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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, 28 Dec 2009 13:01:50 -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/28/t1262030584vcsdqu5jwpoauxj.htm/, Retrieved Sun, 05 May 2024 15:46:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71049, Retrieved Sun, 05 May 2024 15:46:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact124
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [VRM Olie] [2008-12-19 13:50:37] [7458e879e85b911182071700fff19fbd]
- RM D  [Variance Reduction Matrix] [] [2009-12-28 18:04:03] [a171cf7519360d15de770637ace99f7a]
- RM D      [(Partial) Autocorrelation Function] [] [2009-12-28 20:01:50] [8dc3430f82ac55eb052bda9ec3452bd3] [Current]
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Dataseries X:
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27
2513.17
2466.92




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71049&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]4 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=71049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71049&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.9665437.48680
20.9215137.1380
30.8724216.75770
40.8103996.27730
50.7328935.6770
60.6425114.97693e-06
70.5545574.29563.2e-05
80.465283.6040.000319
90.3661232.8360.00311
100.2688472.08250.020785
110.1810441.40240.082981
120.0876050.67860.250004
13-0.001051-0.00810.496766
14-0.082668-0.64030.262195
15-0.149292-1.15640.126049
16-0.210744-1.63240.053915
17-0.274793-2.12850.018704
18-0.324712-2.51520.007296
19-0.363288-2.8140.003303
20-0.400261-3.10040.001471
21-0.435169-3.37080.000658
22-0.460573-3.56760.000358
23-0.474081-3.67220.000257
24-0.474544-3.67580.000254
25-0.469263-3.63490.000289
26-0.452875-3.5080.000431
27-0.433243-3.35590.000688
28-0.415587-3.21910.001038
29-0.391022-3.02880.001809
30-0.362813-2.81030.003337
31-0.33219-2.57310.006284
32-0.300695-2.32920.011618
33-0.276362-2.14070.018186
34-0.246505-1.90940.030497
35-0.212507-1.64610.052489
36-0.179565-1.39090.084696
37-0.146368-1.13380.130702
38-0.116667-0.90370.184885
39-0.090038-0.69740.244114
40-0.063634-0.49290.311939
41-0.036695-0.28420.388602
42-0.013608-0.10540.458201
430.0105720.08190.467503
440.0310720.24070.405311
450.052570.40720.342652
460.0710450.55030.292073
470.078570.60860.272543
480.0808730.62640.266702
490.0788560.61080.271814
500.0754250.58420.280623
510.069780.54050.295422
520.0617070.4780.317199
530.0536110.41530.339713
540.0460180.35650.361376
550.0366960.28420.388601
560.0282830.21910.413667
570.0215180.16670.434092
580.015750.1220.451653
590.0087280.06760.473162
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.966543 & 7.4868 & 0 \tabularnewline
