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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 21:59:13 +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/t1482008379z3y6u8fj81pinrc.htm/, Retrieved Fri, 01 Nov 2024 03:46:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300950, Retrieved Fri, 01 Nov 2024 03:46:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact103
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [autocorrelatie ] [2016-12-17 20:59:13] [f20c721eaecf28dbff8d9b9768e8b0c7] [Current]
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Dataseries X:
3904.45
4137.2
4334.5
4188.6
4304.1
4570.45
4178.85
4515.15
4740.55
4582.2
4493.6
4437
4294
4581.35
4780.15
4632
4648.2
4834.85
4465.25
4671.65
4871.3
4707.8
4580.45
4562.25
4329.7
4646.1
4844.1
4623
4707.2
4844.9
4436.75
4680.85
4873.8
4735.15
4681.9
4607
4436.4
4614.1
4619.25
4507.1
4515.85
4725.4
4250.85
4591.6
4898.15
4675.45
4568.95
4531.05
4387.35
4826.1
4954.35
4814.85
4821.55
5148.05
4810.75
4988.05
5322.65
5157
5006.65
4910.2
4764.05
5093.7
5312.2
5157.6
5192.4
5546.6
5092.05
5423.25
5647.2
5450.05
5360.3
5309.25
5181
5488.6
5668.15
5560.8
5590.45
5850.7
5252.2
5626.1
5819.8
5676.35
5525.5
5359.55
5296.85
5623.75
5899.3
5672.6
5724.75
5995.1
5475.2
6143.95
6366.95
6306.1
6077
5672.4
5458.6
5716.9
5828.1
5706.85
5888.3
6007.7
5581.85
5970.95
6190.4
6079.15
5902.2
5554.4
5320.45
5683.1
5987.9
5843.7
5917.5
6299.45
5846.75
5998.1




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300950&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]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=300950&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300950&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 time1 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.035357-0.35880.360226
2-0.0246-0.24970.401675
30.0709660.72020.236509
4-0.165857-1.68330.047676
50.0334890.33990.36732
6-0.12682-1.28710.100474
7-0.027001-0.2740.392307
80.080360.81560.208316
90.0184010.18670.426112
10-0.029251-0.29690.383582
11-0.005678-0.05760.47708
12-0.291893-2.96240.001895
130.0167880.17040.432523
140.0263430.26740.394865
15-0.134322-1.36320.087893
160.0028830.02930.488357
17-0.005865-0.05950.476325
180.148261.50470.067734
190.078460.79630.21385
200.0570660.57920.281876

