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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 computationMon, 26 Nov 2007 16:21:57 -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/27/t1196118783l24h8nauu4iqj5v.htm/, Retrieved Sun, 05 May 2024 20:10:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6739, Retrieved Sun, 05 May 2024 20:10:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact221

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] [CCM Y=Steenkolen ...] [2007-11-26 23:21:57] [4df98167d5cf79c69ce763f2d4ef5b15] [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 
95,4
101,2
101,5
101,9
101,7
100,1
97,4
96,5
99,2
102,2
105,3
111,1
114,9
124,5
142,2
159,7
165,2
198,6
207,8
219,6
239,6
235,3
218,5
213,8
205,5
198,4
198,5
190,2
180,7
193,6
192,8
195,5
197,2
196,9
178,9
172,4
156,4
143,7
153,6
168,8
185,8
199,9
205,4
197,5
199,6
200,5
193,7
179,6
169,1
169,8
195,5
194,8
204,5
203,8
204,8
204,9
240,0
248,3
258,4
254,9

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=6739&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=6739&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6739&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 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])
-14-0.0155174657067508
-130.0350419483580086
-120.0766438489017833
-110.112287930900743
-100.142807653823877
-90.180569128521430
-80.218665331631546
-70.264859257410718
-60.315250651135354
-50.371931823471846
-40.432856462459734
-30.499788557608947
-20.578061336840118
-10.64557372780114
00.720099435806307
10.686201863963104
20.635788869182475
30.591016163972071
40.543987334202245
50.513853468054545
60.483635759301297
70.456257457548073
80.431573476322734
90.424639447339422
100.416719933574907
110.423112145978759
120.427595853789111
130.421244023534149
140.396466995853214

\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 & -0.0155174657067508 \tabularnewline
-13 & 0.0350419483580086 \tabularnewline
-12 & 0.0766438489017833 \tabularnewline
-11 & 0.112287930900743 \tabularnewline
-10 & 0.142807653823877 \tabularnewline
-9 & 0.180569128521430 \tabularnewline
-8 & 0.218665331631546 \tabularnewline
-7 & 0.264859257410718 \tabularnewline
-6 & 0.315250651135354 \tabularnewline
-5 & 0.371931823471846 \tabularnewline
-4 & 0.432856462459734 \tabularnewline
-3 & 0.499788557608947 \tabularnewline
-2 & 0.578061336840118 \tabularnewline
-1 & 0.64557372780114 \tabularnewline
0 & 0.720099435806307 \tabularnewline
1 & 0.686201863963104 \tabularnewline
2 & 0.635788869182475 \tabularnewline
3 & 0.591016163972071 \tabularnewline
4 & 0.543987334202245 \tabularnewline
5 & 0.513853468054545 \tabularnewline
6 & 0.483635759301297 \tabularnewline
7 & 0.456257457548073 \tabularnewline
8 & 0.431573476322734 \tabularnewline
9 & 0.424639447339422 \tabularnewline
10 & 0.416719933574907 \tabularnewline
11 & 0.423112145978759 \tabularnewline
12 & 0.427595853789111 \tabularnewline
13 & 0.421244023534149 \tabularnewline
14 & 0.396466995853214 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6739&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]-0.0155174657067508[/C][/ROW]
[ROW][C]-13[/C][C]0.0350419483580086[/C][/ROW]
[ROW][C]-12[/C][C]0.0766438489017833[/C][/ROW]
[ROW][C]-11[/C][C]0.112287930900743[/C][/ROW]
[ROW][C]-10[/C][C]0.142807653823877[/C][/ROW]
[ROW][C]-9[/C][C]0.180569128521430[/C][/ROW]
[ROW][C]-8[/C][C]0.218665331631546[/C][/ROW]
[ROW][C]-7[/C][C]0.264859257410718[/C][/ROW]
[ROW][C]-6[/C][C]0.315250651135354[/C][/ROW]
[ROW][C]-5[/C][C]0.371931823471846[/C][/ROW]
[ROW][C]-4[/C][C]0.432856462459734[/C][/ROW]
[ROW][C]-3[/C][C]0.499788557608947[/C][/ROW]
[ROW][C]-2[/C][C]0.578061336840118[/C][/ROW]
[ROW][C]-1[/C][C]0.64557372780114[/C][/ROW]
[ROW][C]0[/C][C]0.720099435806307[/C][/ROW]
[ROW][C]1[/C][C]0.686201863963104[/C][/ROW]
[ROW][C]2[/C][C]0.635788869182475[/C][/ROW]
[ROW][C]3[/C][C]0.591016163972071[/C][/ROW]
[ROW][C]4[/C][C]0.543987334202245[/C][/ROW]
[ROW][C]5[/C][C]0.513853468054545[/C][/ROW]
[ROW][C]6[/C][C]0.483635759301297[/C][/ROW]
[ROW][C]7[/C][C]0.456257457548073[/C][/ROW]
[ROW][C]8[/C][C]0.431573476322734[/C][/ROW]
[ROW][C]9[/C][C]0.424639447339422[/C][/ROW]
[ROW][C]10[/C][C]0.416719933574907[/C][/ROW]
[ROW][C]11[/C][C]0.423112145978759[/C][/ROW]
[ROW][C]12[/C][C]0.427595853789111[/C][/ROW]
[ROW][C]13[/C][C]0.421244023534149[/C][/ROW]
[ROW][C]14[/C][C]0.396466995853214[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6739&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6739&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])
-14-0.0155174657067508
-130.0350419483580086
-120.0766438489017833
-110.112287930900743
-100.142807653823877
-90.180569128521430
-80.218665331631546
-70.264859257410718
-60.315250651135354
-50.371931823471846
-40.432856462459734
-30.499788557608947
-20.578061336840118
-10.64557372780114
00.720099435806307
10.686201863963104
20.635788869182475
30.591016163972071
40.543987334202245
50.513853468054545
60.483635759301297
70.456257457548073
80.431573476322734
90.424639447339422
100.416719933574907
110.423112145978759
120.427595853789111
130.421244023534149
140.396466995853214


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) 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')