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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, 13 Dec 2011 11:25:51 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/13/t1323793567tsxqhrsgjjg9mkh.htm/, Retrieved Thu, 31 Oct 2024 23:23:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=154495, Retrieved Thu, 31 Oct 2024 23:23:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact117
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [] [2011-12-13 16:22:12] [d6b4d011b409693eac2700c83288e3e7]
-    D    [(Partial) Autocorrelation Function] [] [2011-12-13 16:25:51] [e232377fd09030116200e3da7df6eeaf] [Current]
-   P       [(Partial) Autocorrelation Function] [] [2011-12-13 16:27:53] [d6b4d011b409693eac2700c83288e3e7]
-   P       [(Partial) Autocorrelation Function] [] [2011-12-13 16:40:08] [d6b4d011b409693eac2700c83288e3e7]
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Dataseries X:
9676
8642
9402
9610
9294
9448
10319
9548
9801
9596
8923
9746
9829
9125
9782
9441
9162
9915
10444
10209
9985
9842
9429
10132
9849
9172
10313
9819
9955
10048
10082
10541
10208
10233
9439
9963
10158
9225
10474
9757
10490
10281
10444
10640
10695
10786
9832
9747
10411
9511
10402
9701
10540
10112
10915
11183
10384
10834
9886
10216
10943
9867
10203
10837
10573
10647
11502
10656
10866
10835
9945
10331




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154495&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154495&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154495&T=0

As an alternative you can also use a 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' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4221443.5820.000308
20.4491783.81140.000144
30.4637043.93479.5e-05
40.1920021.62920.05382
50.2653742.25180.013694
60.2183671.85290.033997
70.1831851.55440.062239
80.1768771.50090.068884
90.3633873.08340.00145
100.2851562.41960.009031
110.2585462.19380.015738
120.5547774.70746e-06
130.2032941.7250.044409
140.2685532.27870.012825
150.1816821.54160.063774
160.0072540.06150.475546
170.0152960.12980.448548
18-0.043481-0.36890.356626

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.422144 & 3.582 & 0.000308 \tabularnewline
2 & 0.449178 & 3.8114 & 0.000144 \tabularnewline
3 & 0.463704 & 3.9347 & 9.5e-05 \tabularnewline
4 & 0.192002 & 1.6292 & 0.05382 \tabularnewline
5 & 0.265374 & 2.2518 & 0.013694 \tabularnewline
6 & 0.218367 & 1.8529 & 0.033997 \tabularnewline
7 & 0.183185 & 1.5544 & 0.062239 \tabularnewline
8 & 0.176877 & 1.5009 & 0.068884 \tabularnewline
9 & 0.363387 & 3.0834 & 0.00145 \tabularnewline
10 & 0.285156 & 2.4196 & 0.009031 \tabularnewline
11 & 0.258546 & 2.1938 & 0.015738 \tabularnewline
12 & 0.554777 & 4.7074 & 6e-06 \tabularnewline
13 & 0.203294 & 1.725 & 0.044409 \tabularnewline
14 & 0.268553 & 2.2787 & 0.012825 \tabularnewline
15 & 0.181682 & 1.5416 & 0.063774 \tabularnewline
16 & 0.007254 & 0.0615 & 0.475546 \tabularnewline
17 & 0.015296 & 0.1298 & 0.448548 \tabularnewline
18 & -0.043481 & -0.3689 & 0.356626 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154495&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]0.422144[/C][C]3.582[/C][C]0.000308[/C][/ROW]
[ROW][C]2[/C][C]0.449178[/C][C]3.8114[/C][C]0.000144[/C][/ROW]
[ROW][C]3[/C][C]0.463704[/C][C]3.9347[/C][C]9.5e-05[/C][/ROW]
[ROW][C]4[/C][C]0.192002[/C][C]1.6292[/C][C]0.05382[/C][/ROW]
[ROW][C]5[/C][C]0.265374[/C][C]2.2518[/C][C]0.013694[/C][/ROW]
[ROW][C]6[/C][C]0.218367[/C][C]1.8529[/C][C]0.033997[/C][/ROW]
[ROW][C]7[/C][C]0.183185[/C][C]1.5544[/C][C]0.062239[/C][/ROW]
[ROW][C]8[/C][C]0.176877[/C][C]1.5009[/C][C]0.068884[/C][/ROW]
[ROW][C]9[/C][C]0.363387[/C][C]3.0834[/C][C]0.00145[/C][/ROW]
[ROW][C]10[/C][C]0.285156[/C][C]2.4196[/C][C]0.009031[/C][/ROW]
[ROW][C]11[/C][C]0.258546[/C][C]2.1938[/C][C]0.015738[/C][/ROW]
[ROW][C]12[/C][C]0.554777[/C][C]4.7074[/C][C]6e-06[/C][/ROW]
[ROW][C]13[/C][C]0.203294[/C][C]1.725[/C][C]0.044409[/C][/ROW]
[ROW][C]14[/C][C]0.268553[/C][C]2.2787[/C][C]0.012825[/C][/ROW]
[ROW][C]15[/C][C]0.181682[/C][C]1.5416[/C][C]0.063774[/C][/ROW]
[ROW][C]16[/C][C]0.007254[/C][C]0.0615[/C][C]0.475546[/C][/ROW]
[ROW][C]17[/C][C]0.015296[/C][C]0.1298[/C][C]0.448548[/C][/ROW]
[ROW][C]18[/C][C]-0.043481[/C][C]-0.3689[/C][C]0.356626[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154495&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154495&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.4221443.5820.000308
20.4491783.81140.000144
30.4637043.93479.5e-05
40.1920021.62920.05382
50.2653742.25180.013694
60.2183671.85290.033997
70.1831851.55440.062239
80.1768771.50090.068884
90.3633873.08340.00145
100.2851562.41960.009031
110.2585462.19380.015738
120.5547774.70746e-06
130.2032941.7250.044409
140.2685532.27870.012825
150.1816821.54160.063774
160.0072540.06150.475546
170.0152960.12980.448548
18-0.043481-0.36890.356626







