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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 computationThu, 10 Dec 2009 08:28:07 -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/10/t1260459001tsvtl9mo8u9o8ow.htm/, Retrieved Fri, 29 Mar 2024 11:12:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=65474, Retrieved Fri, 29 Mar 2024 11:12:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [(P)ACF Mannen ] [2008-12-23 20:44:20] [ab2167f62c8fd37f7bb79fc194eace61]
- RMPD    [(Partial) Autocorrelation Function] [Paper - 9] [2009-12-10 15:28:07] [64da8748fbb01eed936684060058da39] [Current]
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Dataseries X:
62.7
62.3
61.9
62
62.3
62.8
62.4
62.3
62.7
62.7
62.9
63
62.2
62.3
62.8
62.8
62.8
62.2
62.6
62.8
62.5
62.4
62.3
61.9
61.7
62
62.1
61.7
61.8
61.8
61.8
61.3
61.3
61.3
61.2
61.4
62.2
62.9
63.1
63.5
63.6
64.4
64.1
65.1
65.8
65.9
65.4
65.5
64.8
63.2
62.7
62.1
61.9
60.6
60.7
59.8
59
58.3
59.3
59
59.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65474&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65474&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65474&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.2181041.68940.048164
20.2108781.63350.053805
30.1746441.35280.0906
40.319712.47650.008053
5-0.036778-0.28490.388358
60.0619270.47970.316598
70.1031340.79890.213758
8-0.037995-0.29430.384768
9-0.221989-1.71950.045337
10-0.166926-1.2930.100484
110.0344730.2670.395182
12-0.418752-3.24360.000965
13-0.280031-2.16910.017024
14-0.14662-1.13570.130296
150.0195550.15150.440057
16-0.216757-1.6790.049177
17-0.056151-0.43490.332581
18-0.030096-0.23310.40823
19-0.033825-0.2620.397105
20-0.121471-0.94090.175262
210.0019680.01520.493943
220.1436671.11280.135107
23-0.015721-0.12180.451741
24-0.068402-0.52980.299089
250.0973840.75430.2268
260.0752650.5830.281038
27-0.04864-0.37680.353838
280.0387980.30050.382406
290.0858330.66490.254345
300.0480450.37220.355546
31-0.059026-0.45720.324584
320.0702410.54410.2942
330.1149440.89040.188416
34-0.000544-0.00420.498326
35-0.10619-0.82250.207012
360.0816110.63220.264843
37-0.023517-0.18220.428034
38-0.041751-0.32340.373758
390.0015280.01180.495298
400.0330230.25580.399493
41-0.098653-0.76420.223882
42-0.083605-0.64760.259856
43-0.038125-0.29530.384387
440.0001048e-040.499681
45-0.064621-0.50050.30926
46-0.093991-0.72810.234707
470.0381250.29530.384387
48-0.028412-0.22010.413278
490.0001048e-040.499681
500.0266770.20660.418496
51-0.009557-0.0740.470617
52-0.043331-0.33560.369157
530.035690.27650.391574
540.0406370.31480.377013
550.041570.3220.374287
56-0.008003-0.0620.475388
57-0.016395-0.1270.449685
580.0017610.01360.49458
59-0.003522-0.02730.489162
