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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 02 Dec 2008 11:02:47 -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/2008/Dec/02/t1228241012thldf4t39idmpyk.htm/, Retrieved Sat, 25 May 2024 09:57:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28164, Retrieved Sat, 25 May 2024 09:57:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSeverijns Britt
Estimated Impact199

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 17:57:26] [9ea94c8297ec7e569f27218c1d8ea30f]
-    D      [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 18:02:47] [78308c9f3efc33d1da821bcd963df161] [Current]
F             [(Partial) Autocorrelation Function] [non stationary ti...] [2008-12-02 18:04:45] [4f5e3fd83f430616bbe7746c57513b8b]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98.1
101.1
111.1
93.3
100
108
70.4
75.4
105.5
112.3
102.5
93.5
86.7
95.2
103.8
97
95.5
101
67.5
64
106.7
100.6
101.2
93.1
84.2
85.8
91.8
92.4
80.3
79.7
62.5
57.1
100.8
100.7
86.2
83.2
71.7
77.5
89.8
80.3
78.7
93.8
57.6
60.6
91
85.3
77.4
77.3
68.3
69.9
81.7
75.1
69.9
84
54.3
60
89.9
77
85.3
77.6
69.2
75.5
85.7
72.2
79.9
85.3
52.2
61.2
82.4
85.4
78.2
70.2
70.2
69.3
77.5
66.1
69
79.2
56.2
63.3
77.8
92
78.1
65.1
71.1
70.9
72
81.9
70.6
72.5
65.1
54.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28164&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28164&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28164&T=0

As an alternative you can also use a QR Code:  
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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.176267-1.68150.048049
2-0.456542-4.35511.7e-05
30.1792831.71030.045313
4-0.186175-1.7760.039538
5-0.021231-0.20250.419976
60.3267193.11670.001224
7-0.033061-0.31540.376596
8-0.131763-1.25690.105996
90.1266051.20770.11514
10-0.385253-3.67510.000201
11-0.101102-0.96450.168688
120.7274396.93930
13-0.088426-0.84350.200572
14-0.393967-3.75820.000151
150.1284081.22490.111881
16-0.133455-1.27310.103117
17-0.03465-0.33050.370875
180.3056192.91540.002236
19-0.03989-0.38050.352221

