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Author

*The author of this computation has been verified*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Thu, 18 Dec 2008 11:26:49 -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/18/t1229624837kxvjllmiq7cmupi.htm/, Retrieved Sat, 11 May 2024 04:31:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34916, Retrieved Sat, 11 May 2024 04:31:51 +0000

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No (this computation is public)

User-defined keywords

acf

Estimated Impact

190

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP   [Standard Deviation-Mean Plot] [q1] [2008-12-08 12:37:39] [3ffd109c9e040b1ae7e5dbe576d4698c]
F    D    [Standard Deviation-Mean Plot] [SMP] [2008-12-08 12:41:29] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM        [Variance Reduction Matrix] [VRM] [2008-12-08 13:10:17] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM          [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:14:12] [3ffd109c9e040b1ae7e5dbe576d4698c]
F               [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:17:45] [3ffd109c9e040b1ae7e5dbe576d4698c]
- RM              [Spectral Analysis] [spectraal] [2008-12-08 13:23:27] [3ffd109c9e040b1ae7e5dbe576d4698c]
F RM                [(Partial) Autocorrelation Function] [ACF] [2008-12-08 13:40:41] [3ffd109c9e040b1ae7e5dbe576d4698c]
- R P                   [(Partial) Autocorrelation Function] [acf] [2008-12-18 18:26:49] [962e6c9020896982bc8283b8971710a9] [Current]

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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=34916&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=34916&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34916&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	-0.17288	-1.1978	0.118448
2	-0.039533	-0.2739	0.392672
3	-0.046214	-0.3202	0.37511
4	0.078875	0.5465	0.293639
5	-0.1397	-0.9679	0.16898
6	0.152149	1.0541	0.148552
7	0.028761	0.1993	0.421451
8	-0.018547	-0.1285	0.449146
9	0.037996	0.2632	0.396743
10	-0.107249	-0.743	0.230539
11	0.328488	2.2758	0.013679
12	-0.311691	-2.1595	0.01792
13	-0.092808	-0.643	0.261644
14	0.054879	0.3802	0.352732
15	0.025463	0.1764	0.430355
16	-0.282905	-1.96	0.027906
17	0.083079	0.5756	0.283791

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.17288 & -1.1978 & 0.118448 \tabularnewline
2 & -0.039533 & -0.2739 & 0.392672 \tabularnewline
3 & -0.046214 & -0.3202 & 0.37511 \tabularnewline
4 & 0.078875 & 0.5465 & 0.293639 \tabularnewline
5 & -0.1397 & -0.9679 & 0.16898 \tabularnewline
6 & 0.152149 & 1.0541 & 0.148552 \tabularnewline
7 & 0.028761 & 0.1993 & 0.421451 \tabularnewline
8 & -0.018547 & -0.1285 & 0.449146 \tabularnewline
9 & 0.037996 & 0.2632 & 0.396743 \tabularnewline
10 & -0.107249 & -0.743 & 0.230539 \tabularnewline
11 & 0.328488 & 2.2758 & 0.013679 \tabularnewline
12 & -0.311691 & -2.1595 & 0.01792 \tabularnewline
13 & -0.092808 & -0.643 & 0.261644 \tabularnewline
14 & 0.054879 & 0.3802 & 0.352732 \tabularnewline
15 & 0.025463 & 0.1764 & 0.430355 \tabularnewline
16 & -0.282905 & -1.96 & 0.027906 \tabularnewline
17 & 0.083079 & 0.5756 & 0.283791 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34916&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]-0.17288[/C][C]-1.1978[/C][C]0.118448[/C][/ROW]
[ROW][C]2[/C][C]-0.039533[/C][C]-0.2739[/C][C]0.392672[/C][/ROW]
[ROW][C]3[/C][C]-0.046214[/C][C]-0.3202[/C][C]0.37511[/C][/ROW]
[ROW][C]4[/C][C]0.078875[/C][C]0.5465[/C][C]0.293639[/C][/ROW]
[ROW][C]5[/C][C]-0.1397[/C][C]-0.9679[/C][C]0.16898[/C][/ROW]
[ROW][C]6[/C][C]0.152149[/C][C]1.0541[/C][C]0.148552[/C][/ROW]
[ROW][C]7[/C][C]0.028761[/C][C]0.1993[/C][C]0.421451[/C][/ROW]
[ROW][C]8[/C][C]-0.018547[/C][C]-0.1285[/C][C]0.449146[/C][/ROW]
[ROW][C]9[/C][C]0.037996[/C][C]0.2632[/C][C]0.396743[/C][/ROW]
[ROW][C]10[/C][C]-0.107249[/C][C]-0.743[/C][C]0.230539[/C][/ROW]
[ROW][C]11[/C][C]0.328488[/C][C]2.2758[/C][C]0.013679[/C][/ROW]
[ROW][C]12[/C][C]-0.311691[/C][C]-2.1595[/C][C]0.01792[/C][/ROW]
[ROW][C]13[/C][C]-0.092808[/C][C]-0.643[/C][C]0.261644[/C][/ROW]
[ROW][C]14[/C][C]0.054879[/C][C]0.3802[/C][C]0.352732[/C][/ROW]
[ROW][C]15[/C][C]0.025463[/C][C]0.1764[/C][C]0.430355[/C][/ROW]
[ROW][C]16[/C][C]-0.282905[/C][C]-1.96[/C][C]0.027906[/C][/ROW]
[ROW][C]17[/C][C]0.083079[/C][C]0.5756[/C][C]0.283791[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34916&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34916&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	-0.17288	-1.1978	0.118448
2	-0.039533	-0.2739	0.392672
3	-0.046214	-0.3202	0.37511
4	0.078875	0.5465	0.293639
5	-0.1397	-0.9679	0.16898
6	0.152149	1.0541	0.148552
7	0.028761	0.1993	0.421451
8	-0.018547	-0.1285	0.449146
9	0.037996	0.2632	0.396743
10	-0.107249	-0.743	0.230539
11	0.328488	2.2758	0.013679
12	-0.311691	-2.1595	0.01792
13	-0.092808	-0.643	0.261644
14	0.054879	0.3802	0.352732
15	0.025463	0.1764	0.430355
16	-0.282905	-1.96	0.027906
17	0.083079	0.5756	0.283791

