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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 computationThu, 09 Dec 2010 09:43:43 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/09/t1291887703lz5phd5zxbbwutt.htm/, Retrieved Mon, 29 Apr 2024 02:41:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107148, Retrieved Mon, 29 Apr 2024 02:41:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Ws4 part 1.1 s090...] [2009-10-27 21:56:53] [e0fc65a5811681d807296d590d5b45de]
-  M D    [Bivariate Explorative Data Analysis] [Paper; bivariate ...] [2009-12-19 19:10:37] [e0fc65a5811681d807296d590d5b45de]
- RMPD      [Cross Correlation Function] [cross correlation...] [2010-12-08 19:50:23] [74be16979710d4c4e7c6647856088456]
-   PD          [Cross Correlation Function] [] [2010-12-09 09:43:43] [c6b3e187a4a1689d42fffda4bc860ab5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.03
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
Dataseries Y:
Download CSV
Histogram 
25.64
27.97
27.62
23.31
29.07
29.58
28.63
29.92
32.68
31.54
32.43
26.54
25.85
27.6
25.71
25.38
28.57
27.64
25.36
25.9
26.29
21.74
19.2
19.32
19.82
20.36
24.31
25.97
25.61
24.67
25.59
26.09
28.37
27.34
24.46
27.46
30.23
32.33
29.87
24.87
25.48
27.28
28.24
29.58
26.95
29.08
28.76
29.59
30.7
30.52
32.67
33.19
37.13
35.54
37.75
41.84
42.94
49.14
44.61
40.22
44.23
45.85
53.38
53.26
51.8
55.3
57.81
63.96
63.77
59.15
56.12
57.42
63.52
61.71
63.01
68.18
72.03
69.75
74.41
74.33
64.24
60.03
59.44
62.5
55.04
58.34
61.92
67.65
67.68
70.3
75.26
71.44
76.36
81.71
92.6
90.6
92.23
94.09
102.79
109.65
124.05
132.69
135.81
116.07
101.42
75.73
55.48
43.8
45.29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 1 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107148&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107148&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107148&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 time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






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 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 series0
krho(Y[t],X[t+k])
-160.0323855994067322
-15-0.0342499660221456
-14-0.0597441590832788
-130.00345818966598631
-12-0.0123110779645512
-11-0.09710148297212
-10-0.0911450152473816
-9-0.156680012777283
-8-0.112838313219394
-7-0.022668557685786
-6-0.00837437841833647
-5-0.0566026727292671
-4-0.150861065623419
-30.0529041336236735
-2-0.0030441093895735
-1-0.114220038187733
0-0.00778127815971281
1-0.0069564675567362
20.155745812521432
3-0.10247905922824
40.137046707647123
50.0683070682732078
6-0.0371257072554045
7-0.128429126482864
8-0.0463413525405561
90.172376183541822
100.00796616670433751
11-0.0500099916757579
12-0.0455740369888212
130.141921642904847
14-0.0353197779369102
150.00952089451675311
16-0.0700934371917083

