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

Thu, 23 Oct 2014 12:38:02 +0100

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/Oct/23/t1414064345nizv8srh5y7jowu.htm/, Retrieved Fri, 10 May 2024 09:51:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=245642, Retrieved Fri, 10 May 2024 09:51:23 +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

Estimated Impact

112

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

-       [(Partial) Autocorrelation Function] [] [2014-10-23 11:38:02] [fced41568b3cc41e6659ad201d611503] [Current]
- R PD    [(Partial) Autocorrelation Function] [] [2014-12-20 10:10:12] [46d78fa4bef23992fc20db72a2a0da97] 
- R PD    [(Partial) Autocorrelation Function] [] [2014-12-20 10:10:12] [46d78fa4bef23992fc20db72a2a0da97] 

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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=245642&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=245642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=245642&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' @ jenkins.wessa.net

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	0.273835	2.683	0.004296
2	0.135548	1.3281	0.093649
3	0.24795	2.4294	0.008492
4	-0.052642	-0.5158	0.303594
5	-0.146387	-1.4343	0.07737
6	-0.258389	-2.5317	0.006488
7	-0.170622	-1.6717	0.048916
8	-0.096155	-0.9421	0.174248
9	0.176635	1.7307	0.043362
10	0.063369	0.6209	0.268072
11	0.147466	1.4449	0.075876
12	0.776629	7.6094	0
13	0.173882	1.7037	0.045837
14	0.063227	0.6195	0.268529
15	0.187947	1.8415	0.034319
16	-0.079558	-0.7795	0.2188
17	-0.142063	-1.3919	0.08358
18	-0.250306	-2.4525	0.007996
19	-0.20233	-1.9824	0.025145

