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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 13:32:42 +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/t1481891775x4e6dbwpzbg9wtv.htm/, Retrieved Fri, 01 Nov 2024 03:38:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300217, Retrieved Fri, 01 Nov 2024 03:38:04 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2016-12-16 12:32:42] [e4ba36542a85095b1e29ea62dbc4ff31] [Current]
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Dataseries X:
1100
680
860
440
1480
1620
1240
1440
1540
860
1180
1180
1480
940
1300
860
1220
2180
940
920
2060
1160
980
1020
740
720
1340
1140
1200
1900
1020
2140
2020
1340
1400
2320
1280
1160
2120
1540
2400
1420
1480
3380
1880
2200
1980
1340
1960
1340
3300
1780
2040
4460
800
1420
1960
1940
1880
940
1880
720
1660
4260
2540
2320
2860
5880
3140
4440
3600
2920
2260
3740
3380
4560
3320
4760
4000
4840
6160
3440
3280
2000
3600
4320
3480
5620
4200
8540
3800
5380
5140
2720
3120
3440
5020
5800
2260
5800
5660
4880
3440
5900
5960
5520
5920
3840




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=300217&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=300217&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300217&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
10.6588266.84670
20.6634496.89480
30.6308056.55550
40.5704685.92850
50.5473535.68830
60.4765164.95211e-06
70.5522535.73920
80.5060215.25870
90.4870845.06191e-06
100.5784366.01130
110.4916795.10971e-06
120.5339395.54890
130.4334034.50418e-06
140.4706584.89122e-06
150.4293334.46181e-05
160.3814253.96396.6e-05
170.4117094.27862e-05
180.3309513.43930.000415
190.3068333.18870.000935
200.3162513.28660.000684

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.658826 & 6.8467 & 0 \tabularnewline
2 & 0.663449 & 6.8948 & 0 \tabularnewline
3 & 0.630805 & 6.5555 & 0 \tabularnewline
4 & 0.570468 & 5.9285 & 0 \tabularnewline
5 & 0.547353 & 5.6883 & 0 \tabularnewline
6 & 0.476516 & 4.9521 & 1e-06 \tabularnewline
7 & 0.552253 & 5.7392 & 0 \tabularnewline
8 & 0.506021 & 5.2587 & 0 \tabularnewline
9 & 0.487084 & 5.0619 & 1e-06 \tabularnewline
10 & 0.578436 & 6.0113 & 0 \tabularnewline
11 & 0.491679 & 5.1097 & 1e-06 \tabularnewline
12 & 0.533939 & 5.5489 & 0 \tabularnewline
13 & 0.433403 & 4.5041 & 8e-06 \tabularnewline
14 & 0.470658 & 4.8912 & 2e-06 \tabularnewline
15 & 0.429333 & 4.4618 & 1e-05 \tabularnewline
16 & 0.381425 & 3.9639 & 6.6e-05 \tabularnewline
17 & 0.411709 & 4.2786 & 2e-05 \tabularnewline
18 & 0.330951 & 3.4393 & 0.000415 \tabularnewline
19 & 0.306833 & 3.1887 & 0.000935 \tabularnewline
20 & 0.316251 & 3.2866 & 0.000684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300217&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]0.658826[/C][C]6.8467[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.663449[/C][C]6.8948[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.630805[/C][C]6.5555[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.570468[/C][C]5.9285[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.547353[/C][C]5.6883[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.476516[/C][C]4.9521[/C][C]1e-06[/C][/ROW]
[ROW][C]7[/C][C]0.552253[/C][C]5.7392[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.506021[/C][C]5.2587[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.487084[/C][C]5.0619[/C][C]1e-06[/C][/ROW]
[ROW][C]10[/C][C]0.578436[/C][C]6.0113[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.491679[/C][C]5.1097[/C][C]1e-06[/C][/ROW]
[ROW][C]12[/C][C]0.533939[/C][C]5.5489[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.433403[/C][C]4.5041[/C][C]8e-06[/C][/ROW]
[ROW][C]14[/C][C]0.470658[/C][C]4.8912[/C][C]2e-06[/C][/ROW]
[ROW][C]15[/C][C]0.429333[/C][C]4.4618[/C][C]1e-05[/C][/ROW]
[ROW][C]16[/C][C]0.381425[/C][C]3.9639[/C][C]6.6e-05[/C][/ROW]
[ROW][C]17[/C][C]0.411709[/C][C]4.2786[/C][C]2e-05[/C][/ROW]
[ROW][C]18[/C][C]0.330951[/C][C]3.4393[/C][C]0.000415[/C][/ROW]
[ROW][C]19[/C][C]0.306833[/C][C]3.1887[/C][C]0.000935[/C][/ROW]
[ROW][C]20[/C][C]0.316251[/C][C]3.2866[/C][C]0.000684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300217&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300217&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
10.6588266.84670
20.6634496.89480
30.6308056.55550
40.5704685.92850
50.5473535.68830
60.4765164.95211e-06
70.5522535.73920
80.5060215.25870
90.4870845.06191e-06
100.5784366.01130
110.4916795.10971e-06
120.5339395.54890
130.4334034.50418e-06
140.4706584.89122e-06
150.4293334.46181e-05
160.3814253.96396.6e-05
170.4117094.27862e-05
180.3309513.43930.000415
190.3068333.18870.000935
200.3162513.28660.000684







