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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 29 Nov 2010 20:17:15 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/29/t12910617362h2oyyt693ki68l.htm/, Retrieved Thu, 25 Apr 2024 05:21:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=103082, Retrieved Thu, 25 Apr 2024 05:21:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact201
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Workshop 8 autoco...] [2010-11-28 20:30:20] [3635fb7041b1998c5a1332cf9de22bce]
-         [(Partial) Autocorrelation Function] [Workshop 8, autoc...] [2010-11-29 20:17:15] [23a9b79f355c69a75648521a893cf584] [Current]
-    D      [(Partial) Autocorrelation Function] [WS 8 Autocorrelatie] [2010-11-29 22:46:06] [8081b8996d5947580de3eb171e82db4f]
- R  D      [(Partial) Autocorrelation Function] [] [2011-11-24 16:08:51] [74be16979710d4c4e7c6647856088456]
-    D        [(Partial) Autocorrelation Function] [] [2011-11-25 08:38:31] [46896e8a404bb9354f2d070359621409]
- R  D      [(Partial) Autocorrelation Function] [WS 8 Autocorrelatie] [2011-11-27 15:00:53] [74be16979710d4c4e7c6647856088456]
- RM        [(Partial) Autocorrelation Function] [] [2011-11-29 11:47:52] [74be16979710d4c4e7c6647856088456]
- R  D      [(Partial) Autocorrelation Function] [Autocorrelatie] [2011-11-29 14:32:40] [c505444e07acba7694d29053ca5d114e]
- RM        [(Partial) Autocorrelation Function] [] [2012-11-27 21:13:34] [74be16979710d4c4e7c6647856088456]
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Dataseries X:
9 911
8 915
9 452
9 112
8 472
8 230
8 384
8 625
8 221
8 649
8 625
10 443
10 357
8 586
8 892
8 329
8 101
7 922
8 120
7 838
7 735
8 406
8 209
9 451
10 041
9 411
10 405
8 467
8 464
8 102
7 627
7 513
7 510
8 291
8 064
9 383
9 706
8 579
9 474
8 318
8 213
8 059
9 111
7 708
7 680
8 014
8 007
8 718
9 486
9 113
9 025
8 476
7 952
7 759
7 835
7 600
7 651
8 319
8 812
8 630




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=103082&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=103082&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103082&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5418244.1974.5e-05
20.321052.48680.007844
30.0348010.26960.394208
4-0.299251-2.3180.011938
5-0.427385-3.31050.00079
6-0.475716-3.68490.000247
7-0.37676-2.91840.002473
8-0.314266-2.43430.008957
90.0302210.23410.407857
100.2169411.68040.049038
110.3602682.79060.003522
120.6050494.68678e-06
130.37022.86760.00285
140.3018992.33850.011356
150.0973130.75380.226964
16-0.134519-1.0420.150801
17-0.29067-2.25150.014013

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.541824 & 4.197 & 4.5e-05 \tabularnewline
2 & 0.32105 & 2.4868 & 0.007844 \tabularnewline
3 & 0.034801 & 0.2696 & 0.394208 \tabularnewline
4 & -0.299251 & -2.318 & 0.011938 \tabularnewline
5 & -0.427385 & -3.3105 & 0.00079 \tabularnewline
6 & -0.475716 & -3.6849 & 0.000247 \tabularnewline
7 & -0.37676 & -2.9184 & 0.002473 \tabularnewline
8 & -0.314266 & -2.4343 & 0.008957 \tabularnewline
9 & 0.030221 & 0.2341 & 0.407857 \tabularnewline
10 & 0.216941 & 1.6804 & 0.049038 \tabularnewline
11 & 0.360268 & 2.7906 & 0.003522 \tabularnewline
12 & 0.605049 & 4.6867 & 8e-06 \tabularnewline
13 & 0.3702 & 2.8676 & 0.00285 \tabularnewline
14 & 0.301899 & 2.3385 & 0.011356 \tabularnewline
15 & 0.097313 & 0.7538 & 0.226964 \tabularnewline
16 & -0.134519 & -1.042 & 0.150801 \tabularnewline
17 & -0.29067 & -2.2515 & 0.014013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103082&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]0.541824[/C][C]4.197[/C][C]4.5e-05[/C][/ROW]
[ROW][C]2[/C][C]0.32105[/C][C]2.4868[/C][C]0.007844[/C][/ROW]
[ROW][C]3[/C][C]0.034801[/C][C]0.2696[/C][C]0.394208[/C][/ROW]
[ROW][C]4[/C][C]-0.299251[/C][C]-2.318[/C][C]0.011938[/C][/ROW]
[ROW][C]5[/C][C]-0.427385[/C][C]-3.3105[/C][C]0.00079[/C][/ROW]
[ROW][C]6[/C][C]-0.475716[/C][C]-3.6849[/C][C]0.000247[/C][/ROW]
[ROW][C]7[/C][C]-0.37676[/C][C]-2.9184[/C][C]0.002473[/C][/ROW]
[ROW][C]8[/C][C]-0.314266[/C][C]-2.4343[/C][C]0.008957[/C][/ROW]
[ROW][C]9[/C][C]0.030221[/C][C]0.2341[/C][C]0.407857[/C][/ROW]
[ROW][C]10[/C][C]0.216941[/C][C]1.6804[/C][C]0.049038[/C][/ROW]
[ROW][C]11[/C][C]0.360268[/C][C]2.7906[/C][C]0.003522[/C][/ROW]
[ROW][C]12[/C][C]0.605049[/C][C]4.6867[/C][C]8e-06[/C][/ROW]
[ROW][C]13[/C][C]0.3702[/C][C]2.8676[/C][C]0.00285[/C][/ROW]
[ROW][C]14[/C][C]0.301899[/C][C]2.3385[/C][C]0.011356[/C][/ROW]
[ROW][C]15[/C][C]0.097313[/C][C]0.7538[/C][C]0.226964[/C][/ROW]
[ROW][C]16[/C][C]-0.134519[/C][C]-1.042[/C][C]0.150801[/C][/ROW]
[ROW][C]17[/C][C]-0.29067[/C][C]-2.2515[/C][C]0.014013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103082&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103082&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
10.5418244.1974.5e-05
20.321052.48680.007844
30.0348010.26960.394208
4-0.299251-2.3180.011938
5-0.427385-3.31050.00079
6-0.475716-3.68490.000247
7-0.37676-2.91840.002473
8-0.314266-2.43430.008957
90.0302210.23410.407857
100.2169411.68040.049038
110.3602682.79060.003522
120.6050494.68678e-06
130.37022.86760.00285
140.3018992.33850.011356
150.0973130.75380.226964
16-0.134519-1.0420.150801
17-0.29067-2.25150.014013