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.273835 & 2.683 & 0.004296 \tabularnewline
2 & 0.135548 & 1.3281 & 0.093649 \tabularnewline
3 & 0.24795 & 2.4294 & 0.008492 \tabularnewline
4 & -0.052642 & -0.5158 & 0.303594 \tabularnewline
5 & -0.146387 & -1.4343 & 0.07737 \tabularnewline
6 & -0.258389 & -2.5317 & 0.006488 \tabularnewline
7 & -0.170622 & -1.6717 & 0.048916 \tabularnewline
8 & -0.096155 & -0.9421 & 0.174248 \tabularnewline
9 & 0.176635 & 1.7307 & 0.043362 \tabularnewline
10 & 0.063369 & 0.6209 & 0.268072 \tabularnewline
11 & 0.147466 & 1.4449 & 0.075876 \tabularnewline
12 & 0.776629 & 7.6094 & 0 \tabularnewline
13 & 0.173882 & 1.7037 & 0.045837 \tabularnewline
14 & 0.063227 & 0.6195 & 0.268529 \tabularnewline
15 & 0.187947 & 1.8415 & 0.034319 \tabularnewline
16 & -0.079558 & -0.7795 & 0.2188 \tabularnewline
17 & -0.142063 & -1.3919 & 0.08358 \tabularnewline
18 & -0.250306 & -2.4525 & 0.007996 \tabularnewline
19 & -0.20233 & -1.9824 & 0.025145 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=245642&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]0.273835[/C][C]2.683[/C][C]0.004296[/C][/ROW]
[ROW][C]2[/C][C]0.135548[/C][C]1.3281[/C][C]0.093649[/C][/ROW]
[ROW][C]3[/C][C]0.24795[/C][C]2.4294[/C][C]0.008492[/C][/ROW]
[ROW][C]4[/C][C]-0.052642[/C][C]-0.5158[/C][C]0.303594[/C][/ROW]
[ROW][C]5[/C][C]-0.146387[/C][C]-1.4343[/C][C]0.07737[/C][/ROW]
[ROW][C]6[/C][C]-0.258389[/C][C]-2.5317[/C][C]0.006488[/C][/ROW]
[ROW][C]7[/C][C]-0.170622[/C][C]-1.6717[/C][C]0.048916[/C][/ROW]
[ROW][C]8[/C][C]-0.096155[/C][C]-0.9421[/C][C]0.174248[/C][/ROW]
[ROW][C]9[/C][C]0.176635[/C][C]1.7307[/C][C]0.043362[/C][/ROW]
[ROW][C]10[/C][C]0.063369[/C][C]0.6209[/C][C]0.268072[/C][/ROW]
[ROW][C]11[/C][C]0.147466[/C][C]1.4449[/C][C]0.075876[/C][/ROW]
[ROW][C]12[/C][C]0.776629[/C][C]7.6094[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.173882[/C][C]1.7037[/C][C]0.045837[/C][/ROW]
[ROW][C]14[/C][C]0.063227[/C][C]0.6195[/C][C]0.268529[/C][/ROW]
[ROW][C]15[/C][C]0.187947[/C][C]1.8415[/C][C]0.034319[/C][/ROW]
[ROW][C]16[/C][C]-0.079558[/C][C]-0.7795[/C][C]0.2188[/C][/ROW]
[ROW][C]17[/C][C]-0.142063[/C][C]-1.3919[/C][C]0.08358[/C][/ROW]
[ROW][C]18[/C][C]-0.250306[/C][C]-2.4525[/C][C]0.007996[/C][/ROW]
[ROW][C]19[/C][C]-0.20233[/C][C]-1.9824[/C][C]0.025145[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=245642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=245642&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	0.273835	2.683	0.004296
2	0.135548	1.3281	0.093649
3	0.24795	2.4294	0.008492
4	-0.052642	-0.5158	0.303594
5	-0.146387	-1.4343	0.07737
6	-0.258389	-2.5317	0.006488
7	-0.170622	-1.6717	0.048916
8	-0.096155	-0.9421	0.174248
9	0.176635	1.7307	0.043362
10	0.063369	0.6209	0.268072
11	0.147466	1.4449	0.075876
12	0.776629	7.6094	0
13	0.173882	1.7037	0.045837
14	0.063227	0.6195	0.268529
15	0.187947	1.8415	0.034319
16	-0.079558	-0.7795	0.2188
17	-0.142063	-1.3919	0.08358
18	-0.250306	-2.4525	0.007996
19	-0.20233	-1.9824	0.025145

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	0.273835	2.683	0.004296
2	0.065471	0.6415	0.261368
3	0.212078	2.0779	0.020192
4	-0.195815	-1.9186	0.029003
5	-0.137523	-1.3474	0.090505
6	-0.270054	-2.646	0.00476
7	0.030337	0.2972	0.383463
8	0.041973	0.4112	0.340905
9	0.414446	4.0607	5e-05
10	-0.092536	-0.9067	0.183428
11	0.097904	0.9593	0.169918
12	0.680364	6.6662	0
13	-0.38943	-3.8156	0.00012
14	-0.066965	-0.6561	0.256657
15	-0.093637	-0.9174	0.180603
16	0.024411	0.2392	0.40574
17	0.04602	0.4509	0.326537
18	0.003296	0.0323	0.487153
19	-0.096521	-0.9457	0.173335

