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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 computationWed, 29 Dec 2010 09:19:43 +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/Dec/29/t1293614260xpoh5zbn6pi0uae.htm/, Retrieved Fri, 03 May 2024 13:13:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116630, Retrieved Fri, 03 May 2024 13:13:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [(Partial) Autocorrelation Function] [autocorrelatie ru...] [2010-12-14 18:37:20] [d6e648f00513dd750579ba7880c5fbf5]
- R  D    [(Partial) Autocorrelation Function] [] [2010-12-16 10:15:17] [b10d6b9682dfaaa479f495240bcd67cf]
-             [(Partial) Autocorrelation Function] [] [2010-12-29 09:19:43] [a3cd012a7211edfe9ed4466e21aef6a6] [Current]
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Dataseries X:
41.85
41.75
41.75
41.75
41.58
41.61
41.42
41.37
41.37
41.33
41.37
41.34
41.33
41.29
41.29
41.27
41.04
40.90
40.89
40.72
40.72
40.58
40.24
40.07
40.12
40.10
40.10
40.08
40.06
39.99
40.05
39.66
39.66
39.67
39.56
39.64
39.73
39.70
39.70
39.68
39.76
40.00
39.96
40.01
40.01
40.01
40.00
39.91
39.86
39.79
39.79
39.80
39.64
39.55
39.36
39.28




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=116630&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=116630&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116630&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
10.9382057.02090
20.8786416.57510
30.8208056.14230
40.7595575.6840
50.7101755.31451e-06
60.6542814.89624e-06
70.6017384.5031.7e-05
80.5529514.13795.9e-05
90.5033623.76682e-04
100.4552973.40710.000611
110.4040963.0240.00188
120.3536572.64650.00527
130.3013592.25520.014025
140.2491751.86470.033737
150.1990251.48940.071001
160.1350681.01080.158241
170.0750370.56150.288339

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.938205 & 7.0209 & 0 \tabularnewline
2 & 0.878641 & 6.5751 & 0 \tabularnewline
3 & 0.820805 & 6.1423 & 0 \tabularnewline
4 & 0.759557 & 5.684 & 0 \tabularnewline
5 & 0.710175 & 5.3145 & 1e-06 \tabularnewline
6 & 0.654281 & 4.8962 & 4e-06 \tabularnewline
7 & 0.601738 & 4.503 & 1.7e-05 \tabularnewline
8 & 0.552951 & 4.1379 & 5.9e-05 \tabularnewline
9 & 0.503362 & 3.7668 & 2e-04 \tabularnewline
10 & 0.455297 & 3.4071 & 0.000611 \tabularnewline
11 & 0.404096 & 3.024 & 0.00188 \tabularnewline
12 & 0.353657 & 2.6465 & 0.00527 \tabularnewline
13 & 0.301359 & 2.2552 & 0.014025 \tabularnewline
14 & 0.249175 & 1.8647 & 0.033737 \tabularnewline
15 & 0.199025 & 1.4894 & 0.071001 \tabularnewline
16 & 0.135068 & 1.0108 & 0.158241 \tabularnewline
17 & 0.075037 & 0.5615 & 0.288339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116630&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]0.938205[/C][C]7.0209[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.878641[/C][C]6.5751[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.820805[/C][C]6.1423[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.759557[/C][C]5.684[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.710175[/C][C]5.3145[/C][C]1e-06[/C][/ROW]
[ROW][C]6[/C][C]0.654281[/C][C]4.8962[/C][C]4e-06[/C][/ROW]
[ROW][C]7[/C][C]0.601738[/C][C]4.503[/C][C]1.7e-05[/C][/ROW]
[ROW][C]8[/C][C]0.552951[/C][C]4.1379[/C][C]5.9e-05[/C][/ROW]
[ROW][C]9[/C][C]0.503362[/C][C]3.7668[/C][C]2e-04[/C][/ROW]
[ROW][C]10[/C][C]0.455297[/C][C]3.4071[/C][C]0.000611[/C][/ROW]
[ROW][C]11[/C][C]0.404096[/C][C]3.024[/C][C]0.00188[/C][/ROW]
[ROW][C]12[/C][C]0.353657[/C][C]2.6465[/C][C]0.00527[/C][/ROW]
[ROW][C]13[/C][C]0.301359[/C][C]2.2552[/C][C]0.014025[/C][/ROW]
[ROW][C]14[/C][C]0.249175[/C][C]1.8647[/C][C]0.033737[/C][/ROW]
[ROW][C]15[/C][C]0.199025[/C][C]1.4894[/C][C]0.071001[/C][/ROW]
[ROW][C]16[/C][C]0.135068[/C][C]1.0108[/C][C]0.158241[/C][/ROW]
[ROW][C]17[/C][C]0.075037[/C][C]0.5615[/C][C]0.288339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116630&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116630&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
10.9382057.02090
20.8786416.57510
30.8208056.14230
40.7595575.6840
50.7101755.31451e-06
60.6542814.89624e-06
70.6017384.5031.7e-05
80.5529514.13795.9e-05
90.5033623.76682e-04
100.4552973.40710.000611
110.4040963.0240.00188
120.3536572.64650.00527
130.3013592.25520.014025
140.2491751.86470.033737
150.1990251.48940.071001
160.1350681.01080.158241
170.0750370.56150.288339







