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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 26 Nov 2009 12:09:40 -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/26/t1259262605fia8d6qdgfqwa85.htm/, Retrieved Sun, 28 Apr 2024 20:37:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60296, Retrieved Sun, 28 Apr 2024 20:37:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105

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 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [Industriële produ...] [2009-11-26 19:09:40] [fcf610eda12f49b9bf9c81ec9669e97a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25.7
24.7
24.2
23.6
24.4
22.5
19.4
18.1
18.1
20.7
19.1
18.3
16.9
17.9
20.2
21.2
23.8
24
26.6
25.3
27.6
24.7
26.6
24.4
24.6
26
24.8
24
22.7
23
24.1
24
22.7
22.6
23.1
24.4
23
22
21.3
21.5
21.3
23.2
21.8
23.3
21
22.4
20.4
19.9
21.3
18.9
15.6
12.5
7.8
5.5
4
3.3
3.7
3.1
5
6.3

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=60296&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=60296&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60296&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
10.9238047.15580
20.8339196.45950
30.7093385.49450
40.5923684.58851.2e-05
50.4617663.57680.000348
60.3309332.56340.006445
70.2151711.66670.050393
80.1198760.92860.17842
90.0578370.4480.327882
100.0110370.08550.466078
11-0.009457-0.07330.470925
12-0.015627-0.1210.45203
13-0.01401-0.10850.456973
14-0.014524-0.11250.455401
15-0.005958-0.04610.481673
16-0.010087-0.07810.468991
17-0.013193-0.10220.459471

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.923804 & 7.1558 & 0 \tabularnewline
2 & 0.833919 & 6.4595 & 0 \tabularnewline
3 & 0.709338 & 5.4945 & 0 \tabularnewline
4 & 0.592368 & 4.5885 & 1.2e-05 \tabularnewline
5 & 0.461766 & 3.5768 & 0.000348 \tabularnewline
6 & 0.330933 & 2.5634 & 0.006445 \tabularnewline
7 & 0.215171 & 1.6667 & 0.050393 \tabularnewline
8 & 0.119876 & 0.9286 & 0.17842 \tabularnewline
9 & 0.057837 & 0.448 & 0.327882 \tabularnewline
10 & 0.011037 & 0.0855 & 0.466078 \tabularnewline
11 & -0.009457 & -0.0733 & 0.470925 \tabularnewline
12 & -0.015627 & -0.121 & 0.45203 \tabularnewline
13 & -0.01401 & -0.1085 & 0.456973 \tabularnewline
14 & -0.014524 & -0.1125 & 0.455401 \tabularnewline
15 & -0.005958 & -0.0461 & 0.481673 \tabularnewline
16 & -0.010087 & -0.0781 & 0.468991 \tabularnewline
17 & -0.013193 & -0.1022 & 0.459471 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60296&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]0.923804[/C][C]7.1558[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.833919[/C][C]6.4595[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.709338[/C][C]5.4945[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.592368[/C][C]4.5885[/C][C]1.2e-05[/C][/ROW]
[ROW][C]5[/C][C]0.461766[/C][C]3.5768[/C][C]0.000348[/C][/ROW]
[ROW][C]6[/C][C]0.330933[/C][C]2.5634[/C][C]0.006445[/C][/ROW]
[ROW][C]7[/C][C]0.215171[/C][C]1.6667[/C][C]0.050393[/C][/ROW]
[ROW][C]8[/C][C]0.119876[/C][C]0.9286[/C][C]0.17842[/C][/ROW]
[ROW][C]9[/C][C]0.057837[/C][C]0.448[/C][C]0.327882[/C][/ROW]
[ROW][C]10[/C][C]0.011037[/C][C]0.0855[/C][C]0.466078[/C][/ROW]
[ROW][C]11[/C][C]-0.009457[/C][C]-0.0733[/C][C]0.470925[/C][/ROW]
[ROW][C]12[/C][C]-0.015627[/C][C]-0.121[/C][C]0.45203[/C][/ROW]
[ROW][C]13[/C][C]-0.01401[/C][C]-0.1085[/C][C]0.456973[/C][/ROW]
[ROW][C]14[/C][C]-0.014524[/C][C]-0.1125[/C][C]0.455401[/C][/ROW]
[ROW][C]15[/C][C]-0.005958[/C][C]-0.0461[/C][C]0.481673[/C][/ROW]
[ROW][C]16[/C][C]-0.010087[/C][C]-0.0781[/C][C]0.468991[/C][/ROW]
[ROW][C]17[/C][C]-0.013193[/C][C]-0.1022[/C][C]0.459471[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60296&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60296&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
10.9238047.15580
20.8339196.45950
30.7093385.49450
40.5923684.58851.2e-05
50.4617663.57680.000348
60.3309332.56340.006445
70.2151711.66670.050393
80.1198760.92860.17842
90.0578370.4480.327882
100.0110370.08550.466078
11-0.009457-0.07330.470925
12-0.015627-0.1210.45203
13-0.01401-0.10850.456973
14-0.014524-0.11250.455401
15-0.005958-0.04610.481673
16-0.010087-0.07810.468991
17-0.013193-0.10220.459471






