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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 21 Dec 2009 04:35:38 -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/21/t1261395369dk98swq6xdrsbdi.htm/, Retrieved Sun, 05 May 2024 13:59:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70109, Retrieved Sun, 05 May 2024 13:59:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2009-12-21 11:35:38] [f340d7563d07b81b9aae66c73f3e92ac] [Current]
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Dataseries X:
581
597
587
536
524
537
536
533
528
516
502
506
518
534
528
478
469
490
493
508
517
514
510
527
542
565
555
499
511
526
532
549
561
557
566
588
620
626
620
573
573
574
580
590
593
597
595
612
628
629
621
569
567
573
584
589
591
595
594
611




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=70109&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=70109&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70109&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
10.1345660.92250.180481
20.2489181.70650.047258
30.3396732.32870.012114
40.2301851.57810.060629
50.0752050.51560.304282
60.191381.3120.09794
70.0510290.34980.364012
80.1683531.15420.127132
90.0294350.20180.420473
10-0.068755-0.47140.319783
110.3147332.15770.018047
12-0.153266-1.05070.149375
13-0.062419-0.42790.335331
140.0863740.59210.278295
150.0634070.43470.332886
16-0.065479-0.44890.327783
170.0640460.43910.331309
18-0.152196-1.04340.15105
19-0.022869-0.15680.438045
20-0.148765-1.01990.156503
21-0.213856-1.46610.074637
22-0.062969-0.43170.333969
23-0.193208-1.32460.09586
24-0.174013-1.1930.119434
25-0.12482-0.85570.198246
26-0.109814-0.75280.227648
27-0.228909-1.56930.061641
28-0.132983-0.91170.183293
29-0.157247-1.0780.143261
30-0.091276-0.62580.26725
31-0.068017-0.46630.321578
32-0.081637-0.55970.28918
33-0.030276-0.20760.418235
34-0.022299-0.15290.439575
35-0.020296-0.13910.444965
36-0.038556-0.26430.396342
37-0.019448-0.13330.447253
38-0.023276-0.15960.43695
39-0.011216-0.07690.469516
40-0.008287-0.05680.477467
41-0.008403-0.05760.477152
42-0.001977-0.01360.494621
43-0.000753-0.00520.497952
440.0003790.00260.498969
45-0.000905-0.00620.497539
460.0005050.00350.498625
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.134566 & 0.9225 & 0.180481 \tabularnewline
2 & 0.248918 & 1.7065 & 0.047258 \tabularnewline
3 & 0.339673 & 2.3287 & 0.012114 \tabularnewline
4 & 0.230185 & 1.5781 & 0.060629 \tabularnewline
5 & 0.075205 & 0.5156 & 0.304282 \tabularnewline
6 & 0.19138 & 1.312 & 0.09794 \tabularnewline
7 & 0.051029 & 0.3498 & 0.364012 \tabularnewline
8 & 0.168353 & 1.1542 & 0.127132 \tabularnewline
9 & 0.029435 & 0.2018 & 0.420473 \tabularnewline
10 & -0.068755 & -0.4714 & 0.319783 \tabularnewline
11 & 0.314733 & 2.1577 & 0.018047 \tabularnewline
12 & -0.153266 & -1.0507 & 0.149375 \tabularnewline
13 & -0.062419 & -0.4279 & 0.335331 \tabularnewline
14 & 0.086374 & 0.5921 & 0.278295 \tabularnewline
