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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 computationSun, 27 Dec 2009 02:56:27 -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/27/t12619082664x4qh0pu3l2f2ir.htm/, Retrieved Thu, 02 May 2024 15:30:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70807, Retrieved Thu, 02 May 2024 15:30:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [Spectraalanalyse ...] [2008-12-11 17:29:14] [12d343c4448a5f9e527bb31caeac580b]
- RMPD    [(Partial) Autocorrelation Function] [Paper PACF d=1] [2009-12-27 09:56:27] [eba9f01697e64705b70041e6f338cb22] [Current]
-   PD      [(Partial) Autocorrelation Function] [paper lambda 0] [2010-12-18 12:47:28] [d87a19cd5db53e12ea62bda70b3bb267]
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Dataseries X:
100.21
100.36
100.62
100.78
100.93
100.70
100.00
100.20
99.68
99.56
100.06
100.50
99.30
99.37
99.20
98.11
97.60
97.76
98.06
98.25
98.50
97.39
98.09
97.78
98.12
97.50
97.30
97.64
96.88
97.40
98.27
97.94
98.61
98.72
98.62
98.56
98.06
97.40
97.76
97.05
97.85
97.40
97.27
97.93
98.60
98.70
98.88
98.27
97.85
97.70
96.97
97.72
97.66
99.00
98.86
99.56
100.19
100.37
100.01
99.68
99.78
99.36
99.21
99.26
99.26
100.43
101.50
102.27
102.69
103.47
104.02
103.55
103.77
104.19
103.64
103.68
105.39
106.61
108.12
109.22
110.17
110.31
111.06
111.14
111.39
112.51
111.28
112.22
113.19
114.32
115.34
116.61
117.83
117.70
118.51
118.82
119.49
119.57
120.00
121.96
121.45
123.41
124.44
126.25
127.41
127.63
129.19
129.82
130.45
132.02
132.72
132.96
135.06
137.04
137.83
139.17
140.35
141.01
141.89
143.28
142.90
143.37
145.03
146.05
147.39
149.58
151.02
153.57
155.60
157.18
158.77
159.95
161.34
161.95
163.36
165.00
166.65
168.65
170.29
172.70
173.79
176.45
177.58
179.19
181.01
184.08
185.63
188.51
190.18
192.19
193.47
196.73
200.39
203.24
205.53
208.21
208.88
212.85
216.41
216.23
219.27
222.02
224.89
230.37
232.29
235.53
236.92
242.37
242.75
244.19
247.94
248.80
250.18
251.55
254.40
255.72
257.69
258.37
258.22
258.59
257.45
257.45
256.73
258.82
257.99
262.85
262.58
261.55
261.25
259.78
256.26
254.29
248.50
241.88
238.53
232.24
232.46
225.79
221.63
219.62
215.94
211.81
205.57
201.25
194.70
187.94
185.61
181.15
186.50
183.21
182.61
187.09
189.10
191.25
190.74
190.79




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=70807&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=70807&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70807&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.99507914.62460
20.98984314.54770
30.98421114.46490
40.97832314.37840
50.97227514.28950
60.96611814.1990
70.95955414.10250
80.95258614.00010
90.94553913.89650
100.93792313.78460
110.92996313.66760
120.92141913.5420
130.91197513.40320
140.90202213.2570
150.89149713.10230
160.8803612.93860
170.86874812.76790
180.85694212.59440
190.8449112.41760
200.8325212.23550
210.82000412.05150
220.8068311.85790
230.79343711.66110

