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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 computationSat, 17 Dec 2016 15:54:51 +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/2016/Dec/17/t1481986520qlfd6zwzk61enst.htm/, Retrieved Thu, 02 May 2024 05:54:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300835, Retrieved Thu, 02 May 2024 05:54:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [""N2582"" autocorr 1] [2016-12-17 14:54:51] [afe7f6443461a2cd6ee0b843643e84a9] [Current]
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Dataseries X:
4028.8
4076.6
4125.8
4177.2
4183
4222.6
4255.8
4260.8
4279.2
4328.8
4356.6
4393
4419.4
4426.2
4467.2
4517.4
4517
4560.4
4589
4596
4621.2
4654.6
4708.6
4774.4
4824.8
4839
4869.8
4895.8
4895.8
4968.8
5010
5032.4
5054
5083.8
5117.4
5170.8
5182.2
5163.6
5212.6
5288
5303.4
5367.6
5433.8
5465.8
5493.8
5549.4
5590.2
5661.2
5699
5654.2
5671.8
5730.8
5693
5720.4
5747.8
5764.2
5783
5822.4
5836.2
5864.6
5913.4
5906.8
5954
6031.2
6011.2
6059.8
6091.6
6088
6082.2
6108
6151.4
6187
6190
6152.2
6183.8
6222.8
6165.8
6223.4
6292.8
6320.6
6344
6391.2
6443.4
6504
6520.2
6518.8
6563.8
6614
6555.6
6601.8
6632.4
6657.8
6674.4
6687
6697.6
6732
6736.4
6745.8
6805.2
6850.4
6807.2
6844.6
6850.8
6848.2
6837.8
6857.6
6900.8
6940.8
6937.4
6950.4
6978.8
6997.8
6934.8
6946.8
6956.2
6968.2
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA




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=300835&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=300835&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300835&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
10.97686810.52120
20.95384610.27320
30.93110710.02830
40.9081739.78130
50.8833369.51380
60.8587169.24860
70.8342298.98490
80.8094358.71790
90.7839378.44330
100.7587818.17230
110.7343617.90930
120.7102977.65010
130.6849977.37760
140.6593037.10090
150.6338216.82650
160.6086456.55530
170.5819156.26740
180.5558955.98720
190.530475.71330
200.5046825.43560
210.4784865.15351e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.976868 & 10.5212 & 0 \tabularnewline
2 & 0.953846 & 10.2732 & 0 \tabularnewline
3 & 0.931107 & 10.0283 & 0 \tabularnewline
4 & 0.908173 & 9.7813 & 0 \tabularnewline
5 & 0.883336 & 9.5138 & 0 \tabularnewline
6 & 0.858716 & 9.2486 & 0 \tabularnewline
7 & 0.834229 & 8.9849 & 0 \tabularnewline
8 & 0.809435 & 8.7179 & 0 \tabularnewline
9 & 0.783937 & 8.4433 & 0 \tabularnewline
10 & 0.758781 & 8.1723 & 0 \tabularnewline
11 & 0.734361 & 7.9093 & 0 \tabularnewline
12 & 0.710297 & 7.6501 & 0 \tabularnewline
13 & 0.684997 & 7.3776 & 0 \tabularnewline
14 & 0.659303 & 7.1009 & 0 \tabularnewline
15 & 0.633821 & 6.8265 & 0 \tabularnewline
16 & 0.608645 & 6.5553 & 0 \tabularnewline
17 & 0.581915 & 6.2674 & 0 \tabularnewline
18 & 0.555895 & 5.9872 & 0 \tabularnewline
19 & 0.53047 & 5.7133 & 0 \tabularnewline
20 & 0.504682 & 5.4356 & 0 \tabularnewline
21 & 0.478486 & 5.1535 & 1e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300835&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]0.976868[/C][C]10.5212[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.953846[/C][C]10.2732[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.931107[/C][C]10.0283[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.908173[/C][C]9.7813[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.883336[/C][C]9.5138[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.858716[/C][C]9.2486[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.834229[/C][C]8.9849[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.809435[/C][C]8.7179[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.783937[/C][C]8.4433[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.758781[/C][C]8.1723[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.734361[/C][C]7.9093[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.710297[/C][C]7.6501[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.684997[/C][C]7.3776[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.659303[/C][C]7.1009[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.633821[/C][C]6.8265[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.608645[/C][C]6.5553[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.581915[/C][C]6.2674[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.555895[/C][C]5.9872[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.53047[/C][C]5.7133[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.504682[/C][C]5.4356[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.478486[/C][C]5.1535[/C][C]1e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300835&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300835&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
10.97686810.52120
20.95384610.27320
30.93110710.02830
40.9081739.78130
50.8833369.51380
60.8587169.24860
70.8342298.98490
80.8094358.71790
90.7839378.44330
100.7587818.17230
110.7343617.90930
120.7102977.65010
130.6849977.37760
140.6593037.10090
150.6338216.82650
160.6086456.55530
170.5819156.26740
180.5558955.98720
190.530475.71330
200.5046825.43560
210.4784865.15351e-06







