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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 16:46:42 +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/t148198965455he9ozbatekqdd.htm/, Retrieved Fri, 01 Nov 2024 03:41:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300861, Retrieved Fri, 01 Nov 2024 03:41:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelation F...] [2016-12-17 15:46:42] [153c3207812fd13fe5ceee3276565119] [Current]
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Dataseries X:
200
2100
1250
2250
5850
4900
4700
3650
4950
10250
3850
3050
9150
8650
7350
7050
8150
9200
7050
11800
10950
13200
5250
14500
8000
8350
8750
7750
7300
9750
7100
9500
7050
7300
5900
8350
8050
4200
7300
6900
5300
9600
7900
4150
4900
8100
7200
6700
7350
4650
7100




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=300861&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=300861&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300861&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
1-0.541587-3.82960.000179
2-0.001451-0.01030.495927
30.0337230.23850.40625
40.1428281.00990.158692
5-0.13736-0.97130.168041
60.0821960.58120.281854
7-0.057312-0.40530.343507
80.1104760.78120.219188
9-0.147906-1.04590.150329
100.0973750.68850.247145
11-0.058865-0.41620.339508
120.1961921.38730.085753
13-0.226643-1.60260.05766
140.0270050.1910.424667
150.1045340.73920.231631
16-0.043675-0.30880.379368
170.002560.01810.492814

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.541587 & -3.8296 & 0.000179 \tabularnewline
2 & -0.001451 & -0.0103 & 0.495927 \tabularnewline
3 & 0.033723 & 0.2385 & 0.40625 \tabularnewline
4 & 0.142828 & 1.0099 & 0.158692 \tabularnewline
5 & -0.13736 & -0.9713 & 0.168041 \tabularnewline
6 & 0.082196 & 0.5812 & 0.281854 \tabularnewline
7 & -0.057312 & -0.4053 & 0.343507 \tabularnewline
8 & 0.110476 & 0.7812 & 0.219188 \tabularnewline
9 & -0.147906 & -1.0459 & 0.150329 \tabularnewline
10 & 0.097375 & 0.6885 & 0.247145 \tabularnewline
11 & -0.058865 & -0.4162 & 0.339508 \tabularnewline
12 & 0.196192 & 1.3873 & 0.085753 \tabularnewline
13 & -0.226643 & -1.6026 & 0.05766 \tabularnewline
14 & 0.027005 & 0.191 & 0.424667 \tabularnewline
15 & 0.104534 & 0.7392 & 0.231631 \tabularnewline
16 & -0.043675 & -0.3088 & 0.379368 \tabularnewline
17 & 0.00256 & 0.0181 & 0.492814 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300861&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]-0.541587[/C][C]-3.8296[/C][C]0.000179[/C][/ROW]
[ROW][C]2[/C][C]-0.001451[/C][C]-0.0103[/C][C]0.495927[/C][/ROW]
[ROW][C]3[/C][C]0.033723[/C][C]0.2385[/C][C]0.40625[/C][/ROW]
[ROW][C]4[/C][C]0.142828[/C][C]1.0099[/C][C]0.158692[/C][/ROW]
[ROW][C]5[/C][C]-0.13736[/C][C]-0.9713[/C][C]0.168041[/C][/ROW]
[ROW][C]6[/C][C]0.082196[/C][C]0.5812[/C][C]0.281854[/C][/ROW]
[ROW][C]7[/C][C]-0.057312[/C][C]-0.4053[/C][C]0.343507[/C][/ROW]
[ROW][C]8[/C][C]0.110476[/C][C]0.7812[/C][C]0.219188[/C][/ROW]
[ROW][C]9[/C][C]-0.147906[/C][C]-1.0459[/C][C]0.150329[/C][/ROW]
[ROW][C]10[/C][C]0.097375[/C][C]0.6885[/C][C]0.247145[/C][/ROW]
[ROW][C]11[/C][C]-0.058865[/C][C]-0.4162[/C][C]0.339508[/C][/ROW]
[ROW][C]12[/C][C]0.196192[/C][C]1.3873[/C][C]0.085753[/C][/ROW]
[ROW][C]13[/C][C]-0.226643[/C][C]-1.6026[/C][C]0.05766[/C][/ROW]
[ROW][C]14[/C][C]0.027005[/C][C]0.191[/C][C]0.424667[/C][/ROW]
[ROW][C]15[/C][C]0.104534[/C][C]0.7392[/C][C]0.231631[/C][/ROW]
[ROW][C]16[/C][C]-0.043675[/C][C]-0.3088[/C][C]0.379368[/C][/ROW]
[ROW][C]17[/C][C]0.00256[/C][C]0.0181[/C][C]0.492814[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300861&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300861&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
1-0.541587-3.82960.000179
2-0.001451-0.01030.495927
30.0337230.23850.40625
40.1428281.00990.158692
5-0.13736-0.97130.168041
60.0821960.58120.281854
7-0.057312-0.40530.343507
80.1104760.78120.219188
9-0.147906-1.04590.150329
100.0973750.68850.247145
11-0.058865-0.41620.339508
120.1961921.38730.085753
13-0.226643-1.60260.05766
140.0270050.1910.424667
150.1045340.73920.231631
16-0.043675-0.30880.379368
170.002560.01810.492814







