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Description of Statistical Computation

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 computationWed, 15 Dec 2010 16:03:05 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/15/t1292428893ee026ngtbf9mde3.htm/, Retrieved Fri, 03 May 2024 09:32:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110512, Retrieved Fri, 03 May 2024 09:32:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [Unemployment] [2010-11-29 09:09:37] [b98453cac15ba1066b407e146608df68]
-    D      [(Partial) Autocorrelation Function] [] [2010-12-15 16:03:05] [9b9a58c480cb5dafe4bfceb51e1cfd12] [Current]
F             [(Partial) Autocorrelation Function] [] [2010-12-16 15:14:11] [75b8170d590d2aca2c97c1862bb2167f]
-               [(Partial) Autocorrelation Function] [workshop 6] [2010-12-17 19:19:12] [916599f00c9c716123aa8433d9efa14f]
-    D          [(Partial) Autocorrelation Function] [TUM (d=1)] [2010-12-26 11:31:02] [c895532cb7349383dee5125244983cc8]
-   P             [(Partial) Autocorrelation Function] [TUM (d=1)] [2010-12-28 08:57:52] [75b8170d590d2aca2c97c1862bb2167f]
-   P             [(Partial) Autocorrelation Function] [berekening 11] [2010-12-28 14:03:23] [916599f00c9c716123aa8433d9efa14f]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10
10
10
10
10
9,94
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
10,06
9,94
9,94
9,94
9,94
9,94
9,94
10,06
10,06
9,94
10,06
10,06
10,06
10,18
10,28
10,28
10,18
10,28
10,28
10,28
10,18
10,28
10,28
10,18
10,18
10,18
10,28
10,28
10,18
10,18
10,18
10,18
10,18
10,18
10,28
10,28
10,28
10,18
10,18
10,18
10,28
10,18
10,18
10,28
10,18
10,18
10,18
10,28
10,28
10,28
10,28
10,28
10,28
10,18
10,18
10,18
10,18
10,18
10,18
10,18
10,18
10,18
10,28
10,28
10,28
10,28
10,28
10,28
10,28
10,28
10,18
10,28
10,28
10,28
10,28
10,18
10,28
10,28
10,28
10,18
10,18
10,28
10,28
10,28
10,28
10,28
10,28
10,28
10,18
10,28
10,28
10,28
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,34
10,42
10,42
10,42
10,42
10,34
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,34
10,34
10,42
10,42
10,34
10,34
10,34
10,42
10,42
10,42
10,34
10,34
10,34
10,34
10,34
10,42
10,42
10,42
10,34
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,34
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,42
10,34
10,34
10,42
10,42
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,49
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,49
10,55
10,55
10,55
10,49
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,55
10,49
10,49
10,49
10,55
10,55
10,55
10,49
10,55
10,55
10,55
10,63
10,63
10,63
10,63
10,63
10,57
10,63
10,63
10,63
10,63
10,57
10,57
10,57
10,63
10,63
10,63
10,63
10,57
10,63
10,63
10,57
10,63
10,63
10,63
10,63
10,57
10,63
10,6
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,6
10,6
10,6
10,6
10,7
10,7
10,6
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,7
10,8