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.218104 & 1.6894 & 0.048164 \tabularnewline
2 & 0.210878 & 1.6335 & 0.053805 \tabularnewline
3 & 0.174644 & 1.3528 & 0.0906 \tabularnewline
4 & 0.31971 & 2.4765 & 0.008053 \tabularnewline
5 & -0.036778 & -0.2849 & 0.388358 \tabularnewline
6 & 0.061927 & 0.4797 & 0.316598 \tabularnewline
7 & 0.103134 & 0.7989 & 0.213758 \tabularnewline
8 & -0.037995 & -0.2943 & 0.384768 \tabularnewline
9 & -0.221989 & -1.7195 & 0.045337 \tabularnewline
10 & -0.166926 & -1.293 & 0.100484 \tabularnewline
11 & 0.034473 & 0.267 & 0.395182 \tabularnewline
12 & -0.418752 & -3.2436 & 0.000965 \tabularnewline
13 & -0.280031 & -2.1691 & 0.017024 \tabularnewline
14 & -0.14662 & -1.1357 & 0.130296 \tabularnewline
15 & 0.019555 & 0.1515 & 0.440057 \tabularnewline
16 & -0.216757 & -1.679 & 0.049177 \tabularnewline
17 & -0.056151 & -0.4349 & 0.332581 \tabularnewline
18 & -0.030096 & -0.2331 & 0.40823 \tabularnewline
19 & -0.033825 & -0.262 & 0.397105 \tabularnewline
20 & -0.121471 & -0.9409 & 0.175262 \tabularnewline
21 & 0.001968 & 0.0152 & 0.493943 \tabularnewline
22 & 0.143667 & 1.1128 & 0.135107 \tabularnewline
23 & -0.015721 & -0.1218 & 0.451741 \tabularnewline
24 & -0.068402 & -0.5298 & 0.299089 \tabularnewline
25 & 0.097384 & 0.7543 & 0.2268 \tabularnewline
26 & 0.075265 & 0.583 & 0.281038 \tabularnewline
27 & -0.04864 & -0.3768 & 0.353838 \tabularnewline
28 & 0.038798 & 0.3005 & 0.382406 \tabularnewline
29 & 0.085833 & 0.6649 & 0.254345 \tabularnewline
30 & 0.048045 & 0.3722 & 0.355546 \tabularnewline
31 & -0.059026 & -0.4572 & 0.324584 \tabularnewline
32 & 0.070241 & 0.5441 & 0.2942 \tabularnewline
33 & 0.114944 & 0.8904 & 0.188416 \tabularnewline
34 & -0.000544 & -0.0042 & 0.498326 \tabularnewline
35 & -0.10619 & -0.8225 & 0.207012 \tabularnewline
36 & 0.081611 & 0.6322 & 0.264843 \tabularnewline
37 & -0.023517 & -0.1822 & 0.428034 \tabularnewline
38 & -0.041751 & -0.3234 & 0.373758 \tabularnewline
39 & 0.001528 & 0.0118 & 0.495298 \tabularnewline
40 & 0.033023 & 0.2558 & 0.399493 \tabularnewline
41 & -0.098653 & -0.7642 & 0.223882 \tabularnewline
42 & -0.083605 & -0.6476 & 0.259856 \tabularnewline
43 & -0.038125 & -0.2953 & 0.384387 \tabularnewline
44 & 0.000104 & 8e-04 & 0.499681 \tabularnewline
45 & -0.064621 & -0.5005 & 0.30926 \tabularnewline
46 & -0.093991 & -0.7281 & 0.234707 \tabularnewline
47 & 0.038125 & 0.2953 & 0.384387 \tabularnewline
48 & -0.028412 & -0.2201 & 0.413278 \tabularnewline
49 & 0.000104 & 8e-04 & 0.499681 \tabularnewline
50 & 0.026677 & 0.2066 & 0.418496 \tabularnewline
51 & -0.009557 & -0.074 & 0.470617 \tabularnewline
52 & -0.043331 & -0.3356 & 0.369157 \tabularnewline
53 & 0.03569 & 0.2765 & 0.391574 \tabularnewline
