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 computationSat, 17 Dec 2016 15:09:32 +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/t1481984329l46e4zapcwo6cer.htm/, Retrieved Thu, 02 May 2024 08:21:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=300803, Retrieved Thu, 02 May 2024 08:21:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact94
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelatie Te...] [2016-12-17 14:09:32] [549e222e79c75c10edc4b0c7b20158c3] [Current]
Feedback Forum

Post a new message
Dataseries X:
38.93
34.83
42.62
55.26
62.28
70.75
76.41
73.40
63.30
52.59
44.08
36.57
31.35
32.41
47.66
50.54
62.33
69.87
74.70
74.64
66.43
56.68
44.01
33.22
30.27
34.70
41.86
50.40
59.36
69.60
74.08
72.28
65.21
53.98
43.92
31.87
31.05
36.77
42.87
50.92
61.65
68.54
72.63
71.89
66.38
50.50
45.84
29.64
30.67
31.80
43.57
53.24
59.88
70.48
74.71
74.05
66.49
56.14
42.31
32.47
29.71
33.04
43.07
51.96
59.13
69.82
76.14
75.00
66.09
55.09
43.75
35.40
36.12
37.51
50.41
54.68
63.45
70.54
76.77
73.80
66.31
53.89
44.01
35.92
32.25
34.77
40.91
49.68
60.85
70.39
74.21
72.99
66.96
53.44
41.61
31.06
30.56
32.13
40.51
51.69
61.27
69.58
73.29
72.25
66.20
56.93
39.25
36.81
33.08
32.97
45.39
53.24
60.84
71.37
73.92
72.95
68.54
57.25
44.60
38.66
32.22
39.49
47.50
53.22
60.31
71.78
75.22
73.54
67.14
57.72
48.02




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=300803&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=300803&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300803&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
10.8496529.72470
20.4861535.56430
30.0018550.02120.491544
4-0.471456-5.39610
5-0.812299-9.29720
6-0.930648-10.65180
7-0.802078-9.18020
8-0.46215-5.28950
9-0.002732-0.03130.48755
100.4527815.18230
110.7872159.01010
120.90402210.3470
130.7724518.84110
140.4425285.0651e-06
150.0041530.04750.481082
16-0.428898-4.9091e-06
17-0.739777-8.46710
18-0.850426-9.73360
19-0.735567-8.4190
20-0.427039-4.88771e-06
21-0.009141-0.10460.458418

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.849652 & 9.7247 & 0 \tabularnewline
2 & 0.486153 & 5.5643 & 0 \tabularnewline
3 & 0.001855 & 0.0212 & 0.491544 \tabularnewline
4 & -0.471456 & -5.3961 & 0 \tabularnewline
5 & -0.812299 & -9.2972 & 0 \tabularnewline
6 & -0.930648 & -10.6518 & 0 \tabularnewline
7 & -0.802078 & -9.1802 & 0 \tabularnewline
8 & -0.46215 & -5.2895 & 0 \tabularnewline
9 & -0.002732 & -0.0313 & 0.48755 \tabularnewline
10 & 0.452781 & 5.1823 & 0 \tabularnewline
11 & 0.787215 & 9.0101 & 0 \tabularnewline
12 & 0.904022 & 10.347 & 0 \tabularnewline
13 & 0.772451 & 8.8411 & 0 \tabularnewline
14 & 0.442528 & 5.065 & 1e-06 \tabularnewline
15 & 0.004153 & 0.0475 & 0.481082 \tabularnewline
16 & -0.428898 & -4.909 & 1e-06 \tabularnewline
17 & -0.739777 & -8.4671 & 0 \tabularnewline
18 & -0.850426 & -9.7336 & 0 \tabularnewline
19 & -0.735567 & -8.419 & 0 \tabularnewline
20 & -0.427039 & -4.8877 & 1e-06 \tabularnewline
21 & -0.009141 & -0.1046 & 0.458418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300803&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]0.849652[/C][C]9.7247[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.486153[/C][C]5.5643[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.001855[/C][C]0.0212[/C][C]0.491544[/C][/ROW]
[ROW][C]4[/C][C]-0.471456[/C][C]-5.3961[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]-0.812299[/C][C]-9.2972[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]-0.930648[/C][C]-10.6518[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]-0.802078[/C][C]-9.1802[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]-0.46215[/C][C]-5.2895[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]-0.002732[/C][C]-0.0313[/C][C]0.48755[/C][/ROW]
[ROW][C]10[/C][C]0.452781[/C][C]5.1823[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.787215[/C][C]9.0101[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.904022[/C][C]10.347[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.772451[/C][C]8.8411[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.442528[/C][C]5.065[/C][C]1e-06[/C][/ROW]
[ROW][C]15[/C][C]0.004153[/C][C]0.0475[/C][C]0.481082[/C][/ROW]
[ROW][C]16[/C][C]-0.428898[/C][C]-4.909[/C][C]1e-06[/C][/ROW]
[ROW][C]17[/C][C]-0.739777[/C][C]-8.4671[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]-0.850426[/C][C]-9.7336[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]-0.735567[/C][C]-8.419[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]-0.427039[/C][C]-4.8877[/C][C]1e-06[/C][/ROW]
[ROW][C]21[/C][C]-0.009141[/C][C]-0.1046[/C][C]0.458418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300803&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300803&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
10.8496529.72470
20.4861535.56430
30.0018550.02120.491544
4-0.471456-5.39610
5-0.812299-9.29720
6-0.930648-10.65180
7-0.802078-9.18020
8-0.46215-5.28950
9-0.002732-0.03130.48755
100.4527815.18230
110.7872159.01010
120.90402210.3470
130.7724518.84110
140.4425285.0651e-06
150.0041530.04750.481082
16-0.428898-4.9091e-06
17-0.739777-8.46710
18-0.850426-9.73360
19-0.735567-8.4190
20-0.427039-4.88771e-06
21-0.009141-0.10460.458418