2 & 0.921513 & 7.138 & 0 \tabularnewline
3 & 0.872421 & 6.7577 & 0 \tabularnewline
4 & 0.810399 & 6.2773 & 0 \tabularnewline
5 & 0.732893 & 5.677 & 0 \tabularnewline
6 & 0.642511 & 4.9769 & 3e-06 \tabularnewline
7 & 0.554557 & 4.2956 & 3.2e-05 \tabularnewline
8 & 0.46528 & 3.604 & 0.000319 \tabularnewline
9 & 0.366123 & 2.836 & 0.00311 \tabularnewline
10 & 0.268847 & 2.0825 & 0.020785 \tabularnewline
11 & 0.181044 & 1.4024 & 0.082981 \tabularnewline
12 & 0.087605 & 0.6786 & 0.250004 \tabularnewline
13 & -0.001051 & -0.0081 & 0.496766 \tabularnewline
14 & -0.082668 & -0.6403 & 0.262195 \tabularnewline
15 & -0.149292 & -1.1564 & 0.126049 \tabularnewline
16 & -0.210744 & -1.6324 & 0.053915 \tabularnewline
17 & -0.274793 & -2.1285 & 0.018704 \tabularnewline
18 & -0.324712 & -2.5152 & 0.007296 \tabularnewline
19 & -0.363288 & -2.814 & 0.003303 \tabularnewline
20 & -0.400261 & -3.1004 & 0.001471 \tabularnewline
21 & -0.435169 & -3.3708 & 0.000658 \tabularnewline
22 & -0.460573 & -3.5676 & 0.000358 \tabularnewline
23 & -0.474081 & -3.6722 & 0.000257 \tabularnewline
24 & -0.474544 & -3.6758 & 0.000254 \tabularnewline
25 & -0.469263 & -3.6349 & 0.000289 \tabularnewline
26 & -0.452875 & -3.508 & 0.000431 \tabularnewline
27 & -0.433243 & -3.3559 & 0.000688 \tabularnewline
28 & -0.415587 & -3.2191 & 0.001038 \tabularnewline
29 & -0.391022 & -3.0288 & 0.001809 \tabularnewline
30 & -0.362813 & -2.8103 & 0.003337 \tabularnewline
31 & -0.33219 & -2.5731 & 0.006284 \tabularnewline
32 & -0.300695 & -2.3292 & 0.011618 \tabularnewline
33 & -0.276362 & -2.1407 & 0.018186 \tabularnewline
34 & -0.246505 & -1.9094 & 0.030497 \tabularnewline
35 & -0.212507 & -1.6461 & 0.052489 \tabularnewline
36 & -0.179565 & -1.3909 & 0.084696 \tabularnewline
37 & -0.146368 & -1.1338 & 0.130702 \tabularnewline
38 & -0.116667 & -0.9037 & 0.184885 \tabularnewline
39 & -0.090038 & -0.6974 & 0.244114 \tabularnewline
40 & -0.063634 & -0.4929 & 0.311939 \tabularnewline
41 & -0.036695 & -0.2842 & 0.388602 \tabularnewline
42 & -0.013608 & -0.1054 & 0.458201 \tabularnewline
43 & 0.010572 & 0.0819 & 0.467503 \tabularnewline
44 & 0.031072 & 0.2407 & 0.405311 \tabularnewline
45 & 0.05257 & 0.4072 & 0.342652 \tabularnewline
46 & 0.071045 & 0.5503 & 0.292073 \tabularnewline
47 & 0.07857 & 0.6086 & 0.272543 \tabularnewline
48 & 0.080873 & 0.6264 & 0.266702 \tabularnewline
49 & 0.078856 & 0.6108 & 0.271814 \tabularnewline
50 & 0.075425 & 0.5842 & 0.280623 \tabularnewline
51 & 0.06978 & 0.5405 & 0.295422 \tabularnewline
52 & 0.061707 & 0.478 & 0.317199 \tabularnewline
53 & 0.053611 & 0.4153 & 0.339713 \tabularnewline
54 & 0.046018 & 0.3565 & 0.361376 \tabularnewline
