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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 computationThu, 26 Nov 2009 08:23:48 -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/2009/Nov/26/t1259249431q5s1p5z6wwoc9dm.htm/, Retrieved Mon, 29 Apr 2024 01:31:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60095, Retrieved Mon, 29 Apr 2024 01:31:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
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       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:19:56] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [] [2009-11-26 15:23:48] [bcaf453a09027aa0f995cb78bdc3c98a] [Current]
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Dataseries X:
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8
8.2
8.1
8.1
8
7.9
7.9
8
8
7.9
8
7.7
7.2
7.5
7.3
7
7
7
7.2
7.3
7.1
6.8
6.4
6.1
6.5
7.7
7.9
7.5
6.9
6.6
6.9
7.7
8
8
7.7
7.3
7.4
8.1
8.3
8.2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60095&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60095&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60095&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'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8774316.1420
20.6650034.6551.2e-05
30.4814243.370.000736
40.3780672.64650.005453
50.3647492.55320.006918
60.3741962.61940.005846
70.3385932.37020.010881
80.2301171.61080.056822
90.0747840.52350.301497
10-0.049713-0.3480.36467
11-0.137592-0.96310.170103
12-0.185059-1.29540.100624
13-0.206749-1.44720.077099
14-0.222657-1.55860.062764
15-0.256874-1.79810.03916
16-0.296392-2.07470.021642
17-0.310433-2.1730.017321
18-0.309297-2.16510.01764
19-0.308463-2.15920.017877
20-0.291006-2.0370.023533
21-0.286678-2.00670.025156
22-0.310476-2.17330.017309
23-0.327047-2.28930.013204
24-0.317359-2.22150.015484

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.877431 & 6.142 & 0 \tabularnewline
2 & 0.665003 & 4.655 & 1.2e-05 \tabularnewline
3 & 0.481424 & 3.37 & 0.000736 \tabularnewline
4 & 0.378067 & 2.6465 & 0.005453 \tabularnewline
5 & 0.364749 & 2.5532 & 0.006918 \tabularnewline
6 & 0.374196 & 2.6194 & 0.005846 \tabularnewline
7 & 0.338593 & 2.3702 & 0.010881 \tabularnewline
8 & 0.230117 & 1.6108 & 0.056822 \tabularnewline
9 & 0.074784 & 0.5235 & 0.301497 \tabularnewline
10 & -0.049713 & -0.348 & 0.36467 \tabularnewline
11 & -0.137592 & -0.9631 & 0.170103 \tabularnewline
12 & -0.185059 & -1.2954 & 0.100624 \tabularnewline
13 & -0.206749 & -1.4472 & 0.077099 \tabularnewline
14 & -0.222657 & -1.5586 & 0.062764 \tabularnewline
15 & -0.256874 & -1.7981 & 0.03916 \tabularnewline
16 & -0.296392 & -2.0747 & 0.021642 \tabularnewline
17 & -0.310433 & -2.173 & 0.017321 \tabularnewline
18 & -0.309297 & -2.1651 & 0.01764 \tabularnewline
19 & -0.308463 & -2.1592 & 0.017877 \tabularnewline
20 & -0.291006 & -2.037 & 0.023533 \tabularnewline
21 & -0.286678 & -2.0067 & 0.025156 \tabularnewline
22 & -0.310476 & -2.1733 & 0.017309 \tabularnewline
23 & -0.327047 & -2.2893 & 0.013204 \tabularnewline
24 & -0.317359 & -2.2215 & 0.015484 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60095&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]0.877431[/C][C]6.142[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.665003[/C][C]4.655[/C][C]1.2e-05[/C][/ROW]
[ROW][C]3[/C][C]0.481424[/C][C]3.37[/C][C]0.000736[/C][/ROW]