15 & 0.063407 & 0.4347 & 0.332886 \tabularnewline
16 & -0.065479 & -0.4489 & 0.327783 \tabularnewline
17 & 0.064046 & 0.4391 & 0.331309 \tabularnewline
18 & -0.152196 & -1.0434 & 0.15105 \tabularnewline
19 & -0.022869 & -0.1568 & 0.438045 \tabularnewline
20 & -0.148765 & -1.0199 & 0.156503 \tabularnewline
21 & -0.213856 & -1.4661 & 0.074637 \tabularnewline
22 & -0.062969 & -0.4317 & 0.333969 \tabularnewline
23 & -0.193208 & -1.3246 & 0.09586 \tabularnewline
24 & -0.174013 & -1.193 & 0.119434 \tabularnewline
25 & -0.12482 & -0.8557 & 0.198246 \tabularnewline
26 & -0.109814 & -0.7528 & 0.227648 \tabularnewline
27 & -0.228909 & -1.5693 & 0.061641 \tabularnewline
28 & -0.132983 & -0.9117 & 0.183293 \tabularnewline
29 & -0.157247 & -1.078 & 0.143261 \tabularnewline
30 & -0.091276 & -0.6258 & 0.26725 \tabularnewline
31 & -0.068017 & -0.4663 & 0.321578 \tabularnewline
32 & -0.081637 & -0.5597 & 0.28918 \tabularnewline
33 & -0.030276 & -0.2076 & 0.418235 \tabularnewline
34 & -0.022299 & -0.1529 & 0.439575 \tabularnewline
35 & -0.020296 & -0.1391 & 0.444965 \tabularnewline
36 & -0.038556 & -0.2643 & 0.396342 \tabularnewline
37 & -0.019448 & -0.1333 & 0.447253 \tabularnewline
38 & -0.023276 & -0.1596 & 0.43695 \tabularnewline
39 & -0.011216 & -0.0769 & 0.469516 \tabularnewline
40 & -0.008287 & -0.0568 & 0.477467 \tabularnewline
41 & -0.008403 & -0.0576 & 0.477152 \tabularnewline
42 & -0.001977 & -0.0136 & 0.494621 \tabularnewline
43 & -0.000753 & -0.0052 & 0.497952 \tabularnewline
44 & 0.000379 & 0.0026 & 0.498969 \tabularnewline
45 & -0.000905 & -0.0062 & 0.497539 \tabularnewline
46 & 0.000505 & 0.0035 & 0.498625 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70109&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]0.134566[/C][C]0.9225[/C][C]0.180481[/C][/ROW]
[ROW][C]2[/C][C]0.248918[/C][C]1.7065[/C][C]0.047258[/C][/ROW]
[ROW][C]3[/C][C]0.339673[/C][C]2.3287[/C][C]0.012114[/C][/ROW]
[ROW][C]4[/C][C]0.230185[/C][C]1.5781[/C][C]0.060629[/C][/ROW]
[ROW][C]5[/C][C]0.075205[/C][C]0.5156[/C][C]0.304282[/C][/ROW]
[ROW][C]6[/C][C]0.19138[/C][C]1.312[/C][C]0.09794[/C][/ROW]
[ROW][C]7[/C][C]0.051029[/C][C]0.3498[/C][C]0.364012[/C][/ROW]
[ROW][C]8[/C][C]0.168353[/C][C]1.1542[/C][C]0.127132[/C][/ROW]
[ROW][C]9[/C][C]0.029435[/C][C]0.2018[/C][C]0.420473[/C][/ROW]
[ROW][C]10[/C][C]-0.068755[/C][C]-0.4714[/C][C]0.319783[/C][/ROW]
[ROW][C]11[/C][C]0.314733[/C][C]2.1577[/C][C]0.018047[/C][/ROW]
[ROW][C]12[/C][C]-0.153266[/C][C]-1.0507[/C][C]0.149375[/C][/ROW]
[ROW][C]13[/C][C]-0.062419[/C][C]-0.4279[/C][C]0.335331[/C][/ROW]
[ROW][C]14[/C][C]0.086374[/C][C]0.5921[/C][C]0.278295[/C][/ROW]
[ROW][C]15[/C][C]0.063407[/C][C]0.4347[/C][C]0.332886[/C][/ROW]
[ROW][C]16[/C][C]-0.065479[/C][C]-0.4489[/C][C]0.327783[/C][/ROW]
[ROW][C]17[/C][C]0.064046[/C][C]0.4391[/C][C]0.331309[/C][/ROW]
[ROW][C]18[/C][C]-0.152196[/C][C]-1.0434[/C][C]0.15105[/C][/ROW]
[ROW][C]19[/C][C]-0.022869[/C][C]-0.1568[/C][C]0.438045[/C][/ROW]
[ROW][C]20[/C][C]-0.148765[/C][C]-1.0199[/C][C]0.156503[/C][/ROW]
