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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 computationMon, 19 Dec 2016 20:39:03 +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/19/t14821763731nr8c8zlvw7eio4.htm/, Retrieved Fri, 17 May 2024 16:27:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=301470, Retrieved Fri, 17 May 2024 16:27:28 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact73
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [N2044 Variance re...] [2016-12-19 19:39:03] [2e11ca31a00cf8de75c33c1af2d59434] [Current]
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Dataseries X:
3880
3740
3990
3970
4100
3920
3850
4190
3990
4140
4080
3900
4070
3930
4210
4020
4120
4020
3910
4110
4130
4340
4200
4200
4160
3920
4280
3940
4190
4150
4070
4130
3960
4320
4110
4100
4280
3990
4360
4240
4450
4190
3950
4300
4150
4540
4240
4210
4390
4140
4460
4290
4430
4390
4340
4570
4470
4550
4420
4490
4480
4400
4770
4450
4610
4540
4520
4710
4580
4760
4450
4500
4660
4370
5030
4510
4740
4690
4580
4850
4730
4890
4740
4600
4740
4520
5000
4670
4940
4790
4820
5010
4870
5070
4770
4840
4850
4590
5050
4770
4720
4740
4400
4840
4650
4860
4580
4640
4800
4660
5020
4700
4800
4700
4560




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=301470&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=301470&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301470&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
10.5008115.08271e-06
20.4468784.53538e-06
30.3780573.83690.000108
40.2212872.24580.013425
50.3016853.06180.001403
60.2448162.48460.00729
70.1536391.55930.061001
80.232632.36090.010055
90.0776310.78790.216293
100.1112271.12880.130796
11-0.000653-0.00660.497362
12-0.226068-2.29430.0119
13-0.011735-0.11910.452714
14-0.066882-0.67880.249402
150.0240970.24460.403644
160.1179151.19670.117084
17-0.038643-0.39220.347867
18-0.010483-0.10640.457741
19-0.031192-0.31660.376109
20-0.136798-1.38830.084014

