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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 computationFri, 05 Dec 2008 04:53:55 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/05/t1228478163cza74hsfifx09ee.htm/, Retrieved Thu, 31 Oct 2024 23:45:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29201, Retrieved Thu, 31 Oct 2024 23:45:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact223
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Werkloosheid 25 t...] [2008-11-28 13:12:46] [6743688719638b0cb1c0a6e0bf433315]
-   P   [Univariate Data Series] [Unemployment betw...] [2008-12-02 18:02:05] [6743688719638b0cb1c0a6e0bf433315]
- RMP     [Variance Reduction Matrix] [Total unemploymen...] [2008-12-03 16:40:35] [6743688719638b0cb1c0a6e0bf433315]
- RMP         [(Partial) Autocorrelation Function] [ACF unemployment ...] [2008-12-05 11:53:55] [9b05d7ef5dbcfba4217d280d9092f628] [Current]
-   P           [(Partial) Autocorrelation Function] [ACF unemployment ...] [2008-12-05 11:58:57] [6743688719638b0cb1c0a6e0bf433315]
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Dataseries X:
374556
375021
375787
372720
364431
370490
376974
377632
378205
370861
369167
371551
382842
381903
384502
392058
384359
388884
386586
387495
385705
378670
377367
376911
389827
387820
387267
380575
372402
376740
377795
376126
370804
367980
367866
366121
379421
378519
372423
355072
344693
342892
344178
337606
327103
323953
316532
306307
327225
329573
313761
307836
300074
304198
306122
300414
292133
290616
280244
285179
305486




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29201&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29201&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29201&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' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0307790.21320.416022
20.0170860.11840.453133
30.0986190.68330.248865
40.0883940.61240.271577
50.0074720.05180.479465
60.0297150.20590.418881
7-0.002934-0.02030.491932
80.1424750.98710.164272
9-0.068271-0.4730.319181
10-0.172454-1.19480.119018
110.1085490.7520.227847
12-0.171346-1.18710.120511
13-0.203029-1.40660.08299
140.0124370.08620.465846
15-0.010354-0.07170.471555
16-0.069798-0.48360.315443
17-0.052812-0.36590.358028

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.030779 & 0.2132 & 0.416022 \tabularnewline
2 & 0.017086 & 0.1184 & 0.453133 \tabularnewline
3 & 0.098619 & 0.6833 & 0.248865 \tabularnewline
4 & 0.088394 & 0.6124 & 0.271577 \tabularnewline
5 & 0.007472 & 0.0518 & 0.479465 \tabularnewline
6 & 0.029715 & 0.2059 & 0.418881 \tabularnewline
7 & -0.002934 & -0.0203 & 0.491932 \tabularnewline
8 & 0.142475 & 0.9871 & 0.164272 \tabularnewline
9 & -0.068271 & -0.473 & 0.319181 \tabularnewline
10 & -0.172454 & -1.1948 & 0.119018 \tabularnewline
11 & 0.108549 & 0.752 & 0.227847 \tabularnewline
12 & -0.171346 & -1.1871 & 0.120511 \tabularnewline
13 & -0.203029 & -1.4066 & 0.08299 \tabularnewline
14 & 0.012437 & 0.0862 & 0.465846 \tabularnewline
15 & -0.010354 & -0.0717 & 0.471555 \tabularnewline
16 & -0.069798 & -0.4836 & 0.315443 \tabularnewline
17 & -0.052812 & -0.3659 & 0.358028 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29201&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]0.030779[/C][C]0.2132[/C][C]0.416022[/C][/ROW]
[ROW][C]2[/C][C]0.017086[/C][C]0.1184[/C][C]0.453133[/C][/ROW]
[ROW][C]3[/C][C]0.098619[/C][C]0.6833[/C][C]0.248865[/C][/ROW]
[ROW][C]4[/C][C]0.088394[/C][C]0.6124[/C][C]0.271577[/C][/ROW]
[ROW][C]5[/C][C]0.007472[/C][C]0.0518[/C][C]0.479465[/C][/ROW]
[ROW][C]6[/C][C]0.029715[/C][C]0.2059[/C][C]0.418881[/C][/ROW]
[ROW][C]7[/C][C]-0.002934[/C][C]-0.0203[/C][C]0.491932[/C][/ROW]
[ROW][C]8[/C][C]0.142475[/C][C]0.9871[/C][C]0.164272[/C][/ROW]
[ROW][C]9[/C][C]-0.068271[/C][C]-0.473[/C][C]0.319181[/C][/ROW]
[ROW][C]10[/C][C]-0.172454[/C][C]-1.1948[/C][C]0.119018[/C][/ROW]
[ROW][C]11[/C][C]0.108549[/C][C]0.752[/C][C]0.227847[/C][/ROW]
[ROW][C]12[/C][C]-0.171346[/C][C]-1.1871[/C][C]0.120511[/C][/ROW]
[ROW][C]13[/C][C]-0.203029[/C][C]-1.4066[/C][C]0.08299[/C][/ROW]
[ROW][C]14[/C][C]0.012437[/C][C]0.0862[/C][C]0.465846[/C][/ROW]
[ROW][C]15[/C][C]-0.010354[/C][C]-0.0717[/C][C]0.471555[/C][/ROW]
[ROW][C]16[/C][C]-0.069798[/C][C]-0.4836[/C][C]0.315443[/C][/ROW]
[ROW][C]17[/C][C]-0.052812[/C][C]-0.3659[/C][C]0.358028[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29201&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29201&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
10.0307790.21320.416022
20.0170860.11840.453133
30.0986190.68330.248865
40.0883940.61240.271577
50.0074720.05180.479465
60.0297150.20590.418881
7-0.002934-0.02030.491932
80.1424750.98710.164272
9-0.068271-0.4730.319181
10-0.172454-1.19480.119018
110.1085490.7520.227847
12-0.171346-1.18710.120511
13-0.203029-1.40660.08299
140.0124370.08620.465846
15-0.010354-0.07170.471555
16-0.069798-0.48360.315443
17-0.052812-0.36590.358028







