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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 computationTue, 08 Dec 2009 12:36:17 -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/08/t12603011031ti1tfpflchpmlo.htm/, Retrieved Sun, 28 Apr 2024 16:20:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64813, Retrieved Sun, 28 Apr 2024 16:20:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsJSSHWWS9Rev
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Backward Selection] [WS 9 Arima backwa...] [2009-12-04 14:47:12] [2f17fb7f9ce5412e0690130b6ae01587]
- RMP   [(Partial) Autocorrelation Function] [review] [2009-12-08 19:25:53] [214e6e00abbde49700521a7ef1d30da2]
-   PD      [(Partial) Autocorrelation Function] [Review] [2009-12-08 19:36:17] [c8fd62404619100d8e91184019148412] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
96.8
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

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=64813&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=64813&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64813&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
1-0.336203-2.58240.006156
2-0.240933-1.85060.034615
30.1320681.01440.15726
4-0.204044-1.56730.061197
50.1423941.09380.139255
60.0985040.75660.226144
70.0321090.24660.403025
8-0.068914-0.52930.299279
90.118020.90650.184171
10-0.325682-2.50160.007578
11-0.097652-0.75010.228093
120.6015384.62051.1e-05
13-0.183193-1.40710.082317
14-0.140815-1.08160.141911
15-0.029761-0.22860.409986
16-0.061794-0.47460.318395
170.1327561.01970.156013

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.336203 & -2.5824 & 0.006156 \tabularnewline
2 & -0.240933 & -1.8506 & 0.034615 \tabularnewline
3 & 0.132068 & 1.0144 & 0.15726 \tabularnewline
4 & -0.204044 & -1.5673 & 0.061197 \tabularnewline
5 & 0.142394 & 1.0938 & 0.139255 \tabularnewline
6 & 0.098504 & 0.7566 & 0.226144 \tabularnewline
7 & 0.032109 & 0.2466 & 0.403025 \tabularnewline
8 & -0.068914 & -0.5293 & 0.299279 \tabularnewline
9 & 0.11802 & 0.9065 & 0.184171 \tabularnewline
10 & -0.325682 & -2.5016 & 0.007578 \tabularnewline
11 & -0.097652 & -0.7501 & 0.228093 \tabularnewline
12 & 0.601538 & 4.6205 & 1.1e-05 \tabularnewline
13 & -0.183193 & -1.4071 & 0.082317 \tabularnewline
14 & -0.140815 & -1.0816 & 0.141911 \tabularnewline
15 & -0.029761 & -0.2286 & 0.409986 \tabularnewline
16 & -0.061794 & -0.4746 & 0.318395 \tabularnewline
17 & 0.132756 & 1.0197 & 0.156013 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64813&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]-0.336203[/C][C]-2.5824[/C][C]0.006156[/C][/ROW]
[ROW][C]2[/C][C]-0.240933[/C][C]-1.8506[/C][C]0.034615[/C][/ROW]
[ROW][C]3[/C][C]0.132068[/C][C]1.0144[/C][C]0.15726[/C][/ROW]
[ROW][C]4[/C][C]-0.204044[/C][C]-1.5673[/C][C]0.061197[/C][/ROW]
[ROW][C]5[/C][C]0.142394[/C][C]1.0938[/C][C]0.139255[/C][/ROW]
[ROW][C]6[/C][C]0.098504[/C][C]0.7566[/C][C]0.226144[/C][/ROW]
[ROW][C]7[/C][C]0.032109[/C][C]0.2466[/C][C]0.403025[/C][/ROW]
[ROW][C]8[/C][C]-0.068914[/C][C]-0.5293[/C][C]0.299279[/C][/ROW]
[ROW][C]9[/C][C]0.11802[/C][C]0.9065[/C][C]0.184171[/C][/ROW]
[ROW][C]10[/C][C]-0.325682[/C][C]-2.5016[/C][C]0.007578[/C][/ROW]
[ROW][C]11[/C][C]-0.097652[/C][C]-0.7501[/C][C]0.228093[/C][/ROW]
[ROW][C]12[/C][C]0.601538[/C][C]4.6205[/C][C]1.1e-05[/C][/ROW]
[ROW][C]13[/C][C]-0.183193[/C][C]-1.4071[/C][C]0.082317[/C][/ROW]
[ROW][C]14[/C][C]-0.140815[/C][C]-1.0816[/C][C]0.141911[/C][/ROW]
[ROW][C]15[/C][C]-0.029761[/C][C]-0.2286[/C][C]0.409986[/C][/ROW]
[ROW][C]16[/C][C]-0.061794[/C][C]-0.4746[/C][C]0.318395[/C][/ROW]
[ROW][C]17[/C][C]0.132756[/C][C]1.0197[/C][C]0.156013[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64813&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64813&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
1-0.336203-2.58240.006156
2-0.240933-1.85060.034615
30.1320681.01440.15726
4-0.204044-1.56730.061197
50.1423941.09380.139255
60.0985040.75660.226144
70.0321090.24660.403025
8-0.068914-0.52930.299279
90.118020.90650.184171
10-0.325682-2.50160.007578
11-0.097652-0.75010.228093
120.6015384.62051.1e-05
13-0.183193-1.40710.082317
14-0.140815-1.08160.141911
15-0.029761-0.22860.409986
16-0.061794-0.47460.318395
170.1327561.01970.156013






