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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, 19 Dec 2010 19:09:45 +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/19/t1292785656fnnwlsfwhdvagnx.htm/, Retrieved Sat, 04 May 2024 21:52:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112679, Retrieved Sat, 04 May 2024 21:52:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149

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 09:25:48] [b98453cac15ba1066b407e146608df68]
-    D            [Cross Correlation Function] [] [2010-12-19 19:09:45] [6b31f806e9ccc1f74a26091056f791cb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
54.64
52.39
52.51
52.92
55.22
55.41
57.02
58.55
57.49
55.52
57.84
58.69
59.74
60.7
60.74
64.32
66.9
70.93
75.89
80.6
81.39
81.33
77.04
79.54
81.93
80.79
81.98
85.94
86.6
87.42
93.14
95.76
99.75
97.71
94.99
96.41
96.28
100.14
99.9
102.87
107.37
115.68
124.33
128.44
130.19
148.4
169.14
153.98
163.13
165.4
166.35
173.73
174.23
177.04
170.78
174.01
183.76
201.95
205.38
197.36
196.53
179.94
174.84
179.86
172.77
162.56
178.4
190.83
201.07
198.95
190.46
186.27
187.96
174.99
164.1
131.48
116.14
103.43
96.87
93.68
96.49
105.22
110.11
118.47
122.15
137.35
134.83
138.34
141.98
149.45
154.68
145.98
156.33
176.28
159.08
151.18
162.63
174.2
180.51
185.31
186.33
Dataseries Y:
Download CSV
Histogram 
14.36
14.62
13.51
14.95
16.72
16.33
15.21
16.69
15.81
16.02
16.7
15.99
17.68
18.89
18.72
21.14
20.97
23.75
23.05
23.45
21.74
19.37
21.1
21.2
22.67
22.24
23.78
23.27
25.74
26.1
27.49
31.41
28.79
26.76
26.41
27.05
29.43
32.1
36.84
34.22
36.53
40.99
45.97
43.6
47.84
51.47
51.31
48.47
48.28
46.56
43.83
51.17
49.59
49.11
49.97
50.07
53.3
57.08
68.54
71.62
67.64
64.79
80.97
88.42
110.22
99
95.95
107.94
97.82
111.64
114.73
117.58
99.19
90.19
59.74
44.51
23.94
21.29
20.77
25.07
32.95
40.05
44.59
40.28
41.19
38.14
41.85
43.76
50.16
52.94
47.69
51.52
58.69
50.44
45.72
43.24
51.49
50.43
58.73
65.12
64.13

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112679&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112679&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112679&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






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])
-170.391976183063338
-160.433066949762332
-150.474412473636239
-140.515515476420562
-130.548572716671301
-120.571930298731566
-110.590992834818795
-100.605596107414318
-90.61921797796217
-80.637036036736538
-70.665785203910422
-60.69120725831845
-50.715246829942505
-40.743824069743526
-30.778005452465515
-20.809536038289156
-10.83837168984565
00.854281796226088
10.829973551314203
20.784398914631934
30.731347267509663
40.675133183009624
50.607889233920757
60.539139368042909
70.475885889379895
80.41708615181214
90.358354138317626
100.307942376664822
110.261578513965555
120.221134391316744
130.18596777221296
140.164520984068516
150.148001171698494
160.135324701279730
170.124142998745491

