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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 15 Aug 2017 14:40:46 +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/2017/Aug/15/t1502800892nuronmojk6vri75.htm/, Retrieved Mon, 20 May 2024 00:33:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=307278, Retrieved Mon, 20 May 2024 00:33:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2017-08-15 12:40:46] [eec775fda337aa2da775a098928b5865] [Current]
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Dataseries X:
1053000
1014000
1072500
858000
1111500
1092000
1170000
1209000
1345500
1170000
1111500
1384500
1170000
877500
1033500
780000
1092000
897000
1189500
1072500
1131000
1267500
1248000
1482000
1072500
897000
994500
721500
1033500
799500
1131000
1072500
955500
1365000
1228500
1404000
1053000
975000
877500
721500
955500
858000
1170000
1131000
975000
1306500
1209000
1560000
1248000
760500
760500
760500
897000
897000
1209000
1111500
994500
1248000
1150500
1657500
1306500
760500
799500
663000
916500
1053000
1326000
1306500
1053000
1228500
1092000
1560000
1189500
955500
858000
643500
955500
1150500
1345500
1267500
936000
1345500
1053000
1618500
1345500
975000
897000
604500
955500
916500
1384500
1384500
1053000
1365000
1014000
1579500
1345500
994500
760500
526500
1033500
994500
1306500
1501500
1111500
1248000
936000
1618500




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=307278&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=307278&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307278&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
1-0.34099-3.52720.00031
20.1611711.66720.049203
3-0.187224-1.93670.027712
4-0.339596-3.51280.000325
50.3709553.83720.000105
6-0.34395-3.55780.000279
70.4181114.3251.7e-05
8-0.287596-2.97490.001811
9-0.184079-1.90410.02979
100.1344191.39040.083641
11-0.313093-3.23878e-04
120.7895528.16720
13-0.255181-2.63960.00477
140.1906571.97220.025585
15-0.164844-1.70520.045533
16-0.350569-3.62630.000221
170.3377353.49360.000347
18-0.308274-3.18880.000937
190.3765073.89468.6e-05
20-0.224228-2.31940.011135

