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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, 18 Dec 2007 03:52:49 -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/Dec/18/t1197974265vrzjbzsa8j4sulp.htm/, Retrieved Sat, 04 May 2024 06:31:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4486, Retrieved Sat, 04 May 2024 06:31:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact220

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] [] [2007-12-18 10:52:49] [ba3202e2798d2e4685d19d988e9c69df] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
85.6
89
97.5
104
99.4
103.2
103
91.2
85.9
80.7
86.7
80.7
81.5
83.4
83.5
89.5
85.8
77.4
67.5
63.7
59.4
62
62.4
58.1
58
56.3
61.4
59.8
54.3
47
50.5
48.1
58.8
70.4
71.9
73.3
83.5
90.1
101.3
98.3
106.7
109.9
111.1
119
120.7
104.5
121.6
129.6
124.5
130.1
142.3
140
143.3
113.4
113.8
120.7
112.9
115.5
121.9
119.3
111
114.2
113.5
94
83.2
82.8
85.8
88.7
105.3
113.1
113.8
109.4
Dataseries Y:
Download CSV
Histogram 
88
88,4
95
101,8
107,6
118,9
126,9
106,3
109,2
104,6
100,8
92,1
86,4
96
98,5
112
113,9
120
126,7
112,8
116,2
110,6
105
101,2
99,3
101,9
106,4
118,9
121,9
132
121,4
117
122,7
113
104
101,2
100,8
98,9
103
117,8
126,6
127,6
115,8
114,8
119,2
109,9
98,9
98,6
96,6
96,7
103,5
115,3
122,5
125,3
111,2
110,7
114,2
105,6
95,5
97,3
95,5
96,3
100,2
113,4
121,4
122,1
119,3
110,8
110,1
99,7
104,8
105,4

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4486&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4486&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4486&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series1
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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-14-0.0977248829217369
-130.0941879343475155
-120.162282461390043
-11-0.217762371704730
-10-0.0547345408368157
-9-0.0689697912063102
-80.0225603487029320
-7-0.0443344532188259
-60.0170616234603974
-50.0928545101046508
-4-0.00265720462299864
-30.0453492776344094
-20.0390972574308377
-10.281428549071881
0-0.414784120366332
1-0.0205975953924442
20.123001505864384
3-0.0479046306068082
4-0.116625164856908
5-0.157069395685383
60.217061548599939
70.064342311213093
80.00399517886940731
9-0.00149034191559218
100.0402162378618912
110.198678698072283
12-0.295261242856782
13-0.0554601770361303
140.106983240090953

\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 & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & -0.0977248829217369 \tabularnewline
-13 & 0.0941879343475155 \tabularnewline
-12 & 0.162282461390043 \tabularnewline
-11 & -0.217762371704730 \tabularnewline
-10 & -0.0547345408368157 \tabularnewline
-9 & -0.0689697912063102 \tabularnewline
-8 & 0.0225603487029320 \tabularnewline
-7 & -0.0443344532188259 \tabularnewline
-6 & 0.0170616234603974 \tabularnewline
-5 & 0.0928545101046508 \tabularnewline
-4 & -0.00265720462299864 \tabularnewline
-3 & 0.0453492776344094 \tabularnewline
-2 & 0.0390972574308377 \tabularnewline
-1 & 0.281428549071881 \tabularnewline
0 & -0.414784120366332 \tabularnewline
1 & -0.0205975953924442 \tabularnewline
2 & 0.123001505864384 \tabularnewline
3 & -0.0479046306068082 \tabularnewline
4 & -0.116625164856908 \tabularnewline
5 & -0.157069395685383 \tabularnewline
6 & 0.217061548599939 \tabularnewline
7 & 0.064342311213093 \tabularnewline
8 & 0.00399517886940731 \tabularnewline
9 & -0.00149034191559218 \tabularnewline
10 & 0.0402162378618912 \tabularnewline
11 & 0.198678698072283 \tabularnewline
12 & -0.295261242856782 \tabularnewline
13 & -0.0554601770361303 \tabularnewline
14 & 0.106983240090953 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4486&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]1[/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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]-0.0977248829217369[/C][/ROW]
[ROW][C]-13[/C][C]0.0941879343475155[/C][/ROW]
[ROW][C]-12[/C][C]0.162282461390043[/C][/ROW]
[ROW][C]-11[/C][C]-0.217762371704730[/C][/ROW]
[ROW][C]-10[/C][C]-0.0547345408368157[/C][/ROW]
[ROW][C]-9[/C][C]-0.0689697912063102[/C][/ROW]
[ROW][C]-8[/C][C]0.0225603487029320[/C][/ROW]
[ROW][C]-7[/C][C]-0.0443344532188259[/C][/ROW]
[ROW][C]-6[/C][C]0.0170616234603974[/C][/ROW]
[ROW][C]-5[/C][C]0.0928545101046508[/C][/ROW]
[ROW][C]-4[/C][C]-0.00265720462299864[/C][/ROW]
[ROW][C]-3[/C][C]0.0453492776344094[/C][/ROW]
[ROW][C]-2[/C][C]0.0390972574308377[/C][/ROW]
[ROW][C]-1[/C][C]0.281428549071881[/C][/ROW]
[ROW][C]0[/C][C]-0.414784120366332[/C][/ROW]
[ROW][C]1[/C][C]-0.0205975953924442[/C][/ROW]
[ROW][C]2[/C][C]0.123001505864384[/C][/ROW]
[ROW][C]3[/C][C]-0.0479046306068082[/C][/ROW]
[ROW][C]4[/C][C]-0.116625164856908[/C][/ROW]
[ROW][C]5[/C][C]-0.157069395685383[/C][/ROW]
[ROW][C]6[/C][C]0.217061548599939[/C][/ROW]
[ROW][C]7[/C][C]0.064342311213093[/C][/ROW]
[ROW][C]8[/C][C]0.00399517886940731[/C][/ROW]
[ROW][C]9[/C][C]-0.00149034191559218[/C][/ROW]
[ROW][C]10[/C][C]0.0402162378618912[/C][/ROW]
[ROW][C]11[/C][C]0.198678698072283[/C][/ROW]
[ROW][C]12[/C][C]-0.295261242856782[/C][/ROW]
[ROW][C]13[/C][C]-0.0554601770361303[/C][/ROW]
[ROW][C]14[/C][C]0.106983240090953[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4486&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4486&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 series1
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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-14-0.0977248829217369
-130.0941879343475155
-120.162282461390043
-11-0.217762371704730
-10-0.0547345408368157
-9-0.0689697912063102
-80.0225603487029320
-7-0.0443344532188259
-60.0170616234603974
-50.0928545101046508
-4-0.00265720462299864
-30.0453492776344094
-20.0390972574308377
-10.281428549071881
0-0.414784120366332
1-0.0205975953924442
20.123001505864384
3-0.0479046306068082
4-0.116625164856908
5-0.157069395685383
60.217061548599939
70.064342311213093
80.00399517886940731
9-0.00149034191559218
100.0402162378618912
110.198678698072283
12-0.295261242856782
13-0.0554601770361303
140.106983240090953


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 1 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 1 ;
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',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')