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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 10:54:40 -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/2008/Dec/02/t1228240567oofnctoyv2scs9s.htm/, Retrieved Fri, 17 May 2024 06:36:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28150, Retrieved Fri, 17 May 2024 06:36:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138

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 17:54:40] [e02910eed3830f1815f587e12f46cbdb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
107.1
110.7
117.1
118.7
126.5
127.5
134.6
131.8
135.9
142.7
141.7
153.4
145.0
137.7
148.3
152.2
169.4
168.6
161.1
174.1
179.0
190.6
190.0
181.6
174.8
180.5
196.8
193.8
197.0
216.3
221.4
217.9
229.7
227.4
204.2
196.6
198.8
207.5
190.7
201.6
210.5
223.5
223.8
231.2
244.0
234.7
250.2
265.7
287.6
283.3
295.4
312.3
333.8
347.7
383.2
407.1
413.6
362.7
321.9
239.4
Dataseries Y:
Download CSV
Histogram 
107.1
110.7
117.1
118.7
126.5
127.5
134.6
131.8
135.9
142.7
141.7
153.4
145.0
137.7
148.3
152.2
169.4
168.6
161.1
174.1
179.0
190.6
190.0
181.6
174.8
180.5
196.8
193.8
197.0
216.3
221.4
217.9
229.7
227.4
204.2
196.6
198.8
207.5
190.7
201.6
210.5
223.5
223.8
231.2
244.0
234.7
250.2
265.7
287.6
283.3
295.4
312.3
333.8
347.7
383.2
407.1
413.6
362.7
321.9
239.4

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=28150&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=28150&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28150&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 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])
-140.150089394926911
-130.185188995271011
-120.223392073633954
-110.263218198470475
-100.308424983869126
-90.353939498376474
-80.408823788559452
-70.468824811204089
-60.531292385307913
-50.605252904465295
-40.691171921164578
-30.784401256514189
-20.876805739965778
-10.953573594122783
01
10.953573594122783
20.876805739965778
30.784401256514189
40.691171921164578
50.605252904465295
60.531292385307913
70.468824811204089
80.408823788559452
90.353939498376474
100.308424983869126
110.263218198470475
120.223392073633954
130.185188995271011
140.150089394926911

\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 & 0.150089394926911 \tabularnewline
-13 & 0.185188995271011 \tabularnewline
-12 & 0.223392073633954 \tabularnewline
-11 & 0.263218198470475 \tabularnewline
-10 & 0.308424983869126 \tabularnewline
-9 & 0.353939498376474 \tabularnewline
-8 & 0.408823788559452 \tabularnewline
-7 & 0.468824811204089 \tabularnewline
-6 & 0.531292385307913 \tabularnewline
-5 & 0.605252904465295 \tabularnewline
-4 & 0.691171921164578 \tabularnewline
-3 & 0.784401256514189 \tabularnewline
-2 & 0.876805739965778 \tabularnewline
-1 & 0.953573594122783 \tabularnewline
0 & 1 \tabularnewline
1 & 0.953573594122783 \tabularnewline
2 & 0.876805739965778 \tabularnewline
3 & 0.784401256514189 \tabularnewline
4 & 0.691171921164578 \tabularnewline
5 & 0.605252904465295 \tabularnewline
6 & 0.531292385307913 \tabularnewline
7 & 0.468824811204089 \tabularnewline
8 & 0.408823788559452 \tabularnewline
9 & 0.353939498376474 \tabularnewline
10 & 0.308424983869126 \tabularnewline
11 & 0.263218198470475 \tabularnewline
12 & 0.223392073633954 \tabularnewline
13 & 0.185188995271011 \tabularnewline
14 & 0.150089394926911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28150&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]0.150089394926911[/C][/ROW]
[ROW][C]-13[/C][C]0.185188995271011[/C][/ROW]
[ROW][C]-12[/C][C]0.223392073633954[/C][/ROW]
[ROW][C]-11[/C][C]0.263218198470475[/C][/ROW]
[ROW][C]-10[/C][C]0.308424983869126[/C][/ROW]
[ROW][C]-9[/C][C]0.353939498376474[/C][/ROW]
[ROW][C]-8[/C][C]0.408823788559452[/C][/ROW]
[ROW][C]-7[/C][C]0.468824811204089[/C][/ROW]
[ROW][C]-6[/C][C]0.531292385307913[/C][/ROW]
[ROW][C]-5[/C][C]0.605252904465295[/C][/ROW]
[ROW][C]-4[/C][C]0.691171921164578[/C][/ROW]
[ROW][C]-3[/C][C]0.784401256514189[/C][/ROW]
[ROW][C]-2[/C][C]0.876805739965778[/C][/ROW]
[ROW][C]-1[/C][C]0.953573594122783[/C][/ROW]
[ROW][C]0[/C][C]1[/C][/ROW]
[ROW][C]1[/C][C]0.953573594122783[/C][/ROW]
[ROW][C]2[/C][C]0.876805739965778[/C][/ROW]
[ROW][C]3[/C][C]0.784401256514189[/C][/ROW]
[ROW][C]4[/C][C]0.691171921164578[/C][/ROW]
[ROW][C]5[/C][C]0.605252904465295[/C][/ROW]
[ROW][C]6[/C][C]0.531292385307913[/C][/ROW]
[ROW][C]7[/C][C]0.468824811204089[/C][/ROW]
[ROW][C]8[/C][C]0.408823788559452[/C][/ROW]
[ROW][C]9[/C][C]0.353939498376474[/C][/ROW]
[ROW][C]10[/C][C]0.308424983869126[/C][/ROW]
[ROW][C]11[/C][C]0.263218198470475[/C][/ROW]
[ROW][C]12[/C][C]0.223392073633954[/C][/ROW]
[ROW][C]13[/C][C]0.185188995271011[/C][/ROW]
[ROW][C]14[/C][C]0.150089394926911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28150&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28150&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])
-140.150089394926911
-130.185188995271011
-120.223392073633954
-110.263218198470475
-100.308424983869126
-90.353939498376474
-80.408823788559452
-70.468824811204089
-60.531292385307913
-50.605252904465295
-40.691171921164578
-30.784401256514189
-20.876805739965778
-10.953573594122783
01
10.953573594122783
20.876805739965778
30.784401256514189
40.691171921164578
50.605252904465295
60.531292385307913
70.468824811204089
80.408823788559452
90.353939498376474
100.308424983869126
110.263218198470475
120.223392073633954
130.185188995271011
140.150089394926911


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')