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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 computationFri, 05 Dec 2008 15:37:51 -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/05/t1228516872tkkyec3zpsj07zo.htm/, Retrieved Thu, 16 May 2024 13:08:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29412, Retrieved Thu, 16 May 2024 13:08:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [Paper Hoofdstuk 4...] [2008-12-05 10:14:55] [6fea0e9a9b3b29a63badf2c274e82506]
- RMP   [(Partial) Autocorrelation Function] [Paper Hoofdstuk 4...] [2008-12-05 11:21:04] [6fea0e9a9b3b29a63badf2c274e82506]
-   P       [(Partial) Autocorrelation Function] [Paper Hoofdstuk 4...] [2008-12-05 22:37:51] [286e96bd53289970f8e5f25a93fb50b3] [Current]
Feedback Forum

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Dataseries X:
493.000
481.000
462.000
457.000
442.000
439.000
488.000
521.000
501.000
485.000
464.000
460.000
467.000
460.000
448.000
443.000
436.000
431.000
484.000
510.000
513.000
503.000
471.000
471.000
476.000
475.000
470.000
461.000
455.000
456.000
517.000
525.000
523.000
519.000
509.000
512.000
519.000
517.000
510.000
509.000
501.000
507.000
569.000
580.000
578.000
565.000
547.000
555.000
562.000
561.000
555.000
544.000
537.000
543.000
594.000
611.000
613.000
611.000
594.000
595.000




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29412&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29412&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29412&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.410074-2.78130.003912
2-0.085543-0.58020.282313
3-0.087588-0.5940.277695
4-0.000966-0.00660.497401
50.1875161.27180.10492
6-0.089699-0.60840.272968
7-0.06877-0.46640.321559
8-0.041111-0.27880.390814
90.2342241.58860.059502
100.0097850.06640.473686
11-0.177547-1.20420.117339
12-0.163736-1.11050.136275
130.0914910.62050.268989
140.3016922.04620.02324
15-0.245355-1.66410.051447
160.1464230.99310.16293
17-0.208607-1.41480.081925
180.1292220.87640.192677
190.0317550.21540.415214
20-0.118617-0.80450.212623
210.0652480.44250.330088
22-0.089132-0.60450.274232
230.2273171.54170.064995
24-0.044626-0.30270.381754

