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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 10 Aug 2015 12:21:50 +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/2015/Aug/10/t1439205724xcs24j16lg1n6ri.htm/, Retrieved Sun, 19 May 2024 03:09:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279979, Retrieved Sun, 19 May 2024 03:09:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Histogram] [omzetontwikkeling...] [2014-09-24 09:10:11] [3d50c3f1d1505d45371c80c331b9aa00]
- R  D  [Histogram] [] [2015-07-23 12:50:11] [74be16979710d4c4e7c6647856088456]
- RMPD    [Harrell-Davis Quantiles] [] [2015-08-10 08:16:05] [74be16979710d4c4e7c6647856088456]
- RMP       [Mean versus Median] [] [2015-08-10 09:14:26] [74be16979710d4c4e7c6647856088456]
- RMP         [Mean Plot] [] [2015-08-10 09:32:31] [74be16979710d4c4e7c6647856088456]
- RMP             [(Partial) Autocorrelation Function] [] [2015-08-10 11:21:50] [d41d8cd98f00b204e9800998ecf8427e] [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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279979&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279979&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279979&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3366633.49870.00034
20.1690571.75690.040885
3-0.231794-2.40890.008847
4-0.382786-3.9786.3e-05
5-0.131504-1.36660.087291
6-0.338556-3.51840.000318
7-0.077437-0.80480.211365
8-0.354641-3.68550.000179
9-0.217904-2.26450.012769
100.1332671.3850.084461
110.2916383.03080.001527
120.8222228.54480
130.3196633.3220.00061
140.1907961.98280.024964
15-0.211977-2.20290.014862
16-0.378625-3.93487.4e-05
17-0.123426-1.28270.101174
18-0.302499-3.14370.001077
19-0.043995-0.45720.324218
20-0.271734-2.82390.002825

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.336663 & 3.4987 & 0.00034 \tabularnewline
2 & 0.169057 & 1.7569 & 0.040885 \tabularnewline
3 & -0.231794 & -2.4089 & 0.008847 \tabularnewline
4 & -0.382786 & -3.978 & 6.3e-05 \tabularnewline
5 & -0.131504 & -1.3666 & 0.087291 \tabularnewline
6 & -0.338556 & -3.5184 & 0.000318 \tabularnewline
7 & -0.077437 & -0.8048 & 0.211365 \tabularnewline
8 & -0.354641 & -3.6855 & 0.000179 \tabularnewline
9 & -0.217904 & -2.2645 & 0.012769 \tabularnewline
10 & 0.133267 & 1.385 & 0.084461 \tabularnewline
11 & 0.291638 & 3.0308 & 0.001527 \tabularnewline
12 & 0.822222 & 8.5448 & 0 \tabularnewline
13 & 0.319663 & 3.322 & 0.00061 \tabularnewline
14 & 0.190796 & 1.9828 & 0.024964 \tabularnewline
15 & -0.211977 & -2.2029 & 0.014862 \tabularnewline
16 & -0.378625 & -3.9348 & 7.4e-05 \tabularnewline
17 & -0.123426 & -1.2827 & 0.101174 \tabularnewline
18 & -0.302499 & -3.1437 & 0.001077 \tabularnewline
19 & -0.043995 & -0.4572 & 0.324218 \tabularnewline
20 & -0.271734 & -2.8239 & 0.002825 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279979&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]0.336663[/C][C]3.4987[/C][C]0.00034[/C][/ROW]
