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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationSat, 10 Oct 2020 15:08:34 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2020/Oct/10/t1602335390q0r7qpp5se36xl9.htm/, Retrieved Wed, 21 Apr 2021 07:10:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=319261, Retrieved Wed, 21 Apr 2021 07:10:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact21
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [D0d0] [2020-10-10 13:08:34] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
12.00
9.00
8.00
26.00
18.00
19.00
17.00
21.00
4.00
85.00
29.00
10.00
15.00
16.00
20.00
26.00
46.00
54.00
27.00
29.00
90.00
92.00
74.00
115.00
127.00
106.00
45.00
54.00
92.00
37.00
44.00
33.00
26.00
75.00
35.00
43.00
55.00
46.00
55.00
44.00
46.00
55.00
35.00
232.00
549.00
824.00
776.00
787.00
813.00
688.00
720.00
697.00




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig 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=319261&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=319261&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319261&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 Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9114796.57280
20.7842325.65520
30.6529184.70839e-06
40.4986363.59570.00036
50.3554052.56290.006658
60.2211951.59510.058379
70.0882760.63660.2636
8-0.000275-0.0020.499214
9-0.038702-0.27910.390644
10-0.038126-0.27490.39223
11-0.042307-0.30510.38076
12-0.04733-0.34130.367126
13-0.05553-0.40040.34524
14-0.063159-0.45540.325342
15-0.065401-0.47160.319587
16-0.068589-0.49460.311481
17-0.067156-0.48430.315114

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.911479 & 6.5728 & 0 \tabularnewline
2 & 0.784232 & 5.6552 & 0 \tabularnewline
3 & 0.652918 & 4.7083 & 9e-06 \tabularnewline
4 & 0.498636 & 3.5957 & 0.00036 \tabularnewline
5 & 0.355405 & 2.5629 & 0.006658 \tabularnewline
6 & 0.221195 & 1.5951 & 0.058379 \tabularnewline
7 & 0.088276 & 0.6366 & 0.2636 \tabularnewline
8 & -0.000275 & -0.002 & 0.499214 \tabularnewline
9 & -0.038702 & -0.2791 & 0.390644 \tabularnewline
10 & -0.038126 & -0.2749 & 0.39223 \tabularnewline
11 & -0.042307 & -0.3051 & 0.38076 \tabularnewline
12 & -0.04733 & -0.3413 & 0.367126 \tabularnewline
13 & -0.05553 & -0.4004 & 0.34524 \tabularnewline
14 & -0.063159 & -0.4554 & 0.325342 \tabularnewline
15 & -0.065401 & -0.4716 & 0.319587 \tabularnewline
16 & -0.068589 & -0.4946 & 0.311481 \tabularnewline
17 & -0.067156 & -0.4843 & 0.315114 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319261&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]0.911479[/C][C]6.5728[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.784232[/C][C]5.6552[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.652918[/C][C]4.7083[/C][C]9e-06[/C][/ROW]
[ROW][C]4[/C][C]0.498636[/C][C]3.5957[/C][C]0.00036[/C][/ROW]
[ROW][C]5[/C][C]0.355405[/C][C]2.5629[/C][C]0.006658[/C][/ROW]
[ROW][C]6[/C][C]0.221195[/C][C]1.5951[/C][C]0.058379[/C][/ROW]
[ROW][C]7[/C][C]0.088276[/C][C]0.6366[/C][C]0.2636[/C][/ROW]
[ROW][C]8[/C][C]-0.000275[/C][C]-0.002[/C][C]0.499214[/C][/ROW]
[ROW][C]9[/C][C]-0.038702[/C][C]-0.2791[/C][C]0.390644[/C][/ROW]
[ROW][C]10[/C][C]-0.038126[/C][C]-0.2749[/C][C]0.39223[/C][/ROW]
[ROW][C]11[/C][C]-0.042307[/C][C]-0.3051[/C][C]0.38076[/C][/ROW]
[ROW][C]12[/C][C]-0.04733[/C][C]-0.3413[/C][C]0.367126[/C][/ROW]
[ROW][C]13[/C][C]-0.05553[/C][C]-0.4004[/C][C]0.34524[/C][/ROW]
[ROW][C]14[/C][C]-0.063159[/C][C]-0.4554[/C][C]0.325342[/C][/ROW]
[ROW][C]15[/C][C]-0.065401[/C][C]-0.4716[/C][C]0.319587[/C][/ROW]
[ROW][C]16[/C][C]-0.068589[/C][C]-0.4946[/C][C]0.311481[/C][/ROW]
[ROW][C]17[/C][C]-0.067156[/C][C]-0.4843[/C][C]0.315114[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319261&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319261&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 kACF(k)T-STATP-value
10.9114796.57280
20.7842325.65520
30.6529184.70839e-06
40.4986363.59570.00036
50.3554052.56290.006658
60.2211951.59510.058379
70.0882760.63660.2636
8-0.000275-0.0020.499214
9-0.038702-0.27910.390644
10-0.038126-0.27490.39223
11-0.042307-0.30510.38076
12-0.04733-0.34130.367126
13-0.05553-0.40040.34524
14-0.063159-0.45540.325342
15-0.065401-0.47160.319587
16-0.068589-0.49460.311481
17-0.067156-0.48430.315114







