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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 computationMon, 08 Dec 2008 14:45:34 -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/08/t12287727783pv2r4cps5uvk0v.htm/, Retrieved Thu, 16 May 2024 14:38:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31085, Retrieved Thu, 16 May 2024 14:38:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [(Partial) Autocorrelation Function] [Q6 1] [2008-11-29 17:27:48] [aa5573c1db401b164e448aef050955a1]
-   P     [(Partial) Autocorrelation Function] [Q6 2] [2008-11-29 17:36:16] [aa5573c1db401b164e448aef050955a1]
- RMP       [Variance Reduction Matrix] [Q6 VRM] [2008-11-29 17:44:58] [aa5573c1db401b164e448aef050955a1]
- RMPD        [Cross Correlation Function] [Q7 bouwproductie-...] [2008-11-29 23:52:28] [aa5573c1db401b164e448aef050955a1]
-               [Cross Correlation Function] [Q9 Cross Correlat...] [2008-11-30 00:49:16] [aa5573c1db401b164e448aef050955a1]
-   P               [Cross Correlation Function] [Correctie Q9] [2008-12-08 21:45:34] [8a1195ff8db4df756ce44b463a631c76] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3
99.4
85.9
109.4
97.6
Dataseries Y:
Download CSV
Histogram 
97.4
97
105.4
102.7
98.1
104.5
87.4
89.9
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31085&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31085&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31085&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'Gwilym Jenkins' @ 72.249.127.135






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 series-0.2
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-14-0.114870421074566
-13-0.0166038126257455
-12-0.0545200497972176
-110.00605529351210127
-10-0.0165828071305758
-90.145338229017926
-80.078146843851905
-7-0.0254950892507797
-60.288326725313428
-50.07561082355591
-40.112699349483332
-30.0891581429905266
-20.148549448331679
-1-0.227472072935884
00.825539378440313
1-0.278230720751615
20.0403460525405211
30.220221585659712
40.00907389000663658
5-0.0355686349416026
60.237302525480769
7-0.140807452786591
80.0244274773428329
90.277324969375011
10-0.0198005323757452
11-0.0229805518362877
120.0468172091140052
130.0138705855192229
14-0.0337209107962623

\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 & -0.2 \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
-14 & -0.114870421074566 \tabularnewline
-13 & -0.0166038126257455 \tabularnewline
-12 & -0.0545200497972176 \tabularnewline
-11 & 0.00605529351210127 \tabularnewline
-10 & -0.0165828071305758 \tabularnewline
-9 & 0.145338229017926 \tabularnewline
-8 & 0.078146843851905 \tabularnewline
-7 & -0.0254950892507797 \tabularnewline
-6 & 0.288326725313428 \tabularnewline
-5 & 0.07561082355591 \tabularnewline
-4 & 0.112699349483332 \tabularnewline
-3 & 0.0891581429905266 \tabularnewline
-2 & 0.148549448331679 \tabularnewline
-1 & -0.227472072935884 \tabularnewline
0 & 0.825539378440313 \tabularnewline
1 & -0.278230720751615 \tabularnewline
2 & 0.0403460525405211 \tabularnewline
3 & 0.220221585659712 \tabularnewline
4 & 0.00907389000663658 \tabularnewline
5 & -0.0355686349416026 \tabularnewline
6 & 0.237302525480769 \tabularnewline
7 & -0.140807452786591 \tabularnewline
8 & 0.0244274773428329 \tabularnewline
9 & 0.277324969375011 \tabularnewline
10 & -0.0198005323757452 \tabularnewline
11 & -0.0229805518362877 \tabularnewline
12 & 0.0468172091140052 \tabularnewline
13 & 0.0138705855192229 \tabularnewline
14 & -0.0337209107962623 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31085&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]-0.2[/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]-14[/C][C]-0.114870421074566[/C][/ROW]
[ROW][C]-13[/C][C]-0.0166038126257455[/C][/ROW]
[ROW][C]-12[/C][C]-0.0545200497972176[/C][/ROW]
[ROW][C]-11[/C][C]0.00605529351210127[/C][/ROW]
[ROW][C]-10[/C][C]-0.0165828071305758[/C][/ROW]
[ROW][C]-9[/C][C]0.145338229017926[/C][/ROW]
[ROW][C]-8[/C][C]0.078146843851905[/C][/ROW]
[ROW][C]-7[/C][C]-0.0254950892507797[/C][/ROW]
[ROW][C]-6[/C][C]0.288326725313428[/C][/ROW]
[ROW][C]-5[/C][C]0.07561082355591[/C][/ROW]
[ROW][C]-4[/C][C]0.112699349483332[/C][/ROW]
[ROW][C]-3[/C][C]0.0891581429905266[/C][/ROW]
[ROW][C]-2[/C][C]0.148549448331679[/C][/ROW]
[ROW][C]-1[/C][C]-0.227472072935884[/C][/ROW]
[ROW][C]0[/C][C]0.825539378440313[/C][/ROW]
[ROW][C]1[/C][C]-0.278230720751615[/C][/ROW]
[ROW][C]2[/C][C]0.0403460525405211[/C][/ROW]
[ROW][C]3[/C][C]0.220221585659712[/C][/ROW]
[ROW][C]4[/C][C]0.00907389000663658[/C][/ROW]
[ROW][C]5[/C][C]-0.0355686349416026[/C][/ROW]
[ROW][C]6[/C][C]0.237302525480769[/C][/ROW]
[ROW][C]7[/C][C]-0.140807452786591[/C][/ROW]
[ROW][C]8[/C][C]0.0244274773428329[/C][/ROW]
[ROW][C]9[/C][C]0.277324969375011[/C][/ROW]
[ROW][C]10[/C][C]-0.0198005323757452[/C][/ROW]
[ROW][C]11[/C][C]-0.0229805518362877[/C][/ROW]
[ROW][C]12[/C][C]0.0468172091140052[/C][/ROW]
[ROW][C]13[/C][C]0.0138705855192229[/C][/ROW]
[ROW][C]14[/C][C]-0.0337209107962623[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31085&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31085&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 series-0.2
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-14-0.114870421074566
-13-0.0166038126257455
-12-0.0545200497972176
-110.00605529351210127
-10-0.0165828071305758
-90.145338229017926
-80.078146843851905
-7-0.0254950892507797
-60.288326725313428
-50.07561082355591
-40.112699349483332
-30.0891581429905266
-20.148549448331679
-1-0.227472072935884
00.825539378440313
1-0.278230720751615
20.0403460525405211
30.220221585659712
40.00907389000663658
5-0.0355686349416026
60.237302525480769
7-0.140807452786591
80.0244274773428329
90.277324969375011
10-0.0198005323757452
11-0.0229805518362877
120.0468172091140052
130.0138705855192229
14-0.0337209107962623


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.0 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 0.0 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -0.2 ; 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')