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.176267 & -1.6815 & 0.048049 \tabularnewline
2 & -0.456542 & -4.3551 & 1.7e-05 \tabularnewline
3 & 0.179283 & 1.7103 & 0.045313 \tabularnewline
4 & -0.186175 & -1.776 & 0.039538 \tabularnewline
5 & -0.021231 & -0.2025 & 0.419976 \tabularnewline
6 & 0.326719 & 3.1167 & 0.001224 \tabularnewline
7 & -0.033061 & -0.3154 & 0.376596 \tabularnewline
8 & -0.131763 & -1.2569 & 0.105996 \tabularnewline
9 & 0.126605 & 1.2077 & 0.11514 \tabularnewline
10 & -0.385253 & -3.6751 & 0.000201 \tabularnewline
11 & -0.101102 & -0.9645 & 0.168688 \tabularnewline
12 & 0.727439 & 6.9393 & 0 \tabularnewline
13 & -0.088426 & -0.8435 & 0.200572 \tabularnewline
14 & -0.393967 & -3.7582 & 0.000151 \tabularnewline
15 & 0.128408 & 1.2249 & 0.111881 \tabularnewline
16 & -0.133455 & -1.2731 & 0.103117 \tabularnewline
17 & -0.03465 & -0.3305 & 0.370875 \tabularnewline
18 & 0.305619 & 2.9154 & 0.002236 \tabularnewline
19 & -0.03989 & -0.3805 & 0.352221 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28164&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]-0.176267[/C][C]-1.6815[/C][C]0.048049[/C][/ROW]
[ROW][C]2[/C][C]-0.456542[/C][C]-4.3551[/C][C]1.7e-05[/C][/ROW]
[ROW][C]3[/C][C]0.179283[/C][C]1.7103[/C][C]0.045313[/C][/ROW]
[ROW][C]4[/C][C]-0.186175[/C][C]-1.776[/C][C]0.039538[/C][/ROW]
[ROW][C]5[/C][C]-0.021231[/C][C]-0.2025[/C][C]0.419976[/C][/ROW]
[ROW][C]6[/C][C]0.326719[/C][C]3.1167[/C][C]0.001224[/C][/ROW]
[ROW][C]7[/C][C]-0.033061[/C][C]-0.3154[/C][C]0.376596[/C][/ROW]
[ROW][C]8[/C][C]-0.131763[/C][C]-1.2569[/C][C]0.105996[/C][/ROW]
[ROW][C]9[/C][C]0.126605[/C][C]1.2077[/C][C]0.11514[/C][/ROW]
[ROW][C]10[/C][C]-0.385253[/C][C]-3.6751[/C][C]0.000201[/C][/ROW]
[ROW][C]11[/C][C]-0.101102[/C][C]-0.9645[/C][C]0.168688[/C][/ROW]
[ROW][C]12[/C][C]0.727439[/C][C]6.9393[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.088426[/C][C]-0.8435[/C][C]0.200572[/C][/ROW]
[ROW][C]14[/C][C]-0.393967[/C][C]-3.7582[/C][C]0.000151[/C][/ROW]
[ROW][C]15[/C][C]0.128408[/C][C]1.2249[/C][C]0.111881[/C][/ROW]
[ROW][C]16[/C][C]-0.133455[/C][C]-1.2731[/C][C]0.103117[/C][/ROW]
[ROW][C]17[/C][C]-0.03465[/C][C]-0.3305[/C][C]0.370875[/C][/ROW]
[ROW][C]18[/C][C]0.305619[/C][C]2.9154[/C][C]0.002236[/C][/ROW]
[ROW][C]19[/C][C]-0.03989[/C][C]-0.3805[/C][C]0.352221[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28164&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28164&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.176267-1.68150.048049
2-0.456542-4.35511.7e-05
30.1792831.71030.045313
4-0.186175-1.7760.039538
5-0.021231-0.20250.419976
60.3267193.11670.001224
7-0.033061-0.31540.376596
8-0.131763-1.25690.105996
90.1266051.20770.11514
10-0.385253-3.67510.000201
11-0.101102-0.96450.168688
120.7274396.93930
13-0.088426-0.84350.200572
14-0.393967-3.75820.000151
150.1284081.22490.111881
16-0.133455-1.27310.103117
17-0.03465-0.33050.370875
180.3056192.91540.002236
19-0.03989-0.38050.352221






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.176267-1.68150.048049
2-0.503248-4.80073e-06
3-0.042008-0.40070.344779
4-0.522135-4.98081e-06
5-0.223901-2.13590.017687
6-0.159583-1.52230.065697
7-0.02664-0.25410.399985
8-0.034074-0.3250.372946
90.2397152.28670.012265
10-0.471918-4.50181e-05
11-0.37913-3.61670.000245
120.2208642.10690.018938
130.1482451.41420.080362
140.0143030.13640.445887
15-0.021308-0.20330.419691
160.0021910.02090.491685
170.0052130.04970.480226
18-0.004576-0.04370.482638
19-0.034239-0.32660.372353

