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*Unverified author*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Wed, 10 Dec 2008 01:04:48 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Dec/10/t1228896310h88e96l4lnb966a.htm/, Retrieved Sun, 19 May 2024 07:10:49 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31873, Retrieved Sun, 19 May 2024 07:10:49 +0000

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Estimated Impact

211

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F       [(Partial) Autocorrelation Function] [] [2008-12-10 08:04:48] [d41d8cd98f00b204e9800998ecf8427e] [Current]

Feedback Forum

2008-12-14 16:06:46 [Steven Vanhooreweghe] [reply] 
in de eerste stap heb je gezegd dat je lambda niet ging gebruiken. Nu heb e dat toch gedaan en je model blijkt niet echt goed te zijn. Ik heb het gereproduceerd en lambda=1 ingevuld. Je bekomt zo een beter model.

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=31873&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=31873&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31873&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 Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.061447	0.5989	0.27533
2	-0.119346	-1.1632	0.123822
3	0.105236	1.0257	0.153815
4	0.083904	0.8178	0.207761
5	-0.261046	-2.5444	0.00628
6	-0.113216	-1.1035	0.136299
7	0.122322	1.1922	0.118067
8	0.00367	0.0358	0.485772
9	0.023305	0.2272	0.410397
10	0.017252	0.1682	0.433411
11	0.139868	1.3633	0.088011
12	-0.078161	-0.7618	0.224027
13	-0.167706	-1.6346	0.052722
14	-0.080373	-0.7834	0.217677
15	-0.001102	-0.0107	0.495728
16	-0.146496	-1.4279	0.078305
17	-0.075476	-0.7357	0.231878
18	0.104243	1.016	0.156096
19	0.07508	0.7318	0.23305