10,8
10,8
10,8
10,7
10,7
10,7
10,85
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,75
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,85
10,75
10,75
10,85
10,85
10,85
10,85
10,75
10,75
10,75
10,75
10,75

Tables (Output of Computation)





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=110512&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=110512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110512&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.210985-3.94154.9e-05
2-0.129439-2.41810.008056
3-0.05129-0.95820.169318
4-0.035156-0.65680.255882
50.0645931.20670.114183
6-0.097305-1.81780.034975
70.0847671.58360.057098
80.0196310.36670.357017
90.000390.00730.497094
10-0.128459-2.39980.008464
11-0.057128-1.06720.143303
120.0388610.7260.234169
13-0.014382-0.26870.394169
140.0708461.32350.093266
15-0.009015-0.16840.43318
160.0133490.24940.401605
17-0.079537-1.48590.069107
18-0.035369-0.66080.254604
190.0974311.82020.034795
20-0.047074-0.87940.18989
210.0812171.51730.065054
22-0.056128-1.04860.147555
23-0.053586-1.00110.158745
240.0664721.24180.107572
25-0.062377-1.16530.122347
260.0634261.18490.118432
27-0.031443-0.58740.278659
28-0.042292-0.79010.215012
290.0549111.02580.152841
300.0452770.84580.199109
310.0056270.10510.458173
32-0.056333-1.05240.146673
330.0647681.210.113555
340.014640.27350.392313
35-0.075435-1.40920.079826
360.0109250.20410.419198
370.0194140.36270.358533
380.0352650.65880.25523
39-0.030034-0.56110.287553
40-0.055059-1.02860.152194
41-0.06979-1.30380.096583
420.0309910.5790.281495
43-0.038392-0.71720.236857
440.027580.51520.303358
450.0989531.84860.032681
46-0.097573-1.82280.034593
470.0462490.8640.194087
48-0.059946-1.11990.131767

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.210985 & -3.9415 & 4.9e-05 \tabularnewline
2 & -0.129439 & -2.4181 & 0.008056 \tabularnewline
3 & -0.05129 & -0.9582 & 0.169318 \tabularnewline
4 & -0.035156 & -0.6568 & 0.255882 \tabularnewline
5 & 0.064593 & 1.2067 & 0.114183 \tabularnewline
6 & -0.097305 & -1.8178 & 0.034975 \tabularnewline
7 & 0.084767 & 1.5836 & 0.057098 \tabularnewline
8 & 0.019631 & 0.3667 & 0.357017 \tabularnewline
9 & 0.00039 & 0.0073 & 0.497094 \tabularnewline
10 & -0.128459 & -2.3998 & 0.008464 \tabularnewline
11 & -0.057128 & -1.0672 & 0.143303 \tabularnewline
12 & 0.038861 & 0.726 & 0.234169 \tabularnewline
13 & -0.014382 & -0.2687 & 0.394169 \tabularnewline
14 & 0.070846 & 1.3235 & 0.093266 \tabularnewline
15 & -0.009015 & -0.1684 & 0.43318 \tabularnewline
16 & 0.013349 & 0.2494 & 0.401605 \tabularnewline
17 & -0.079537 & -1.4859 & 0.069107 \tabularnewline
18 & -0.035369 & -0.6608 & 0.254604 \tabularnewline
19 & 0.097431 & 1.8202 & 0.034795 \tabularnewline
20 & -0.047074 & -0.8794 & 0.18989 \tabularnewline
21 & 0.081217 & 1.5173 & 0.065054 \tabularnewline
22 & -0.056128 & -1.0486 & 0.147555 \tabularnewline
