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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 computationTue, 13 Dec 2016 12:42:39 +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/13/t14816294066k06y78fofqjxxb.htm/, Retrieved Fri, 01 Nov 2024 03:37:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299075, Retrieved Fri, 01 Nov 2024 03:37:23 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelatie oo...] [2016-12-13 11:42:39] [e8b5e2ae4a4517822f644e6c122e1af0] [Current]
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Dataseries X:
3800
1650
4250
3200
2050
3600
3700
6000
8550
9050
6000
8550
6700
3850
2950
2900
2200
3500
4900
6650
10050
8300
7650
5750
4600
5250
3250
1150
1950
2850
2950
4950
6000
6650
6150
4300
4450
1250
3000
2600
1200
2050
2000
5050
4050
5150
6450
3700
3300
2000
2650
900
1350
4550
1850
3650
3250
5950
4050
3250
2200
1050
2250
2650
650
1100
2900
6450
3100
6050
4200
1800
2100
1550
1050
900
1800
1700
1700
2250
4000
3500
3300
1550
2750
1900
1200
1150
1150
2200
1500
3850
2950
3750
4600
3350
2300
1400
900
1250
1650
1600
1200
2300
2950
5650
4000
3300




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=299075&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=299075&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299075&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
10.7008387.28330
20.5165175.36780
30.2884392.99750.001689
40.0444120.46150.322668
5-0.120255-1.24970.10705
6-0.212546-2.20880.014649
7-0.135204-1.40510.081433
8-0.043008-0.4470.327901
90.2116632.19970.014981
100.4271464.4391.1e-05
110.5495725.71130
120.6249916.49510
130.541235.62460
140.4177264.34111.6e-05
150.1338551.39110.083533
16-0.070837-0.73620.231613
17-0.157347-1.63520.05246
18-0.248204-2.57940.005621
19-0.203199-2.11170.018509
20-0.100582-1.04530.149113

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.700838 & 7.2833 & 0 \tabularnewline
2 & 0.516517 & 5.3678 & 0 \tabularnewline
3 & 0.288439 & 2.9975 & 0.001689 \tabularnewline
4 & 0.044412 & 0.4615 & 0.322668 \tabularnewline
5 & -0.120255 & -1.2497 & 0.10705 \tabularnewline
6 & -0.212546 & -2.2088 & 0.014649 \tabularnewline
7 & -0.135204 & -1.4051 & 0.081433 \tabularnewline
8 & -0.043008 & -0.447 & 0.327901 \tabularnewline
9 & 0.211663 & 2.1997 & 0.014981 \tabularnewline
10 & 0.427146 & 4.439 & 1.1e-05 \tabularnewline
11 & 0.549572 & 5.7113 & 0 \tabularnewline
12 & 0.624991 & 6.4951 & 0 \tabularnewline
13 & 0.54123 & 5.6246 & 0 \tabularnewline
14 & 0.417726 & 4.3411 & 1.6e-05 \tabularnewline
15 & 0.133855 & 1.3911 & 0.083533 \tabularnewline
16 & -0.070837 & -0.7362 & 0.231613 \tabularnewline
17 & -0.157347 & -1.6352 & 0.05246 \tabularnewline
18 & -0.248204 & -2.5794 & 0.005621 \tabularnewline
19 & -0.203199 & -2.1117 & 0.018509 \tabularnewline
20 & -0.100582 & -1.0453 & 0.149113 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299075&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]0.700838[/C][C]7.2833[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.516517[/C][C]5.3678[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.288439[/C][C]2.9975[/C][C]0.001689[/C][/ROW]
[ROW][C]4[/C][C]0.044412[/C][C]0.4615[/C][C]0.322668[/C][/ROW]
[ROW][C]5[/C][C]-0.120255[/C][C]-1.2497[/C][C]0.10705[/C][/ROW]
[ROW][C]6[/C][C]-0.212546[/C][C]-2.2088[/C][C]0.014649[/C][/ROW]
[ROW][C]7[/C][C]-0.135204[/C][C]-1.4051[/C][C]0.081433[/C][/ROW]
[ROW][C]8[/C][C]-0.043008[/C][C]-0.447[/C][C]0.327901[/C][/ROW]
[ROW][C]9[/C][C]0.211663[/C][C]2.1997[/C][C]0.014981[/C][/ROW]
[ROW][C]10[/C][C]0.427146[/C][C]4.439[/C][C]1.1e-05[/C][/ROW]
[ROW][C]11[/C][C]0.549572[/C][C]5.7113[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.624991[/C][C]6.4951[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.54123[/C][C]5.6246[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.417726[/C][C]4.3411[/C][C]1.6e-05[/C][/ROW]
[ROW][C]15[/C][C]0.133855[/C][C]1.3911[/C][C]0.083533[/C][/ROW]
[ROW][C]16[/C][C]-0.070837[/C][C]-0.7362[/C][C]0.231613[/C][/ROW]
[ROW][C]17[/C][C]-0.157347[/C][C]-1.6352[/C][C]0.05246[/C][/ROW]
[ROW][C]18[/C][C]-0.248204[/C][C]-2.5794[/C][C]0.005621[/C][/ROW]
[ROW][C]19[/C][C]-0.203199[/C][C]-2.1117[/C][C]0.018509[/C][/ROW]
[ROW][C]20[/C][C]-0.100582[/C][C]-1.0453[/C][C]0.149113[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299075&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299075&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
10.7008387.28330
20.5165175.36780
30.2884392.99750.001689
40.0444120.46150.322668
5-0.120255-1.24970.10705
6-0.212546-2.20880.014649
7-0.135204-1.40510.081433
8-0.043008-0.4470.327901
90.2116632.19970.014981
100.4271464.4391.1e-05
110.5495725.71130
120.6249916.49510
130.541235.62460
140.4177264.34111.6e-05
150.1338551.39110.083533
16-0.070837-0.73620.231613
17-0.157347-1.63520.05246
18-0.248204-2.57940.005621
19-0.203199-2.11170.018509
20-0.100582-1.04530.149113







