Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 23 Jan 2017 10:48:53 +0100
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/Jan/23/t14851649623f453tj35lrzi0l.htm/, Retrieved Thu, 31 Oct 2024 23:56:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=304661, Retrieved Thu, 31 Oct 2024 23:56:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [examen] [2017-01-23 09:48:53] [2ea868439aa9f960cb5a0f1a9b97f873] [Current]
Feedback Forum

Post a new message
Dataseries X:
3035
2552
2704
2554
2014
1655
1721
1524
1596
2074
2199
2512
2933
2889
2938
2497
1870
1726
1607
1545
1396
1787
2076
2837
2787
3891
3179
2011
1636
1580
1489
1300
1356
1653
2013
2823
3102
2294
2385
2444
1748
1554
1498
1361
1346
1564
1640
2293
2815
3137
2679
1969
1870
1633
1529
1366
1357
1570
1535
2491
3084
2605
2573
2143
1693
1504
1461
1354
1333
1492
1781
1915




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=304661&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=304661&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304661&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
10.0666510.51630.303779
2-0.306029-2.37050.010497
3-0.033184-0.2570.399012
4-0.010116-0.07840.468902
5-0.076217-0.59040.278578
6-0.002803-0.02170.491376
70.0129580.10040.460192
8-0.041669-0.32280.373998
90.0953340.73850.231559
100.4009613.10580.001448
110.0098460.07630.469731
12-0.57189-4.42982e-05
13-0.031461-0.24370.404149
140.1095510.84860.199745
15-0.082553-0.63950.262481
160.0287980.22310.412121
170.0648230.50210.308712
18-0.010242-0.07930.468516

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.066651 & 0.5163 & 0.303779 \tabularnewline
2 & -0.306029 & -2.3705 & 0.010497 \tabularnewline
3 & -0.033184 & -0.257 & 0.399012 \tabularnewline
4 & -0.010116 & -0.0784 & 0.468902 \tabularnewline
5 & -0.076217 & -0.5904 & 0.278578 \tabularnewline
6 & -0.002803 & -0.0217 & 0.491376 \tabularnewline
7 & 0.012958 & 0.1004 & 0.460192 \tabularnewline
8 & -0.041669 & -0.3228 & 0.373998 \tabularnewline
9 & 0.095334 & 0.7385 & 0.231559 \tabularnewline
10 & 0.400961 & 3.1058 & 0.001448 \tabularnewline
11 & 0.009846 & 0.0763 & 0.469731 \tabularnewline
12 & -0.57189 & -4.4298 & 2e-05 \tabularnewline
13 & -0.031461 & -0.2437 & 0.404149 \tabularnewline
14 & 0.109551 & 0.8486 & 0.199745 \tabularnewline
15 & -0.082553 & -0.6395 & 0.262481 \tabularnewline
16 & 0.028798 & 0.2231 & 0.412121 \tabularnewline
17 & 0.064823 & 0.5021 & 0.308712 \tabularnewline
18 & -0.010242 & -0.0793 & 0.468516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304661&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]0.066651[/C][C]0.5163[/C][C]0.303779[/C][/ROW]
[ROW][C]2[/C][C]-0.306029[/C][C]-2.3705[/C][C]0.010497[/C][/ROW]
[ROW][C]3[/C][C]-0.033184[/C][C]-0.257[/C][C]0.399012[/C][/ROW]
[ROW][C]4[/C][C]-0.010116[/C][C]-0.0784[/C][C]0.468902[/C][/ROW]
[ROW][C]5[/C][C]-0.076217[/C][C]-0.5904[/C][C]0.278578[/C][/ROW]
[ROW][C]6[/C][C]-0.002803[/C][C]-0.0217[/C][C]0.491376[/C][/ROW]
[ROW][C]7[/C][C]0.012958[/C][C]0.1004[/C][C]0.460192[/C][/ROW]
[ROW][C]8[/C][C]-0.041669[/C][C]-0.3228[/C][C]0.373998[/C][/ROW]
[ROW][C]9[/C][C]0.095334[/C][C]0.7385[/C][C]0.231559[/C][/ROW]
[ROW][C]10[/C][C]0.400961[/C][C]3.1058[/C][C]0.001448[/C][/ROW]
[ROW][C]11[/C][C]0.009846[/C][C]0.0763[/C][C]0.469731[/C][/ROW]
[ROW][C]12[/C][C]-0.57189[/C][C]-4.4298[/C][C]2e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.031461[/C][C]-0.2437[/C][C]0.404149[/C][/ROW]
[ROW][C]14[/C][C]0.109551[/C][C]0.8486[/C][C]0.199745[/C][/ROW]
[ROW][C]15[/C][C]-0.082553[/C][C]-0.6395[/C][C]0.262481[/C][/ROW]
[ROW][C]16[/C][C]0.028798[/C][C]0.2231[/C][C]0.412121[/C][/ROW]
[ROW][C]17[/C][C]0.064823[/C][C]0.5021[/C][C]0.308712[/C][/ROW]
[ROW][C]18[/C][C]-0.010242[/C][C]-0.0793[/C][C]0.468516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304661&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304661&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
10.0666510.51630.303779
2-0.306029-2.37050.010497
3-0.033184-0.2570.399012
4-0.010116-0.07840.468902
5-0.076217-0.59040.278578
6-0.002803-0.02170.491376
70.0129580.10040.460192
8-0.041669-0.32280.373998
90.0953340.73850.231559
100.4009613.10580.001448
110.0098460.07630.469731
12-0.57189-4.42982e-05
13-0.031461-0.24370.404149
140.1095510.84860.199745
15-0.082553-0.63950.262481
160.0287980.22310.412121
170.0648230.50210.308712
18-0.010242-0.07930.468516







