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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 computationFri, 07 Dec 2007 03:22:11 -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/2007/Dec/07/t11970222007c7ix20x5s30tqi.htm/, Retrieved Mon, 29 Apr 2024 05:17:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2734, Retrieved Mon, 29 Apr 2024 05:17:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact239

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] [Partial Autocorre...] [2007-12-07 10:22:11] [ca5e0f9f346e091f4d0fe7e17f7dba21] [Current]
-   PD    [(Partial) Autocorrelation Function] [Partial Autocorre...] [2008-10-27 19:38:03] [504b73e6de93b01331326637b3288ad4]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99
115,4
106,9
107,1
99,3
99,2
108,3
105,6
99,5
107,4
93,1
88,1
110,7
113,1
99,6
93,6
98,6
99,6
114,3
107,8
101,2
112,5
100,5
93,9
116,2
112
106,4
95,7
96
95,8
103
102,2
98,4
111,4
86,6
91,3
107,9
101,8
104,4
93,4
100,1
98,5
112,9
101,4
107,1
110,8
90,3
95,5
111,4
113
107,5
95,9
106,3
105,2
117,2
106,9
108,2
110
96,1
100,6

Tables (Output of Computation)





Summary of compuational 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 compuational 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=2734&T=0

[TABLE]
[ROW][C]Summary of compuational 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=2734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2734&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 compuational 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
017.7460
10.0809360.62690.266544
2-0.255226-1.9770.973677
3-0.095211-0.73750.768154
4-0.050211-0.38890.650648
50.1785251.38290.085918
60.2403551.86180.033767
70.090640.70210.242667
8-0.134468-1.04160.849108
9-0.164966-1.27780.896883
10-0.38219-2.96040.997803
110.0527950.40890.342018
120.5501724.26163.6e-05
13-0.149211-1.15580.873825
14-0.284067-2.20040.984179
15-0.151829-1.17610.877893
16-0.131079-1.01530.842988

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
0 & 1 & 7.746 & 0 \tabularnewline
1 & 0.080936 & 0.6269 & 0.266544 \tabularnewline
2 & -0.255226 & -1.977 & 0.973677 \tabularnewline
3 & -0.095211 & -0.7375 & 0.768154 \tabularnewline
4 & -0.050211 & -0.3889 & 0.650648 \tabularnewline
5 & 0.178525 & 1.3829 & 0.085918 \tabularnewline
6 & 0.240355 & 1.8618 & 0.033767 \tabularnewline
7 & 0.09064 & 0.7021 & 0.242667 \tabularnewline
8 & -0.134468 & -1.0416 & 0.849108 \tabularnewline
9 & -0.164966 & -1.2778 & 0.896883 \tabularnewline
10 & -0.38219 & -2.9604 & 0.997803 \tabularnewline
11 & 0.052795 & 0.4089 & 0.342018 \tabularnewline
12 & 0.550172 & 4.2616 & 3.6e-05 \tabularnewline
13 & -0.149211 & -1.1558 & 0.873825 \tabularnewline
14 & -0.284067 & -2.2004 & 0.984179 \tabularnewline
15 & -0.151829 & -1.1761 & 0.877893 \tabularnewline
16 & -0.131079 & -1.0153 & 0.842988 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2734&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]0[/C][C]1[/C][C]7.746[/C][C]0[/C][/ROW]
[ROW][C]1[/C][C]0.080936[/C][C]0.6269[/C][C]0.266544[/C][/ROW]
[ROW][C]2[/C][C]-0.255226[/C][C]-1.977[/C][C]0.973677[/C][/ROW]
[ROW][C]3[/C][C]-0.095211[/C][C]-0.7375[/C][C]0.768154[/C][/ROW]
[ROW][C]4[/C][C]-0.050211[/C][C]-0.3889[/C][C]0.650648[/C][/ROW]
[ROW][C]5[/C][C]0.178525[/C][C]1.3829[/C][C]0.085918[/C][/ROW]
[ROW][C]6[/C][C]0.240355[/C][C]1.8618[/C][C]0.033767[/C][/ROW]
[ROW][C]7[/C][C]0.09064[/C][C]0.7021[/C][C]0.242667[/C][/ROW]
[ROW][C]8[/C][C]-0.134468[/C][C]-1.0416[/C][C]0.849108[/C][/ROW]
[ROW][C]9[/C][C]-0.164966[/C][C]-1.2778[/C][C]0.896883[/C][/ROW]
[ROW][C]10[/C][C]-0.38219[/C][C]-2.9604[/C][C]0.997803[/C][/ROW]
[ROW][C]11[/C][C]0.052795[/C][C]0.4089[/C][C]0.342018[/C][/ROW]
[ROW][C]12[/C][C]0.550172[/C][C]4.2616[/C][C]3.6e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.149211[/C][C]-1.1558[/C][C]0.873825[/C][/ROW]
[ROW][C]14[/C][C]-0.284067[/C][C]-2.2004[/C][C]0.984179[/C][/ROW]
[ROW][C]15[/C][C]-0.151829[/C][C]-1.1761[/C][C]0.877893[/C][/ROW]
[ROW][C]16[/C][C]-0.131079[/C][C]-1.0153[/C][C]0.842988[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2734&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
017.7460
10.0809360.62690.266544
2-0.255226-1.9770.973677
3-0.095211-0.73750.768154
4-0.050211-0.38890.650648
50.1785251.38290.085918
60.2403551.86180.033767
70.090640.70210.242667
8-0.134468-1.04160.849108
9-0.164966-1.27780.896883
10-0.38219-2.96040.997803
110.0527950.40890.342018
120.5501724.26163.6e-05
13-0.149211-1.15580.873825
14-0.284067-2.20040.984179
15-0.151829-1.17610.877893
16-0.131079-1.01530.842988