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.336203-2.58240.006156
2-0.399073-3.06530.001639
3-0.154792-1.1890.119605
4-0.411488-3.16070.001242
5-0.197839-1.51960.066972
6-0.143465-1.1020.137473
70.113320.87040.193797
80.0633760.48680.314102
90.4394073.37510.000655
10-0.076782-0.58980.278797
11-0.340083-2.61220.005696
120.2237531.71870.045458
130.2387181.83360.035877
140.081340.62480.26726
15-0.171152-1.31460.096858
160.0409680.31470.377057
170.1163960.89410.187463

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.336203 & -2.5824 & 0.006156 \tabularnewline
2 & -0.399073 & -3.0653 & 0.001639 \tabularnewline
3 & -0.154792 & -1.189 & 0.119605 \tabularnewline
4 & -0.411488 & -3.1607 & 0.001242 \tabularnewline
5 & -0.197839 & -1.5196 & 0.066972 \tabularnewline
6 & -0.143465 & -1.102 & 0.137473 \tabularnewline
7 & 0.11332 & 0.8704 & 0.193797 \tabularnewline
8 & 0.063376 & 0.4868 & 0.314102 \tabularnewline
9 & 0.439407 & 3.3751 & 0.000655 \tabularnewline
10 & -0.076782 & -0.5898 & 0.278797 \tabularnewline
11 & -0.340083 & -2.6122 & 0.005696 \tabularnewline
12 & 0.223753 & 1.7187 & 0.045458 \tabularnewline
13 & 0.238718 & 1.8336 & 0.035877 \tabularnewline
14 & 0.08134 & 0.6248 & 0.26726 \tabularnewline
15 & -0.171152 & -1.3146 & 0.096858 \tabularnewline
16 & 0.040968 & 0.3147 & 0.377057 \tabularnewline
17 & 0.116396 & 0.8941 & 0.187463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64813&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]-0.336203[/C][C]-2.5824[/C][C]0.006156[/C][/ROW]
[ROW][C]2[/C][C]-0.399073[/C][C]-3.0653[/C][C]0.001639[/C][/ROW]
[ROW][C]3[/C][C]-0.154792[/C][C]-1.189[/C][C]0.119605[/C][/ROW]
[ROW][C]4[/C][C]-0.411488[/C][C]-3.1607[/C][C]0.001242[/C][/ROW]
[ROW][C]5[/C][C]-0.197839[/C][C]-1.5196[/C][C]0.066972[/C][/ROW]
[ROW][C]6[/C][C]-0.143465[/C][C]-1.102[/C][C]0.137473[/C][/ROW]
[ROW][C]7[/C][C]0.11332[/C][C]0.8704[/C][C]0.193797[/C][/ROW]
[ROW][C]8[/C][C]0.063376[/C][C]0.4868[/C][C]0.314102[/C][/ROW]
[ROW][C]9[/C][C]0.439407[/C][C]3.3751[/C][C]0.000655[/C][/ROW]
[ROW][C]10[/C][C]-0.076782[/C][C]-0.5898[/C][C]0.278797[/C][/ROW]
[ROW][C]11[/C][C]-0.340083[/C][C]-2.6122[/C][C]0.005696[/C][/ROW]
[ROW][C]12[/C][C]0.223753[/C][C]1.7187[/C][C]0.045458[/C][/ROW]
[ROW][C]13[/C][C]0.238718[/C][C]1.8336[/C][C]0.035877[/C][/ROW]
[ROW][C]14[/C][C]0.08134[/C][C]0.6248[/C][C]0.26726[/C][/ROW]
[ROW][C]15[/C][C]-0.171152[/C][C]-1.3146[/C][C]0.096858[/C][/ROW]
[ROW][C]16[/C][C]0.040968[/C][C]0.3147[/C][C]0.377057[/C][/ROW]
[ROW][C]17[/C][C]0.116396[/C][C]0.8941[/C][C]0.187463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64813&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64813&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
1-0.336203-2.58240.006156
2-0.399073-3.06530.001639
3-0.154792-1.1890.119605
4-0.411488-3.16070.001242
5-0.197839-1.51960.066972
6-0.143465-1.1020.137473
70.113320.87040.193797
80.0633760.48680.314102
90.4394073.37510.000655
10-0.076782-0.58980.278797
11-0.340083-2.61220.005696
120.2237531.71870.045458
130.2387181.83360.035877
140.081340.62480.26726
15-0.171152-1.31460.096858
160.0409680.31470.377057
170.1163960.89410.187463


Figures (Output of Computation)

Input Parameters & R Code

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