23 & -0.053586 & -1.0011 & 0.158745 \tabularnewline
24 & 0.066472 & 1.2418 & 0.107572 \tabularnewline
25 & -0.062377 & -1.1653 & 0.122347 \tabularnewline
26 & 0.063426 & 1.1849 & 0.118432 \tabularnewline
27 & -0.031443 & -0.5874 & 0.278659 \tabularnewline
28 & -0.042292 & -0.7901 & 0.215012 \tabularnewline
29 & 0.054911 & 1.0258 & 0.152841 \tabularnewline
30 & 0.045277 & 0.8458 & 0.199109 \tabularnewline
31 & 0.005627 & 0.1051 & 0.458173 \tabularnewline
32 & -0.056333 & -1.0524 & 0.146673 \tabularnewline
33 & 0.064768 & 1.21 & 0.113555 \tabularnewline
34 & 0.01464 & 0.2735 & 0.392313 \tabularnewline
35 & -0.075435 & -1.4092 & 0.079826 \tabularnewline
36 & 0.010925 & 0.2041 & 0.419198 \tabularnewline
37 & 0.019414 & 0.3627 & 0.358533 \tabularnewline
38 & 0.035265 & 0.6588 & 0.25523 \tabularnewline
39 & -0.030034 & -0.5611 & 0.287553 \tabularnewline
40 & -0.055059 & -1.0286 & 0.152194 \tabularnewline
41 & -0.06979 & -1.3038 & 0.096583 \tabularnewline
42 & 0.030991 & 0.579 & 0.281495 \tabularnewline
43 & -0.038392 & -0.7172 & 0.236857 \tabularnewline
44 & 0.02758 & 0.5152 & 0.303358 \tabularnewline
45 & 0.098953 & 1.8486 & 0.032681 \tabularnewline
46 & -0.097573 & -1.8228 & 0.034593 \tabularnewline
47 & 0.046249 & 0.864 & 0.194087 \tabularnewline
48 & -0.059946 & -1.1199 & 0.131767 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110512&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]-0.210985[/C][C]-3.9415[/C][C]4.9e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.129439[/C][C]-2.4181[/C][C]0.008056[/C][/ROW]
[ROW][C]3[/C][C]-0.05129[/C][C]-0.9582[/C][C]0.169318[/C][/ROW]
[ROW][C]4[/C][C]-0.035156[/C][C]-0.6568[/C][C]0.255882[/C][/ROW]
[ROW][C]5[/C][C]0.064593[/C][C]1.2067[/C][C]0.114183[/C][/ROW]
[ROW][C]6[/C][C]-0.097305[/C][C]-1.8178[/C][C]0.034975[/C][/ROW]
[ROW][C]7[/C][C]0.084767[/C][C]1.5836[/C][C]0.057098[/C][/ROW]
[ROW][C]8[/C][C]0.019631[/C][C]0.3667[/C][C]0.357017[/C][/ROW]
[ROW][C]9[/C][C]0.00039[/C][C]0.0073[/C][C]0.497094[/C][/ROW]
[ROW][C]10[/C][C]-0.128459[/C][C]-2.3998[/C][C]0.008464[/C][/ROW]
[ROW][C]11[/C][C]-0.057128[/C][C]-1.0672[/C][C]0.143303[/C][/ROW]
[ROW][C]12[/C][C]0.038861[/C][C]0.726[/C][C]0.234169[/C][/ROW]
[ROW][C]13[/C][C]-0.014382[/C][C]-0.2687[/C][C]0.394169[/C][/ROW]
[ROW][C]14[/C][C]0.070846[/C][C]1.3235[/C][C]0.093266[/C][/ROW]
[ROW][C]15[/C][C]-0.009015[/C][C]-0.1684[/C][C]0.43318[/C][/ROW]
[ROW][C]16[/C][C]0.013349[/C][C]0.2494[/C][C]0.401605[/C][/ROW]
[ROW][C]17[/C][C]-0.079537[/C][C]-1.4859[/C][C]0.069107[/C][/ROW]
[ROW][C]18[/C][C]-0.035369[/C][C]-0.6608[/C][C]0.254604[/C][/ROW]
[ROW][C]19[/C][C]0.097431[/C][C]1.8202[/C][C]0.034795[/C][/ROW]
[ROW][C]20[/C][C]-0.047074[/C][C]-0.8794[/C][C]0.18989[/C][/ROW]
[ROW][C]21[/C][C]0.081217[/C][C]1.5173[/C][C]0.065054[/C][/ROW]
[ROW][C]22[/C][C]-0.056128[/C][C]-1.0486[/C][C]0.147555[/C][/ROW]
[ROW][C]23[/C][C]-0.053586[/C][C]-1.0011[/C][C]0.158745[/C][/ROW]