55 & 0.036696 & 0.2842 & 0.388601 \tabularnewline
56 & 0.028283 & 0.2191 & 0.413667 \tabularnewline
57 & 0.021518 & 0.1667 & 0.434092 \tabularnewline
58 & 0.01575 & 0.122 & 0.451653 \tabularnewline
59 & 0.008728 & 0.0676 & 0.473162 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71049&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]0.966543[/C][C]7.4868[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.921513[/C][C]7.138[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.872421[/C][C]6.7577[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.810399[/C][C]6.2773[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.732893[/C][C]5.677[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.642511[/C][C]4.9769[/C][C]3e-06[/C][/ROW]
[ROW][C]7[/C][C]0.554557[/C][C]4.2956[/C][C]3.2e-05[/C][/ROW]
[ROW][C]8[/C][C]0.46528[/C][C]3.604[/C][C]0.000319[/C][/ROW]
[ROW][C]9[/C][C]0.366123[/C][C]2.836[/C][C]0.00311[/C][/ROW]
[ROW][C]10[/C][C]0.268847[/C][C]2.0825[/C][C]0.020785[/C][/ROW]
[ROW][C]11[/C][C]0.181044[/C][C]1.4024[/C][C]0.082981[/C][/ROW]
[ROW][C]12[/C][C]0.087605[/C][C]0.6786[/C][C]0.250004[/C][/ROW]
[ROW][C]13[/C][C]-0.001051[/C][C]-0.0081[/C][C]0.496766[/C][/ROW]
[ROW][C]14[/C][C]-0.082668[/C][C]-0.6403[/C][C]0.262195[/C][/ROW]
[ROW][C]15[/C][C]-0.149292[/C][C]-1.1564[/C][C]0.126049[/C][/ROW]
[ROW][C]16[/C][C]-0.210744[/C][C]-1.6324[/C][C]0.053915[/C][/ROW]
[ROW][C]17[/C][C]-0.274793[/C][C]-2.1285[/C][C]0.018704[/C][/ROW]
[ROW][C]18[/C][C]-0.324712[/C][C]-2.5152[/C][C]0.007296[/C][/ROW]
[ROW][C]19[/C][C]-0.363288[/C][C]-2.814[/C][C]0.003303[/C][/ROW]
[ROW][C]20[/C][C]-0.400261[/C][C]-3.1004[/C][C]0.001471[/C][/ROW]
[ROW][C]21[/C][C]-0.435169[/C][C]-3.3708[/C][C]0.000658[/C][/ROW]
[ROW][C]22[/C][C]-0.460573[/C][C]-3.5676[/C][C]0.000358[/C][/ROW]
[ROW][C]23[/C][C]-0.474081[/C][C]-3.6722[/C][C]0.000257[/C][/ROW]
[ROW][C]24[/C][C]-0.474544[/C][C]-3.6758[/C][C]0.000254[/C][/ROW]
[ROW][C]25[/C][C]-0.469263[/C][C]-3.6349[/C][C]0.000289[/C][/ROW]
[ROW][C]26[/C][C]-0.452875[/C][C]-3.508[/C][C]0.000431[/C][/ROW]
[ROW][C]27[/C][C]-0.433243[/C][C]-3.3559[/C][C]0.000688[/C][/ROW]
[ROW][C]28[/C][C]-0.415587[/C][C]-3.2191[/C][C]0.001038[/C][/ROW]
[ROW][C]29[/C][C]-0.391022[/C][C]-3.0288[/C][C]0.001809[/C][/ROW]
[ROW][C]30[/C][C]-0.362813[/C][C]-2.8103[/C][C]0.003337[/C][/ROW]
[ROW][C]31[/C][C]-0.33219[/C][C]-2.5731[/C][C]0.006284[/C][/ROW]
[ROW][C]32[/C][C]-0.300695[/C][C]-2.3292[/C][C]0.011618[/C][/ROW]
[ROW][C]33[/C][C]-0.276362[/C][C]-2.1407[/C][C]0.018186[/C][/ROW]
[ROW][C]34[/C][C]-0.246505[/C][C]-1.9094[/C][C]0.030497[/C][/ROW]
[ROW][C]35[/C][C]-0.212507[/C][C]-1.6461[/C][C]0.052489[/C][/ROW]
[ROW][C]36[/C][C]-0.179565[/C][C]-1.3909[/C][C]0.084696[/C][/ROW]