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.410074 & -2.7813 & 0.003912 \tabularnewline
2 & -0.085543 & -0.5802 & 0.282313 \tabularnewline
3 & -0.087588 & -0.594 & 0.277695 \tabularnewline
4 & -0.000966 & -0.0066 & 0.497401 \tabularnewline
5 & 0.187516 & 1.2718 & 0.10492 \tabularnewline
6 & -0.089699 & -0.6084 & 0.272968 \tabularnewline
7 & -0.06877 & -0.4664 & 0.321559 \tabularnewline
8 & -0.041111 & -0.2788 & 0.390814 \tabularnewline
9 & 0.234224 & 1.5886 & 0.059502 \tabularnewline
10 & 0.009785 & 0.0664 & 0.473686 \tabularnewline
11 & -0.177547 & -1.2042 & 0.117339 \tabularnewline
12 & -0.163736 & -1.1105 & 0.136275 \tabularnewline
13 & 0.091491 & 0.6205 & 0.268989 \tabularnewline
14 & 0.301692 & 2.0462 & 0.02324 \tabularnewline
15 & -0.245355 & -1.6641 & 0.051447 \tabularnewline
16 & 0.146423 & 0.9931 & 0.16293 \tabularnewline
17 & -0.208607 & -1.4148 & 0.081925 \tabularnewline
18 & 0.129222 & 0.8764 & 0.192677 \tabularnewline
19 & 0.031755 & 0.2154 & 0.415214 \tabularnewline
20 & -0.118617 & -0.8045 & 0.212623 \tabularnewline
21 & 0.065248 & 0.4425 & 0.330088 \tabularnewline
22 & -0.089132 & -0.6045 & 0.274232 \tabularnewline
23 & 0.227317 & 1.5417 & 0.064995 \tabularnewline
24 & -0.044626 & -0.3027 & 0.381754 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29412&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]-0.410074[/C][C]-2.7813[/C][C]0.003912[/C][/ROW]
[ROW][C]2[/C][C]-0.085543[/C][C]-0.5802[/C][C]0.282313[/C][/ROW]
[ROW][C]3[/C][C]-0.087588[/C][C]-0.594[/C][C]0.277695[/C][/ROW]
[ROW][C]4[/C][C]-0.000966[/C][C]-0.0066[/C][C]0.497401[/C][/ROW]
[ROW][C]5[/C][C]0.187516[/C][C]1.2718[/C][C]0.10492[/C][/ROW]
[ROW][C]6[/C][C]-0.089699[/C][C]-0.6084[/C][C]0.272968[/C][/ROW]
[ROW][C]7[/C][C]-0.06877[/C][C]-0.4664[/C][C]0.321559[/C][/ROW]
[ROW][C]8[/C][C]-0.041111[/C][C]-0.2788[/C][C]0.390814[/C][/ROW]
[ROW][C]9[/C][C]0.234224[/C][C]1.5886[/C][C]0.059502[/C][/ROW]
[ROW][C]10[/C][C]0.009785[/C][C]0.0664[/C][C]0.473686[/C][/ROW]
[ROW][C]11[/C][C]-0.177547[/C][C]-1.2042[/C][C]0.117339[/C][/ROW]
[ROW][C]12[/C][C]-0.163736[/C][C]-1.1105[/C][C]0.136275[/C][/ROW]
[ROW][C]13[/C][C]0.091491[/C][C]0.6205[/C][C]0.268989[/C][/ROW]
[ROW][C]14[/C][C]0.301692[/C][C]2.0462[/C][C]0.02324[/C][/ROW]
[ROW][C]15[/C][C]-0.245355[/C][C]-1.6641[/C][C]0.051447[/C][/ROW]
[ROW][C]16[/C][C]0.146423[/C][C]0.9931[/C][C]0.16293[/C][/ROW]
[ROW][C]17[/C][C]-0.208607[/C][C]-1.4148[/C][C]0.081925[/C][/ROW]
[ROW][C]18[/C][C]0.129222[/C][C]0.8764[/C][C]0.192677[/C][/ROW]
[ROW][C]19[/C][C]0.031755[/C][C]0.2154[/C][C]0.415214[/C][/ROW]
[ROW][C]20[/C][C]-0.118617[/C][C]-0.8045[/C][C]0.212623[/C][/ROW]
[ROW][C]21[/C][C]0.065248[/C][C]0.4425[/C][C]0.330088[/C][/ROW]
[ROW][C]22[/C][C]-0.089132[/C][C]-0.6045[/C][C]0.274232[/C][/ROW]
[ROW][C]23[/C][C]0.227317[/C][C]1.5417[/C][C]0.064995[/C][/ROW]
[ROW][C]24[/C][C]-0.044626[/C][C]-0.3027[/C][C]0.381754[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29412&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29412&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
1-0.410074-2.78130.003912
2-0.085543-0.58020.282313
3-0.087588-0.5940.277695
4-0.000966-0.00660.497401
50.1875161.27180.10492
6-0.089699-0.60840.272968
7-0.06877-0.46640.321559
8-0.041111-0.27880.390814
90.2342241.58860.059502
100.0097850.06640.473686
11-0.177547-1.20420.117339
12-0.163736-1.11050.136275
130.0914910.62050.268989
140.3016922.04620.02324
15-0.245355-1.66410.051447
160.1464230.99310.16293
17-0.208607-1.41480.081925
180.1292220.87640.192677
190.0317550.21540.415214
20-0.118617-0.80450.212623
210.0652480.44250.330088
22-0.089132-0.60450.274232
230.2273171.54170.064995
24-0.044626-0.30270.381754







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.410074-2.78130.003912
2-0.30499-2.06850.022118
3-0.34254-2.32320.012321
4-0.359231-2.43640.009382
5-0.116589-0.79070.216575
6-0.144359-0.97910.166329
7-0.217174-1.47290.073788
8-0.31196-2.11580.019902
9-0.005997-0.04070.483865
100.1837691.24640.109468
110.1095750.74320.230578
12-0.177401-1.20320.117529
13-0.281254-1.90760.031352
140.0387820.2630.396851
15-0.233447-1.58330.060101
160.0601380.40790.342629
17-0.020964-0.14220.443778
180.0049680.03370.486634
19-0.102819-0.69730.244547
20-0.123396-0.83690.203484
210.0905580.61420.271057
22-0.052402-0.35540.361954
23-0.017401-0.1180.453284
240.0739620.50160.309158

