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Author's title

Author*Unverified author*
R Software Module--
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 04 Dec 2012 10:54:33 -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/2012/Dec/04/t13546364992qvo1fpjcxk1tee.htm/, Retrieved Tue, 23 Apr 2024 21:42:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196322, Retrieved Tue, 23 Apr 2024 21:42:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [(Partial) Autocorrelation Function] [Births] [2010-11-29 09:36:27] [b98453cac15ba1066b407e146608df68]
- R PD          [(Partial) Autocorrelation Function] [ws9 3.1 ACF d=0, D=1] [2010-12-07 10:32:56] [afe9379cca749d06b3d6872e02cc47ed]
- RM                [(Partial) Autocorrelation Function] [] [2012-12-04 15:54:33] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
12008
9169
8788
8417
8247
8197
8236
8253
7733
8366
8626
8863
10102
8463
9114
8563
8872
8301
8301
8278
7736
7973
8268
9476
11100
8962
9173
8738
8459
8078
8411
8291
7810
8616
8312
9692
9911
8915
9452
9112
8472
8230
8384
8625
8221
8649
8625
10443
10357
8586
8892
8329
8101
7922
8120
7838
7735
8406
8209
9451
10041
9411
10405
8467
8464
8102
7627
7513
7510
8291
8064
9383
9706
8579
9474
8318
8213
8059
9111
7708
7680
8014
8007
8718
9486
9113
9025
8476
7952
7759
7835
7600
7651
8319
8812
8630




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196322&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196322&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3635063.33160.000643
20.0440520.40370.343714
3-0.12229-1.12080.132782
4-0.177569-1.62750.053693
5-0.190564-1.74650.042186
6-0.073214-0.6710.252026
70.0645470.59160.277861
80.0327680.30030.382338
90.0994730.91170.182273
10-0.087425-0.80130.212619
11-0.369297-3.38470.000543
12-0.474287-4.34691.9e-05
13-0.11077-1.01520.156457
140.1785151.63610.052778
150.2399922.19960.015293
160.3237152.96690.001958
170.2160991.98060.025456
180.0688250.63080.264944
19-0.022489-0.20610.418599

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.363506 & 3.3316 & 0.000643 \tabularnewline
2 & 0.044052 & 0.4037 & 0.343714 \tabularnewline
3 & -0.12229 & -1.1208 & 0.132782 \tabularnewline
4 & -0.177569 & -1.6275 & 0.053693 \tabularnewline
5 & -0.190564 & -1.7465 & 0.042186 \tabularnewline
6 & -0.073214 & -0.671 & 0.252026 \tabularnewline
7 & 0.064547 & 0.5916 & 0.277861 \tabularnewline
8 & 0.032768 & 0.3003 & 0.382338 \tabularnewline
9 & 0.099473 & 0.9117 & 0.182273 \tabularnewline
10 & -0.087425 & -0.8013 & 0.212619 \tabularnewline
11 & -0.369297 & -3.3847 & 0.000543 \tabularnewline
12 & -0.474287 & -4.3469 & 1.9e-05 \tabularnewline
13 & -0.11077 & -1.0152 & 0.156457 \tabularnewline
14 & 0.178515 & 1.6361 & 0.052778 \tabularnewline
15 & 0.239992 & 2.1996 & 0.015293 \tabularnewline
16 & 0.323715 & 2.9669 & 0.001958 \tabularnewline
17 & 0.216099 & 1.9806 & 0.025456 \tabularnewline
18 & 0.068825 & 0.6308 & 0.264944 \tabularnewline
19 & -0.022489 & -0.2061 & 0.418599 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196322&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]0.363506[/C][C]3.3316[/C][C]0.000643[/C][/ROW]
[ROW][C]2[/C][C]0.044052[/C][C]0.4037[/C][C]0.343714[/C][/ROW]
[ROW][C]3[/C][C]-0.12229[/C][C]-1.1208[/C][C]0.132782[/C][/ROW]
[ROW][C]4[/C][C]-0.177569[/C][C]-1.6275[/C][C]0.053693[/C][/ROW]
[ROW][C]5[/C][C]-0.190564[/C][C]-1.7465[/C][C]0.042186[/C][/ROW]
[ROW][C]6[/C][C]-0.073214[/C][C]-0.671[/C][C]0.252026[/C][/ROW]
[ROW][C]7[/C][C]0.064547[/C][C]0.5916[/C][C]0.277861[/C][/ROW]
[ROW][C]8[/C][C]0.032768[/C][C]0.3003[/C][C]0.382338[/C][/ROW]
[ROW][C]9[/C][C]0.099473[/C][C]0.9117[/C][C]0.182273[/C][/ROW]
[ROW][C]10[/C][C]-0.087425[/C][C]-0.8013[/C][C]0.212619[/C][/ROW]
[ROW][C]11[/C][C]-0.369297[/C][C]-3.3847[/C][C]0.000543[/C][/ROW]
[ROW][C]12[/C][C]-0.474287[/C][C]-4.3469[/C][C]1.9e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.11077[/C][C]-1.0152[/C][C]0.156457[/C][/ROW]
[ROW][C]14[/C][C]0.178515[/C][C]1.6361[/C][C]0.052778[/C][/ROW]
[ROW][C]15[/C][C]0.239992[/C][C]2.1996[/C][C]0.015293[/C][/ROW]
[ROW][C]16[/C][C]0.323715[/C][C]2.9669[/C][C]0.001958[/C][/ROW]
[ROW][C]17[/C][C]0.216099[/C][C]1.9806[/C][C]0.025456[/C][/ROW]
[ROW][C]18[/C][C]0.068825[/C][C]0.6308[/C][C]0.264944[/C][/ROW]
[ROW][C]19[/C][C]-0.022489[/C][C]-0.2061[/C][C]0.418599[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196322&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
10.3635063.33160.000643
20.0440520.40370.343714
3-0.12229-1.12080.132782
4-0.177569-1.62750.053693
5-0.190564-1.74650.042186
6-0.073214-0.6710.252026
70.0645470.59160.277861
80.0327680.30030.382338
90.0994730.91170.182273
10-0.087425-0.80130.212619
11-0.369297-3.38470.000543
12-0.474287-4.34691.9e-05
13-0.11077-1.01520.156457
140.1785151.63610.052778
150.2399922.19960.015293
160.3237152.96690.001958
170.2160991.98060.025456
180.0688250.63080.264944
19-0.022489-0.20610.418599