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9382057.02090
2-0.01325-0.09920.460684
3-0.016964-0.12690.449718
4-0.059777-0.44730.328181
50.063890.47810.317218
6-0.081838-0.61240.271368
7-0.003172-0.02370.490572
8-0.007533-0.05640.477623
9-0.025143-0.18820.425718
10-0.030896-0.23120.409
11-0.053446-0.40.345357
12-0.02784-0.20830.417862
13-0.056223-0.42070.33778
14-0.035061-0.26240.396998
15-0.029414-0.22010.413291
16-0.154907-1.15920.125643
17-0.027772-0.20780.418058

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.938205 & 7.0209 & 0 \tabularnewline
2 & -0.01325 & -0.0992 & 0.460684 \tabularnewline
3 & -0.016964 & -0.1269 & 0.449718 \tabularnewline
4 & -0.059777 & -0.4473 & 0.328181 \tabularnewline
5 & 0.06389 & 0.4781 & 0.317218 \tabularnewline
6 & -0.081838 & -0.6124 & 0.271368 \tabularnewline
7 & -0.003172 & -0.0237 & 0.490572 \tabularnewline
8 & -0.007533 & -0.0564 & 0.477623 \tabularnewline
9 & -0.025143 & -0.1882 & 0.425718 \tabularnewline
10 & -0.030896 & -0.2312 & 0.409 \tabularnewline
11 & -0.053446 & -0.4 & 0.345357 \tabularnewline
12 & -0.02784 & -0.2083 & 0.417862 \tabularnewline
13 & -0.056223 & -0.4207 & 0.33778 \tabularnewline
14 & -0.035061 & -0.2624 & 0.396998 \tabularnewline
15 & -0.029414 & -0.2201 & 0.413291 \tabularnewline
16 & -0.154907 & -1.1592 & 0.125643 \tabularnewline
17 & -0.027772 & -0.2078 & 0.418058 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116630&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]0.938205[/C][C]7.0209[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.01325[/C][C]-0.0992[/C][C]0.460684[/C][/ROW]
[ROW][C]3[/C][C]-0.016964[/C][C]-0.1269[/C][C]0.449718[/C][/ROW]
[ROW][C]4[/C][C]-0.059777[/C][C]-0.4473[/C][C]0.328181[/C][/ROW]
[ROW][C]5[/C][C]0.06389[/C][C]0.4781[/C][C]0.317218[/C][/ROW]
[ROW][C]6[/C][C]-0.081838[/C][C]-0.6124[/C][C]0.271368[/C][/ROW]
[ROW][C]7[/C][C]-0.003172[/C][C]-0.0237[/C][C]0.490572[/C][/ROW]
[ROW][C]8[/C][C]-0.007533[/C][C]-0.0564[/C][C]0.477623[/C][/ROW]
[ROW][C]9[/C][C]-0.025143[/C][C]-0.1882[/C][C]0.425718[/C][/ROW]
[ROW][C]10[/C][C]-0.030896[/C][C]-0.2312[/C][C]0.409[/C][/ROW]
[ROW][C]11[/C][C]-0.053446[/C][C]-0.4[/C][C]0.345357[/C][/ROW]
[ROW][C]12[/C][C]-0.02784[/C][C]-0.2083[/C][C]0.417862[/C][/ROW]
[ROW][C]13[/C][C]-0.056223[/C][C]-0.4207[/C][C]0.33778[/C][/ROW]
[ROW][C]14[/C][C]-0.035061[/C][C]-0.2624[/C][C]0.396998[/C][/ROW]
[ROW][C]15[/C][C]-0.029414[/C][C]-0.2201[/C][C]0.413291[/C][/ROW]
[ROW][C]16[/C][C]-0.154907[/C][C]-1.1592[/C][C]0.125643[/C][/ROW]
[ROW][C]17[/C][C]-0.027772[/C][C]-0.2078[/C][C]0.418058[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116630&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116630&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
10.9382057.02090
2-0.01325-0.09920.460684
3-0.016964-0.12690.449718
4-0.059777-0.44730.328181
50.063890.47810.317218
6-0.081838-0.61240.271368
7-0.003172-0.02370.490572
8-0.007533-0.05640.477623
9-0.025143-0.18820.425718
10-0.030896-0.23120.409
11-0.053446-0.40.345357
12-0.02784-0.20830.417862
13-0.056223-0.42070.33778
14-0.035061-0.26240.396998
15-0.029414-0.22010.413291
16-0.154907-1.15920.125643
17-0.027772-0.20780.418058



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 = ;
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')