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.8496529.72470
2-0.847769-9.70320
3-0.525117-6.01020
4-0.282806-3.23690.000765
5-0.211826-2.42450.008348
6-0.075424-0.86330.194785
7-0.066852-0.76520.222777
80.0214010.2450.403439
90.0822420.94130.174142
100.0768680.87980.19029
110.1441311.64970.050704
12-0.06836-0.78240.21769
13-0.132509-1.51660.065884
140.1505791.72350.043583
150.1219241.39550.082616
16-0.018785-0.2150.415047
170.016520.18910.425162
18-0.016032-0.18350.427347
19-0.015648-0.17910.429068
200.0193540.22150.412519
210.0146390.16750.433599

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.849652 & 9.7247 & 0 \tabularnewline
2 & -0.847769 & -9.7032 & 0 \tabularnewline
3 & -0.525117 & -6.0102 & 0 \tabularnewline
4 & -0.282806 & -3.2369 & 0.000765 \tabularnewline
5 & -0.211826 & -2.4245 & 0.008348 \tabularnewline
6 & -0.075424 & -0.8633 & 0.194785 \tabularnewline
7 & -0.066852 & -0.7652 & 0.222777 \tabularnewline
8 & 0.021401 & 0.245 & 0.403439 \tabularnewline
9 & 0.082242 & 0.9413 & 0.174142 \tabularnewline
10 & 0.076868 & 0.8798 & 0.19029 \tabularnewline
11 & 0.144131 & 1.6497 & 0.050704 \tabularnewline
12 & -0.06836 & -0.7824 & 0.21769 \tabularnewline
13 & -0.132509 & -1.5166 & 0.065884 \tabularnewline
14 & 0.150579 & 1.7235 & 0.043583 \tabularnewline
15 & 0.121924 & 1.3955 & 0.082616 \tabularnewline
16 & -0.018785 & -0.215 & 0.415047 \tabularnewline
17 & 0.01652 & 0.1891 & 0.425162 \tabularnewline
18 & -0.016032 & -0.1835 & 0.427347 \tabularnewline
19 & -0.015648 & -0.1791 & 0.429068 \tabularnewline
20 & 0.019354 & 0.2215 & 0.412519 \tabularnewline
21 & 0.014639 & 0.1675 & 0.433599 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=300803&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]0.849652[/C][C]9.7247[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.847769[/C][C]-9.7032[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]-0.525117[/C][C]-6.0102[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]-0.282806[/C][C]-3.2369[/C][C]0.000765[/C][/ROW]
[ROW][C]5[/C][C]-0.211826[/C][C]-2.4245[/C][C]0.008348[/C][/ROW]
[ROW][C]6[/C][C]-0.075424[/C][C]-0.8633[/C][C]0.194785[/C][/ROW]
[ROW][C]7[/C][C]-0.066852[/C][C]-0.7652[/C][C]0.222777[/C][/ROW]
[ROW][C]8[/C][C]0.021401[/C][C]0.245[/C][C]0.403439[/C][/ROW]
[ROW][C]9[/C][C]0.082242[/C][C]0.9413[/C][C]0.174142[/C][/ROW]
[ROW][C]10[/C][C]0.076868[/C][C]0.8798[/C][C]0.19029[/C][/ROW]
[ROW][C]11[/C][C]0.144131[/C][C]1.6497[/C][C]0.050704[/C][/ROW]
[ROW][C]12[/C][C]-0.06836[/C][C]-0.7824[/C][C]0.21769[/C][/ROW]
[ROW][C]13[/C][C]-0.132509[/C][C]-1.5166[/C][C]0.065884[/C][/ROW]
[ROW][C]14[/C][C]0.150579[/C][C]1.7235[/C][C]0.043583[/C][/ROW]
[ROW][C]15[/C][C]0.121924[/C][C]1.3955[/C][C]0.082616[/C][/ROW]
[ROW][C]16[/C][C]-0.018785[/C][C]-0.215[/C][C]0.415047[/C][/ROW]
[ROW][C]17[/C][C]0.01652[/C][C]0.1891[/C][C]0.425162[/C][/ROW]
[ROW][C]18[/C][C]-0.016032[/C][C]-0.1835[/C][C]0.427347[/C][/ROW]
[ROW][C]19[/C][C]-0.015648[/C][C]-0.1791[/C][C]0.429068[/C][/ROW]
[ROW][C]20[/C][C]0.019354[/C][C]0.2215[/C][C]0.412519[/C][/ROW]
[ROW][C]21[/C][C]0.014639[/C][C]0.1675[/C][C]0.433599[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=300803&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=300803&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
10.8496529.72470
2-0.847769-9.70320
3-0.525117-6.01020
4-0.282806-3.23690.000765
5-0.211826-2.42450.008348
6-0.075424-0.86330.194785
7-0.066852-0.76520.222777
80.0214010.2450.403439
90.0822420.94130.174142
100.0768680.87980.19029
110.1441311.64970.050704
12-0.06836-0.78240.21769
13-0.132509-1.51660.065884
140.1505791.72350.043583
150.1219241.39550.082616
16-0.018785-0.2150.415047
170.016520.18910.425162
18-0.016032-0.18350.427347
19-0.015648-0.17910.429068
200.0193540.22150.412519
210.0146390.16750.433599



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)
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')