[ROW][C]24[/C][C]0.066472[/C][C]1.2418[/C][C]0.107572[/C][/ROW]
[ROW][C]25[/C][C]-0.062377[/C][C]-1.1653[/C][C]0.122347[/C][/ROW]
[ROW][C]26[/C][C]0.063426[/C][C]1.1849[/C][C]0.118432[/C][/ROW]
[ROW][C]27[/C][C]-0.031443[/C][C]-0.5874[/C][C]0.278659[/C][/ROW]
[ROW][C]28[/C][C]-0.042292[/C][C]-0.7901[/C][C]0.215012[/C][/ROW]
[ROW][C]29[/C][C]0.054911[/C][C]1.0258[/C][C]0.152841[/C][/ROW]
[ROW][C]30[/C][C]0.045277[/C][C]0.8458[/C][C]0.199109[/C][/ROW]
[ROW][C]31[/C][C]0.005627[/C][C]0.1051[/C][C]0.458173[/C][/ROW]
[ROW][C]32[/C][C]-0.056333[/C][C]-1.0524[/C][C]0.146673[/C][/ROW]
[ROW][C]33[/C][C]0.064768[/C][C]1.21[/C][C]0.113555[/C][/ROW]
[ROW][C]34[/C][C]0.01464[/C][C]0.2735[/C][C]0.392313[/C][/ROW]
[ROW][C]35[/C][C]-0.075435[/C][C]-1.4092[/C][C]0.079826[/C][/ROW]
[ROW][C]36[/C][C]0.010925[/C][C]0.2041[/C][C]0.419198[/C][/ROW]
[ROW][C]37[/C][C]0.019414[/C][C]0.3627[/C][C]0.358533[/C][/ROW]
[ROW][C]38[/C][C]0.035265[/C][C]0.6588[/C][C]0.25523[/C][/ROW]
[ROW][C]39[/C][C]-0.030034[/C][C]-0.5611[/C][C]0.287553[/C][/ROW]
[ROW][C]40[/C][C]-0.055059[/C][C]-1.0286[/C][C]0.152194[/C][/ROW]
[ROW][C]41[/C][C]-0.06979[/C][C]-1.3038[/C][C]0.096583[/C][/ROW]
[ROW][C]42[/C][C]0.030991[/C][C]0.579[/C][C]0.281495[/C][/ROW]
[ROW][C]43[/C][C]-0.038392[/C][C]-0.7172[/C][C]0.236857[/C][/ROW]
[ROW][C]44[/C][C]0.02758[/C][C]0.5152[/C][C]0.303358[/C][/ROW]
[ROW][C]45[/C][C]0.098953[/C][C]1.8486[/C][C]0.032681[/C][/ROW]
[ROW][C]46[/C][C]-0.097573[/C][C]-1.8228[/C][C]0.034593[/C][/ROW]
[ROW][C]47[/C][C]0.046249[/C][C]0.864[/C][C]0.194087[/C][/ROW]
[ROW][C]48[/C][C]-0.059946[/C][C]-1.1199[/C][C]0.131767[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110512&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110512&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
1-0.210985-3.94154.9e-05
2-0.129439-2.41810.008056
3-0.05129-0.95820.169318
4-0.035156-0.65680.255882
50.0645931.20670.114183
6-0.097305-1.81780.034975
70.0847671.58360.057098
80.0196310.36670.357017
90.000390.00730.497094
10-0.128459-2.39980.008464
11-0.057128-1.06720.143303
120.0388610.7260.234169
13-0.014382-0.26870.394169
140.0708461.32350.093266
15-0.009015-0.16840.43318
160.0133490.24940.401605
17-0.079537-1.48590.069107
18-0.035369-0.66080.254604
190.0974311.82020.034795
20-0.047074-0.87940.18989
210.0812171.51730.065054
22-0.056128-1.04860.147555
23-0.053586-1.00110.158745
240.0664721.24180.107572
25-0.062377-1.16530.122347
260.0634261.18490.118432
27-0.031443-0.58740.278659
28-0.042292-0.79010.215012
290.0549111.02580.152841
300.0452770.84580.199109
310.0056270.10510.458173
32-0.056333-1.05240.146673
330.0647681.210.113555
340.014640.27350.392313
35-0.075435-1.40920.079826
360.0109250.20410.419198
370.0194140.36270.358533
380.0352650.65880.25523
39-0.030034-0.56110.287553
40-0.055059-1.02860.152194
41-0.06979-1.30380.096583
420.0309910.5790.281495
43-0.038392-0.71720.236857