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.035357 & -0.3588 & 0.360226 \tabularnewline
2 & -0.0246 & -0.2497 & 0.401675 \tabularnewline
3 & 0.070966 & 0.7202 & 0.236509 \tabularnewline
4 & -0.165857 & -1.6833 & 0.047676 \tabularnewline
5 & 0.033489 & 0.3399 & 0.36732 \tabularnewline
6 & -0.12682 & -1.2871 & 0.100474 \tabularnewline
7 & -0.027001 & -0.274 & 0.392307 \tabularnewline
8 & 0.08036 & 0.8156 & 0.208316 \tabularnewline
9 & 0.018401 & 0.1867 & 0.426112 \tabularnewline
10 & -0.029251 & -0.2969 & 0.383582 \tabularnewline
11 & -0.005678 & -0.0576 & 0.47708 \tabularnewline
12 & -0.291893 & -2.9624 & 0.001895 \tabularnewline
13 & 0.016788 & 0.1704 & 0.432523 \tabularnewline
14 & 0.026343 & 0.2674 & 0.394865 \tabularnewline
15 & -0.134322 & -1.3632 & 0.087893 \tabularnewline
16 & 0.002883 & 0.0293 & 0.488357 \tabularnewline
17 & -0.005865 & -0.0595 & 0.476325 \tabularnewline
18 & 0.14826 & 1.5047 & 0.067734 \tabularnewline
19 & 0.07846 & 0.7963 & 0.21385 \tabularnewline
20 & 0.057066 & 0.5792 & 0.281876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300950&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]-0.035357[/C][C]-0.3588[/C][C]0.360226[/C][/ROW]
[ROW][C]2[/C][C]-0.0246[/C][C]-0.2497[/C][C]0.401675[/C][/ROW]
[ROW][C]3[/C][C]0.070966[/C][C]0.7202[/C][C]0.236509[/C][/ROW]
[ROW][C]4[/C][C]-0.165857[/C][C]-1.6833[/C][C]0.047676[/C][/ROW]
[ROW][C]5[/C][C]0.033489[/C][C]0.3399[/C][C]0.36732[/C][/ROW]
[ROW][C]6[/C][C]-0.12682[/C][C]-1.2871[/C][C]0.100474[/C][/ROW]
[ROW][C]7[/C][C]-0.027001[/C][C]-0.274[/C][C]0.392307[/C][/ROW]
[ROW][C]8[/C][C]0.08036[/C][C]0.8156[/C][C]0.208316[/C][/ROW]
[ROW][C]9[/C][C]0.018401[/C][C]0.1867[/C][C]0.426112[/C][/ROW]
[ROW][C]10[/C][C]-0.029251[/C][C]-0.2969[/C][C]0.383582[/C][/ROW]
[ROW][C]11[/C][C]-0.005678[/C][C]-0.0576[/C][C]0.47708[/C][/ROW]
[ROW][C]12[/C][C]-0.291893[/C][C]-2.9624[/C][C]0.001895[/C][/ROW]
[ROW][C]13[/C][C]0.016788[/C][C]0.1704[/C][C]0.432523[/C][/ROW]
[ROW][C]14[/C][C]0.026343[/C][C]0.2674[/C][C]0.394865[/C][/ROW]
[ROW][C]15[/C][C]-0.134322[/C][C]-1.3632[/C][C]0.087893[/C][/ROW]
[ROW][C]16[/C][C]0.002883[/C][C]0.0293[/C][C]0.488357[/C][/ROW]
[ROW][C]17[/C][C]-0.005865[/C][C]-0.0595[/C][C]0.476325[/C][/ROW]
[ROW][C]18[/C][C]0.14826[/C][C]1.5047[/C][C]0.067734[/C][/ROW]
[ROW][C]19[/C][C]0.07846[/C][C]0.7963[/C][C]0.21385[/C][/ROW]
[ROW][C]20[/C][C]0.057066[/C][C]0.5792[/C][C]0.281876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300950&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300950&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
1-0.035357-0.35880.360226
2-0.0246-0.24970.401675
30.0709660.72020.236509
4-0.165857-1.68330.047676
50.0334890.33990.36732
6-0.12682-1.28710.100474
7-0.027001-0.2740.392307
80.080360.81560.208316
90.0184010.18670.426112
10-0.029251-0.29690.383582
11-0.005678-0.05760.47708
12-0.291893-2.96240.001895
130.0167880.17040.432523
140.0263430.26740.394865
15-0.134322-1.36320.087893
160.0028830.02930.488357
17-0.005865-0.05950.476325
180.148261.50470.067734
190.078460.79630.21385
200.0570660.57920.281876







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.035357-0.35880.360226
2-0.025882-0.26270.396663
30.0692910.70320.24175
4-0.162626-1.65050.050946
50.0283180.28740.387192
6-0.1434-1.45540.074306
7-0.007951-0.08070.467923
80.0400090.4060.342777
90.0505250.51280.304603
10-0.069346-0.70380.241577
11-0.011355-0.11520.454238
12-0.318924-3.23670.000813
130.0199740.20270.419878
14-0.005799-0.05890.476593
15-0.082439-0.83670.202358
16-0.135725-1.37750.085679
17-0.011101-0.11270.45526
180.0790480.80220.212129
190.0731320.74220.229825
200.1004661.01960.155148

