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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 computationTue, 02 Dec 2008 08:56:51 -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/02/t12282334644yghejrea0orgwx.htm/, Retrieved Sun, 19 May 2024 11:15:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27984, Retrieved Sun, 19 May 2024 11:15:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [] [2008-12-02 15:26:02] [74be16979710d4c4e7c6647856088456]
- RMPD    [Cross Correlation Function] [] [2008-12-02 15:56:51] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
132.7
128.6
127.8
128.9
124.6
129.2
130.5
124.3
125.8
123.5
120.7
123.1
122.0
121.0
121.2
117.4
113.0
113.1
116.1
121.3
108.6
114.3
113.5
111.2
109.3
108.2
102.7
110.4
108.1
112.8
108.1
102.6
109.2
108.2
107.1
108.4
103.6
104.0
111.5
105.4
Dataseries Y:
Download CSV
Histogram 
116.5
118.2
118.8
116.4
118.6
131.4
119.4
119.3
119.1
119.4
120.4
120.3
118.3
118.9
119.9
119.2
118.6
117.5
118.2
120.4
118.0
119.6
120.1
118.5
112.0
112.9
111.1
114.8
113.8
110.8
113.3
115.3
115.1
115.4
113.2
119.4
119.3
115.8
112.8
115.2

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27984&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27984&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27984&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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 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])
-12-0.0593021112550188
-110.00454952506724006
-100.0539783175901577
-90.0601909115510137
-8-0.0898173021123936
-7-0.0229200663202682
-6-0.0923121199316536
-50.0386692472408530
-4-0.00595092978105064
-3-0.0117774618372751
-2-0.0859879969761262
-10.0574086920916397
0-0.0375239302571145
1-0.074265012763171
2-0.101121623637660
3-0.098688146765469
4-0.062852593904608
50.0429776980965335
60.0183216400784418
7-0.0666089762366671
8-0.0826708673000027
9-0.0185429822370970
10-0.0776735104233913
11-0.02657993317617
120.117335365716817

\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 & 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
-12 & -0.0593021112550188 \tabularnewline
-11 & 0.00454952506724006 \tabularnewline
-10 & 0.0539783175901577 \tabularnewline
-9 & 0.0601909115510137 \tabularnewline
-8 & -0.0898173021123936 \tabularnewline
-7 & -0.0229200663202682 \tabularnewline
-6 & -0.0923121199316536 \tabularnewline
-5 & 0.0386692472408530 \tabularnewline
-4 & -0.00595092978105064 \tabularnewline
-3 & -0.0117774618372751 \tabularnewline
-2 & -0.0859879969761262 \tabularnewline
-1 & 0.0574086920916397 \tabularnewline
0 & -0.0375239302571145 \tabularnewline
1 & -0.074265012763171 \tabularnewline
2 & -0.101121623637660 \tabularnewline
3 & -0.098688146765469 \tabularnewline
4 & -0.062852593904608 \tabularnewline
5 & 0.0429776980965335 \tabularnewline
6 & 0.0183216400784418 \tabularnewline
7 & -0.0666089762366671 \tabularnewline
8 & -0.0826708673000027 \tabularnewline
9 & -0.0185429822370970 \tabularnewline
10 & -0.0776735104233913 \tabularnewline
11 & -0.02657993317617 \tabularnewline
12 & 0.117335365716817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27984&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]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]-12[/C][C]-0.0593021112550188[/C][/ROW]
[ROW][C]-11[/C][C]0.00454952506724006[/C][/ROW]
[ROW][C]-10[/C][C]0.0539783175901577[/C][/ROW]
[ROW][C]-9[/C][C]0.0601909115510137[/C][/ROW]
[ROW][C]-8[/C][C]-0.0898173021123936[/C][/ROW]
[ROW][C]-7[/C][C]-0.0229200663202682[/C][/ROW]
[ROW][C]-6[/C][C]-0.0923121199316536[/C][/ROW]
[ROW][C]-5[/C][C]0.0386692472408530[/C][/ROW]
[ROW][C]-4[/C][C]-0.00595092978105064[/C][/ROW]
[ROW][C]-3[/C][C]-0.0117774618372751[/C][/ROW]
[ROW][C]-2[/C][C]-0.0859879969761262[/C][/ROW]
[ROW][C]-1[/C][C]0.0574086920916397[/C][/ROW]
[ROW][C]0[/C][C]-0.0375239302571145[/C][/ROW]
[ROW][C]1[/C][C]-0.074265012763171[/C][/ROW]
[ROW][C]2[/C][C]-0.101121623637660[/C][/ROW]
[ROW][C]3[/C][C]-0.098688146765469[/C][/ROW]
[ROW][C]4[/C][C]-0.062852593904608[/C][/ROW]
[ROW][C]5[/C][C]0.0429776980965335[/C][/ROW]
[ROW][C]6[/C][C]0.0183216400784418[/C][/ROW]
[ROW][C]7[/C][C]-0.0666089762366671[/C][/ROW]
[ROW][C]8[/C][C]-0.0826708673000027[/C][/ROW]
[ROW][C]9[/C][C]-0.0185429822370970[/C][/ROW]
[ROW][C]10[/C][C]-0.0776735104233913[/C][/ROW]
[ROW][C]11[/C][C]-0.02657993317617[/C][/ROW]
[ROW][C]12[/C][C]0.117335365716817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27984&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27984&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 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])
-12-0.0593021112550188
-110.00454952506724006
-100.0539783175901577
-90.0601909115510137
-8-0.0898173021123936
-7-0.0229200663202682
-6-0.0923121199316536
-50.0386692472408530
-4-0.00595092978105064
-3-0.0117774618372751
-2-0.0859879969761262
-10.0574086920916397
0-0.0375239302571145
1-0.074265012763171
2-0.101121623637660
3-0.098688146765469
4-0.062852593904608
50.0429776980965335
60.0183216400784418
7-0.0666089762366671
8-0.0826708673000027
9-0.0185429822370970
10-0.0776735104233913
11-0.02657993317617
120.117335365716817


Figures (Output of Computation)

Input Parameters & R Code

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