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R Software Module

rwasp_autocorrelation.wasp

Title produced by software

(Partial) Autocorrelation Function

Date of computation

Fri, 16 Dec 2016 16:37:16 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/16/t1481902653fk0d402g9jpi9iy.htm/, Retrieved Fri, 01 Nov 2024 03:47:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300372, Retrieved Fri, 01 Nov 2024 03:47:18 +0000

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User-defined keywords

Estimated Impact

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

-     [ARIMA Backward Selection] [] [2016-12-16 13:36:55] [683f400e1b95307fc738e729f07c4fce]
-    D  [ARIMA Backward Selection] [] [2016-12-16 14:17:56] [683f400e1b95307fc738e729f07c4fce]
- R  D    [ARIMA Backward Selection] [] [2016-12-16 14:51:40] [683f400e1b95307fc738e729f07c4fce]
- RM D        [(Partial) Autocorrelation Function] [] [2016-12-16 15:37:16] [404ac5ee4f7301873f6a96ef36861981] [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	Big Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300372&T=0

[TABLE]
[ROW]

Summary of computational transaction[/C][/ROW] [ROW]

Raw Input[/C]

view raw input (R code) [/C][/ROW] [ROW]

Raw Output[/C]

view raw output of R engine [/C][/ROW] [ROW]

Computing time[/C]

1 seconds[/C][/ROW] [ROW]

R Server[/C]

Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=300372&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300372&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	Big Analytics Cloud Computing Center

Autocorrelation Function
Time lag k	ACF(k)	T-STAT	P-value
1	-0.173133	-1.4065	0.082128
2	-0.018132	-0.1473	0.44167
3	-0.121175	-0.9844	0.164249
4	0.165338	1.3432	0.091902
5	0.255956	2.0794	0.020735
6	-0.034928	-0.2838	0.388744
7	-0.095892	-0.779	0.219373
8	-0.188405	-1.5306	0.065323
9	0.159072	1.2923	0.100379
10	0.021535	0.175	0.430827
11	0.244396	1.9855	0.025624
12	-0.474855	-3.8577	0.000131
13	0.093717	0.7614	0.224576
14	0.095924	0.7793	0.219297
15	0.144222	1.1717	0.122772
16	-0.078574	-0.6383	0.262732
17	-0.121517	-0.9872	0.163574
18	0.039856	0.3238	0.373558