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.273835 & 2.683 & 0.004296 \tabularnewline
2 & 0.065471 & 0.6415 & 0.261368 \tabularnewline
3 & 0.212078 & 2.0779 & 0.020192 \tabularnewline
4 & -0.195815 & -1.9186 & 0.029003 \tabularnewline
5 & -0.137523 & -1.3474 & 0.090505 \tabularnewline
6 & -0.270054 & -2.646 & 0.00476 \tabularnewline
7 & 0.030337 & 0.2972 & 0.383463 \tabularnewline
8 & 0.041973 & 0.4112 & 0.340905 \tabularnewline
9 & 0.414446 & 4.0607 & 5e-05 \tabularnewline
10 & -0.092536 & -0.9067 & 0.183428 \tabularnewline
11 & 0.097904 & 0.9593 & 0.169918 \tabularnewline
12 & 0.680364 & 6.6662 & 0 \tabularnewline
13 & -0.38943 & -3.8156 & 0.00012 \tabularnewline
14 & -0.066965 & -0.6561 & 0.256657 \tabularnewline
15 & -0.093637 & -0.9174 & 0.180603 \tabularnewline
16 & 0.024411 & 0.2392 & 0.40574 \tabularnewline
17 & 0.04602 & 0.4509 & 0.326537 \tabularnewline
18 & 0.003296 & 0.0323 & 0.487153 \tabularnewline
19 & -0.096521 & -0.9457 & 0.173335 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=245642&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]0.273835[/C][C]2.683[/C][C]0.004296[/C][/ROW]
[ROW][C]2[/C][C]0.065471[/C][C]0.6415[/C][C]0.261368[/C][/ROW]
[ROW][C]3[/C][C]0.212078[/C][C]2.0779[/C][C]0.020192[/C][/ROW]
[ROW][C]4[/C][C]-0.195815[/C][C]-1.9186[/C][C]0.029003[/C][/ROW]
[ROW][C]5[/C][C]-0.137523[/C][C]-1.3474[/C][C]0.090505[/C][/ROW]
[ROW][C]6[/C][C]-0.270054[/C][C]-2.646[/C][C]0.00476[/C][/ROW]
[ROW][C]7[/C][C]0.030337[/C][C]0.2972[/C][C]0.383463[/C][/ROW]
[ROW][C]8[/C][C]0.041973[/C][C]0.4112[/C][C]0.340905[/C][/ROW]
[ROW][C]9[/C][C]0.414446[/C][C]4.0607[/C][C]5e-05[/C][/ROW]
[ROW][C]10[/C][C]-0.092536[/C][C]-0.9067[/C][C]0.183428[/C][/ROW]
[ROW][C]11[/C][C]0.097904[/C][C]0.9593[/C][C]0.169918[/C][/ROW]
[ROW][C]12[/C][C]0.680364[/C][C]6.6662[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.38943[/C][C]-3.8156[/C][C]0.00012[/C][/ROW]
[ROW][C]14[/C][C]-0.066965[/C][C]-0.6561[/C][C]0.256657[/C][/ROW]
[ROW][C]15[/C][C]-0.093637[/C][C]-0.9174[/C][C]0.180603[/C][/ROW]
[ROW][C]16[/C][C]0.024411[/C][C]0.2392[/C][C]0.40574[/C][/ROW]
[ROW][C]17[/C][C]0.04602[/C][C]0.4509[/C][C]0.326537[/C][/ROW]
[ROW][C]18[/C][C]0.003296[/C][C]0.0323[/C][C]0.487153[/C][/ROW]
[ROW][C]19[/C][C]-0.096521[/C][C]-0.9457[/C][C]0.173335[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=245642&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=245642&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	0.273835	2.683	0.004296
2	0.065471	0.6415	0.261368
3	0.212078	2.0779	0.020192
4	-0.195815	-1.9186	0.029003
5	-0.137523	-1.3474	0.090505
6	-0.270054	-2.646	0.00476
7	0.030337	0.2972	0.383463
8	0.041973	0.4112	0.340905
9	0.414446	4.0607	5e-05
10	-0.092536	-0.9067	0.183428
11	0.097904	0.9593	0.169918
12	0.680364	6.6662	0
13	-0.38943	-3.8156	0.00012
14	-0.066965	-0.6561	0.256657
15	-0.093637	-0.9174	0.180603
16	0.024411	0.2392	0.40574
17	0.04602	0.4509	0.326537
18	0.003296	0.0323	0.487153
19	-0.096521	-0.9457	0.173335

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 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;

Parameters (R input):

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

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 (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