54 & 0.040637 & 0.3148 & 0.377013 \tabularnewline
55 & 0.04157 & 0.322 & 0.374287 \tabularnewline
56 & -0.008003 & -0.062 & 0.475388 \tabularnewline
57 & -0.016395 & -0.127 & 0.449685 \tabularnewline
58 & 0.001761 & 0.0136 & 0.49458 \tabularnewline
59 & -0.003522 & -0.0273 & 0.489162 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65474&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]0.218104[/C][C]1.6894[/C][C]0.048164[/C][/ROW]
[ROW][C]2[/C][C]0.210878[/C][C]1.6335[/C][C]0.053805[/C][/ROW]
[ROW][C]3[/C][C]0.174644[/C][C]1.3528[/C][C]0.0906[/C][/ROW]
[ROW][C]4[/C][C]0.31971[/C][C]2.4765[/C][C]0.008053[/C][/ROW]
[ROW][C]5[/C][C]-0.036778[/C][C]-0.2849[/C][C]0.388358[/C][/ROW]
[ROW][C]6[/C][C]0.061927[/C][C]0.4797[/C][C]0.316598[/C][/ROW]
[ROW][C]7[/C][C]0.103134[/C][C]0.7989[/C][C]0.213758[/C][/ROW]
[ROW][C]8[/C][C]-0.037995[/C][C]-0.2943[/C][C]0.384768[/C][/ROW]
[ROW][C]9[/C][C]-0.221989[/C][C]-1.7195[/C][C]0.045337[/C][/ROW]
[ROW][C]10[/C][C]-0.166926[/C][C]-1.293[/C][C]0.100484[/C][/ROW]
[ROW][C]11[/C][C]0.034473[/C][C]0.267[/C][C]0.395182[/C][/ROW]
[ROW][C]12[/C][C]-0.418752[/C][C]-3.2436[/C][C]0.000965[/C][/ROW]
[ROW][C]13[/C][C]-0.280031[/C][C]-2.1691[/C][C]0.017024[/C][/ROW]
[ROW][C]14[/C][C]-0.14662[/C][C]-1.1357[/C][C]0.130296[/C][/ROW]
[ROW][C]15[/C][C]0.019555[/C][C]0.1515[/C][C]0.440057[/C][/ROW]
[ROW][C]16[/C][C]-0.216757[/C][C]-1.679[/C][C]0.049177[/C][/ROW]
[ROW][C]17[/C][C]-0.056151[/C][C]-0.4349[/C][C]0.332581[/C][/ROW]
[ROW][C]18[/C][C]-0.030096[/C][C]-0.2331[/C][C]0.40823[/C][/ROW]
[ROW][C]19[/C][C]-0.033825[/C][C]-0.262[/C][C]0.397105[/C][/ROW]
[ROW][C]20[/C][C]-0.121471[/C][C]-0.9409[/C][C]0.175262[/C][/ROW]
[ROW][C]21[/C][C]0.001968[/C][C]0.0152[/C][C]0.493943[/C][/ROW]
[ROW][C]22[/C][C]0.143667[/C][C]1.1128[/C][C]0.135107[/C][/ROW]
[ROW][C]23[/C][C]-0.015721[/C][C]-0.1218[/C][C]0.451741[/C][/ROW]
[ROW][C]24[/C][C]-0.068402[/C][C]-0.5298[/C][C]0.299089[/C][/ROW]
[ROW][C]25[/C][C]0.097384[/C][C]0.7543[/C][C]0.2268[/C][/ROW]
[ROW][C]26[/C][C]0.075265[/C][C]0.583[/C][C]0.281038[/C][/ROW]
[ROW][C]27[/C][C]-0.04864[/C][C]-0.3768[/C][C]0.353838[/C][/ROW]
[ROW][C]28[/C][C]0.038798[/C][C]0.3005[/C][C]0.382406[/C][/ROW]
[ROW][C]29[/C][C]0.085833[/C][C]0.6649[/C][C]0.254345[/C][/ROW]
[ROW][C]30[/C][C]0.048045[/C][C]0.3722[/C][C]0.355546[/C][/ROW]
[ROW][C]31[/C][C]-0.059026[/C][C]-0.4572[/C][C]0.324584[/C][/ROW]
[ROW][C]32[/C][C]0.070241[/C][C]0.5441[/C][C]0.2942[/C][/ROW]
[ROW][C]33[/C][C]0.114944[/C][C]0.8904[/C][C]0.188416[/C][/ROW]
[ROW][C]34[/C][C]-0.000544[/C][C]-0.0042[/C][C]0.498326[/C][/ROW]
[ROW][C]35[/C][C]-0.10619[/C][C]-0.8225[/C][C]0.207012[/C][/ROW]
[ROW][C]36[/C][C]0.081611[/C][C]0.6322[/C][C]0.264843[/C][/ROW]
