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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, 19 Dec 2016 18:25:41 +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/19/t1482168370c5z6hs6t6lamqi6.htm/, Retrieved Fri, 01 Nov 2024 03:44:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301430, Retrieved Fri, 01 Nov 2024 03:44:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [N1993 Autocorrela...] [2016-12-19 17:25:41] [1eb03b74c4069f30e782d39ada1a3213] [Current]
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Dataseries X:
6970
6455
8005
8115
8180
7930
7275
7865
7610
7435
8480
8850
8345
8275
8595
8430
8395
7735
7890
8435
7620
7610
8005
8935
8320
7670
8660
8485
8160
7910
7725
7555
7685
7740
7455
7850
6930
6600
7290
7625
7755
6915
6145
5985
6100
5955
5800
5905
5705
5430
6435
6025
5815
5160
4985
5585
5790
6190
6300
6340
6610
6685
7450
7410
7255
6460
6035
6745
6655
7070
7415
7720
7815
7260
7925
7825
7805
7530
7015
6575
6640
7075
6405
6720
6385
6085
6475
6555
6500
5790
5195
5680
5745
6010
5705
6310
6870
6260
7210
7090
7055
6535
6320
6010
6165
6985
6760
7220
6995
6475
7225
7325
7515
6925
7165
6895
6400
6685
6955
7550
7645
6710
7470
7355
7525
7165




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=301430&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=301430&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301430&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
1-0.102174-1.08610.139867
2-0.150246-1.59710.056514
30.0661220.70290.241787
4-0.090714-0.96430.168475
50.0707020.75160.226934
60.1019881.08410.140305
70.0453780.48240.315235
80.0551280.5860.279517
9-0.045486-0.48350.314831
100.0157360.16730.433725
110.147741.57050.059548
12-0.433983-4.61335e-06
130.0514080.54650.292908
140.1496351.59060.057242
15-0.105212-1.11840.132881
160.0534510.56820.285515
170.0062890.06690.473407
18-0.127611-1.35650.088818
19-0.124852-1.32720.09356
200.0305960.32520.372802
210.0846220.89950.185139

