FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 03 May 2010 18:15:51 +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/May/03/t12729106155kh93z40xcnfb36.htm/, Retrieved Sat, 20 Apr 2024 13:22:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=75286, Retrieved Sat, 20 Apr 2024 13:22:51 +0000
QR Codes:

Original text written by user:jaar 56 tem 66
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W21
Estimated Impact124

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] [opgave 6bis Fiere...] [2010-05-03 18:15:51] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93,2
96
95,2
77,1
70,9
64,8
70,1
77,3
79,5
100,6
100,7
107,1
95,9
82,8
83,3
80
80,4
67,5
75,7
71,1
89,3
101,1
105,2
114,1
96,3
84,4
91,2
81,9
80,5
70,4
74,8
75,9
86,3
98,7
100,9
113,8
89,8
84,4
87,2
85,6
72
69,2
77,5
78,1
94,3
97,7
100,2
116,4
97,1
93
96
80,5
76,1
69,9
73,6
92,6
94,2
93,5
108,5
109,4
105,1
92,5
97,1
81,4
79,1
72,1
78,7
87,1
91,4
109,9
116,3
113
100
84,8
94,3
87,1
90,3
72,4
84,9
92,7
92,2
114,9
112,5
118,3
106
91,2
96,6
96,3
88,2
70,2
86,5
88,2
102,8
119,1
119,2
125,1
106,1
102,1
105,2
101
84,3
87,5
92,7
94,4
113
113,9
122,9
132,7
106,9
96,6
127,3
98,2
100,2
89,4
95,3
104,2
106,4
116,2
135,9
134
104,6
107,1
123,5
98,8
98,6
90,6
89,1
105,2
114
122,1
138
142,2

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=75286&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=75286&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75286&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
10.7268768.35120
20.4745885.45260
30.2425912.78720.003051
4-0.005761-0.06620.473662
5-0.144331-1.65820.049822
6-0.211878-2.43430.008129
7-0.133464-1.53340.063787
80.0346760.39840.345489
90.2521292.89670.002208
100.4106364.71783e-06

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.726876 & 8.3512 & 0 \tabularnewline
2 & 0.474588 & 5.4526 & 0 \tabularnewline
3 & 0.242591 & 2.7872 & 0.003051 \tabularnewline
4 & -0.005761 & -0.0662 & 0.473662 \tabularnewline
5 & -0.144331 & -1.6582 & 0.049822 \tabularnewline
6 & -0.211878 & -2.4343 & 0.008129 \tabularnewline
7 & -0.133464 & -1.5334 & 0.063787 \tabularnewline
8 & 0.034676 & 0.3984 & 0.345489 \tabularnewline
9 & 0.252129 & 2.8967 & 0.002208 \tabularnewline
10 & 0.410636 & 4.7178 & 3e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75286&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]0.726876[/C][C]8.3512[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.474588[/C][C]5.4526[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.242591[/C][C]2.7872[/C][C]0.003051[/C][/ROW]
[ROW][C]4[/C][C]-0.005761[/C][C]-0.0662[/C][C]0.473662[/C][/ROW]
[ROW][C]5[/C][C]-0.144331[/C][C]-1.6582[/C][C]0.049822[/C][/ROW]
[ROW][C]6[/C][C]-0.211878[/C][C]-2.4343[/C][C]0.008129[/C][/ROW]
[ROW][C]7[/C][C]-0.133464[/C][C]-1.5334[/C][C]0.063787[/C][/ROW]
[ROW][C]8[/C][C]0.034676[/C][C]0.3984[/C][C]0.345489[/C][/ROW]
[ROW][C]9[/C][C]0.252129[/C][C]2.8967[/C][C]0.002208[/C][/ROW]
[ROW][C]10[/C][C]0.410636[/C][C]4.7178[/C][C]3e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75286&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75286&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
10.7268768.35120
20.4745885.45260
30.2425912.78720.003051
4-0.005761-0.06620.473662
5-0.144331-1.65820.049822
6-0.211878-2.43430.008129
7-0.133464-1.53340.063787
80.0346760.39840.345489
90.2521292.89670.002208
100.4106364.71783e-06






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7268768.35120
2-0.113985-1.30960.096305
3-0.126403-1.45230.074401
4-0.221135-2.54070.006111
50.0018270.0210.491643
6-0.020357-0.23390.407718
70.2005972.30470.011373
80.1846072.1210.017897
90.246332.83010.002691
100.0691630.79460.214131

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.726876 & 8.3512 & 0 \tabularnewline
2 & -0.113985 & -1.3096 & 0.096305 \tabularnewline
3 & -0.126403 & -1.4523 & 0.074401 \tabularnewline
4 & -0.221135 & -2.5407 & 0.006111 \tabularnewline
5 & 0.001827 & 0.021 & 0.491643 \tabularnewline
6 & -0.020357 & -0.2339 & 0.407718 \tabularnewline
7 & 0.200597 & 2.3047 & 0.011373 \tabularnewline
8 & 0.184607 & 2.121 & 0.017897 \tabularnewline
9 & 0.24633 & 2.8301 & 0.002691 \tabularnewline
10 & 0.069163 & 0.7946 & 0.214131 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=75286&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]0.726876[/C][C]8.3512[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.113985[/C][C]-1.3096[/C][C]0.096305[/C][/ROW]
[ROW][C]3[/C][C]-0.126403[/C][C]-1.4523[/C][C]0.074401[/C][/ROW]
[ROW][C]4[/C][C]-0.221135[/C][C]-2.5407[/C][C]0.006111[/C][/ROW]
[ROW][C]5[/C][C]0.001827[/C][C]0.021[/C][C]0.491643[/C][/ROW]
[ROW][C]6[/C][C]-0.020357[/C][C]-0.2339[/C][C]0.407718[/C][/ROW]
[ROW][C]7[/C][C]0.200597[/C][C]2.3047[/C][C]0.011373[/C][/ROW]
[ROW][C]8[/C][C]0.184607[/C][C]2.121[/C][C]0.017897[/C][/ROW]
[ROW][C]9[/C][C]0.24633[/C][C]2.8301[/C][C]0.002691[/C][/ROW]
[ROW][C]10[/C][C]0.069163[/C][C]0.7946[/C][C]0.214131[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=75286&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=75286&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
10.7268768.35120
2-0.113985-1.30960.096305
3-0.126403-1.45230.074401
4-0.221135-2.54070.006111
50.0018270.0210.491643
6-0.020357-0.23390.407718
70.2005972.30470.011373
80.1846072.1210.017897
90.246332.83010.002691
100.0691630.79460.214131


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 10 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 10 ; par2 = 1 ; par3 = 0 ; 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')