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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 computationFri, 23 Nov 2007 02:56:08 -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/23/t11958116142ju35rs591t2utp.htm/, Retrieved Sun, 28 Apr 2024 21:23:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6125, Retrieved Sun, 28 Apr 2024 21:23:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsGroep 1, WS7, Q5
Estimated Impact245

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] [WS7, Q5] [2007-11-23 09:56:08] [ce556af355e2eff84137e549c6ea8397] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,3
101
113,2
101
105,7
113,9
86,4
96,5
103,3
114,9
105,8
94,2
98,4
99,4
108,8
112,6
104,4
112,2
81,1
97,1
112,6
113,8
107,8
103,2
103,3
101,2
107,7
110,4
101,9
115,9
89,9
88,6
117,2
123,9
100
103,6
94,1
98,7
119,5
112,7
104,4
124,7
89,1
97
121,6
118,8
114
111,5
97,2
102,5
113,4
109,8
104,9
126,1
80
96,8
117,2
112,3
117,3
111,1
102,2
104,3
122,9
107,6
121,3
131,5
89
104,4
128,9
135,9
133,3
121,3
120,5
120,4
137,9
126,1
133,2
146,6
103,4
117,2
Dataseries Y:
Download CSV
Histogram 
106,7
110,2
125,9
100,1
106,4
114,8
81,3
87
104,2
108
105
94,5
92
95,9
108,8
103,4
102,1
110,1
83,2
82,7
106,8
113,7
102,5
96,6
92,1
95,6
102,3
98,6
98,2
104,5
84
73,8
103,9
106
97,2
102,6
89
93,8
116,7
106,8
98,5
118,7
90
91,9
113,3
113,1
104,1
108,7
96,7
101
116,9
105,8
99
129,4
83
88,9
115,9
104,2
113,4
112,2
100,8
107,3
126,6
102,9
117,9
128,8
87,5
93,8
122,7
126,2
124,6
116,7
115,2
111,1
129,9
113,3
118,5
133,5
102,1
102,4

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=6125&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=6125&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6125&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 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])
-16-0.102225583659569
-150.0522188886977425
-14-0.112427000880887
-130.105355219695334
-120.575147628591569
-110.0154701621313484
-10-0.179977696861669
-90.125809785878261
-80.0322797109296083
-70.194517314176721
-60.48721774063806
-50.221797554220720
-40.0410569036910198
-30.206783238599475
-2-0.0146518071705129
-10.300053667977281
00.90313330613718
10.162944592706389
2-0.00508983891563739
30.254043504325098
40.0627797407073858
50.269906800832284
60.4741437986524
70.20876221555064
80.0539497892962499
90.0961528581654558
10-0.162152894995445
110.151140273494568
120.602555210115747
130.0119183980153662
14-0.110661517458544
150.0903813869165657
16-0.107589772264368

