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Author's title

Author

*Unverified author*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Tue, 02 Dec 2008 11:21:15 -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/02/t12282421440beav8l3nga7fwk.htm/, Retrieved Sat, 25 May 2024 13:35:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28212, Retrieved Sat, 25 May 2024 13:35:45 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Severijns Britt

Estimated Impact

160

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

F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD    [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 18:21:15] [7bf28d4d60530086dbc44ae6b648927e] [Current]

Feedback Forum

2008-12-08 18:07:00 [Jessica Alves Pires] [reply] 
We zien dat de differentiatie inderdaad een gunstig effect heeft, maar ik zou toch eerst de VRM hebben berekend om zeker te zijn van welke waarden ik best voor d en D gebruik.

Post a new message

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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	'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28212&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28212&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28212&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	'George Udny Yule' @ 72.249.76.132

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.253407	2.4173	0.008814
2	-0.161071	-1.5365	0.06394
3	-0.276166	-2.6345	0.004952
4	-0.293648	-2.8012	0.003109
5	0.03327	0.3174	0.375844
6	0.171348	1.6346	0.052799
7	0.037319	0.356	0.361333
8	-0.269175	-2.5678	0.005933
9	-0.254036	-2.4233	0.008679
10	-0.146388	-1.3965	0.082987
11	0.262513	2.5042	0.007027
12	0.78641	7.5019	0
13	0.156788	1.4957	0.0691
14	-0.133791	-1.2763	0.102551
15	-0.240878	-2.2978	0.011932
16	-0.235079	-2.2425	0.013679
17	0.025182	0.2402	0.40535
18	0.123027	1.1736	0.121809
19	0.011396	0.1087	0.456837

