Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Tue, 16 Dec 2014 14:39:00 +0000

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/2014/Dec/16/t1418740834mm5ozeek2na0wbi.htm/, Retrieved Thu, 16 May 2024 13:42:53 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269639, Retrieved Thu, 16 May 2024 13:42:53 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Tessa Bertels

Estimated Impact

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

-     [(Partial) Autocorrelation Function] [] [2014-10-23 19:03:11] [e7e8e094e7ba7df261235586ec2da9e3]
- R P     [(Partial) Autocorrelation Function] [] [2014-12-16 14:39:00] [a4941b106213b8203102126a01fbfecf] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

1.38
1.96
1.36
1.24
1.35
1.23
1.09
1.08
1.33
1.35
1.38
1.5
1.47
2.09
1.52
1.29
1.52
1.27
1.35
1.29
1.41
1.39
1.45
1.53
1.45
2.11
1.53
1.38
1.54
1.35
1.29
1.33
1.47
1.47
1.54
1.59
1.5
2
1.51
1.4
1.62
1.44
1.29
1.28
1.4
1.39
1.46
1.49
1.45
2.05
1.59
1.42
1.73
1.39
1.23
1.37
1.51
1.47
1.5
1.54
1.54
2.15
1.62
1.4
1.65
1.49
1.45
1.45
1.51
1.48
1.56
1.57
1.57
2.28
1.7
1.56
1.8
1.56
1.51
1.46
1.51
1.55
1.57
1.64
1.58
2.16
1.77
1.54
1.64
1.53
1.49
1.43
1.52
1.56
1.59
1.64

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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269639&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269639&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269639&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	'Gertrude Mary Cox' @ cox.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.343775	3.3683	0.000545
2	0.190479	1.8663	0.032525
3	0.287437	2.8163	0.002948
4	-0.020062	-0.1966	0.422291
5	-0.136193	-1.3344	0.092612
6	-0.257414	-2.5221	0.006655
7	-0.165184	-1.6185	0.054421
8	-0.078583	-0.77	0.221609
9	0.195397	1.9145	0.029268
10	0.093377	0.9149	0.181268
11	0.184708	1.8098	0.036731
12	0.738646	7.2372	0
13	0.207064	2.0288	0.022624
14	0.093851	0.9196	0.180056
15	0.209053	2.0483	0.021631
16	-0.064972	-0.6366	0.262953
17	-0.137726	-1.3494	0.090186
18	-0.253051	-2.4794	0.007452
19	-0.207406	-2.0322	0.02245

