Free Statistics

of Irreproducible Research!

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 computationSun, 18 Dec 2016 17:20:35 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/18/t14820780661k6ola3s51jigxj.htm/, Retrieved Wed, 08 May 2024 03:44:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301163, Retrieved Wed, 08 May 2024 03:44:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact47
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [partial autocorre...] [2016-12-18 16:20:35] [33f2a624cfeb2efbc43d2c77b7c0dad6] [Current]
Feedback Forum

Post a new message
Dataseries X:
4870
4240
3800
3990
3290
4710
4210
4440
5040
5070
4900
4790
3890
3450
4080
3280
3130
3310
3860
4570
5110
4820
4250
4210
3610
3710
2760
2710
2710
3290
2670
3620
4440
3910
4610
3760
3460
3020
3360
2610
2670
2480
2610
3320
2800
3030
3740
3060
3040
2620
3190
2750
2630
3290
2430
2730
3690
2980
2590
3360
2370
2200
2330
2370
2200
2430
2400
2840
2870
3320
3090
2680
2420
2550
2420
2430
2330
2520
2630
2570
2800
2680
2430
2790
2420
2750
2350
2330
2290
2330
2490
2480
2760
2590
2950
2570
2960
2540
2400
2470
2390
2310
2470
2490
2510
2690
3060
2690
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301163&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=301163&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301163&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.7877148.18620
20.7287597.57350
30.6565686.82330
40.5155595.35780
50.4310064.47919e-06
60.4061634.2212.5e-05
70.3818243.9686.5e-05
80.3976684.13273.6e-05
90.4893945.08591e-06
100.5479095.6940
110.5917416.14950
120.5916176.14830
130.5825776.05430
140.5325685.53460
150.4196884.36151.5e-05
160.339363.52670.000309
170.2802552.91250.002179
180.2536462.6360.004812
190.2368542.46150.00771
200.2274332.36360.009944
210.2837372.94870.001956

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.787714 & 8.1862 & 0 \tabularnewline
2 & 0.728759 & 7.5735 & 0 \tabularnewline
3 & 0.656568 & 6.8233 & 0 \tabularnewline
4 & 0.515559 & 5.3578 & 0 \tabularnewline
5 & 0.431006 & 4.4791 & 9e-06 \tabularnewline
6 & 0.406163 & 4.221 & 2.5e-05 \tabularnewline
7 & 0.381824 & 3.968 & 6.5e-05 \tabularnewline
8 & 0.397668 & 4.1327 & 3.6e-05 \tabularnewline
9 & 0.489394 & 5.0859 & 1e-06 \tabularnewline
10 & 0.547909 & 5.694 & 0 \tabularnewline
11 & 0.591741 & 6.1495 & 0 \tabularnewline
12 & 0.591617 & 6.1483 & 0 \tabularnewline
13 & 0.582577 & 6.0543 & 0 \tabularnewline
14 & 0.532568 & 5.5346 & 0 \tabularnewline
15 & 0.419688 & 4.3615 & 1.5e-05 \tabularnewline
16 & 0.33936 & 3.5267 & 0.000309 \tabularnewline
17 & 0.280255 & 2.9125 & 0.002179 \tabularnewline
18 & 0.253646 & 2.636 & 0.004812 \tabularnewline
19 & 0.236854 & 2.4615 & 0.00771 \tabularnewline
20 & 0.227433 & 2.3636 & 0.009944 \tabularnewline
21 & 0.283737 & 2.9487 & 0.001956 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301163&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]0.787714[/C][C]8.1862[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.728759[/C][C]7.5735[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.656568[/C][C]6.8233[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.515559[/C][C]5.3578[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.431006[/C][C]4.4791[/C][C]9e-06[/C][/ROW]
[ROW][C]6[/C][C]0.406163[/C][C]4.221[/C][C]2.5e-05[/C][/ROW]
[ROW][C]7[/C][C]0.381824[/C][C]3.968[/C][C]6.5e-05[/C][/ROW]
[ROW][C]8[/C][C]0.397668[/C][C]4.1327[/C][C]3.6e-05[/C][/ROW]
[ROW][C]9[/C][C]0.489394[/C][C]5.0859[/C][C]1e-06[/C][/ROW]
[ROW][C]10[/C][C]0.547909[/C][C]5.694[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.591741[/C][C]6.1495[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.591617[/C][C]6.1483[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.582577[/C][C]6.0543[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.532568[/C][C]5.5346[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.419688[/C][C]4.3615[/C][C]1.5e-05[/C][/ROW]
[ROW][C]16[/C][C]0.33936[/C][C]3.5267[/C][C]0.000309[/C][/ROW]
[ROW][C]17[/C][C]0.280255[/C][C]2.9125[/C][C]0.002179[/C][/ROW]
[ROW][C]18[/C][C]0.253646[/C][C]2.636[/C][C]0.004812[/C][/ROW]
[ROW][C]19[/C][C]0.236854[/C][C]2.4615[/C][C]0.00771[/C][/ROW]
[ROW][C]20[/C][C]0.227433[/C][C]2.3636[/C][C]0.009944[/C][/ROW]
[ROW][C]21[/C][C]0.283737[/C][C]2.9487[/C][C]0.001956[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301163&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301163&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
10.7877148.18620
20.7287597.57350
30.6565686.82330
40.5155595.35780
50.4310064.47919e-06
60.4061634.2212.5e-05
70.3818243.9686.5e-05
80.3976684.13273.6e-05
90.4893945.08591e-06
100.5479095.6940
110.5917416.14950
120.5916176.14830
130.5825776.05430
140.5325685.53460
150.4196884.36151.5e-05
160.339363.52670.000309
170.2802552.91250.002179
180.2536462.6360.004812
190.2368542.46150.00771
200.2274332.36360.009944
210.2837372.94870.001956







