7
7.4
7.5
7.2
7.5
7.6
7.6
7.8
7.7
7.7
8.2
8.2
8.1
7.8
7.8
7.7
6.7
6.7
6.7
7.2
6.9
6.8
7.2
7.1
6.9
6.9
6.7
6.5
6.6
6.6
6.5
6.3
Dataseries Y:
Download CSV
Histogram 
10.7
10.4
10
9.7
9.6
8.7
8.5
8.2
8.3
8
8.1
8.7
9.3
8.9
8.8
8.4
8.4
7.3
7.2
7
7
6.9
6.9
7.1
7.5
7.4
8.9
8.3
8.3
9
8.9
8.8
7.8
7.8
7.8
9.2
9.3
9.2
8.6
8.5
8.5
9
9
8.8
8
7.9
8.1
9.3
9.4
9.4
9.3
9
9.1
9.7
9.7
9.6
8.3
8.2
8.4
10.6
10.9
10.9
9.6
9.3
9.3
9.6
9.5
9.5
9
8.9
9
10.1
10.2
10.2
9.5
9.3
9.3
9.4
9.3
9.1
9
8.9
9
9.8
10
9.8
9.4
9
8.9
9.3
9.1
8.8
8.9
8.7
8.6
9.1
9.3
8.9
8.4

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=6463&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=6463&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6463&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 series1
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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-16-0.093300003133284
-150.0235109855360353
-14-0.0297423313859254
-13-0.0389311584212469
-120.0797764813086734
-110.151036751883210
-100.0336641920567706
-90.193980003086650
-8-0.115918185711050
-70.0496336259517038
-60.0299603605944977
-50.0429716787603198
-4-0.0687731131649893
-3-0.147901725376013
-2-0.0792097068933745
-1-0.0253488778518351
00.395299392197837
10.115693557248201
20.079934863411292
3-0.0710531555172657
4-0.0889087070477067
50.0542085589783774
60.101995789728964
7-0.0024714207262739
8-0.0537080309233077
9-0.176557210346215
10-0.0499190436991305
11-0.103929117414291
120.32658986030962
130.083953174721552
140.113314906807997
15-0.0772851359108368
16-0.0936420221769986

\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 & 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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.093300003133284 \tabularnewline
-15 & 0.0235109855360353 \tabularnewline
-14 & -0.0297423313859254 \tabularnewline
-13 & -0.0389311584212469 \tabularnewline
-12 & 0.0797764813086734 \tabularnewline
-11 & 0.151036751883210 \tabularnewline
-10 & 0.0336641920567706 \tabularnewline
-9 & 0.193980003086650 \tabularnewline
-8 & -0.115918185711050 \tabularnewline
-7 & 0.0496336259517038 \tabularnewline
-6 & 0.0299603605944977 \tabularnewline
-5 & 0.0429716787603198 \tabularnewline
-4 & -0.0687731131649893 \tabularnewline
-3 & -0.147901725376013 \tabularnewline
-2 & -0.0792097068933745 \tabularnewline
-1 & -0.0253488778518351 \tabularnewline
0 & 0.395299392197837 \tabularnewline
1 & 0.115693557248201 \tabularnewline
2 & 0.079934863411292 \tabularnewline
3 & -0.0710531555172657 \tabularnewline
4 & -0.0889087070477067 \tabularnewline
5 & 0.0542085589783774 \tabularnewline
6 & 0.101995789728964 \tabularnewline
7 & -0.0024714207262739 \tabularnewline
8 & -0.0537080309233077 \tabularnewline
9 & -0.176557210346215 \tabularnewline
10 & -0.0499190436991305 \tabularnewline
11 & -0.103929117414291 \tabularnewline
12 & 0.32658986030962 \tabularnewline
13 & 0.083953174721552 \tabularnewline
14 & 0.113314906807997 \tabularnewline
15 & -0.0772851359108368 \tabularnewline
16 & -0.0936420221769986 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6463&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]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]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]-16[/C][C]-0.093300003133284[/C][/ROW]
[ROW][C]-15[/C][C]0.0235109855360353[/C][/ROW]
[ROW][C]-14[/C][C]-0.0297423313859254[/C][/ROW]
[ROW][C]-13[/C][C]-0.0389311584212469[/C][/ROW]
[ROW][C]-12[/C][C]0.0797764813086734[/C][/ROW]
[ROW][C]-11[/C][C]0.151036751883210[/C][/ROW]
[ROW][C]-10[/C][C]0.0336641920567706[/C][/ROW]
[ROW][C]-9[/C][C]0.193980003086650[/C][/ROW]
[ROW][C]-8[/C][C]-0.115918185711050[/C][/ROW]
[ROW][C]-7[/C][C]0.0496336259517038[/C][/ROW]
[ROW][C]-6[/C][C]0.0299603605944977[/C][/ROW]
[ROW][C]-5[/C][C]0.0429716787603198[/C][/ROW]
[ROW][C]-4[/C][C]-0.0687731131649893[/C][/ROW]
[ROW][C]-3[/C][C]-0.147901725376013[/C][/ROW]
[ROW][C]-2[/C][C]-0.0792097068933745[/C][/ROW]
[ROW][C]-1[/C][C]-0.0253488778518351[/C][/ROW]
[ROW][C]0[/C][C]0.395299392197837[/C][/ROW]
[ROW][C]1[/C][C]0.115693557248201[/C][/ROW]
[ROW][C]2[/C][C]0.079934863411292[/C][/ROW]
[ROW][C]3[/C][C]-0.0710531555172657[/C][/ROW]
[ROW][C]4[/C][C]-0.0889087070477067[/C][/ROW]
[ROW][C]5[/C][C]0.0542085589783774[/C][/ROW]
[ROW][C]6[/C][C]0.101995789728964[/C][/ROW]
[ROW][C]7[/C][C]-0.0024714207262739[/C][/ROW]
[ROW][C]8[/C][C]-0.0537080309233077[/C][/ROW]
[ROW][C]9[/C][C]-0.176557210346215[/C][/ROW]
[ROW][C]10[/C][C]-0.0499190436991305[/C][/ROW]
[ROW][C]11[/C][C]-0.103929117414291[/C][/ROW]
[ROW][C]12[/C][C]0.32658986030962[/C][/ROW]
[ROW][C]13[/C][C]0.083953174721552[/C][/ROW]
[ROW][C]14[/C][C]0.113314906807997[/C][/ROW]
[ROW][C]15[/C][C]-0.0772851359108368[/C][/ROW]
[ROW][C]16[/C][C]-0.0936420221769986[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6463&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6463&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 series0
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])
-16-0.093300003133284
-150.0235109855360353
-14-0.0297423313859254
-13-0.0389311584212469
-120.0797764813086734
-110.151036751883210
-100.0336641920567706
-90.193980003086650
-8-0.115918185711050
-70.0496336259517038
-60.0299603605944977
-50.0429716787603198
-4-0.0687731131649893
-3-0.147901725376013
-2-0.0792097068933745
-1-0.0253488778518351
00.395299392197837
10.115693557248201
20.079934863411292
3-0.0710531555172657
4-0.0889087070477067
50.0542085589783774
60.101995789728964
7-0.0024714207262739
8-0.0537080309233077
9-0.176557210346215
10-0.0499190436991305
11-0.103929117414291
120.32658986030962
130.083953174721552
140.113314906807997
15-0.0772851359108368
16-0.0936420221769986


Figures (Output of Computation)

Input Parameters & R Code

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