[ROW][C]37[/C][C]-0.146368[/C][C]-1.1338[/C][C]0.130702[/C][/ROW]
[ROW][C]38[/C][C]-0.116667[/C][C]-0.9037[/C][C]0.184885[/C][/ROW]
[ROW][C]39[/C][C]-0.090038[/C][C]-0.6974[/C][C]0.244114[/C][/ROW]
[ROW][C]40[/C][C]-0.063634[/C][C]-0.4929[/C][C]0.311939[/C][/ROW]
[ROW][C]41[/C][C]-0.036695[/C][C]-0.2842[/C][C]0.388602[/C][/ROW]
[ROW][C]42[/C][C]-0.013608[/C][C]-0.1054[/C][C]0.458201[/C][/ROW]
[ROW][C]43[/C][C]0.010572[/C][C]0.0819[/C][C]0.467503[/C][/ROW]
[ROW][C]44[/C][C]0.031072[/C][C]0.2407[/C][C]0.405311[/C][/ROW]
[ROW][C]45[/C][C]0.05257[/C][C]0.4072[/C][C]0.342652[/C][/ROW]
[ROW][C]46[/C][C]0.071045[/C][C]0.5503[/C][C]0.292073[/C][/ROW]
[ROW][C]47[/C][C]0.07857[/C][C]0.6086[/C][C]0.272543[/C][/ROW]
[ROW][C]48[/C][C]0.080873[/C][C]0.6264[/C][C]0.266702[/C][/ROW]
[ROW][C]49[/C][C]0.078856[/C][C]0.6108[/C][C]0.271814[/C][/ROW]
[ROW][C]50[/C][C]0.075425[/C][C]0.5842[/C][C]0.280623[/C][/ROW]
[ROW][C]51[/C][C]0.06978[/C][C]0.5405[/C][C]0.295422[/C][/ROW]
[ROW][C]52[/C][C]0.061707[/C][C]0.478[/C][C]0.317199[/C][/ROW]
[ROW][C]53[/C][C]0.053611[/C][C]0.4153[/C][C]0.339713[/C][/ROW]
[ROW][C]54[/C][C]0.046018[/C][C]0.3565[/C][C]0.361376[/C][/ROW]
[ROW][C]55[/C][C]0.036696[/C][C]0.2842[/C][C]0.388601[/C][/ROW]
[ROW][C]56[/C][C]0.028283[/C][C]0.2191[/C][C]0.413667[/C][/ROW]
[ROW][C]57[/C][C]0.021518[/C][C]0.1667[/C][C]0.434092[/C][/ROW]
[ROW][C]58[/C][C]0.01575[/C][C]0.122[/C][C]0.451653[/C][/ROW]
[ROW][C]59[/C][C]0.008728[/C][C]0.0676[/C][C]0.473162[/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=71049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71049&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
10.9665437.48680
20.9215137.1380
30.8724216.75770
40.8103996.27730
50.7328935.6770
60.6425114.97693e-06
70.5545574.29563.2e-05
80.465283.6040.000319
90.3661232.8360.00311
100.2688472.08250.020785
110.1810441.40240.082981
120.0876050.67860.250004
13-0.001051-0.00810.496766
14-0.082668-0.64030.262195
15-0.149292-1.15640.126049
16-0.210744-1.63240.053915
17-0.274793-2.12850.018704
18-0.324712-2.51520.007296
19-0.363288-2.8140.003303
20-0.400261-3.10040.001471
21-0.435169-3.37080.000658
22-0.460573-3.56760.000358
23-0.474081-3.67220.000257
24-0.474544-3.67580.000254
25-0.469263-3.63490.000289
26-0.452875-3.5080.000431
27-0.433243-3.35590.000688
28-0.415587-3.21910.001038
29-0.391022-3.02880.001809
30-0.362813-2.81030.003337
31-0.33219-2.57310.006284
32-0.300695-2.32920.011618
33-0.276362-2.14070.018186
34-0.246505-1.90940.030497
35-0.212507-1.64610.052489
36-0.179565-1.39090.084696
37-0.146368-1.13380.130702
38-0.116667-0.90370.184885
39-0.090038-0.69740.244114
40-0.063634-0.49290.311939
41-0.036695-0.28420.388602