440.027580.51520.303358
450.0989531.84860.032681
46-0.097573-1.82280.034593
470.0462490.8640.194087
48-0.059946-1.11990.131767






Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.210985-3.94154.9e-05
2-0.182058-3.40110.000374
3-0.132043-2.46680.007057
4-0.11553-2.15830.015794
5-0.00381-0.07120.471648
6-0.124414-2.32420.010343
70.0313430.58550.27928
80.0180750.33770.367905
90.0234190.43750.331006
10-0.129006-2.410.008234
11-0.116373-2.1740.015187
12-0.076156-1.42270.077857
13-0.083008-1.55070.060939
140.005140.0960.461781
15-0.010048-0.18770.425607
160.0014990.0280.488838
17-0.082087-1.53350.063027
18-0.068807-1.28540.099748
190.0346180.64670.259118
20-0.062283-1.16350.122704
210.0339250.63380.26332
22-0.050827-0.94950.171503
23-0.09377-1.75180.040347
240.0194610.36360.358202
25-0.046866-0.87550.190946
260.0184580.34480.365217
27-0.039433-0.73670.23091
28-0.102284-1.91080.028423
290.0017830.03330.486722
300.0573271.0710.142463
310.0414360.77410.2197
32-0.013314-0.24870.401858
330.0389760.72810.233511
340.0373170.69710.243092
35-0.064614-1.20710.114108
360.0124950.23340.407781
370.0139280.26020.397435
380.0057130.10670.457536
390.0059380.11090.455864
40-0.057468-1.07360.141875
41-0.100086-1.86980.031178
42-0.035044-0.65470.256557
43-0.09848-1.83980.033326
44-0.01857-0.34690.364431
450.0227110.42430.335813
46-0.083093-1.55230.060748
470.0299510.55950.288078
48-0.063225-1.18110.119177

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.210985 & -3.9415 & 4.9e-05 \tabularnewline
2 & -0.182058 & -3.4011 & 0.000374 \tabularnewline
3 & -0.132043 & -2.4668 & 0.007057 \tabularnewline
4 & -0.11553 & -2.1583 & 0.015794 \tabularnewline
5 & -0.00381 & -0.0712 & 0.471648 \tabularnewline
6 & -0.124414 & -2.3242 & 0.010343 \tabularnewline
7 & 0.031343 & 0.5855 & 0.27928 \tabularnewline
8 & 0.018075 & 0.3377 & 0.367905 \tabularnewline
9 & 0.023419 & 0.4375 & 0.331006 \tabularnewline
10 & -0.129006 & -2.41 & 0.008234 \tabularnewline
11 & -0.116373 & -2.174 & 0.015187 \tabularnewline
12 & -0.076156 & -1.4227 & 0.077857 \tabularnewline
13 & -0.083008 & -1.5507 & 0.060939 \tabularnewline
14 & 0.00514 & 0.096 & 0.461781 \tabularnewline
15 & -0.010048 & -0.1877 & 0.425607 \tabularnewline
16 & 0.001499 & 0.028 & 0.488838 \tabularnewline
17 & -0.082087 & -1.5335 & 0.063027 \tabularnewline
18 & -0.068807 & -1.2854 & 0.099748 \tabularnewline
19 & 0.034618 & 0.6467 & 0.259118 \tabularnewline
20 & -0.062283 & -1.1635 & 0.122704 \tabularnewline
21 & 0.033925 & 0.6338 & 0.26332 \tabularnewline
22 & -0.050827 & -0.9495 & 0.171503 \tabularnewline
23 & -0.09377 & -1.7518 & 0.040347 \tabularnewline
24 & 0.019461 & 0.3636 & 0.358202 \tabularnewline
25 & -0.046866 & -0.8755 & 0.190946 \tabularnewline
26 & 0.018458 & 0.3448 & 0.365217 \tabularnewline
27 & -0.039433 & -0.7367 & 0.23091 \tabularnewline
28 & -0.102284 & -1.9108 & 0.028423 \tabularnewline