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.035357 & -0.3588 & 0.360226 \tabularnewline
2 & -0.025882 & -0.2627 & 0.396663 \tabularnewline
3 & 0.069291 & 0.7032 & 0.24175 \tabularnewline
4 & -0.162626 & -1.6505 & 0.050946 \tabularnewline
5 & 0.028318 & 0.2874 & 0.387192 \tabularnewline
6 & -0.1434 & -1.4554 & 0.074306 \tabularnewline
7 & -0.007951 & -0.0807 & 0.467923 \tabularnewline
8 & 0.040009 & 0.406 & 0.342777 \tabularnewline
9 & 0.050525 & 0.5128 & 0.304603 \tabularnewline
10 & -0.069346 & -0.7038 & 0.241577 \tabularnewline
11 & -0.011355 & -0.1152 & 0.454238 \tabularnewline
12 & -0.318924 & -3.2367 & 0.000813 \tabularnewline
13 & 0.019974 & 0.2027 & 0.419878 \tabularnewline
14 & -0.005799 & -0.0589 & 0.476593 \tabularnewline
15 & -0.082439 & -0.8367 & 0.202358 \tabularnewline
16 & -0.135725 & -1.3775 & 0.085679 \tabularnewline
17 & -0.011101 & -0.1127 & 0.45526 \tabularnewline
18 & 0.079048 & 0.8022 & 0.212129 \tabularnewline
19 & 0.073132 & 0.7422 & 0.229825 \tabularnewline
20 & 0.100466 & 1.0196 & 0.155148 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300950&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]-0.035357[/C][C]-0.3588[/C][C]0.360226[/C][/ROW]
[ROW][C]2[/C][C]-0.025882[/C][C]-0.2627[/C][C]0.396663[/C][/ROW]
[ROW][C]3[/C][C]0.069291[/C][C]0.7032[/C][C]0.24175[/C][/ROW]
[ROW][C]4[/C][C]-0.162626[/C][C]-1.6505[/C][C]0.050946[/C][/ROW]
[ROW][C]5[/C][C]0.028318[/C][C]0.2874[/C][C]0.387192[/C][/ROW]
[ROW][C]6[/C][C]-0.1434[/C][C]-1.4554[/C][C]0.074306[/C][/ROW]
[ROW][C]7[/C][C]-0.007951[/C][C]-0.0807[/C][C]0.467923[/C][/ROW]
[ROW][C]8[/C][C]0.040009[/C][C]0.406[/C][C]0.342777[/C][/ROW]
[ROW][C]9[/C][C]0.050525[/C][C]0.5128[/C][C]0.304603[/C][/ROW]
[ROW][C]10[/C][C]-0.069346[/C][C]-0.7038[/C][C]0.241577[/C][/ROW]
[ROW][C]11[/C][C]-0.011355[/C][C]-0.1152[/C][C]0.454238[/C][/ROW]
[ROW][C]12[/C][C]-0.318924[/C][C]-3.2367[/C][C]0.000813[/C][/ROW]
[ROW][C]13[/C][C]0.019974[/C][C]0.2027[/C][C]0.419878[/C][/ROW]
[ROW][C]14[/C][C]-0.005799[/C][C]-0.0589[/C][C]0.476593[/C][/ROW]
[ROW][C]15[/C][C]-0.082439[/C][C]-0.8367[/C][C]0.202358[/C][/ROW]
[ROW][C]16[/C][C]-0.135725[/C][C]-1.3775[/C][C]0.085679[/C][/ROW]
[ROW][C]17[/C][C]-0.011101[/C][C]-0.1127[/C][C]0.45526[/C][/ROW]
[ROW][C]18[/C][C]0.079048[/C][C]0.8022[/C][C]0.212129[/C][/ROW]
[ROW][C]19[/C][C]0.073132[/C][C]0.7422[/C][C]0.229825[/C][/ROW]
[ROW][C]20[/C][C]0.100466[/C][C]1.0196[/C][C]0.155148[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300950&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300950&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
1-0.035357-0.35880.360226
2-0.025882-0.26270.396663
30.0692910.70320.24175
4-0.162626-1.65050.050946
50.0283180.28740.387192
6-0.1434-1.45540.074306
7-0.007951-0.08070.467923
80.0400090.4060.342777
90.0505250.51280.304603
10-0.069346-0.70380.241577
11-0.011355-0.11520.454238
12-0.318924-3.23670.000813
130.0199740.20270.419878
14-0.005799-0.05890.476593
15-0.082439-0.83670.202358
16-0.135725-1.37750.085679
17-0.011101-0.11270.45526
180.0790480.80220.212129
190.0731320.74220.229825
200.1004661.01960.155148



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