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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, 16 Dec 2016 09:17:35 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/16/t1481876351zvfjgxl56gfqji8.htm/, Retrieved Thu, 02 May 2024 23:33:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300099, Retrieved Thu, 02 May 2024 23:33:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact63
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Partial autocorel...] [2016-12-16 08:17:35] [f07fac15bca656f595926f3a45d3c842] [Current]
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Dataseries X:
8450
7050
7700
7650
6900
6600
7400
7550
7450
8850
6100
5850
6800
7800
4950
7200
7450
6200
8450
7900
6600
7900
6200
8400
7600
5200
7450
9550
7800
7650
9750
8700
7150
10550
10150
12300
7850
8450
10000
11150
7750
11100
8650
9050
7200
8600
7500
8200
10050
9900
9500




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300099&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=300099&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300099&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.632763-4.42932.6e-05
20.0916590.64160.262057
3-0.004037-0.02830.488784
40.2054921.43840.078332
5-0.316936-2.21860.015591
60.2680381.87630.033291
7-0.209988-1.46990.073988
80.1992891.3950.084651
9-0.129233-0.90460.185043
10-0.006161-0.04310.482889
110.0036630.02560.489824
120.2016211.41130.082231
13-0.323586-2.26510.013981
140.1271970.89040.188808
150.1682681.17790.122268
16-0.199446-1.39610.084486
17-0.001221-0.00850.496607

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.632763 & -4.4293 & 2.6e-05 \tabularnewline
2 & 0.091659 & 0.6416 & 0.262057 \tabularnewline
3 & -0.004037 & -0.0283 & 0.488784 \tabularnewline
4 & 0.205492 & 1.4384 & 0.078332 \tabularnewline
5 & -0.316936 & -2.2186 & 0.015591 \tabularnewline
6 & 0.268038 & 1.8763 & 0.033291 \tabularnewline
7 & -0.209988 & -1.4699 & 0.073988 \tabularnewline
8 & 0.199289 & 1.395 & 0.084651 \tabularnewline
9 & -0.129233 & -0.9046 & 0.185043 \tabularnewline
10 & -0.006161 & -0.0431 & 0.482889 \tabularnewline
11 & 0.003663 & 0.0256 & 0.489824 \tabularnewline
12 & 0.201621 & 1.4113 & 0.082231 \tabularnewline
13 & -0.323586 & -2.2651 & 0.013981 \tabularnewline
14 & 0.127197 & 0.8904 & 0.188808 \tabularnewline
15 & 0.168268 & 1.1779 & 0.122268 \tabularnewline
16 & -0.199446 & -1.3961 & 0.084486 \tabularnewline
17 & -0.001221 & -0.0085 & 0.496607 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300099&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]-0.632763[/C][C]-4.4293[/C][C]2.6e-05[/C][/ROW]
[ROW][C]2[/C][C]0.091659[/C][C]0.6416[/C][C]0.262057[/C][/ROW]
[ROW][C]3[/C][C]-0.004037[/C][C]-0.0283[/C][C]0.488784[/C][/ROW]
[ROW][C]4[/C][C]0.205492[/C][C]1.4384[/C][C]0.078332[/C][/ROW]
[ROW][C]5[/C][C]-0.316936[/C][C]-2.2186[/C][C]0.015591[/C][/ROW]
[ROW][C]6[/C][C]0.268038[/C][C]1.8763[/C][C]0.033291[/C][/ROW]
[ROW][C]7[/C][C]-0.209988[/C][C]-1.4699[/C][C]0.073988[/C][/ROW]
[ROW][C]8[/C][C]0.199289[/C][C]1.395[/C][C]0.084651[/C][/ROW]
[ROW][C]9[/C][C]-0.129233[/C][C]-0.9046[/C][C]0.185043[/C][/ROW]
[ROW][C]10[/C][C]-0.006161[/C][C]-0.0431[/C][C]0.482889[/C][/ROW]
[ROW][C]11[/C][C]0.003663[/C][C]0.0256[/C][C]0.489824[/C][/ROW]
[ROW][C]12[/C][C]0.201621[/C][C]1.4113[/C][C]0.082231[/C][/ROW]
[ROW][C]13[/C][C]-0.323586[/C][C]-2.2651[/C][C]0.013981[/C][/ROW]
[ROW][C]14[/C][C]0.127197[/C][C]0.8904[/C][C]0.188808[/C][/ROW]
[ROW][C]15[/C][C]0.168268[/C][C]1.1779[/C][C]0.122268[/C][/ROW]
[ROW][C]16[/C][C]-0.199446[/C][C]-1.3961[/C][C]0.084486[/C][/ROW]
[ROW][C]17[/C][C]-0.001221[/C][C]-0.0085[/C][C]0.496607[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300099&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300099&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
1-0.632763-4.42932.6e-05
20.0916590.64160.262057
3-0.004037-0.02830.488784
40.2054921.43840.078332
5-0.316936-2.21860.015591
60.2680381.87630.033291
7-0.209988-1.46990.073988
80.1992891.3950.084651
9-0.129233-0.90460.185043
10-0.006161-0.04310.482889
110.0036630.02560.489824
120.2016211.41130.082231
13-0.323586-2.26510.013981
140.1271970.89040.188808
150.1682681.17790.122268
16-0.199446-1.39610.084486
17-0.001221-0.00850.496607