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
00.0809360.62690.266544
1-0.263503-2.04110.977176
2-0.051688-0.40040.654849
3-0.112246-0.86950.805969
40.1689091.30840.09787
50.1841551.42650.079459
60.1592931.23390.11103
7-0.033856-0.26220.602985
8-0.068075-0.52730.700037
9-0.497251-3.85170.999856
10-0.074173-0.57450.716126
110.3812822.95340.002241
12-0.25576-1.98110.973916
13-0.032965-0.25530.600337
140.0115670.08960.464452
15-0.094432-0.73150.766329
16-0.068026-0.52690.699908

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
0 & 0.080936 & 0.6269 & 0.266544 \tabularnewline
1 & -0.263503 & -2.0411 & 0.977176 \tabularnewline
2 & -0.051688 & -0.4004 & 0.654849 \tabularnewline
3 & -0.112246 & -0.8695 & 0.805969 \tabularnewline
4 & 0.168909 & 1.3084 & 0.09787 \tabularnewline
5 & 0.184155 & 1.4265 & 0.079459 \tabularnewline
6 & 0.159293 & 1.2339 & 0.11103 \tabularnewline
7 & -0.033856 & -0.2622 & 0.602985 \tabularnewline
8 & -0.068075 & -0.5273 & 0.700037 \tabularnewline
9 & -0.497251 & -3.8517 & 0.999856 \tabularnewline
10 & -0.074173 & -0.5745 & 0.716126 \tabularnewline
11 & 0.381282 & 2.9534 & 0.002241 \tabularnewline
12 & -0.25576 & -1.9811 & 0.973916 \tabularnewline
13 & -0.032965 & -0.2553 & 0.600337 \tabularnewline
14 & 0.011567 & 0.0896 & 0.464452 \tabularnewline
15 & -0.094432 & -0.7315 & 0.766329 \tabularnewline
16 & -0.068026 & -0.5269 & 0.699908 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2734&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]0[/C][C]0.080936[/C][C]0.6269[/C][C]0.266544[/C][/ROW]
[ROW][C]1[/C][C]-0.263503[/C][C]-2.0411[/C][C]0.977176[/C][/ROW]
[ROW][C]2[/C][C]-0.051688[/C][C]-0.4004[/C][C]0.654849[/C][/ROW]
[ROW][C]3[/C][C]-0.112246[/C][C]-0.8695[/C][C]0.805969[/C][/ROW]
[ROW][C]4[/C][C]0.168909[/C][C]1.3084[/C][C]0.09787[/C][/ROW]
[ROW][C]5[/C][C]0.184155[/C][C]1.4265[/C][C]0.079459[/C][/ROW]
[ROW][C]6[/C][C]0.159293[/C][C]1.2339[/C][C]0.11103[/C][/ROW]
[ROW][C]7[/C][C]-0.033856[/C][C]-0.2622[/C][C]0.602985[/C][/ROW]
[ROW][C]8[/C][C]-0.068075[/C][C]-0.5273[/C][C]0.700037[/C][/ROW]
[ROW][C]9[/C][C]-0.497251[/C][C]-3.8517[/C][C]0.999856[/C][/ROW]
[ROW][C]10[/C][C]-0.074173[/C][C]-0.5745[/C][C]0.716126[/C][/ROW]
[ROW][C]11[/C][C]0.381282[/C][C]2.9534[/C][C]0.002241[/C][/ROW]
[ROW][C]12[/C][C]-0.25576[/C][C]-1.9811[/C][C]0.973916[/C][/ROW]
[ROW][C]13[/C][C]-0.032965[/C][C]-0.2553[/C][C]0.600337[/C][/ROW]
[ROW][C]14[/C][C]0.011567[/C][C]0.0896[/C][C]0.464452[/C][/ROW]
[ROW][C]15[/C][C]-0.094432[/C][C]-0.7315[/C][C]0.766329[/C][/ROW]
[ROW][C]16[/C][C]-0.068026[/C][C]-0.5269[/C][C]0.699908[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2734&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2734&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
00.0809360.62690.266544
1-0.263503-2.04110.977176
2-0.051688-0.40040.654849
3-0.112246-0.86950.805969
40.1689091.30840.09787
50.1841551.42650.079459
60.1592931.23390.11103
7-0.033856-0.26220.602985
8-0.068075-0.52730.700037
9-0.497251-3.85170.999856
10-0.074173-0.57450.716126
110.3812822.95340.002241
12-0.25576-1.98110.973916
13-0.032965-0.25530.600337
140.0115670.08960.464452
15-0.094432-0.73150.766329
16-0.068026-0.52690.699908


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; 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 1:par1) {
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(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-1,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(mytstat,lengthx),6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')