\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 & 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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.0323855994067322 \tabularnewline
-15 & -0.0342499660221456 \tabularnewline
-14 & -0.0597441590832788 \tabularnewline
-13 & 0.00345818966598631 \tabularnewline
-12 & -0.0123110779645512 \tabularnewline
-11 & -0.09710148297212 \tabularnewline
-10 & -0.0911450152473816 \tabularnewline
-9 & -0.156680012777283 \tabularnewline
-8 & -0.112838313219394 \tabularnewline
-7 & -0.022668557685786 \tabularnewline
-6 & -0.00837437841833647 \tabularnewline
-5 & -0.0566026727292671 \tabularnewline
-4 & -0.150861065623419 \tabularnewline
-3 & 0.0529041336236735 \tabularnewline
-2 & -0.0030441093895735 \tabularnewline
-1 & -0.114220038187733 \tabularnewline
0 & -0.00778127815971281 \tabularnewline
1 & -0.0069564675567362 \tabularnewline
2 & 0.155745812521432 \tabularnewline
3 & -0.10247905922824 \tabularnewline
4 & 0.137046707647123 \tabularnewline
5 & 0.0683070682732078 \tabularnewline
6 & -0.0371257072554045 \tabularnewline
7 & -0.128429126482864 \tabularnewline
8 & -0.0463413525405561 \tabularnewline
9 & 0.172376183541822 \tabularnewline
10 & 0.00796616670433751 \tabularnewline
11 & -0.0500099916757579 \tabularnewline
12 & -0.0455740369888212 \tabularnewline
13 & 0.141921642904847 \tabularnewline
14 & -0.0353197779369102 \tabularnewline
15 & 0.00952089451675311 \tabularnewline
16 & -0.0700934371917083 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107148&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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]0.0323855994067322[/C][/ROW]
[ROW][C]-15[/C][C]-0.0342499660221456[/C][/ROW]
[ROW][C]-14[/C][C]-0.0597441590832788[/C][/ROW]
[ROW][C]-13[/C][C]0.00345818966598631[/C][/ROW]
[ROW][C]-12[/C][C]-0.0123110779645512[/C][/ROW]
[ROW][C]-11[/C][C]-0.09710148297212[/C][/ROW]
[ROW][C]-10[/C][C]-0.0911450152473816[/C][/ROW]
[ROW][C]-9[/C][C]-0.156680012777283[/C][/ROW]
[ROW][C]-8[/C][C]-0.112838313219394[/C][/ROW]
[ROW][C]-7[/C][C]-0.022668557685786[/C][/ROW]
[ROW][C]-6[/C][C]-0.00837437841833647[/C][/ROW]
[ROW][C]-5[/C][C]-0.0566026727292671[/C][/ROW]
[ROW][C]-4[/C][C]-0.150861065623419[/C][/ROW]
[ROW][C]-3[/C][C]0.0529041336236735[/C][/ROW]
[ROW][C]-2[/C][C]-0.0030441093895735[/C][/ROW]
[ROW][C]-1[/C][C]-0.114220038187733[/C][/ROW]
[ROW][C]0[/C][C]-0.00778127815971281[/C][/ROW]
[ROW][C]1[/C][C]-0.0069564675567362[/C][/ROW]
[ROW][C]2[/C][C]0.155745812521432[/C][/ROW]
[ROW][C]3[/C][C]-0.10247905922824[/C][/ROW]
[ROW][C]4[/C][C]0.137046707647123[/C][/ROW]
[ROW][C]5[/C][C]0.0683070682732078[/C][/ROW]
[ROW][C]6[/C][C]-0.0371257072554045[/C][/ROW]
[ROW][C]7[/C][C]-0.128429126482864[/C][/ROW]
[ROW][C]8[/C][C]-0.0463413525405561[/C][/ROW]
[ROW][C]9[/C][C]0.172376183541822[/C][/ROW]
[ROW][C]10[/C][C]0.00796616670433751[/C][/ROW]
[ROW][C]11[/C][C]-0.0500099916757579[/C][/ROW]
[ROW][C]12[/C][C]-0.0455740369888212[/C][/ROW]
[ROW][C]13[/C][C]0.141921642904847[/C][/ROW]
[ROW][C]14[/C][C]-0.0353197779369102[/C][/ROW]
[ROW][C]15[/C][C]0.00952089451675311[/C][/ROW]
[ROW][C]16[/C][C]-0.0700934371917083[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107148&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107148&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 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 series0
krho(Y[t],X[t+k])
-160.0323855994067322
-15-0.0342499660221456
-14-0.0597441590832788
-130.00345818966598631
-12-0.0123110779645512
-11-0.09710148297212
-10-0.0911450152473816
-9-0.156680012777283
-8-0.112838313219394
-7-0.022668557685786
-6-0.00837437841833647
-5-0.0566026727292671
-4-0.150861065623419
-30.0529041336236735
-2-0.0030441093895735
-1-0.114220038187733
0-0.00778127815971281
1-0.0069564675567362
20.155745812521432
3-0.10247905922824
40.137046707647123
50.0683070682732078
6-0.0371257072554045
7-0.128429126482864
8-0.0463413525405561
90.172376183541822
100.00796616670433751
11-0.0500099916757579
12-0.0455740369888212
130.141921642904847
14-0.0353197779369102
150.00952089451675311
16-0.0700934371917083


Figures (Output of Computation)

Input Parameters & R Code

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