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 computationTue, 13 Dec 2016 16:21:54 +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/13/t1481642679v8ze4yygayvb1hv.htm/, Retrieved Fri, 01 Nov 2024 03:31:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=299151, Retrieved Fri, 01 Nov 2024 03:31:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact84
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Partial autocorre...] [2016-12-13 15:21:54] [94c1b173d9287822f5e2740a4a602bdd] [Current]
Feedback Forum

Post a new message
Dataseries X:
2880
2160
2040
2360
2160
3300
2700
3900
4620
3860
4040
3460
2820
2040
2100
1820
1840
2680
3060
3540
4700
4880
3960
2440
2440
2340
2340
2220
1560
2940
2280
2400
2700
3100
3160
3520
2300
2680
2140
2320
1940
2260
2300
2980
2800
3060
3140
2740
2480
1720
2060
1920
2000
2820
2440
2700
2880
3100
3060
2040
1880
2180
1820
1700
1700
1680
2240
2400
2920
3380
2700
1900
1960
2040
1860
1720
2340
2060
2200
2520
2700
2000
2120
1780
1820
1480
1780
1600
1720
2100
2000
2420
2660
3140
2280
2220
1860
1980
1520
1540
1660
2500
1660
2220
2160
2540
2540
2340




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=299151&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=299151&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299151&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
10.2988772.92840.002128
20.0975820.95610.17071
3-0.07028-0.68860.246367
4-0.112043-1.09780.137521
5-0.157806-1.54620.062676
6-0.121894-1.19430.117649
7-0.098858-0.96860.167588
80.1152011.12870.130911
9-0.036456-0.35720.360867
10-0.053489-0.52410.300715
11-0.184994-1.81260.036513
12-0.448646-4.39581.4e-05
13-0.038171-0.3740.354614
140.0037570.03680.485356
150.1126361.10360.136261
160.1580081.54820.062438
170.207682.03480.022312
180.1738521.70340.045864
190.0598710.58660.27942
20-0.209767-2.05530.021284

