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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSun, 22 Dec 2013 07:18:06 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/22/t1387714749eunh4h7vdl4sc6i.htm/, Retrieved Sun, 05 Dec 2021 16:19:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232506, Retrieved Sun, 05 Dec 2021 16:19:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2013-12-22 12:18:06] [54713e3426a13268f2edfca2b563126c] [Current]
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Dataseries X:
0,43
0,45
0,44
0,44
0,44
0,48
0,47
0,47
0,47
0,49
0,49
0,46
0,45
0,44
0,42
0,43
0,43
0,47
0,47
0,47
0,47
0,48
0,48
0,48
0,49
0,49
0,47
0,5
0,51
0,5
0,49
0,5
0,51
0,51
0,5
0,53
0,5
0,49
0,46
0,46
0,47
0,49
0,5
0,5
0,51
0,5
0,52
0,5
0,48
0,47
0,43
0,42
0,45
0,5
0,52
0,52
0,51
0,52
0,52
0,51
0,51
0,51
0,48
0,49
0,47
0,51
0,5
0,51
0,51
0,52
0,51
0,52
0,48
0,49
0,47
0,44
0,44
0,47
0,51
0,51
0,52
0,52
0,52
0,52




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 5 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232506&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232506&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232506&T=0

As an alternative you can also use a 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 time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0298130.27160.393297
20.0656070.59770.275832
3-0.231511-2.10920.018972
4-0.017412-0.15860.437173
5-0.211518-1.9270.028699
6-0.177776-1.61960.054554
7-0.118674-1.08120.141375
80.0660490.60170.274494
9-0.162627-1.48160.071116
100.006820.06210.475304
110.1110551.01180.157297
120.2938142.67680.004478
130.1162511.05910.146314
140.0606870.55290.290914
15-0.134205-1.22270.112458
16-0.098019-0.8930.187221
17-0.085229-0.77650.219839
18-0.027698-0.25230.4007
19-0.044284-0.40340.343829

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.029813 & 0.2716 & 0.393297 \tabularnewline
2 & 0.065607 & 0.5977 & 0.275832 \tabularnewline
3 & -0.231511 & -2.1092 & 0.018972 \tabularnewline
4 & -0.017412 & -0.1586 & 0.437173 \tabularnewline
5 & -0.211518 & -1.927 & 0.028699 \tabularnewline
6 & -0.177776 & -1.6196 & 0.054554 \tabularnewline
7 & -0.118674 & -1.0812 & 0.141375 \tabularnewline
8 & 0.066049 & 0.6017 & 0.274494 \tabularnewline
9 & -0.162627 & -1.4816 & 0.071116 \tabularnewline
10 & 0.00682 & 0.0621 & 0.475304 \tabularnewline
11 & 0.111055 & 1.0118 & 0.157297 \tabularnewline
12 & 0.293814 & 2.6768 & 0.004478 \tabularnewline
13 & 0.116251 & 1.0591 & 0.146314 \tabularnewline
14 & 0.060687 & 0.5529 & 0.290914 \tabularnewline
15 & -0.134205 & -1.2227 & 0.112458 \tabularnewline
16 & -0.098019 & -0.893 & 0.187221 \tabularnewline
17 & -0.085229 & -0.7765 & 0.219839 \tabularnewline
18 & -0.027698 & -0.2523 & 0.4007 \tabularnewline
19 & -0.044284 & -0.4034 & 0.343829 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232506&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]0.029813[/C][C]0.2716[/C][C]0.393297[/C][/ROW]
[ROW][C]2[/C][C]0.065607[/C][C]0.5977[/C][C]0.275832[/C][/ROW]
[ROW][C]3[/C][C]-0.231511[/C][C]-2.1092[/C][C]0.018972[/C][/ROW]
[ROW][C]4[/C][C]-0.017412[/C][C]-0.1586[/C][C]0.437173[/C][/ROW]
[ROW][C]5[/C][C]-0.211518[/C][C]-1.927[/C][C]0.028699[/C][/ROW]
[ROW][C]6[/C][C]-0.177776[/C][C]-1.6196[/C][C]0.054554[/C][/ROW]
[ROW][C]7[/C][C]-0.118674[/C][C]-1.0812[/C][C]0.141375[/C][/ROW]
[ROW][C]8[/C][C]0.066049[/C][C]0.6017[/C][C]0.274494[/C][/ROW]
[ROW][C]9[/C][C]-0.162627[/C][C]-1.4816[/C][C]0.071116[/C][/ROW]
[ROW][C]10[/C][C]0.00682[/C][C]0.0621[/C][C]0.475304[/C][/ROW]
[ROW][C]11[/C][C]0.111055[/C][C]1.0118[/C][C]0.157297[/C][/ROW]
[ROW][C]12[/C][C]0.293814[/C][C]2.6768[/C][C]0.004478[/C][/ROW]
[ROW][C]13[/C][C]0.116251[/C][C]1.0591[/C][C]0.146314[/C][/ROW]
[ROW][C]14[/C][C]0.060687[/C][C]0.5529[/C][C]0.290914[/C][/ROW]
[ROW][C]15[/C][C]-0.134205[/C][C]-1.2227[/C][C]0.112458[/C][/ROW]
[ROW][C]16[/C][C]-0.098019[/C][C]-0.893[/C][C]0.187221[/C][/ROW]
[ROW][C]17[/C][C]-0.085229[/C][C]-0.7765[/C][C]0.219839[/C][/ROW]
[ROW][C]18[/C][C]-0.027698[/C][C]-0.2523[/C][C]0.4007[/C][/ROW]
[ROW][C]19[/C][C]-0.044284[/C][C]-0.4034[/C][C]0.343829[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232506&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232506&T=1