[ROW][C]37[/C][C]-0.023517[/C][C]-0.1822[/C][C]0.428034[/C][/ROW]
[ROW][C]38[/C][C]-0.041751[/C][C]-0.3234[/C][C]0.373758[/C][/ROW]
[ROW][C]39[/C][C]0.001528[/C][C]0.0118[/C][C]0.495298[/C][/ROW]
[ROW][C]40[/C][C]0.033023[/C][C]0.2558[/C][C]0.399493[/C][/ROW]
[ROW][C]41[/C][C]-0.098653[/C][C]-0.7642[/C][C]0.223882[/C][/ROW]
[ROW][C]42[/C][C]-0.083605[/C][C]-0.6476[/C][C]0.259856[/C][/ROW]
[ROW][C]43[/C][C]-0.038125[/C][C]-0.2953[/C][C]0.384387[/C][/ROW]
[ROW][C]44[/C][C]0.000104[/C][C]8e-04[/C][C]0.499681[/C][/ROW]
[ROW][C]45[/C][C]-0.064621[/C][C]-0.5005[/C][C]0.30926[/C][/ROW]
[ROW][C]46[/C][C]-0.093991[/C][C]-0.7281[/C][C]0.234707[/C][/ROW]
[ROW][C]47[/C][C]0.038125[/C][C]0.2953[/C][C]0.384387[/C][/ROW]
[ROW][C]48[/C][C]-0.028412[/C][C]-0.2201[/C][C]0.413278[/C][/ROW]
[ROW][C]49[/C][C]0.000104[/C][C]8e-04[/C][C]0.499681[/C][/ROW]
[ROW][C]50[/C][C]0.026677[/C][C]0.2066[/C][C]0.418496[/C][/ROW]
[ROW][C]51[/C][C]-0.009557[/C][C]-0.074[/C][C]0.470617[/C][/ROW]
[ROW][C]52[/C][C]-0.043331[/C][C]-0.3356[/C][C]0.369157[/C][/ROW]
[ROW][C]53[/C][C]0.03569[/C][C]0.2765[/C][C]0.391574[/C][/ROW]
[ROW][C]54[/C][C]0.040637[/C][C]0.3148[/C][C]0.377013[/C][/ROW]
[ROW][C]55[/C][C]0.04157[/C][C]0.322[/C][C]0.374287[/C][/ROW]
[ROW][C]56[/C][C]-0.008003[/C][C]-0.062[/C][C]0.475388[/C][/ROW]
[ROW][C]57[/C][C]-0.016395[/C][C]-0.127[/C][C]0.449685[/C][/ROW]
[ROW][C]58[/C][C]0.001761[/C][C]0.0136[/C][C]0.49458[/C][/ROW]
[ROW][C]59[/C][C]-0.003522[/C][C]-0.0273[/C][C]0.489162[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65474&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65474&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
10.2181041.68940.048164
20.2108781.63350.053805
30.1746441.35280.0906
40.319712.47650.008053
5-0.036778-0.28490.388358
60.0619270.47970.316598
70.1031340.79890.213758
8-0.037995-0.29430.384768
9-0.221989-1.71950.045337
10-0.166926-1.2930.100484
110.0344730.2670.395182
12-0.418752-3.24360.000965
13-0.280031-2.16910.017024
14-0.14662-1.13570.130296
150.0195550.15150.440057
16-0.216757-1.6790.049177
17-0.056151-0.43490.332581
18-0.030096-0.23310.40823
19-0.033825-0.2620.397105
20-0.121471-0.94090.175262
210.0019680.01520.493943
220.1436671.11280.135107
23-0.015721-0.12180.451741
24-0.068402-0.52980.299089
250.0973840.75430.2268
260.0752650.5830.281038
27-0.04864-0.37680.353838
280.0387980.30050.382406
290.0858330.66490.254345
300.0480450.37220.355546
31-0.059026-0.45720.324584
320.0702410.54410.2942
330.1149440.89040.188416
34-0.000544-0.00420.498326
35-0.10619-0.82250.207012
360.0816110.63220.264843
37-0.023517-0.18220.428034
38-0.041751-0.32340.373758
390.0015280.01180.495298
400.0330230.25580.399493
41-0.098653-0.76420.223882