29 & 0.001783 & 0.0333 & 0.486722 \tabularnewline
30 & 0.057327 & 1.071 & 0.142463 \tabularnewline
31 & 0.041436 & 0.7741 & 0.2197 \tabularnewline
32 & -0.013314 & -0.2487 & 0.401858 \tabularnewline
33 & 0.038976 & 0.7281 & 0.233511 \tabularnewline
34 & 0.037317 & 0.6971 & 0.243092 \tabularnewline
35 & -0.064614 & -1.2071 & 0.114108 \tabularnewline
36 & 0.012495 & 0.2334 & 0.407781 \tabularnewline
37 & 0.013928 & 0.2602 & 0.397435 \tabularnewline
38 & 0.005713 & 0.1067 & 0.457536 \tabularnewline
39 & 0.005938 & 0.1109 & 0.455864 \tabularnewline
40 & -0.057468 & -1.0736 & 0.141875 \tabularnewline
41 & -0.100086 & -1.8698 & 0.031178 \tabularnewline
42 & -0.035044 & -0.6547 & 0.256557 \tabularnewline
43 & -0.09848 & -1.8398 & 0.033326 \tabularnewline
44 & -0.01857 & -0.3469 & 0.364431 \tabularnewline
45 & 0.022711 & 0.4243 & 0.335813 \tabularnewline
46 & -0.083093 & -1.5523 & 0.060748 \tabularnewline
47 & 0.029951 & 0.5595 & 0.288078 \tabularnewline
48 & -0.063225 & -1.1811 & 0.119177 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110512&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]-0.210985[/C][C]-3.9415[/C][C]4.9e-05[/C][/ROW]
[ROW][C]2[/C][C]-0.182058[/C][C]-3.4011[/C][C]0.000374[/C][/ROW]
[ROW][C]3[/C][C]-0.132043[/C][C]-2.4668[/C][C]0.007057[/C][/ROW]
[ROW][C]4[/C][C]-0.11553[/C][C]-2.1583[/C][C]0.015794[/C][/ROW]
[ROW][C]5[/C][C]-0.00381[/C][C]-0.0712[/C][C]0.471648[/C][/ROW]
[ROW][C]6[/C][C]-0.124414[/C][C]-2.3242[/C][C]0.010343[/C][/ROW]
[ROW][C]7[/C][C]0.031343[/C][C]0.5855[/C][C]0.27928[/C][/ROW]
[ROW][C]8[/C][C]0.018075[/C][C]0.3377[/C][C]0.367905[/C][/ROW]
[ROW][C]9[/C][C]0.023419[/C][C]0.4375[/C][C]0.331006[/C][/ROW]
[ROW][C]10[/C][C]-0.129006[/C][C]-2.41[/C][C]0.008234[/C][/ROW]
[ROW][C]11[/C][C]-0.116373[/C][C]-2.174[/C][C]0.015187[/C][/ROW]
[ROW][C]12[/C][C]-0.076156[/C][C]-1.4227[/C][C]0.077857[/C][/ROW]
[ROW][C]13[/C][C]-0.083008[/C][C]-1.5507[/C][C]0.060939[/C][/ROW]
[ROW][C]14[/C][C]0.00514[/C][C]0.096[/C][C]0.461781[/C][/ROW]
[ROW][C]15[/C][C]-0.010048[/C][C]-0.1877[/C][C]0.425607[/C][/ROW]
[ROW][C]16[/C][C]0.001499[/C][C]0.028[/C][C]0.488838[/C][/ROW]
[ROW][C]17[/C][C]-0.082087[/C][C]-1.5335[/C][C]0.063027[/C][/ROW]
[ROW][C]18[/C][C]-0.068807[/C][C]-1.2854[/C][C]0.099748[/C][/ROW]
[ROW][C]19[/C][C]0.034618[/C][C]0.6467[/C][C]0.259118[/C][/ROW]
[ROW][C]20[/C][C]-0.062283[/C][C]-1.1635[/C][C]0.122704[/C][/ROW]
[ROW][C]21[/C][C]0.033925[/C][C]0.6338[/C][C]0.26332[/C][/ROW]
[ROW][C]22[/C][C]-0.050827[/C][C]-0.9495[/C][C]0.171503[/C][/ROW]
[ROW][C]23[/C][C]-0.09377[/C][C]-1.7518[/C][C]0.040347[/C][/ROW]
[ROW][C]24[/C][C]0.019461[/C][C]0.3636[/C][C]0.358202[/C][/ROW]
[ROW][C]25[/C][C]-0.046866[/C][C]-0.8755[/C][C]0.190946[/C][/ROW]
[ROW][C]26[/C][C]0.018458[/C][C]0.3448[/C][C]0.365217[/C][/ROW]
[ROW][C]27[/C][C]-0.039433[/C][C]-0.7367[/C][C]0.23091[/C][/ROW]
[ROW][C]28[/C][C]-0.102284[/C][C]-1.9108[/C][C]0.028423[/C][/ROW]