[ROW][C]4[/C][C]0.378067[/C][C]2.6465[/C][C]0.005453[/C][/ROW]
[ROW][C]5[/C][C]0.364749[/C][C]2.5532[/C][C]0.006918[/C][/ROW]
[ROW][C]6[/C][C]0.374196[/C][C]2.6194[/C][C]0.005846[/C][/ROW]
[ROW][C]7[/C][C]0.338593[/C][C]2.3702[/C][C]0.010881[/C][/ROW]
[ROW][C]8[/C][C]0.230117[/C][C]1.6108[/C][C]0.056822[/C][/ROW]
[ROW][C]9[/C][C]0.074784[/C][C]0.5235[/C][C]0.301497[/C][/ROW]
[ROW][C]10[/C][C]-0.049713[/C][C]-0.348[/C][C]0.36467[/C][/ROW]
[ROW][C]11[/C][C]-0.137592[/C][C]-0.9631[/C][C]0.170103[/C][/ROW]
[ROW][C]12[/C][C]-0.185059[/C][C]-1.2954[/C][C]0.100624[/C][/ROW]
[ROW][C]13[/C][C]-0.206749[/C][C]-1.4472[/C][C]0.077099[/C][/ROW]
[ROW][C]14[/C][C]-0.222657[/C][C]-1.5586[/C][C]0.062764[/C][/ROW]
[ROW][C]15[/C][C]-0.256874[/C][C]-1.7981[/C][C]0.03916[/C][/ROW]
[ROW][C]16[/C][C]-0.296392[/C][C]-2.0747[/C][C]0.021642[/C][/ROW]
[ROW][C]17[/C][C]-0.310433[/C][C]-2.173[/C][C]0.017321[/C][/ROW]
[ROW][C]18[/C][C]-0.309297[/C][C]-2.1651[/C][C]0.01764[/C][/ROW]
[ROW][C]19[/C][C]-0.308463[/C][C]-2.1592[/C][C]0.017877[/C][/ROW]
[ROW][C]20[/C][C]-0.291006[/C][C]-2.037[/C][C]0.023533[/C][/ROW]
[ROW][C]21[/C][C]-0.286678[/C][C]-2.0067[/C][C]0.025156[/C][/ROW]
[ROW][C]22[/C][C]-0.310476[/C][C]-2.1733[/C][C]0.017309[/C][/ROW]
[ROW][C]23[/C][C]-0.327047[/C][C]-2.2893[/C][C]0.013204[/C][/ROW]
[ROW][C]24[/C][C]-0.317359[/C][C]-2.2215[/C][C]0.015484[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60095&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60095&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
10.8774316.1420
20.6650034.6551.2e-05
30.4814243.370.000736
40.3780672.64650.005453
50.3647492.55320.006918
60.3741962.61940.005846
70.3385932.37020.010881
80.2301171.61080.056822
90.0747840.52350.301497
10-0.049713-0.3480.36467
11-0.137592-0.96310.170103
12-0.185059-1.29540.100624
13-0.206749-1.44720.077099
14-0.222657-1.55860.062764
15-0.256874-1.79810.03916
16-0.296392-2.07470.021642
17-0.310433-2.1730.017321
18-0.309297-2.16510.01764
19-0.308463-2.15920.017877
20-0.291006-2.0370.023533
21-0.286678-2.00670.025156
22-0.310476-2.17330.017309
23-0.327047-2.28930.013204
24-0.317359-2.22150.015484







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8774316.1420
2-0.455776-3.19040.001239
30.174971.22480.113255
40.129720.9080.184151
50.1827171.2790.103457
6-0.097559-0.68290.248939
7-0.129543-0.90680.184475
8-0.174718-1.2230.113584
9-0.107156-0.75010.228392
100.0655390.45880.324213
11-0.21921-1.53450.065673
12-0.008372-0.05860.476754
13-0.046844-0.32790.372188
140.0618230.43280.333544
15-0.119429-0.8360.203606
160.0459060.32130.374659
170.0657080.460.323792
18-0.091434-0.640.262566
19-0.046845-0.32790.372187
200.0474310.3320.370647
21-0.151605-1.06120.146892
22-0.159061-1.11340.135479
230.0705450.49380.311822
24-0.050178-0.35120.363455

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.877431 & 6.142 & 0 \tabularnewline
2 & -0.455776 & -3.1904 & 0.001239 \tabularnewline
3 & 0.17497 & 1.2248 & 0.113255 \tabularnewline
4 & 0.12972 & 0.908 & 0.184151 \tabularnewline
5 & 0.182717 & 1.279 & 0.103457 \tabularnewline
6 & -0.097559 & -0.6829 & 0.248939 \tabularnewline
7 & -0.129543 & -0.9068 & 0.184475 \tabularnewline
8 & -0.174718 & -1.223 & 0.113584 \tabularnewline
9 & -0.107156 & -0.7501 & 0.228392 \tabularnewline
10 & 0.065539 & 0.4588 & 0.324213 \tabularnewline