42-0.083605-0.64760.259856
43-0.038125-0.29530.384387
440.0001048e-040.499681
45-0.064621-0.50050.30926
46-0.093991-0.72810.234707
470.0381250.29530.384387
48-0.028412-0.22010.413278
490.0001048e-040.499681
500.0266770.20660.418496
51-0.009557-0.0740.470617
52-0.043331-0.33560.369157
530.035690.27650.391574
540.0406370.31480.377013
550.041570.3220.374287
56-0.008003-0.0620.475388
57-0.016395-0.1270.449685
580.0017610.01360.49458
59-0.003522-0.02730.489162
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.2181041.68940.048164
20.1714651.32820.094577
30.1072440.83070.204716
40.2581541.99970.025036
5-0.198862-1.54040.064363
6-0.004273-0.03310.486851
70.0744720.57690.283096
8-0.15811-1.22470.112734
9-0.181622-1.40680.082317
10-0.143872-1.11440.134771
110.1494621.15770.125782
12-0.391856-3.03530.001775
13-0.082325-0.63770.263051
140.0797630.61780.26951
150.1297961.00540.159372
160.0835920.64750.259888
17-0.064217-0.49740.310354
18-0.02985-0.23120.408967
19-0.015448-0.11970.452576
20-0.039075-0.30270.381593
21-0.149572-1.15860.12561
220.0197070.15260.439594
230.0751320.5820.281383
24-0.23071-1.78710.039489
250.0357170.27670.391496
26-0.053277-0.41270.340656
270.0896150.69420.245132
280.1043320.80820.211098
29-0.051969-0.40260.344355
300.0374210.28990.38646
31-0.086417-0.66940.25291
320.072470.56130.288325
33-0.054018-0.41840.338566
34-0.004404-0.03410.486451
35-0.05989-0.46390.322198
36-0.079764-0.61780.269507
37-0.040852-0.31640.376383
38-0.034835-0.26980.394109
390.1442291.11720.134183
40-0.046045-0.35670.361299
41-0.044189-0.34230.366665
420.0235670.18260.427883
43-0.105527-0.81740.208464
440.0589240.45640.324867
45-0.046398-0.35940.360281
460.0122710.0950.462296
47-0.029138-0.22570.411102
48-0.046047-0.35670.361291
490.0461610.35760.360962
50-0.021954-0.17010.432769
51-0.029565-0.2290.409819
52-0.02333-0.18070.428601
530.0379010.29360.385045
54-0.011575-0.08970.464428
55-0.080707-0.62520.267119
56-0.016236-0.12580.45017
57-0.0222-0.1720.432024
58-0.013631-0.10560.458133
59-0.013111-0.10160.459725
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.218104 & 1.6894 & 0.048164 \tabularnewline
2 & 0.171465 & 1.3282 & 0.094577 \tabularnewline
3 & 0.107244 & 0.8307 & 0.204716 \tabularnewline
4 & 0.258154 & 1.9997 & 0.025036 \tabularnewline
5 & -0.198862 & -1.5404 & 0.064363 \tabularnewline
6 & -0.004273 & -0.0331 & 0.486851 \tabularnewline
7 & 0.074472 & 0.5769 & 0.283096 \tabularnewline
8 & -0.15811 & -1.2247 & 0.112734 \tabularnewline
9 & -0.181622 & -1.4068 & 0.082317 \tabularnewline
10 & -0.143872 & -1.1144 & 0.134771 \tabularnewline
11 & 0.149462 & 1.1577 & 0.125782 \tabularnewline
12 & -0.391856 & -3.0353 & 0.001775 \tabularnewline
