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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 08:14:52 -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/t1195744016vcv6yczav8tjb1k.htm/, Retrieved Thu, 02 May 2024 15:33:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6045, Retrieved Thu, 02 May 2024 15:33:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact169

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] [bla] [2007-11-22 15:14:52] [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=6045&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=6045&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6045&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)1
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])
-140.336176486839543
-130.396103407336587
-120.443300221447245
-110.486492218327384
-100.518303751230256
-90.548952476520842
-80.576489805519889
-70.620821467918153
-60.666407238751709
-50.719318147689638
-40.764280753934114
-30.813710325725234
-20.87221750570551
-10.930465987337816
00.993726597812152
10.92843405537639
20.870905339835008
30.814549965863655
40.770115120685922
50.732652318392913
60.68823714312554
70.654094646487045
80.622738480597059
90.606422027746129
100.581074237849216
110.553302411427614
120.514465348355309
130.469155304137428
140.406337080752815

\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) & 1 \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 & 0.336176486839543 \tabularnewline
-13 & 0.396103407336587 \tabularnewline
-12 & 0.443300221447245 \tabularnewline
-11 & 0.486492218327384 \tabularnewline
-10 & 0.518303751230256 \tabularnewline
-9 & 0.548952476520842 \tabularnewline
-8 & 0.576489805519889 \tabularnewline
-7 & 0.620821467918153 \tabularnewline
-6 & 0.666407238751709 \tabularnewline
-5 & 0.719318147689638 \tabularnewline
-4 & 0.764280753934114 \tabularnewline
-3 & 0.813710325725234 \tabularnewline
-2 & 0.87221750570551 \tabularnewline
-1 & 0.930465987337816 \tabularnewline
0 & 0.993726597812152 \tabularnewline
1 & 0.92843405537639 \tabularnewline
2 & 0.870905339835008 \tabularnewline
3 & 0.814549965863655 \tabularnewline
4 & 0.770115120685922 \tabularnewline
5 & 0.732652318392913 \tabularnewline
6 & 0.68823714312554 \tabularnewline
7 & 0.654094646487045 \tabularnewline
8 & 0.622738480597059 \tabularnewline
9 & 0.606422027746129 \tabularnewline
10 & 0.581074237849216 \tabularnewline
11 & 0.553302411427614 \tabularnewline
12 & 0.514465348355309 \tabularnewline
13 & 0.469155304137428 \tabularnewline
14 & 0.406337080752815 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6045&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]1[/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]0.336176486839543[/C][/ROW]
[ROW][C]-13[/C][C]0.396103407336587[/C][/ROW]
[ROW][C]-12[/C][C]0.443300221447245[/C][/ROW]
[ROW][C]-11[/C][C]0.486492218327384[/C][/ROW]
[ROW][C]-10[/C][C]0.518303751230256[/C][/ROW]
[ROW][C]-9[/C][C]0.548952476520842[/C][/ROW]
[ROW][C]-8[/C][C]0.576489805519889[/C][/ROW]
[ROW][C]-7[/C][C]0.620821467918153[/C][/ROW]
[ROW][C]-6[/C][C]0.666407238751709[/C][/ROW]
[ROW][C]-5[/C][C]0.719318147689638[/C][/ROW]
[ROW][C]-4[/C][C]0.764280753934114[/C][/ROW]
[ROW][C]-3[/C][C]0.813710325725234[/C][/ROW]
[ROW][C]-2[/C][C]0.87221750570551[/C][/ROW]
[ROW][C]-1[/C][C]0.930465987337816[/C][/ROW]
[ROW][C]0[/C][C]0.993726597812152[/C][/ROW]
[ROW][C]1[/C][C]0.92843405537639[/C][/ROW]
[ROW][C]2[/C][C]0.870905339835008[/C][/ROW]
[ROW][C]3[/C][C]0.814549965863655[/C][/ROW]
[ROW][C]4[/C][C]0.770115120685922[/C][/ROW]
[ROW][C]5[/C][C]0.732652318392913[/C][/ROW]
[ROW][C]6[/C][C]0.68823714312554[/C][/ROW]
[ROW][C]7[/C][C]0.654094646487045[/C][/ROW]
[ROW][C]8[/C][C]0.622738480597059[/C][/ROW]
[ROW][C]9[/C][C]0.606422027746129[/C][/ROW]
[ROW][C]10[/C][C]0.581074237849216[/C][/ROW]
[ROW][C]11[/C][C]0.553302411427614[/C][/ROW]
[ROW][C]12[/C][C]0.514465348355309[/C][/ROW]
[ROW][C]13[/C][C]0.469155304137428[/C][/ROW]
[ROW][C]14[/C][C]0.406337080752815[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6045&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6045&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)1
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])
-140.336176486839543
-130.396103407336587
-120.443300221447245
-110.486492218327384
-100.518303751230256
-90.548952476520842
-80.576489805519889
-70.620821467918153
-60.666407238751709
-50.719318147689638
-40.764280753934114
-30.813710325725234
-20.87221750570551
-10.930465987337816
00.993726597812152
10.92843405537639
20.870905339835008
30.814549965863655
40.770115120685922
50.732652318392913
60.68823714312554
70.654094646487045
80.622738480597059
90.606422027746129
100.581074237849216
110.553302411427614
120.514465348355309
130.469155304137428
140.406337080752815


Figures (Output of Computation)

Input Parameters & R Code

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