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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 computationSat, 17 Dec 2016 08:18:22 +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/17/t1481959256r530gsplgo4eteo.htm/, Retrieved Fri, 01 Nov 2024 03:34:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300600, Retrieved Fri, 01 Nov 2024 03:34:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [N 2460- ACF (1)] [2016-12-17 07:18:22] [86c7fb9c8a0af864c0a27e2f433e80d7] [Current]
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Dataseries X:
3850
3900
3900
3950
3950
3900
3400
2150
3800
3950
3950
3850
3750
3900
3850
3900
3900
4000
3450
2300
3900
4100
4150
4150
3950
4150
4150
4150
4150
4250
3750
2350
4200
4250
4350
4300
4150
4250
4250
4200
4150
4350
3750
2450
4250
4350
4450
4500
4350
4500
4550
4550
3050
3850
4100
2700
4450
4800
4950
4950
4800
4850
4850
5000
5000
5000
4450
2800
4850
5150
5050
5100
5100
5250
5250
5350
5150
5200
4600
2950
5100
5350
5350
5400
5250
5450
5500
5450
5200
5400
4800
3050
5450
5600
5750
5750
5650
5700
5750
5800
5750
5750
4950
3500
5750
6050
6150
6200
6150
6250
6300
6100
6350
6250
5400
3900
6100
6450
6600
6350
6500
6700
6550
6550
6550
6500




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=300600&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=300600&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300600&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
10.7302428.19690
20.5954866.68430
30.5717676.41810
40.531915.97070
50.5209945.84810
60.4927825.53150
70.4832975.4250
80.4425744.96791e-06
90.4512925.06571e-06
100.4430214.97291e-06
110.5537096.21540
120.7636318.57170
130.5293145.94150
140.4176254.68784e-06
150.3951294.43531e-05
160.3450213.87298.6e-05
170.3374583.7880.000117
180.311323.49460.000328
190.2964993.32820.000573
200.255452.86740.002426
210.2618792.93960.001955

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.730242 & 8.1969 & 0 \tabularnewline
2 & 0.595486 & 6.6843 & 0 \tabularnewline
3 & 0.571767 & 6.4181 & 0 \tabularnewline
4 & 0.53191 & 5.9707 & 0 \tabularnewline
5 & 0.520994 & 5.8481 & 0 \tabularnewline
6 & 0.492782 & 5.5315 & 0 \tabularnewline
7 & 0.483297 & 5.425 & 0 \tabularnewline
8 & 0.442574 & 4.9679 & 1e-06 \tabularnewline
9 & 0.451292 & 5.0657 & 1e-06 \tabularnewline
10 & 0.443021 & 4.9729 & 1e-06 \tabularnewline
11 & 0.553709 & 6.2154 & 0 \tabularnewline
12 & 0.763631 & 8.5717 & 0 \tabularnewline
13 & 0.529314 & 5.9415 & 0 \tabularnewline
14 & 0.417625 & 4.6878 & 4e-06 \tabularnewline
15 & 0.395129 & 4.4353 & 1e-05 \tabularnewline
16 & 0.345021 & 3.8729 & 8.6e-05 \tabularnewline
17 & 0.337458 & 3.788 & 0.000117 \tabularnewline
18 & 0.31132 & 3.4946 & 0.000328 \tabularnewline
19 & 0.296499 & 3.3282 & 0.000573 \tabularnewline
20 & 0.25545 & 2.8674 & 0.002426 \tabularnewline
21 & 0.261879 & 2.9396 & 0.001955 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300600&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]0.730242[/C][C]8.1969[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.595486[/C][C]6.6843[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.571767[/C][C]6.4181[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.53191[/C][C]5.9707[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.520994[/C][C]5.8481[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.492782[/C][C]5.5315[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.483297[/C][C]5.425[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.442574[/C][C]4.9679[/C][C]1e-06[/C][/ROW]
[ROW][C]9[/C][C]0.451292[/C][C]5.0657[/C][C]1e-06[/C][/ROW]
[ROW][C]10[/C][C]0.443021[/C][C]4.9729[/C][C]1e-06[/C][/ROW]
[ROW][C]11[/C][C]0.553709[/C][C]6.2154[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.763631[/C][C]8.5717[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.529314[/C][C]5.9415[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.417625[/C][C]4.6878[/C][C]4e-06[/C][/ROW]
[ROW][C]15[/C][C]0.395129[/C][C]4.4353[/C][C]1e-05[/C][/ROW]
[ROW][C]16[/C][C]0.345021[/C][C]3.8729[/C][C]8.6e-05[/C][/ROW]
[ROW][C]17[/C][C]0.337458[/C][C]3.788[/C][C]0.000117[/C][/ROW]
[ROW][C]18[/C][C]0.31132[/C][C]3.4946[/C][C]0.000328[/C][/ROW]
[ROW][C]19[/C][C]0.296499[/C][C]3.3282[/C][C]0.000573[/C][/ROW]
[ROW][C]20[/C][C]0.25545[/C][C]2.8674[/C][C]0.002426[/C][/ROW]
[ROW][C]21[/C][C]0.261879[/C][C]2.9396[/C][C]0.001955[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300600&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300600&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
10.7302428.19690
20.5954866.68430
30.5717676.41810
40.531915.97070
50.5209945.84810
60.4927825.53150
70.4832975.4250
80.4425744.96791e-06
90.4512925.06571e-06
100.4430214.97291e-06
110.5537096.21540
120.7636318.57170
130.5293145.94150
140.4176254.68784e-06
150.3951294.43531e-05
160.3450213.87298.6e-05
170.3374583.7880.000117
180.311323.49460.000328
190.2964993.32820.000573
200.255452.86740.002426
210.2618792.93960.001955