As an alternative you can also use a QR Code:  

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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0298130.27160.393297
20.0656070.59770.275832
3-0.231511-2.10920.018972
4-0.017412-0.15860.437173
5-0.211518-1.9270.028699
6-0.177776-1.61960.054554
7-0.118674-1.08120.141375
80.0660490.60170.274494
9-0.162627-1.48160.071116
100.006820.06210.475304
110.1110551.01180.157297
120.2938142.67680.004478
130.1162511.05910.146314
140.0606870.55290.290914
15-0.134205-1.22270.112458
16-0.098019-0.8930.187221
17-0.085229-0.77650.219839
18-0.027698-0.25230.4007
19-0.044284-0.40340.343829







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0298130.27160.393297
20.0647750.59010.278353
3-0.236473-2.15440.017055
4-0.005369-0.04890.480554
5-0.190063-1.73160.043534
6-0.237147-2.16050.016808
7-0.11402-1.03880.150963
8-0.020032-0.18250.427818
9-0.313715-2.85810.002693
10-0.150456-1.37070.087079
110.025220.22980.409421
120.0913840.83250.203744
130.0413370.37660.353716
140.0326040.2970.38359
15-0.150778-1.37370.086624
16-0.115204-1.04960.148485
170.0771410.70280.242077
180.019030.17340.431389
19-0.054439-0.4960.310617