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.6588266.84670
20.4053344.21242.6e-05
30.2195382.28150.01224
40.0510280.53030.298496
50.0464070.48230.315293
6-0.054854-0.57010.28491
70.2195732.28190.012229
80.0730250.75890.224783
90.0103990.10810.45707
100.2294222.38420.00943
11-0.05112-0.53130.298165
120.0599930.62350.267146
13-0.146939-1.5270.064838
140.0429210.4460.328227
15-0.024789-0.25760.398597
16-0.006138-0.06380.474628
170.000610.00630.497478
18-0.103508-1.07570.142232
19-0.12995-1.35050.089842
200.0147140.15290.439378

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.658826 & 6.8467 & 0 \tabularnewline
2 & 0.405334 & 4.2124 & 2.6e-05 \tabularnewline
3 & 0.219538 & 2.2815 & 0.01224 \tabularnewline
4 & 0.051028 & 0.5303 & 0.298496 \tabularnewline
5 & 0.046407 & 0.4823 & 0.315293 \tabularnewline
6 & -0.054854 & -0.5701 & 0.28491 \tabularnewline
7 & 0.219573 & 2.2819 & 0.012229 \tabularnewline
8 & 0.073025 & 0.7589 & 0.224783 \tabularnewline
9 & 0.010399 & 0.1081 & 0.45707 \tabularnewline
10 & 0.229422 & 2.3842 & 0.00943 \tabularnewline
11 & -0.05112 & -0.5313 & 0.298165 \tabularnewline
12 & 0.059993 & 0.6235 & 0.267146 \tabularnewline
13 & -0.146939 & -1.527 & 0.064838 \tabularnewline
14 & 0.042921 & 0.446 & 0.328227 \tabularnewline
15 & -0.024789 & -0.2576 & 0.398597 \tabularnewline
16 & -0.006138 & -0.0638 & 0.474628 \tabularnewline
17 & 0.00061 & 0.0063 & 0.497478 \tabularnewline
18 & -0.103508 & -1.0757 & 0.142232 \tabularnewline
19 & -0.12995 & -1.3505 & 0.089842 \tabularnewline
20 & 0.014714 & 0.1529 & 0.439378 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300217&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]0.658826[/C][C]6.8467[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.405334[/C][C]4.2124[/C][C]2.6e-05[/C][/ROW]
[ROW][C]3[/C][C]0.219538[/C][C]2.2815[/C][C]0.01224[/C][/ROW]
[ROW][C]4[/C][C]0.051028[/C][C]0.5303[/C][C]0.298496[/C][/ROW]
[ROW][C]5[/C][C]0.046407[/C][C]0.4823[/C][C]0.315293[/C][/ROW]
[ROW][C]6[/C][C]-0.054854[/C][C]-0.5701[/C][C]0.28491[/C][/ROW]
[ROW][C]7[/C][C]0.219573[/C][C]2.2819[/C][C]0.012229[/C][/ROW]
[ROW][C]8[/C][C]0.073025[/C][C]0.7589[/C][C]0.224783[/C][/ROW]
[ROW][C]9[/C][C]0.010399[/C][C]0.1081[/C][C]0.45707[/C][/ROW]
[ROW][C]10[/C][C]0.229422[/C][C]2.3842[/C][C]0.00943[/C][/ROW]
[ROW][C]11[/C][C]-0.05112[/C][C]-0.5313[/C][C]0.298165[/C][/ROW]
[ROW][C]12[/C][C]0.059993[/C][C]0.6235[/C][C]0.267146[/C][/ROW]
[ROW][C]13[/C][C]-0.146939[/C][C]-1.527[/C][C]0.064838[/C][/ROW]
[ROW][C]14[/C][C]0.042921[/C][C]0.446[/C][C]0.328227[/C][/ROW]
[ROW][C]15[/C][C]-0.024789[/C][C]-0.2576[/C][C]0.398597[/C][/ROW]
[ROW][C]16[/C][C]-0.006138[/C][C]-0.0638[/C][C]0.474628[/C][/ROW]
[ROW][C]17[/C][C]0.00061[/C][C]0.0063[/C][C]0.497478[/C][/ROW]
[ROW][C]18[/C][C]-0.103508[/C][C]-1.0757[/C][C]0.142232[/C][/ROW]
[ROW][C]19[/C][C]-0.12995[/C][C]-1.3505[/C][C]0.089842[/C][/ROW]
[ROW][C]20[/C][C]0.014714[/C][C]0.1529[/C][C]0.439378[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300217&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300217&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
10.6588266.84670
20.4053344.21242.6e-05
30.2195382.28150.01224
40.0510280.53030.298496
50.0464070.48230.315293
6-0.054854-0.57010.28491
70.2195732.28190.012229
80.0730250.75890.224783
90.0103990.10810.45707
100.2294222.38420.00943
11-0.05112-0.53130.298165
120.0599930.62350.267146
13-0.146939-1.5270.064838
140.0429210.4460.328227
15-0.024789-0.25760.398597
16-0.006138-0.06380.474628
170.000610.00630.497478
18-0.103508-1.07570.142232
19-0.12995-1.35050.089842
200.0147140.15290.439378



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)
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')