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.500811 & 5.0827 & 1e-06 \tabularnewline
2 & 0.446878 & 4.5353 & 8e-06 \tabularnewline
3 & 0.378057 & 3.8369 & 0.000108 \tabularnewline
4 & 0.221287 & 2.2458 & 0.013425 \tabularnewline
5 & 0.301685 & 3.0618 & 0.001403 \tabularnewline
6 & 0.244816 & 2.4846 & 0.00729 \tabularnewline
7 & 0.153639 & 1.5593 & 0.061001 \tabularnewline
8 & 0.23263 & 2.3609 & 0.010055 \tabularnewline
9 & 0.077631 & 0.7879 & 0.216293 \tabularnewline
10 & 0.111227 & 1.1288 & 0.130796 \tabularnewline
11 & -0.000653 & -0.0066 & 0.497362 \tabularnewline
12 & -0.226068 & -2.2943 & 0.0119 \tabularnewline
13 & -0.011735 & -0.1191 & 0.452714 \tabularnewline
14 & -0.066882 & -0.6788 & 0.249402 \tabularnewline
15 & 0.024097 & 0.2446 & 0.403644 \tabularnewline
16 & 0.117915 & 1.1967 & 0.117084 \tabularnewline
17 & -0.038643 & -0.3922 & 0.347867 \tabularnewline
18 & -0.010483 & -0.1064 & 0.457741 \tabularnewline
19 & -0.031192 & -0.3166 & 0.376109 \tabularnewline
20 & -0.136798 & -1.3883 & 0.084014 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301470&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]0.500811[/C][C]5.0827[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.446878[/C][C]4.5353[/C][C]8e-06[/C][/ROW]
[ROW][C]3[/C][C]0.378057[/C][C]3.8369[/C][C]0.000108[/C][/ROW]
[ROW][C]4[/C][C]0.221287[/C][C]2.2458[/C][C]0.013425[/C][/ROW]
[ROW][C]5[/C][C]0.301685[/C][C]3.0618[/C][C]0.001403[/C][/ROW]
[ROW][C]6[/C][C]0.244816[/C][C]2.4846[/C][C]0.00729[/C][/ROW]
[ROW][C]7[/C][C]0.153639[/C][C]1.5593[/C][C]0.061001[/C][/ROW]
[ROW][C]8[/C][C]0.23263[/C][C]2.3609[/C][C]0.010055[/C][/ROW]
[ROW][C]9[/C][C]0.077631[/C][C]0.7879[/C][C]0.216293[/C][/ROW]
[ROW][C]10[/C][C]0.111227[/C][C]1.1288[/C][C]0.130796[/C][/ROW]
[ROW][C]11[/C][C]-0.000653[/C][C]-0.0066[/C][C]0.497362[/C][/ROW]
[ROW][C]12[/C][C]-0.226068[/C][C]-2.2943[/C][C]0.0119[/C][/ROW]
[ROW][C]13[/C][C]-0.011735[/C][C]-0.1191[/C][C]0.452714[/C][/ROW]
[ROW][C]14[/C][C]-0.066882[/C][C]-0.6788[/C][C]0.249402[/C][/ROW]
[ROW][C]15[/C][C]0.024097[/C][C]0.2446[/C][C]0.403644[/C][/ROW]
[ROW][C]16[/C][C]0.117915[/C][C]1.1967[/C][C]0.117084[/C][/ROW]
[ROW][C]17[/C][C]-0.038643[/C][C]-0.3922[/C][C]0.347867[/C][/ROW]
[ROW][C]18[/C][C]-0.010483[/C][C]-0.1064[/C][C]0.457741[/C][/ROW]
[ROW][C]19[/C][C]-0.031192[/C][C]-0.3166[/C][C]0.376109[/C][/ROW]
[ROW][C]20[/C][C]-0.136798[/C][C]-1.3883[/C][C]0.084014[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301470&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301470&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
10.5008115.08271e-06
20.4468784.53538e-06
30.3780573.83690.000108
40.2212872.24580.013425
50.3016853.06180.001403
60.2448162.48460.00729
70.1536391.55930.061001
80.232632.36090.010055
90.0776310.78790.216293
100.1112271.12880.130796
11-0.000653-0.00660.497362
12-0.226068-2.29430.0119
13-0.011735-0.11910.452714
14-0.066882-0.67880.249402
150.0240970.24460.403644
160.1179151.19670.117084
17-0.038643-0.39220.347867
18-0.010483-0.10640.457741
19-0.031192-0.31660.376109
20-0.136798-1.38830.084014







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.5008115.08271e-06
20.2617052.6560.004582
30.1171571.1890.118584
4-0.09178-0.93150.176896
50.1667871.69270.046767
60.045070.45740.32417
7-0.079599-0.80780.210522
80.1061871.07770.141847
9-0.113539-1.15230.125933
100.0295760.30020.382329
11-0.162245-1.64660.051343
12-0.307038-3.11610.001187
130.2338562.37340.00974
140.051590.52360.300846
150.1381581.40210.081939
160.0761890.77320.220577
17-0.080372-0.81570.208281
18-0.0478-0.48510.314312
19-0.053342-0.54140.294713
20-0.079401-0.80580.211097