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.7877148.18620
20.285282.96470.001864
30.0618480.64270.260878
4-0.212346-2.20680.014723
5-0.05574-0.57930.281808
60.172781.79560.037679
70.1626511.69030.046925
80.1355531.40870.080897
90.2692442.79810.003045
100.174061.80890.036625
110.055180.57340.283767
12-0.140154-1.45650.074075
13-0.039521-0.41070.341047
140.0027340.02840.488692
15-0.171063-1.77770.03913
16-0.105692-1.09840.137239
170.0536370.55740.289198
180.1713391.78060.038894
19-0.018175-0.18890.425272
20-0.232414-2.41530.0087
210.0375470.39020.34858

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.787714 & 8.1862 & 0 \tabularnewline
2 & 0.28528 & 2.9647 & 0.001864 \tabularnewline
3 & 0.061848 & 0.6427 & 0.260878 \tabularnewline
4 & -0.212346 & -2.2068 & 0.014723 \tabularnewline
5 & -0.05574 & -0.5793 & 0.281808 \tabularnewline
6 & 0.17278 & 1.7956 & 0.037679 \tabularnewline
7 & 0.162651 & 1.6903 & 0.046925 \tabularnewline
8 & 0.135553 & 1.4087 & 0.080897 \tabularnewline
9 & 0.269244 & 2.7981 & 0.003045 \tabularnewline
10 & 0.17406 & 1.8089 & 0.036625 \tabularnewline
11 & 0.05518 & 0.5734 & 0.283767 \tabularnewline
12 & -0.140154 & -1.4565 & 0.074075 \tabularnewline
13 & -0.039521 & -0.4107 & 0.341047 \tabularnewline
14 & 0.002734 & 0.0284 & 0.488692 \tabularnewline
15 & -0.171063 & -1.7777 & 0.03913 \tabularnewline
16 & -0.105692 & -1.0984 & 0.137239 \tabularnewline
17 & 0.053637 & 0.5574 & 0.289198 \tabularnewline
18 & 0.171339 & 1.7806 & 0.038894 \tabularnewline
19 & -0.018175 & -0.1889 & 0.425272 \tabularnewline
20 & -0.232414 & -2.4153 & 0.0087 \tabularnewline
21 & 0.037547 & 0.3902 & 0.34858 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301163&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]0.787714[/C][C]8.1862[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.28528[/C][C]2.9647[/C][C]0.001864[/C][/ROW]
[ROW][C]3[/C][C]0.061848[/C][C]0.6427[/C][C]0.260878[/C][/ROW]
[ROW][C]4[/C][C]-0.212346[/C][C]-2.2068[/C][C]0.014723[/C][/ROW]
[ROW][C]5[/C][C]-0.05574[/C][C]-0.5793[/C][C]0.281808[/C][/ROW]
[ROW][C]6[/C][C]0.17278[/C][C]1.7956[/C][C]0.037679[/C][/ROW]
[ROW][C]7[/C][C]0.162651[/C][C]1.6903[/C][C]0.046925[/C][/ROW]
[ROW][C]8[/C][C]0.135553[/C][C]1.4087[/C][C]0.080897[/C][/ROW]
[ROW][C]9[/C][C]0.269244[/C][C]2.7981[/C][C]0.003045[/C][/ROW]
[ROW][C]10[/C][C]0.17406[/C][C]1.8089[/C][C]0.036625[/C][/ROW]
[ROW][C]11[/C][C]0.05518[/C][C]0.5734[/C][C]0.283767[/C][/ROW]
[ROW][C]12[/C][C]-0.140154[/C][C]-1.4565[/C][C]0.074075[/C][/ROW]
[ROW][C]13[/C][C]-0.039521[/C][C]-0.4107[/C][C]0.341047[/C][/ROW]
[ROW][C]14[/C][C]0.002734[/C][C]0.0284[/C][C]0.488692[/C][/ROW]
[ROW][C]15[/C][C]-0.171063[/C][C]-1.7777[/C][C]0.03913[/C][/ROW]
[ROW][C]16[/C][C]-0.105692[/C][C]-1.0984[/C][C]0.137239[/C][/ROW]
[ROW][C]17[/C][C]0.053637[/C][C]0.5574[/C][C]0.289198[/C][/ROW]
[ROW][C]18[/C][C]0.171339[/C][C]1.7806[/C][C]0.038894[/C][/ROW]
[ROW][C]19[/C][C]-0.018175[/C][C]-0.1889[/C][C]0.425272[/C][/ROW]
[ROW][C]20[/C][C]-0.232414[/C][C]-2.4153[/C][C]0.0087[/C][/ROW]
[ROW][C]21[/C][C]0.037547[/C][C]0.3902[/C][C]0.34858[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301163&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301163&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
10.7877148.18620
20.285282.96470.001864
30.0618480.64270.260878
4-0.212346-2.20680.014723
5-0.05574-0.57930.281808
60.172781.79560.037679
70.1626511.69030.046925
80.1355531.40870.080897
90.2692442.79810.003045
100.174061.80890.036625
110.055180.57340.283767
12-0.140154-1.45650.074075
13-0.039521-0.41070.341047
140.0027340.02840.488692
15-0.171063-1.77770.03913
16-0.105692-1.09840.137239
170.0536370.55740.289198
180.1713391.78060.038894
19-0.018175-0.18890.425272
20-0.232414-2.41530.0087
210.0375470.39020.34858



Parameters (Session):
par4 = 12 ;
Parameters (R input):
par1 = Default ; par2 = -1.0 ; 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)
x <- na.omit(x)
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,'ACF(k)',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,'PACF(k)',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')