\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
-17 & 0.391976183063338 \tabularnewline
-16 & 0.433066949762332 \tabularnewline
-15 & 0.474412473636239 \tabularnewline
-14 & 0.515515476420562 \tabularnewline
-13 & 0.548572716671301 \tabularnewline
-12 & 0.571930298731566 \tabularnewline
-11 & 0.590992834818795 \tabularnewline
-10 & 0.605596107414318 \tabularnewline
-9 & 0.61921797796217 \tabularnewline
-8 & 0.637036036736538 \tabularnewline
-7 & 0.665785203910422 \tabularnewline
-6 & 0.69120725831845 \tabularnewline
-5 & 0.715246829942505 \tabularnewline
-4 & 0.743824069743526 \tabularnewline
-3 & 0.778005452465515 \tabularnewline
-2 & 0.809536038289156 \tabularnewline
-1 & 0.83837168984565 \tabularnewline
0 & 0.854281796226088 \tabularnewline
1 & 0.829973551314203 \tabularnewline
2 & 0.784398914631934 \tabularnewline
3 & 0.731347267509663 \tabularnewline
4 & 0.675133183009624 \tabularnewline
5 & 0.607889233920757 \tabularnewline
6 & 0.539139368042909 \tabularnewline
7 & 0.475885889379895 \tabularnewline
8 & 0.41708615181214 \tabularnewline
9 & 0.358354138317626 \tabularnewline
10 & 0.307942376664822 \tabularnewline
11 & 0.261578513965555 \tabularnewline
12 & 0.221134391316744 \tabularnewline
13 & 0.18596777221296 \tabularnewline
14 & 0.164520984068516 \tabularnewline
15 & 0.148001171698494 \tabularnewline
16 & 0.135324701279730 \tabularnewline
17 & 0.124142998745491 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112679&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]-17[/C][C]0.391976183063338[/C][/ROW]
[ROW][C]-16[/C][C]0.433066949762332[/C][/ROW]
[ROW][C]-15[/C][C]0.474412473636239[/C][/ROW]
[ROW][C]-14[/C][C]0.515515476420562[/C][/ROW]
[ROW][C]-13[/C][C]0.548572716671301[/C][/ROW]
[ROW][C]-12[/C][C]0.571930298731566[/C][/ROW]
[ROW][C]-11[/C][C]0.590992834818795[/C][/ROW]
[ROW][C]-10[/C][C]0.605596107414318[/C][/ROW]
[ROW][C]-9[/C][C]0.61921797796217[/C][/ROW]
[ROW][C]-8[/C][C]0.637036036736538[/C][/ROW]
[ROW][C]-7[/C][C]0.665785203910422[/C][/ROW]
[ROW][C]-6[/C][C]0.69120725831845[/C][/ROW]
[ROW][C]-5[/C][C]0.715246829942505[/C][/ROW]
[ROW][C]-4[/C][C]0.743824069743526[/C][/ROW]
[ROW][C]-3[/C][C]0.778005452465515[/C][/ROW]
[ROW][C]-2[/C][C]0.809536038289156[/C][/ROW]
[ROW][C]-1[/C][C]0.83837168984565[/C][/ROW]
[ROW][C]0[/C][C]0.854281796226088[/C][/ROW]
[ROW][C]1[/C][C]0.829973551314203[/C][/ROW]
[ROW][C]2[/C][C]0.784398914631934[/C][/ROW]
[ROW][C]3[/C][C]0.731347267509663[/C][/ROW]
[ROW][C]4[/C][C]0.675133183009624[/C][/ROW]
[ROW][C]5[/C][C]0.607889233920757[/C][/ROW]
[ROW][C]6[/C][C]0.539139368042909[/C][/ROW]
[ROW][C]7[/C][C]0.475885889379895[/C][/ROW]
[ROW][C]8[/C][C]0.41708615181214[/C][/ROW]
[ROW][C]9[/C][C]0.358354138317626[/C][/ROW]
[ROW][C]10[/C][C]0.307942376664822[/C][/ROW]
[ROW][C]11[/C][C]0.261578513965555[/C][/ROW]
[ROW][C]12[/C][C]0.221134391316744[/C][/ROW]
[ROW][C]13[/C][C]0.18596777221296[/C][/ROW]
[ROW][C]14[/C][C]0.164520984068516[/C][/ROW]
[ROW][C]15[/C][C]0.148001171698494[/C][/ROW]
[ROW][C]16[/C][C]0.135324701279730[/C][/ROW]
[ROW][C]17[/C][C]0.124142998745491[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112679&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112679&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])
-170.391976183063338
-160.433066949762332
-150.474412473636239
-140.515515476420562
-130.548572716671301
-120.571930298731566
-110.590992834818795
-100.605596107414318
-90.61921797796217
-80.637036036736538
-70.665785203910422
-60.69120725831845
-50.715246829942505
-40.743824069743526
-30.778005452465515
-20.809536038289156
-10.83837168984565
00.854281796226088
10.829973551314203
20.784398914631934
30.731347267509663
40.675133183009624
50.607889233920757
60.539139368042909
70.475885889379895
80.41708615181214
90.358354138317626
100.307942376664822
110.261578513965555
120.221134391316744
130.18596777221296
140.164520984068516
150.148001171698494
160.135324701279730
170.124142998745491


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) 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')