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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 computationWed, 17 Dec 2008 03:36:38 -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/2008/Dec/17/t1229510250armhaur4rc7ecgi.htm/, Retrieved Sun, 19 May 2024 07:46:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34296, Retrieved Sun, 19 May 2024 07:46:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

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] [PACF paper d=0 D=1] [2008-12-17 10:36:38] [e1dd70d3b1099218056e8ae5041dcc2f] [Current]
-   P     [(Partial) Autocorrelation Function] [autocorrelation f...] [2008-12-17 12:28:16] [74be16979710d4c4e7c6647856088456]
- RMP     [ARIMA Forecasting] [arima forecasting ] [2008-12-17 12:42:38] [11edab5c4db3615abbf782b1c6e7cacf]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.5
14.8
15.9
14.8
12.9
14.3
14.2
15.9
15.3
15.5
15.1
15
12.1
15.8
16.9
15.1
13.7
14.8
14.7
16
15.4
15
15.5
15.1
11.7
16.3
16.7
15
14.9
14.6
15.3
17.9
16.4
15.4
17.9
15.9
13.9
17.8
17.9
17.4
16.7
16
16.6
19.1
17.8
17.2
18.6
16.3
15.1
19.2
17.7
19.1
18
17.5
17.8
21.1
17.2
19.4
19.8
17.6
16.2
19.5
19.9
20
17.3
18.9
18.6
21.4
18.6
19.8
20.8
19.6
17.7
19.8
22.2
20.7
17.9
21.2
21.4
21.7
23.2
21.5
22.9
23.2
18.6

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=34296&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=34296&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34296&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
10.0920020.78610.217187
20.2783592.37830.010006
30.5343434.56541e-05
40.1095580.93610.176164
50.1595721.36340.088476
60.3327982.84340.002893
7-0.078036-0.66670.25352
80.1078220.92120.179983
90.1986411.69720.04696
10-0.092172-0.78750.216763
11-0.033537-0.28650.387639
120.0446640.38160.351931
13-0.144822-1.23740.109959
14-0.055549-0.47460.318241
15-0.021719-0.18560.42665
16-0.256374-2.19050.015843
170.0099180.08470.46635
18-0.021188-0.1810.428421
19-0.182929-1.5630.061195

