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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 computationThu, 03 Dec 2009 10:25:34 -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/Dec/03/t1259861208f5qisx0rgld39om.htm/, Retrieved Fri, 19 Apr 2024 20:35:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62946, Retrieved Fri, 19 Apr 2024 20:35:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [Partiele autocorr...] [2009-12-03 17:25:34] [b1ac221d009d6e5c29a4ef1869874933] [Current]
-   P         [(Partial) Autocorrelation Function] [Partial correlati...] [2009-12-03 17:57:16] [863a41223bd4bb97f4e5094488ffff34]
-   P           [(Partial) Autocorrelation Function] [Autocorrelation e...] [2009-12-04 17:50:40] [863a41223bd4bb97f4e5094488ffff34]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
89.6
92.8
107.6
104.6
103
106.9
56.3
93.4
109.1
113.8
97.4
72.5
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62946&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]3 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=62946&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62946&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.082019-0.64060.262095
20.1777551.38830.085046
30.1412551.10320.137129
40.1194190.93270.177328
50.1222720.9550.171679
60.2498721.95160.027793
7-0.067954-0.53070.298764
80.1872211.46220.074404
90.1875941.46520.074007
10-0.024809-0.19380.423501
110.1717621.34150.092365
12-0.129591-1.01210.157735
130.0070290.05490.478198
140.0031680.02470.490169
150.1377981.07620.143029
16-0.108743-0.84930.199516
170.1575831.23080.111569
18-0.089705-0.70060.243102

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.082019 & -0.6406 & 0.262095 \tabularnewline
2 & 0.177755 & 1.3883 & 0.085046 \tabularnewline
3 & 0.141255 & 1.1032 & 0.137129 \tabularnewline
4 & 0.119419 & 0.9327 & 0.177328 \tabularnewline
5 & 0.122272 & 0.955 & 0.171679 \tabularnewline
6 & 0.249872 & 1.9516 & 0.027793 \tabularnewline
7 & -0.067954 & -0.5307 & 0.298764 \tabularnewline
8 & 0.187221 & 1.4622 & 0.074404 \tabularnewline
9 & 0.187594 & 1.4652 & 0.074007 \tabularnewline
10 & -0.024809 & -0.1938 & 0.423501 \tabularnewline
11 & 0.171762 & 1.3415 & 0.092365 \tabularnewline
12 & -0.129591 & -1.0121 & 0.157735 \tabularnewline
13 & 0.007029 & 0.0549 & 0.478198 \tabularnewline
14 & 0.003168 & 0.0247 & 0.490169 \tabularnewline
15 & 0.137798 & 1.0762 & 0.143029 \tabularnewline
16 & -0.108743 & -0.8493 & 0.199516 \tabularnewline
17 & 0.157583 & 1.2308 & 0.111569 \tabularnewline
18 & -0.089705 & -0.7006 & 0.243102 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62946&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]-0.082019[/C][C]-0.6406[/C][C]0.262095[/C][/ROW]
[ROW][C]2[/C][C]0.177755[/C][C]1.3883[/C][C]0.085046[/C][/ROW]
[ROW][C]3[/C][C]0.141255[/C][C]1.1032[/C][C]0.137129[/C][/ROW]
[ROW][C]4[/C][C]0.119419[/C][C]0.9327[/C][C]0.177328[/C][/ROW]
[ROW][C]5[/C][C]0.122272[/C][C]0.955[/C][C]0.171679[/C][/ROW]
[ROW][C]6[/C][C]0.249872[/C][C]1.9516[/C][C]0.027793[/C][/ROW]
[ROW][C]7[/C][C]-0.067954[/C][C]-0.5307[/C][C]0.298764[/C][/ROW]
[ROW][C]8[/C][C]0.187221[/C][C]1.4622[/C][C]0.074404[/C][/ROW]
[ROW][C]9[/C][C]0.187594[/C][C]1.4652[/C][C]0.074007[/C][/ROW]
[ROW][C]10[/C][C]-0.024809[/C][C]-0.1938[/C][C]0.423501[/C][/ROW]
[ROW][C]11[/C][C]0.171762[/C][C]1.3415[/C][C]0.092365[/C][/ROW]
[ROW][C]12[/C][C]-0.129591[/C][C]-1.0121[/C][C]0.157735[/C][/ROW]
[ROW][C]13[/C][C]0.007029[/C][C]0.0549[/C][C]0.478198[/C][/ROW]
[ROW][C]14[/C][C]0.003168[/C][C]0.0247[/C][C]0.490169[/C][/ROW]
[ROW][C]15[/C][C]0.137798[/C][C]1.0762[/C][C]0.143029[/C][/ROW]
[ROW][C]16[/C][C]-0.108743[/C][C]-0.8493[/C][C]0.199516[/C][/ROW]
[ROW][C]17[/C][C]0.157583[/C][C]1.2308[/C][C]0.111569[/C][/ROW]
[ROW][C]18[/C][C]-0.089705[/C][C]-0.7006[/C][C]0.243102[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62946&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62946&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
1-0.082019-0.64060.262095
20.1777551.38830.085046
30.1412551.10320.137129
40.1194190.93270.177328
50.1222720.9550.171679
60.2498721.95160.027793
7-0.067954-0.53070.298764
80.1872211.46220.074404
90.1875941.46520.074007
10-0.024809-0.19380.423501
110.1717621.34150.092365
12-0.129591-1.01210.157735
130.0070290.05490.478198
140.0031680.02470.490169
150.1377981.07620.143029
16-0.108743-0.84930.199516
170.1575831.23080.111569
18-0.089705-0.70060.243102