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.102174 & -1.0861 & 0.139867 \tabularnewline
2 & -0.150246 & -1.5971 & 0.056514 \tabularnewline
3 & 0.066122 & 0.7029 & 0.241787 \tabularnewline
4 & -0.090714 & -0.9643 & 0.168475 \tabularnewline
5 & 0.070702 & 0.7516 & 0.226934 \tabularnewline
6 & 0.101988 & 1.0841 & 0.140305 \tabularnewline
7 & 0.045378 & 0.4824 & 0.315235 \tabularnewline
8 & 0.055128 & 0.586 & 0.279517 \tabularnewline
9 & -0.045486 & -0.4835 & 0.314831 \tabularnewline
10 & 0.015736 & 0.1673 & 0.433725 \tabularnewline
11 & 0.14774 & 1.5705 & 0.059548 \tabularnewline
12 & -0.433983 & -4.6133 & 5e-06 \tabularnewline
13 & 0.051408 & 0.5465 & 0.292908 \tabularnewline
14 & 0.149635 & 1.5906 & 0.057242 \tabularnewline
15 & -0.105212 & -1.1184 & 0.132881 \tabularnewline
16 & 0.053451 & 0.5682 & 0.285515 \tabularnewline
17 & 0.006289 & 0.0669 & 0.473407 \tabularnewline
18 & -0.127611 & -1.3565 & 0.088818 \tabularnewline
19 & -0.124852 & -1.3272 & 0.09356 \tabularnewline
20 & 0.030596 & 0.3252 & 0.372802 \tabularnewline
21 & 0.084622 & 0.8995 & 0.185139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301430&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]-0.102174[/C][C]-1.0861[/C][C]0.139867[/C][/ROW]
[ROW][C]2[/C][C]-0.150246[/C][C]-1.5971[/C][C]0.056514[/C][/ROW]
[ROW][C]3[/C][C]0.066122[/C][C]0.7029[/C][C]0.241787[/C][/ROW]
[ROW][C]4[/C][C]-0.090714[/C][C]-0.9643[/C][C]0.168475[/C][/ROW]
[ROW][C]5[/C][C]0.070702[/C][C]0.7516[/C][C]0.226934[/C][/ROW]
[ROW][C]6[/C][C]0.101988[/C][C]1.0841[/C][C]0.140305[/C][/ROW]
[ROW][C]7[/C][C]0.045378[/C][C]0.4824[/C][C]0.315235[/C][/ROW]
[ROW][C]8[/C][C]0.055128[/C][C]0.586[/C][C]0.279517[/C][/ROW]
[ROW][C]9[/C][C]-0.045486[/C][C]-0.4835[/C][C]0.314831[/C][/ROW]
[ROW][C]10[/C][C]0.015736[/C][C]0.1673[/C][C]0.433725[/C][/ROW]
[ROW][C]11[/C][C]0.14774[/C][C]1.5705[/C][C]0.059548[/C][/ROW]
[ROW][C]12[/C][C]-0.433983[/C][C]-4.6133[/C][C]5e-06[/C][/ROW]
[ROW][C]13[/C][C]0.051408[/C][C]0.5465[/C][C]0.292908[/C][/ROW]
[ROW][C]14[/C][C]0.149635[/C][C]1.5906[/C][C]0.057242[/C][/ROW]
[ROW][C]15[/C][C]-0.105212[/C][C]-1.1184[/C][C]0.132881[/C][/ROW]
[ROW][C]16[/C][C]0.053451[/C][C]0.5682[/C][C]0.285515[/C][/ROW]
[ROW][C]17[/C][C]0.006289[/C][C]0.0669[/C][C]0.473407[/C][/ROW]
[ROW][C]18[/C][C]-0.127611[/C][C]-1.3565[/C][C]0.088818[/C][/ROW]
[ROW][C]19[/C][C]-0.124852[/C][C]-1.3272[/C][C]0.09356[/C][/ROW]
[ROW][C]20[/C][C]0.030596[/C][C]0.3252[/C][C]0.372802[/C][/ROW]
[ROW][C]21[/C][C]0.084622[/C][C]0.8995[/C][C]0.185139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301430&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301430&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
1-0.102174-1.08610.139867
2-0.150246-1.59710.056514
30.0661220.70290.241787
4-0.090714-0.96430.168475
50.0707020.75160.226934
60.1019881.08410.140305
70.0453780.48240.315235
80.0551280.5860.279517
9-0.045486-0.48350.314831
100.0157360.16730.433725
110.147741.57050.059548
12-0.433983-4.61335e-06
130.0514080.54650.292908
140.1496351.59060.057242
15-0.105212-1.11840.132881
160.0534510.56820.285515
170.0062890.06690.473407
18-0.127611-1.35650.088818
19-0.124852-1.32720.09356
200.0305960.32520.372802
210.0846220.89950.185139







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.102174-1.08610.139867
2-0.162381-1.72610.043529
30.0328880.34960.363643
4-0.107712-1.1450.127316
50.0677440.72010.236467
60.0875420.93060.177026
70.1033471.09860.137141
80.0934890.99380.161221
9-0.000147-0.00160.499377
100.0406550.43220.333219
110.1465781.55810.060998
12-0.441629-4.69464e-06
13-0.024181-0.2570.398806
14-0.019616-0.20850.417599
15-0.058326-0.620.268247
16-0.03196-0.33970.367341
170.0495370.52660.299757
18-0.034493-0.36670.357276
19-0.119386-1.26910.103508
200.040420.42970.334128
210.0747240.79430.214334

