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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, 12 Dec 2016 14:59:05 +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/12/t1481551532y7pnrw5sy5m8yj2.htm/, Retrieved Fri, 03 May 2024 17:43:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298908, Retrieved Fri, 03 May 2024 17:43:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [(Partial) Autocor...] [2016-12-12 13:59:05] [2a4be59ea15844c348dc523b08af79fc] [Current]
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Dataseries X:
6151.2
5847.6
5662.8
5807.7
5907
6036.3
5668.2
5578.5
5760.6
5918.1
6030
6242.4
6425.1
6610.8
6943.5
5316.3
4356.6
4073.1
4239.9
4401.3
4590.6
4671
4772.1
4875.3
4601.7
4482.3
4455.6
4487.7
4606.8
4727.7
4617.9
4507.8
4398.6
4334.7
4272.9
4209.6
3963.3
3717
3469.5
3587.1
3703.5
3819.6
3777
3732.9
3687.6
3756.3
3824.7
3893.7
4039.2
4184.7
4329.9
4867.8
5405.7
5943.6
6440.7
6938.4
7435.8
6696.3
5957.1
5217.9
4781.7
4345.2
3909
3944.7
3980.1
4015.5
3983.7
3951.6
3919.8
3992.1
4064.4
4136.7
3950.1
3763.2
3577.2
3690.3
3804
3917.7
3900.9
3884.1
3867
3915
3962.4
4009.5
3820.2
3631.2
3441.9
3557.7
3674.1
3789.9
3886.2
3981.9
4078.2
4181.4
4284.9
4388.4
4190.1
3991.8
3793.5
3734.7
3675.9
3617.4
3557.7
3498
3438.6
3478.5
3518.7
3558.9
3401.1
3230.7
3060.3
3043.5
3026.4
3009.6
3159
3308.1
3457.5
3327.6
3198
3068.1
3108
3147.6
3187.5




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=298908&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=298908&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298908&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
10.94145710.44130
20.8451139.37280
30.7373458.17760
40.6313417.00190
50.5341275.92380
60.4481384.97011e-06
70.3855314.27571.9e-05
80.3397113.76760.000127
90.2997863.32480.000583
100.2547422.82520.002757
110.2113922.34440.010329
120.1696061.8810.031167
130.130441.44660.07527
140.092371.02440.15382
150.0467720.51870.302444
160.0234150.25970.397772
170.0165070.18310.427521
180.019540.21670.414396
190.0281210.31190.377829
200.0403710.44770.327566