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.061447 & 0.5989 & 0.27533 \tabularnewline
2 & -0.119346 & -1.1632 & 0.123822 \tabularnewline
3 & 0.105236 & 1.0257 & 0.153815 \tabularnewline
4 & 0.083904 & 0.8178 & 0.207761 \tabularnewline
5 & -0.261046 & -2.5444 & 0.00628 \tabularnewline
6 & -0.113216 & -1.1035 & 0.136299 \tabularnewline
7 & 0.122322 & 1.1922 & 0.118067 \tabularnewline
8 & 0.00367 & 0.0358 & 0.485772 \tabularnewline
9 & 0.023305 & 0.2272 & 0.410397 \tabularnewline
10 & 0.017252 & 0.1682 & 0.433411 \tabularnewline
11 & 0.139868 & 1.3633 & 0.088011 \tabularnewline
12 & -0.078161 & -0.7618 & 0.224027 \tabularnewline
13 & -0.167706 & -1.6346 & 0.052722 \tabularnewline
14 & -0.080373 & -0.7834 & 0.217677 \tabularnewline
15 & -0.001102 & -0.0107 & 0.495728 \tabularnewline
16 & -0.146496 & -1.4279 & 0.078305 \tabularnewline
17 & -0.075476 & -0.7357 & 0.231878 \tabularnewline
18 & 0.104243 & 1.016 & 0.156096 \tabularnewline
19 & 0.07508 & 0.7318 & 0.23305 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31873&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]0.061447[/C][C]0.5989[/C][C]0.27533[/C][/ROW]
[ROW][C]2[/C][C]-0.119346[/C][C]-1.1632[/C][C]0.123822[/C][/ROW]
[ROW][C]3[/C][C]0.105236[/C][C]1.0257[/C][C]0.153815[/C][/ROW]
[ROW][C]4[/C][C]0.083904[/C][C]0.8178[/C][C]0.207761[/C][/ROW]
[ROW][C]5[/C][C]-0.261046[/C][C]-2.5444[/C][C]0.00628[/C][/ROW]
[ROW][C]6[/C][C]-0.113216[/C][C]-1.1035[/C][C]0.136299[/C][/ROW]
[ROW][C]7[/C][C]0.122322[/C][C]1.1922[/C][C]0.118067[/C][/ROW]
[ROW][C]8[/C][C]0.00367[/C][C]0.0358[/C][C]0.485772[/C][/ROW]
[ROW][C]9[/C][C]0.023305[/C][C]0.2272[/C][C]0.410397[/C][/ROW]
[ROW][C]10[/C][C]0.017252[/C][C]0.1682[/C][C]0.433411[/C][/ROW]
[ROW][C]11[/C][C]0.139868[/C][C]1.3633[/C][C]0.088011[/C][/ROW]
[ROW][C]12[/C][C]-0.078161[/C][C]-0.7618[/C][C]0.224027[/C][/ROW]
[ROW][C]13[/C][C]-0.167706[/C][C]-1.6346[/C][C]0.052722[/C][/ROW]
[ROW][C]14[/C][C]-0.080373[/C][C]-0.7834[/C][C]0.217677[/C][/ROW]
[ROW][C]15[/C][C]-0.001102[/C][C]-0.0107[/C][C]0.495728[/C][/ROW]
[ROW][C]16[/C][C]-0.146496[/C][C]-1.4279[/C][C]0.078305[/C][/ROW]
[ROW][C]17[/C][C]-0.075476[/C][C]-0.7357[/C][C]0.231878[/C][/ROW]
[ROW][C]18[/C][C]0.104243[/C][C]1.016[/C][C]0.156096[/C][/ROW]
[ROW][C]19[/C][C]0.07508[/C][C]0.7318[/C][C]0.23305[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31873&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31873&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 k	ACF(k)	T-STAT	P-value
1	0.061447	0.5989	0.27533
2	-0.119346	-1.1632	0.123822
3	0.105236	1.0257	0.153815
4	0.083904	0.8178	0.207761
5	-0.261046	-2.5444	0.00628
6	-0.113216	-1.1035	0.136299
7	0.122322	1.1922	0.118067
8	0.00367	0.0358	0.485772
9	0.023305	0.2272	0.410397
10	0.017252	0.1682	0.433411
11	0.139868	1.3633	0.088011
12	-0.078161	-0.7618	0.224027
13	-0.167706	-1.6346	0.052722
14	-0.080373	-0.7834	0.217677
15	-0.001102	-0.0107	0.495728
16	-0.146496	-1.4279	0.078305
17	-0.075476	-0.7357	0.231878
18	0.104243	1.016	0.156096
19	0.07508	0.7318	0.23305

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.061447	0.5989	0.27533
2	-0.123589	-1.2046	0.115677
3	0.123414	1.2029	0.116004
4	0.053498	0.5214	0.301638
5	-0.252779	-2.4638	0.007773
6	-0.073592	-0.7173	0.237479
7	0.075243	0.7334	0.232568
8	0.017266	0.1683	0.433359
9	0.104747	1.0209	0.154936
10	-0.065935	-0.6427	0.261
11	0.100793	0.9824	0.164198
12	-0.083794	-0.8167	0.208065
13	-0.138837	-1.3532	0.089599
14	-0.072598	-0.7076	0.240463
15	-0.018924	-0.1845	0.427026
16	-0.090827	-0.8853	0.189124
17	-0.037811	-0.3685	0.356647
18	-0.002959	-0.0288	0.488528
19	0.045632	0.4448	0.328749