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.995079 & 14.6246 & 0 \tabularnewline
2 & 0.989843 & 14.5477 & 0 \tabularnewline
3 & 0.984211 & 14.4649 & 0 \tabularnewline
4 & 0.978323 & 14.3784 & 0 \tabularnewline
5 & 0.972275 & 14.2895 & 0 \tabularnewline
6 & 0.966118 & 14.199 & 0 \tabularnewline
7 & 0.959554 & 14.1025 & 0 \tabularnewline
8 & 0.952586 & 14.0001 & 0 \tabularnewline
9 & 0.945539 & 13.8965 & 0 \tabularnewline
10 & 0.937923 & 13.7846 & 0 \tabularnewline
11 & 0.929963 & 13.6676 & 0 \tabularnewline
12 & 0.921419 & 13.542 & 0 \tabularnewline
13 & 0.911975 & 13.4032 & 0 \tabularnewline
14 & 0.902022 & 13.257 & 0 \tabularnewline
15 & 0.891497 & 13.1023 & 0 \tabularnewline
16 & 0.88036 & 12.9386 & 0 \tabularnewline
17 & 0.868748 & 12.7679 & 0 \tabularnewline
18 & 0.856942 & 12.5944 & 0 \tabularnewline
19 & 0.84491 & 12.4176 & 0 \tabularnewline
20 & 0.83252 & 12.2355 & 0 \tabularnewline
21 & 0.820004 & 12.0515 & 0 \tabularnewline
22 & 0.80683 & 11.8579 & 0 \tabularnewline
23 & 0.793437 & 11.6611 & 0 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70807&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]0.995079[/C][C]14.6246[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.989843[/C][C]14.5477[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.984211[/C][C]14.4649[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.978323[/C][C]14.3784[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.972275[/C][C]14.2895[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.966118[/C][C]14.199[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.959554[/C][C]14.1025[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.952586[/C][C]14.0001[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.945539[/C][C]13.8965[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.937923[/C][C]13.7846[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.929963[/C][C]13.6676[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.921419[/C][C]13.542[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.911975[/C][C]13.4032[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.902022[/C][C]13.257[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.891497[/C][C]13.1023[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.88036[/C][C]12.9386[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.868748[/C][C]12.7679[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.856942[/C][C]12.5944[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.84491[/C][C]12.4176[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.83252[/C][C]12.2355[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.820004[/C][C]12.0515[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.80683[/C][C]11.8579[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.793437[/C][C]11.6611[/C][C]0[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70807&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70807&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
10.99507914.62460
20.98984314.54770
30.98421114.46490
40.97832314.37840
50.97227514.28950
60.96611814.1990
70.95955414.10250
80.95258614.00010
90.94553913.89650
100.93792313.78460
110.92996313.66760
120.92141913.5420
130.91197513.40320
140.90202213.2570
150.89149713.10230
160.8803612.93860
170.86874812.76790
180.85694212.59440
190.8449112.41760
200.8325212.23550
210.82000412.05150
220.8068311.85790
230.79343711.66110







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.99507914.62460
2-0.034497-0.5070.306335
3-0.04201-0.61740.268806
4-0.026468-0.3890.34883
5-0.016399-0.2410.404885
6-0.011309-0.16620.434073
7-0.042346-0.62240.267183
8-0.041126-0.60440.273098
9-0.005732-0.08420.466472
10-0.056692-0.83320.202826
11-0.033188-0.48780.313104
12-0.056791-0.83470.202416
13-0.088057-1.29420.098496
14-0.045227-0.66470.253474
15-0.05309-0.78030.218045
16-0.057185-0.84040.200795
17-0.042902-0.63050.264509
18-0.015254-0.22420.411411
19-0.014356-0.2110.416545
20-0.030884-0.45390.325177
21-0.006953-0.10220.45935
22-0.057015-0.83790.201493
23-0.012123-0.17820.429379