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.298877 & 2.9284 & 0.002128 \tabularnewline
2 & 0.097582 & 0.9561 & 0.17071 \tabularnewline
3 & -0.07028 & -0.6886 & 0.246367 \tabularnewline
4 & -0.112043 & -1.0978 & 0.137521 \tabularnewline
5 & -0.157806 & -1.5462 & 0.062676 \tabularnewline
6 & -0.121894 & -1.1943 & 0.117649 \tabularnewline
7 & -0.098858 & -0.9686 & 0.167588 \tabularnewline
8 & 0.115201 & 1.1287 & 0.130911 \tabularnewline
9 & -0.036456 & -0.3572 & 0.360867 \tabularnewline
10 & -0.053489 & -0.5241 & 0.300715 \tabularnewline
11 & -0.184994 & -1.8126 & 0.036513 \tabularnewline
12 & -0.448646 & -4.3958 & 1.4e-05 \tabularnewline
13 & -0.038171 & -0.374 & 0.354614 \tabularnewline
14 & 0.003757 & 0.0368 & 0.485356 \tabularnewline
15 & 0.112636 & 1.1036 & 0.136261 \tabularnewline
16 & 0.158008 & 1.5482 & 0.062438 \tabularnewline
17 & 0.20768 & 2.0348 & 0.022312 \tabularnewline
18 & 0.173852 & 1.7034 & 0.045864 \tabularnewline
19 & 0.059871 & 0.5866 & 0.27942 \tabularnewline
20 & -0.209767 & -2.0553 & 0.021284 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299151&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]0.298877[/C][C]2.9284[/C][C]0.002128[/C][/ROW]
[ROW][C]2[/C][C]0.097582[/C][C]0.9561[/C][C]0.17071[/C][/ROW]
[ROW][C]3[/C][C]-0.07028[/C][C]-0.6886[/C][C]0.246367[/C][/ROW]
[ROW][C]4[/C][C]-0.112043[/C][C]-1.0978[/C][C]0.137521[/C][/ROW]
[ROW][C]5[/C][C]-0.157806[/C][C]-1.5462[/C][C]0.062676[/C][/ROW]
[ROW][C]6[/C][C]-0.121894[/C][C]-1.1943[/C][C]0.117649[/C][/ROW]
[ROW][C]7[/C][C]-0.098858[/C][C]-0.9686[/C][C]0.167588[/C][/ROW]
[ROW][C]8[/C][C]0.115201[/C][C]1.1287[/C][C]0.130911[/C][/ROW]
[ROW][C]9[/C][C]-0.036456[/C][C]-0.3572[/C][C]0.360867[/C][/ROW]
[ROW][C]10[/C][C]-0.053489[/C][C]-0.5241[/C][C]0.300715[/C][/ROW]
[ROW][C]11[/C][C]-0.184994[/C][C]-1.8126[/C][C]0.036513[/C][/ROW]
[ROW][C]12[/C][C]-0.448646[/C][C]-4.3958[/C][C]1.4e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.038171[/C][C]-0.374[/C][C]0.354614[/C][/ROW]
[ROW][C]14[/C][C]0.003757[/C][C]0.0368[/C][C]0.485356[/C][/ROW]
[ROW][C]15[/C][C]0.112636[/C][C]1.1036[/C][C]0.136261[/C][/ROW]
[ROW][C]16[/C][C]0.158008[/C][C]1.5482[/C][C]0.062438[/C][/ROW]
[ROW][C]17[/C][C]0.20768[/C][C]2.0348[/C][C]0.022312[/C][/ROW]
[ROW][C]18[/C][C]0.173852[/C][C]1.7034[/C][C]0.045864[/C][/ROW]
[ROW][C]19[/C][C]0.059871[/C][C]0.5866[/C][C]0.27942[/C][/ROW]
[ROW][C]20[/C][C]-0.209767[/C][C]-2.0553[/C][C]0.021284[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299151&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299151&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
10.2988772.92840.002128
20.0975820.95610.17071
3-0.07028-0.68860.246367
4-0.112043-1.09780.137521
5-0.157806-1.54620.062676
6-0.121894-1.19430.117649
7-0.098858-0.96860.167588
80.1152011.12870.130911
9-0.036456-0.35720.360867
10-0.053489-0.52410.300715
11-0.184994-1.81260.036513
12-0.448646-4.39581.4e-05
13-0.038171-0.3740.354614
140.0037570.03680.485356
150.1126361.10360.136261
160.1580081.54820.062438
170.207682.03480.022312
180.1738521.70340.045864
190.0598710.58660.27942
20-0.209767-2.05530.021284







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2988772.92840.002128
20.0090640.08880.464708
3-0.111893-1.09630.137839
4-0.068764-0.67370.251045
5-0.103609-1.01520.156292
6-0.050482-0.49460.311001
7-0.055226-0.54110.294845
80.1592471.56030.06099
9-0.151262-1.48210.0708
10-0.068937-0.67540.250508
11-0.173364-1.69860.046315
12-0.443101-4.34151.8e-05
130.2809562.75280.003533
14-0.069623-0.68220.248389
150.0445410.43640.331759
160.0257250.25210.400768
170.0298680.29260.385211
180.0574590.5630.287379
19-0.080587-0.78960.215858
20-0.072191-0.70730.24054