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.632763-4.42932.6e-05
2-0.514884-3.60420.000366
3-0.549134-3.84390.000175
4-0.167491-1.17240.123345
5-0.282336-1.97640.026879
6-0.032765-0.22940.409773
7-0.20266-1.41860.081169
8-0.074077-0.51850.303208
90.0952840.6670.253954
10-0.066504-0.46550.321808
11-0.178703-1.25090.108451
120.102710.7190.237787
130.0713710.49960.309798
14-0.18407-1.28850.101813
150.0493150.34520.365708
160.0106010.07420.470573
170.0206940.14490.442709

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.632763 & -4.4293 & 2.6e-05 \tabularnewline
2 & -0.514884 & -3.6042 & 0.000366 \tabularnewline
3 & -0.549134 & -3.8439 & 0.000175 \tabularnewline
4 & -0.167491 & -1.1724 & 0.123345 \tabularnewline
5 & -0.282336 & -1.9764 & 0.026879 \tabularnewline
6 & -0.032765 & -0.2294 & 0.409773 \tabularnewline
7 & -0.20266 & -1.4186 & 0.081169 \tabularnewline
8 & -0.074077 & -0.5185 & 0.303208 \tabularnewline
9 & 0.095284 & 0.667 & 0.253954 \tabularnewline
10 & -0.066504 & -0.4655 & 0.321808 \tabularnewline
11 & -0.178703 & -1.2509 & 0.108451 \tabularnewline
12 & 0.10271 & 0.719 & 0.237787 \tabularnewline
13 & 0.071371 & 0.4996 & 0.309798 \tabularnewline
14 & -0.18407 & -1.2885 & 0.101813 \tabularnewline
15 & 0.049315 & 0.3452 & 0.365708 \tabularnewline
16 & 0.010601 & 0.0742 & 0.470573 \tabularnewline
17 & 0.020694 & 0.1449 & 0.442709 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300099&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]-0.632763[/C][C]-4.4293[/C][C]2.6e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.514884[/C][C]-3.6042[/C][C]0.000366[/C][/ROW]
[ROW][C]3[/C][C]-0.549134[/C][C]-3.8439[/C][C]0.000175[/C][/ROW]
[ROW][C]4[/C][C]-0.167491[/C][C]-1.1724[/C][C]0.123345[/C][/ROW]
[ROW][C]5[/C][C]-0.282336[/C][C]-1.9764[/C][C]0.026879[/C][/ROW]
[ROW][C]6[/C][C]-0.032765[/C][C]-0.2294[/C][C]0.409773[/C][/ROW]
[ROW][C]7[/C][C]-0.20266[/C][C]-1.4186[/C][C]0.081169[/C][/ROW]
[ROW][C]8[/C][C]-0.074077[/C][C]-0.5185[/C][C]0.303208[/C][/ROW]
[ROW][C]9[/C][C]0.095284[/C][C]0.667[/C][C]0.253954[/C][/ROW]
[ROW][C]10[/C][C]-0.066504[/C][C]-0.4655[/C][C]0.321808[/C][/ROW]
[ROW][C]11[/C][C]-0.178703[/C][C]-1.2509[/C][C]0.108451[/C][/ROW]
[ROW][C]12[/C][C]0.10271[/C][C]0.719[/C][C]0.237787[/C][/ROW]
[ROW][C]13[/C][C]0.071371[/C][C]0.4996[/C][C]0.309798[/C][/ROW]
[ROW][C]14[/C][C]-0.18407[/C][C]-1.2885[/C][C]0.101813[/C][/ROW]
[ROW][C]15[/C][C]0.049315[/C][C]0.3452[/C][C]0.365708[/C][/ROW]
[ROW][C]16[/C][C]0.010601[/C][C]0.0742[/C][C]0.470573[/C][/ROW]
[ROW][C]17[/C][C]0.020694[/C][C]0.1449[/C][C]0.442709[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300099&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300099&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
1-0.632763-4.42932.6e-05
2-0.514884-3.60420.000366
3-0.549134-3.84390.000175
4-0.167491-1.17240.123345
5-0.282336-1.97640.026879
6-0.032765-0.22940.409773
7-0.20266-1.41860.081169
8-0.074077-0.51850.303208
90.0952840.6670.253954
10-0.066504-0.46550.321808
11-0.178703-1.25090.108451
120.102710.7190.237787
130.0713710.49960.309798
14-0.18407-1.28850.101813
150.0493150.34520.365708
160.0106010.07420.470573
170.0206940.14490.442709



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 2 ; 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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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')