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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 17:42:21 +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/t14821657677pbfrnplb8uvx39.htm/, Retrieved Fri, 01 Nov 2024 03:45:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301417, Retrieved Fri, 01 Nov 2024 03:45:57 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2016-12-19 16:42:21] [361c8dad91b3f1ef2e651cd04783c23b] [Current]
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Dataseries X:
2755
2765
3000
2890
2940
3290
2815
3035
3070
3040
2685
2540
3090
2995
3440
3335
3205
3285
2790
3225
3360
3275
3505
3185
3470
3510
3840
3605
3655
3555
3140
3380
3255
3460
3245
3120
3265
3220
3140
3050
3300
2950
2630
2795
2840
2945
2790
2605
4590
4230
4245
4300
4475
3910
4100
3500
4390
3550
3865
3715
3310
3945
5050
4350
4060
4345
4360
4915
4650
4805
4775
4220
3975
3820
5515
4895
5535
4230
3695
5590
5000
4875
4360
4405
4500
4070
4800
4080
4850
4105
3805
5060
4060
4600
4635
3900
4120
3960
4400
3700
3970
4550
5140
5000
3650
4300
3650
3355
4000
3450
3295
3390
3415
3440
3680
3900
3965
4295
4210
4100
4690
3860
4250
4495
3800
3845




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=301417&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=301417&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301417&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
1-0.280719-2.98410.001743
2-0.237142-2.52090.006551
30.0607460.64570.259877
40.0562320.59780.275601
50.0712120.7570.225315
6-0.104601-1.11190.134265
7-0.042915-0.45620.324565
80.0562120.59750.275669
90.0153120.16280.435497
10-0.058523-0.62210.267561
110.0836510.88920.187885
12-0.284939-3.02890.001521
130.0559580.59480.276571
140.2245382.38690.009326
15-0.026233-0.27890.390429
16-0.317173-3.37160.000512
170.1417731.50710.067292
180.2492882.650.004602
19-0.131764-1.40070.082026
20-0.099471-1.05740.146294
210.0336790.3580.360502