13 & -0.082325 & -0.6377 & 0.263051 \tabularnewline
14 & 0.079763 & 0.6178 & 0.26951 \tabularnewline
15 & 0.129796 & 1.0054 & 0.159372 \tabularnewline
16 & 0.083592 & 0.6475 & 0.259888 \tabularnewline
17 & -0.064217 & -0.4974 & 0.310354 \tabularnewline
18 & -0.02985 & -0.2312 & 0.408967 \tabularnewline
19 & -0.015448 & -0.1197 & 0.452576 \tabularnewline
20 & -0.039075 & -0.3027 & 0.381593 \tabularnewline
21 & -0.149572 & -1.1586 & 0.12561 \tabularnewline
22 & 0.019707 & 0.1526 & 0.439594 \tabularnewline
23 & 0.075132 & 0.582 & 0.281383 \tabularnewline
24 & -0.23071 & -1.7871 & 0.039489 \tabularnewline
25 & 0.035717 & 0.2767 & 0.391496 \tabularnewline
26 & -0.053277 & -0.4127 & 0.340656 \tabularnewline
27 & 0.089615 & 0.6942 & 0.245132 \tabularnewline
28 & 0.104332 & 0.8082 & 0.211098 \tabularnewline
29 & -0.051969 & -0.4026 & 0.344355 \tabularnewline
30 & 0.037421 & 0.2899 & 0.38646 \tabularnewline
31 & -0.086417 & -0.6694 & 0.25291 \tabularnewline
32 & 0.07247 & 0.5613 & 0.288325 \tabularnewline
33 & -0.054018 & -0.4184 & 0.338566 \tabularnewline
34 & -0.004404 & -0.0341 & 0.486451 \tabularnewline
35 & -0.05989 & -0.4639 & 0.322198 \tabularnewline
36 & -0.079764 & -0.6178 & 0.269507 \tabularnewline
37 & -0.040852 & -0.3164 & 0.376383 \tabularnewline
38 & -0.034835 & -0.2698 & 0.394109 \tabularnewline
39 & 0.144229 & 1.1172 & 0.134183 \tabularnewline
40 & -0.046045 & -0.3567 & 0.361299 \tabularnewline
41 & -0.044189 & -0.3423 & 0.366665 \tabularnewline
42 & 0.023567 & 0.1826 & 0.427883 \tabularnewline
43 & -0.105527 & -0.8174 & 0.208464 \tabularnewline
44 & 0.058924 & 0.4564 & 0.324867 \tabularnewline
45 & -0.046398 & -0.3594 & 0.360281 \tabularnewline
46 & 0.012271 & 0.095 & 0.462296 \tabularnewline
47 & -0.029138 & -0.2257 & 0.411102 \tabularnewline
48 & -0.046047 & -0.3567 & 0.361291 \tabularnewline
49 & 0.046161 & 0.3576 & 0.360962 \tabularnewline
50 & -0.021954 & -0.1701 & 0.432769 \tabularnewline
51 & -0.029565 & -0.229 & 0.409819 \tabularnewline
52 & -0.02333 & -0.1807 & 0.428601 \tabularnewline
53 & 0.037901 & 0.2936 & 0.385045 \tabularnewline
54 & -0.011575 & -0.0897 & 0.464428 \tabularnewline
55 & -0.080707 & -0.6252 & 0.267119 \tabularnewline
56 & -0.016236 & -0.1258 & 0.45017 \tabularnewline
57 & -0.0222 & -0.172 & 0.432024 \tabularnewline
58 & -0.013631 & -0.1056 & 0.458133 \tabularnewline
59 & -0.013111 & -0.1016 & 0.459725 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=65474&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]0.218104[/C][C]1.6894[/C][C]0.048164[/C][/ROW]
[ROW][C]2[/C][C]0.171465[/C][C]1.3282[/C][C]0.094577[/C][/ROW]
[ROW][C]3[/C][C]0.107244[/C][C]0.8307[/C][C]0.204716[/C][/ROW]
[ROW][C]4[/C][C]0.258154[/C][C]1.9997[/C][C]0.025036[/C][/ROW]
