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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 21 Dec 2008 14:26:49 -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/2008/Dec/21/t1229894857izct3fz8s0ojf2x.htm/, Retrieved Sat, 18 May 2024 10:41:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35836, Retrieved Sat, 18 May 2024 10:41:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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] [cross correlation...] [2008-12-19 12:35:03] [fad8a251ac01c156a8ae23a83577546f]
-   PD    [Cross Correlation Function] [cross correlation...] [2008-12-21 21:26:49] [fa8b44cd657c07c6ee11bb2476ca3f8d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.0
99.2
112.2
112.1
103.3
108.2
90.4
72.8
111.0
117.9
111.3
110.5
94.8
100.4
132.1
114.6
101.9
130.2
84.0
86.4
122.3
120.9
110.2
112.6
102.0
105.0
130.5
115.5
103.7
130.9
89.1
93.8
123.8
111.9
118.3
116.9
103.6
116.6
141.3
107.0
125.2
136.4
91.6
95.3
132.3
130.6
131.9
118.6
114.3
111.3
126.5
112.1
119.3
142.4
101.1
97.4
129.1
136.9
129.8
123.9
Dataseries Y:
Download CSV
Histogram 
72.5
72.0
98.8
75.2
81.2
88.0
54.6
68.6
101.5
93.4
84.5
91.4
64.5
64.5
117.3
73.5
79.7
102.6
57.9
73.1
102.4
82.3
89.1
84.7
81.4
67.5
113.9
83.8
73.9
103.9
67.9
62.5
125.4
79.1
106.3
96.2
94.3
85.6
117.4
88.5
124.2
119.3
76.8
70.6
122.1
109.5
119.9
102.3
79.6
78.2
103.6
77.8
99.1
105.7
84.1
88.7
108.0
98.1
101.0
82.0

Tables (Output of Computation)





Summary of computational 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 computational 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=35836&T=0

[TABLE]
[ROW][C]Summary of computational 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=35836&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35836&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 computational 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 series0
Degree of seasonal differencing (D) of X series1
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 series1
krho(Y[t],X[t+k])
-13-0.110458021650096
-12-0.311168084796673
-11-0.174377683343227
-100.0707382064458564
-90.0777871066303111
-8-0.0477012847961929
-7-0.0743157428718044
-6-0.097429349775767
-50.0289946676803308
-4-0.192038216497748
-30.130733614873556
-20.0862286877480604
-10.0752137904297719
00.533041809752547
10.0336782518010532
20.0510943151218205
30.140475009553332
4-0.0114474692783546
50.12174624691073
60.203272741103554
7-0.113238888484194
80.197031298588928
9-0.181018404610602
10-0.0820519035572743
110.0157142440196137
12-0.119281500728294
130.00619897944102594

\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 & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.110458021650096 \tabularnewline
-12 & -0.311168084796673 \tabularnewline
-11 & -0.174377683343227 \tabularnewline
-10 & 0.0707382064458564 \tabularnewline
-9 & 0.0777871066303111 \tabularnewline
-8 & -0.0477012847961929 \tabularnewline
-7 & -0.0743157428718044 \tabularnewline
-6 & -0.097429349775767 \tabularnewline
-5 & 0.0289946676803308 \tabularnewline
-4 & -0.192038216497748 \tabularnewline
-3 & 0.130733614873556 \tabularnewline
-2 & 0.0862286877480604 \tabularnewline
-1 & 0.0752137904297719 \tabularnewline
0 & 0.533041809752547 \tabularnewline
1 & 0.0336782518010532 \tabularnewline
2 & 0.0510943151218205 \tabularnewline
3 & 0.140475009553332 \tabularnewline
4 & -0.0114474692783546 \tabularnewline
5 & 0.12174624691073 \tabularnewline
6 & 0.203272741103554 \tabularnewline
7 & -0.113238888484194 \tabularnewline
8 & 0.197031298588928 \tabularnewline
9 & -0.181018404610602 \tabularnewline
10 & -0.0820519035572743 \tabularnewline
11 & 0.0157142440196137 \tabularnewline
12 & -0.119281500728294 \tabularnewline
13 & 0.00619897944102594 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35836&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]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.110458021650096[/C][/ROW]
[ROW][C]-12[/C][C]-0.311168084796673[/C][/ROW]
[ROW][C]-11[/C][C]-0.174377683343227[/C][/ROW]
[ROW][C]-10[/C][C]0.0707382064458564[/C][/ROW]
[ROW][C]-9[/C][C]0.0777871066303111[/C][/ROW]
[ROW][C]-8[/C][C]-0.0477012847961929[/C][/ROW]
[ROW][C]-7[/C][C]-0.0743157428718044[/C][/ROW]
[ROW][C]-6[/C][C]-0.097429349775767[/C][/ROW]
[ROW][C]-5[/C][C]0.0289946676803308[/C][/ROW]
[ROW][C]-4[/C][C]-0.192038216497748[/C][/ROW]
[ROW][C]-3[/C][C]0.130733614873556[/C][/ROW]
[ROW][C]-2[/C][C]0.0862286877480604[/C][/ROW]
[ROW][C]-1[/C][C]0.0752137904297719[/C][/ROW]
[ROW][C]0[/C][C]0.533041809752547[/C][/ROW]
[ROW][C]1[/C][C]0.0336782518010532[/C][/ROW]
[ROW][C]2[/C][C]0.0510943151218205[/C][/ROW]
[ROW][C]3[/C][C]0.140475009553332[/C][/ROW]
[ROW][C]4[/C][C]-0.0114474692783546[/C][/ROW]
[ROW][C]5[/C][C]0.12174624691073[/C][/ROW]
[ROW][C]6[/C][C]0.203272741103554[/C][/ROW]
[ROW][C]7[/C][C]-0.113238888484194[/C][/ROW]
[ROW][C]8[/C][C]0.197031298588928[/C][/ROW]
[ROW][C]9[/C][C]-0.181018404610602[/C][/ROW]
[ROW][C]10[/C][C]-0.0820519035572743[/C][/ROW]
[ROW][C]11[/C][C]0.0157142440196137[/C][/ROW]
[ROW][C]12[/C][C]-0.119281500728294[/C][/ROW]
[ROW][C]13[/C][C]0.00619897944102594[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35836&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35836&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 series1
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 series1
krho(Y[t],X[t+k])
-13-0.110458021650096
-12-0.311168084796673
-11-0.174377683343227
-100.0707382064458564
-90.0777871066303111
-8-0.0477012847961929
-7-0.0743157428718044
-6-0.097429349775767
-50.0289946676803308
-4-0.192038216497748
-30.130733614873556
-20.0862286877480604
-10.0752137904297719
00.533041809752547
10.0336782518010532
20.0510943151218205
30.140475009553332
4-0.0114474692783546
50.12174624691073
60.203272741103554
7-0.113238888484194
80.197031298588928
9-0.181018404610602
10-0.0820519035572743
110.0157142440196137
12-0.119281500728294
130.00619897944102594


Figures (Output of Computation)

Input Parameters & R Code

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