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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 25 Apr 2012 15:29:01 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/25/t1335382256x642dmnszlhjcad.htm/, Retrieved Mon, 06 May 2024 23:53:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164845, Retrieved Mon, 06 May 2024 23:53:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords KDGP2W12
Estimated Impact91

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2012-04-25 19:29:01] [09b6c15525a7e41be57b956512900af9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164845&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164845&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164845&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'Gertrude Mary Cox' @ cox.wessa.net






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.024915-0.72980.232852
20.1122293.28740.000526
30.0488711.43150.076325
40.1202263.52160.000226
5-0.018618-0.54540.292825
60.0441661.29370.098062
70.0118650.34760.364132
8-0.022785-0.66740.252345
90.0619611.8150.03494
100.0615331.80240.035917
11-0.006263-0.18350.427243
12-0.020492-0.60030.274246

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.024915 & -0.7298 & 0.232852 \tabularnewline
2 & 0.112229 & 3.2874 & 0.000526 \tabularnewline
3 & 0.048871 & 1.4315 & 0.076325 \tabularnewline
4 & 0.120226 & 3.5216 & 0.000226 \tabularnewline
5 & -0.018618 & -0.5454 & 0.292825 \tabularnewline
6 & 0.044166 & 1.2937 & 0.098062 \tabularnewline
7 & 0.011865 & 0.3476 & 0.364132 \tabularnewline
8 & -0.022785 & -0.6674 & 0.252345 \tabularnewline
9 & 0.061961 & 1.815 & 0.03494 \tabularnewline
10 & 0.061533 & 1.8024 & 0.035917 \tabularnewline
11 & -0.006263 & -0.1835 & 0.427243 \tabularnewline
12 & -0.020492 & -0.6003 & 0.274246 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164845&T=1

[TABLE]
[ROW][C]Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]ACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]-0.024915[/C][C]-0.7298[/C][C]0.232852[/C][/ROW]
[ROW][C]2[/C][C]0.112229[/C][C]3.2874[/C][C]0.000526[/C][/ROW]
[ROW][C]3[/C][C]0.048871[/C][C]1.4315[/C][C]0.076325[/C][/ROW]
[ROW][C]4[/C][C]0.120226[/C][C]3.5216[/C][C]0.000226[/C][/ROW]
[ROW][C]5[/C][C]-0.018618[/C][C]-0.5454[/C][C]0.292825[/C][/ROW]
[ROW][C]6[/C][C]0.044166[/C][C]1.2937[/C][C]0.098062[/C][/ROW]
[ROW][C]7[/C][C]0.011865[/C][C]0.3476[/C][C]0.364132[/C][/ROW]
[ROW][C]8[/C][C]-0.022785[/C][C]-0.6674[/C][C]0.252345[/C][/ROW]
[ROW][C]9[/C][C]0.061961[/C][C]1.815[/C][C]0.03494[/C][/ROW]
[ROW][C]10[/C][C]0.061533[/C][C]1.8024[/C][C]0.035917[/C][/ROW]
[ROW][C]11[/C][C]-0.006263[/C][C]-0.1835[/C][C]0.427243[/C][/ROW]
[ROW][C]12[/C][C]-0.020492[/C][C]-0.6003[/C][C]0.274246[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164845&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164845&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:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.024915-0.72980.232852
20.1122293.28740.000526
30.0488711.43150.076325
40.1202263.52160.000226
5-0.018618-0.54540.292825
60.0441661.29370.098062
70.0118650.34760.364132
8-0.022785-0.66740.252345
90.0619611.8150.03494
100.0615331.80240.035917
11-0.006263-0.18350.427243
12-0.020492-0.60030.274246






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.024915-0.72980.232852
20.1116773.27120.000557
30.0548551.60680.054234
40.1121043.28370.000533
5-0.023774-0.69640.243187
60.0157810.46230.322008
70.0057760.16920.43285
8-0.040546-1.18770.117648
90.0616061.80450.035748
100.0655521.92010.027587
11-0.012456-0.36480.357658
12-0.034887-1.02190.153561

