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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 computationMon, 21 Dec 2009 06:28:15 -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/21/t1261402152wr252qu1iupb9h6.htm/, Retrieved Sun, 05 May 2024 09:31:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70151, Retrieved Sun, 05 May 2024 09:31:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact95

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] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:19:56] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [Autocorrelation f...] [2009-12-21 13:28:15] [0744dbfa8cdb263e2e292d0a5ee9dc89] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
115.9
96
99.8
116.8
115.7
99.4
94.3
91
93.2
103.1
94.1
91.8
102.7
82.6
89.1
104.5

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70151&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70151&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70151&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'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.5536523.87560.000158
20.6523474.56641.7e-05
30.7049844.93495e-06
40.4511343.15790.00136
50.4728423.30990.000878
60.3952.7650.004001
70.2305831.61410.056466
80.2734561.91420.030723
90.0987310.69110.246377
100.0946260.66240.255415
110.0943850.66070.25595
12-0.054996-0.3850.350962
130.0254860.17840.429572
14-0.003505-0.02450.490263
15-0.036148-0.2530.400651
16-0.067196-0.47040.320087
17-0.037242-0.26070.39771

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.553652 & 3.8756 & 0.000158 \tabularnewline
2 & 0.652347 & 4.5664 & 1.7e-05 \tabularnewline
3 & 0.704984 & 4.9349 & 5e-06 \tabularnewline
4 & 0.451134 & 3.1579 & 0.00136 \tabularnewline
5 & 0.472842 & 3.3099 & 0.000878 \tabularnewline
6 & 0.395 & 2.765 & 0.004001 \tabularnewline
7 & 0.230583 & 1.6141 & 0.056466 \tabularnewline
8 & 0.273456 & 1.9142 & 0.030723 \tabularnewline
9 & 0.098731 & 0.6911 & 0.246377 \tabularnewline
10 & 0.094626 & 0.6624 & 0.255415 \tabularnewline
11 & 0.094385 & 0.6607 & 0.25595 \tabularnewline
12 & -0.054996 & -0.385 & 0.350962 \tabularnewline
13 & 0.025486 & 0.1784 & 0.429572 \tabularnewline
14 & -0.003505 & -0.0245 & 0.490263 \tabularnewline
15 & -0.036148 & -0.253 & 0.400651 \tabularnewline
16 & -0.067196 & -0.4704 & 0.320087 \tabularnewline
17 & -0.037242 & -0.2607 & 0.39771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70151&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]0.553652[/C][C]3.8756[/C][C]0.000158[/C][/ROW]
[ROW][C]2[/C][C]0.652347[/C][C]4.5664[/C][C]1.7e-05[/C][/ROW]
[ROW][C]3[/C][C]0.704984[/C][C]4.9349[/C][C]5e-06[/C][/ROW]
[ROW][C]4[/C][C]0.451134[/C][C]3.1579[/C][C]0.00136[/C][/ROW]
[ROW][C]5[/C][C]0.472842[/C][C]3.3099[/C][C]0.000878[/C][/ROW]
[ROW][C]6[/C][C]0.395[/C][C]2.765[/C][C]0.004001[/C][/ROW]
[ROW][C]7[/C][C]0.230583[/C][C]1.6141[/C][C]0.056466[/C][/ROW]
[ROW][C]8[/C][C]0.273456[/C][C]1.9142[/C][C]0.030723[/C][/ROW]
[ROW][C]9[/C][C]0.098731[/C][C]0.6911[/C][C]0.246377[/C][/ROW]
[ROW][C]10[/C][C]0.094626[/C][C]0.6624[/C][C]0.255415[/C][/ROW]
[ROW][C]11[/C][C]0.094385[/C][C]0.6607[/C][C]0.25595[/C][/ROW]
[ROW][C]12[/C][C]-0.054996[/C][C]-0.385[/C][C]0.350962[/C][/ROW]
[ROW][C]13[/C][C]0.025486[/C][C]0.1784[/C][C]0.429572[/C][/ROW]
[ROW][C]14[/C][C]-0.003505[/C][C]-0.0245[/C][C]0.490263[/C][/ROW]
[ROW][C]15[/C][C]-0.036148[/C][C]-0.253[/C][C]0.400651[/C][/ROW]
[ROW][C]16[/C][C]-0.067196[/C][C]-0.4704[/C][C]0.320087[/C][/ROW]
[ROW][C]17[/C][C]-0.037242[/C][C]-0.2607[/C][C]0.39771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70151&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70151&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
10.5536523.87560.000158
20.6523474.56641.7e-05
30.7049844.93495e-06
40.4511343.15790.00136
50.4728423.30990.000878
60.3952.7650.004001
70.2305831.61410.056466
80.2734561.91420.030723
90.0987310.69110.246377
100.0946260.66240.255415
110.0943850.66070.25595
12-0.054996-0.3850.350962
130.0254860.17840.429572
14-0.003505-0.02450.490263
15-0.036148-0.2530.400651
16-0.067196-0.47040.320087
17-0.037242-0.26070.39771