11 & -0.21921 & -1.5345 & 0.065673 \tabularnewline
12 & -0.008372 & -0.0586 & 0.476754 \tabularnewline
13 & -0.046844 & -0.3279 & 0.372188 \tabularnewline
14 & 0.061823 & 0.4328 & 0.333544 \tabularnewline
15 & -0.119429 & -0.836 & 0.203606 \tabularnewline
16 & 0.045906 & 0.3213 & 0.374659 \tabularnewline
17 & 0.065708 & 0.46 & 0.323792 \tabularnewline
18 & -0.091434 & -0.64 & 0.262566 \tabularnewline
19 & -0.046845 & -0.3279 & 0.372187 \tabularnewline
20 & 0.047431 & 0.332 & 0.370647 \tabularnewline
21 & -0.151605 & -1.0612 & 0.146892 \tabularnewline
22 & -0.159061 & -1.1134 & 0.135479 \tabularnewline
23 & 0.070545 & 0.4938 & 0.311822 \tabularnewline
24 & -0.050178 & -0.3512 & 0.363455 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60095&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]0.877431[/C][C]6.142[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.455776[/C][C]-3.1904[/C][C]0.001239[/C][/ROW]
[ROW][C]3[/C][C]0.17497[/C][C]1.2248[/C][C]0.113255[/C][/ROW]
[ROW][C]4[/C][C]0.12972[/C][C]0.908[/C][C]0.184151[/C][/ROW]
[ROW][C]5[/C][C]0.182717[/C][C]1.279[/C][C]0.103457[/C][/ROW]
[ROW][C]6[/C][C]-0.097559[/C][C]-0.6829[/C][C]0.248939[/C][/ROW]
[ROW][C]7[/C][C]-0.129543[/C][C]-0.9068[/C][C]0.184475[/C][/ROW]
[ROW][C]8[/C][C]-0.174718[/C][C]-1.223[/C][C]0.113584[/C][/ROW]
[ROW][C]9[/C][C]-0.107156[/C][C]-0.7501[/C][C]0.228392[/C][/ROW]
[ROW][C]10[/C][C]0.065539[/C][C]0.4588[/C][C]0.324213[/C][/ROW]
[ROW][C]11[/C][C]-0.21921[/C][C]-1.5345[/C][C]0.065673[/C][/ROW]
[ROW][C]12[/C][C]-0.008372[/C][C]-0.0586[/C][C]0.476754[/C][/ROW]
[ROW][C]13[/C][C]-0.046844[/C][C]-0.3279[/C][C]0.372188[/C][/ROW]
[ROW][C]14[/C][C]0.061823[/C][C]0.4328[/C][C]0.333544[/C][/ROW]
[ROW][C]15[/C][C]-0.119429[/C][C]-0.836[/C][C]0.203606[/C][/ROW]
[ROW][C]16[/C][C]0.045906[/C][C]0.3213[/C][C]0.374659[/C][/ROW]
[ROW][C]17[/C][C]0.065708[/C][C]0.46[/C][C]0.323792[/C][/ROW]
[ROW][C]18[/C][C]-0.091434[/C][C]-0.64[/C][C]0.262566[/C][/ROW]
[ROW][C]19[/C][C]-0.046845[/C][C]-0.3279[/C][C]0.372187[/C][/ROW]
[ROW][C]20[/C][C]0.047431[/C][C]0.332[/C][C]0.370647[/C][/ROW]
[ROW][C]21[/C][C]-0.151605[/C][C]-1.0612[/C][C]0.146892[/C][/ROW]
[ROW][C]22[/C][C]-0.159061[/C][C]-1.1134[/C][C]0.135479[/C][/ROW]
[ROW][C]23[/C][C]0.070545[/C][C]0.4938[/C][C]0.311822[/C][/ROW]
[ROW][C]24[/C][C]-0.050178[/C][C]-0.3512[/C][C]0.363455[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60095&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60095&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
10.8774316.1420
2-0.455776-3.19040.001239
30.174971.22480.113255
40.129720.9080.184151
50.1827171.2790.103457
6-0.097559-0.68290.248939
7-0.129543-0.90680.184475
8-0.174718-1.2230.113584
9-0.107156-0.75010.228392
100.0655390.45880.324213
11-0.21921-1.53450.065673
12-0.008372-0.05860.476754
13-0.046844-0.32790.372188
140.0618230.43280.333544
15-0.119429-0.8360.203606
160.0459060.32130.374659
170.0657080.460.323792
18-0.091434-0.640.262566
19-0.046845-0.32790.372187
200.0474310.3320.370647
21-0.151605-1.06120.146892
22-0.159061-1.11340.135479
230.0705450.49380.311822
24-0.050178-0.35120.363455



Parameters (Session):
par1 = 24 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 24 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
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')