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9238047.15580
2-0.132991-1.03010.153538
3-0.282201-2.18590.016367
40.0138990.10770.457313
5-0.133771-1.03620.152136
6-0.116715-0.90410.184787
70.0560510.43420.332861
80.039350.30480.380786
90.1012290.78410.218028
10-0.008454-0.06550.474003
110.0465030.36020.359978
120.0203010.15730.437787
13-0.071399-0.55310.29114
14-0.071322-0.55250.291344
150.0622180.48190.315801
16-0.101884-0.78920.216554
170.0043210.03350.486704

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.923804 & 7.1558 & 0 \tabularnewline
2 & -0.132991 & -1.0301 & 0.153538 \tabularnewline
3 & -0.282201 & -2.1859 & 0.016367 \tabularnewline
4 & 0.013899 & 0.1077 & 0.457313 \tabularnewline
5 & -0.133771 & -1.0362 & 0.152136 \tabularnewline
6 & -0.116715 & -0.9041 & 0.184787 \tabularnewline
7 & 0.056051 & 0.4342 & 0.332861 \tabularnewline
8 & 0.03935 & 0.3048 & 0.380786 \tabularnewline
9 & 0.101229 & 0.7841 & 0.218028 \tabularnewline
10 & -0.008454 & -0.0655 & 0.474003 \tabularnewline
11 & 0.046503 & 0.3602 & 0.359978 \tabularnewline
12 & 0.020301 & 0.1573 & 0.437787 \tabularnewline
13 & -0.071399 & -0.5531 & 0.29114 \tabularnewline
14 & -0.071322 & -0.5525 & 0.291344 \tabularnewline
15 & 0.062218 & 0.4819 & 0.315801 \tabularnewline
16 & -0.101884 & -0.7892 & 0.216554 \tabularnewline
17 & 0.004321 & 0.0335 & 0.486704 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60296&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]0.923804[/C][C]7.1558[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.132991[/C][C]-1.0301[/C][C]0.153538[/C][/ROW]
[ROW][C]3[/C][C]-0.282201[/C][C]-2.1859[/C][C]0.016367[/C][/ROW]
[ROW][C]4[/C][C]0.013899[/C][C]0.1077[/C][C]0.457313[/C][/ROW]
[ROW][C]5[/C][C]-0.133771[/C][C]-1.0362[/C][C]0.152136[/C][/ROW]
[ROW][C]6[/C][C]-0.116715[/C][C]-0.9041[/C][C]0.184787[/C][/ROW]
[ROW][C]7[/C][C]0.056051[/C][C]0.4342[/C][C]0.332861[/C][/ROW]
[ROW][C]8[/C][C]0.03935[/C][C]0.3048[/C][C]0.380786[/C][/ROW]
[ROW][C]9[/C][C]0.101229[/C][C]0.7841[/C][C]0.218028[/C][/ROW]
[ROW][C]10[/C][C]-0.008454[/C][C]-0.0655[/C][C]0.474003[/C][/ROW]
[ROW][C]11[/C][C]0.046503[/C][C]0.3602[/C][C]0.359978[/C][/ROW]
[ROW][C]12[/C][C]0.020301[/C][C]0.1573[/C][C]0.437787[/C][/ROW]
[ROW][C]13[/C][C]-0.071399[/C][C]-0.5531[/C][C]0.29114[/C][/ROW]
[ROW][C]14[/C][C]-0.071322[/C][C]-0.5525[/C][C]0.291344[/C][/ROW]
[ROW][C]15[/C][C]0.062218[/C][C]0.4819[/C][C]0.315801[/C][/ROW]
[ROW][C]16[/C][C]-0.101884[/C][C]-0.7892[/C][C]0.216554[/C][/ROW]
[ROW][C]17[/C][C]0.004321[/C][C]0.0335[/C][C]0.486704[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60296&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60296&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
10.9238047.15580
2-0.132991-1.03010.153538
3-0.282201-2.18590.016367
40.0138990.10770.457313
5-0.133771-1.03620.152136
6-0.116715-0.90410.184787
70.0560510.43420.332861
80.039350.30480.380786
90.1012290.78410.218028
10-0.008454-0.06550.474003
110.0465030.36020.359978
120.0203010.15730.437787
13-0.071399-0.55310.29114
14-0.071322-0.55250.291344
150.0622180.48190.315801
16-0.101884-0.78920.216554
170.0043210.03350.486704


Figures (Output of Computation)

Input Parameters & R Code

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