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3635063.33160.000643
2-0.101496-0.93020.17746
3-0.119957-1.09940.137362
4-0.099382-0.91080.182491
5-0.10883-0.99740.160707
60.0191070.17510.430703
70.066020.60510.273377
8-0.069639-0.63830.262523
90.0894790.82010.207242
10-0.194135-1.77930.039406
11-0.343827-3.15120.001127
12-0.302028-2.76810.003467
130.1426291.30720.097353
140.1906391.74720.042126
150.034430.31560.376561
160.1075070.98530.163649
170.0059080.05410.478473
180.0047390.04340.482728
190.0724090.66360.25437

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.363506 & 3.3316 & 0.000643 \tabularnewline
2 & -0.101496 & -0.9302 & 0.17746 \tabularnewline
3 & -0.119957 & -1.0994 & 0.137362 \tabularnewline
4 & -0.099382 & -0.9108 & 0.182491 \tabularnewline
5 & -0.10883 & -0.9974 & 0.160707 \tabularnewline
6 & 0.019107 & 0.1751 & 0.430703 \tabularnewline
7 & 0.06602 & 0.6051 & 0.273377 \tabularnewline
8 & -0.069639 & -0.6383 & 0.262523 \tabularnewline
9 & 0.089479 & 0.8201 & 0.207242 \tabularnewline
10 & -0.194135 & -1.7793 & 0.039406 \tabularnewline
11 & -0.343827 & -3.1512 & 0.001127 \tabularnewline
12 & -0.302028 & -2.7681 & 0.003467 \tabularnewline
13 & 0.142629 & 1.3072 & 0.097353 \tabularnewline
14 & 0.190639 & 1.7472 & 0.042126 \tabularnewline
15 & 0.03443 & 0.3156 & 0.376561 \tabularnewline
16 & 0.107507 & 0.9853 & 0.163649 \tabularnewline
17 & 0.005908 & 0.0541 & 0.478473 \tabularnewline
18 & 0.004739 & 0.0434 & 0.482728 \tabularnewline
19 & 0.072409 & 0.6636 & 0.25437 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196322&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]0.363506[/C][C]3.3316[/C][C]0.000643[/C][/ROW]
[ROW][C]2[/C][C]-0.101496[/C][C]-0.9302[/C][C]0.17746[/C][/ROW]
[ROW][C]3[/C][C]-0.119957[/C][C]-1.0994[/C][C]0.137362[/C][/ROW]
[ROW][C]4[/C][C]-0.099382[/C][C]-0.9108[/C][C]0.182491[/C][/ROW]
[ROW][C]5[/C][C]-0.10883[/C][C]-0.9974[/C][C]0.160707[/C][/ROW]
[ROW][C]6[/C][C]0.019107[/C][C]0.1751[/C][C]0.430703[/C][/ROW]
[ROW][C]7[/C][C]0.06602[/C][C]0.6051[/C][C]0.273377[/C][/ROW]
[ROW][C]8[/C][C]-0.069639[/C][C]-0.6383[/C][C]0.262523[/C][/ROW]
[ROW][C]9[/C][C]0.089479[/C][C]0.8201[/C][C]0.207242[/C][/ROW]
[ROW][C]10[/C][C]-0.194135[/C][C]-1.7793[/C][C]0.039406[/C][/ROW]
[ROW][C]11[/C][C]-0.343827[/C][C]-3.1512[/C][C]0.001127[/C][/ROW]
[ROW][C]12[/C][C]-0.302028[/C][C]-2.7681[/C][C]0.003467[/C][/ROW]
[ROW][C]13[/C][C]0.142629[/C][C]1.3072[/C][C]0.097353[/C][/ROW]
[ROW][C]14[/C][C]0.190639[/C][C]1.7472[/C][C]0.042126[/C][/ROW]
[ROW][C]15[/C][C]0.03443[/C][C]0.3156[/C][C]0.376561[/C][/ROW]
[ROW][C]16[/C][C]0.107507[/C][C]0.9853[/C][C]0.163649[/C][/ROW]
[ROW][C]17[/C][C]0.005908[/C][C]0.0541[/C][C]0.478473[/C][/ROW]
[ROW][C]18[/C][C]0.004739[/C][C]0.0434[/C][C]0.482728[/C][/ROW]
[ROW][C]19[/C][C]0.072409[/C][C]0.6636[/C][C]0.25437[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196322&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196322&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
10.3635063.33160.000643
2-0.101496-0.93020.17746
3-0.119957-1.09940.137362
4-0.099382-0.91080.182491
5-0.10883-0.99740.160707
60.0191070.17510.430703
70.066020.60510.273377
8-0.069639-0.63830.262523
90.0894790.82010.207242
10-0.194135-1.77930.039406
11-0.343827-3.15120.001127
12-0.302028-2.76810.003467
130.1426291.30720.097353
140.1906391.74720.042126
150.034430.31560.376561
160.1075070.98530.163649
170.0059080.05410.478473
180.0047390.04340.482728
190.0724090.66360.25437



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')