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.173133 & -1.4065 & 0.082128 \tabularnewline
2 & -0.018132 & -0.1473 & 0.44167 \tabularnewline
3 & -0.121175 & -0.9844 & 0.164249 \tabularnewline
4 & 0.165338 & 1.3432 & 0.091902 \tabularnewline
5 & 0.255956 & 2.0794 & 0.020735 \tabularnewline
6 & -0.034928 & -0.2838 & 0.388744 \tabularnewline
7 & -0.095892 & -0.779 & 0.219373 \tabularnewline
8 & -0.188405 & -1.5306 & 0.065323 \tabularnewline
9 & 0.159072 & 1.2923 & 0.100379 \tabularnewline
10 & 0.021535 & 0.175 & 0.430827 \tabularnewline
11 & 0.244396 & 1.9855 & 0.025624 \tabularnewline
12 & -0.474855 & -3.8577 & 0.000131 \tabularnewline
13 & 0.093717 & 0.7614 & 0.224576 \tabularnewline
14 & 0.095924 & 0.7793 & 0.219297 \tabularnewline
15 & 0.144222 & 1.1717 & 0.122772 \tabularnewline
16 & -0.078574 & -0.6383 & 0.262732 \tabularnewline
17 & -0.121517 & -0.9872 & 0.163574 \tabularnewline
18 & 0.039856 & 0.3238 & 0.373558 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300372&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]-0.173133[/C][C]-1.4065[/C][C]0.082128[/C][/ROW]
[ROW][C]2[/C][C]-0.018132[/C][C]-0.1473[/C][C]0.44167[/C][/ROW]
[ROW][C]3[/C][C]-0.121175[/C][C]-0.9844[/C][C]0.164249[/C][/ROW]
[ROW][C]4[/C][C]0.165338[/C][C]1.3432[/C][C]0.091902[/C][/ROW]
[ROW][C]5[/C][C]0.255956[/C][C]2.0794[/C][C]0.020735[/C][/ROW]
[ROW][C]6[/C][C]-0.034928[/C][C]-0.2838[/C][C]0.388744[/C][/ROW]
[ROW][C]7[/C][C]-0.095892[/C][C]-0.779[/C][C]0.219373[/C][/ROW]
[ROW][C]8[/C][C]-0.188405[/C][C]-1.5306[/C][C]0.065323[/C][/ROW]
[ROW][C]9[/C][C]0.159072[/C][C]1.2923[/C][C]0.100379[/C][/ROW]
[ROW][C]10[/C][C]0.021535[/C][C]0.175[/C][C]0.430827[/C][/ROW]
[ROW][C]11[/C][C]0.244396[/C][C]1.9855[/C][C]0.025624[/C][/ROW]
[ROW][C]12[/C][C]-0.474855[/C][C]-3.8577[/C][C]0.000131[/C][/ROW]
[ROW][C]13[/C][C]0.093717[/C][C]0.7614[/C][C]0.224576[/C][/ROW]
[ROW][C]14[/C][C]0.095924[/C][C]0.7793[/C][C]0.219297[/C][/ROW]
[ROW][C]15[/C][C]0.144222[/C][C]1.1717[/C][C]0.122772[/C][/ROW]
[ROW][C]16[/C][C]-0.078574[/C][C]-0.6383[/C][C]0.262732[/C][/ROW]
[ROW][C]17[/C][C]-0.121517[/C][C]-0.9872[/C][C]0.163574[/C][/ROW]
[ROW][C]18[/C][C]0.039856[/C][C]0.3238[/C][C]0.373558[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300372&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300372&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	-0.173133	-1.4065	0.082128
2	-0.018132	-0.1473	0.44167
3	-0.121175	-0.9844	0.164249
4	0.165338	1.3432	0.091902
5	0.255956	2.0794	0.020735
6	-0.034928	-0.2838	0.388744
7	-0.095892	-0.779	0.219373
8	-0.188405	-1.5306	0.065323
9	0.159072	1.2923	0.100379
10	0.021535	0.175	0.430827
11	0.244396	1.9855	0.025624
12	-0.474855	-3.8577	0.000131
13	0.093717	0.7614	0.224576
14	0.095924	0.7793	0.219297
15	0.144222	1.1717	0.122772
16	-0.078574	-0.6383	0.262732
17	-0.121517	-0.9872	0.163574
18	0.039856	0.3238	0.373558

Partial Autocorrelation Function
Time lag k	PACF(k)	T-STAT	P-value
1	-0.173133	-1.4065	0.082128
2	-0.049594	-0.4029	0.344162
3	-0.137506	-1.1171	0.134
4	0.123593	1.0041	0.159504
5	0.316338	2.5699	0.006218
6	0.083778	0.6806	0.249249
7	-0.043453	-0.353	0.362601
8	-0.224333	-1.8225	0.036455
9	-0.03532	-0.2869	0.387529
10	-0.062333	-0.5064	0.307134
11	0.308191	2.5038	0.007384
12	-0.307163	-2.4954	0.007545
13	0.058895	0.4785	0.31695
14	0.090243	0.7331	0.233035
15	0.055594	0.4517	0.3265
16	-0.099175	-0.8057	0.211655
17	0.115691	0.9399	0.175354
18	-0.027122	-0.2203	0.413142