[ROW][C]5[/C][C]-0.198862[/C][C]-1.5404[/C][C]0.064363[/C][/ROW]
[ROW][C]6[/C][C]-0.004273[/C][C]-0.0331[/C][C]0.486851[/C][/ROW]
[ROW][C]7[/C][C]0.074472[/C][C]0.5769[/C][C]0.283096[/C][/ROW]
[ROW][C]8[/C][C]-0.15811[/C][C]-1.2247[/C][C]0.112734[/C][/ROW]
[ROW][C]9[/C][C]-0.181622[/C][C]-1.4068[/C][C]0.082317[/C][/ROW]
[ROW][C]10[/C][C]-0.143872[/C][C]-1.1144[/C][C]0.134771[/C][/ROW]
[ROW][C]11[/C][C]0.149462[/C][C]1.1577[/C][C]0.125782[/C][/ROW]
[ROW][C]12[/C][C]-0.391856[/C][C]-3.0353[/C][C]0.001775[/C][/ROW]
[ROW][C]13[/C][C]-0.082325[/C][C]-0.6377[/C][C]0.263051[/C][/ROW]
[ROW][C]14[/C][C]0.079763[/C][C]0.6178[/C][C]0.26951[/C][/ROW]
[ROW][C]15[/C][C]0.129796[/C][C]1.0054[/C][C]0.159372[/C][/ROW]
[ROW][C]16[/C][C]0.083592[/C][C]0.6475[/C][C]0.259888[/C][/ROW]
[ROW][C]17[/C][C]-0.064217[/C][C]-0.4974[/C][C]0.310354[/C][/ROW]
[ROW][C]18[/C][C]-0.02985[/C][C]-0.2312[/C][C]0.408967[/C][/ROW]
[ROW][C]19[/C][C]-0.015448[/C][C]-0.1197[/C][C]0.452576[/C][/ROW]
[ROW][C]20[/C][C]-0.039075[/C][C]-0.3027[/C][C]0.381593[/C][/ROW]
[ROW][C]21[/C][C]-0.149572[/C][C]-1.1586[/C][C]0.12561[/C][/ROW]
[ROW][C]22[/C][C]0.019707[/C][C]0.1526[/C][C]0.439594[/C][/ROW]
[ROW][C]23[/C][C]0.075132[/C][C]0.582[/C][C]0.281383[/C][/ROW]
[ROW][C]24[/C][C]-0.23071[/C][C]-1.7871[/C][C]0.039489[/C][/ROW]
[ROW][C]25[/C][C]0.035717[/C][C]0.2767[/C][C]0.391496[/C][/ROW]
[ROW][C]26[/C][C]-0.053277[/C][C]-0.4127[/C][C]0.340656[/C][/ROW]
[ROW][C]27[/C][C]0.089615[/C][C]0.6942[/C][C]0.245132[/C][/ROW]
[ROW][C]28[/C][C]0.104332[/C][C]0.8082[/C][C]0.211098[/C][/ROW]
[ROW][C]29[/C][C]-0.051969[/C][C]-0.4026[/C][C]0.344355[/C][/ROW]
[ROW][C]30[/C][C]0.037421[/C][C]0.2899[/C][C]0.38646[/C][/ROW]
[ROW][C]31[/C][C]-0.086417[/C][C]-0.6694[/C][C]0.25291[/C][/ROW]
[ROW][C]32[/C][C]0.07247[/C][C]0.5613[/C][C]0.288325[/C][/ROW]
[ROW][C]33[/C][C]-0.054018[/C][C]-0.4184[/C][C]0.338566[/C][/ROW]
[ROW][C]34[/C][C]-0.004404[/C][C]-0.0341[/C][C]0.486451[/C][/ROW]
[ROW][C]35[/C][C]-0.05989[/C][C]-0.4639[/C][C]0.322198[/C][/ROW]
[ROW][C]36[/C][C]-0.079764[/C][C]-0.6178[/C][C]0.269507[/C][/ROW]
[ROW][C]37[/C][C]-0.040852[/C][C]-0.3164[/C][C]0.376383[/C][/ROW]
[ROW][C]38[/C][C]-0.034835[/C][C]-0.2698[/C][C]0.394109[/C][/ROW]
[ROW][C]39[/C][C]0.144229[/C][C]1.1172[/C][C]0.134183[/C][/ROW]
[ROW][C]40[/C][C]-0.046045[/C][C]-0.3567[/C][C]0.361299[/C][/ROW]
[ROW][C]41[/C][C]-0.044189[/C][C]-0.3423[/C][C]0.366665[/C][/ROW]
[ROW][C]42[/C][C]0.023567[/C][C]0.1826[/C][C]0.427883[/C][/ROW]
[ROW][C]43[/C][C]-0.105527[/C][C]-0.8174[/C][C]0.208464[/C][/ROW]
[ROW][C]44[/C][C]0.058924[/C][C]0.4564[/C][C]0.324867[/C][/ROW]
[ROW][C]45[/C][C]-0.046398[/C][C]-0.3594[/C][C]0.360281[/C][/ROW]