[ROW][C]2[/C][C]0.169057[/C][C]1.7569[/C][C]0.040885[/C][/ROW]
[ROW][C]3[/C][C]-0.231794[/C][C]-2.4089[/C][C]0.008847[/C][/ROW]
[ROW][C]4[/C][C]-0.382786[/C][C]-3.978[/C][C]6.3e-05[/C][/ROW]
[ROW][C]5[/C][C]-0.131504[/C][C]-1.3666[/C][C]0.087291[/C][/ROW]
[ROW][C]6[/C][C]-0.338556[/C][C]-3.5184[/C][C]0.000318[/C][/ROW]
[ROW][C]7[/C][C]-0.077437[/C][C]-0.8048[/C][C]0.211365[/C][/ROW]
[ROW][C]8[/C][C]-0.354641[/C][C]-3.6855[/C][C]0.000179[/C][/ROW]
[ROW][C]9[/C][C]-0.217904[/C][C]-2.2645[/C][C]0.012769[/C][/ROW]
[ROW][C]10[/C][C]0.133267[/C][C]1.385[/C][C]0.084461[/C][/ROW]
[ROW][C]11[/C][C]0.291638[/C][C]3.0308[/C][C]0.001527[/C][/ROW]
[ROW][C]12[/C][C]0.822222[/C][C]8.5448[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.319663[/C][C]3.322[/C][C]0.00061[/C][/ROW]
[ROW][C]14[/C][C]0.190796[/C][C]1.9828[/C][C]0.024964[/C][/ROW]
[ROW][C]15[/C][C]-0.211977[/C][C]-2.2029[/C][C]0.014862[/C][/ROW]
[ROW][C]16[/C][C]-0.378625[/C][C]-3.9348[/C][C]7.4e-05[/C][/ROW]
[ROW][C]17[/C][C]-0.123426[/C][C]-1.2827[/C][C]0.101174[/C][/ROW]
[ROW][C]18[/C][C]-0.302499[/C][C]-3.1437[/C][C]0.001077[/C][/ROW]
[ROW][C]19[/C][C]-0.043995[/C][C]-0.4572[/C][C]0.324218[/C][/ROW]
[ROW][C]20[/C][C]-0.271734[/C][C]-2.8239[/C][C]0.002825[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279979&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279979&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
10.3366633.49870.00034
20.1690571.75690.040885
3-0.231794-2.40890.008847
4-0.382786-3.9786.3e-05
5-0.131504-1.36660.087291
6-0.338556-3.51840.000318
7-0.077437-0.80480.211365
8-0.354641-3.68550.000179
9-0.217904-2.26450.012769
100.1332671.3850.084461
110.2916383.03080.001527
120.8222228.54480
130.3196633.3220.00061
140.1907961.98280.024964
15-0.211977-2.20290.014862
16-0.378625-3.93487.4e-05
17-0.123426-1.28270.101174
18-0.302499-3.14370.001077
19-0.043995-0.45720.324218
20-0.271734-2.82390.002825







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3366633.49870.00034
20.0628380.6530.257563
3-0.34681-3.60420.000238
4-0.279258-2.90210.002247
50.2070782.1520.016812
6-0.405723-4.21642.6e-05
7-0.104224-1.08310.140582
8-0.444314-4.61745e-06
9-0.286191-2.97420.001812
100.1599921.66270.049637
110.1236311.28480.100804
120.5711325.93540
13-0.098578-1.02450.153955
14-0.005205-0.05410.47848
150.0266640.27710.391115
16-0.017876-0.18580.426486
170.121991.26780.103805
180.018680.19410.423221
19-0.015145-0.15740.437615
200.1667231.73260.043007

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.336663 & 3.4987 & 0.00034 \tabularnewline
2 & 0.062838 & 0.653 & 0.257563 \tabularnewline
3 & -0.34681 & -3.6042 & 0.000238 \tabularnewline
4 & -0.279258 & -2.9021 & 0.002247 \tabularnewline
5 & 0.207078 & 2.152 & 0.016812 \tabularnewline
6 & -0.405723 & -4.2164 & 2.6e-05 \tabularnewline
7 & -0.104224 & -1.0831 & 0.140582 \tabularnewline
8 & -0.444314 & -4.6174 & 5e-06 \tabularnewline
9 & -0.286191 & -2.9742 & 0.001812 \tabularnewline
