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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationFri, 23 Oct 2015 22:25:32 +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/2015/Oct/23/t1445635598radvfx236dl3f4t.htm/, Retrieved Sat, 11 May 2024 10:45:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283000, Retrieved Sat, 11 May 2024 10:45:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Aantal niet-werke...] [2015-10-23 21:25:32] [1e41f2c0cb9908cbb229b763456942f4] [Current]
- R P     [(Partial) Autocorrelation Function] [Aantal niet-werke...] [2015-12-21 08:31:52] [bd0500bc70c400edacc49194edbaf94e]
-   P       [(Partial) Autocorrelation Function] [Aantal niet werke...] [2016-01-08 12:17:00] [bd0500bc70c400edacc49194edbaf94e]
- RMP     [Mean Plot] [Aantal niet-werke...] [2015-12-21 08:39:07] [bd0500bc70c400edacc49194edbaf94e]
- R P     [(Partial) Autocorrelation Function] [Aantal niet-werke...] [2015-12-21 09:22:06] [bd0500bc70c400edacc49194edbaf94e]
- RMP       [Mean Plot] [Aantal niet-werke...] [2015-12-21 09:29:49] [bd0500bc70c400edacc49194edbaf94e]
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Dataseries X:
516922
507561
492622
490243
469357
477580
528379
533590
517945
506174
501866
516141
528222
532638
536322
536535
523597
536214
586570
596594
580523
564478
557560
575093
580112
574761
563250
551531
537034
544686
600991
604378
586111
563668
548604
551174
555654
547970
540324
530577
520579
518654
572273
581302
563280
547612
538712
540735
561649
558685
545732
536352
527676
530455
581744
598714
583775
571477
563278
564872
577537
572399
565430
560619
551227
553397
610893
621668
613148
598778
590623
595902
612186
603453
593362
581940
568075
567467
619423
627325
617144
602280
590816
589812




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283000&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283000&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283000&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.8418087.71530
20.6034825.5310
30.4623414.23742.9e-05
40.4356473.99287e-05
50.4686824.29552.3e-05
60.4718124.32422.1e-05
70.3902373.57660.00029
80.2669962.44710.008243
90.1881221.72420.044178
100.2109851.93370.028258
110.3315063.03830.001585
120.4011273.67640.000208
130.2459892.25450.013383
140.0283660.260.397757
15-0.095579-0.8760.191764
16-0.115941-1.06260.145502
17-0.07794-0.71430.238501
18-0.059386-0.54430.293844
19-0.099607-0.91290.181951

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.841808 & 7.7153 & 0 \tabularnewline
2 & 0.603482 & 5.531 & 0 \tabularnewline
3 & 0.462341 & 4.2374 & 2.9e-05 \tabularnewline
4 & 0.435647 & 3.9928 & 7e-05 \tabularnewline
5 & 0.468682 & 4.2955 & 2.3e-05 \tabularnewline
6 & 0.471812 & 4.3242 & 2.1e-05 \tabularnewline
7 & 0.390237 & 3.5766 & 0.00029 \tabularnewline
8 & 0.266996 & 2.4471 & 0.008243 \tabularnewline
9 & 0.188122 & 1.7242 & 0.044178 \tabularnewline
10 & 0.210985 & 1.9337 & 0.028258 \tabularnewline
11 & 0.331506 & 3.0383 & 0.001585 \tabularnewline
12 & 0.401127 & 3.6764 & 0.000208 \tabularnewline
13 & 0.245989 & 2.2545 & 0.013383 \tabularnewline
14 & 0.028366 & 0.26 & 0.397757 \tabularnewline
15 & -0.095579 & -0.876 & 0.191764 \tabularnewline
16 & -0.115941 & -1.0626 & 0.145502 \tabularnewline
17 & -0.07794 & -0.7143 & 0.238501 \tabularnewline
18 & -0.059386 & -0.5443 & 0.293844 \tabularnewline
19 & -0.099607 & -0.9129 & 0.181951 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283000&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]0.841808[/C][C]7.7153[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.603482[/C][C]5.531[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.462341[/C][C]4.2374[/C][C]2.9e-05[/C][/ROW]
[ROW][C]4[/C][C]0.435647[/C][C]3.9928[/C][C]7e-05[/C][/ROW]
[ROW][C]5[/C][C]0.468682[/C][C]4.2955[/C][C]2.3e-05[/C][/ROW]
[ROW][C]6[/C][C]0.471812[/C][C]4.3242[/C][C]2.1e-05[/C][/ROW]
[ROW][C]7[/C][C]0.390237[/C][C]3.5766[/C][C]0.00029[/C][/ROW]
[ROW][C]8[/C][C]0.266996[/C][C]2.4471[/C][C]0.008243[/C][/ROW]
[ROW][C]9[/C][C]0.188122[/C][C]1.7242[/C][C]0.044178[/C][/ROW]
[ROW][C]10[/C][C]0.210985[/C][C]1.9337[/C][C]0.028258[/C][/ROW]
[ROW][C]11[/C][C]0.331506[/C][C]3.0383[/C][C]0.001585[/C][/ROW]
[ROW][C]12[/C][C]0.401127[/C][C]3.6764[/C][C]0.000208[/C][/ROW]
[ROW][C]13[/C][C]0.245989[/C][C]2.2545[/C][C]0.013383[/C][/ROW]
[ROW][C]14[/C][C]0.028366[/C][C]0.26[/C][C]0.397757[/C][/ROW]
[ROW][C]15[/C][C]-0.095579[/C][C]-0.876[/C][C]0.191764[/C][/ROW]
[ROW][C]16[/C][C]-0.115941[/C][C]-1.0626[/C][C]0.145502[/C][/ROW]
[ROW][C]17[/C][C]-0.07794[/C][C]-0.7143[/C][C]0.238501[/C][/ROW]
[ROW][C]18[/C][C]-0.059386[/C][C]-0.5443[/C][C]0.293844[/C][/ROW]
[ROW][C]19[/C][C]-0.099607[/C][C]-0.9129[/C][C]0.181951[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283000&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283000&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
10.8418087.71530
20.6034825.5310
30.4623414.23742.9e-05
40.4356473.99287e-05
50.4686824.29552.3e-05
60.4718124.32422.1e-05
70.3902373.57660.00029
80.2669962.44710.008243
90.1881221.72420.044178
100.2109851.93370.028258
110.3315063.03830.001585
120.4011273.67640.000208
130.2459892.25450.013383
140.0283660.260.397757
15-0.095579-0.8760.191764
16-0.115941-1.06260.145502
17-0.07794-0.71430.238501
18-0.059386-0.54430.293844
19-0.099607-0.91290.181951







