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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 computationThu, 22 Nov 2007 08:25:02 -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/22/t1195744683wtcda0858wd4jyy.htm/, Retrieved Fri, 03 May 2024 02:07:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6049, Retrieved Fri, 03 May 2024 02:07:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

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] [] [2007-11-22 15:25:02] [1a2581828a3030ed7733053b32a6f065] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96.8
91.2
97.1
104.9
110.9
104.8
94.1
95.8
99.3
101.1
104.0
99.0
105.4
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
Dataseries Y:
Download CSV
Histogram 
96.7
88.0
96.7
106.8
114.3
105.7
90.1
91.6
97.7
100.8
104.6
95.9
102.7
104.0
107.9
113.8
113.8
123.1
125.1
137.6
134.0
140.3
152.1
150.6
167.3
153.2
142.0
154.4
158.5
180.9
181.3
172.4
192.0
199.3
215.4
214.3
201.5
190.5
196.0
215.7
209.4
214.1
237.8
239.0
237.8
251.5
248.8
215.4
201.2
203.1
214.2
188.9
203.0
213.3
228.5
228.2
240.9
258.8
248.5
269.2

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=6049&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=6049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6049&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 series2
Degree of seasonal differencing (D) of X series2
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series2
krho(Y[t],X[t-k])
-12-0.490819006269465
-110.236360560561975
-100.000968598426930546
-9-0.0567898750337835
-80.330882360124449
-7-0.450639225174719
-60.113432701429109
-50.0655208159991688
-40.0383673464246128
-30.157456578356520
-2-0.336581777327137
-1-0.00813252905953489
00.150510074437842
10.0191149717219189
20.0558913986710518
3-0.175097325544351
40.0256720363020873
5-0.0206319944106469
60.120125881234118
70.0407829571200851
8-0.120795935872610
90.0286055885942099
10-0.114881963901968
110.223223682971686
12-0.0712915929746746

\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 & 2 \tabularnewline
Degree of seasonal differencing (D) of X series & 2 \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 & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 2 \tabularnewline
k & rho(Y[t],X[t-k]) \tabularnewline
-12 & -0.490819006269465 \tabularnewline
-11 & 0.236360560561975 \tabularnewline
-10 & 0.000968598426930546 \tabularnewline
-9 & -0.0567898750337835 \tabularnewline
-8 & 0.330882360124449 \tabularnewline
-7 & -0.450639225174719 \tabularnewline
-6 & 0.113432701429109 \tabularnewline
-5 & 0.0655208159991688 \tabularnewline
-4 & 0.0383673464246128 \tabularnewline
-3 & 0.157456578356520 \tabularnewline
-2 & -0.336581777327137 \tabularnewline
-1 & -0.00813252905953489 \tabularnewline
0 & 0.150510074437842 \tabularnewline
1 & 0.0191149717219189 \tabularnewline
2 & 0.0558913986710518 \tabularnewline
3 & -0.175097325544351 \tabularnewline
4 & 0.0256720363020873 \tabularnewline
5 & -0.0206319944106469 \tabularnewline
6 & 0.120125881234118 \tabularnewline
7 & 0.0407829571200851 \tabularnewline
8 & -0.120795935872610 \tabularnewline
9 & 0.0286055885942099 \tabularnewline
10 & -0.114881963901968 \tabularnewline
11 & 0.223223682971686 \tabularnewline
12 & -0.0712915929746746 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6049&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]2[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]2[/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]2[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]2[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t-k])[/C][/ROW]
[ROW][C]-12[/C][C]-0.490819006269465[/C][/ROW]
[ROW][C]-11[/C][C]0.236360560561975[/C][/ROW]
[ROW][C]-10[/C][C]0.000968598426930546[/C][/ROW]
[ROW][C]-9[/C][C]-0.0567898750337835[/C][/ROW]
[ROW][C]-8[/C][C]0.330882360124449[/C][/ROW]
[ROW][C]-7[/C][C]-0.450639225174719[/C][/ROW]
[ROW][C]-6[/C][C]0.113432701429109[/C][/ROW]
[ROW][C]-5[/C][C]0.0655208159991688[/C][/ROW]
[ROW][C]-4[/C][C]0.0383673464246128[/C][/ROW]
[ROW][C]-3[/C][C]0.157456578356520[/C][/ROW]
[ROW][C]-2[/C][C]-0.336581777327137[/C][/ROW]
[ROW][C]-1[/C][C]-0.00813252905953489[/C][/ROW]
[ROW][C]0[/C][C]0.150510074437842[/C][/ROW]
[ROW][C]1[/C][C]0.0191149717219189[/C][/ROW]
[ROW][C]2[/C][C]0.0558913986710518[/C][/ROW]
[ROW][C]3[/C][C]-0.175097325544351[/C][/ROW]
[ROW][C]4[/C][C]0.0256720363020873[/C][/ROW]
[ROW][C]5[/C][C]-0.0206319944106469[/C][/ROW]
[ROW][C]6[/C][C]0.120125881234118[/C][/ROW]
[ROW][C]7[/C][C]0.0407829571200851[/C][/ROW]
[ROW][C]8[/C][C]-0.120795935872610[/C][/ROW]
[ROW][C]9[/C][C]0.0286055885942099[/C][/ROW]
[ROW][C]10[/C][C]-0.114881963901968[/C][/ROW]
[ROW][C]11[/C][C]0.223223682971686[/C][/ROW]
[ROW][C]12[/C][C]-0.0712915929746746[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6049&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 series2
Degree of seasonal differencing (D) of X series2
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series2
krho(Y[t],X[t-k])
-12-0.490819006269465
-110.236360560561975
-100.000968598426930546
-9-0.0567898750337835
-80.330882360124449
-7-0.450639225174719
-60.113432701429109
-50.0655208159991688
-40.0383673464246128
-30.157456578356520
-2-0.336581777327137
-1-0.00813252905953489
00.150510074437842
10.0191149717219189
20.0558913986710518
3-0.175097325544351
40.0256720363020873
5-0.0206319944106469
60.120125881234118
70.0407829571200851
8-0.120795935872610
90.0286055885942099
10-0.114881963901968
110.223223682971686
12-0.0712915929746746


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 2 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 2 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 2 ;
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')