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.029813 & 0.2716 & 0.393297 \tabularnewline
2 & 0.064775 & 0.5901 & 0.278353 \tabularnewline
3 & -0.236473 & -2.1544 & 0.017055 \tabularnewline
4 & -0.005369 & -0.0489 & 0.480554 \tabularnewline
5 & -0.190063 & -1.7316 & 0.043534 \tabularnewline
6 & -0.237147 & -2.1605 & 0.016808 \tabularnewline
7 & -0.11402 & -1.0388 & 0.150963 \tabularnewline
8 & -0.020032 & -0.1825 & 0.427818 \tabularnewline
9 & -0.313715 & -2.8581 & 0.002693 \tabularnewline
10 & -0.150456 & -1.3707 & 0.087079 \tabularnewline
11 & 0.02522 & 0.2298 & 0.409421 \tabularnewline
12 & 0.091384 & 0.8325 & 0.203744 \tabularnewline
13 & 0.041337 & 0.3766 & 0.353716 \tabularnewline
14 & 0.032604 & 0.297 & 0.38359 \tabularnewline
15 & -0.150778 & -1.3737 & 0.086624 \tabularnewline
16 & -0.115204 & -1.0496 & 0.148485 \tabularnewline
17 & 0.077141 & 0.7028 & 0.242077 \tabularnewline
18 & 0.01903 & 0.1734 & 0.431389 \tabularnewline
19 & -0.054439 & -0.496 & 0.310617 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232506&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]0.029813[/C][C]0.2716[/C][C]0.393297[/C][/ROW]
[ROW][C]2[/C][C]0.064775[/C][C]0.5901[/C][C]0.278353[/C][/ROW]
[ROW][C]3[/C][C]-0.236473[/C][C]-2.1544[/C][C]0.017055[/C][/ROW]
[ROW][C]4[/C][C]-0.005369[/C][C]-0.0489[/C][C]0.480554[/C][/ROW]
[ROW][C]5[/C][C]-0.190063[/C][C]-1.7316[/C][C]0.043534[/C][/ROW]
[ROW][C]6[/C][C]-0.237147[/C][C]-2.1605[/C][C]0.016808[/C][/ROW]
[ROW][C]7[/C][C]-0.11402[/C][C]-1.0388[/C][C]0.150963[/C][/ROW]
[ROW][C]8[/C][C]-0.020032[/C][C]-0.1825[/C][C]0.427818[/C][/ROW]
[ROW][C]9[/C][C]-0.313715[/C][C]-2.8581[/C][C]0.002693[/C][/ROW]
[ROW][C]10[/C][C]-0.150456[/C][C]-1.3707[/C][C]0.087079[/C][/ROW]
[ROW][C]11[/C][C]0.02522[/C][C]0.2298[/C][C]0.409421[/C][/ROW]
[ROW][C]12[/C][C]0.091384[/C][C]0.8325[/C][C]0.203744[/C][/ROW]
[ROW][C]13[/C][C]0.041337[/C][C]0.3766[/C][C]0.353716[/C][/ROW]
[ROW][C]14[/C][C]0.032604[/C][C]0.297[/C][C]0.38359[/C][/ROW]
[ROW][C]15[/C][C]-0.150778[/C][C]-1.3737[/C][C]0.086624[/C][/ROW]
[ROW][C]16[/C][C]-0.115204[/C][C]-1.0496[/C][C]0.148485[/C][/ROW]
[ROW][C]17[/C][C]0.077141[/C][C]0.7028[/C][C]0.242077[/C][/ROW]
[ROW][C]18[/C][C]0.01903[/C][C]0.1734[/C][C]0.431389[/C][/ROW]
[ROW][C]19[/C][C]-0.054439[/C][C]-0.496[/C][C]0.310617[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232506&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232506&T=2

As an alternative you can also use a QR Code:  

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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0298130.27160.393297
20.0647750.59010.278353
3-0.236473-2.15440.017055
4-0.005369-0.04890.480554
5-0.190063-1.73160.043534
6-0.237147-2.16050.016808
7-0.11402-1.03880.150963
8-0.020032-0.18250.427818
9-0.313715-2.85810.002693
10-0.150456-1.37070.087079
110.025220.22980.409421
120.0913840.83250.203744
130.0413370.37660.353716
140.0326040.2970.38359
15-0.150778-1.37370.086624
16-0.115204-1.04960.148485
170.0771410.70280.242077
180.019030.17340.431389
19-0.054439-0.4960.310617



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;
R code (references can be found in the software module):
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')