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.410074 & -2.7813 & 0.003912 \tabularnewline
2 & -0.30499 & -2.0685 & 0.022118 \tabularnewline
3 & -0.34254 & -2.3232 & 0.012321 \tabularnewline
4 & -0.359231 & -2.4364 & 0.009382 \tabularnewline
5 & -0.116589 & -0.7907 & 0.216575 \tabularnewline
6 & -0.144359 & -0.9791 & 0.166329 \tabularnewline
7 & -0.217174 & -1.4729 & 0.073788 \tabularnewline
8 & -0.31196 & -2.1158 & 0.019902 \tabularnewline
9 & -0.005997 & -0.0407 & 0.483865 \tabularnewline
10 & 0.183769 & 1.2464 & 0.109468 \tabularnewline
11 & 0.109575 & 0.7432 & 0.230578 \tabularnewline
12 & -0.177401 & -1.2032 & 0.117529 \tabularnewline
13 & -0.281254 & -1.9076 & 0.031352 \tabularnewline
14 & 0.038782 & 0.263 & 0.396851 \tabularnewline
15 & -0.233447 & -1.5833 & 0.060101 \tabularnewline
16 & 0.060138 & 0.4079 & 0.342629 \tabularnewline
17 & -0.020964 & -0.1422 & 0.443778 \tabularnewline
18 & 0.004968 & 0.0337 & 0.486634 \tabularnewline
19 & -0.102819 & -0.6973 & 0.244547 \tabularnewline
20 & -0.123396 & -0.8369 & 0.203484 \tabularnewline
21 & 0.090558 & 0.6142 & 0.271057 \tabularnewline
22 & -0.052402 & -0.3554 & 0.361954 \tabularnewline
23 & -0.017401 & -0.118 & 0.453284 \tabularnewline
24 & 0.073962 & 0.5016 & 0.309158 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29412&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]-0.410074[/C][C]-2.7813[/C][C]0.003912[/C][/ROW]
[ROW][C]2[/C][C]-0.30499[/C][C]-2.0685[/C][C]0.022118[/C][/ROW]
[ROW][C]3[/C][C]-0.34254[/C][C]-2.3232[/C][C]0.012321[/C][/ROW]
[ROW][C]4[/C][C]-0.359231[/C][C]-2.4364[/C][C]0.009382[/C][/ROW]
[ROW][C]5[/C][C]-0.116589[/C][C]-0.7907[/C][C]0.216575[/C][/ROW]
[ROW][C]6[/C][C]-0.144359[/C][C]-0.9791[/C][C]0.166329[/C][/ROW]
[ROW][C]7[/C][C]-0.217174[/C][C]-1.4729[/C][C]0.073788[/C][/ROW]
[ROW][C]8[/C][C]-0.31196[/C][C]-2.1158[/C][C]0.019902[/C][/ROW]
[ROW][C]9[/C][C]-0.005997[/C][C]-0.0407[/C][C]0.483865[/C][/ROW]
[ROW][C]10[/C][C]0.183769[/C][C]1.2464[/C][C]0.109468[/C][/ROW]
[ROW][C]11[/C][C]0.109575[/C][C]0.7432[/C][C]0.230578[/C][/ROW]
[ROW][C]12[/C][C]-0.177401[/C][C]-1.2032[/C][C]0.117529[/C][/ROW]
[ROW][C]13[/C][C]-0.281254[/C][C]-1.9076[/C][C]0.031352[/C][/ROW]
[ROW][C]14[/C][C]0.038782[/C][C]0.263[/C][C]0.396851[/C][/ROW]
[ROW][C]15[/C][C]-0.233447[/C][C]-1.5833[/C][C]0.060101[/C][/ROW]
[ROW][C]16[/C][C]0.060138[/C][C]0.4079[/C][C]0.342629[/C][/ROW]
[ROW][C]17[/C][C]-0.020964[/C][C]-0.1422[/C][C]0.443778[/C][/ROW]
[ROW][C]18[/C][C]0.004968[/C][C]0.0337[/C][C]0.486634[/C][/ROW]
[ROW][C]19[/C][C]-0.102819[/C][C]-0.6973[/C][C]0.244547[/C][/ROW]
[ROW][C]20[/C][C]-0.123396[/C][C]-0.8369[/C][C]0.203484[/C][/ROW]
[ROW][C]21[/C][C]0.090558[/C][C]0.6142[/C][C]0.271057[/C][/ROW]
[ROW][C]22[/C][C]-0.052402[/C][C]-0.3554[/C][C]0.361954[/C][/ROW]
[ROW][C]23[/C][C]-0.017401[/C][C]-0.118[/C][C]0.453284[/C][/ROW]
[ROW][C]24[/C][C]0.073962[/C][C]0.5016[/C][C]0.309158[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29412&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29412&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
1-0.410074-2.78130.003912
2-0.30499-2.06850.022118
3-0.34254-2.32320.012321
4-0.359231-2.43640.009382
5-0.116589-0.79070.216575
6-0.144359-0.97910.166329
7-0.217174-1.47290.073788
8-0.31196-2.11580.019902
9-0.005997-0.04070.483865
100.1837691.24640.109468
110.1095750.74320.230578
12-0.177401-1.20320.117529
13-0.281254-1.90760.031352
140.0387820.2630.396851
15-0.233447-1.58330.060101
160.0601380.40790.342629
17-0.020964-0.14220.443778
180.0049680.03370.486634
19-0.102819-0.69730.244547
20-0.123396-0.83690.203484
210.0905580.61420.271057
22-0.052402-0.35540.361954
23-0.017401-0.1180.453284
240.0739620.50160.309158



Parameters (Session):
par1 = 24 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 24 ; par2 = 1 ; par3 = 2 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')