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.941457 & 10.4413 & 0 \tabularnewline
2 & 0.845113 & 9.3728 & 0 \tabularnewline
3 & 0.737345 & 8.1776 & 0 \tabularnewline
4 & 0.631341 & 7.0019 & 0 \tabularnewline
5 & 0.534127 & 5.9238 & 0 \tabularnewline
6 & 0.448138 & 4.9701 & 1e-06 \tabularnewline
7 & 0.385531 & 4.2757 & 1.9e-05 \tabularnewline
8 & 0.339711 & 3.7676 & 0.000127 \tabularnewline
9 & 0.299786 & 3.3248 & 0.000583 \tabularnewline
10 & 0.254742 & 2.8252 & 0.002757 \tabularnewline
11 & 0.211392 & 2.3444 & 0.010329 \tabularnewline
12 & 0.169606 & 1.881 & 0.031167 \tabularnewline
13 & 0.13044 & 1.4466 & 0.07527 \tabularnewline
14 & 0.09237 & 1.0244 & 0.15382 \tabularnewline
15 & 0.046772 & 0.5187 & 0.302444 \tabularnewline
16 & 0.023415 & 0.2597 & 0.397772 \tabularnewline
17 & 0.016507 & 0.1831 & 0.427521 \tabularnewline
18 & 0.01954 & 0.2167 & 0.414396 \tabularnewline
19 & 0.028121 & 0.3119 & 0.377829 \tabularnewline
20 & 0.040371 & 0.4477 & 0.327566 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298908&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]0.941457[/C][C]10.4413[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.845113[/C][C]9.3728[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.737345[/C][C]8.1776[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.631341[/C][C]7.0019[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.534127[/C][C]5.9238[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.448138[/C][C]4.9701[/C][C]1e-06[/C][/ROW]
[ROW][C]7[/C][C]0.385531[/C][C]4.2757[/C][C]1.9e-05[/C][/ROW]
[ROW][C]8[/C][C]0.339711[/C][C]3.7676[/C][C]0.000127[/C][/ROW]
[ROW][C]9[/C][C]0.299786[/C][C]3.3248[/C][C]0.000583[/C][/ROW]
[ROW][C]10[/C][C]0.254742[/C][C]2.8252[/C][C]0.002757[/C][/ROW]
[ROW][C]11[/C][C]0.211392[/C][C]2.3444[/C][C]0.010329[/C][/ROW]
[ROW][C]12[/C][C]0.169606[/C][C]1.881[/C][C]0.031167[/C][/ROW]
[ROW][C]13[/C][C]0.13044[/C][C]1.4466[/C][C]0.07527[/C][/ROW]
[ROW][C]14[/C][C]0.09237[/C][C]1.0244[/C][C]0.15382[/C][/ROW]
[ROW][C]15[/C][C]0.046772[/C][C]0.5187[/C][C]0.302444[/C][/ROW]
[ROW][C]16[/C][C]0.023415[/C][C]0.2597[/C][C]0.397772[/C][/ROW]
[ROW][C]17[/C][C]0.016507[/C][C]0.1831[/C][C]0.427521[/C][/ROW]
[ROW][C]18[/C][C]0.01954[/C][C]0.2167[/C][C]0.414396[/C][/ROW]
[ROW][C]19[/C][C]0.028121[/C][C]0.3119[/C][C]0.377829[/C][/ROW]
[ROW][C]20[/C][C]0.040371[/C][C]0.4477[/C][C]0.327566[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298908&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298908&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
10.94145710.44130
20.8451139.37280
30.7373458.17760
40.6313417.00190
50.5341275.92380
60.4481384.97011e-06
70.3855314.27571.9e-05
80.3397113.76760.000127
90.2997863.32480.000583
100.2547422.82520.002757
110.2113922.34440.010329
120.1696061.8810.031167
130.130441.44660.07527
140.092371.02440.15382
150.0467720.51870.302444
160.0234150.25970.397772
170.0165070.18310.427521
180.019540.21670.414396
190.0281210.31190.377829
200.0403710.44770.327566







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.94145710.44130
2-0.362739-4.0235e-05
3-0.054683-0.60650.272662
4-0.012914-0.14320.443176
50.0022090.02450.490247
6-0.001187-0.01320.494759
70.1189171.31880.094835
8-0.004324-0.0480.480916
9-0.056391-0.62540.266431
10-0.097764-1.08430.140187
110.0332570.36880.35644
12-0.022872-0.25370.400091
130.0040930.04540.481934
14-0.027247-0.30220.38151
15-0.118363-1.31270.095863
160.217052.40720.008781
170.0051760.05740.477158
180.0010930.01210.495174
190.011460.12710.449534
200.0195070.21630.414539