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.17288	-1.1978	0.118448
2	-0.071559	-0.4958	0.311158
3	-0.068289	-0.4731	0.319136
4	0.057205	0.3963	0.346811
5	-0.126434	-0.876	0.192708
6	0.117103	0.8113	0.210596
7	0.068746	0.4763	0.318017
8	-0.001143	-0.0079	0.496857
9	0.075368	0.5222	0.301979
10	-0.126812	-0.8786	0.192003
11	0.357378	2.476	0.008433
12	-0.30076	-2.0837	0.021266
13	-0.15643	-1.0838	0.141938
14	0.073316	0.508	0.306907
15	-0.157054	-1.0881	0.140991
16	-0.169926	-1.1773	0.122444
17	-0.183492	-1.2713	0.104879

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.17288 & -1.1978 & 0.118448 \tabularnewline
2 & -0.071559 & -0.4958 & 0.311158 \tabularnewline
3 & -0.068289 & -0.4731 & 0.319136 \tabularnewline
4 & 0.057205 & 0.3963 & 0.346811 \tabularnewline
5 & -0.126434 & -0.876 & 0.192708 \tabularnewline
6 & 0.117103 & 0.8113 & 0.210596 \tabularnewline
7 & 0.068746 & 0.4763 & 0.318017 \tabularnewline
8 & -0.001143 & -0.0079 & 0.496857 \tabularnewline
9 & 0.075368 & 0.5222 & 0.301979 \tabularnewline
10 & -0.126812 & -0.8786 & 0.192003 \tabularnewline
11 & 0.357378 & 2.476 & 0.008433 \tabularnewline
12 & -0.30076 & -2.0837 & 0.021266 \tabularnewline
13 & -0.15643 & -1.0838 & 0.141938 \tabularnewline
14 & 0.073316 & 0.508 & 0.306907 \tabularnewline
15 & -0.157054 & -1.0881 & 0.140991 \tabularnewline
16 & -0.169926 & -1.1773 & 0.122444 \tabularnewline
17 & -0.183492 & -1.2713 & 0.104879 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34916&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]-0.17288[/C][C]-1.1978[/C][C]0.118448[/C][/ROW]
[ROW][C]2[/C][C]-0.071559[/C][C]-0.4958[/C][C]0.311158[/C][/ROW]
[ROW][C]3[/C][C]-0.068289[/C][C]-0.4731[/C][C]0.319136[/C][/ROW]
[ROW][C]4[/C][C]0.057205[/C][C]0.3963[/C][C]0.346811[/C][/ROW]
[ROW][C]5[/C][C]-0.126434[/C][C]-0.876[/C][C]0.192708[/C][/ROW]
[ROW][C]6[/C][C]0.117103[/C][C]0.8113[/C][C]0.210596[/C][/ROW]
[ROW][C]7[/C][C]0.068746[/C][C]0.4763[/C][C]0.318017[/C][/ROW]
[ROW][C]8[/C][C]-0.001143[/C][C]-0.0079[/C][C]0.496857[/C][/ROW]
[ROW][C]9[/C][C]0.075368[/C][C]0.5222[/C][C]0.301979[/C][/ROW]
[ROW][C]10[/C][C]-0.126812[/C][C]-0.8786[/C][C]0.192003[/C][/ROW]
[ROW][C]11[/C][C]0.357378[/C][C]2.476[/C][C]0.008433[/C][/ROW]
[ROW][C]12[/C][C]-0.30076[/C][C]-2.0837[/C][C]0.021266[/C][/ROW]
[ROW][C]13[/C][C]-0.15643[/C][C]-1.0838[/C][C]0.141938[/C][/ROW]
[ROW][C]14[/C][C]0.073316[/C][C]0.508[/C][C]0.306907[/C][/ROW]
[ROW][C]15[/C][C]-0.157054[/C][C]-1.0881[/C][C]0.140991[/C][/ROW]
[ROW][C]16[/C][C]-0.169926[/C][C]-1.1773[/C][C]0.122444[/C][/ROW]
[ROW][C]17[/C][C]-0.183492[/C][C]-1.2713[/C][C]0.104879[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34916&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34916&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	-0.17288	-1.1978	0.118448
2	-0.071559	-0.4958	0.311158
3	-0.068289	-0.4731	0.319136
4	0.057205	0.3963	0.346811
5	-0.126434	-0.876	0.192708
6	0.117103	0.8113	0.210596
7	0.068746	0.4763	0.318017
8	-0.001143	-0.0079	0.496857
9	0.075368	0.5222	0.301979
10	-0.126812	-0.8786	0.192003
11	0.357378	2.476	0.008433
12	-0.30076	-2.0837	0.021266
13	-0.15643	-1.0838	0.141938
14	0.073316	0.508	0.306907
15	-0.157054	-1.0881	0.140991
16	-0.169926	-1.1773	0.122444
17	-0.183492	-1.2713	0.104879

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 0.0 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;

Parameters (R input):

par1 = Default ; par2 = 0.0 ; 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')

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