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.995079 & 14.6246 & 0 \tabularnewline
2 & -0.034497 & -0.507 & 0.306335 \tabularnewline
3 & -0.04201 & -0.6174 & 0.268806 \tabularnewline
4 & -0.026468 & -0.389 & 0.34883 \tabularnewline
5 & -0.016399 & -0.241 & 0.404885 \tabularnewline
6 & -0.011309 & -0.1662 & 0.434073 \tabularnewline
7 & -0.042346 & -0.6224 & 0.267183 \tabularnewline
8 & -0.041126 & -0.6044 & 0.273098 \tabularnewline
9 & -0.005732 & -0.0842 & 0.466472 \tabularnewline
10 & -0.056692 & -0.8332 & 0.202826 \tabularnewline
11 & -0.033188 & -0.4878 & 0.313104 \tabularnewline
12 & -0.056791 & -0.8347 & 0.202416 \tabularnewline
13 & -0.088057 & -1.2942 & 0.098496 \tabularnewline
14 & -0.045227 & -0.6647 & 0.253474 \tabularnewline
15 & -0.05309 & -0.7803 & 0.218045 \tabularnewline
16 & -0.057185 & -0.8404 & 0.200795 \tabularnewline
17 & -0.042902 & -0.6305 & 0.264509 \tabularnewline
18 & -0.015254 & -0.2242 & 0.411411 \tabularnewline
19 & -0.014356 & -0.211 & 0.416545 \tabularnewline
20 & -0.030884 & -0.4539 & 0.325177 \tabularnewline
21 & -0.006953 & -0.1022 & 0.45935 \tabularnewline
22 & -0.057015 & -0.8379 & 0.201493 \tabularnewline
23 & -0.012123 & -0.1782 & 0.429379 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70807&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]0.995079[/C][C]14.6246[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.034497[/C][C]-0.507[/C][C]0.306335[/C][/ROW]
[ROW][C]3[/C][C]-0.04201[/C][C]-0.6174[/C][C]0.268806[/C][/ROW]
[ROW][C]4[/C][C]-0.026468[/C][C]-0.389[/C][C]0.34883[/C][/ROW]
[ROW][C]5[/C][C]-0.016399[/C][C]-0.241[/C][C]0.404885[/C][/ROW]
[ROW][C]6[/C][C]-0.011309[/C][C]-0.1662[/C][C]0.434073[/C][/ROW]
[ROW][C]7[/C][C]-0.042346[/C][C]-0.6224[/C][C]0.267183[/C][/ROW]
[ROW][C]8[/C][C]-0.041126[/C][C]-0.6044[/C][C]0.273098[/C][/ROW]
[ROW][C]9[/C][C]-0.005732[/C][C]-0.0842[/C][C]0.466472[/C][/ROW]
[ROW][C]10[/C][C]-0.056692[/C][C]-0.8332[/C][C]0.202826[/C][/ROW]
[ROW][C]11[/C][C]-0.033188[/C][C]-0.4878[/C][C]0.313104[/C][/ROW]
[ROW][C]12[/C][C]-0.056791[/C][C]-0.8347[/C][C]0.202416[/C][/ROW]
[ROW][C]13[/C][C]-0.088057[/C][C]-1.2942[/C][C]0.098496[/C][/ROW]
[ROW][C]14[/C][C]-0.045227[/C][C]-0.6647[/C][C]0.253474[/C][/ROW]
[ROW][C]15[/C][C]-0.05309[/C][C]-0.7803[/C][C]0.218045[/C][/ROW]
[ROW][C]16[/C][C]-0.057185[/C][C]-0.8404[/C][C]0.200795[/C][/ROW]
[ROW][C]17[/C][C]-0.042902[/C][C]-0.6305[/C][C]0.264509[/C][/ROW]
[ROW][C]18[/C][C]-0.015254[/C][C]-0.2242[/C][C]0.411411[/C][/ROW]
[ROW][C]19[/C][C]-0.014356[/C][C]-0.211[/C][C]0.416545[/C][/ROW]
[ROW][C]20[/C][C]-0.030884[/C][C]-0.4539[/C][C]0.325177[/C][/ROW]
[ROW][C]21[/C][C]-0.006953[/C][C]-0.1022[/C][C]0.45935[/C][/ROW]
[ROW][C]22[/C][C]-0.057015[/C][C]-0.8379[/C][C]0.201493[/C][/ROW]
[ROW][C]23[/C][C]-0.012123[/C][C]-0.1782[/C][C]0.429379[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70807&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70807&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
10.99507914.62460
2-0.034497-0.5070.306335
3-0.04201-0.61740.268806
4-0.026468-0.3890.34883
5-0.016399-0.2410.404885
6-0.011309-0.16620.434073
7-0.042346-0.62240.267183
8-0.041126-0.60440.273098
9-0.005732-0.08420.466472
10-0.056692-0.83320.202826
11-0.033188-0.48780.313104
12-0.056791-0.83470.202416
13-0.088057-1.29420.098496
14-0.045227-0.66470.253474
15-0.05309-0.78030.218045
16-0.057185-0.84040.200795
17-0.042902-0.63050.264509
18-0.015254-0.22420.411411
19-0.014356-0.2110.416545
20-0.030884-0.45390.325177
21-0.006953-0.10220.45935
22-0.057015-0.83790.201493
23-0.012123-0.17820.429379



Parameters (Session):
par1 = Default ; par2 = -1.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = Default ; par2 = -1.0 ; par3 = 0 ; 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')