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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 computationFri, 04 Dec 2009 13:05:29 -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/04/t1259957195523zgmkr7px9zkc.htm/, Retrieved Sun, 28 Apr 2024 17:36:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64119, Retrieved Sun, 28 Apr 2024 17:36:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78
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] [] [2009-11-27 14:46:03] [b98453cac15ba1066b407e146608df68]
- R PD      [(Partial) Autocorrelation Function] [ACF & PACF] [2009-12-04 20:05:29] [fe2edc5b0acc9545190e03904e9be55e] [Current]
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Dataseries X:
3.58
3.52
3.45
3.36
3.27
3.21
3.19
3.16
3.12
3.06
3.01
2.98
2.97
3.02
3.07
3.18
3.29
3.43
3.61
3.74
3.87
3.88
4.09
4.19
4.2
4.29
4.37
4.47
4.61
4.65
4.69
4.82
4.86
4.87
5.01
5.03
5.13
5.18
5.21
5.26
5.25
5.2
5.16
5.19
5.39
5.58
5.76
5.89
5.98
6.02
5.62
4.87
4.24
4.02
3.74
3.45
3.34
3.21
3.12
3.04




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=64119&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=64119&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64119&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
10.9663437.48530
20.906397.02090
30.8291136.42230
40.7405845.73650
50.6453294.99873e-06
60.5524544.27933.4e-05
70.4661083.61050.000313
80.3859212.98930.002024
90.31972.47640.008055
100.2685742.08040.020885
110.2253241.74530.043022
120.1807811.40030.083283
130.1341971.03950.151376
140.0860740.66670.253752
150.0356040.27580.39183
16-0.015961-0.12360.45101
17-0.068925-0.53390.297695
18-0.119178-0.92320.179813
19-0.164529-1.27440.103712
20-0.205148-1.58910.05865
21-0.240866-1.86570.033484
22-0.274633-2.12730.018758
23-0.304022-2.35490.010907
24-0.329071-2.5490.00669
25-0.351614-2.72360.004223
26-0.369648-2.86330.002884
27-0.386763-2.99590.001987
28-0.400058-3.09880.001478
29-0.40886-3.1670.001211
30-0.415567-3.2190.001039
31-0.41853-3.24190.00097
32-0.416612-3.22710.001014
33-0.410765-3.18180.001159
34-0.399549-3.09490.001495
35-0.380989-2.95110.002256
36-0.356527-2.76160.00381
37-0.324095-2.51040.007386
38-0.287143-2.22420.014955
39-0.249978-1.93630.028772
40-0.20912-1.61980.055256
41-0.169251-1.3110.097424
42-0.131844-1.02130.155616
43-0.098608-0.76380.223985
44-0.068325-0.52920.299296
45-0.038616-0.29910.382942
46-0.010278-0.07960.468405
470.0168490.13050.448298
480.0411040.31840.375646
490.0629140.48730.313901
500.0821850.63660.263403
510.0947120.73360.233014
520.0974850.75510.226568
530.0922080.71420.238924
540.0837630.64880.259464
550.0715270.5540.290803
560.0566180.43860.331278