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97686810.52120
2-0.009322-0.10040.460098
3-0.005568-0.060.476142
4-0.016012-0.17250.43169
5-0.053636-0.57770.2823
6-0.008715-0.09390.462689
7-0.01081-0.11640.453756
8-0.019712-0.21230.416119
9-0.027526-0.29650.383702
10-0.007354-0.07920.468501
110.0015380.01660.493407
12-0.005409-0.05830.476821
13-0.03991-0.42980.334053
14-0.024581-0.26470.395838
15-0.012543-0.13510.446386
16-0.009053-0.09750.461248
17-0.047407-0.51060.305303
18-0.001329-0.01430.494301
19-0.004987-0.05370.478629
20-0.02435-0.26230.396793
21-0.022314-0.24030.405251

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.976868 & 10.5212 & 0 \tabularnewline
2 & -0.009322 & -0.1004 & 0.460098 \tabularnewline
3 & -0.005568 & -0.06 & 0.476142 \tabularnewline
4 & -0.016012 & -0.1725 & 0.43169 \tabularnewline
5 & -0.053636 & -0.5777 & 0.2823 \tabularnewline
6 & -0.008715 & -0.0939 & 0.462689 \tabularnewline
7 & -0.01081 & -0.1164 & 0.453756 \tabularnewline
8 & -0.019712 & -0.2123 & 0.416119 \tabularnewline
9 & -0.027526 & -0.2965 & 0.383702 \tabularnewline
10 & -0.007354 & -0.0792 & 0.468501 \tabularnewline
11 & 0.001538 & 0.0166 & 0.493407 \tabularnewline
12 & -0.005409 & -0.0583 & 0.476821 \tabularnewline
13 & -0.03991 & -0.4298 & 0.334053 \tabularnewline
14 & -0.024581 & -0.2647 & 0.395838 \tabularnewline
15 & -0.012543 & -0.1351 & 0.446386 \tabularnewline
16 & -0.009053 & -0.0975 & 0.461248 \tabularnewline
17 & -0.047407 & -0.5106 & 0.305303 \tabularnewline
18 & -0.001329 & -0.0143 & 0.494301 \tabularnewline
19 & -0.004987 & -0.0537 & 0.478629 \tabularnewline
20 & -0.02435 & -0.2623 & 0.396793 \tabularnewline
21 & -0.022314 & -0.2403 & 0.405251 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300835&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]0.976868[/C][C]10.5212[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.009322[/C][C]-0.1004[/C][C]0.460098[/C][/ROW]
[ROW][C]3[/C][C]-0.005568[/C][C]-0.06[/C][C]0.476142[/C][/ROW]
[ROW][C]4[/C][C]-0.016012[/C][C]-0.1725[/C][C]0.43169[/C][/ROW]
[ROW][C]5[/C][C]-0.053636[/C][C]-0.5777[/C][C]0.2823[/C][/ROW]
[ROW][C]6[/C][C]-0.008715[/C][C]-0.0939[/C][C]0.462689[/C][/ROW]
[ROW][C]7[/C][C]-0.01081[/C][C]-0.1164[/C][C]0.453756[/C][/ROW]
[ROW][C]8[/C][C]-0.019712[/C][C]-0.2123[/C][C]0.416119[/C][/ROW]
[ROW][C]9[/C][C]-0.027526[/C][C]-0.2965[/C][C]0.383702[/C][/ROW]
[ROW][C]10[/C][C]-0.007354[/C][C]-0.0792[/C][C]0.468501[/C][/ROW]
[ROW][C]11[/C][C]0.001538[/C][C]0.0166[/C][C]0.493407[/C][/ROW]
[ROW][C]12[/C][C]-0.005409[/C][C]-0.0583[/C][C]0.476821[/C][/ROW]
[ROW][C]13[/C][C]-0.03991[/C][C]-0.4298[/C][C]0.334053[/C][/ROW]
[ROW][C]14[/C][C]-0.024581[/C][C]-0.2647[/C][C]0.395838[/C][/ROW]
[ROW][C]15[/C][C]-0.012543[/C][C]-0.1351[/C][C]0.446386[/C][/ROW]
[ROW][C]16[/C][C]-0.009053[/C][C]-0.0975[/C][C]0.461248[/C][/ROW]
[ROW][C]17[/C][C]-0.047407[/C][C]-0.5106[/C][C]0.305303[/C][/ROW]
[ROW][C]18[/C][C]-0.001329[/C][C]-0.0143[/C][C]0.494301[/C][/ROW]
[ROW][C]19[/C][C]-0.004987[/C][C]-0.0537[/C][C]0.478629[/C][/ROW]
[ROW][C]20[/C][C]-0.02435[/C][C]-0.2623[/C][C]0.396793[/C][/ROW]
[ROW][C]21[/C][C]-0.022314[/C][C]-0.2403[/C][C]0.405251[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300835&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300835&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
10.97686810.52120
2-0.009322-0.10040.460098
3-0.005568-0.060.476142
4-0.016012-0.17250.43169
5-0.053636-0.57770.2823
6-0.008715-0.09390.462689
7-0.01081-0.11640.453756
8-0.019712-0.21230.416119
9-0.027526-0.29650.383702
10-0.007354-0.07920.468501
110.0015380.01660.493407
12-0.005409-0.05830.476821
13-0.03991-0.42980.334053
14-0.024581-0.26470.395838
15-0.012543-0.13510.446386
16-0.009053-0.09750.461248
17-0.047407-0.51060.305303
18-0.001329-0.01430.494301
19-0.004987-0.05370.478629
20-0.02435-0.26230.396793
21-0.022314-0.24030.405251



Parameters (Session):
par1 = Default ; par2 = 2.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 2.0 ; 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')