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.024915 & -0.7298 & 0.232852 \tabularnewline
2 & 0.111677 & 3.2712 & 0.000557 \tabularnewline
3 & 0.054855 & 1.6068 & 0.054234 \tabularnewline
4 & 0.112104 & 3.2837 & 0.000533 \tabularnewline
5 & -0.023774 & -0.6964 & 0.243187 \tabularnewline
6 & 0.015781 & 0.4623 & 0.322008 \tabularnewline
7 & 0.005776 & 0.1692 & 0.43285 \tabularnewline
8 & -0.040546 & -1.1877 & 0.117648 \tabularnewline
9 & 0.061606 & 1.8045 & 0.035748 \tabularnewline
10 & 0.065552 & 1.9201 & 0.027587 \tabularnewline
11 & -0.012456 & -0.3648 & 0.357658 \tabularnewline
12 & -0.034887 & -1.0219 & 0.153561 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164845&T=2

[TABLE]
[ROW][C]Partial Autocorrelation Function[/C][/ROW]
[ROW][C]Time lag k[/C][C]PACF(k)[/C][C]T-STAT[/C][C]P-value[/C][/ROW]
[ROW][C]1[/C][C]-0.024915[/C][C]-0.7298[/C][C]0.232852[/C][/ROW]
[ROW][C]2[/C][C]0.111677[/C][C]3.2712[/C][C]0.000557[/C][/ROW]
[ROW][C]3[/C][C]0.054855[/C][C]1.6068[/C][C]0.054234[/C][/ROW]
[ROW][C]4[/C][C]0.112104[/C][C]3.2837[/C][C]0.000533[/C][/ROW]
[ROW][C]5[/C][C]-0.023774[/C][C]-0.6964[/C][C]0.243187[/C][/ROW]
[ROW][C]6[/C][C]0.015781[/C][C]0.4623[/C][C]0.322008[/C][/ROW]
[ROW][C]7[/C][C]0.005776[/C][C]0.1692[/C][C]0.43285[/C][/ROW]
[ROW][C]8[/C][C]-0.040546[/C][C]-1.1877[/C][C]0.117648[/C][/ROW]
[ROW][C]9[/C][C]0.061606[/C][C]1.8045[/C][C]0.035748[/C][/ROW]
[ROW][C]10[/C][C]0.065552[/C][C]1.9201[/C][C]0.027587[/C][/ROW]
[ROW][C]11[/C][C]-0.012456[/C][C]-0.3648[/C][C]0.357658[/C][/ROW]
[ROW][C]12[/C][C]-0.034887[/C][C]-1.0219[/C][C]0.153561[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164845&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164845&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.024915-0.72980.232852
20.1116773.27120.000557
30.0548551.60680.054234
40.1121043.28370.000533
5-0.023774-0.69640.243187
60.0157810.46230.322008
70.0057760.16920.43285
8-0.040546-1.18770.117648
90.0616061.80450.035748
100.0655521.92010.027587
11-0.012456-0.36480.357658
12-0.034887-1.02190.153561


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 12 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '0'
par2 <- '1'
par1 <- 'Default'
if (par1 == 'Default') {
par1 = 10*log10(length(x))
} else {
par1 <- as.numeric(par1)
}
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
par7 <- as.numeric(par7)
if (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
dev.off()
(myacf <- c(racf$acf))
(mypacf <- c(rpacf$acf))
lengthx <- length(x)
sqrtn <- sqrt(lengthx)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 2:(par1+1)) {
a<-table.row.start(a)
a<-table.element(a,i-1,header=TRUE)
a<-table.element(a,round(myacf[i],6))
mytstat <- myacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Time lag k',header=TRUE)
a<-table.element(a,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,'P-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:par1) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,round(mypacf[i],6))
mytstat <- mypacf[i]*sqrtn
a<-table.element(a,round(mytstat,4))
a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')