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.343775 & 3.3683 & 0.000545 \tabularnewline
2 & 0.190479 & 1.8663 & 0.032525 \tabularnewline
3 & 0.287437 & 2.8163 & 0.002948 \tabularnewline
4 & -0.020062 & -0.1966 & 0.422291 \tabularnewline
5 & -0.136193 & -1.3344 & 0.092612 \tabularnewline
6 & -0.257414 & -2.5221 & 0.006655 \tabularnewline
7 & -0.165184 & -1.6185 & 0.054421 \tabularnewline
8 & -0.078583 & -0.77 & 0.221609 \tabularnewline
9 & 0.195397 & 1.9145 & 0.029268 \tabularnewline
10 & 0.093377 & 0.9149 & 0.181268 \tabularnewline
11 & 0.184708 & 1.8098 & 0.036731 \tabularnewline
12 & 0.738646 & 7.2372 & 0 \tabularnewline
13 & 0.207064 & 2.0288 & 0.022624 \tabularnewline
14 & 0.093851 & 0.9196 & 0.180056 \tabularnewline
15 & 0.209053 & 2.0483 & 0.021631 \tabularnewline
16 & -0.064972 & -0.6366 & 0.262953 \tabularnewline
17 & -0.137726 & -1.3494 & 0.090186 \tabularnewline
18 & -0.253051 & -2.4794 & 0.007452 \tabularnewline
19 & -0.207406 & -2.0322 & 0.02245 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269639&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]0.343775[/C][C]3.3683[/C][C]0.000545[/C][/ROW]
[ROW][C]2[/C][C]0.190479[/C][C]1.8663[/C][C]0.032525[/C][/ROW]
[ROW][C]3[/C][C]0.287437[/C][C]2.8163[/C][C]0.002948[/C][/ROW]
[ROW][C]4[/C][C]-0.020062[/C][C]-0.1966[/C][C]0.422291[/C][/ROW]
[ROW][C]5[/C][C]-0.136193[/C][C]-1.3344[/C][C]0.092612[/C][/ROW]
[ROW][C]6[/C][C]-0.257414[/C][C]-2.5221[/C][C]0.006655[/C][/ROW]
[ROW][C]7[/C][C]-0.165184[/C][C]-1.6185[/C][C]0.054421[/C][/ROW]
[ROW][C]8[/C][C]-0.078583[/C][C]-0.77[/C][C]0.221609[/C][/ROW]
[ROW][C]9[/C][C]0.195397[/C][C]1.9145[/C][C]0.029268[/C][/ROW]
[ROW][C]10[/C][C]0.093377[/C][C]0.9149[/C][C]0.181268[/C][/ROW]
[ROW][C]11[/C][C]0.184708[/C][C]1.8098[/C][C]0.036731[/C][/ROW]
[ROW][C]12[/C][C]0.738646[/C][C]7.2372[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.207064[/C][C]2.0288[/C][C]0.022624[/C][/ROW]
[ROW][C]14[/C][C]0.093851[/C][C]0.9196[/C][C]0.180056[/C][/ROW]
[ROW][C]15[/C][C]0.209053[/C][C]2.0483[/C][C]0.021631[/C][/ROW]
[ROW][C]16[/C][C]-0.064972[/C][C]-0.6366[/C][C]0.262953[/C][/ROW]
[ROW][C]17[/C][C]-0.137726[/C][C]-1.3494[/C][C]0.090186[/C][/ROW]
[ROW][C]18[/C][C]-0.253051[/C][C]-2.4794[/C][C]0.007452[/C][/ROW]
[ROW][C]19[/C][C]-0.207406[/C][C]-2.0322[/C][C]0.02245[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269639&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269639&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	0.343775	3.3683	0.000545
2	0.190479	1.8663	0.032525
3	0.287437	2.8163	0.002948
4	-0.020062	-0.1966	0.422291
5	-0.136193	-1.3344	0.092612
6	-0.257414	-2.5221	0.006655
7	-0.165184	-1.6185	0.054421
8	-0.078583	-0.77	0.221609
9	0.195397	1.9145	0.029268
10	0.093377	0.9149	0.181268
11	0.184708	1.8098	0.036731
12	0.738646	7.2372	0
13	0.207064	2.0288	0.022624
14	0.093851	0.9196	0.180056
15	0.209053	2.0483	0.021631
16	-0.064972	-0.6366	0.262953
17	-0.137726	-1.3494	0.090186
18	-0.253051	-2.4794	0.007452
19	-0.207406	-2.0322	0.02245

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.343775	3.3683	0.000545
2	0.081987	0.8033	0.21189
3	0.227355	2.2276	0.014121
4	-0.223359	-2.1885	0.015531
5	-0.141884	-1.3902	0.083845
6	-0.279697	-2.7405	0.003658
7	0.093007	0.9113	0.182215
8	0.092552	0.9068	0.183386
9	0.492978	4.8302	3e-06
10	-0.152832	-1.4974	0.06878
11	0.116889	1.1453	0.127472
12	0.570241	5.5872	0
13	-0.397161	-3.8914	9.2e-05
14	-0.035762	-0.3504	0.363407
15	-0.064898	-0.6359	0.263187
16	-0.000874	-0.0086	0.496592
17	0.064559	0.6325	0.264266
18	-0.032912	-0.3225	0.373898
19	-0.098681	-0.9669	0.168018