570.0419910.32530.373057
580.0276070.21380.415697
590.0136140.10550.458184
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.966343 & 7.4853 & 0 \tabularnewline
2 & 0.90639 & 7.0209 & 0 \tabularnewline
3 & 0.829113 & 6.4223 & 0 \tabularnewline
4 & 0.740584 & 5.7365 & 0 \tabularnewline
5 & 0.645329 & 4.9987 & 3e-06 \tabularnewline
6 & 0.552454 & 4.2793 & 3.4e-05 \tabularnewline
7 & 0.466108 & 3.6105 & 0.000313 \tabularnewline
8 & 0.385921 & 2.9893 & 0.002024 \tabularnewline
9 & 0.3197 & 2.4764 & 0.008055 \tabularnewline
10 & 0.268574 & 2.0804 & 0.020885 \tabularnewline
11 & 0.225324 & 1.7453 & 0.043022 \tabularnewline
12 & 0.180781 & 1.4003 & 0.083283 \tabularnewline
13 & 0.134197 & 1.0395 & 0.151376 \tabularnewline
14 & 0.086074 & 0.6667 & 0.253752 \tabularnewline
15 & 0.035604 & 0.2758 & 0.39183 \tabularnewline
16 & -0.015961 & -0.1236 & 0.45101 \tabularnewline
17 & -0.068925 & -0.5339 & 0.297695 \tabularnewline
18 & -0.119178 & -0.9232 & 0.179813 \tabularnewline
19 & -0.164529 & -1.2744 & 0.103712 \tabularnewline
20 & -0.205148 & -1.5891 & 0.05865 \tabularnewline
21 & -0.240866 & -1.8657 & 0.033484 \tabularnewline
22 & -0.274633 & -2.1273 & 0.018758 \tabularnewline
23 & -0.304022 & -2.3549 & 0.010907 \tabularnewline
24 & -0.329071 & -2.549 & 0.00669 \tabularnewline
25 & -0.351614 & -2.7236 & 0.004223 \tabularnewline
26 & -0.369648 & -2.8633 & 0.002884 \tabularnewline
27 & -0.386763 & -2.9959 & 0.001987 \tabularnewline
28 & -0.400058 & -3.0988 & 0.001478 \tabularnewline
29 & -0.40886 & -3.167 & 0.001211 \tabularnewline
30 & -0.415567 & -3.219 & 0.001039 \tabularnewline
31 & -0.41853 & -3.2419 & 0.00097 \tabularnewline
32 & -0.416612 & -3.2271 & 0.001014 \tabularnewline
33 & -0.410765 & -3.1818 & 0.001159 \tabularnewline
34 & -0.399549 & -3.0949 & 0.001495 \tabularnewline
35 & -0.380989 & -2.9511 & 0.002256 \tabularnewline
36 & -0.356527 & -2.7616 & 0.00381 \tabularnewline
37 & -0.324095 & -2.5104 & 0.007386 \tabularnewline
38 & -0.287143 & -2.2242 & 0.014955 \tabularnewline
39 & -0.249978 & -1.9363 & 0.028772 \tabularnewline
40 & -0.20912 & -1.6198 & 0.055256 \tabularnewline
41 & -0.169251 & -1.311 & 0.097424 \tabularnewline
42 & -0.131844 & -1.0213 & 0.155616 \tabularnewline
43 & -0.098608 & -0.7638 & 0.223985 \tabularnewline
44 & -0.068325 & -0.5292 & 0.299296 \tabularnewline
45 & -0.038616 & -0.2991 & 0.382942 \tabularnewline
46 & -0.010278 & -0.0796 & 0.468405 \tabularnewline
47 & 0.016849 & 0.1305 & 0.448298 \tabularnewline
48 & 0.041104 & 0.3184 & 0.375646 \tabularnewline
49 & 0.062914 & 0.4873 & 0.313901 \tabularnewline
50 & 0.082185 & 0.6366 & 0.263403 \tabularnewline
51 & 0.094712 & 0.7336 & 0.233014 \tabularnewline