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.298877 & 2.9284 & 0.002128 \tabularnewline
2 & 0.009064 & 0.0888 & 0.464708 \tabularnewline
3 & -0.111893 & -1.0963 & 0.137839 \tabularnewline
4 & -0.068764 & -0.6737 & 0.251045 \tabularnewline
5 & -0.103609 & -1.0152 & 0.156292 \tabularnewline
6 & -0.050482 & -0.4946 & 0.311001 \tabularnewline
7 & -0.055226 & -0.5411 & 0.294845 \tabularnewline
8 & 0.159247 & 1.5603 & 0.06099 \tabularnewline
9 & -0.151262 & -1.4821 & 0.0708 \tabularnewline
10 & -0.068937 & -0.6754 & 0.250508 \tabularnewline
11 & -0.173364 & -1.6986 & 0.046315 \tabularnewline
12 & -0.443101 & -4.3415 & 1.8e-05 \tabularnewline
13 & 0.280956 & 2.7528 & 0.003533 \tabularnewline
14 & -0.069623 & -0.6822 & 0.248389 \tabularnewline
15 & 0.044541 & 0.4364 & 0.331759 \tabularnewline
16 & 0.025725 & 0.2521 & 0.400768 \tabularnewline
17 & 0.029868 & 0.2926 & 0.385211 \tabularnewline
18 & 0.057459 & 0.563 & 0.287379 \tabularnewline
19 & -0.080587 & -0.7896 & 0.215858 \tabularnewline
20 & -0.072191 & -0.7073 & 0.24054 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=299151&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]0.298877[/C][C]2.9284[/C][C]0.002128[/C][/ROW]
[ROW][C]2[/C][C]0.009064[/C][C]0.0888[/C][C]0.464708[/C][/ROW]
[ROW][C]3[/C][C]-0.111893[/C][C]-1.0963[/C][C]0.137839[/C][/ROW]
[ROW][C]4[/C][C]-0.068764[/C][C]-0.6737[/C][C]0.251045[/C][/ROW]
[ROW][C]5[/C][C]-0.103609[/C][C]-1.0152[/C][C]0.156292[/C][/ROW]
[ROW][C]6[/C][C]-0.050482[/C][C]-0.4946[/C][C]0.311001[/C][/ROW]
[ROW][C]7[/C][C]-0.055226[/C][C]-0.5411[/C][C]0.294845[/C][/ROW]
[ROW][C]8[/C][C]0.159247[/C][C]1.5603[/C][C]0.06099[/C][/ROW]
[ROW][C]9[/C][C]-0.151262[/C][C]-1.4821[/C][C]0.0708[/C][/ROW]
[ROW][C]10[/C][C]-0.068937[/C][C]-0.6754[/C][C]0.250508[/C][/ROW]
[ROW][C]11[/C][C]-0.173364[/C][C]-1.6986[/C][C]0.046315[/C][/ROW]
[ROW][C]12[/C][C]-0.443101[/C][C]-4.3415[/C][C]1.8e-05[/C][/ROW]
[ROW][C]13[/C][C]0.280956[/C][C]2.7528[/C][C]0.003533[/C][/ROW]
[ROW][C]14[/C][C]-0.069623[/C][C]-0.6822[/C][C]0.248389[/C][/ROW]
[ROW][C]15[/C][C]0.044541[/C][C]0.4364[/C][C]0.331759[/C][/ROW]
[ROW][C]16[/C][C]0.025725[/C][C]0.2521[/C][C]0.400768[/C][/ROW]
[ROW][C]17[/C][C]0.029868[/C][C]0.2926[/C][C]0.385211[/C][/ROW]
[ROW][C]18[/C][C]0.057459[/C][C]0.563[/C][C]0.287379[/C][/ROW]
[ROW][C]19[/C][C]-0.080587[/C][C]-0.7896[/C][C]0.215858[/C][/ROW]
[ROW][C]20[/C][C]-0.072191[/C][C]-0.7073[/C][C]0.24054[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=299151&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=299151&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
10.2988772.92840.002128
20.0090640.08880.464708
3-0.111893-1.09630.137839
4-0.068764-0.67370.251045
5-0.103609-1.01520.156292
6-0.050482-0.49460.311001
7-0.055226-0.54110.294845
80.1592471.56030.06099
9-0.151262-1.48210.0708
10-0.068937-0.67540.250508
11-0.173364-1.69860.046315
12-0.443101-4.34151.8e-05
130.2809562.75280.003533
14-0.069623-0.68220.248389
150.0445410.43640.331759
160.0257250.25210.400768
170.0298680.29260.385211
180.0574590.5630.287379
19-0.080587-0.78960.215858
20-0.072191-0.70730.24054



Parameters (Session):
par1 = 8 ; par2 = 0 ;
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 <- '0'
par3 <- '0'
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')