[ROW][C]21[/C][C]-0.213856[/C][C]-1.4661[/C][C]0.074637[/C][/ROW]
[ROW][C]22[/C][C]-0.062969[/C][C]-0.4317[/C][C]0.333969[/C][/ROW]
[ROW][C]23[/C][C]-0.193208[/C][C]-1.3246[/C][C]0.09586[/C][/ROW]
[ROW][C]24[/C][C]-0.174013[/C][C]-1.193[/C][C]0.119434[/C][/ROW]
[ROW][C]25[/C][C]-0.12482[/C][C]-0.8557[/C][C]0.198246[/C][/ROW]
[ROW][C]26[/C][C]-0.109814[/C][C]-0.7528[/C][C]0.227648[/C][/ROW]
[ROW][C]27[/C][C]-0.228909[/C][C]-1.5693[/C][C]0.061641[/C][/ROW]
[ROW][C]28[/C][C]-0.132983[/C][C]-0.9117[/C][C]0.183293[/C][/ROW]
[ROW][C]29[/C][C]-0.157247[/C][C]-1.078[/C][C]0.143261[/C][/ROW]
[ROW][C]30[/C][C]-0.091276[/C][C]-0.6258[/C][C]0.26725[/C][/ROW]
[ROW][C]31[/C][C]-0.068017[/C][C]-0.4663[/C][C]0.321578[/C][/ROW]
[ROW][C]32[/C][C]-0.081637[/C][C]-0.5597[/C][C]0.28918[/C][/ROW]
[ROW][C]33[/C][C]-0.030276[/C][C]-0.2076[/C][C]0.418235[/C][/ROW]
[ROW][C]34[/C][C]-0.022299[/C][C]-0.1529[/C][C]0.439575[/C][/ROW]
[ROW][C]35[/C][C]-0.020296[/C][C]-0.1391[/C][C]0.444965[/C][/ROW]
[ROW][C]36[/C][C]-0.038556[/C][C]-0.2643[/C][C]0.396342[/C][/ROW]
[ROW][C]37[/C][C]-0.019448[/C][C]-0.1333[/C][C]0.447253[/C][/ROW]
[ROW][C]38[/C][C]-0.023276[/C][C]-0.1596[/C][C]0.43695[/C][/ROW]
[ROW][C]39[/C][C]-0.011216[/C][C]-0.0769[/C][C]0.469516[/C][/ROW]
[ROW][C]40[/C][C]-0.008287[/C][C]-0.0568[/C][C]0.477467[/C][/ROW]
[ROW][C]41[/C][C]-0.008403[/C][C]-0.0576[/C][C]0.477152[/C][/ROW]
[ROW][C]42[/C][C]-0.001977[/C][C]-0.0136[/C][C]0.494621[/C][/ROW]
[ROW][C]43[/C][C]-0.000753[/C][C]-0.0052[/C][C]0.497952[/C][/ROW]
[ROW][C]44[/C][C]0.000379[/C][C]0.0026[/C][C]0.498969[/C][/ROW]
[ROW][C]45[/C][C]-0.000905[/C][C]-0.0062[/C][C]0.497539[/C][/ROW]
[ROW][C]46[/C][C]0.000505[/C][C]0.0035[/C][C]0.498625[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/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=70109&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70109&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
10.1345660.92250.180481
20.2489181.70650.047258
30.3396732.32870.012114
40.2301851.57810.060629
50.0752050.51560.304282
60.191381.3120.09794
70.0510290.34980.364012
80.1683531.15420.127132
90.0294350.20180.420473
10-0.068755-0.47140.319783
110.3147332.15770.018047
12-0.153266-1.05070.149375
13-0.062419-0.42790.335331
140.0863740.59210.278295
150.0634070.43470.332886
16-0.065479-0.44890.327783
170.0640460.43910.331309
18-0.152196-1.04340.15105
19-0.022869-0.15680.438045
20-0.148765-1.01990.156503
21-0.213856-1.46610.074637
22-0.062969-0.43170.333969
23-0.193208-1.32460.09586
24-0.174013-1.1930.119434
25-0.12482-0.85570.198246
26-0.109814-0.75280.227648
27-0.228909-1.56930.061641
28-0.132983-0.91170.183293
29-0.157247-1.0780.143261
30-0.091276-0.62580.26725
31-0.068017-0.46630.321578
32-0.081637-0.55970.28918
33-0.030276-0.20760.418235
34-0.022299-0.15290.439575
35-0.020296-0.13910.444965
36-0.038556-0.26430.396342
37-0.019448-0.13330.447253
38-0.023276-0.15960.43695
39-0.011216-0.07690.469516