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8418087.71530
2-0.360923-3.30790.000693
30.2951742.70530.004131
40.1302161.19350.118026
50.13941.27760.102451
6-0.04357-0.39930.345334
7-0.130982-1.20050.116665
8-0.046356-0.42490.336013
90.0436940.40050.344915
100.1658781.52030.066096
110.2617692.39910.009323
12-0.142729-1.30810.097199
13-0.589993-5.40740
140.1295991.18780.119131
15-0.001478-0.01350.494612
16-0.097537-0.89390.186954
17-0.021114-0.19350.423512
18-0.001962-0.0180.492848
190.1253131.14850.127009

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.841808 & 7.7153 & 0 \tabularnewline
2 & -0.360923 & -3.3079 & 0.000693 \tabularnewline
3 & 0.295174 & 2.7053 & 0.004131 \tabularnewline
4 & 0.130216 & 1.1935 & 0.118026 \tabularnewline
5 & 0.1394 & 1.2776 & 0.102451 \tabularnewline
6 & -0.04357 & -0.3993 & 0.345334 \tabularnewline
7 & -0.130982 & -1.2005 & 0.116665 \tabularnewline
8 & -0.046356 & -0.4249 & 0.336013 \tabularnewline
9 & 0.043694 & 0.4005 & 0.344915 \tabularnewline
10 & 0.165878 & 1.5203 & 0.066096 \tabularnewline
11 & 0.261769 & 2.3991 & 0.009323 \tabularnewline
12 & -0.142729 & -1.3081 & 0.097199 \tabularnewline
13 & -0.589993 & -5.4074 & 0 \tabularnewline
14 & 0.129599 & 1.1878 & 0.119131 \tabularnewline
15 & -0.001478 & -0.0135 & 0.494612 \tabularnewline
16 & -0.097537 & -0.8939 & 0.186954 \tabularnewline
17 & -0.021114 & -0.1935 & 0.423512 \tabularnewline
18 & -0.001962 & -0.018 & 0.492848 \tabularnewline
19 & 0.125313 & 1.1485 & 0.127009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283000&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]0.841808[/C][C]7.7153[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.360923[/C][C]-3.3079[/C][C]0.000693[/C][/ROW]
[ROW][C]3[/C][C]0.295174[/C][C]2.7053[/C][C]0.004131[/C][/ROW]
[ROW][C]4[/C][C]0.130216[/C][C]1.1935[/C][C]0.118026[/C][/ROW]
[ROW][C]5[/C][C]0.1394[/C][C]1.2776[/C][C]0.102451[/C][/ROW]
[ROW][C]6[/C][C]-0.04357[/C][C]-0.3993[/C][C]0.345334[/C][/ROW]
[ROW][C]7[/C][C]-0.130982[/C][C]-1.2005[/C][C]0.116665[/C][/ROW]
[ROW][C]8[/C][C]-0.046356[/C][C]-0.4249[/C][C]0.336013[/C][/ROW]
[ROW][C]9[/C][C]0.043694[/C][C]0.4005[/C][C]0.344915[/C][/ROW]
[ROW][C]10[/C][C]0.165878[/C][C]1.5203[/C][C]0.066096[/C][/ROW]
[ROW][C]11[/C][C]0.261769[/C][C]2.3991[/C][C]0.009323[/C][/ROW]
[ROW][C]12[/C][C]-0.142729[/C][C]-1.3081[/C][C]0.097199[/C][/ROW]
[ROW][C]13[/C][C]-0.589993[/C][C]-5.4074[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.129599[/C][C]1.1878[/C][C]0.119131[/C][/ROW]
[ROW][C]15[/C][C]-0.001478[/C][C]-0.0135[/C][C]0.494612[/C][/ROW]
[ROW][C]16[/C][C]-0.097537[/C][C]-0.8939[/C][C]0.186954[/C][/ROW]
[ROW][C]17[/C][C]-0.021114[/C][C]-0.1935[/C][C]0.423512[/C][/ROW]
[ROW][C]18[/C][C]-0.001962[/C][C]-0.018[/C][C]0.492848[/C][/ROW]
[ROW][C]19[/C][C]0.125313[/C][C]1.1485[/C][C]0.127009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283000&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283000&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
10.8418087.71530
2-0.360923-3.30790.000693
30.2951742.70530.004131
40.1302161.19350.118026
50.13941.27760.102451
6-0.04357-0.39930.345334
7-0.130982-1.20050.116665
8-0.046356-0.42490.336013
90.0436940.40050.344915
100.1658781.52030.066096
110.2617692.39910.009323
12-0.142729-1.30810.097199
13-0.589993-5.40740
140.1295991.18780.119131
15-0.001478-0.01350.494612
16-0.097537-0.89390.186954
17-0.021114-0.19350.423512
18-0.001962-0.0180.492848
190.1253131.14850.127009



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)
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,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),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,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),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')