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0666510.51630.303779
2-0.311857-2.41560.009385
30.0159780.12380.450959
4-0.115724-0.89640.186811
5-0.080077-0.62030.268714
6-0.031392-0.24320.404356
7-0.044444-0.34430.365925
8-0.061528-0.47660.317691
90.0948440.73470.232704
100.3964553.07090.001602
110.0241080.18670.426246
12-0.440689-3.41360.000577
130.0765650.59310.277681
14-0.126158-0.97720.166193
15-0.067602-0.52360.301228
160.009170.0710.471806
17-0.038601-0.2990.382986
18-0.013623-0.10550.458155

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.066651 & 0.5163 & 0.303779 \tabularnewline
2 & -0.311857 & -2.4156 & 0.009385 \tabularnewline
3 & 0.015978 & 0.1238 & 0.450959 \tabularnewline
4 & -0.115724 & -0.8964 & 0.186811 \tabularnewline
5 & -0.080077 & -0.6203 & 0.268714 \tabularnewline
6 & -0.031392 & -0.2432 & 0.404356 \tabularnewline
7 & -0.044444 & -0.3443 & 0.365925 \tabularnewline
8 & -0.061528 & -0.4766 & 0.317691 \tabularnewline
9 & 0.094844 & 0.7347 & 0.232704 \tabularnewline
10 & 0.396455 & 3.0709 & 0.001602 \tabularnewline
11 & 0.024108 & 0.1867 & 0.426246 \tabularnewline
12 & -0.440689 & -3.4136 & 0.000577 \tabularnewline
13 & 0.076565 & 0.5931 & 0.277681 \tabularnewline
14 & -0.126158 & -0.9772 & 0.166193 \tabularnewline
15 & -0.067602 & -0.5236 & 0.301228 \tabularnewline
16 & 0.00917 & 0.071 & 0.471806 \tabularnewline
17 & -0.038601 & -0.299 & 0.382986 \tabularnewline
18 & -0.013623 & -0.1055 & 0.458155 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304661&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]0.066651[/C][C]0.5163[/C][C]0.303779[/C][/ROW]
[ROW][C]2[/C][C]-0.311857[/C][C]-2.4156[/C][C]0.009385[/C][/ROW]
[ROW][C]3[/C][C]0.015978[/C][C]0.1238[/C][C]0.450959[/C][/ROW]
[ROW][C]4[/C][C]-0.115724[/C][C]-0.8964[/C][C]0.186811[/C][/ROW]
[ROW][C]5[/C][C]-0.080077[/C][C]-0.6203[/C][C]0.268714[/C][/ROW]
[ROW][C]6[/C][C]-0.031392[/C][C]-0.2432[/C][C]0.404356[/C][/ROW]
[ROW][C]7[/C][C]-0.044444[/C][C]-0.3443[/C][C]0.365925[/C][/ROW]
[ROW][C]8[/C][C]-0.061528[/C][C]-0.4766[/C][C]0.317691[/C][/ROW]
[ROW][C]9[/C][C]0.094844[/C][C]0.7347[/C][C]0.232704[/C][/ROW]
[ROW][C]10[/C][C]0.396455[/C][C]3.0709[/C][C]0.001602[/C][/ROW]
[ROW][C]11[/C][C]0.024108[/C][C]0.1867[/C][C]0.426246[/C][/ROW]
[ROW][C]12[/C][C]-0.440689[/C][C]-3.4136[/C][C]0.000577[/C][/ROW]
[ROW][C]13[/C][C]0.076565[/C][C]0.5931[/C][C]0.277681[/C][/ROW]
[ROW][C]14[/C][C]-0.126158[/C][C]-0.9772[/C][C]0.166193[/C][/ROW]
[ROW][C]15[/C][C]-0.067602[/C][C]-0.5236[/C][C]0.301228[/C][/ROW]
[ROW][C]16[/C][C]0.00917[/C][C]0.071[/C][C]0.471806[/C][/ROW]
[ROW][C]17[/C][C]-0.038601[/C][C]-0.299[/C][C]0.382986[/C][/ROW]
[ROW][C]18[/C][C]-0.013623[/C][C]-0.1055[/C][C]0.458155[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304661&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304661&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
10.0666510.51630.303779
2-0.311857-2.41560.009385
30.0159780.12380.450959
4-0.115724-0.89640.186811
5-0.080077-0.62030.268714
6-0.031392-0.24320.404356
7-0.044444-0.34430.365925
8-0.061528-0.47660.317691
90.0948440.73470.232704
100.3964553.07090.001602
110.0241080.18670.426246
12-0.440689-3.41360.000577
130.0765650.59310.277681
14-0.126158-0.97720.166193
15-0.067602-0.52360.301228
160.009170.0710.471806
17-0.038601-0.2990.382986
18-0.013623-0.10550.458155



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