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0307790.21320.416022
20.0161540.11190.455678
30.0977230.6770.250814
40.0832250.57660.283452
50.0002750.00190.499244
60.0179790.12460.450694
7-0.021013-0.14560.442431
80.136830.9480.173943
9-0.082378-0.57070.285421
10-0.18028-1.2490.108858
110.1023270.70890.240894
12-0.195802-1.35660.090635
13-0.166699-1.15490.126919
140.0421880.29230.385664
150.0099640.0690.472626
16-0.030756-0.21310.416083
17-0.01007-0.06980.472334

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.030779 & 0.2132 & 0.416022 \tabularnewline
2 & 0.016154 & 0.1119 & 0.455678 \tabularnewline
3 & 0.097723 & 0.677 & 0.250814 \tabularnewline
4 & 0.083225 & 0.5766 & 0.283452 \tabularnewline
5 & 0.000275 & 0.0019 & 0.499244 \tabularnewline
6 & 0.017979 & 0.1246 & 0.450694 \tabularnewline
7 & -0.021013 & -0.1456 & 0.442431 \tabularnewline
8 & 0.13683 & 0.948 & 0.173943 \tabularnewline
9 & -0.082378 & -0.5707 & 0.285421 \tabularnewline
10 & -0.18028 & -1.249 & 0.108858 \tabularnewline
11 & 0.102327 & 0.7089 & 0.240894 \tabularnewline
12 & -0.195802 & -1.3566 & 0.090635 \tabularnewline
13 & -0.166699 & -1.1549 & 0.126919 \tabularnewline
14 & 0.042188 & 0.2923 & 0.385664 \tabularnewline
15 & 0.009964 & 0.069 & 0.472626 \tabularnewline
16 & -0.030756 & -0.2131 & 0.416083 \tabularnewline
17 & -0.01007 & -0.0698 & 0.472334 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29201&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]0.030779[/C][C]0.2132[/C][C]0.416022[/C][/ROW]
[ROW][C]2[/C][C]0.016154[/C][C]0.1119[/C][C]0.455678[/C][/ROW]
[ROW][C]3[/C][C]0.097723[/C][C]0.677[/C][C]0.250814[/C][/ROW]
[ROW][C]4[/C][C]0.083225[/C][C]0.5766[/C][C]0.283452[/C][/ROW]
[ROW][C]5[/C][C]0.000275[/C][C]0.0019[/C][C]0.499244[/C][/ROW]
[ROW][C]6[/C][C]0.017979[/C][C]0.1246[/C][C]0.450694[/C][/ROW]
[ROW][C]7[/C][C]-0.021013[/C][C]-0.1456[/C][C]0.442431[/C][/ROW]
[ROW][C]8[/C][C]0.13683[/C][C]0.948[/C][C]0.173943[/C][/ROW]
[ROW][C]9[/C][C]-0.082378[/C][C]-0.5707[/C][C]0.285421[/C][/ROW]
[ROW][C]10[/C][C]-0.18028[/C][C]-1.249[/C][C]0.108858[/C][/ROW]
[ROW][C]11[/C][C]0.102327[/C][C]0.7089[/C][C]0.240894[/C][/ROW]
[ROW][C]12[/C][C]-0.195802[/C][C]-1.3566[/C][C]0.090635[/C][/ROW]
[ROW][C]13[/C][C]-0.166699[/C][C]-1.1549[/C][C]0.126919[/C][/ROW]
[ROW][C]14[/C][C]0.042188[/C][C]0.2923[/C][C]0.385664[/C][/ROW]
[ROW][C]15[/C][C]0.009964[/C][C]0.069[/C][C]0.472626[/C][/ROW]
[ROW][C]16[/C][C]-0.030756[/C][C]-0.2131[/C][C]0.416083[/C][/ROW]
[ROW][C]17[/C][C]-0.01007[/C][C]-0.0698[/C][C]0.472334[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29201&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29201&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
10.0307790.21320.416022
20.0161540.11190.455678
30.0977230.6770.250814
40.0832250.57660.283452
50.0002750.00190.499244
60.0179790.12460.450694
7-0.021013-0.14560.442431
80.136830.9480.173943
9-0.082378-0.57070.285421
10-0.18028-1.2490.108858
110.1023270.70890.240894
12-0.195802-1.35660.090635
13-0.166699-1.15490.126919
140.0421880.29230.385664
150.0099640.0690.472626
16-0.030756-0.21310.416083
17-0.01007-0.06980.472334



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')