42-0.013608-0.10540.458201
430.0105720.08190.467503
440.0310720.24070.405311
450.052570.40720.342652
460.0710450.55030.292073
470.078570.60860.272543
480.0808730.62640.266702
490.0788560.61080.271814
500.0754250.58420.280623
510.069780.54050.295422
520.0617070.4780.317199
530.0536110.41530.339713
540.0460180.35650.361376
550.0366960.28420.388601
560.0282830.21910.413667
570.0215180.16670.434092
580.015750.1220.451653
590.0087280.06760.473162
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9665437.48680
2-0.192909-1.49430.070173
3-0.057238-0.44340.329548
4-0.215277-1.66750.050311
5-0.227935-1.76560.041278
6-0.205385-1.59090.058444
70.0513430.39770.346132
8-0.032222-0.24960.401878
9-0.144465-1.1190.133796
100.0164090.12710.449641
110.0692850.53670.296736
12-0.212292-1.64440.052661
130.0484490.37530.354387
14-0.005271-0.04080.483785
150.106240.82290.206904
16-0.069369-0.53730.296515
17-0.113558-0.87960.191288
180.0357720.27710.391332
19-0.043734-0.33880.367984
20-0.091104-0.70570.241557
21-0.059775-0.4630.322513
22-0.00278-0.02150.491447
230.0303960.23540.407333
240.1397141.08220.141742
250.0675670.52340.301321
260.0036260.02810.488842
27-0.146216-1.13260.130947
28-0.11423-0.88480.189893
29-0.011152-0.08640.465724
30-0.037748-0.29240.385497
310.0005570.00430.498287
320.0646110.50050.309285
33-0.169446-1.31250.097171
340.0202310.15670.437999
350.028670.22210.412503
360.0812190.62910.265829
370.0146040.11310.455156
38-0.00933-0.07230.471313
39-0.079834-0.61840.26933
40-0.046829-0.36270.359038
410.0611880.4740.318625
42-0.084819-0.6570.256845
430.056580.43830.331383
44-0.035831-0.27750.391157
45-0.014293-0.11070.456106
46-6.5e-05-5e-040.499801
47-0.142895-1.10690.136387
48-0.046259-0.35830.36068
49-0.007065-0.05470.478271
50-0.005686-0.0440.482507
510.0081580.06320.474913
520.0195730.15160.440002
530.0573980.44460.329103
54-0.029033-0.22490.411416
55-0.007903-0.06120.475695
56-0.09483-0.73450.232738
570.0189320.14660.441952
580.0665490.51550.304053
59-0.000732-0.00570.497747
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.966543 & 7.4868 & 0 \tabularnewline
2 & -0.192909 & -1.4943 & 0.070173 \tabularnewline
3 & -0.057238 & -0.4434 & 0.329548 \tabularnewline
4 & -0.215277 & -1.6675 & 0.050311 \tabularnewline
5 & -0.227935 & -1.7656 & 0.041278 \tabularnewline
6 & -0.205385 & -1.5909 & 0.058444 \tabularnewline
7 & 0.051343 & 0.3977 & 0.346132 \tabularnewline
8 & -0.032222 & -0.2496 & 0.401878 \tabularnewline
9 & -0.144465 & -1.119 & 0.133796 \tabularnewline
10 & 0.016409 & 0.1271 & 0.449641 \tabularnewline
11 & 0.069285 & 0.5367 & 0.296736 \tabularnewline
12 & -0.212292 & -1.6444 & 0.052661 \tabularnewline
13 & 0.048449 & 0.3753 & 0.354387 \tabularnewline
