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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 03:56:25 -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/t1197974449f51e4qdgwathant.htm/, Retrieved Sat, 04 May 2024 06:20:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4487, Retrieved Sat, 04 May 2024 06:20:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

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 10:56:25] [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 
75,6
48,7
111,7
119,5
103,4
96,3
96,6
110,4
104,4
110,7
93,6
114,8
74,9
69,8
104,2
109,3
92,7
91,7
84,4
94,5
103,6
105,9
108
119,9
84,5
76,7
120,5
119,6
102,3
101,7
86,9
93,6
113,6
106,7
96,1
124,6
72,5
89
115,3
119,1
104,4
104,9
76,9
95,3
114,9
98,9
102,9
90
81
66,2
86,7
86,7
103,4
89,5
113,7
120,2
137,8
99,1
110,4
112,3
82,2
72,2
106,7
106,4
110
87,5
79,7
83,3
91,8
89,2
90,6
92,6

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 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=4487&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]3 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=4487&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4487&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 time3 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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.00748186831209029
-140.103407785870540
-130.0438359020655286
-12-0.216632909176891
-11-0.154577656132716
-10-0.009070707264473
-90.150908277113281
-80.100879059545131
-70.112530095109874
-60.0778143539034621
-5-0.0145380995887568
-4-0.17373207533699
-3-0.0261374445970838
-20.0485932033328414
-1-0.0609975961608903
0-0.229573333192639
1-0.0600005938877613
20.184781639479823
30.0434051466146954
40.083144643737627
50.138757931522511
6-0.0975164346761797
7-0.112585549827351
8-0.081655646188023
90.066062423725674
100.306777346196247
110.117128705296687
120.00211737489728695
130.066305708193028
140.0573027476133266
150.0371198876762528

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.00748186831209029 \tabularnewline
-14 & 0.103407785870540 \tabularnewline
-13 & 0.0438359020655286 \tabularnewline
-12 & -0.216632909176891 \tabularnewline
-11 & -0.154577656132716 \tabularnewline
-10 & -0.009070707264473 \tabularnewline
-9 & 0.150908277113281 \tabularnewline
-8 & 0.100879059545131 \tabularnewline
-7 & 0.112530095109874 \tabularnewline
-6 & 0.0778143539034621 \tabularnewline
-5 & -0.0145380995887568 \tabularnewline
-4 & -0.17373207533699 \tabularnewline
-3 & -0.0261374445970838 \tabularnewline
-2 & 0.0485932033328414 \tabularnewline
-1 & -0.0609975961608903 \tabularnewline
0 & -0.229573333192639 \tabularnewline
1 & -0.0600005938877613 \tabularnewline
2 & 0.184781639479823 \tabularnewline
3 & 0.0434051466146954 \tabularnewline
4 & 0.083144643737627 \tabularnewline
5 & 0.138757931522511 \tabularnewline
6 & -0.0975164346761797 \tabularnewline
7 & -0.112585549827351 \tabularnewline
8 & -0.081655646188023 \tabularnewline
9 & 0.066062423725674 \tabularnewline
10 & 0.306777346196247 \tabularnewline
11 & 0.117128705296687 \tabularnewline
12 & 0.00211737489728695 \tabularnewline
13 & 0.066305708193028 \tabularnewline
14 & 0.0573027476133266 \tabularnewline
15 & 0.0371198876762528 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4487&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]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]-15[/C][C]-0.00748186831209029[/C][/ROW]
[ROW][C]-14[/C][C]0.103407785870540[/C][/ROW]
[ROW][C]-13[/C][C]0.0438359020655286[/C][/ROW]
[ROW][C]-12[/C][C]-0.216632909176891[/C][/ROW]
[ROW][C]-11[/C][C]-0.154577656132716[/C][/ROW]
[ROW][C]-10[/C][C]-0.009070707264473[/C][/ROW]
[ROW][C]-9[/C][C]0.150908277113281[/C][/ROW]
[ROW][C]-8[/C][C]0.100879059545131[/C][/ROW]
[ROW][C]-7[/C][C]0.112530095109874[/C][/ROW]
[ROW][C]-6[/C][C]0.0778143539034621[/C][/ROW]
[ROW][C]-5[/C][C]-0.0145380995887568[/C][/ROW]
[ROW][C]-4[/C][C]-0.17373207533699[/C][/ROW]
[ROW][C]-3[/C][C]-0.0261374445970838[/C][/ROW]
[ROW][C]-2[/C][C]0.0485932033328414[/C][/ROW]
[ROW][C]-1[/C][C]-0.0609975961608903[/C][/ROW]
[ROW][C]0[/C][C]-0.229573333192639[/C][/ROW]
[ROW][C]1[/C][C]-0.0600005938877613[/C][/ROW]
[ROW][C]2[/C][C]0.184781639479823[/C][/ROW]
[ROW][C]3[/C][C]0.0434051466146954[/C][/ROW]
[ROW][C]4[/C][C]0.083144643737627[/C][/ROW]
[ROW][C]5[/C][C]0.138757931522511[/C][/ROW]
[ROW][C]6[/C][C]-0.0975164346761797[/C][/ROW]
[ROW][C]7[/C][C]-0.112585549827351[/C][/ROW]
[ROW][C]8[/C][C]-0.081655646188023[/C][/ROW]
[ROW][C]9[/C][C]0.066062423725674[/C][/ROW]
[ROW][C]10[/C][C]0.306777346196247[/C][/ROW]
[ROW][C]11[/C][C]0.117128705296687[/C][/ROW]
[ROW][C]12[/C][C]0.00211737489728695[/C][/ROW]
[ROW][C]13[/C][C]0.066305708193028[/C][/ROW]
[ROW][C]14[/C][C]0.0573027476133266[/C][/ROW]
[ROW][C]15[/C][C]0.0371198876762528[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4487&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4487&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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.00748186831209029
-140.103407785870540
-130.0438359020655286
-12-0.216632909176891
-11-0.154577656132716
-10-0.009070707264473
-90.150908277113281
-80.100879059545131
-70.112530095109874
-60.0778143539034621
-5-0.0145380995887568
-4-0.17373207533699
-3-0.0261374445970838
-20.0485932033328414
-1-0.0609975961608903
0-0.229573333192639
1-0.0600005938877613
20.184781639479823
30.0434051466146954
40.083144643737627
50.138757931522511
6-0.0975164346761797
7-0.112585549827351
8-0.081655646188023
90.066062423725674
100.306777346196247
110.117128705296687
120.00211737489728695
130.066305708193028
140.0573027476133266
150.0371198876762528


Figures (Output of Computation)

Input Parameters & R Code

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