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9114796.57280
2-0.275178-1.98430.026253
3-0.049714-0.35850.360714
4-0.227653-1.64160.053351
50.026930.19420.42339
6-0.096201-0.69370.245473
7-0.089687-0.64670.260323
80.1506751.08650.141126
90.1314940.94820.173703
100.1221570.88090.191217
11-0.222873-1.60720.057037
12-0.037727-0.27210.393328
13-0.10269-0.74050.231162
140.0232810.16790.433664
15-0.000441-0.00320.498738
160.0337710.24350.404279
170.144231.04010.151563

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.911479 & 6.5728 & 0 \tabularnewline
2 & -0.275178 & -1.9843 & 0.026253 \tabularnewline
3 & -0.049714 & -0.3585 & 0.360714 \tabularnewline
4 & -0.227653 & -1.6416 & 0.053351 \tabularnewline
5 & 0.02693 & 0.1942 & 0.42339 \tabularnewline
6 & -0.096201 & -0.6937 & 0.245473 \tabularnewline
7 & -0.089687 & -0.6467 & 0.260323 \tabularnewline
8 & 0.150675 & 1.0865 & 0.141126 \tabularnewline
9 & 0.131494 & 0.9482 & 0.173703 \tabularnewline
10 & 0.122157 & 0.8809 & 0.191217 \tabularnewline
11 & -0.222873 & -1.6072 & 0.057037 \tabularnewline
12 & -0.037727 & -0.2721 & 0.393328 \tabularnewline
13 & -0.10269 & -0.7405 & 0.231162 \tabularnewline
14 & 0.023281 & 0.1679 & 0.433664 \tabularnewline
15 & -0.000441 & -0.0032 & 0.498738 \tabularnewline
16 & 0.033771 & 0.2435 & 0.404279 \tabularnewline
17 & 0.14423 & 1.0401 & 0.151563 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=319261&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]0.911479[/C][C]6.5728[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.275178[/C][C]-1.9843[/C][C]0.026253[/C][/ROW]
[ROW][C]3[/C][C]-0.049714[/C][C]-0.3585[/C][C]0.360714[/C][/ROW]
[ROW][C]4[/C][C]-0.227653[/C][C]-1.6416[/C][C]0.053351[/C][/ROW]
[ROW][C]5[/C][C]0.02693[/C][C]0.1942[/C][C]0.42339[/C][/ROW]
[ROW][C]6[/C][C]-0.096201[/C][C]-0.6937[/C][C]0.245473[/C][/ROW]
[ROW][C]7[/C][C]-0.089687[/C][C]-0.6467[/C][C]0.260323[/C][/ROW]
[ROW][C]8[/C][C]0.150675[/C][C]1.0865[/C][C]0.141126[/C][/ROW]
[ROW][C]9[/C][C]0.131494[/C][C]0.9482[/C][C]0.173703[/C][/ROW]
[ROW][C]10[/C][C]0.122157[/C][C]0.8809[/C][C]0.191217[/C][/ROW]
[ROW][C]11[/C][C]-0.222873[/C][C]-1.6072[/C][C]0.057037[/C][/ROW]
[ROW][C]12[/C][C]-0.037727[/C][C]-0.2721[/C][C]0.393328[/C][/ROW]
[ROW][C]13[/C][C]-0.10269[/C][C]-0.7405[/C][C]0.231162[/C][/ROW]
[ROW][C]14[/C][C]0.023281[/C][C]0.1679[/C][C]0.433664[/C][/ROW]
[ROW][C]15[/C][C]-0.000441[/C][C]-0.0032[/C][C]0.498738[/C][/ROW]
[ROW][C]16[/C][C]0.033771[/C][C]0.2435[/C][C]0.404279[/C][/ROW]
[ROW][C]17[/C][C]0.14423[/C][C]1.0401[/C][C]0.151563[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=319261&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=319261&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 kPACF(k)T-STATP-value
10.9114796.57280
2-0.275178-1.98430.026253
3-0.049714-0.35850.360714
4-0.227653-1.64160.053351
50.026930.19420.42339
6-0.096201-0.69370.245473
7-0.089687-0.64670.260323
80.1506751.08650.141126
90.1314940.94820.173703
100.1221570.88090.191217
11-0.222873-1.60720.057037
12-0.037727-0.27210.393328
13-0.10269-0.74050.231162
140.0232810.16790.433664
15-0.000441-0.00320.498738
160.0337710.24350.404279
170.144231.04010.151563



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)
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')