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4221443.5820.000308
20.3297332.79790.003297
30.2695282.2870.012568
4-0.18495-1.56940.060475
50.0307210.26070.397542
60.0494170.41930.338116
70.0948280.80460.211838
8-0.023159-0.19650.422381
90.3286832.7890.00338
100.0769830.65320.257847
11-0.047192-0.40040.345011
120.3642853.09110.001418
13-0.194683-1.65190.051451
14-0.097676-0.82880.204975
15-0.242109-2.05440.021786
16-0.00798-0.06770.473101
17-0.191188-1.62230.054557
18-0.077563-0.65810.256272

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.422144 & 3.582 & 0.000308 \tabularnewline
2 & 0.329733 & 2.7979 & 0.003297 \tabularnewline
3 & 0.269528 & 2.287 & 0.012568 \tabularnewline
4 & -0.18495 & -1.5694 & 0.060475 \tabularnewline
5 & 0.030721 & 0.2607 & 0.397542 \tabularnewline
6 & 0.049417 & 0.4193 & 0.338116 \tabularnewline
7 & 0.094828 & 0.8046 & 0.211838 \tabularnewline
8 & -0.023159 & -0.1965 & 0.422381 \tabularnewline
9 & 0.328683 & 2.789 & 0.00338 \tabularnewline
10 & 0.076983 & 0.6532 & 0.257847 \tabularnewline
11 & -0.047192 & -0.4004 & 0.345011 \tabularnewline
12 & 0.364285 & 3.0911 & 0.001418 \tabularnewline
13 & -0.194683 & -1.6519 & 0.051451 \tabularnewline
14 & -0.097676 & -0.8288 & 0.204975 \tabularnewline
15 & -0.242109 & -2.0544 & 0.021786 \tabularnewline
16 & -0.00798 & -0.0677 & 0.473101 \tabularnewline
17 & -0.191188 & -1.6223 & 0.054557 \tabularnewline
18 & -0.077563 & -0.6581 & 0.256272 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=154495&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]0.422144[/C][C]3.582[/C][C]0.000308[/C][/ROW]
[ROW][C]2[/C][C]0.329733[/C][C]2.7979[/C][C]0.003297[/C][/ROW]
[ROW][C]3[/C][C]0.269528[/C][C]2.287[/C][C]0.012568[/C][/ROW]
[ROW][C]4[/C][C]-0.18495[/C][C]-1.5694[/C][C]0.060475[/C][/ROW]
[ROW][C]5[/C][C]0.030721[/C][C]0.2607[/C][C]0.397542[/C][/ROW]
[ROW][C]6[/C][C]0.049417[/C][C]0.4193[/C][C]0.338116[/C][/ROW]
[ROW][C]7[/C][C]0.094828[/C][C]0.8046[/C][C]0.211838[/C][/ROW]
[ROW][C]8[/C][C]-0.023159[/C][C]-0.1965[/C][C]0.422381[/C][/ROW]
[ROW][C]9[/C][C]0.328683[/C][C]2.789[/C][C]0.00338[/C][/ROW]
[ROW][C]10[/C][C]0.076983[/C][C]0.6532[/C][C]0.257847[/C][/ROW]
[ROW][C]11[/C][C]-0.047192[/C][C]-0.4004[/C][C]0.345011[/C][/ROW]
[ROW][C]12[/C][C]0.364285[/C][C]3.0911[/C][C]0.001418[/C][/ROW]
[ROW][C]13[/C][C]-0.194683[/C][C]-1.6519[/C][C]0.051451[/C][/ROW]
[ROW][C]14[/C][C]-0.097676[/C][C]-0.8288[/C][C]0.204975[/C][/ROW]
[ROW][C]15[/C][C]-0.242109[/C][C]-2.0544[/C][C]0.021786[/C][/ROW]
[ROW][C]16[/C][C]-0.00798[/C][C]-0.0677[/C][C]0.473101[/C][/ROW]
[ROW][C]17[/C][C]-0.191188[/C][C]-1.6223[/C][C]0.054557[/C][/ROW]
[ROW][C]18[/C][C]-0.077563[/C][C]-0.6581[/C][C]0.256272[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=154495&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=154495&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.4221443.5820.000308
20.3297332.79790.003297
30.2695282.2870.012568
4-0.18495-1.56940.060475
50.0307210.26070.397542
60.0494170.41930.338116
70.0948280.80460.211838
8-0.023159-0.19650.422381
90.3286832.7890.00338
100.0769830.65320.257847
11-0.047192-0.40040.345011
120.3642853.09110.001418
13-0.194683-1.65190.051451
14-0.097676-0.82880.204975
15-0.242109-2.05440.021786
16-0.00798-0.06770.473101
17-0.191188-1.62230.054557
18-0.077563-0.65810.256272



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 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')