52 & 0.097485 & 0.7551 & 0.226568 \tabularnewline
53 & 0.092208 & 0.7142 & 0.238924 \tabularnewline
54 & 0.083763 & 0.6488 & 0.259464 \tabularnewline
55 & 0.071527 & 0.554 & 0.290803 \tabularnewline
56 & 0.056618 & 0.4386 & 0.331278 \tabularnewline
57 & 0.041991 & 0.3253 & 0.373057 \tabularnewline
58 & 0.027607 & 0.2138 & 0.415697 \tabularnewline
59 & 0.013614 & 0.1055 & 0.458184 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64119&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]0.966343[/C][C]7.4853[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.90639[/C][C]7.0209[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.829113[/C][C]6.4223[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.740584[/C][C]5.7365[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.645329[/C][C]4.9987[/C][C]3e-06[/C][/ROW]
[ROW][C]6[/C][C]0.552454[/C][C]4.2793[/C][C]3.4e-05[/C][/ROW]
[ROW][C]7[/C][C]0.466108[/C][C]3.6105[/C][C]0.000313[/C][/ROW]
[ROW][C]8[/C][C]0.385921[/C][C]2.9893[/C][C]0.002024[/C][/ROW]
[ROW][C]9[/C][C]0.3197[/C][C]2.4764[/C][C]0.008055[/C][/ROW]
[ROW][C]10[/C][C]0.268574[/C][C]2.0804[/C][C]0.020885[/C][/ROW]
[ROW][C]11[/C][C]0.225324[/C][C]1.7453[/C][C]0.043022[/C][/ROW]
[ROW][C]12[/C][C]0.180781[/C][C]1.4003[/C][C]0.083283[/C][/ROW]
[ROW][C]13[/C][C]0.134197[/C][C]1.0395[/C][C]0.151376[/C][/ROW]
[ROW][C]14[/C][C]0.086074[/C][C]0.6667[/C][C]0.253752[/C][/ROW]
[ROW][C]15[/C][C]0.035604[/C][C]0.2758[/C][C]0.39183[/C][/ROW]
[ROW][C]16[/C][C]-0.015961[/C][C]-0.1236[/C][C]0.45101[/C][/ROW]
[ROW][C]17[/C][C]-0.068925[/C][C]-0.5339[/C][C]0.297695[/C][/ROW]
[ROW][C]18[/C][C]-0.119178[/C][C]-0.9232[/C][C]0.179813[/C][/ROW]
[ROW][C]19[/C][C]-0.164529[/C][C]-1.2744[/C][C]0.103712[/C][/ROW]
[ROW][C]20[/C][C]-0.205148[/C][C]-1.5891[/C][C]0.05865[/C][/ROW]
[ROW][C]21[/C][C]-0.240866[/C][C]-1.8657[/C][C]0.033484[/C][/ROW]
[ROW][C]22[/C][C]-0.274633[/C][C]-2.1273[/C][C]0.018758[/C][/ROW]
[ROW][C]23[/C][C]-0.304022[/C][C]-2.3549[/C][C]0.010907[/C][/ROW]
[ROW][C]24[/C][C]-0.329071[/C][C]-2.549[/C][C]0.00669[/C][/ROW]
[ROW][C]25[/C][C]-0.351614[/C][C]-2.7236[/C][C]0.004223[/C][/ROW]
[ROW][C]26[/C][C]-0.369648[/C][C]-2.8633[/C][C]0.002884[/C][/ROW]
[ROW][C]27[/C][C]-0.386763[/C][C]-2.9959[/C][C]0.001987[/C][/ROW]
[ROW][C]28[/C][C]-0.400058[/C][C]-3.0988[/C][C]0.001478[/C][/ROW]
[ROW][C]29[/C][C]-0.40886[/C][C]-3.167[/C][C]0.001211[/C][/ROW]
[ROW][C]30[/C][C]-0.415567[/C][C]-3.219[/C][C]0.001039[/C][/ROW]
[ROW][C]31[/C][C]-0.41853[/C][C]-3.2419[/C][C]0.00097[/C][/ROW]
[ROW][C]32[/C][C]-0.416612[/C][C]-3.2271[/C][C]0.001014[/C][/ROW]
[ROW][C]33[/C][C]-0.410765[/C][C]-3.1818[/C][C]0.001159[/C][/ROW]