40-0.008287-0.05680.477467
41-0.008403-0.05760.477152
42-0.001977-0.01360.494621
43-0.000753-0.00520.497952
440.0003790.00260.498969
45-0.000905-0.00620.497539
460.0005050.00350.498625
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.1345660.92250.180481
20.2350671.61150.056879
30.3044512.08720.021159
40.1519031.04140.15151
5-0.091334-0.62620.267123
60.0159990.10970.456563
7-0.079559-0.54540.294019
80.1239160.84950.199948
9-0.03081-0.21120.416813
10-0.175113-1.20050.117978
110.3261782.23620.015063
12-0.251841-1.72650.04541
13-0.078854-0.54060.295669
140.0273560.18750.426021
150.1173170.80430.212641
160.0833250.57120.285276
17-0.095659-0.65580.257573
18-0.193702-1.3280.095303
19-0.120242-0.82430.206956
20-0.067125-0.46020.323752
21-0.050048-0.34310.366522
22-0.08917-0.61130.271966
230.0352430.24160.405064
240.0558490.38290.351766
25-0.11003-0.75430.227209
26-0.03698-0.25350.400487
27-0.099226-0.68030.249839
28-0.049537-0.33960.367831
290.1330890.91240.183105
30-0.05235-0.35890.360642
310.0945120.64790.260087
32-0.00059-0.0040.498395
33-0.013035-0.08940.464587
340.0381160.26130.397499
350.0076990.05280.479065
360.0574340.39370.347773
37-0.078887-0.54080.295591
380.0358180.24560.403547
39-0.038318-0.26270.396966
40-0.087697-0.60120.275292
41-0.004918-0.03370.486622
42-0.041886-0.28720.387628
430.0525750.36040.360069
440.0347550.23830.406355
45-0.090845-0.62280.268212
46-0.115518-0.79190.216185
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.134566 & 0.9225 & 0.180481 \tabularnewline
2 & 0.235067 & 1.6115 & 0.056879 \tabularnewline
3 & 0.304451 & 2.0872 & 0.021159 \tabularnewline
4 & 0.151903 & 1.0414 & 0.15151 \tabularnewline
5 & -0.091334 & -0.6262 & 0.267123 \tabularnewline
6 & 0.015999 & 0.1097 & 0.456563 \tabularnewline
7 & -0.079559 & -0.5454 & 0.294019 \tabularnewline
8 & 0.123916 & 0.8495 & 0.199948 \tabularnewline
9 & -0.03081 & -0.2112 & 0.416813 \tabularnewline
10 & -0.175113 & -1.2005 & 0.117978 \tabularnewline
11 & 0.326178 & 2.2362 & 0.015063 \tabularnewline
12 & -0.251841 & -1.7265 & 0.04541 \tabularnewline
13 & -0.078854 & -0.5406 & 0.295669 \tabularnewline
14 & 0.027356 & 0.1875 & 0.426021 \tabularnewline
15 & 0.117317 & 0.8043 & 0.212641 \tabularnewline
16 & 0.083325 & 0.5712 & 0.285276 \tabularnewline
17 & -0.095659 & -0.6558 & 0.257573 \tabularnewline
18 & -0.193702 & -1.328 & 0.095303 \tabularnewline
19 & -0.120242 & -0.8243 & 0.206956 \tabularnewline
20 & -0.067125 & -0.4602 & 0.323752 \tabularnewline
21 & -0.050048 & -0.3431 & 0.366522 \tabularnewline
22 & -0.08917 & -0.6113 & 0.271966 \tabularnewline
23 & 0.035243 & 0.2416 & 0.405064 \tabularnewline
24 & 0.055849 & 0.3829 & 0.351766 \tabularnewline
25 & -0.11003 & -0.7543 & 0.227209 \tabularnewline
26 & -0.03698 & -0.2535 & 0.400487 \tabularnewline
27 & -0.099226 & -0.6803 & 0.249839 \tabularnewline
28 & -0.049537 & -0.3396 & 0.367831 \tabularnewline
29 & 0.133089 & 0.9124 & 0.183105 \tabularnewline
30 & -0.05235 & -0.3589 & 0.360642 \tabularnewline