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.280719 & -2.9841 & 0.001743 \tabularnewline
2 & -0.237142 & -2.5209 & 0.006551 \tabularnewline
3 & 0.060746 & 0.6457 & 0.259877 \tabularnewline
4 & 0.056232 & 0.5978 & 0.275601 \tabularnewline
5 & 0.071212 & 0.757 & 0.225315 \tabularnewline
6 & -0.104601 & -1.1119 & 0.134265 \tabularnewline
7 & -0.042915 & -0.4562 & 0.324565 \tabularnewline
8 & 0.056212 & 0.5975 & 0.275669 \tabularnewline
9 & 0.015312 & 0.1628 & 0.435497 \tabularnewline
10 & -0.058523 & -0.6221 & 0.267561 \tabularnewline
11 & 0.083651 & 0.8892 & 0.187885 \tabularnewline
12 & -0.284939 & -3.0289 & 0.001521 \tabularnewline
13 & 0.055958 & 0.5948 & 0.276571 \tabularnewline
14 & 0.224538 & 2.3869 & 0.009326 \tabularnewline
15 & -0.026233 & -0.2789 & 0.390429 \tabularnewline
16 & -0.317173 & -3.3716 & 0.000512 \tabularnewline
17 & 0.141773 & 1.5071 & 0.067292 \tabularnewline
18 & 0.249288 & 2.65 & 0.004602 \tabularnewline
19 & -0.131764 & -1.4007 & 0.082026 \tabularnewline
20 & -0.099471 & -1.0574 & 0.146294 \tabularnewline
21 & 0.033679 & 0.358 & 0.360502 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301417&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]-0.280719[/C][C]-2.9841[/C][C]0.001743[/C][/ROW]
[ROW][C]2[/C][C]-0.237142[/C][C]-2.5209[/C][C]0.006551[/C][/ROW]
[ROW][C]3[/C][C]0.060746[/C][C]0.6457[/C][C]0.259877[/C][/ROW]
[ROW][C]4[/C][C]0.056232[/C][C]0.5978[/C][C]0.275601[/C][/ROW]
[ROW][C]5[/C][C]0.071212[/C][C]0.757[/C][C]0.225315[/C][/ROW]
[ROW][C]6[/C][C]-0.104601[/C][C]-1.1119[/C][C]0.134265[/C][/ROW]
[ROW][C]7[/C][C]-0.042915[/C][C]-0.4562[/C][C]0.324565[/C][/ROW]
[ROW][C]8[/C][C]0.056212[/C][C]0.5975[/C][C]0.275669[/C][/ROW]
[ROW][C]9[/C][C]0.015312[/C][C]0.1628[/C][C]0.435497[/C][/ROW]
[ROW][C]10[/C][C]-0.058523[/C][C]-0.6221[/C][C]0.267561[/C][/ROW]
[ROW][C]11[/C][C]0.083651[/C][C]0.8892[/C][C]0.187885[/C][/ROW]
[ROW][C]12[/C][C]-0.284939[/C][C]-3.0289[/C][C]0.001521[/C][/ROW]
[ROW][C]13[/C][C]0.055958[/C][C]0.5948[/C][C]0.276571[/C][/ROW]
[ROW][C]14[/C][C]0.224538[/C][C]2.3869[/C][C]0.009326[/C][/ROW]
[ROW][C]15[/C][C]-0.026233[/C][C]-0.2789[/C][C]0.390429[/C][/ROW]
[ROW][C]16[/C][C]-0.317173[/C][C]-3.3716[/C][C]0.000512[/C][/ROW]
[ROW][C]17[/C][C]0.141773[/C][C]1.5071[/C][C]0.067292[/C][/ROW]
[ROW][C]18[/C][C]0.249288[/C][C]2.65[/C][C]0.004602[/C][/ROW]
[ROW][C]19[/C][C]-0.131764[/C][C]-1.4007[/C][C]0.082026[/C][/ROW]
[ROW][C]20[/C][C]-0.099471[/C][C]-1.0574[/C][C]0.146294[/C][/ROW]
[ROW][C]21[/C][C]0.033679[/C][C]0.358[/C][C]0.360502[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301417&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301417&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
1-0.280719-2.98410.001743
2-0.237142-2.52090.006551
30.0607460.64570.259877
40.0562320.59780.275601
50.0712120.7570.225315
6-0.104601-1.11190.134265
7-0.042915-0.45620.324565
80.0562120.59750.275669
90.0153120.16280.435497
10-0.058523-0.62210.267561
110.0836510.88920.187885
12-0.284939-3.02890.001521
130.0559580.59480.276571
140.2245382.38690.009326
15-0.026233-0.27890.390429
16-0.317173-3.37160.000512
170.1417731.50710.067292
180.2492882.650.004602
19-0.131764-1.40070.082026
20-0.099471-1.05740.146294
210.0336790.3580.360502







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.280719-2.98410.001743
2-0.342972-3.64580.000202
3-0.153701-1.63390.052535
4-0.070418-0.74850.227842
50.0742830.78960.215697
6-0.037037-0.39370.347269
7-0.05481-0.58260.280651
8-0.029079-0.30910.378902
9-0.014886-0.15820.437277
10-0.06139-0.65260.257675
110.078460.8340.20301
12-0.322812-3.43150.00042
13-0.191064-2.0310.022299
140.0150590.16010.436553
150.0853790.90760.183014
16-0.299478-3.18350.00094
17-0.035099-0.37310.354884
180.1434651.52510.06502
19-0.021032-0.22360.411745
20-0.058476-0.62160.267727
210.0407950.43370.332681