[ROW][C]34[/C][C]-0.399549[/C][C]-3.0949[/C][C]0.001495[/C][/ROW]
[ROW][C]35[/C][C]-0.380989[/C][C]-2.9511[/C][C]0.002256[/C][/ROW]
[ROW][C]36[/C][C]-0.356527[/C][C]-2.7616[/C][C]0.00381[/C][/ROW]
[ROW][C]37[/C][C]-0.324095[/C][C]-2.5104[/C][C]0.007386[/C][/ROW]
[ROW][C]38[/C][C]-0.287143[/C][C]-2.2242[/C][C]0.014955[/C][/ROW]
[ROW][C]39[/C][C]-0.249978[/C][C]-1.9363[/C][C]0.028772[/C][/ROW]
[ROW][C]40[/C][C]-0.20912[/C][C]-1.6198[/C][C]0.055256[/C][/ROW]
[ROW][C]41[/C][C]-0.169251[/C][C]-1.311[/C][C]0.097424[/C][/ROW]
[ROW][C]42[/C][C]-0.131844[/C][C]-1.0213[/C][C]0.155616[/C][/ROW]
[ROW][C]43[/C][C]-0.098608[/C][C]-0.7638[/C][C]0.223985[/C][/ROW]
[ROW][C]44[/C][C]-0.068325[/C][C]-0.5292[/C][C]0.299296[/C][/ROW]
[ROW][C]45[/C][C]-0.038616[/C][C]-0.2991[/C][C]0.382942[/C][/ROW]
[ROW][C]46[/C][C]-0.010278[/C][C]-0.0796[/C][C]0.468405[/C][/ROW]
[ROW][C]47[/C][C]0.016849[/C][C]0.1305[/C][C]0.448298[/C][/ROW]
[ROW][C]48[/C][C]0.041104[/C][C]0.3184[/C][C]0.375646[/C][/ROW]
[ROW][C]49[/C][C]0.062914[/C][C]0.4873[/C][C]0.313901[/C][/ROW]
[ROW][C]50[/C][C]0.082185[/C][C]0.6366[/C][C]0.263403[/C][/ROW]
[ROW][C]51[/C][C]0.094712[/C][C]0.7336[/C][C]0.233014[/C][/ROW]
[ROW][C]52[/C][C]0.097485[/C][C]0.7551[/C][C]0.226568[/C][/ROW]
[ROW][C]53[/C][C]0.092208[/C][C]0.7142[/C][C]0.238924[/C][/ROW]
[ROW][C]54[/C][C]0.083763[/C][C]0.6488[/C][C]0.259464[/C][/ROW]
[ROW][C]55[/C][C]0.071527[/C][C]0.554[/C][C]0.290803[/C][/ROW]
[ROW][C]56[/C][C]0.056618[/C][C]0.4386[/C][C]0.331278[/C][/ROW]
[ROW][C]57[/C][C]0.041991[/C][C]0.3253[/C][C]0.373057[/C][/ROW]
[ROW][C]58[/C][C]0.027607[/C][C]0.2138[/C][C]0.415697[/C][/ROW]
[ROW][C]59[/C][C]0.013614[/C][C]0.1055[/C][C]0.458184[/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=64119&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64119&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
10.9663437.48530
20.906397.02090
30.8291136.42230
40.7405845.73650
50.6453294.99873e-06
60.5524544.27933.4e-05
70.4661083.61050.000313
80.3859212.98930.002024
90.31972.47640.008055
100.2685742.08040.020885
110.2253241.74530.043022
120.1807811.40030.083283
130.1341971.03950.151376
140.0860740.66670.253752
150.0356040.27580.39183
16-0.015961-0.12360.45101
17-0.068925-0.53390.297695
18-0.119178-0.92320.179813
19-0.164529-1.27440.103712
20-0.205148-1.58910.05865
21-0.240866-1.86570.033484
22-0.274633-2.12730.018758
23-0.304022-2.35490.010907
24-0.329071-2.5490.00669
25-0.351614-2.72360.004223
26-0.369648-2.86330.002884
27-0.386763-2.99590.001987
28-0.400058-3.09880.001478
29-0.40886-3.1670.001211
30-0.415567-3.2190.001039
31-0.41853-3.24190.00097
32-0.416612-3.22710.001014
33-0.410765-3.18180.001159
34-0.399549-3.09490.001495