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.343775 & 3.3683 & 0.000545 \tabularnewline
2 & 0.081987 & 0.8033 & 0.21189 \tabularnewline
3 & 0.227355 & 2.2276 & 0.014121 \tabularnewline
4 & -0.223359 & -2.1885 & 0.015531 \tabularnewline
5 & -0.141884 & -1.3902 & 0.083845 \tabularnewline
6 & -0.279697 & -2.7405 & 0.003658 \tabularnewline
7 & 0.093007 & 0.9113 & 0.182215 \tabularnewline
8 & 0.092552 & 0.9068 & 0.183386 \tabularnewline
9 & 0.492978 & 4.8302 & 3e-06 \tabularnewline
10 & -0.152832 & -1.4974 & 0.06878 \tabularnewline
11 & 0.116889 & 1.1453 & 0.127472 \tabularnewline
12 & 0.570241 & 5.5872 & 0 \tabularnewline
13 & -0.397161 & -3.8914 & 9.2e-05 \tabularnewline
14 & -0.035762 & -0.3504 & 0.363407 \tabularnewline
15 & -0.064898 & -0.6359 & 0.263187 \tabularnewline
16 & -0.000874 & -0.0086 & 0.496592 \tabularnewline
17 & 0.064559 & 0.6325 & 0.264266 \tabularnewline
18 & -0.032912 & -0.3225 & 0.373898 \tabularnewline
19 & -0.098681 & -0.9669 & 0.168018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269639&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]0.343775[/C][C]3.3683[/C][C]0.000545[/C][/ROW]
[ROW][C]2[/C][C]0.081987[/C][C]0.8033[/C][C]0.21189[/C][/ROW]
[ROW][C]3[/C][C]0.227355[/C][C]2.2276[/C][C]0.014121[/C][/ROW]
[ROW][C]4[/C][C]-0.223359[/C][C]-2.1885[/C][C]0.015531[/C][/ROW]
[ROW][C]5[/C][C]-0.141884[/C][C]-1.3902[/C][C]0.083845[/C][/ROW]
[ROW][C]6[/C][C]-0.279697[/C][C]-2.7405[/C][C]0.003658[/C][/ROW]
[ROW][C]7[/C][C]0.093007[/C][C]0.9113[/C][C]0.182215[/C][/ROW]
[ROW][C]8[/C][C]0.092552[/C][C]0.9068[/C][C]0.183386[/C][/ROW]
[ROW][C]9[/C][C]0.492978[/C][C]4.8302[/C][C]3e-06[/C][/ROW]
[ROW][C]10[/C][C]-0.152832[/C][C]-1.4974[/C][C]0.06878[/C][/ROW]
[ROW][C]11[/C][C]0.116889[/C][C]1.1453[/C][C]0.127472[/C][/ROW]
[ROW][C]12[/C][C]0.570241[/C][C]5.5872[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.397161[/C][C]-3.8914[/C][C]9.2e-05[/C][/ROW]
[ROW][C]14[/C][C]-0.035762[/C][C]-0.3504[/C][C]0.363407[/C][/ROW]
[ROW][C]15[/C][C]-0.064898[/C][C]-0.6359[/C][C]0.263187[/C][/ROW]
[ROW][C]16[/C][C]-0.000874[/C][C]-0.0086[/C][C]0.496592[/C][/ROW]
[ROW][C]17[/C][C]0.064559[/C][C]0.6325[/C][C]0.264266[/C][/ROW]
[ROW][C]18[/C][C]-0.032912[/C][C]-0.3225[/C][C]0.373898[/C][/ROW]
[ROW][C]19[/C][C]-0.098681[/C][C]-0.9669[/C][C]0.168018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269639&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269639&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	0.343775	3.3683	0.000545
2	0.081987	0.8033	0.21189
3	0.227355	2.2276	0.014121
4	-0.223359	-2.1885	0.015531
5	-0.141884	-1.3902	0.083845
6	-0.279697	-2.7405	0.003658
7	0.093007	0.9113	0.182215
8	0.092552	0.9068	0.183386
9	0.492978	4.8302	3e-06
10	-0.152832	-1.4974	0.06878
11	0.116889	1.1453	0.127472
12	0.570241	5.5872	0
13	-0.397161	-3.8914	9.2e-05
14	-0.035762	-0.3504	0.363407
15	-0.064898	-0.6359	0.263187
16	-0.000874	-0.0086	0.496592
17	0.064559	0.6325	0.264266
18	-0.032912	-0.3225	0.373898
19	-0.098681	-0.9669	0.168018

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 48 ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

par1 = 48 ; par2 = 0.0 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ;

R code (references can be found in the software module):

par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '0'
par2 <- '0.0'
par1 <- 'Default'
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code