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5536523.87560.000158
20.4986753.49070.000515
30.4756583.32960.000829
4-0.198076-1.38650.085931
5-0.266955-1.86870.033825
6-0.194907-1.36430.089346
7-0.147382-1.03170.153645
80.125260.87680.192432
9-0.047876-0.33510.369479
100.0666420.46650.321466
110.1153180.80720.211719
12-0.057149-0.40.345433
130.0066820.04680.481442
140.0379050.26530.395932
150.1309310.91650.181942
16-0.25703-1.79920.039072
17-0.141842-0.99290.16282

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.553652 & 3.8756 & 0.000158 \tabularnewline
2 & 0.498675 & 3.4907 & 0.000515 \tabularnewline
3 & 0.475658 & 3.3296 & 0.000829 \tabularnewline
4 & -0.198076 & -1.3865 & 0.085931 \tabularnewline
5 & -0.266955 & -1.8687 & 0.033825 \tabularnewline
6 & -0.194907 & -1.3643 & 0.089346 \tabularnewline
7 & -0.147382 & -1.0317 & 0.153645 \tabularnewline
8 & 0.12526 & 0.8768 & 0.192432 \tabularnewline
9 & -0.047876 & -0.3351 & 0.369479 \tabularnewline
10 & 0.066642 & 0.4665 & 0.321466 \tabularnewline
11 & 0.115318 & 0.8072 & 0.211719 \tabularnewline
12 & -0.057149 & -0.4 & 0.345433 \tabularnewline
13 & 0.006682 & 0.0468 & 0.481442 \tabularnewline
14 & 0.037905 & 0.2653 & 0.395932 \tabularnewline
15 & 0.130931 & 0.9165 & 0.181942 \tabularnewline
16 & -0.25703 & -1.7992 & 0.039072 \tabularnewline
17 & -0.141842 & -0.9929 & 0.16282 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70151&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]0.553652[/C][C]3.8756[/C][C]0.000158[/C][/ROW]
[ROW][C]2[/C][C]0.498675[/C][C]3.4907[/C][C]0.000515[/C][/ROW]
[ROW][C]3[/C][C]0.475658[/C][C]3.3296[/C][C]0.000829[/C][/ROW]
[ROW][C]4[/C][C]-0.198076[/C][C]-1.3865[/C][C]0.085931[/C][/ROW]
[ROW][C]5[/C][C]-0.266955[/C][C]-1.8687[/C][C]0.033825[/C][/ROW]
[ROW][C]6[/C][C]-0.194907[/C][C]-1.3643[/C][C]0.089346[/C][/ROW]
[ROW][C]7[/C][C]-0.147382[/C][C]-1.0317[/C][C]0.153645[/C][/ROW]
[ROW][C]8[/C][C]0.12526[/C][C]0.8768[/C][C]0.192432[/C][/ROW]
[ROW][C]9[/C][C]-0.047876[/C][C]-0.3351[/C][C]0.369479[/C][/ROW]
[ROW][C]10[/C][C]0.066642[/C][C]0.4665[/C][C]0.321466[/C][/ROW]
[ROW][C]11[/C][C]0.115318[/C][C]0.8072[/C][C]0.211719[/C][/ROW]
[ROW][C]12[/C][C]-0.057149[/C][C]-0.4[/C][C]0.345433[/C][/ROW]
[ROW][C]13[/C][C]0.006682[/C][C]0.0468[/C][C]0.481442[/C][/ROW]
[ROW][C]14[/C][C]0.037905[/C][C]0.2653[/C][C]0.395932[/C][/ROW]
[ROW][C]15[/C][C]0.130931[/C][C]0.9165[/C][C]0.181942[/C][/ROW]
[ROW][C]16[/C][C]-0.25703[/C][C]-1.7992[/C][C]0.039072[/C][/ROW]
[ROW][C]17[/C][C]-0.141842[/C][C]-0.9929[/C][C]0.16282[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70151&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70151&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
10.5536523.87560.000158
20.4986753.49070.000515
30.4756583.32960.000829
4-0.198076-1.38650.085931
5-0.266955-1.86870.033825
6-0.194907-1.36430.089346
7-0.147382-1.03170.153645
80.125260.87680.192432
9-0.047876-0.33510.369479
100.0666420.46650.321466
110.1153180.80720.211719
12-0.057149-0.40.345433
130.0066820.04680.481442
140.0379050.26530.395932
150.1309310.91650.181942
16-0.25703-1.79920.039072
17-0.141842-0.99290.16282


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')