35-0.380989-2.95110.002256
36-0.356527-2.76160.00381
37-0.324095-2.51040.007386
38-0.287143-2.22420.014955
39-0.249978-1.93630.028772
40-0.20912-1.61980.055256
41-0.169251-1.3110.097424
42-0.131844-1.02130.155616
43-0.098608-0.76380.223985
44-0.068325-0.52920.299296
45-0.038616-0.29910.382942
46-0.010278-0.07960.468405
470.0168490.13050.448298
480.0411040.31840.375646
490.0629140.48730.313901
500.0821850.63660.263403
510.0947120.73360.233014
520.0974850.75510.226568
530.0922080.71420.238924
540.0837630.64880.259464
550.0715270.5540.290803
560.0566180.43860.331278
570.0419910.32530.373057
580.0276070.21380.415697
590.0136140.10550.458184
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.9663437.48530
2-0.414473-3.21050.001065
3-0.169267-1.31110.097404
4-0.09389-0.72730.234945
5-0.063509-0.49190.312279
60.0573630.44430.329202
70.033240.25750.398846
8-0.032492-0.25170.401073
90.1144430.88650.189452
100.0544820.4220.33726
11-0.094272-0.73020.234047
12-0.181183-1.40340.082821
13-0.093339-0.7230.236245
14-0.02705-0.20950.417373
15-0.014881-0.11530.454308
16-0.00662-0.05130.479637
17-0.051897-0.4020.344558
180.0350670.27160.393421
190.026940.20870.417705
20-0.069447-0.53790.296306
21-0.088014-0.68180.249008
22-0.121628-0.94210.174952
230.0030410.02360.490644
240.0163460.12660.449835
25-0.047601-0.36870.356818
260.0165460.12820.449225
27-0.062374-0.48310.315375
280.0310370.24040.405415
29-0.001672-0.01290.494856
30-0.120224-0.93120.177729
31-0.032981-0.25550.399616
320.0184110.14260.443538
330.0030820.02390.490517
340.0425420.32950.371452
350.0325340.2520.400947
360.0030520.02360.490609
370.088250.68360.248434
38-0.018694-0.14480.442674
39-0.121171-0.93860.175854
400.0439950.34080.367229
41-0.027869-0.21590.414911
42-0.006464-0.05010.480117
430.0074180.05750.477184
440.0008080.00630.497513
450.0771990.5980.276052
460.0455210.35260.362811
47-0.053922-0.41770.338836
48-0.093957-0.72780.234788
49-0.039601-0.30670.380049
50-0.008528-0.06610.473776
51-0.096372-0.74650.229142
52-0.134247-1.03990.151286
53-0.021666-0.16780.433642
540.1311491.01590.156883
550.031080.24070.405286
56-0.073319-0.56790.286102
57-0.055796-0.43220.333575
58-0.063059-0.48850.313505
59-0.01038-0.08040.468091
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.966343 & 7.4853 & 0 \tabularnewline
2 & -0.414473 & -3.2105 & 0.001065 \tabularnewline
3 & -0.169267 & -1.3111 & 0.097404 \tabularnewline
4 & -0.09389 & -0.7273 & 0.234945 \tabularnewline
5 & -0.063509 & -0.4919 & 0.312279 \tabularnewline
6 & 0.057363 & 0.4443 & 0.329202 \tabularnewline
7 & 0.03324 & 0.2575 & 0.398846 \tabularnewline
8 & -0.032492 & -0.2517 & 0.401073 \tabularnewline
9 & 0.114443 & 0.8865 & 0.189452 \tabularnewline