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7302428.19690
20.1333341.49670.06849
30.2127442.3880.009212
40.0724140.81280.208921
50.1259481.41380.079949
60.0349350.39210.347807
70.0856490.96140.169093
8-0.026537-0.29790.383145
90.1104211.23950.108737
100.0137990.15490.438578
110.3448993.87158.6e-05
120.5607926.29490
13-0.640167-7.18590
14-0.131945-1.48110.070541
15-0.094441-1.06010.145564
16-0.124505-1.39760.08235
170.1280151.4370.076604
18-0.000805-0.0090.4964
190.0092680.1040.458656
200.1160481.30260.097537
21-0.037936-0.42580.33548

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.730242 & 8.1969 & 0 \tabularnewline
2 & 0.133334 & 1.4967 & 0.06849 \tabularnewline
3 & 0.212744 & 2.388 & 0.009212 \tabularnewline
4 & 0.072414 & 0.8128 & 0.208921 \tabularnewline
5 & 0.125948 & 1.4138 & 0.079949 \tabularnewline
6 & 0.034935 & 0.3921 & 0.347807 \tabularnewline
7 & 0.085649 & 0.9614 & 0.169093 \tabularnewline
8 & -0.026537 & -0.2979 & 0.383145 \tabularnewline
9 & 0.110421 & 1.2395 & 0.108737 \tabularnewline
10 & 0.013799 & 0.1549 & 0.438578 \tabularnewline
11 & 0.344899 & 3.8715 & 8.6e-05 \tabularnewline
12 & 0.560792 & 6.2949 & 0 \tabularnewline
13 & -0.640167 & -7.1859 & 0 \tabularnewline
14 & -0.131945 & -1.4811 & 0.070541 \tabularnewline
15 & -0.094441 & -1.0601 & 0.145564 \tabularnewline
16 & -0.124505 & -1.3976 & 0.08235 \tabularnewline
17 & 0.128015 & 1.437 & 0.076604 \tabularnewline
18 & -0.000805 & -0.009 & 0.4964 \tabularnewline
19 & 0.009268 & 0.104 & 0.458656 \tabularnewline
20 & 0.116048 & 1.3026 & 0.097537 \tabularnewline
21 & -0.037936 & -0.4258 & 0.33548 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300600&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]0.730242[/C][C]8.1969[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.133334[/C][C]1.4967[/C][C]0.06849[/C][/ROW]
[ROW][C]3[/C][C]0.212744[/C][C]2.388[/C][C]0.009212[/C][/ROW]
[ROW][C]4[/C][C]0.072414[/C][C]0.8128[/C][C]0.208921[/C][/ROW]
[ROW][C]5[/C][C]0.125948[/C][C]1.4138[/C][C]0.079949[/C][/ROW]
[ROW][C]6[/C][C]0.034935[/C][C]0.3921[/C][C]0.347807[/C][/ROW]
[ROW][C]7[/C][C]0.085649[/C][C]0.9614[/C][C]0.169093[/C][/ROW]
[ROW][C]8[/C][C]-0.026537[/C][C]-0.2979[/C][C]0.383145[/C][/ROW]
[ROW][C]9[/C][C]0.110421[/C][C]1.2395[/C][C]0.108737[/C][/ROW]
[ROW][C]10[/C][C]0.013799[/C][C]0.1549[/C][C]0.438578[/C][/ROW]
[ROW][C]11[/C][C]0.344899[/C][C]3.8715[/C][C]8.6e-05[/C][/ROW]
[ROW][C]12[/C][C]0.560792[/C][C]6.2949[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.640167[/C][C]-7.1859[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]-0.131945[/C][C]-1.4811[/C][C]0.070541[/C][/ROW]
[ROW][C]15[/C][C]-0.094441[/C][C]-1.0601[/C][C]0.145564[/C][/ROW]
[ROW][C]16[/C][C]-0.124505[/C][C]-1.3976[/C][C]0.08235[/C][/ROW]
[ROW][C]17[/C][C]0.128015[/C][C]1.437[/C][C]0.076604[/C][/ROW]
[ROW][C]18[/C][C]-0.000805[/C][C]-0.009[/C][C]0.4964[/C][/ROW]
[ROW][C]19[/C][C]0.009268[/C][C]0.104[/C][C]0.458656[/C][/ROW]
[ROW][C]20[/C][C]0.116048[/C][C]1.3026[/C][C]0.097537[/C][/ROW]
[ROW][C]21[/C][C]-0.037936[/C][C]-0.4258[/C][C]0.33548[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300600&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300600&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
10.7302428.19690
20.1333341.49670.06849
30.2127442.3880.009212
40.0724140.81280.208921
50.1259481.41380.079949
60.0349350.39210.347807
70.0856490.96140.169093
8-0.026537-0.29790.383145
90.1104211.23950.108737
100.0137990.15490.438578
110.3448993.87158.6e-05
120.5607926.29490
13-0.640167-7.18590
14-0.131945-1.48110.070541
15-0.094441-1.06010.145564
16-0.124505-1.39760.08235
170.1280151.4370.076604
18-0.000805-0.0090.4964
190.0092680.1040.458656
200.1160481.30260.097537
21-0.037936-0.42580.33548



Parameters (Session):
par4 = 12 ;
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')