31 & 0.094512 & 0.6479 & 0.260087 \tabularnewline
32 & -0.00059 & -0.004 & 0.498395 \tabularnewline
33 & -0.013035 & -0.0894 & 0.464587 \tabularnewline
34 & 0.038116 & 0.2613 & 0.397499 \tabularnewline
35 & 0.007699 & 0.0528 & 0.479065 \tabularnewline
36 & 0.057434 & 0.3937 & 0.347773 \tabularnewline
37 & -0.078887 & -0.5408 & 0.295591 \tabularnewline
38 & 0.035818 & 0.2456 & 0.403547 \tabularnewline
39 & -0.038318 & -0.2627 & 0.396966 \tabularnewline
40 & -0.087697 & -0.6012 & 0.275292 \tabularnewline
41 & -0.004918 & -0.0337 & 0.486622 \tabularnewline
42 & -0.041886 & -0.2872 & 0.387628 \tabularnewline
43 & 0.052575 & 0.3604 & 0.360069 \tabularnewline
44 & 0.034755 & 0.2383 & 0.406355 \tabularnewline
45 & -0.090845 & -0.6228 & 0.268212 \tabularnewline
46 & -0.115518 & -0.7919 & 0.216185 \tabularnewline
47 & NA & NA & NA \tabularnewline
48 & NA & NA & NA \tabularnewline
49 & NA & NA & NA \tabularnewline
50 & NA & NA & NA \tabularnewline
51 & NA & NA & NA \tabularnewline
52 & NA & NA & NA \tabularnewline
53 & NA & NA & NA \tabularnewline
54 & NA & NA & NA \tabularnewline
55 & NA & NA & NA \tabularnewline
56 & NA & NA & NA \tabularnewline
57 & NA & NA & NA \tabularnewline
58 & NA & NA & NA \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70109&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]0.134566[/C][C]0.9225[/C][C]0.180481[/C][/ROW]
[ROW][C]2[/C][C]0.235067[/C][C]1.6115[/C][C]0.056879[/C][/ROW]
[ROW][C]3[/C][C]0.304451[/C][C]2.0872[/C][C]0.021159[/C][/ROW]
[ROW][C]4[/C][C]0.151903[/C][C]1.0414[/C][C]0.15151[/C][/ROW]
[ROW][C]5[/C][C]-0.091334[/C][C]-0.6262[/C][C]0.267123[/C][/ROW]
[ROW][C]6[/C][C]0.015999[/C][C]0.1097[/C][C]0.456563[/C][/ROW]
[ROW][C]7[/C][C]-0.079559[/C][C]-0.5454[/C][C]0.294019[/C][/ROW]
[ROW][C]8[/C][C]0.123916[/C][C]0.8495[/C][C]0.199948[/C][/ROW]
[ROW][C]9[/C][C]-0.03081[/C][C]-0.2112[/C][C]0.416813[/C][/ROW]
[ROW][C]10[/C][C]-0.175113[/C][C]-1.2005[/C][C]0.117978[/C][/ROW]
[ROW][C]11[/C][C]0.326178[/C][C]2.2362[/C][C]0.015063[/C][/ROW]
[ROW][C]12[/C][C]-0.251841[/C][C]-1.7265[/C][C]0.04541[/C][/ROW]
[ROW][C]13[/C][C]-0.078854[/C][C]-0.5406[/C][C]0.295669[/C][/ROW]
[ROW][C]14[/C][C]0.027356[/C][C]0.1875[/C][C]0.426021[/C][/ROW]
[ROW][C]15[/C][C]0.117317[/C][C]0.8043[/C][C]0.212641[/C][/ROW]
[ROW][C]16[/C][C]0.083325[/C][C]0.5712[/C][C]0.285276[/C][/ROW]
[ROW][C]17[/C][C]-0.095659[/C][C]-0.6558[/C][C]0.257573[/C][/ROW]
[ROW][C]18[/C][C]-0.193702[/C][C]-1.328[/C][C]0.095303[/C][/ROW]
[ROW][C]19[/C][C]-0.120242[/C][C]-0.8243[/C][C]0.206956[/C][/ROW]
[ROW][C]20[/C][C]-0.067125[/C][C]-0.4602[/C][C]0.323752[/C][/ROW]
[ROW][C]21[/C][C]-0.050048[/C][C]-0.3431[/C][C]0.366522[/C][/ROW]
[ROW][C]22[/C][C]-0.08917[/C][C]-0.6113[/C][C]0.271966[/C][/ROW]
[ROW][C]23[/C][C]0.035243[/C][C]0.2416[/C][C]0.405064[/C][/ROW]
[ROW][C]24[/C][C]0.055849[/C][C]0.3829[/C][C]0.351766[/C][/ROW]
[ROW][C]25[/C][C]-0.11003[/C][C]-0.7543[/C][C]0.227209[/C][/ROW]
[ROW][C]26[/C][C]-0.03698[/C][C]-0.2535[/C][C]0.400487[/C][/ROW]