10 & 0.054482 & 0.422 & 0.33726 \tabularnewline
11 & -0.094272 & -0.7302 & 0.234047 \tabularnewline
12 & -0.181183 & -1.4034 & 0.082821 \tabularnewline
13 & -0.093339 & -0.723 & 0.236245 \tabularnewline
14 & -0.02705 & -0.2095 & 0.417373 \tabularnewline
15 & -0.014881 & -0.1153 & 0.454308 \tabularnewline
16 & -0.00662 & -0.0513 & 0.479637 \tabularnewline
17 & -0.051897 & -0.402 & 0.344558 \tabularnewline
18 & 0.035067 & 0.2716 & 0.393421 \tabularnewline
19 & 0.02694 & 0.2087 & 0.417705 \tabularnewline
20 & -0.069447 & -0.5379 & 0.296306 \tabularnewline
21 & -0.088014 & -0.6818 & 0.249008 \tabularnewline
22 & -0.121628 & -0.9421 & 0.174952 \tabularnewline
23 & 0.003041 & 0.0236 & 0.490644 \tabularnewline
24 & 0.016346 & 0.1266 & 0.449835 \tabularnewline
25 & -0.047601 & -0.3687 & 0.356818 \tabularnewline
26 & 0.016546 & 0.1282 & 0.449225 \tabularnewline
27 & -0.062374 & -0.4831 & 0.315375 \tabularnewline
28 & 0.031037 & 0.2404 & 0.405415 \tabularnewline
29 & -0.001672 & -0.0129 & 0.494856 \tabularnewline
30 & -0.120224 & -0.9312 & 0.177729 \tabularnewline
31 & -0.032981 & -0.2555 & 0.399616 \tabularnewline
32 & 0.018411 & 0.1426 & 0.443538 \tabularnewline
33 & 0.003082 & 0.0239 & 0.490517 \tabularnewline
34 & 0.042542 & 0.3295 & 0.371452 \tabularnewline
35 & 0.032534 & 0.252 & 0.400947 \tabularnewline
36 & 0.003052 & 0.0236 & 0.490609 \tabularnewline
37 & 0.08825 & 0.6836 & 0.248434 \tabularnewline
38 & -0.018694 & -0.1448 & 0.442674 \tabularnewline
39 & -0.121171 & -0.9386 & 0.175854 \tabularnewline
40 & 0.043995 & 0.3408 & 0.367229 \tabularnewline
41 & -0.027869 & -0.2159 & 0.414911 \tabularnewline
42 & -0.006464 & -0.0501 & 0.480117 \tabularnewline
43 & 0.007418 & 0.0575 & 0.477184 \tabularnewline
44 & 0.000808 & 0.0063 & 0.497513 \tabularnewline
45 & 0.077199 & 0.598 & 0.276052 \tabularnewline
46 & 0.045521 & 0.3526 & 0.362811 \tabularnewline
47 & -0.053922 & -0.4177 & 0.338836 \tabularnewline
48 & -0.093957 & -0.7278 & 0.234788 \tabularnewline
49 & -0.039601 & -0.3067 & 0.380049 \tabularnewline
50 & -0.008528 & -0.0661 & 0.473776 \tabularnewline
51 & -0.096372 & -0.7465 & 0.229142 \tabularnewline
52 & -0.134247 & -1.0399 & 0.151286 \tabularnewline
53 & -0.021666 & -0.1678 & 0.433642 \tabularnewline
54 & 0.131149 & 1.0159 & 0.156883 \tabularnewline
55 & 0.03108 & 0.2407 & 0.405286 \tabularnewline
56 & -0.073319 & -0.5679 & 0.286102 \tabularnewline
57 & -0.055796 & -0.4322 & 0.333575 \tabularnewline
58 & -0.063059 & -0.4885 & 0.313505 \tabularnewline
59 & -0.01038 & -0.0804 & 0.468091 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64119&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]0.966343[/C][C]7.4853[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.414473[/C][C]-3.2105[/C][C]0.001065[/C][/ROW]
