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Description of Statistical Computation

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 computationFri, 03 Dec 2010 14:12:17 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/03/t1291385415ayqgex0v6ed3cal.htm/, Retrieved Sun, 28 Apr 2024 23:37:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104806, Retrieved Sun, 28 Apr 2024 23:37:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Monthly US soldie...] [2010-11-02 12:07:39] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Soldiers] [2010-11-29 09:48:36] [b98453cac15ba1066b407e146608df68]
-   PD    [(Partial) Autocorrelation Function] [] [2010-12-03 11:32:19] [8a9a6f7c332640af31ddca253a8ded58]
-   PD        [(Partial) Autocorrelation Function] [] [2010-12-03 14:12:17] [df17410ebb98883e83037e1662207ccb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.76
102.37
102.38
102.86
102.87
102.92
102.95
103.02
104.08
104.16
104.24
104.33
104.73
104.86
105.03
105.62
105.63
105.63
105.94
106.61
107.69
107.78
107.93
108.48
108.14
108.48
108.48
108.89
108.93
109.21
109.47
109.80
111.73
111.85
112.12
112.15
112.17
112.67
112.80
113.44
113.53
114.53
114.51
115.05
116.67
117.07
116.92
117.00
117.02
117.35
117.36
117.82
117.88
118.24
118.50
118.80
119.76
120.09

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104806&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104806&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104806&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.085651-0.64660.260228
2-0.038335-0.28940.386654
3-0.06786-0.51230.305199
4-0.145992-1.10220.137501
50.074780.56460.287288
6-0.232557-1.75580.04225
70.1613581.21820.114078
8-0.236061-1.78220.04002
90.0107020.08080.467944
10-0.096398-0.72780.234861
11-9e-04-0.00680.497302
120.6108734.6121.2e-05
13-0.016346-0.12340.451108
14-0.061554-0.46470.321951
15-0.108155-0.81660.208792
16-0.209846-1.58430.059329
170.0831650.62790.266294

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.085651 & -0.6466 & 0.260228 \tabularnewline
2 & -0.038335 & -0.2894 & 0.386654 \tabularnewline
3 & -0.06786 & -0.5123 & 0.305199 \tabularnewline
4 & -0.145992 & -1.1022 & 0.137501 \tabularnewline
5 & 0.07478 & 0.5646 & 0.287288 \tabularnewline
6 & -0.232557 & -1.7558 & 0.04225 \tabularnewline
7 & 0.161358 & 1.2182 & 0.114078 \tabularnewline
8 & -0.236061 & -1.7822 & 0.04002 \tabularnewline
9 & 0.010702 & 0.0808 & 0.467944 \tabularnewline
10 & -0.096398 & -0.7278 & 0.234861 \tabularnewline
11 & -9e-04 & -0.0068 & 0.497302 \tabularnewline
12 & 0.610873 & 4.612 & 1.2e-05 \tabularnewline
13 & -0.016346 & -0.1234 & 0.451108 \tabularnewline
14 & -0.061554 & -0.4647 & 0.321951 \tabularnewline
15 & -0.108155 & -0.8166 & 0.208792 \tabularnewline
16 & -0.209846 & -1.5843 & 0.059329 \tabularnewline
17 & 0.083165 & 0.6279 & 0.266294 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104806&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]-0.085651[/C][C]-0.6466[/C][C]0.260228[/C][/ROW]
[ROW][C]2[/C][C]-0.038335[/C][C]-0.2894[/C][C]0.386654[/C][/ROW]
[ROW][C]3[/C][C]-0.06786[/C][C]-0.5123[/C][C]0.305199[/C][/ROW]
[ROW][C]4[/C][C]-0.145992[/C][C]-1.1022[/C][C]0.137501[/C][/ROW]
[ROW][C]5[/C][C]0.07478[/C][C]0.5646[/C][C]0.287288[/C][/ROW]
[ROW][C]6[/C][C]-0.232557[/C][C]-1.7558[/C][C]0.04225[/C][/ROW]
[ROW][C]7[/C][C]0.161358[/C][C]1.2182[/C][C]0.114078[/C][/ROW]
[ROW][C]8[/C][C]-0.236061[/C][C]-1.7822[/C][C]0.04002[/C][/ROW]
[ROW][C]9[/C][C]0.010702[/C][C]0.0808[/C][C]0.467944[/C][/ROW]
[ROW][C]10[/C][C]-0.096398[/C][C]-0.7278[/C][C]0.234861[/C][/ROW]
[ROW][C]11[/C][C]-9e-04[/C][C]-0.0068[/C][C]0.497302[/C][/ROW]
[ROW][C]12[/C][C]0.610873[/C][C]4.612[/C][C]1.2e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.016346[/C][C]-0.1234[/C][C]0.451108[/C][/ROW]
[ROW][C]14[/C][C]-0.061554[/C][C]-0.4647[/C][C]0.321951[/C][/ROW]
[ROW][C]15[/C][C]-0.108155[/C][C]-0.8166[/C][C]0.208792[/C][/ROW]
[ROW][C]16[/C][C]-0.209846[/C][C]-1.5843[/C][C]0.059329[/C][/ROW]
[ROW][C]17[/C][C]0.083165[/C][C]0.6279[/C][C]0.266294[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104806&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104806&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.085651-0.64660.260228
2-0.038335-0.28940.386654
3-0.06786-0.51230.305199
4-0.145992-1.10220.137501
50.074780.56460.287288
6-0.232557-1.75580.04225
70.1613581.21820.114078
8-0.236061-1.78220.04002
90.0107020.08080.467944
10-0.096398-0.72780.234861
11-9e-04-0.00680.497302
120.6108734.6121.2e-05
13-0.016346-0.12340.451108
14-0.061554-0.46470.321951
15-0.108155-0.81660.208792
16-0.209846-1.58430.059329
170.0831650.62790.266294