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.082019-0.64060.262095
20.1721861.34480.091831
30.1737311.35690.089909
40.1227950.95910.170657
50.0985820.76990.222151
60.229261.79060.039162
7-0.089497-0.6990.243606
80.0599080.46790.320762
90.172861.35010.090989
10-0.070944-0.55410.290771
110.0538440.42050.337787
12-0.223373-1.74460.043045
13-0.102422-0.79990.213425
14-0.106303-0.83030.204816
150.1293361.01010.158208
16-0.023903-0.18670.426263
170.0919860.71840.237615
180.0223570.17460.43098

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.082019 & -0.6406 & 0.262095 \tabularnewline
2 & 0.172186 & 1.3448 & 0.091831 \tabularnewline
3 & 0.173731 & 1.3569 & 0.089909 \tabularnewline
4 & 0.122795 & 0.9591 & 0.170657 \tabularnewline
5 & 0.098582 & 0.7699 & 0.222151 \tabularnewline
6 & 0.22926 & 1.7906 & 0.039162 \tabularnewline
7 & -0.089497 & -0.699 & 0.243606 \tabularnewline
8 & 0.059908 & 0.4679 & 0.320762 \tabularnewline
9 & 0.17286 & 1.3501 & 0.090989 \tabularnewline
10 & -0.070944 & -0.5541 & 0.290771 \tabularnewline
11 & 0.053844 & 0.4205 & 0.337787 \tabularnewline
12 & -0.223373 & -1.7446 & 0.043045 \tabularnewline
13 & -0.102422 & -0.7999 & 0.213425 \tabularnewline
14 & -0.106303 & -0.8303 & 0.204816 \tabularnewline
15 & 0.129336 & 1.0101 & 0.158208 \tabularnewline
16 & -0.023903 & -0.1867 & 0.426263 \tabularnewline
17 & 0.091986 & 0.7184 & 0.237615 \tabularnewline
18 & 0.022357 & 0.1746 & 0.43098 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62946&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]-0.082019[/C][C]-0.6406[/C][C]0.262095[/C][/ROW]
[ROW][C]2[/C][C]0.172186[/C][C]1.3448[/C][C]0.091831[/C][/ROW]
[ROW][C]3[/C][C]0.173731[/C][C]1.3569[/C][C]0.089909[/C][/ROW]
[ROW][C]4[/C][C]0.122795[/C][C]0.9591[/C][C]0.170657[/C][/ROW]
[ROW][C]5[/C][C]0.098582[/C][C]0.7699[/C][C]0.222151[/C][/ROW]
[ROW][C]6[/C][C]0.22926[/C][C]1.7906[/C][C]0.039162[/C][/ROW]
[ROW][C]7[/C][C]-0.089497[/C][C]-0.699[/C][C]0.243606[/C][/ROW]
[ROW][C]8[/C][C]0.059908[/C][C]0.4679[/C][C]0.320762[/C][/ROW]
[ROW][C]9[/C][C]0.17286[/C][C]1.3501[/C][C]0.090989[/C][/ROW]
[ROW][C]10[/C][C]-0.070944[/C][C]-0.5541[/C][C]0.290771[/C][/ROW]
[ROW][C]11[/C][C]0.053844[/C][C]0.4205[/C][C]0.337787[/C][/ROW]
[ROW][C]12[/C][C]-0.223373[/C][C]-1.7446[/C][C]0.043045[/C][/ROW]
[ROW][C]13[/C][C]-0.102422[/C][C]-0.7999[/C][C]0.213425[/C][/ROW]
[ROW][C]14[/C][C]-0.106303[/C][C]-0.8303[/C][C]0.204816[/C][/ROW]
[ROW][C]15[/C][C]0.129336[/C][C]1.0101[/C][C]0.158208[/C][/ROW]
[ROW][C]16[/C][C]-0.023903[/C][C]-0.1867[/C][C]0.426263[/C][/ROW]
[ROW][C]17[/C][C]0.091986[/C][C]0.7184[/C][C]0.237615[/C][/ROW]
[ROW][C]18[/C][C]0.022357[/C][C]0.1746[/C][C]0.43098[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62946&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62946&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
1-0.082019-0.64060.262095
20.1721861.34480.091831
30.1737311.35690.089909
40.1227950.95910.170657
50.0985820.76990.222151
60.229261.79060.039162
7-0.089497-0.6990.243606
80.0599080.46790.320762
90.172861.35010.090989
10-0.070944-0.55410.290771
110.0538440.42050.337787
12-0.223373-1.74460.043045
13-0.102422-0.79990.213425
14-0.106303-0.83030.204816
150.1293361.01010.158208
16-0.023903-0.18670.426263
170.0919860.71840.237615
180.0223570.17460.43098


Figures (Output of Computation)

Input Parameters & R Code

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