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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, 29 Nov 2007 06:53:36 -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/29/t1196343868fmtv180bomq0yux.htm/, Retrieved Fri, 03 May 2024 09:22:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7471, Retrieved Fri, 03 May 2024 09:22:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing stationarity time serie
Estimated Impact198

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] [Case IV Question ...] [2007-11-29 13:53:36] [fd802f308f037a9692de8c23f8b60e49] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
113,2
105,5
77,8
102,1
97
95,5
99,3
86,4
92,4
85,7
61,9
104,9
107,9
95,6
79,8
94,8
93,7
108,1
96,9
88,8
106,7
86,8
69,8
110,9
105,4
99,2
84,4
87,2
91,9
97,9
94,5
85
100,3
78,7
65,8
104,8
96
103,3
82,9
91,4
94,5
109,3
92,1
99,3
109,6
87,5
73,1
110,7
111,6
110,7
84
101,6
102,1
113,9
99
100,4
109,5
93
76,8
105,3
Dataseries Y:
Download CSV
Histogram 
73,8
55,2
54,4
80,8
88
74,5
55,1
47,2
54,2
70,6
78,5
77,1
56,6
39,8
44,1
66,9
75,3
74,9
48,8
37
49,8
63,2
75,9
68,5
49,2
40,3
38,6
54,2
70,6
68
43
42,3
47,7
57,7
75,8
57,2
43,6
40
35,9
59,5
72,7
70,9
44,9
44,5
48
60,4
71,8
63,2
32,4
33,9
24,2
64,7
73
61,7
31,9
30,8
36,7
47,4
54
41,1

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=7471&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=7471&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7471&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 series1
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])
-13-0.0609396192003923
-120.0838803568270282
-11-0.126213793920785
-100.0431506215755817
-90.0680985106819433
-8-0.117810719403372
-70.0578687454941555
-60.0957210347495147
-5-0.14920845702516
-40.0575396490719432
-3-0.13655011451955
-20.0687013262889537
-10.129280588328136
0-0.0515951337298002
1-0.0603309028255786
2-0.00314947389127824
3-0.100750411406283
4-0.0241678890428967
50.205924954195667
6-0.00110694904776506
7-0.101581687538153
8-0.0798641824098033
9-0.109425365935190
100.197387273229368
110.0816120114950802
12-0.00194923939076972
13-0.0468454540917849

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0609396192003923 \tabularnewline
-12 & 0.0838803568270282 \tabularnewline
-11 & -0.126213793920785 \tabularnewline
-10 & 0.0431506215755817 \tabularnewline
-9 & 0.0680985106819433 \tabularnewline
-8 & -0.117810719403372 \tabularnewline
-7 & 0.0578687454941555 \tabularnewline
-6 & 0.0957210347495147 \tabularnewline
-5 & -0.14920845702516 \tabularnewline
-4 & 0.0575396490719432 \tabularnewline
-3 & -0.13655011451955 \tabularnewline
-2 & 0.0687013262889537 \tabularnewline
-1 & 0.129280588328136 \tabularnewline
0 & -0.0515951337298002 \tabularnewline
1 & -0.0603309028255786 \tabularnewline
2 & -0.00314947389127824 \tabularnewline
3 & -0.100750411406283 \tabularnewline
4 & -0.0241678890428967 \tabularnewline
5 & 0.205924954195667 \tabularnewline
6 & -0.00110694904776506 \tabularnewline
7 & -0.101581687538153 \tabularnewline
8 & -0.0798641824098033 \tabularnewline
9 & -0.109425365935190 \tabularnewline
10 & 0.197387273229368 \tabularnewline
11 & 0.0816120114950802 \tabularnewline
12 & -0.00194923939076972 \tabularnewline
13 & -0.0468454540917849 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7471&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]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]-13[/C][C]-0.0609396192003923[/C][/ROW]
[ROW][C]-12[/C][C]0.0838803568270282[/C][/ROW]
[ROW][C]-11[/C][C]-0.126213793920785[/C][/ROW]
[ROW][C]-10[/C][C]0.0431506215755817[/C][/ROW]
[ROW][C]-9[/C][C]0.0680985106819433[/C][/ROW]
[ROW][C]-8[/C][C]-0.117810719403372[/C][/ROW]
[ROW][C]-7[/C][C]0.0578687454941555[/C][/ROW]
[ROW][C]-6[/C][C]0.0957210347495147[/C][/ROW]
[ROW][C]-5[/C][C]-0.14920845702516[/C][/ROW]
[ROW][C]-4[/C][C]0.0575396490719432[/C][/ROW]
[ROW][C]-3[/C][C]-0.13655011451955[/C][/ROW]
[ROW][C]-2[/C][C]0.0687013262889537[/C][/ROW]
[ROW][C]-1[/C][C]0.129280588328136[/C][/ROW]
[ROW][C]0[/C][C]-0.0515951337298002[/C][/ROW]
[ROW][C]1[/C][C]-0.0603309028255786[/C][/ROW]
[ROW][C]2[/C][C]-0.00314947389127824[/C][/ROW]
[ROW][C]3[/C][C]-0.100750411406283[/C][/ROW]
[ROW][C]4[/C][C]-0.0241678890428967[/C][/ROW]
[ROW][C]5[/C][C]0.205924954195667[/C][/ROW]
[ROW][C]6[/C][C]-0.00110694904776506[/C][/ROW]
[ROW][C]7[/C][C]-0.101581687538153[/C][/ROW]
[ROW][C]8[/C][C]-0.0798641824098033[/C][/ROW]
[ROW][C]9[/C][C]-0.109425365935190[/C][/ROW]
[ROW][C]10[/C][C]0.197387273229368[/C][/ROW]
[ROW][C]11[/C][C]0.0816120114950802[/C][/ROW]
[ROW][C]12[/C][C]-0.00194923939076972[/C][/ROW]
[ROW][C]13[/C][C]-0.0468454540917849[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7471&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7471&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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0609396192003923
-120.0838803568270282
-11-0.126213793920785
-100.0431506215755817
-90.0680985106819433
-8-0.117810719403372
-70.0578687454941555
-60.0957210347495147
-5-0.14920845702516
-40.0575396490719432
-3-0.13655011451955
-20.0687013262889537
-10.129280588328136
0-0.0515951337298002
1-0.0603309028255786
2-0.00314947389127824
3-0.100750411406283
4-0.0241678890428967
50.205924954195667
6-0.00110694904776506
7-0.101581687538153
8-0.0798641824098033
9-0.109425365935190
100.197387273229368
110.0816120114950802
12-0.00194923939076972
13-0.0468454540917849


Figures (Output of Computation)

Input Parameters & R Code

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