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.173133 & -1.4065 & 0.082128 \tabularnewline
2 & -0.049594 & -0.4029 & 0.344162 \tabularnewline
3 & -0.137506 & -1.1171 & 0.134 \tabularnewline
4 & 0.123593 & 1.0041 & 0.159504 \tabularnewline
5 & 0.316338 & 2.5699 & 0.006218 \tabularnewline
6 & 0.083778 & 0.6806 & 0.249249 \tabularnewline
7 & -0.043453 & -0.353 & 0.362601 \tabularnewline
8 & -0.224333 & -1.8225 & 0.036455 \tabularnewline
9 & -0.03532 & -0.2869 & 0.387529 \tabularnewline
10 & -0.062333 & -0.5064 & 0.307134 \tabularnewline
11 & 0.308191 & 2.5038 & 0.007384 \tabularnewline
12 & -0.307163 & -2.4954 & 0.007545 \tabularnewline
13 & 0.058895 & 0.4785 & 0.31695 \tabularnewline
14 & 0.090243 & 0.7331 & 0.233035 \tabularnewline
15 & 0.055594 & 0.4517 & 0.3265 \tabularnewline
16 & -0.099175 & -0.8057 & 0.211655 \tabularnewline
17 & 0.115691 & 0.9399 & 0.175354 \tabularnewline
18 & -0.027122 & -0.2203 & 0.413142 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300372&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]-0.173133[/C][C]-1.4065[/C][C]0.082128[/C][/ROW]
[ROW][C]2[/C][C]-0.049594[/C][C]-0.4029[/C][C]0.344162[/C][/ROW]
[ROW][C]3[/C][C]-0.137506[/C][C]-1.1171[/C][C]0.134[/C][/ROW]
[ROW][C]4[/C][C]0.123593[/C][C]1.0041[/C][C]0.159504[/C][/ROW]
[ROW][C]5[/C][C]0.316338[/C][C]2.5699[/C][C]0.006218[/C][/ROW]
[ROW][C]6[/C][C]0.083778[/C][C]0.6806[/C][C]0.249249[/C][/ROW]
[ROW][C]7[/C][C]-0.043453[/C][C]-0.353[/C][C]0.362601[/C][/ROW]
[ROW][C]8[/C][C]-0.224333[/C][C]-1.8225[/C][C]0.036455[/C][/ROW]
[ROW][C]9[/C][C]-0.03532[/C][C]-0.2869[/C][C]0.387529[/C][/ROW]
[ROW][C]10[/C][C]-0.062333[/C][C]-0.5064[/C][C]0.307134[/C][/ROW]
[ROW][C]11[/C][C]0.308191[/C][C]2.5038[/C][C]0.007384[/C][/ROW]
[ROW][C]12[/C][C]-0.307163[/C][C]-2.4954[/C][C]0.007545[/C][/ROW]
[ROW][C]13[/C][C]0.058895[/C][C]0.4785[/C][C]0.31695[/C][/ROW]
[ROW][C]14[/C][C]0.090243[/C][C]0.7331[/C][C]0.233035[/C][/ROW]
[ROW][C]15[/C][C]0.055594[/C][C]0.4517[/C][C]0.3265[/C][/ROW]
[ROW][C]16[/C][C]-0.099175[/C][C]-0.8057[/C][C]0.211655[/C][/ROW]
[ROW][C]17[/C][C]0.115691[/C][C]0.9399[/C][C]0.175354[/C][/ROW]
[ROW][C]18[/C][C]-0.027122[/C][C]-0.2203[/C][C]0.413142[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300372&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300372&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	-0.173133	-1.4065	0.082128
2	-0.049594	-0.4029	0.344162
3	-0.137506	-1.1171	0.134
4	0.123593	1.0041	0.159504
5	0.316338	2.5699	0.006218
6	0.083778	0.6806	0.249249
7	-0.043453	-0.353	0.362601
8	-0.224333	-1.8225	0.036455
9	-0.03532	-0.2869	0.387529
10	-0.062333	-0.5064	0.307134
11	0.308191	2.5038	0.007384
12	-0.307163	-2.4954	0.007545
13	0.058895	0.4785	0.31695
14	0.090243	0.7331	0.233035
15	0.055594	0.4517	0.3265
16	-0.099175	-0.8057	0.211655
17	0.115691	0.9399	0.175354
18	-0.027122	-0.2203	0.413142

Figure 1

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Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = FALSE ; par2 = 1 ; par3 = 2 ; par4 = 0 ; par5 = 1 ; par6 = 3 ; par7 = 1 ; par8 = 2 ; par9 = 0 ;

Parameters (R input):

par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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 <- '1'
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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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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Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code