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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 08 Dec 2008 14:06:05 -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/08/t122877050384ypake4x49ieiw.htm/, Retrieved Thu, 16 May 2024 20:45:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31024, Retrieved Thu, 16 May 2024 20:45:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact161

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [Spectral analyse] [2008-12-06 14:44:56] [4300be8b33fd3dcdacd2aa9800ceba23]
-    D  [Spectral Analysis] [Spectral Analyse ...] [2008-12-06 14:59:38] [4300be8b33fd3dcdacd2aa9800ceba23]
- RMPD    [Kendall tau Correlation Matrix] [Kendall tau corre...] [2008-12-06 16:31:25] [4300be8b33fd3dcdacd2aa9800ceba23]
- RMPD        [Cross Correlation Function] [cross correlation...] [2008-12-08 21:06:05] [6912578025c824de531bc660dd61b996] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109
109
109.2
113.3
112.3
112.3
116.3
118.3
119.4
119.4
119.4
120.1
121.7
123.7
123.7
128.5
127.1
122.6
119.8
122.7
123.4
123.8
121.8
121.2
121.2
121.2
121.2
129.6
131
131
129.8
129.8
134.9
131.2
127.1
130.5
130.5
131.7
131.7
131.7
131.7
128.7
125
124.5
123
122.8
123.1
124.8
126.9
131.7
136.8
143.7
150.1
152.7
152.6
150.5
154.9
158
158.1
160.6
160.6
Dataseries Y:
Download CSV
Histogram 
99.2
99.5
99.3
99.9
100
100.3
100.5
100.7
100.9
100.8
100.9
101
100.3
100.1
99.8
99.9
99.9
100.2
99.7
100.4
100.9
101.3
101.4
101.3
100.9
100.9
100.9
101.1
101.1
101.3
101.8
102.9
103.2
103.3
104.5
105
104.9
104.9
105.4
106
105.7
105.9
106.2
106.4
106.9
107.3
107.9
109.2
110.2
110.2
110.5
110.6
110.8
111.3
111.1
111.2
111.2
111.1
111.5
112.1
111.4

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31024&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31024&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31024&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'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])
-140.182111221211492
-130.18230357850595
-120.187701140699791
-110.197709401860484
-100.218944996426953
-90.255192424262135
-80.306733155418712
-70.36436478002209
-60.417235355195692
-50.46630783291927
-40.528920107983865
-30.598298639508142
-20.671004452029585
-10.743982556232428
00.818782494290757
10.792892154287839
20.755496118846367
30.720433235097631
40.692568622575429
50.65424984516173
60.60766320060874
70.561494633295839
80.51413244065083
90.46913962755558
100.422760443331276
110.373818842383402
120.327468164529168
130.279706979828803
140.242859218523768

\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 & 0.182111221211492 \tabularnewline
-13 & 0.18230357850595 \tabularnewline
-12 & 0.187701140699791 \tabularnewline
-11 & 0.197709401860484 \tabularnewline
-10 & 0.218944996426953 \tabularnewline
-9 & 0.255192424262135 \tabularnewline
-8 & 0.306733155418712 \tabularnewline
-7 & 0.36436478002209 \tabularnewline
-6 & 0.417235355195692 \tabularnewline
-5 & 0.46630783291927 \tabularnewline
-4 & 0.528920107983865 \tabularnewline
-3 & 0.598298639508142 \tabularnewline
-2 & 0.671004452029585 \tabularnewline
-1 & 0.743982556232428 \tabularnewline
0 & 0.818782494290757 \tabularnewline
1 & 0.792892154287839 \tabularnewline
2 & 0.755496118846367 \tabularnewline
3 & 0.720433235097631 \tabularnewline
4 & 0.692568622575429 \tabularnewline
5 & 0.65424984516173 \tabularnewline
6 & 0.60766320060874 \tabularnewline
7 & 0.561494633295839 \tabularnewline
8 & 0.51413244065083 \tabularnewline
9 & 0.46913962755558 \tabularnewline
10 & 0.422760443331276 \tabularnewline
11 & 0.373818842383402 \tabularnewline
12 & 0.327468164529168 \tabularnewline
13 & 0.279706979828803 \tabularnewline
14 & 0.242859218523768 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31024&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]0.182111221211492[/C][/ROW]
[ROW][C]-13[/C][C]0.18230357850595[/C][/ROW]
[ROW][C]-12[/C][C]0.187701140699791[/C][/ROW]
[ROW][C]-11[/C][C]0.197709401860484[/C][/ROW]
[ROW][C]-10[/C][C]0.218944996426953[/C][/ROW]
[ROW][C]-9[/C][C]0.255192424262135[/C][/ROW]
[ROW][C]-8[/C][C]0.306733155418712[/C][/ROW]
[ROW][C]-7[/C][C]0.36436478002209[/C][/ROW]
[ROW][C]-6[/C][C]0.417235355195692[/C][/ROW]
[ROW][C]-5[/C][C]0.46630783291927[/C][/ROW]
[ROW][C]-4[/C][C]0.528920107983865[/C][/ROW]
[ROW][C]-3[/C][C]0.598298639508142[/C][/ROW]
[ROW][C]-2[/C][C]0.671004452029585[/C][/ROW]
[ROW][C]-1[/C][C]0.743982556232428[/C][/ROW]
[ROW][C]0[/C][C]0.818782494290757[/C][/ROW]
[ROW][C]1[/C][C]0.792892154287839[/C][/ROW]
[ROW][C]2[/C][C]0.755496118846367[/C][/ROW]
[ROW][C]3[/C][C]0.720433235097631[/C][/ROW]
[ROW][C]4[/C][C]0.692568622575429[/C][/ROW]
[ROW][C]5[/C][C]0.65424984516173[/C][/ROW]
[ROW][C]6[/C][C]0.60766320060874[/C][/ROW]
[ROW][C]7[/C][C]0.561494633295839[/C][/ROW]
[ROW][C]8[/C][C]0.51413244065083[/C][/ROW]
[ROW][C]9[/C][C]0.46913962755558[/C][/ROW]
[ROW][C]10[/C][C]0.422760443331276[/C][/ROW]
[ROW][C]11[/C][C]0.373818842383402[/C][/ROW]
[ROW][C]12[/C][C]0.327468164529168[/C][/ROW]
[ROW][C]13[/C][C]0.279706979828803[/C][/ROW]
[ROW][C]14[/C][C]0.242859218523768[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31024&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31024&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])
-140.182111221211492
-130.18230357850595
-120.187701140699791
-110.197709401860484
-100.218944996426953
-90.255192424262135
-80.306733155418712
-70.36436478002209
-60.417235355195692
-50.46630783291927
-40.528920107983865
-30.598298639508142
-20.671004452029585
-10.743982556232428
00.818782494290757
10.792892154287839
20.755496118846367
30.720433235097631
40.692568622575429
50.65424984516173
60.60766320060874
70.561494633295839
80.51413244065083
90.46913962755558
100.422760443331276
110.373818842383402
120.327468164529168
130.279706979828803
140.242859218523768


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) 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')