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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 computationWed, 25 Nov 2009 13:19:42 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/25/t1259180488e8jpmgvmgw0xj3g.htm/, Retrieved Tue, 07 May 2024 21:42:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=59615, Retrieved Tue, 07 May 2024 21:42:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [acf methode] [2009-11-25 20:19:42] [bef26de542bed2eafc60fe4615b06e47] [Current]
- RMPD    [Variance Reduction Matrix] [] [2009-11-26 09:49:54] [5edbdb7a459c4059b6c3b063ba86821c]
-    D      [Variance Reduction Matrix] [] [2009-12-12 16:30:56] [5edbdb7a459c4059b6c3b063ba86821c]
-    D      [Variance Reduction Matrix] [] [2009-12-12 16:30:56] [5edbdb7a459c4059b6c3b063ba86821c]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
121.6
118.8
114.0
111.5
97.2
102.5
113.4
109.8
104.9
126.1
80.0
96.8
117.2
112.3
117.3
111.1
102.2
104.3
122.9
107.6
121.3
131.5
89.0
104.4
128.9
135.9
133.3
121.3
120.5
120.4
137.9
126.1
133.2
151.1
105.0
119.0
140.4
156.6
137.1
122.7
125.8
139.3
134.9
149.2
132.3
149.0
117.2
119.6
152.0
149.4
127.3
114.1
102.1
107.7
104.4
102.1
96.0
109.3
90.0
83.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59615&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59615&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59615&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7824525.4211e-06
20.7894065.46921e-06
30.6761294.68441.2e-05
40.5693993.94490.00013
50.4589483.17970.001291
60.3576732.4780.00839
70.2421291.67750.049971
80.1794591.24330.109892
90.1035670.71750.238261
100.0804410.55730.289953
110.027210.18850.425632
12-0.001325-0.00920.496356
13-0.016147-0.11190.455697
14-0.054762-0.37940.35303
15-0.046083-0.31930.375452
16-0.130795-0.90620.184686
17-0.086189-0.59710.276613

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.782452 & 5.421 & 1e-06 \tabularnewline
2 & 0.789406 & 5.4692 & 1e-06 \tabularnewline
3 & 0.676129 & 4.6844 & 1.2e-05 \tabularnewline
4 & 0.569399 & 3.9449 & 0.00013 \tabularnewline
5 & 0.458948 & 3.1797 & 0.001291 \tabularnewline
6 & 0.357673 & 2.478 & 0.00839 \tabularnewline
7 & 0.242129 & 1.6775 & 0.049971 \tabularnewline
8 & 0.179459 & 1.2433 & 0.109892 \tabularnewline
9 & 0.103567 & 0.7175 & 0.238261 \tabularnewline
10 & 0.080441 & 0.5573 & 0.289953 \tabularnewline
11 & 0.02721 & 0.1885 & 0.425632 \tabularnewline
12 & -0.001325 & -0.0092 & 0.496356 \tabularnewline
13 & -0.016147 & -0.1119 & 0.455697 \tabularnewline
14 & -0.054762 & -0.3794 & 0.35303 \tabularnewline
15 & -0.046083 & -0.3193 & 0.375452 \tabularnewline
16 & -0.130795 & -0.9062 & 0.184686 \tabularnewline
17 & -0.086189 & -0.5971 & 0.276613 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59615&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]0.782452[/C][C]5.421[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.789406[/C][C]5.4692[/C][C]1e-06[/C][/ROW]
[ROW][C]3[/C][C]0.676129[/C][C]4.6844[/C][C]1.2e-05[/C][/ROW]
[ROW][C]4[/C][C]0.569399[/C][C]3.9449[/C][C]0.00013[/C][/ROW]
[ROW][C]5[/C][C]0.458948[/C][C]3.1797[/C][C]0.001291[/C][/ROW]
[ROW][C]6[/C][C]0.357673[/C][C]2.478[/C][C]0.00839[/C][/ROW]
[ROW][C]7[/C][C]0.242129[/C][C]1.6775[/C][C]0.049971[/C][/ROW]
[ROW][C]8[/C][C]0.179459[/C][C]1.2433[/C][C]0.109892[/C][/ROW]
[ROW][C]9[/C][C]0.103567[/C][C]0.7175[/C][C]0.238261[/C][/ROW]
[ROW][C]10[/C][C]0.080441[/C][C]0.5573[/C][C]0.289953[/C][/ROW]
[ROW][C]11[/C][C]0.02721[/C][C]0.1885[/C][C]0.425632[/C][/ROW]
[ROW][C]12[/C][C]-0.001325[/C][C]-0.0092[/C][C]0.496356[/C][/ROW]
[ROW][C]13[/C][C]-0.016147[/C][C]-0.1119[/C][C]0.455697[/C][/ROW]
[ROW][C]14[/C][C]-0.054762[/C][C]-0.3794[/C][C]0.35303[/C][/ROW]
[ROW][C]15[/C][C]-0.046083[/C][C]-0.3193[/C][C]0.375452[/C][/ROW]
[ROW][C]16[/C][C]-0.130795[/C][C]-0.9062[/C][C]0.184686[/C][/ROW]
[ROW][C]17[/C][C]-0.086189[/C][C]-0.5971[/C][C]0.276613[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59615&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59615&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
10.7824525.4211e-06
20.7894065.46921e-06
30.6761294.68441.2e-05
40.5693993.94490.00013
50.4589483.17970.001291
60.3576732.4780.00839
70.2421291.67750.049971
80.1794591.24330.109892
90.1035670.71750.238261
100.0804410.55730.289953
110.027210.18850.425632
12-0.001325-0.00920.496356
13-0.016147-0.11190.455697
14-0.054762-0.37940.35303
15-0.046083-0.31930.375452
16-0.130795-0.90620.184686
17-0.086189-0.59710.276613