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.092002 & 0.7861 & 0.217187 \tabularnewline
2 & 0.278359 & 2.3783 & 0.010006 \tabularnewline
3 & 0.534343 & 4.5654 & 1e-05 \tabularnewline
4 & 0.109558 & 0.9361 & 0.176164 \tabularnewline
5 & 0.159572 & 1.3634 & 0.088476 \tabularnewline
6 & 0.332798 & 2.8434 & 0.002893 \tabularnewline
7 & -0.078036 & -0.6667 & 0.25352 \tabularnewline
8 & 0.107822 & 0.9212 & 0.179983 \tabularnewline
9 & 0.198641 & 1.6972 & 0.04696 \tabularnewline
10 & -0.092172 & -0.7875 & 0.216763 \tabularnewline
11 & -0.033537 & -0.2865 & 0.387639 \tabularnewline
12 & 0.044664 & 0.3816 & 0.351931 \tabularnewline
13 & -0.144822 & -1.2374 & 0.109959 \tabularnewline
14 & -0.055549 & -0.4746 & 0.318241 \tabularnewline
15 & -0.021719 & -0.1856 & 0.42665 \tabularnewline
16 & -0.256374 & -2.1905 & 0.015843 \tabularnewline
17 & 0.009918 & 0.0847 & 0.46635 \tabularnewline
18 & -0.021188 & -0.181 & 0.428421 \tabularnewline
19 & -0.182929 & -1.563 & 0.061195 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34296&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]0.092002[/C][C]0.7861[/C][C]0.217187[/C][/ROW]
[ROW][C]2[/C][C]0.278359[/C][C]2.3783[/C][C]0.010006[/C][/ROW]
[ROW][C]3[/C][C]0.534343[/C][C]4.5654[/C][C]1e-05[/C][/ROW]
[ROW][C]4[/C][C]0.109558[/C][C]0.9361[/C][C]0.176164[/C][/ROW]
[ROW][C]5[/C][C]0.159572[/C][C]1.3634[/C][C]0.088476[/C][/ROW]
[ROW][C]6[/C][C]0.332798[/C][C]2.8434[/C][C]0.002893[/C][/ROW]
[ROW][C]7[/C][C]-0.078036[/C][C]-0.6667[/C][C]0.25352[/C][/ROW]
[ROW][C]8[/C][C]0.107822[/C][C]0.9212[/C][C]0.179983[/C][/ROW]
[ROW][C]9[/C][C]0.198641[/C][C]1.6972[/C][C]0.04696[/C][/ROW]
[ROW][C]10[/C][C]-0.092172[/C][C]-0.7875[/C][C]0.216763[/C][/ROW]
[ROW][C]11[/C][C]-0.033537[/C][C]-0.2865[/C][C]0.387639[/C][/ROW]
[ROW][C]12[/C][C]0.044664[/C][C]0.3816[/C][C]0.351931[/C][/ROW]
[ROW][C]13[/C][C]-0.144822[/C][C]-1.2374[/C][C]0.109959[/C][/ROW]
[ROW][C]14[/C][C]-0.055549[/C][C]-0.4746[/C][C]0.318241[/C][/ROW]
[ROW][C]15[/C][C]-0.021719[/C][C]-0.1856[/C][C]0.42665[/C][/ROW]
[ROW][C]16[/C][C]-0.256374[/C][C]-2.1905[/C][C]0.015843[/C][/ROW]
[ROW][C]17[/C][C]0.009918[/C][C]0.0847[/C][C]0.46635[/C][/ROW]
[ROW][C]18[/C][C]-0.021188[/C][C]-0.181[/C][C]0.428421[/C][/ROW]
[ROW][C]19[/C][C]-0.182929[/C][C]-1.563[/C][C]0.061195[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34296&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34296&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
10.0920020.78610.217187
20.2783592.37830.010006
30.5343434.56541e-05
40.1095580.93610.176164
50.1595721.36340.088476
60.3327982.84340.002893
7-0.078036-0.66670.25352
80.1078220.92120.179983
90.1986411.69720.04696
10-0.092172-0.78750.216763
11-0.033537-0.28650.387639
120.0446640.38160.351931
13-0.144822-1.23740.109959
14-0.055549-0.47460.318241
15-0.021719-0.18560.42665
16-0.256374-2.19050.015843
170.0099180.08470.46635
18-0.021188-0.1810.428421
19-0.182929-1.5630.061195






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0920020.78610.217187
20.2721992.32570.011409
30.5344494.56631e-05
40.0557070.4760.317761
5-0.157485-1.34560.091306
60.0187430.16010.436606
7-0.208088-1.77790.039792
8-0.048932-0.41810.338559
90.1348761.15240.126462
100.0574970.49130.312359
11-0.167858-1.43420.077896
12-0.164619-1.40650.081909
13-0.050108-0.42810.334911
140.0414440.35410.362145
150.089840.76760.222603
16-0.134442-1.14870.127221
170.0554070.47340.318671
180.0891980.76210.224226
190.0133580.11410.454725