[ROW][C]27[/C][C]-0.099226[/C][C]-0.6803[/C][C]0.249839[/C][/ROW]
[ROW][C]28[/C][C]-0.049537[/C][C]-0.3396[/C][C]0.367831[/C][/ROW]
[ROW][C]29[/C][C]0.133089[/C][C]0.9124[/C][C]0.183105[/C][/ROW]
[ROW][C]30[/C][C]-0.05235[/C][C]-0.3589[/C][C]0.360642[/C][/ROW]
[ROW][C]31[/C][C]0.094512[/C][C]0.6479[/C][C]0.260087[/C][/ROW]
[ROW][C]32[/C][C]-0.00059[/C][C]-0.004[/C][C]0.498395[/C][/ROW]
[ROW][C]33[/C][C]-0.013035[/C][C]-0.0894[/C][C]0.464587[/C][/ROW]
[ROW][C]34[/C][C]0.038116[/C][C]0.2613[/C][C]0.397499[/C][/ROW]
[ROW][C]35[/C][C]0.007699[/C][C]0.0528[/C][C]0.479065[/C][/ROW]
[ROW][C]36[/C][C]0.057434[/C][C]0.3937[/C][C]0.347773[/C][/ROW]
[ROW][C]37[/C][C]-0.078887[/C][C]-0.5408[/C][C]0.295591[/C][/ROW]
[ROW][C]38[/C][C]0.035818[/C][C]0.2456[/C][C]0.403547[/C][/ROW]
[ROW][C]39[/C][C]-0.038318[/C][C]-0.2627[/C][C]0.396966[/C][/ROW]
[ROW][C]40[/C][C]-0.087697[/C][C]-0.6012[/C][C]0.275292[/C][/ROW]
[ROW][C]41[/C][C]-0.004918[/C][C]-0.0337[/C][C]0.486622[/C][/ROW]
[ROW][C]42[/C][C]-0.041886[/C][C]-0.2872[/C][C]0.387628[/C][/ROW]
[ROW][C]43[/C][C]0.052575[/C][C]0.3604[/C][C]0.360069[/C][/ROW]
[ROW][C]44[/C][C]0.034755[/C][C]0.2383[/C][C]0.406355[/C][/ROW]
[ROW][C]45[/C][C]-0.090845[/C][C]-0.6228[/C][C]0.268212[/C][/ROW]
[ROW][C]46[/C][C]-0.115518[/C][C]-0.7919[/C][C]0.216185[/C][/ROW]
[ROW][C]47[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]48[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]NA[/C][C]NA[/C][C]NA[/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=70109&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70109&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
10.1345660.92250.180481
20.2350671.61150.056879
30.3044512.08720.021159
40.1519031.04140.15151
5-0.091334-0.62620.267123
60.0159990.10970.456563
7-0.079559-0.54540.294019
80.1239160.84950.199948
9-0.03081-0.21120.416813
10-0.175113-1.20050.117978
110.3261782.23620.015063
12-0.251841-1.72650.04541
13-0.078854-0.54060.295669
140.0273560.18750.426021
150.1173170.80430.212641
160.0833250.57120.285276
17-0.095659-0.65580.257573
18-0.193702-1.3280.095303
19-0.120242-0.82430.206956
20-0.067125-0.46020.323752
21-0.050048-0.34310.366522
22-0.08917-0.61130.271966
230.0352430.24160.405064
240.0558490.38290.351766
25-0.11003-0.75430.227209
26-0.03698-0.25350.400487
27-0.099226-0.68030.249839
28-0.049537-0.33960.367831
290.1330890.91240.183105
30-0.05235-0.35890.360642
310.0945120.64790.260087
32-0.00059-0.0040.498395
33-0.013035-0.08940.464587
340.0381160.26130.397499
350.0076990.05280.479065
360.0574340.39370.347773
37-0.078887-0.54080.295591
380.0358180.24560.403547
39-0.038318-0.26270.396966
40-0.087697-0.60120.275292
41-0.004918-0.03370.486622
42-0.041886-0.28720.387628
430.0525750.36040.360069
440.0347550.23830.406355
45-0.090845-0.62280.268212
46-0.115518-0.79190.216185
47NANANA
48NANANA
49NANANA
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



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