10 & 0.159992 & 1.6627 & 0.049637 \tabularnewline
11 & 0.123631 & 1.2848 & 0.100804 \tabularnewline
12 & 0.571132 & 5.9354 & 0 \tabularnewline
13 & -0.098578 & -1.0245 & 0.153955 \tabularnewline
14 & -0.005205 & -0.0541 & 0.47848 \tabularnewline
15 & 0.026664 & 0.2771 & 0.391115 \tabularnewline
16 & -0.017876 & -0.1858 & 0.426486 \tabularnewline
17 & 0.12199 & 1.2678 & 0.103805 \tabularnewline
18 & 0.01868 & 0.1941 & 0.423221 \tabularnewline
19 & -0.015145 & -0.1574 & 0.437615 \tabularnewline
20 & 0.166723 & 1.7326 & 0.043007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279979&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]0.336663[/C][C]3.4987[/C][C]0.00034[/C][/ROW]
[ROW][C]2[/C][C]0.062838[/C][C]0.653[/C][C]0.257563[/C][/ROW]
[ROW][C]3[/C][C]-0.34681[/C][C]-3.6042[/C][C]0.000238[/C][/ROW]
[ROW][C]4[/C][C]-0.279258[/C][C]-2.9021[/C][C]0.002247[/C][/ROW]
[ROW][C]5[/C][C]0.207078[/C][C]2.152[/C][C]0.016812[/C][/ROW]
[ROW][C]6[/C][C]-0.405723[/C][C]-4.2164[/C][C]2.6e-05[/C][/ROW]
[ROW][C]7[/C][C]-0.104224[/C][C]-1.0831[/C][C]0.140582[/C][/ROW]
[ROW][C]8[/C][C]-0.444314[/C][C]-4.6174[/C][C]5e-06[/C][/ROW]
[ROW][C]9[/C][C]-0.286191[/C][C]-2.9742[/C][C]0.001812[/C][/ROW]
[ROW][C]10[/C][C]0.159992[/C][C]1.6627[/C][C]0.049637[/C][/ROW]
[ROW][C]11[/C][C]0.123631[/C][C]1.2848[/C][C]0.100804[/C][/ROW]
[ROW][C]12[/C][C]0.571132[/C][C]5.9354[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.098578[/C][C]-1.0245[/C][C]0.153955[/C][/ROW]
[ROW][C]14[/C][C]-0.005205[/C][C]-0.0541[/C][C]0.47848[/C][/ROW]
[ROW][C]15[/C][C]0.026664[/C][C]0.2771[/C][C]0.391115[/C][/ROW]
[ROW][C]16[/C][C]-0.017876[/C][C]-0.1858[/C][C]0.426486[/C][/ROW]
[ROW][C]17[/C][C]0.12199[/C][C]1.2678[/C][C]0.103805[/C][/ROW]
[ROW][C]18[/C][C]0.01868[/C][C]0.1941[/C][C]0.423221[/C][/ROW]
[ROW][C]19[/C][C]-0.015145[/C][C]-0.1574[/C][C]0.437615[/C][/ROW]
[ROW][C]20[/C][C]0.166723[/C][C]1.7326[/C][C]0.043007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279979&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279979&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
10.3366633.49870.00034
20.0628380.6530.257563
3-0.34681-3.60420.000238
4-0.279258-2.90210.002247
50.2070782.1520.016812
6-0.405723-4.21642.6e-05
7-0.104224-1.08310.140582
8-0.444314-4.61745e-06
9-0.286191-2.97420.001812
100.1599921.66270.049637
110.1236311.28480.100804
120.5711325.93540
13-0.098578-1.02450.153955
14-0.005205-0.05410.47848
150.0266640.27710.391115
16-0.017876-0.18580.426486
170.121991.26780.103805
180.018680.19410.423221
19-0.015145-0.15740.437615
200.1667231.73260.043007



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)
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,hyperlink('basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),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,hyperlink('basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),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')