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7824525.4211e-06
20.456913.16560.001344
3-0.054862-0.38010.352776
4-0.232203-1.60870.057115
5-0.16452-1.13980.130008
6-0.039768-0.27550.39205
7-0.06045-0.41880.338612
80.0649370.44990.327406
90.0512070.35480.362157
100.1015990.70390.242449
11-0.042123-0.29180.385834
12-0.102901-0.71290.239673
13-0.01732-0.120.452492
14-0.069282-0.480.316703
150.0578510.40080.345172
16-0.210652-1.45940.075479
170.1438950.99690.161899

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.782452 & 5.421 & 1e-06 \tabularnewline
2 & 0.45691 & 3.1656 & 0.001344 \tabularnewline
3 & -0.054862 & -0.3801 & 0.352776 \tabularnewline
4 & -0.232203 & -1.6087 & 0.057115 \tabularnewline
5 & -0.16452 & -1.1398 & 0.130008 \tabularnewline
6 & -0.039768 & -0.2755 & 0.39205 \tabularnewline
7 & -0.06045 & -0.4188 & 0.338612 \tabularnewline
8 & 0.064937 & 0.4499 & 0.327406 \tabularnewline
9 & 0.051207 & 0.3548 & 0.362157 \tabularnewline
10 & 0.101599 & 0.7039 & 0.242449 \tabularnewline
11 & -0.042123 & -0.2918 & 0.385834 \tabularnewline
12 & -0.102901 & -0.7129 & 0.239673 \tabularnewline
13 & -0.01732 & -0.12 & 0.452492 \tabularnewline
14 & -0.069282 & -0.48 & 0.316703 \tabularnewline
15 & 0.057851 & 0.4008 & 0.345172 \tabularnewline
16 & -0.210652 & -1.4594 & 0.075479 \tabularnewline
17 & 0.143895 & 0.9969 & 0.161899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=59615&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]0.782452[/C][C]5.421[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.45691[/C][C]3.1656[/C][C]0.001344[/C][/ROW]
[ROW][C]3[/C][C]-0.054862[/C][C]-0.3801[/C][C]0.352776[/C][/ROW]
[ROW][C]4[/C][C]-0.232203[/C][C]-1.6087[/C][C]0.057115[/C][/ROW]
[ROW][C]5[/C][C]-0.16452[/C][C]-1.1398[/C][C]0.130008[/C][/ROW]
[ROW][C]6[/C][C]-0.039768[/C][C]-0.2755[/C][C]0.39205[/C][/ROW]
[ROW][C]7[/C][C]-0.06045[/C][C]-0.4188[/C][C]0.338612[/C][/ROW]
[ROW][C]8[/C][C]0.064937[/C][C]0.4499[/C][C]0.327406[/C][/ROW]
[ROW][C]9[/C][C]0.051207[/C][C]0.3548[/C][C]0.362157[/C][/ROW]
[ROW][C]10[/C][C]0.101599[/C][C]0.7039[/C][C]0.242449[/C][/ROW]
[ROW][C]11[/C][C]-0.042123[/C][C]-0.2918[/C][C]0.385834[/C][/ROW]
[ROW][C]12[/C][C]-0.102901[/C][C]-0.7129[/C][C]0.239673[/C][/ROW]
[ROW][C]13[/C][C]-0.01732[/C][C]-0.12[/C][C]0.452492[/C][/ROW]
[ROW][C]14[/C][C]-0.069282[/C][C]-0.48[/C][C]0.316703[/C][/ROW]
[ROW][C]15[/C][C]0.057851[/C][C]0.4008[/C][C]0.345172[/C][/ROW]
[ROW][C]16[/C][C]-0.210652[/C][C]-1.4594[/C][C]0.075479[/C][/ROW]
[ROW][C]17[/C][C]0.143895[/C][C]0.9969[/C][C]0.161899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=59615&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=59615&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
10.7824525.4211e-06
20.456913.16560.001344
3-0.054862-0.38010.352776
4-0.232203-1.60870.057115
5-0.16452-1.13980.130008
6-0.039768-0.27550.39205
7-0.06045-0.41880.338612
80.0649370.44990.327406
90.0512070.35480.362157
100.1015990.70390.242449
11-0.042123-0.29180.385834
12-0.102901-0.71290.239673
13-0.01732-0.120.452492
14-0.069282-0.480.316703
150.0578510.40080.345172
16-0.210652-1.45940.075479
170.1438950.99690.161899


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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')