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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, 01 Dec 2008 05:16:39 -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/01/t1228133834y2b5cmpas5sfk3v.htm/, Retrieved Sun, 05 May 2024 16:10:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26895, Retrieved Sun, 05 May 2024 16:10:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196

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] [Q7 Cross correlat...] [2008-11-30 17:52:44] [2d4aec5ed1856c4828162be37be304d9]
-   PD  [Cross Correlation Function] [Q7 CCF] [2008-12-01 11:34:58] [2d4aec5ed1856c4828162be37be304d9]
-   P       [Cross Correlation Function] [Q9 CCF] [2008-12-01 12:16:39] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
115.9
96
97.6
Dataseries Y:
Download CSV
Histogram 
148.8
146.7
118.8
99.4
97.6
110.2
146.6
136.4
126.2
154.9
109
128.5
144.9
136.3
134.8
103.4
106.6
119.2
149.3
150.2
142.9
163.6
98.2
138.2
143.7
132.8
149.4
128.8
98.9
106.2
140.7
133
156.4
157.7
107.9
133.6
148.1
205.6
193.1
117.5
116.4
129.5
157.1
157
158.4
161.7
116.9
161.1
155.7
160.8
145.4
111
144.8
149.2
156.6
182.5
171.3
172.7
133
148.1

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'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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26895&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26895&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26895&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'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series2
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 series0.1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.068698693702569
-12-0.0046645995637923
-110.233581600255054
-100.0309523924322575
-90.0157011715578688
-80.131307483279505
-70.0392327856327341
-60.247023485231335
-50.211198698693762
-4-0.0450054193735484
-30.0519494199510339
-20.00499978094620672
-1-0.117141251376232
00.372796520062981
1-0.115609909576300
2-0.144226281877777
30.125972498363372
4-0.113892989885277
50.113256557441453
6-0.0448322799703757
7-0.171076724495605
8-0.0250495436796872
90.186972104454703
100.0444795433138197
11-0.0572233555720028
120.0497040799636459
13-0.0913128842595816

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 2 \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 & 0.1 \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
-13 & -0.068698693702569 \tabularnewline
-12 & -0.0046645995637923 \tabularnewline
-11 & 0.233581600255054 \tabularnewline
-10 & 0.0309523924322575 \tabularnewline
-9 & 0.0157011715578688 \tabularnewline
-8 & 0.131307483279505 \tabularnewline
-7 & 0.0392327856327341 \tabularnewline
-6 & 0.247023485231335 \tabularnewline
-5 & 0.211198698693762 \tabularnewline
-4 & -0.0450054193735484 \tabularnewline
-3 & 0.0519494199510339 \tabularnewline
-2 & 0.00499978094620672 \tabularnewline
-1 & -0.117141251376232 \tabularnewline
0 & 0.372796520062981 \tabularnewline
1 & -0.115609909576300 \tabularnewline
2 & -0.144226281877777 \tabularnewline
3 & 0.125972498363372 \tabularnewline
4 & -0.113892989885277 \tabularnewline
5 & 0.113256557441453 \tabularnewline
6 & -0.0448322799703757 \tabularnewline
7 & -0.171076724495605 \tabularnewline
8 & -0.0250495436796872 \tabularnewline
9 & 0.186972104454703 \tabularnewline
10 & 0.0444795433138197 \tabularnewline
11 & -0.0572233555720028 \tabularnewline
12 & 0.0497040799636459 \tabularnewline
13 & -0.0913128842595816 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26895&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]2[/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]0.1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.068698693702569[/C][/ROW]
[ROW][C]-12[/C][C]-0.0046645995637923[/C][/ROW]
[ROW][C]-11[/C][C]0.233581600255054[/C][/ROW]
[ROW][C]-10[/C][C]0.0309523924322575[/C][/ROW]
[ROW][C]-9[/C][C]0.0157011715578688[/C][/ROW]
[ROW][C]-8[/C][C]0.131307483279505[/C][/ROW]
[ROW][C]-7[/C][C]0.0392327856327341[/C][/ROW]
[ROW][C]-6[/C][C]0.247023485231335[/C][/ROW]
[ROW][C]-5[/C][C]0.211198698693762[/C][/ROW]
[ROW][C]-4[/C][C]-0.0450054193735484[/C][/ROW]
[ROW][C]-3[/C][C]0.0519494199510339[/C][/ROW]
[ROW][C]-2[/C][C]0.00499978094620672[/C][/ROW]
[ROW][C]-1[/C][C]-0.117141251376232[/C][/ROW]
[ROW][C]0[/C][C]0.372796520062981[/C][/ROW]
[ROW][C]1[/C][C]-0.115609909576300[/C][/ROW]
[ROW][C]2[/C][C]-0.144226281877777[/C][/ROW]
[ROW][C]3[/C][C]0.125972498363372[/C][/ROW]
[ROW][C]4[/C][C]-0.113892989885277[/C][/ROW]
[ROW][C]5[/C][C]0.113256557441453[/C][/ROW]
[ROW][C]6[/C][C]-0.0448322799703757[/C][/ROW]
[ROW][C]7[/C][C]-0.171076724495605[/C][/ROW]
[ROW][C]8[/C][C]-0.0250495436796872[/C][/ROW]
[ROW][C]9[/C][C]0.186972104454703[/C][/ROW]
[ROW][C]10[/C][C]0.0444795433138197[/C][/ROW]
[ROW][C]11[/C][C]-0.0572233555720028[/C][/ROW]
[ROW][C]12[/C][C]0.0497040799636459[/C][/ROW]
[ROW][C]13[/C][C]-0.0913128842595816[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26895&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26895&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 series2
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 series0.1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.068698693702569
-12-0.0046645995637923
-110.233581600255054
-100.0309523924322575
-90.0157011715578688
-80.131307483279505
-70.0392327856327341
-60.247023485231335
-50.211198698693762
-4-0.0450054193735484
-30.0519494199510339
-20.00499978094620672
-1-0.117141251376232
00.372796520062981
1-0.115609909576300
2-0.144226281877777
30.125972498363372
4-0.113892989885277
50.113256557441453
6-0.0448322799703757
7-0.171076724495605
8-0.0250495436796872
90.186972104454703
100.0444795433138197
11-0.0572233555720028
120.0497040799636459
13-0.0913128842595816


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 0.1 ; 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')