\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
-16 & -0.102225583659569 \tabularnewline
-15 & 0.0522188886977425 \tabularnewline
-14 & -0.112427000880887 \tabularnewline
-13 & 0.105355219695334 \tabularnewline
-12 & 0.575147628591569 \tabularnewline
-11 & 0.0154701621313484 \tabularnewline
-10 & -0.179977696861669 \tabularnewline
-9 & 0.125809785878261 \tabularnewline
-8 & 0.0322797109296083 \tabularnewline
-7 & 0.194517314176721 \tabularnewline
-6 & 0.48721774063806 \tabularnewline
-5 & 0.221797554220720 \tabularnewline
-4 & 0.0410569036910198 \tabularnewline
-3 & 0.206783238599475 \tabularnewline
-2 & -0.0146518071705129 \tabularnewline
-1 & 0.300053667977281 \tabularnewline
0 & 0.90313330613718 \tabularnewline
1 & 0.162944592706389 \tabularnewline
2 & -0.00508983891563739 \tabularnewline
3 & 0.254043504325098 \tabularnewline
4 & 0.0627797407073858 \tabularnewline
5 & 0.269906800832284 \tabularnewline
6 & 0.4741437986524 \tabularnewline
7 & 0.20876221555064 \tabularnewline
8 & 0.0539497892962499 \tabularnewline
9 & 0.0961528581654558 \tabularnewline
10 & -0.162152894995445 \tabularnewline
11 & 0.151140273494568 \tabularnewline
12 & 0.602555210115747 \tabularnewline
13 & 0.0119183980153662 \tabularnewline
14 & -0.110661517458544 \tabularnewline
15 & 0.0903813869165657 \tabularnewline
16 & -0.107589772264368 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6125&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]-16[/C][C]-0.102225583659569[/C][/ROW]
[ROW][C]-15[/C][C]0.0522188886977425[/C][/ROW]
[ROW][C]-14[/C][C]-0.112427000880887[/C][/ROW]
[ROW][C]-13[/C][C]0.105355219695334[/C][/ROW]
[ROW][C]-12[/C][C]0.575147628591569[/C][/ROW]
[ROW][C]-11[/C][C]0.0154701621313484[/C][/ROW]
[ROW][C]-10[/C][C]-0.179977696861669[/C][/ROW]
[ROW][C]-9[/C][C]0.125809785878261[/C][/ROW]
[ROW][C]-8[/C][C]0.0322797109296083[/C][/ROW]
[ROW][C]-7[/C][C]0.194517314176721[/C][/ROW]
[ROW][C]-6[/C][C]0.48721774063806[/C][/ROW]
[ROW][C]-5[/C][C]0.221797554220720[/C][/ROW]
[ROW][C]-4[/C][C]0.0410569036910198[/C][/ROW]
[ROW][C]-3[/C][C]0.206783238599475[/C][/ROW]
[ROW][C]-2[/C][C]-0.0146518071705129[/C][/ROW]
[ROW][C]-1[/C][C]0.300053667977281[/C][/ROW]
[ROW][C]0[/C][C]0.90313330613718[/C][/ROW]
[ROW][C]1[/C][C]0.162944592706389[/C][/ROW]
[ROW][C]2[/C][C]-0.00508983891563739[/C][/ROW]
[ROW][C]3[/C][C]0.254043504325098[/C][/ROW]
[ROW][C]4[/C][C]0.0627797407073858[/C][/ROW]
[ROW][C]5[/C][C]0.269906800832284[/C][/ROW]
[ROW][C]6[/C][C]0.4741437986524[/C][/ROW]
[ROW][C]7[/C][C]0.20876221555064[/C][/ROW]
[ROW][C]8[/C][C]0.0539497892962499[/C][/ROW]
[ROW][C]9[/C][C]0.0961528581654558[/C][/ROW]
[ROW][C]10[/C][C]-0.162152894995445[/C][/ROW]
[ROW][C]11[/C][C]0.151140273494568[/C][/ROW]
[ROW][C]12[/C][C]0.602555210115747[/C][/ROW]
[ROW][C]13[/C][C]0.0119183980153662[/C][/ROW]
[ROW][C]14[/C][C]-0.110661517458544[/C][/ROW]
[ROW][C]15[/C][C]0.0903813869165657[/C][/ROW]
[ROW][C]16[/C][C]-0.107589772264368[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6125&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6125&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])
-16-0.102225583659569
-150.0522188886977425
-14-0.112427000880887
-130.105355219695334
-120.575147628591569
-110.0154701621313484
-10-0.179977696861669
-90.125809785878261
-80.0322797109296083
-70.194517314176721
-60.48721774063806
-50.221797554220720
-40.0410569036910198
-30.206783238599475
-2-0.0146518071705129
-10.300053667977281
00.90313330613718
10.162944592706389
2-0.00508983891563739
30.254043504325098
40.0627797407073858
50.269906800832284
60.4741437986524
70.20876221555064
80.0539497892962499
90.0961528581654558
10-0.162152894995445
110.151140273494568
120.602555210115747
130.0119183980153662
14-0.110661517458544
150.0903813869165657
16-0.107589772264368


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')