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.34099 & -3.5272 & 0.00031 \tabularnewline
2 & 0.161171 & 1.6672 & 0.049203 \tabularnewline
3 & -0.187224 & -1.9367 & 0.027712 \tabularnewline
4 & -0.339596 & -3.5128 & 0.000325 \tabularnewline
5 & 0.370955 & 3.8372 & 0.000105 \tabularnewline
6 & -0.34395 & -3.5578 & 0.000279 \tabularnewline
7 & 0.418111 & 4.325 & 1.7e-05 \tabularnewline
8 & -0.287596 & -2.9749 & 0.001811 \tabularnewline
9 & -0.184079 & -1.9041 & 0.02979 \tabularnewline
10 & 0.134419 & 1.3904 & 0.083641 \tabularnewline
11 & -0.313093 & -3.2387 & 8e-04 \tabularnewline
12 & 0.789552 & 8.1672 & 0 \tabularnewline
13 & -0.255181 & -2.6396 & 0.00477 \tabularnewline
14 & 0.190657 & 1.9722 & 0.025585 \tabularnewline
15 & -0.164844 & -1.7052 & 0.045533 \tabularnewline
16 & -0.350569 & -3.6263 & 0.000221 \tabularnewline
17 & 0.337735 & 3.4936 & 0.000347 \tabularnewline
18 & -0.308274 & -3.1888 & 0.000937 \tabularnewline
19 & 0.376507 & 3.8946 & 8.6e-05 \tabularnewline
20 & -0.224228 & -2.3194 & 0.011135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307278&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]-0.34099[/C][C]-3.5272[/C][C]0.00031[/C][/ROW]
[ROW][C]2[/C][C]0.161171[/C][C]1.6672[/C][C]0.049203[/C][/ROW]
[ROW][C]3[/C][C]-0.187224[/C][C]-1.9367[/C][C]0.027712[/C][/ROW]
[ROW][C]4[/C][C]-0.339596[/C][C]-3.5128[/C][C]0.000325[/C][/ROW]
[ROW][C]5[/C][C]0.370955[/C][C]3.8372[/C][C]0.000105[/C][/ROW]
[ROW][C]6[/C][C]-0.34395[/C][C]-3.5578[/C][C]0.000279[/C][/ROW]
[ROW][C]7[/C][C]0.418111[/C][C]4.325[/C][C]1.7e-05[/C][/ROW]
[ROW][C]8[/C][C]-0.287596[/C][C]-2.9749[/C][C]0.001811[/C][/ROW]
[ROW][C]9[/C][C]-0.184079[/C][C]-1.9041[/C][C]0.02979[/C][/ROW]
[ROW][C]10[/C][C]0.134419[/C][C]1.3904[/C][C]0.083641[/C][/ROW]
[ROW][C]11[/C][C]-0.313093[/C][C]-3.2387[/C][C]8e-04[/C][/ROW]
[ROW][C]12[/C][C]0.789552[/C][C]8.1672[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.255181[/C][C]-2.6396[/C][C]0.00477[/C][/ROW]
[ROW][C]14[/C][C]0.190657[/C][C]1.9722[/C][C]0.025585[/C][/ROW]
[ROW][C]15[/C][C]-0.164844[/C][C]-1.7052[/C][C]0.045533[/C][/ROW]
[ROW][C]16[/C][C]-0.350569[/C][C]-3.6263[/C][C]0.000221[/C][/ROW]
[ROW][C]17[/C][C]0.337735[/C][C]3.4936[/C][C]0.000347[/C][/ROW]
[ROW][C]18[/C][C]-0.308274[/C][C]-3.1888[/C][C]0.000937[/C][/ROW]
[ROW][C]19[/C][C]0.376507[/C][C]3.8946[/C][C]8.6e-05[/C][/ROW]
[ROW][C]20[/C][C]-0.224228[/C][C]-2.3194[/C][C]0.011135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307278&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307278&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
1-0.34099-3.52720.00031
20.1611711.66720.049203
3-0.187224-1.93670.027712
4-0.339596-3.51280.000325
50.3709553.83720.000105
6-0.34395-3.55780.000279
70.4181114.3251.7e-05
8-0.287596-2.97490.001811
9-0.184079-1.90410.02979
100.1344191.39040.083641
11-0.313093-3.23878e-04
120.7895528.16720
13-0.255181-2.63960.00477
140.1906571.97220.025585
15-0.164844-1.70520.045533
16-0.350569-3.62630.000221
170.3377353.49360.000347
18-0.308274-3.18880.000937
190.3765073.89468.6e-05
20-0.224228-2.31940.011135







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.34099-3.52720.00031
20.0508040.52550.300154
3-0.13357-1.38170.084977
4-0.514821-5.32530
50.1798151.860.032814
6-0.220958-2.28560.012124
70.0767560.7940.214484
8-0.234549-2.42620.008465
9-0.434093-4.49039e-06
10-0.217-2.24470.013423
11-0.396937-4.10593.9e-05
120.4450364.60356e-06
130.1086521.12390.131784
140.0436250.45130.326357
15-0.004306-0.04450.48228
16-0.015357-0.15890.43704
170.0497710.51480.303866
180.0897240.92810.17772
19-0.104654-1.08250.140722
20-0.051051-0.52810.299269