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.280719 & -2.9841 & 0.001743 \tabularnewline
2 & -0.342972 & -3.6458 & 0.000202 \tabularnewline
3 & -0.153701 & -1.6339 & 0.052535 \tabularnewline
4 & -0.070418 & -0.7485 & 0.227842 \tabularnewline
5 & 0.074283 & 0.7896 & 0.215697 \tabularnewline
6 & -0.037037 & -0.3937 & 0.347269 \tabularnewline
7 & -0.05481 & -0.5826 & 0.280651 \tabularnewline
8 & -0.029079 & -0.3091 & 0.378902 \tabularnewline
9 & -0.014886 & -0.1582 & 0.437277 \tabularnewline
10 & -0.06139 & -0.6526 & 0.257675 \tabularnewline
11 & 0.07846 & 0.834 & 0.20301 \tabularnewline
12 & -0.322812 & -3.4315 & 0.00042 \tabularnewline
13 & -0.191064 & -2.031 & 0.022299 \tabularnewline
14 & 0.015059 & 0.1601 & 0.436553 \tabularnewline
15 & 0.085379 & 0.9076 & 0.183014 \tabularnewline
16 & -0.299478 & -3.1835 & 0.00094 \tabularnewline
17 & -0.035099 & -0.3731 & 0.354884 \tabularnewline
18 & 0.143465 & 1.5251 & 0.06502 \tabularnewline
19 & -0.021032 & -0.2236 & 0.411745 \tabularnewline
20 & -0.058476 & -0.6216 & 0.267727 \tabularnewline
21 & 0.040795 & 0.4337 & 0.332681 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301417&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]-0.280719[/C][C]-2.9841[/C][C]0.001743[/C][/ROW]
[ROW][C]2[/C][C]-0.342972[/C][C]-3.6458[/C][C]0.000202[/C][/ROW]
[ROW][C]3[/C][C]-0.153701[/C][C]-1.6339[/C][C]0.052535[/C][/ROW]
[ROW][C]4[/C][C]-0.070418[/C][C]-0.7485[/C][C]0.227842[/C][/ROW]
[ROW][C]5[/C][C]0.074283[/C][C]0.7896[/C][C]0.215697[/C][/ROW]
[ROW][C]6[/C][C]-0.037037[/C][C]-0.3937[/C][C]0.347269[/C][/ROW]
[ROW][C]7[/C][C]-0.05481[/C][C]-0.5826[/C][C]0.280651[/C][/ROW]
[ROW][C]8[/C][C]-0.029079[/C][C]-0.3091[/C][C]0.378902[/C][/ROW]
[ROW][C]9[/C][C]-0.014886[/C][C]-0.1582[/C][C]0.437277[/C][/ROW]
[ROW][C]10[/C][C]-0.06139[/C][C]-0.6526[/C][C]0.257675[/C][/ROW]
[ROW][C]11[/C][C]0.07846[/C][C]0.834[/C][C]0.20301[/C][/ROW]
[ROW][C]12[/C][C]-0.322812[/C][C]-3.4315[/C][C]0.00042[/C][/ROW]
[ROW][C]13[/C][C]-0.191064[/C][C]-2.031[/C][C]0.022299[/C][/ROW]
[ROW][C]14[/C][C]0.015059[/C][C]0.1601[/C][C]0.436553[/C][/ROW]
[ROW][C]15[/C][C]0.085379[/C][C]0.9076[/C][C]0.183014[/C][/ROW]
[ROW][C]16[/C][C]-0.299478[/C][C]-3.1835[/C][C]0.00094[/C][/ROW]
[ROW][C]17[/C][C]-0.035099[/C][C]-0.3731[/C][C]0.354884[/C][/ROW]
[ROW][C]18[/C][C]0.143465[/C][C]1.5251[/C][C]0.06502[/C][/ROW]
[ROW][C]19[/C][C]-0.021032[/C][C]-0.2236[/C][C]0.411745[/C][/ROW]
[ROW][C]20[/C][C]-0.058476[/C][C]-0.6216[/C][C]0.267727[/C][/ROW]
[ROW][C]21[/C][C]0.040795[/C][C]0.4337[/C][C]0.332681[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301417&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301417&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
1-0.280719-2.98410.001743
2-0.342972-3.64580.000202
3-0.153701-1.63390.052535
4-0.070418-0.74850.227842
50.0742830.78960.215697
6-0.037037-0.39370.347269
7-0.05481-0.58260.280651
8-0.029079-0.30910.378902
9-0.014886-0.15820.437277
10-0.06139-0.65260.257675
110.078460.8340.20301
12-0.322812-3.43150.00042
13-0.191064-2.0310.022299
140.0150590.16010.436553
150.0853790.90760.183014
16-0.299478-3.18350.00094
17-0.035099-0.37310.354884
180.1434651.52510.06502
19-0.021032-0.22360.411745
20-0.058476-0.62160.267727
210.0407950.43370.332681



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):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '3'
par4 <- '2'
par3 <- '1'
par2 <- '1'
par1 <- 'Default'
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')