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.253407 & 2.4173 & 0.008814 \tabularnewline
2 & -0.161071 & -1.5365 & 0.06394 \tabularnewline
3 & -0.276166 & -2.6345 & 0.004952 \tabularnewline
4 & -0.293648 & -2.8012 & 0.003109 \tabularnewline
5 & 0.03327 & 0.3174 & 0.375844 \tabularnewline
6 & 0.171348 & 1.6346 & 0.052799 \tabularnewline
7 & 0.037319 & 0.356 & 0.361333 \tabularnewline
8 & -0.269175 & -2.5678 & 0.005933 \tabularnewline
9 & -0.254036 & -2.4233 & 0.008679 \tabularnewline
10 & -0.146388 & -1.3965 & 0.082987 \tabularnewline
11 & 0.262513 & 2.5042 & 0.007027 \tabularnewline
12 & 0.78641 & 7.5019 & 0 \tabularnewline
13 & 0.156788 & 1.4957 & 0.0691 \tabularnewline
14 & -0.133791 & -1.2763 & 0.102551 \tabularnewline
15 & -0.240878 & -2.2978 & 0.011932 \tabularnewline
16 & -0.235079 & -2.2425 & 0.013679 \tabularnewline
17 & 0.025182 & 0.2402 & 0.40535 \tabularnewline
18 & 0.123027 & 1.1736 & 0.121809 \tabularnewline
19 & 0.011396 & 0.1087 & 0.456837 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28212&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]0.253407[/C][C]2.4173[/C][C]0.008814[/C][/ROW]
[ROW][C]2[/C][C]-0.161071[/C][C]-1.5365[/C][C]0.06394[/C][/ROW]
[ROW][C]3[/C][C]-0.276166[/C][C]-2.6345[/C][C]0.004952[/C][/ROW]
[ROW][C]4[/C][C]-0.293648[/C][C]-2.8012[/C][C]0.003109[/C][/ROW]
[ROW][C]5[/C][C]0.03327[/C][C]0.3174[/C][C]0.375844[/C][/ROW]
[ROW][C]6[/C][C]0.171348[/C][C]1.6346[/C][C]0.052799[/C][/ROW]
[ROW][C]7[/C][C]0.037319[/C][C]0.356[/C][C]0.361333[/C][/ROW]
[ROW][C]8[/C][C]-0.269175[/C][C]-2.5678[/C][C]0.005933[/C][/ROW]
[ROW][C]9[/C][C]-0.254036[/C][C]-2.4233[/C][C]0.008679[/C][/ROW]
[ROW][C]10[/C][C]-0.146388[/C][C]-1.3965[/C][C]0.082987[/C][/ROW]
[ROW][C]11[/C][C]0.262513[/C][C]2.5042[/C][C]0.007027[/C][/ROW]
[ROW][C]12[/C][C]0.78641[/C][C]7.5019[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.156788[/C][C]1.4957[/C][C]0.0691[/C][/ROW]
[ROW][C]14[/C][C]-0.133791[/C][C]-1.2763[/C][C]0.102551[/C][/ROW]
[ROW][C]15[/C][C]-0.240878[/C][C]-2.2978[/C][C]0.011932[/C][/ROW]
[ROW][C]16[/C][C]-0.235079[/C][C]-2.2425[/C][C]0.013679[/C][/ROW]
[ROW][C]17[/C][C]0.025182[/C][C]0.2402[/C][C]0.40535[/C][/ROW]
[ROW][C]18[/C][C]0.123027[/C][C]1.1736[/C][C]0.121809[/C][/ROW]
[ROW][C]19[/C][C]0.011396[/C][C]0.1087[/C][C]0.456837[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28212&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28212&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	0.253407	2.4173	0.008814
2	-0.161071	-1.5365	0.06394
3	-0.276166	-2.6345	0.004952
4	-0.293648	-2.8012	0.003109
5	0.03327	0.3174	0.375844
6	0.171348	1.6346	0.052799
7	0.037319	0.356	0.361333
8	-0.269175	-2.5678	0.005933
9	-0.254036	-2.4233	0.008679
10	-0.146388	-1.3965	0.082987
11	0.262513	2.5042	0.007027
12	0.78641	7.5019	0
13	0.156788	1.4957	0.0691
14	-0.133791	-1.2763	0.102551
15	-0.240878	-2.2978	0.011932
16	-0.235079	-2.2425	0.013679
17	0.025182	0.2402	0.40535
18	0.123027	1.1736	0.121809
19	0.011396	0.1087	0.456837

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.253407	2.4173	0.008814
2	-0.240745	-2.2966	0.011969
3	-0.186622	-1.7803	0.039185
4	-0.236541	-2.2565	0.013218
5	0.096378	0.9194	0.180162
6	0.008163	0.0779	0.469052
7	-0.107097	-1.0216	0.154831
8	-0.337759	-3.222	0.000883
9	-0.113649	-1.0841	0.140583
10	-0.197939	-1.8882	0.031091
11	0.196013	1.8698	0.032361
12	0.665678	6.3502	0
13	-0.210637	-2.0094	0.023731
14	0.124044	1.1833	0.119885
15	0.060246	0.5747	0.283452
16	0.109784	1.0473	0.148873
17	-0.096015	-0.9159	0.181064
18	-0.064109	-0.6116	0.271178
19	-0.012442	-0.1187	0.452893