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.34099 & -3.5272 & 0.00031 \tabularnewline
2 & 0.050804 & 0.5255 & 0.300154 \tabularnewline
3 & -0.13357 & -1.3817 & 0.084977 \tabularnewline
4 & -0.514821 & -5.3253 & 0 \tabularnewline
5 & 0.179815 & 1.86 & 0.032814 \tabularnewline
6 & -0.220958 & -2.2856 & 0.012124 \tabularnewline
7 & 0.076756 & 0.794 & 0.214484 \tabularnewline
8 & -0.234549 & -2.4262 & 0.008465 \tabularnewline
9 & -0.434093 & -4.4903 & 9e-06 \tabularnewline
10 & -0.217 & -2.2447 & 0.013423 \tabularnewline
11 & -0.396937 & -4.1059 & 3.9e-05 \tabularnewline
12 & 0.445036 & 4.6035 & 6e-06 \tabularnewline
13 & 0.108652 & 1.1239 & 0.131784 \tabularnewline
14 & 0.043625 & 0.4513 & 0.326357 \tabularnewline
15 & -0.004306 & -0.0445 & 0.48228 \tabularnewline
16 & -0.015357 & -0.1589 & 0.43704 \tabularnewline
17 & 0.049771 & 0.5148 & 0.303866 \tabularnewline
18 & 0.089724 & 0.9281 & 0.17772 \tabularnewline
19 & -0.104654 & -1.0825 & 0.140722 \tabularnewline
20 & -0.051051 & -0.5281 & 0.299269 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=307278&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]-0.34099[/C][C]-3.5272[/C][C]0.00031[/C][/ROW]
[ROW][C]2[/C][C]0.050804[/C][C]0.5255[/C][C]0.300154[/C][/ROW]
[ROW][C]3[/C][C]-0.13357[/C][C]-1.3817[/C][C]0.084977[/C][/ROW]
[ROW][C]4[/C][C]-0.514821[/C][C]-5.3253[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.179815[/C][C]1.86[/C][C]0.032814[/C][/ROW]
[ROW][C]6[/C][C]-0.220958[/C][C]-2.2856[/C][C]0.012124[/C][/ROW]
[ROW][C]7[/C][C]0.076756[/C][C]0.794[/C][C]0.214484[/C][/ROW]
[ROW][C]8[/C][C]-0.234549[/C][C]-2.4262[/C][C]0.008465[/C][/ROW]
[ROW][C]9[/C][C]-0.434093[/C][C]-4.4903[/C][C]9e-06[/C][/ROW]
[ROW][C]10[/C][C]-0.217[/C][C]-2.2447[/C][C]0.013423[/C][/ROW]
[ROW][C]11[/C][C]-0.396937[/C][C]-4.1059[/C][C]3.9e-05[/C][/ROW]
[ROW][C]12[/C][C]0.445036[/C][C]4.6035[/C][C]6e-06[/C][/ROW]
[ROW][C]13[/C][C]0.108652[/C][C]1.1239[/C][C]0.131784[/C][/ROW]
[ROW][C]14[/C][C]0.043625[/C][C]0.4513[/C][C]0.326357[/C][/ROW]
[ROW][C]15[/C][C]-0.004306[/C][C]-0.0445[/C][C]0.48228[/C][/ROW]
[ROW][C]16[/C][C]-0.015357[/C][C]-0.1589[/C][C]0.43704[/C][/ROW]
[ROW][C]17[/C][C]0.049771[/C][C]0.5148[/C][C]0.303866[/C][/ROW]
[ROW][C]18[/C][C]0.089724[/C][C]0.9281[/C][C]0.17772[/C][/ROW]
[ROW][C]19[/C][C]-0.104654[/C][C]-1.0825[/C][C]0.140722[/C][/ROW]
[ROW][C]20[/C][C]-0.051051[/C][C]-0.5281[/C][C]0.299269[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=307278&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=307278&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
1-0.34099-3.52720.00031
20.0508040.52550.300154
3-0.13357-1.38170.084977
4-0.514821-5.32530
50.1798151.860.032814
6-0.220958-2.28560.012124
70.0767560.7940.214484
8-0.234549-2.42620.008465
9-0.434093-4.49039e-06
10-0.217-2.24470.013423
11-0.396937-4.10593.9e-05
120.4450364.60356e-06
130.1086521.12390.131784
140.0436250.45130.326357
15-0.004306-0.04450.48228
16-0.015357-0.15890.43704
170.0497710.51480.303866
180.0897240.92810.17772
19-0.104654-1.08250.140722
20-0.051051-0.52810.299269



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; 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 <- '1'
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')