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.092002 & 0.7861 & 0.217187 \tabularnewline
2 & 0.272199 & 2.3257 & 0.011409 \tabularnewline
3 & 0.534449 & 4.5663 & 1e-05 \tabularnewline
4 & 0.055707 & 0.476 & 0.317761 \tabularnewline
5 & -0.157485 & -1.3456 & 0.091306 \tabularnewline
6 & 0.018743 & 0.1601 & 0.436606 \tabularnewline
7 & -0.208088 & -1.7779 & 0.039792 \tabularnewline
8 & -0.048932 & -0.4181 & 0.338559 \tabularnewline
9 & 0.134876 & 1.1524 & 0.126462 \tabularnewline
10 & 0.057497 & 0.4913 & 0.312359 \tabularnewline
11 & -0.167858 & -1.4342 & 0.077896 \tabularnewline
12 & -0.164619 & -1.4065 & 0.081909 \tabularnewline
13 & -0.050108 & -0.4281 & 0.334911 \tabularnewline
14 & 0.041444 & 0.3541 & 0.362145 \tabularnewline
15 & 0.08984 & 0.7676 & 0.222603 \tabularnewline
16 & -0.134442 & -1.1487 & 0.127221 \tabularnewline
17 & 0.055407 & 0.4734 & 0.318671 \tabularnewline
18 & 0.089198 & 0.7621 & 0.224226 \tabularnewline
19 & 0.013358 & 0.1141 & 0.454725 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34296&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]0.092002[/C][C]0.7861[/C][C]0.217187[/C][/ROW]
[ROW][C]2[/C][C]0.272199[/C][C]2.3257[/C][C]0.011409[/C][/ROW]
[ROW][C]3[/C][C]0.534449[/C][C]4.5663[/C][C]1e-05[/C][/ROW]
[ROW][C]4[/C][C]0.055707[/C][C]0.476[/C][C]0.317761[/C][/ROW]
[ROW][C]5[/C][C]-0.157485[/C][C]-1.3456[/C][C]0.091306[/C][/ROW]
[ROW][C]6[/C][C]0.018743[/C][C]0.1601[/C][C]0.436606[/C][/ROW]
[ROW][C]7[/C][C]-0.208088[/C][C]-1.7779[/C][C]0.039792[/C][/ROW]
[ROW][C]8[/C][C]-0.048932[/C][C]-0.4181[/C][C]0.338559[/C][/ROW]
[ROW][C]9[/C][C]0.134876[/C][C]1.1524[/C][C]0.126462[/C][/ROW]
[ROW][C]10[/C][C]0.057497[/C][C]0.4913[/C][C]0.312359[/C][/ROW]
[ROW][C]11[/C][C]-0.167858[/C][C]-1.4342[/C][C]0.077896[/C][/ROW]
[ROW][C]12[/C][C]-0.164619[/C][C]-1.4065[/C][C]0.081909[/C][/ROW]
[ROW][C]13[/C][C]-0.050108[/C][C]-0.4281[/C][C]0.334911[/C][/ROW]
[ROW][C]14[/C][C]0.041444[/C][C]0.3541[/C][C]0.362145[/C][/ROW]
[ROW][C]15[/C][C]0.08984[/C][C]0.7676[/C][C]0.222603[/C][/ROW]
[ROW][C]16[/C][C]-0.134442[/C][C]-1.1487[/C][C]0.127221[/C][/ROW]
[ROW][C]17[/C][C]0.055407[/C][C]0.4734[/C][C]0.318671[/C][/ROW]
[ROW][C]18[/C][C]0.089198[/C][C]0.7621[/C][C]0.224226[/C][/ROW]
[ROW][C]19[/C][C]0.013358[/C][C]0.1141[/C][C]0.454725[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34296&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34296&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
10.0920020.78610.217187
20.2721992.32570.011409
30.5344494.56631e-05
40.0557070.4760.317761
5-0.157485-1.34560.091306
60.0187430.16010.436606
7-0.208088-1.77790.039792
8-0.048932-0.41810.338559
90.1348761.15240.126462
100.0574970.49130.312359
11-0.167858-1.43420.077896
12-0.164619-1.40650.081909
13-0.050108-0.42810.334911
140.0414440.35410.362145
150.089840.76760.222603
16-0.134442-1.14870.127221
170.0554070.47340.318671
180.0891980.76210.224226
190.0133580.11410.454725


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')