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.102174 & -1.0861 & 0.139867 \tabularnewline
2 & -0.162381 & -1.7261 & 0.043529 \tabularnewline
3 & 0.032888 & 0.3496 & 0.363643 \tabularnewline
4 & -0.107712 & -1.145 & 0.127316 \tabularnewline
5 & 0.067744 & 0.7201 & 0.236467 \tabularnewline
6 & 0.087542 & 0.9306 & 0.177026 \tabularnewline
7 & 0.103347 & 1.0986 & 0.137141 \tabularnewline
8 & 0.093489 & 0.9938 & 0.161221 \tabularnewline
9 & -0.000147 & -0.0016 & 0.499377 \tabularnewline
10 & 0.040655 & 0.4322 & 0.333219 \tabularnewline
11 & 0.146578 & 1.5581 & 0.060998 \tabularnewline
12 & -0.441629 & -4.6946 & 4e-06 \tabularnewline
13 & -0.024181 & -0.257 & 0.398806 \tabularnewline
14 & -0.019616 & -0.2085 & 0.417599 \tabularnewline
15 & -0.058326 & -0.62 & 0.268247 \tabularnewline
16 & -0.03196 & -0.3397 & 0.367341 \tabularnewline
17 & 0.049537 & 0.5266 & 0.299757 \tabularnewline
18 & -0.034493 & -0.3667 & 0.357276 \tabularnewline
19 & -0.119386 & -1.2691 & 0.103508 \tabularnewline
20 & 0.04042 & 0.4297 & 0.334128 \tabularnewline
21 & 0.074724 & 0.7943 & 0.214334 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301430&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]-0.102174[/C][C]-1.0861[/C][C]0.139867[/C][/ROW]
[ROW][C]2[/C][C]-0.162381[/C][C]-1.7261[/C][C]0.043529[/C][/ROW]
[ROW][C]3[/C][C]0.032888[/C][C]0.3496[/C][C]0.363643[/C][/ROW]
[ROW][C]4[/C][C]-0.107712[/C][C]-1.145[/C][C]0.127316[/C][/ROW]
[ROW][C]5[/C][C]0.067744[/C][C]0.7201[/C][C]0.236467[/C][/ROW]
[ROW][C]6[/C][C]0.087542[/C][C]0.9306[/C][C]0.177026[/C][/ROW]
[ROW][C]7[/C][C]0.103347[/C][C]1.0986[/C][C]0.137141[/C][/ROW]
[ROW][C]8[/C][C]0.093489[/C][C]0.9938[/C][C]0.161221[/C][/ROW]
[ROW][C]9[/C][C]-0.000147[/C][C]-0.0016[/C][C]0.499377[/C][/ROW]
[ROW][C]10[/C][C]0.040655[/C][C]0.4322[/C][C]0.333219[/C][/ROW]
[ROW][C]11[/C][C]0.146578[/C][C]1.5581[/C][C]0.060998[/C][/ROW]
[ROW][C]12[/C][C]-0.441629[/C][C]-4.6946[/C][C]4e-06[/C][/ROW]
[ROW][C]13[/C][C]-0.024181[/C][C]-0.257[/C][C]0.398806[/C][/ROW]
[ROW][C]14[/C][C]-0.019616[/C][C]-0.2085[/C][C]0.417599[/C][/ROW]
[ROW][C]15[/C][C]-0.058326[/C][C]-0.62[/C][C]0.268247[/C][/ROW]
[ROW][C]16[/C][C]-0.03196[/C][C]-0.3397[/C][C]0.367341[/C][/ROW]
[ROW][C]17[/C][C]0.049537[/C][C]0.5266[/C][C]0.299757[/C][/ROW]
[ROW][C]18[/C][C]-0.034493[/C][C]-0.3667[/C][C]0.357276[/C][/ROW]
[ROW][C]19[/C][C]-0.119386[/C][C]-1.2691[/C][C]0.103508[/C][/ROW]
[ROW][C]20[/C][C]0.04042[/C][C]0.4297[/C][C]0.334128[/C][/ROW]
[ROW][C]21[/C][C]0.074724[/C][C]0.7943[/C][C]0.214334[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301430&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301430&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
1-0.102174-1.08610.139867
2-0.162381-1.72610.043529
30.0328880.34960.363643
4-0.107712-1.1450.127316
50.0677440.72010.236467
60.0875420.93060.177026
70.1033471.09860.137141
80.0934890.99380.161221
9-0.000147-0.00160.499377
100.0406550.43220.333219
110.1465781.55810.060998
12-0.441629-4.69464e-06
13-0.024181-0.2570.398806
14-0.019616-0.20850.417599
15-0.058326-0.620.268247
16-0.03196-0.33970.367341
170.0495370.52660.299757
18-0.034493-0.36670.357276
19-0.119386-1.26910.103508
200.040420.42970.334128
210.0747240.79430.214334



Parameters (Session):
par1 = Default ; par2 = 1.8 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1.8 ; par3 = 1 ; par4 = 1 ; 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')