[ROW][C]29[/C][C]0.001783[/C][C]0.0333[/C][C]0.486722[/C][/ROW]
[ROW][C]30[/C][C]0.057327[/C][C]1.071[/C][C]0.142463[/C][/ROW]
[ROW][C]31[/C][C]0.041436[/C][C]0.7741[/C][C]0.2197[/C][/ROW]
[ROW][C]32[/C][C]-0.013314[/C][C]-0.2487[/C][C]0.401858[/C][/ROW]
[ROW][C]33[/C][C]0.038976[/C][C]0.7281[/C][C]0.233511[/C][/ROW]
[ROW][C]34[/C][C]0.037317[/C][C]0.6971[/C][C]0.243092[/C][/ROW]
[ROW][C]35[/C][C]-0.064614[/C][C]-1.2071[/C][C]0.114108[/C][/ROW]
[ROW][C]36[/C][C]0.012495[/C][C]0.2334[/C][C]0.407781[/C][/ROW]
[ROW][C]37[/C][C]0.013928[/C][C]0.2602[/C][C]0.397435[/C][/ROW]
[ROW][C]38[/C][C]0.005713[/C][C]0.1067[/C][C]0.457536[/C][/ROW]
[ROW][C]39[/C][C]0.005938[/C][C]0.1109[/C][C]0.455864[/C][/ROW]
[ROW][C]40[/C][C]-0.057468[/C][C]-1.0736[/C][C]0.141875[/C][/ROW]
[ROW][C]41[/C][C]-0.100086[/C][C]-1.8698[/C][C]0.031178[/C][/ROW]
[ROW][C]42[/C][C]-0.035044[/C][C]-0.6547[/C][C]0.256557[/C][/ROW]
[ROW][C]43[/C][C]-0.09848[/C][C]-1.8398[/C][C]0.033326[/C][/ROW]
[ROW][C]44[/C][C]-0.01857[/C][C]-0.3469[/C][C]0.364431[/C][/ROW]
[ROW][C]45[/C][C]0.022711[/C][C]0.4243[/C][C]0.335813[/C][/ROW]
[ROW][C]46[/C][C]-0.083093[/C][C]-1.5523[/C][C]0.060748[/C][/ROW]
[ROW][C]47[/C][C]0.029951[/C][C]0.5595[/C][C]0.288078[/C][/ROW]
[ROW][C]48[/C][C]-0.063225[/C][C]-1.1811[/C][C]0.119177[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110512&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110512&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
1-0.210985-3.94154.9e-05
2-0.182058-3.40110.000374
3-0.132043-2.46680.007057
4-0.11553-2.15830.015794
5-0.00381-0.07120.471648
6-0.124414-2.32420.010343
70.0313430.58550.27928
80.0180750.33770.367905
90.0234190.43750.331006
10-0.129006-2.410.008234
11-0.116373-2.1740.015187
12-0.076156-1.42270.077857
13-0.083008-1.55070.060939
140.005140.0960.461781
15-0.010048-0.18770.425607
160.0014990.0280.488838
17-0.082087-1.53350.063027
18-0.068807-1.28540.099748
190.0346180.64670.259118
20-0.062283-1.16350.122704
210.0339250.63380.26332
22-0.050827-0.94950.171503
23-0.09377-1.75180.040347
240.0194610.36360.358202
25-0.046866-0.87550.190946
260.0184580.34480.365217
27-0.039433-0.73670.23091
28-0.102284-1.91080.028423
290.0017830.03330.486722
300.0573271.0710.142463
310.0414360.77410.2197
32-0.013314-0.24870.401858
330.0389760.72810.233511
340.0373170.69710.243092
35-0.064614-1.20710.114108
360.0124950.23340.407781
370.0139280.26020.397435
380.0057130.10670.457536
390.0059380.11090.455864
40-0.057468-1.07360.141875
41-0.100086-1.86980.031178
42-0.035044-0.65470.256557
43-0.09848-1.83980.033326
44-0.01857-0.34690.364431
450.0227110.42430.335813
46-0.083093-1.55230.060748
470.0299510.55950.288078
48-0.063225-1.18110.119177


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; 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 (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')