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.176267 & -1.6815 & 0.048049 \tabularnewline
2 & -0.503248 & -4.8007 & 3e-06 \tabularnewline
3 & -0.042008 & -0.4007 & 0.344779 \tabularnewline
4 & -0.522135 & -4.9808 & 1e-06 \tabularnewline
5 & -0.223901 & -2.1359 & 0.017687 \tabularnewline
6 & -0.159583 & -1.5223 & 0.065697 \tabularnewline
7 & -0.02664 & -0.2541 & 0.399985 \tabularnewline
8 & -0.034074 & -0.325 & 0.372946 \tabularnewline
9 & 0.239715 & 2.2867 & 0.012265 \tabularnewline
10 & -0.471918 & -4.5018 & 1e-05 \tabularnewline
11 & -0.37913 & -3.6167 & 0.000245 \tabularnewline
12 & 0.220864 & 2.1069 & 0.018938 \tabularnewline
13 & 0.148245 & 1.4142 & 0.080362 \tabularnewline
14 & 0.014303 & 0.1364 & 0.445887 \tabularnewline
15 & -0.021308 & -0.2033 & 0.419691 \tabularnewline
16 & 0.002191 & 0.0209 & 0.491685 \tabularnewline
17 & 0.005213 & 0.0497 & 0.480226 \tabularnewline
18 & -0.004576 & -0.0437 & 0.482638 \tabularnewline
19 & -0.034239 & -0.3266 & 0.372353 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28164&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]-0.176267[/C][C]-1.6815[/C][C]0.048049[/C][/ROW]
[ROW][C]2[/C][C]-0.503248[/C][C]-4.8007[/C][C]3e-06[/C][/ROW]
[ROW][C]3[/C][C]-0.042008[/C][C]-0.4007[/C][C]0.344779[/C][/ROW]
[ROW][C]4[/C][C]-0.522135[/C][C]-4.9808[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]-0.223901[/C][C]-2.1359[/C][C]0.017687[/C][/ROW]
[ROW][C]6[/C][C]-0.159583[/C][C]-1.5223[/C][C]0.065697[/C][/ROW]
[ROW][C]7[/C][C]-0.02664[/C][C]-0.2541[/C][C]0.399985[/C][/ROW]
[ROW][C]8[/C][C]-0.034074[/C][C]-0.325[/C][C]0.372946[/C][/ROW]
[ROW][C]9[/C][C]0.239715[/C][C]2.2867[/C][C]0.012265[/C][/ROW]
[ROW][C]10[/C][C]-0.471918[/C][C]-4.5018[/C][C]1e-05[/C][/ROW]
[ROW][C]11[/C][C]-0.37913[/C][C]-3.6167[/C][C]0.000245[/C][/ROW]
[ROW][C]12[/C][C]0.220864[/C][C]2.1069[/C][C]0.018938[/C][/ROW]
[ROW][C]13[/C][C]0.148245[/C][C]1.4142[/C][C]0.080362[/C][/ROW]
[ROW][C]14[/C][C]0.014303[/C][C]0.1364[/C][C]0.445887[/C][/ROW]
[ROW][C]15[/C][C]-0.021308[/C][C]-0.2033[/C][C]0.419691[/C][/ROW]
[ROW][C]16[/C][C]0.002191[/C][C]0.0209[/C][C]0.491685[/C][/ROW]
[ROW][C]17[/C][C]0.005213[/C][C]0.0497[/C][C]0.480226[/C][/ROW]
[ROW][C]18[/C][C]-0.004576[/C][C]-0.0437[/C][C]0.482638[/C][/ROW]
[ROW][C]19[/C][C]-0.034239[/C][C]-0.3266[/C][C]0.372353[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28164&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28164&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.176267-1.68150.048049
2-0.503248-4.80073e-06
3-0.042008-0.40070.344779
4-0.522135-4.98081e-06
5-0.223901-2.13590.017687
6-0.159583-1.52230.065697
7-0.02664-0.25410.399985
8-0.034074-0.3250.372946
90.2397152.28670.012265
10-0.471918-4.50181e-05
11-0.37913-3.61670.000245
120.2208642.10690.018938
130.1482451.41420.080362
140.0143030.13640.445887
15-0.021308-0.20330.419691
160.0021910.02090.491685
170.0052130.04970.480226
18-0.004576-0.04370.482638
19-0.034239-0.32660.372353


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = Default ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')