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.541587-3.82960.000179
2-0.417114-2.94940.002416
3-0.331136-2.34150.011617
4-0.013362-0.09450.46255
50.0150540.10650.457825
60.1405570.99390.162531
70.0764060.54030.295704
80.1818661.2860.102185
90.0130550.09230.463408
10-0.007408-0.05240.479216
11-0.107759-0.7620.224829
120.1988391.4060.082954
130.1173910.83010.20522
14-0.051903-0.3670.35758
15-0.012213-0.08640.465764
16-0.099276-0.7020.24297
170.040810.28860.38705

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.541587 & -3.8296 & 0.000179 \tabularnewline
2 & -0.417114 & -2.9494 & 0.002416 \tabularnewline
3 & -0.331136 & -2.3415 & 0.011617 \tabularnewline
4 & -0.013362 & -0.0945 & 0.46255 \tabularnewline
5 & 0.015054 & 0.1065 & 0.457825 \tabularnewline
6 & 0.140557 & 0.9939 & 0.162531 \tabularnewline
7 & 0.076406 & 0.5403 & 0.295704 \tabularnewline
8 & 0.181866 & 1.286 & 0.102185 \tabularnewline
9 & 0.013055 & 0.0923 & 0.463408 \tabularnewline
10 & -0.007408 & -0.0524 & 0.479216 \tabularnewline
11 & -0.107759 & -0.762 & 0.224829 \tabularnewline
12 & 0.198839 & 1.406 & 0.082954 \tabularnewline
13 & 0.117391 & 0.8301 & 0.20522 \tabularnewline
14 & -0.051903 & -0.367 & 0.35758 \tabularnewline
15 & -0.012213 & -0.0864 & 0.465764 \tabularnewline
16 & -0.099276 & -0.702 & 0.24297 \tabularnewline
17 & 0.04081 & 0.2886 & 0.38705 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300861&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]-0.541587[/C][C]-3.8296[/C][C]0.000179[/C][/ROW]
[ROW][C]2[/C][C]-0.417114[/C][C]-2.9494[/C][C]0.002416[/C][/ROW]
[ROW][C]3[/C][C]-0.331136[/C][C]-2.3415[/C][C]0.011617[/C][/ROW]
[ROW][C]4[/C][C]-0.013362[/C][C]-0.0945[/C][C]0.46255[/C][/ROW]
[ROW][C]5[/C][C]0.015054[/C][C]0.1065[/C][C]0.457825[/C][/ROW]
[ROW][C]6[/C][C]0.140557[/C][C]0.9939[/C][C]0.162531[/C][/ROW]
[ROW][C]7[/C][C]0.076406[/C][C]0.5403[/C][C]0.295704[/C][/ROW]
[ROW][C]8[/C][C]0.181866[/C][C]1.286[/C][C]0.102185[/C][/ROW]
[ROW][C]9[/C][C]0.013055[/C][C]0.0923[/C][C]0.463408[/C][/ROW]
[ROW][C]10[/C][C]-0.007408[/C][C]-0.0524[/C][C]0.479216[/C][/ROW]
[ROW][C]11[/C][C]-0.107759[/C][C]-0.762[/C][C]0.224829[/C][/ROW]
[ROW][C]12[/C][C]0.198839[/C][C]1.406[/C][C]0.082954[/C][/ROW]
[ROW][C]13[/C][C]0.117391[/C][C]0.8301[/C][C]0.20522[/C][/ROW]
[ROW][C]14[/C][C]-0.051903[/C][C]-0.367[/C][C]0.35758[/C][/ROW]
[ROW][C]15[/C][C]-0.012213[/C][C]-0.0864[/C][C]0.465764[/C][/ROW]
[ROW][C]16[/C][C]-0.099276[/C][C]-0.702[/C][C]0.24297[/C][/ROW]
[ROW][C]17[/C][C]0.04081[/C][C]0.2886[/C][C]0.38705[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300861&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300861&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
1-0.541587-3.82960.000179
2-0.417114-2.94940.002416
3-0.331136-2.34150.011617
4-0.013362-0.09450.46255
50.0150540.10650.457825
60.1405570.99390.162531
70.0764060.54030.295704
80.1818661.2860.102185
90.0130550.09230.463408
10-0.007408-0.05240.479216
11-0.107759-0.7620.224829
120.1988391.4060.082954
130.1173910.83010.20522
14-0.051903-0.3670.35758
15-0.012213-0.08640.465764
16-0.099276-0.7020.24297
170.040810.28860.38705



Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 1 ; 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):
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')