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.500811 & 5.0827 & 1e-06 \tabularnewline
2 & 0.261705 & 2.656 & 0.004582 \tabularnewline
3 & 0.117157 & 1.189 & 0.118584 \tabularnewline
4 & -0.09178 & -0.9315 & 0.176896 \tabularnewline
5 & 0.166787 & 1.6927 & 0.046767 \tabularnewline
6 & 0.04507 & 0.4574 & 0.32417 \tabularnewline
7 & -0.079599 & -0.8078 & 0.210522 \tabularnewline
8 & 0.106187 & 1.0777 & 0.141847 \tabularnewline
9 & -0.113539 & -1.1523 & 0.125933 \tabularnewline
10 & 0.029576 & 0.3002 & 0.382329 \tabularnewline
11 & -0.162245 & -1.6466 & 0.051343 \tabularnewline
12 & -0.307038 & -3.1161 & 0.001187 \tabularnewline
13 & 0.233856 & 2.3734 & 0.00974 \tabularnewline
14 & 0.05159 & 0.5236 & 0.300846 \tabularnewline
15 & 0.138158 & 1.4021 & 0.081939 \tabularnewline
16 & 0.076189 & 0.7732 & 0.220577 \tabularnewline
17 & -0.080372 & -0.8157 & 0.208281 \tabularnewline
18 & -0.0478 & -0.4851 & 0.314312 \tabularnewline
19 & -0.053342 & -0.5414 & 0.294713 \tabularnewline
20 & -0.079401 & -0.8058 & 0.211097 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=301470&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]0.500811[/C][C]5.0827[/C][C]1e-06[/C][/ROW]
[ROW][C]2[/C][C]0.261705[/C][C]2.656[/C][C]0.004582[/C][/ROW]
[ROW][C]3[/C][C]0.117157[/C][C]1.189[/C][C]0.118584[/C][/ROW]
[ROW][C]4[/C][C]-0.09178[/C][C]-0.9315[/C][C]0.176896[/C][/ROW]
[ROW][C]5[/C][C]0.166787[/C][C]1.6927[/C][C]0.046767[/C][/ROW]
[ROW][C]6[/C][C]0.04507[/C][C]0.4574[/C][C]0.32417[/C][/ROW]
[ROW][C]7[/C][C]-0.079599[/C][C]-0.8078[/C][C]0.210522[/C][/ROW]
[ROW][C]8[/C][C]0.106187[/C][C]1.0777[/C][C]0.141847[/C][/ROW]
[ROW][C]9[/C][C]-0.113539[/C][C]-1.1523[/C][C]0.125933[/C][/ROW]
[ROW][C]10[/C][C]0.029576[/C][C]0.3002[/C][C]0.382329[/C][/ROW]
[ROW][C]11[/C][C]-0.162245[/C][C]-1.6466[/C][C]0.051343[/C][/ROW]
[ROW][C]12[/C][C]-0.307038[/C][C]-3.1161[/C][C]0.001187[/C][/ROW]
[ROW][C]13[/C][C]0.233856[/C][C]2.3734[/C][C]0.00974[/C][/ROW]
[ROW][C]14[/C][C]0.05159[/C][C]0.5236[/C][C]0.300846[/C][/ROW]
[ROW][C]15[/C][C]0.138158[/C][C]1.4021[/C][C]0.081939[/C][/ROW]
[ROW][C]16[/C][C]0.076189[/C][C]0.7732[/C][C]0.220577[/C][/ROW]
[ROW][C]17[/C][C]-0.080372[/C][C]-0.8157[/C][C]0.208281[/C][/ROW]
[ROW][C]18[/C][C]-0.0478[/C][C]-0.4851[/C][C]0.314312[/C][/ROW]
[ROW][C]19[/C][C]-0.053342[/C][C]-0.5414[/C][C]0.294713[/C][/ROW]
[ROW][C]20[/C][C]-0.079401[/C][C]-0.8058[/C][C]0.211097[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=301470&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=301470&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
10.5008115.08271e-06
20.2617052.6560.004582
30.1171571.1890.118584
4-0.09178-0.93150.176896
50.1667871.69270.046767
60.045070.45740.32417
7-0.079599-0.80780.210522
80.1061871.07770.141847
9-0.113539-1.15230.125933
100.0295760.30020.382329
11-0.162245-1.64660.051343
12-0.307038-3.11610.001187
130.2338562.37340.00974
140.051590.52360.300846
150.1381581.40210.081939
160.0761890.77320.220577
17-0.080372-0.81570.208281
18-0.0478-0.48510.314312
19-0.053342-0.54140.294713
20-0.079401-0.80580.211097



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; 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')