14 & -0.005271 & -0.0408 & 0.483785 \tabularnewline
15 & 0.10624 & 0.8229 & 0.206904 \tabularnewline
16 & -0.069369 & -0.5373 & 0.296515 \tabularnewline
17 & -0.113558 & -0.8796 & 0.191288 \tabularnewline
18 & 0.035772 & 0.2771 & 0.391332 \tabularnewline
19 & -0.043734 & -0.3388 & 0.367984 \tabularnewline
20 & -0.091104 & -0.7057 & 0.241557 \tabularnewline
21 & -0.059775 & -0.463 & 0.322513 \tabularnewline
22 & -0.00278 & -0.0215 & 0.491447 \tabularnewline
23 & 0.030396 & 0.2354 & 0.407333 \tabularnewline
24 & 0.139714 & 1.0822 & 0.141742 \tabularnewline
25 & 0.067567 & 0.5234 & 0.301321 \tabularnewline
26 & 0.003626 & 0.0281 & 0.488842 \tabularnewline
27 & -0.146216 & -1.1326 & 0.130947 \tabularnewline
28 & -0.11423 & -0.8848 & 0.189893 \tabularnewline
29 & -0.011152 & -0.0864 & 0.465724 \tabularnewline
30 & -0.037748 & -0.2924 & 0.385497 \tabularnewline
31 & 0.000557 & 0.0043 & 0.498287 \tabularnewline
32 & 0.064611 & 0.5005 & 0.309285 \tabularnewline
33 & -0.169446 & -1.3125 & 0.097171 \tabularnewline
34 & 0.020231 & 0.1567 & 0.437999 \tabularnewline
35 & 0.02867 & 0.2221 & 0.412503 \tabularnewline
36 & 0.081219 & 0.6291 & 0.265829 \tabularnewline
37 & 0.014604 & 0.1131 & 0.455156 \tabularnewline
38 & -0.00933 & -0.0723 & 0.471313 \tabularnewline
39 & -0.079834 & -0.6184 & 0.26933 \tabularnewline
40 & -0.046829 & -0.3627 & 0.359038 \tabularnewline
41 & 0.061188 & 0.474 & 0.318625 \tabularnewline
42 & -0.084819 & -0.657 & 0.256845 \tabularnewline
43 & 0.05658 & 0.4383 & 0.331383 \tabularnewline
44 & -0.035831 & -0.2775 & 0.391157 \tabularnewline
45 & -0.014293 & -0.1107 & 0.456106 \tabularnewline
46 & -6.5e-05 & -5e-04 & 0.499801 \tabularnewline
47 & -0.142895 & -1.1069 & 0.136387 \tabularnewline
48 & -0.046259 & -0.3583 & 0.36068 \tabularnewline
49 & -0.007065 & -0.0547 & 0.478271 \tabularnewline
50 & -0.005686 & -0.044 & 0.482507 \tabularnewline
51 & 0.008158 & 0.0632 & 0.474913 \tabularnewline
52 & 0.019573 & 0.1516 & 0.440002 \tabularnewline
53 & 0.057398 & 0.4446 & 0.329103 \tabularnewline
54 & -0.029033 & -0.2249 & 0.411416 \tabularnewline
55 & -0.007903 & -0.0612 & 0.475695 \tabularnewline
56 & -0.09483 & -0.7345 & 0.232738 \tabularnewline
57 & 0.018932 & 0.1466 & 0.441952 \tabularnewline
58 & 0.066549 & 0.5155 & 0.304053 \tabularnewline
59 & -0.000732 & -0.0057 & 0.497747 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71049&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]0.966543[/C][C]7.4868[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.192909[/C][C]-1.4943[/C][C]0.070173[/C][/ROW]
[ROW][C]3[/C][C]-0.057238[/C][C]-0.4434[/C][C]0.329548[/C][/ROW]
[ROW][C]4[/C][C]-0.215277[/C][C]-1.6675[/C][C]0.050311[/C][/ROW]