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.941457 & 10.4413 & 0 \tabularnewline
2 & -0.362739 & -4.023 & 5e-05 \tabularnewline
3 & -0.054683 & -0.6065 & 0.272662 \tabularnewline
4 & -0.012914 & -0.1432 & 0.443176 \tabularnewline
5 & 0.002209 & 0.0245 & 0.490247 \tabularnewline
6 & -0.001187 & -0.0132 & 0.494759 \tabularnewline
7 & 0.118917 & 1.3188 & 0.094835 \tabularnewline
8 & -0.004324 & -0.048 & 0.480916 \tabularnewline
9 & -0.056391 & -0.6254 & 0.266431 \tabularnewline
10 & -0.097764 & -1.0843 & 0.140187 \tabularnewline
11 & 0.033257 & 0.3688 & 0.35644 \tabularnewline
12 & -0.022872 & -0.2537 & 0.400091 \tabularnewline
13 & 0.004093 & 0.0454 & 0.481934 \tabularnewline
14 & -0.027247 & -0.3022 & 0.38151 \tabularnewline
15 & -0.118363 & -1.3127 & 0.095863 \tabularnewline
16 & 0.21705 & 2.4072 & 0.008781 \tabularnewline
17 & 0.005176 & 0.0574 & 0.477158 \tabularnewline
18 & 0.001093 & 0.0121 & 0.495174 \tabularnewline
19 & 0.01146 & 0.1271 & 0.449534 \tabularnewline
20 & 0.019507 & 0.2163 & 0.414539 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298908&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]0.941457[/C][C]10.4413[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.362739[/C][C]-4.023[/C][C]5e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.054683[/C][C]-0.6065[/C][C]0.272662[/C][/ROW]
[ROW][C]4[/C][C]-0.012914[/C][C]-0.1432[/C][C]0.443176[/C][/ROW]
[ROW][C]5[/C][C]0.002209[/C][C]0.0245[/C][C]0.490247[/C][/ROW]
[ROW][C]6[/C][C]-0.001187[/C][C]-0.0132[/C][C]0.494759[/C][/ROW]
[ROW][C]7[/C][C]0.118917[/C][C]1.3188[/C][C]0.094835[/C][/ROW]
[ROW][C]8[/C][C]-0.004324[/C][C]-0.048[/C][C]0.480916[/C][/ROW]
[ROW][C]9[/C][C]-0.056391[/C][C]-0.6254[/C][C]0.266431[/C][/ROW]
[ROW][C]10[/C][C]-0.097764[/C][C]-1.0843[/C][C]0.140187[/C][/ROW]
[ROW][C]11[/C][C]0.033257[/C][C]0.3688[/C][C]0.35644[/C][/ROW]
[ROW][C]12[/C][C]-0.022872[/C][C]-0.2537[/C][C]0.400091[/C][/ROW]
[ROW][C]13[/C][C]0.004093[/C][C]0.0454[/C][C]0.481934[/C][/ROW]
[ROW][C]14[/C][C]-0.027247[/C][C]-0.3022[/C][C]0.38151[/C][/ROW]
[ROW][C]15[/C][C]-0.118363[/C][C]-1.3127[/C][C]0.095863[/C][/ROW]
[ROW][C]16[/C][C]0.21705[/C][C]2.4072[/C][C]0.008781[/C][/ROW]
[ROW][C]17[/C][C]0.005176[/C][C]0.0574[/C][C]0.477158[/C][/ROW]
[ROW][C]18[/C][C]0.001093[/C][C]0.0121[/C][C]0.495174[/C][/ROW]
[ROW][C]19[/C][C]0.01146[/C][C]0.1271[/C][C]0.449534[/C][/ROW]
[ROW][C]20[/C][C]0.019507[/C][C]0.2163[/C][C]0.414539[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298908&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298908&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
10.94145710.44130
2-0.362739-4.0235e-05
3-0.054683-0.60650.272662
4-0.012914-0.14320.443176
50.0022090.02450.490247
6-0.001187-0.01320.494759
70.1189171.31880.094835
8-0.004324-0.0480.480916
9-0.056391-0.62540.266431
10-0.097764-1.08430.140187
110.0332570.36880.35644
12-0.022872-0.25370.400091
130.0040930.04540.481934
14-0.027247-0.30220.38151
15-0.118363-1.31270.095863
160.217052.40720.008781
170.0051760.05740.477158
180.0010930.01210.495174
190.011460.12710.449534
200.0195070.21630.414539



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)
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')