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.253407 & 2.4173 & 0.008814 \tabularnewline
2 & -0.240745 & -2.2966 & 0.011969 \tabularnewline
3 & -0.186622 & -1.7803 & 0.039185 \tabularnewline
4 & -0.236541 & -2.2565 & 0.013218 \tabularnewline
5 & 0.096378 & 0.9194 & 0.180162 \tabularnewline
6 & 0.008163 & 0.0779 & 0.469052 \tabularnewline
7 & -0.107097 & -1.0216 & 0.154831 \tabularnewline
8 & -0.337759 & -3.222 & 0.000883 \tabularnewline
9 & -0.113649 & -1.0841 & 0.140583 \tabularnewline
10 & -0.197939 & -1.8882 & 0.031091 \tabularnewline
11 & 0.196013 & 1.8698 & 0.032361 \tabularnewline
12 & 0.665678 & 6.3502 & 0 \tabularnewline
13 & -0.210637 & -2.0094 & 0.023731 \tabularnewline
14 & 0.124044 & 1.1833 & 0.119885 \tabularnewline
15 & 0.060246 & 0.5747 & 0.283452 \tabularnewline
16 & 0.109784 & 1.0473 & 0.148873 \tabularnewline
17 & -0.096015 & -0.9159 & 0.181064 \tabularnewline
18 & -0.064109 & -0.6116 & 0.271178 \tabularnewline
19 & -0.012442 & -0.1187 & 0.452893 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28212&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]0.253407[/C][C]2.4173[/C][C]0.008814[/C][/ROW]
[ROW][C]2[/C][C]-0.240745[/C][C]-2.2966[/C][C]0.011969[/C][/ROW]
[ROW][C]3[/C][C]-0.186622[/C][C]-1.7803[/C][C]0.039185[/C][/ROW]
[ROW][C]4[/C][C]-0.236541[/C][C]-2.2565[/C][C]0.013218[/C][/ROW]
[ROW][C]5[/C][C]0.096378[/C][C]0.9194[/C][C]0.180162[/C][/ROW]
[ROW][C]6[/C][C]0.008163[/C][C]0.0779[/C][C]0.469052[/C][/ROW]
[ROW][C]7[/C][C]-0.107097[/C][C]-1.0216[/C][C]0.154831[/C][/ROW]
[ROW][C]8[/C][C]-0.337759[/C][C]-3.222[/C][C]0.000883[/C][/ROW]
[ROW][C]9[/C][C]-0.113649[/C][C]-1.0841[/C][C]0.140583[/C][/ROW]
[ROW][C]10[/C][C]-0.197939[/C][C]-1.8882[/C][C]0.031091[/C][/ROW]
[ROW][C]11[/C][C]0.196013[/C][C]1.8698[/C][C]0.032361[/C][/ROW]
[ROW][C]12[/C][C]0.665678[/C][C]6.3502[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.210637[/C][C]-2.0094[/C][C]0.023731[/C][/ROW]
[ROW][C]14[/C][C]0.124044[/C][C]1.1833[/C][C]0.119885[/C][/ROW]
[ROW][C]15[/C][C]0.060246[/C][C]0.5747[/C][C]0.283452[/C][/ROW]
[ROW][C]16[/C][C]0.109784[/C][C]1.0473[/C][C]0.148873[/C][/ROW]
[ROW][C]17[/C][C]-0.096015[/C][C]-0.9159[/C][C]0.181064[/C][/ROW]
[ROW][C]18[/C][C]-0.064109[/C][C]-0.6116[/C][C]0.271178[/C][/ROW]
[ROW][C]19[/C][C]-0.012442[/C][C]-0.1187[/C][C]0.452893[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28212&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28212&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	0.253407	2.4173	0.008814
2	-0.240745	-2.2966	0.011969
3	-0.186622	-1.7803	0.039185
4	-0.236541	-2.2565	0.013218
5	0.096378	0.9194	0.180162
6	0.008163	0.0779	0.469052
7	-0.107097	-1.0216	0.154831
8	-0.337759	-3.222	0.000883
9	-0.113649	-1.0841	0.140583
10	-0.197939	-1.8882	0.031091
11	0.196013	1.8698	0.032361
12	0.665678	6.3502	0
13	-0.210637	-2.0094	0.023731
14	0.124044	1.1833	0.119885
15	0.060246	0.5747	0.283452
16	0.109784	1.0473	0.148873
17	-0.096015	-0.9159	0.181064
18	-0.064109	-0.6116	0.271178
19	-0.012442	-0.1187	0.452893

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

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

Parameters (R input):

par1 = Default ; par2 = 1 ; 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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Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code