[ROW][C]5[/C][C]-0.227935[/C][C]-1.7656[/C][C]0.041278[/C][/ROW]
[ROW][C]6[/C][C]-0.205385[/C][C]-1.5909[/C][C]0.058444[/C][/ROW]
[ROW][C]7[/C][C]0.051343[/C][C]0.3977[/C][C]0.346132[/C][/ROW]
[ROW][C]8[/C][C]-0.032222[/C][C]-0.2496[/C][C]0.401878[/C][/ROW]
[ROW][C]9[/C][C]-0.144465[/C][C]-1.119[/C][C]0.133796[/C][/ROW]
[ROW][C]10[/C][C]0.016409[/C][C]0.1271[/C][C]0.449641[/C][/ROW]
[ROW][C]11[/C][C]0.069285[/C][C]0.5367[/C][C]0.296736[/C][/ROW]
[ROW][C]12[/C][C]-0.212292[/C][C]-1.6444[/C][C]0.052661[/C][/ROW]
[ROW][C]13[/C][C]0.048449[/C][C]0.3753[/C][C]0.354387[/C][/ROW]
[ROW][C]14[/C][C]-0.005271[/C][C]-0.0408[/C][C]0.483785[/C][/ROW]
[ROW][C]15[/C][C]0.10624[/C][C]0.8229[/C][C]0.206904[/C][/ROW]
[ROW][C]16[/C][C]-0.069369[/C][C]-0.5373[/C][C]0.296515[/C][/ROW]
[ROW][C]17[/C][C]-0.113558[/C][C]-0.8796[/C][C]0.191288[/C][/ROW]
[ROW][C]18[/C][C]0.035772[/C][C]0.2771[/C][C]0.391332[/C][/ROW]
[ROW][C]19[/C][C]-0.043734[/C][C]-0.3388[/C][C]0.367984[/C][/ROW]
[ROW][C]20[/C][C]-0.091104[/C][C]-0.7057[/C][C]0.241557[/C][/ROW]
[ROW][C]21[/C][C]-0.059775[/C][C]-0.463[/C][C]0.322513[/C][/ROW]
[ROW][C]22[/C][C]-0.00278[/C][C]-0.0215[/C][C]0.491447[/C][/ROW]
[ROW][C]23[/C][C]0.030396[/C][C]0.2354[/C][C]0.407333[/C][/ROW]
[ROW][C]24[/C][C]0.139714[/C][C]1.0822[/C][C]0.141742[/C][/ROW]
[ROW][C]25[/C][C]0.067567[/C][C]0.5234[/C][C]0.301321[/C][/ROW]
[ROW][C]26[/C][C]0.003626[/C][C]0.0281[/C][C]0.488842[/C][/ROW]
[ROW][C]27[/C][C]-0.146216[/C][C]-1.1326[/C][C]0.130947[/C][/ROW]
[ROW][C]28[/C][C]-0.11423[/C][C]-0.8848[/C][C]0.189893[/C][/ROW]
[ROW][C]29[/C][C]-0.011152[/C][C]-0.0864[/C][C]0.465724[/C][/ROW]
[ROW][C]30[/C][C]-0.037748[/C][C]-0.2924[/C][C]0.385497[/C][/ROW]
[ROW][C]31[/C][C]0.000557[/C][C]0.0043[/C][C]0.498287[/C][/ROW]
[ROW][C]32[/C][C]0.064611[/C][C]0.5005[/C][C]0.309285[/C][/ROW]
[ROW][C]33[/C][C]-0.169446[/C][C]-1.3125[/C][C]0.097171[/C][/ROW]
[ROW][C]34[/C][C]0.020231[/C][C]0.1567[/C][C]0.437999[/C][/ROW]
[ROW][C]35[/C][C]0.02867[/C][C]0.2221[/C][C]0.412503[/C][/ROW]
[ROW][C]36[/C][C]0.081219[/C][C]0.6291[/C][C]0.265829[/C][/ROW]
[ROW][C]37[/C][C]0.014604[/C][C]0.1131[/C][C]0.455156[/C][/ROW]
[ROW][C]38[/C][C]-0.00933[/C][C]-0.0723[/C][C]0.471313[/C][/ROW]
[ROW][C]39[/C][C]-0.079834[/C][C]-0.6184[/C][C]0.26933[/C][/ROW]
[ROW][C]40[/C][C]-0.046829[/C][C]-0.3627[/C][C]0.359038[/C][/ROW]
[ROW][C]41[/C][C]0.061188[/C][C]0.474[/C][C]0.318625[/C][/ROW]
[ROW][C]42[/C][C]-0.084819[/C][C]-0.657[/C][C]0.256845[/C][/ROW]
[ROW][C]43[/C][C]0.05658[/C][C]0.4383[/C][C]0.331383[/C][/ROW]
[ROW][C]44[/C][C]-0.035831[/C][C]-0.2775[/C][C]0.391157[/C][/ROW]
[ROW][C]45[/C][C]-0.014293[/C][C]-0.1107[/C][C]0.456106[/C][/ROW]