[ROW][C]46[/C][C]0.012271[/C][C]0.095[/C][C]0.462296[/C][/ROW]
[ROW][C]47[/C][C]-0.029138[/C][C]-0.2257[/C][C]0.411102[/C][/ROW]
[ROW][C]48[/C][C]-0.046047[/C][C]-0.3567[/C][C]0.361291[/C][/ROW]
[ROW][C]49[/C][C]0.046161[/C][C]0.3576[/C][C]0.360962[/C][/ROW]
[ROW][C]50[/C][C]-0.021954[/C][C]-0.1701[/C][C]0.432769[/C][/ROW]
[ROW][C]51[/C][C]-0.029565[/C][C]-0.229[/C][C]0.409819[/C][/ROW]
[ROW][C]52[/C][C]-0.02333[/C][C]-0.1807[/C][C]0.428601[/C][/ROW]
[ROW][C]53[/C][C]0.037901[/C][C]0.2936[/C][C]0.385045[/C][/ROW]
[ROW][C]54[/C][C]-0.011575[/C][C]-0.0897[/C][C]0.464428[/C][/ROW]
[ROW][C]55[/C][C]-0.080707[/C][C]-0.6252[/C][C]0.267119[/C][/ROW]
[ROW][C]56[/C][C]-0.016236[/C][C]-0.1258[/C][C]0.45017[/C][/ROW]
[ROW][C]57[/C][C]-0.0222[/C][C]-0.172[/C][C]0.432024[/C][/ROW]
[ROW][C]58[/C][C]-0.013631[/C][C]-0.1056[/C][C]0.458133[/C][/ROW]
[ROW][C]59[/C][C]-0.013111[/C][C]-0.1016[/C][C]0.459725[/C][/ROW]
[ROW][C]60[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=65474&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=65474&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
10.2181041.68940.048164
20.1714651.32820.094577
30.1072440.83070.204716
40.2581541.99970.025036
5-0.198862-1.54040.064363
6-0.004273-0.03310.486851
70.0744720.57690.283096
8-0.15811-1.22470.112734
9-0.181622-1.40680.082317
10-0.143872-1.11440.134771
110.1494621.15770.125782
12-0.391856-3.03530.001775
13-0.082325-0.63770.263051
140.0797630.61780.26951
150.1297961.00540.159372
160.0835920.64750.259888
17-0.064217-0.49740.310354
18-0.02985-0.23120.408967
19-0.015448-0.11970.452576
20-0.039075-0.30270.381593
21-0.149572-1.15860.12561
220.0197070.15260.439594
230.0751320.5820.281383
24-0.23071-1.78710.039489
250.0357170.27670.391496
26-0.053277-0.41270.340656
270.0896150.69420.245132
280.1043320.80820.211098
29-0.051969-0.40260.344355
300.0374210.28990.38646
31-0.086417-0.66940.25291
320.072470.56130.288325
33-0.054018-0.41840.338566
34-0.004404-0.03410.486451
35-0.05989-0.46390.322198
36-0.079764-0.61780.269507
37-0.040852-0.31640.376383
38-0.034835-0.26980.394109
390.1442291.11720.134183
40-0.046045-0.35670.361299
41-0.044189-0.34230.366665
420.0235670.18260.427883
43-0.105527-0.81740.208464
440.0589240.45640.324867
45-0.046398-0.35940.360281
460.0122710.0950.462296
47-0.029138-0.22570.411102
48-0.046047-0.35670.361291
490.0461610.35760.360962
50-0.021954-0.17010.432769
51-0.029565-0.2290.409819
52-0.02333-0.18070.428601
530.0379010.29360.385045
54-0.011575-0.08970.464428
55-0.080707-0.62520.267119
56-0.016236-0.12580.45017
57-0.0222-0.1720.432024
58-0.013631-0.10560.458133
59-0.013111-0.10160.459725
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; 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')