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.061447 & 0.5989 & 0.27533 \tabularnewline
2 & -0.123589 & -1.2046 & 0.115677 \tabularnewline
3 & 0.123414 & 1.2029 & 0.116004 \tabularnewline
4 & 0.053498 & 0.5214 & 0.301638 \tabularnewline
5 & -0.252779 & -2.4638 & 0.007773 \tabularnewline
6 & -0.073592 & -0.7173 & 0.237479 \tabularnewline
7 & 0.075243 & 0.7334 & 0.232568 \tabularnewline
8 & 0.017266 & 0.1683 & 0.433359 \tabularnewline
9 & 0.104747 & 1.0209 & 0.154936 \tabularnewline
10 & -0.065935 & -0.6427 & 0.261 \tabularnewline
11 & 0.100793 & 0.9824 & 0.164198 \tabularnewline
12 & -0.083794 & -0.8167 & 0.208065 \tabularnewline
13 & -0.138837 & -1.3532 & 0.089599 \tabularnewline
14 & -0.072598 & -0.7076 & 0.240463 \tabularnewline
15 & -0.018924 & -0.1845 & 0.427026 \tabularnewline
16 & -0.090827 & -0.8853 & 0.189124 \tabularnewline
17 & -0.037811 & -0.3685 & 0.356647 \tabularnewline
18 & -0.002959 & -0.0288 & 0.488528 \tabularnewline
19 & 0.045632 & 0.4448 & 0.328749 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31873&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]0.061447[/C][C]0.5989[/C][C]0.27533[/C][/ROW]
[ROW][C]2[/C][C]-0.123589[/C][C]-1.2046[/C][C]0.115677[/C][/ROW]
[ROW][C]3[/C][C]0.123414[/C][C]1.2029[/C][C]0.116004[/C][/ROW]
[ROW][C]4[/C][C]0.053498[/C][C]0.5214[/C][C]0.301638[/C][/ROW]
[ROW][C]5[/C][C]-0.252779[/C][C]-2.4638[/C][C]0.007773[/C][/ROW]
[ROW][C]6[/C][C]-0.073592[/C][C]-0.7173[/C][C]0.237479[/C][/ROW]
[ROW][C]7[/C][C]0.075243[/C][C]0.7334[/C][C]0.232568[/C][/ROW]
[ROW][C]8[/C][C]0.017266[/C][C]0.1683[/C][C]0.433359[/C][/ROW]
[ROW][C]9[/C][C]0.104747[/C][C]1.0209[/C][C]0.154936[/C][/ROW]
[ROW][C]10[/C][C]-0.065935[/C][C]-0.6427[/C][C]0.261[/C][/ROW]
[ROW][C]11[/C][C]0.100793[/C][C]0.9824[/C][C]0.164198[/C][/ROW]
[ROW][C]12[/C][C]-0.083794[/C][C]-0.8167[/C][C]0.208065[/C][/ROW]
[ROW][C]13[/C][C]-0.138837[/C][C]-1.3532[/C][C]0.089599[/C][/ROW]
[ROW][C]14[/C][C]-0.072598[/C][C]-0.7076[/C][C]0.240463[/C][/ROW]
[ROW][C]15[/C][C]-0.018924[/C][C]-0.1845[/C][C]0.427026[/C][/ROW]
[ROW][C]16[/C][C]-0.090827[/C][C]-0.8853[/C][C]0.189124[/C][/ROW]
[ROW][C]17[/C][C]-0.037811[/C][C]-0.3685[/C][C]0.356647[/C][/ROW]
[ROW][C]18[/C][C]-0.002959[/C][C]-0.0288[/C][C]0.488528[/C][/ROW]
[ROW][C]19[/C][C]0.045632[/C][C]0.4448[/C][C]0.328749[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31873&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31873&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 k	PACF(k)	T-STAT	P-value
1	0.061447	0.5989	0.27533
2	-0.123589	-1.2046	0.115677
3	0.123414	1.2029	0.116004
4	0.053498	0.5214	0.301638
5	-0.252779	-2.4638	0.007773
6	-0.073592	-0.7173	0.237479
7	0.075243	0.7334	0.232568
8	0.017266	0.1683	0.433359
9	0.104747	1.0209	0.154936
10	-0.065935	-0.6427	0.261
11	0.100793	0.9824	0.164198
12	-0.083794	-0.8167	0.208065
13	-0.138837	-1.3532	0.089599
14	-0.072598	-0.7076	0.240463
15	-0.018924	-0.1845	0.427026
16	-0.090827	-0.8853	0.189124
17	-0.037811	-0.3685	0.356647
18	-0.002959	-0.0288	0.488528
19	0.045632	0.4448	0.328749

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = -0.5 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;

Parameters (R input):

par1 = Default ; par2 = -0.5 ; par3 = 1 ; par4 = 0 ; 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')

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