[ROW][C]46[/C][C]-6.5e-05[/C][C]-5e-04[/C][C]0.499801[/C][/ROW]
[ROW][C]47[/C][C]-0.142895[/C][C]-1.1069[/C][C]0.136387[/C][/ROW]
[ROW][C]48[/C][C]-0.046259[/C][C]-0.3583[/C][C]0.36068[/C][/ROW]
[ROW][C]49[/C][C]-0.007065[/C][C]-0.0547[/C][C]0.478271[/C][/ROW]
[ROW][C]50[/C][C]-0.005686[/C][C]-0.044[/C][C]0.482507[/C][/ROW]
[ROW][C]51[/C][C]0.008158[/C][C]0.0632[/C][C]0.474913[/C][/ROW]
[ROW][C]52[/C][C]0.019573[/C][C]0.1516[/C][C]0.440002[/C][/ROW]
[ROW][C]53[/C][C]0.057398[/C][C]0.4446[/C][C]0.329103[/C][/ROW]
[ROW][C]54[/C][C]-0.029033[/C][C]-0.2249[/C][C]0.411416[/C][/ROW]
[ROW][C]55[/C][C]-0.007903[/C][C]-0.0612[/C][C]0.475695[/C][/ROW]
[ROW][C]56[/C][C]-0.09483[/C][C]-0.7345[/C][C]0.232738[/C][/ROW]
[ROW][C]57[/C][C]0.018932[/C][C]0.1466[/C][C]0.441952[/C][/ROW]
[ROW][C]58[/C][C]0.066549[/C][C]0.5155[/C][C]0.304053[/C][/ROW]
[ROW][C]59[/C][C]-0.000732[/C][C]-0.0057[/C][C]0.497747[/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=71049&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71049&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
10.9665437.48680
2-0.192909-1.49430.070173
3-0.057238-0.44340.329548
4-0.215277-1.66750.050311
5-0.227935-1.76560.041278
6-0.205385-1.59090.058444
70.0513430.39770.346132
8-0.032222-0.24960.401878
9-0.144465-1.1190.133796
100.0164090.12710.449641
110.0692850.53670.296736
12-0.212292-1.64440.052661
130.0484490.37530.354387
14-0.005271-0.04080.483785
150.106240.82290.206904
16-0.069369-0.53730.296515
17-0.113558-0.87960.191288
180.0357720.27710.391332
19-0.043734-0.33880.367984
20-0.091104-0.70570.241557
21-0.059775-0.4630.322513
22-0.00278-0.02150.491447
230.0303960.23540.407333
240.1397141.08220.141742
250.0675670.52340.301321
260.0036260.02810.488842
27-0.146216-1.13260.130947
28-0.11423-0.88480.189893
29-0.011152-0.08640.465724
30-0.037748-0.29240.385497
310.0005570.00430.498287
320.0646110.50050.309285
33-0.169446-1.31250.097171
340.0202310.15670.437999
350.028670.22210.412503
360.0812190.62910.265829
370.0146040.11310.455156
38-0.00933-0.07230.471313
39-0.079834-0.61840.26933
40-0.046829-0.36270.359038
410.0611880.4740.318625
42-0.084819-0.6570.256845
430.056580.43830.331383
44-0.035831-0.27750.391157
45-0.014293-0.11070.456106
46-6.5e-05-5e-040.499801
47-0.142895-1.10690.136387
48-0.046259-0.35830.36068
49-0.007065-0.05470.478271
50-0.005686-0.0440.482507
510.0081580.06320.474913
520.0195730.15160.440002
530.0573980.44460.329103
54-0.029033-0.22490.411416
55-0.007903-0.06120.475695
56-0.09483-0.73450.232738
570.0189320.14660.441952
580.0665490.51550.304053
59-0.000732-0.00570.497747
60NANANA



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 0.9 ; 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')