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5418244.1974.5e-05
20.0388950.30130.382122
3-0.217563-1.68520.048569
4-0.370029-2.86620.00286
5-0.160174-1.24070.109773
6-0.116476-0.90220.185273
7-0.025439-0.19710.422227
8-0.221641-1.71680.045585
90.2231761.72870.044502
100.0754010.58410.280686
110.071450.55350.291006
120.3484152.69880.004513
13-0.182277-1.41190.081571
140.1584011.2270.112313
150.07560.58560.280172
160.0014030.01090.495682
170.0273940.21220.416336

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.541824 & 4.197 & 4.5e-05 \tabularnewline
2 & 0.038895 & 0.3013 & 0.382122 \tabularnewline
3 & -0.217563 & -1.6852 & 0.048569 \tabularnewline
4 & -0.370029 & -2.8662 & 0.00286 \tabularnewline
5 & -0.160174 & -1.2407 & 0.109773 \tabularnewline
6 & -0.116476 & -0.9022 & 0.185273 \tabularnewline
7 & -0.025439 & -0.1971 & 0.422227 \tabularnewline
8 & -0.221641 & -1.7168 & 0.045585 \tabularnewline
9 & 0.223176 & 1.7287 & 0.044502 \tabularnewline
10 & 0.075401 & 0.5841 & 0.280686 \tabularnewline
11 & 0.07145 & 0.5535 & 0.291006 \tabularnewline
12 & 0.348415 & 2.6988 & 0.004513 \tabularnewline
13 & -0.182277 & -1.4119 & 0.081571 \tabularnewline
14 & 0.158401 & 1.227 & 0.112313 \tabularnewline
15 & 0.0756 & 0.5856 & 0.280172 \tabularnewline
16 & 0.001403 & 0.0109 & 0.495682 \tabularnewline
17 & 0.027394 & 0.2122 & 0.416336 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=103082&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]0.541824[/C][C]4.197[/C][C]4.5e-05[/C][/ROW]
[ROW][C]2[/C][C]0.038895[/C][C]0.3013[/C][C]0.382122[/C][/ROW]
[ROW][C]3[/C][C]-0.217563[/C][C]-1.6852[/C][C]0.048569[/C][/ROW]
[ROW][C]4[/C][C]-0.370029[/C][C]-2.8662[/C][C]0.00286[/C][/ROW]
[ROW][C]5[/C][C]-0.160174[/C][C]-1.2407[/C][C]0.109773[/C][/ROW]
[ROW][C]6[/C][C]-0.116476[/C][C]-0.9022[/C][C]0.185273[/C][/ROW]
[ROW][C]7[/C][C]-0.025439[/C][C]-0.1971[/C][C]0.422227[/C][/ROW]
[ROW][C]8[/C][C]-0.221641[/C][C]-1.7168[/C][C]0.045585[/C][/ROW]
[ROW][C]9[/C][C]0.223176[/C][C]1.7287[/C][C]0.044502[/C][/ROW]
[ROW][C]10[/C][C]0.075401[/C][C]0.5841[/C][C]0.280686[/C][/ROW]
[ROW][C]11[/C][C]0.07145[/C][C]0.5535[/C][C]0.291006[/C][/ROW]
[ROW][C]12[/C][C]0.348415[/C][C]2.6988[/C][C]0.004513[/C][/ROW]
[ROW][C]13[/C][C]-0.182277[/C][C]-1.4119[/C][C]0.081571[/C][/ROW]
[ROW][C]14[/C][C]0.158401[/C][C]1.227[/C][C]0.112313[/C][/ROW]
[ROW][C]15[/C][C]0.0756[/C][C]0.5856[/C][C]0.280172[/C][/ROW]
[ROW][C]16[/C][C]0.001403[/C][C]0.0109[/C][C]0.495682[/C][/ROW]
[ROW][C]17[/C][C]0.027394[/C][C]0.2122[/C][C]0.416336[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=103082&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=103082&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
10.5418244.1974.5e-05
20.0388950.30130.382122
3-0.217563-1.68520.048569
4-0.370029-2.86620.00286
5-0.160174-1.24070.109773
6-0.116476-0.90220.185273
7-0.025439-0.19710.422227
8-0.221641-1.71680.045585
90.2231761.72870.044502
100.0754010.58410.280686
110.071450.55350.291006
120.3484152.69880.004513
13-0.182277-1.41190.081571
140.1584011.2270.112313
150.07560.58560.280172
160.0014030.01090.495682
170.0273940.21220.416336



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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')