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.085651-0.64660.260228
2-0.046009-0.34740.364801
3-0.075952-0.57340.284307
4-0.163313-1.2330.111321
50.0393580.29710.383716
6-0.25321-1.91170.030473
70.110310.83280.204211
8-0.29866-2.25480.014001
9-0.01619-0.12220.451573
10-0.26968-2.0360.023202
110.0184270.13910.444922
120.5055643.81690.000168
130.1639141.23750.110483
14-0.161131-1.21650.114402
150.0188030.1420.443808
16-0.344694-2.60240.005889
170.1477341.11540.134687

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.085651 & -0.6466 & 0.260228 \tabularnewline
2 & -0.046009 & -0.3474 & 0.364801 \tabularnewline
3 & -0.075952 & -0.5734 & 0.284307 \tabularnewline
4 & -0.163313 & -1.233 & 0.111321 \tabularnewline
5 & 0.039358 & 0.2971 & 0.383716 \tabularnewline
6 & -0.25321 & -1.9117 & 0.030473 \tabularnewline
7 & 0.11031 & 0.8328 & 0.204211 \tabularnewline
8 & -0.29866 & -2.2548 & 0.014001 \tabularnewline
9 & -0.01619 & -0.1222 & 0.451573 \tabularnewline
10 & -0.26968 & -2.036 & 0.023202 \tabularnewline
11 & 0.018427 & 0.1391 & 0.444922 \tabularnewline
12 & 0.505564 & 3.8169 & 0.000168 \tabularnewline
13 & 0.163914 & 1.2375 & 0.110483 \tabularnewline
14 & -0.161131 & -1.2165 & 0.114402 \tabularnewline
15 & 0.018803 & 0.142 & 0.443808 \tabularnewline
16 & -0.344694 & -2.6024 & 0.005889 \tabularnewline
17 & 0.147734 & 1.1154 & 0.134687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104806&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]-0.085651[/C][C]-0.6466[/C][C]0.260228[/C][/ROW]
[ROW][C]2[/C][C]-0.046009[/C][C]-0.3474[/C][C]0.364801[/C][/ROW]
[ROW][C]3[/C][C]-0.075952[/C][C]-0.5734[/C][C]0.284307[/C][/ROW]
[ROW][C]4[/C][C]-0.163313[/C][C]-1.233[/C][C]0.111321[/C][/ROW]
[ROW][C]5[/C][C]0.039358[/C][C]0.2971[/C][C]0.383716[/C][/ROW]
[ROW][C]6[/C][C]-0.25321[/C][C]-1.9117[/C][C]0.030473[/C][/ROW]
[ROW][C]7[/C][C]0.11031[/C][C]0.8328[/C][C]0.204211[/C][/ROW]
[ROW][C]8[/C][C]-0.29866[/C][C]-2.2548[/C][C]0.014001[/C][/ROW]
[ROW][C]9[/C][C]-0.01619[/C][C]-0.1222[/C][C]0.451573[/C][/ROW]
[ROW][C]10[/C][C]-0.26968[/C][C]-2.036[/C][C]0.023202[/C][/ROW]
[ROW][C]11[/C][C]0.018427[/C][C]0.1391[/C][C]0.444922[/C][/ROW]
[ROW][C]12[/C][C]0.505564[/C][C]3.8169[/C][C]0.000168[/C][/ROW]
[ROW][C]13[/C][C]0.163914[/C][C]1.2375[/C][C]0.110483[/C][/ROW]
[ROW][C]14[/C][C]-0.161131[/C][C]-1.2165[/C][C]0.114402[/C][/ROW]
[ROW][C]15[/C][C]0.018803[/C][C]0.142[/C][C]0.443808[/C][/ROW]
[ROW][C]16[/C][C]-0.344694[/C][C]-2.6024[/C][C]0.005889[/C][/ROW]
[ROW][C]17[/C][C]0.147734[/C][C]1.1154[/C][C]0.134687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104806&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104806&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.085651-0.64660.260228
2-0.046009-0.34740.364801
3-0.075952-0.57340.284307
4-0.163313-1.2330.111321
50.0393580.29710.383716
6-0.25321-1.91170.030473
70.110310.83280.204211
8-0.29866-2.25480.014001
9-0.01619-0.12220.451573
10-0.26968-2.0360.023202
110.0184270.13910.444922
120.5055643.81690.000168
130.1639141.23750.110483
14-0.161131-1.21650.114402
150.0188030.1420.443808
16-0.344694-2.60240.005889
170.1477341.11540.134687


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; 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 ;
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 (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
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')