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7008387.28330
20.0498060.51760.302898
3-0.17817-1.85160.033408
4-0.228649-2.37620.009627
5-0.076296-0.79290.214789
60.0030490.03170.487389
70.2406282.50070.006949
80.0997271.03640.151166
90.3521493.65960.000196
100.2329462.42080.008576
110.0806450.83810.201916
120.0928860.96530.168275
13-0.047919-0.4980.309751
140.0113670.11810.453092
15-0.237021-2.46320.007675
16-0.093649-0.97320.166308
170.1760711.82980.035021
18-0.025738-0.26750.394806
19-0.061195-0.6360.263076
20-0.066833-0.69460.244414

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.700838 & 7.2833 & 0 \tabularnewline
2 & 0.049806 & 0.5176 & 0.302898 \tabularnewline
3 & -0.17817 & -1.8516 & 0.033408 \tabularnewline
4 & -0.228649 & -2.3762 & 0.009627 \tabularnewline
5 & -0.076296 & -0.7929 & 0.214789 \tabularnewline
6 & 0.003049 & 0.0317 & 0.487389 \tabularnewline
7 & 0.240628 & 2.5007 & 0.006949 \tabularnewline
8 & 0.099727 & 1.0364 & 0.151166 \tabularnewline
9 & 0.352149 & 3.6596 & 0.000196 \tabularnewline
10 & 0.232946 & 2.4208 & 0.008576 \tabularnewline
11 & 0.080645 & 0.8381 & 0.201916 \tabularnewline
12 & 0.092886 & 0.9653 & 0.168275 \tabularnewline
13 & -0.047919 & -0.498 & 0.309751 \tabularnewline
14 & 0.011367 & 0.1181 & 0.453092 \tabularnewline
15 & -0.237021 & -2.4632 & 0.007675 \tabularnewline
16 & -0.093649 & -0.9732 & 0.166308 \tabularnewline
17 & 0.176071 & 1.8298 & 0.035021 \tabularnewline
18 & -0.025738 & -0.2675 & 0.394806 \tabularnewline
19 & -0.061195 & -0.636 & 0.263076 \tabularnewline
20 & -0.066833 & -0.6946 & 0.244414 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299075&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]0.700838[/C][C]7.2833[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.049806[/C][C]0.5176[/C][C]0.302898[/C][/ROW]
[ROW][C]3[/C][C]-0.17817[/C][C]-1.8516[/C][C]0.033408[/C][/ROW]
[ROW][C]4[/C][C]-0.228649[/C][C]-2.3762[/C][C]0.009627[/C][/ROW]
[ROW][C]5[/C][C]-0.076296[/C][C]-0.7929[/C][C]0.214789[/C][/ROW]
[ROW][C]6[/C][C]0.003049[/C][C]0.0317[/C][C]0.487389[/C][/ROW]
[ROW][C]7[/C][C]0.240628[/C][C]2.5007[/C][C]0.006949[/C][/ROW]
[ROW][C]8[/C][C]0.099727[/C][C]1.0364[/C][C]0.151166[/C][/ROW]
[ROW][C]9[/C][C]0.352149[/C][C]3.6596[/C][C]0.000196[/C][/ROW]
[ROW][C]10[/C][C]0.232946[/C][C]2.4208[/C][C]0.008576[/C][/ROW]
[ROW][C]11[/C][C]0.080645[/C][C]0.8381[/C][C]0.201916[/C][/ROW]
[ROW][C]12[/C][C]0.092886[/C][C]0.9653[/C][C]0.168275[/C][/ROW]
[ROW][C]13[/C][C]-0.047919[/C][C]-0.498[/C][C]0.309751[/C][/ROW]
[ROW][C]14[/C][C]0.011367[/C][C]0.1181[/C][C]0.453092[/C][/ROW]
[ROW][C]15[/C][C]-0.237021[/C][C]-2.4632[/C][C]0.007675[/C][/ROW]
[ROW][C]16[/C][C]-0.093649[/C][C]-0.9732[/C][C]0.166308[/C][/ROW]
[ROW][C]17[/C][C]0.176071[/C][C]1.8298[/C][C]0.035021[/C][/ROW]
[ROW][C]18[/C][C]-0.025738[/C][C]-0.2675[/C][C]0.394806[/C][/ROW]
[ROW][C]19[/C][C]-0.061195[/C][C]-0.636[/C][C]0.263076[/C][/ROW]
[ROW][C]20[/C][C]-0.066833[/C][C]-0.6946[/C][C]0.244414[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299075&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299075&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
10.7008387.28330
20.0498060.51760.302898
3-0.17817-1.85160.033408
4-0.228649-2.37620.009627
5-0.076296-0.79290.214789
60.0030490.03170.487389
70.2406282.50070.006949
80.0997271.03640.151166
90.3521493.65960.000196
100.2329462.42080.008576
110.0806450.83810.201916
120.0928860.96530.168275
13-0.047919-0.4980.309751
140.0113670.11810.453092
15-0.237021-2.46320.007675
16-0.093649-0.97320.166308
170.1760711.82980.035021
18-0.025738-0.26750.394806
19-0.061195-0.6360.263076
20-0.066833-0.69460.244414



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')