[ROW][C]3[/C][C]-0.169267[/C][C]-1.3111[/C][C]0.097404[/C][/ROW]
[ROW][C]4[/C][C]-0.09389[/C][C]-0.7273[/C][C]0.234945[/C][/ROW]
[ROW][C]5[/C][C]-0.063509[/C][C]-0.4919[/C][C]0.312279[/C][/ROW]
[ROW][C]6[/C][C]0.057363[/C][C]0.4443[/C][C]0.329202[/C][/ROW]
[ROW][C]7[/C][C]0.03324[/C][C]0.2575[/C][C]0.398846[/C][/ROW]
[ROW][C]8[/C][C]-0.032492[/C][C]-0.2517[/C][C]0.401073[/C][/ROW]
[ROW][C]9[/C][C]0.114443[/C][C]0.8865[/C][C]0.189452[/C][/ROW]
[ROW][C]10[/C][C]0.054482[/C][C]0.422[/C][C]0.33726[/C][/ROW]
[ROW][C]11[/C][C]-0.094272[/C][C]-0.7302[/C][C]0.234047[/C][/ROW]
[ROW][C]12[/C][C]-0.181183[/C][C]-1.4034[/C][C]0.082821[/C][/ROW]
[ROW][C]13[/C][C]-0.093339[/C][C]-0.723[/C][C]0.236245[/C][/ROW]
[ROW][C]14[/C][C]-0.02705[/C][C]-0.2095[/C][C]0.417373[/C][/ROW]
[ROW][C]15[/C][C]-0.014881[/C][C]-0.1153[/C][C]0.454308[/C][/ROW]
[ROW][C]16[/C][C]-0.00662[/C][C]-0.0513[/C][C]0.479637[/C][/ROW]
[ROW][C]17[/C][C]-0.051897[/C][C]-0.402[/C][C]0.344558[/C][/ROW]
[ROW][C]18[/C][C]0.035067[/C][C]0.2716[/C][C]0.393421[/C][/ROW]
[ROW][C]19[/C][C]0.02694[/C][C]0.2087[/C][C]0.417705[/C][/ROW]
[ROW][C]20[/C][C]-0.069447[/C][C]-0.5379[/C][C]0.296306[/C][/ROW]
[ROW][C]21[/C][C]-0.088014[/C][C]-0.6818[/C][C]0.249008[/C][/ROW]
[ROW][C]22[/C][C]-0.121628[/C][C]-0.9421[/C][C]0.174952[/C][/ROW]
[ROW][C]23[/C][C]0.003041[/C][C]0.0236[/C][C]0.490644[/C][/ROW]
[ROW][C]24[/C][C]0.016346[/C][C]0.1266[/C][C]0.449835[/C][/ROW]
[ROW][C]25[/C][C]-0.047601[/C][C]-0.3687[/C][C]0.356818[/C][/ROW]
[ROW][C]26[/C][C]0.016546[/C][C]0.1282[/C][C]0.449225[/C][/ROW]
[ROW][C]27[/C][C]-0.062374[/C][C]-0.4831[/C][C]0.315375[/C][/ROW]
[ROW][C]28[/C][C]0.031037[/C][C]0.2404[/C][C]0.405415[/C][/ROW]
[ROW][C]29[/C][C]-0.001672[/C][C]-0.0129[/C][C]0.494856[/C][/ROW]
[ROW][C]30[/C][C]-0.120224[/C][C]-0.9312[/C][C]0.177729[/C][/ROW]
[ROW][C]31[/C][C]-0.032981[/C][C]-0.2555[/C][C]0.399616[/C][/ROW]
[ROW][C]32[/C][C]0.018411[/C][C]0.1426[/C][C]0.443538[/C][/ROW]
[ROW][C]33[/C][C]0.003082[/C][C]0.0239[/C][C]0.490517[/C][/ROW]
[ROW][C]34[/C][C]0.042542[/C][C]0.3295[/C][C]0.371452[/C][/ROW]
[ROW][C]35[/C][C]0.032534[/C][C]0.252[/C][C]0.400947[/C][/ROW]
[ROW][C]36[/C][C]0.003052[/C][C]0.0236[/C][C]0.490609[/C][/ROW]
[ROW][C]37[/C][C]0.08825[/C][C]0.6836[/C][C]0.248434[/C][/ROW]
[ROW][C]38[/C][C]-0.018694[/C][C]-0.1448[/C][C]0.442674[/C][/ROW]
[ROW][C]39[/C][C]-0.121171[/C][C]-0.9386[/C][C]0.175854[/C][/ROW]
[ROW][C]40[/C][C]0.043995[/C][C]0.3408[/C][C]0.367229[/C][/ROW]
[ROW][C]41[/C][C]-0.027869[/C][C]-0.2159[/C][C]0.414911[/C][/ROW]
[ROW][C]42[/C][C]-0.006464[/C][C]-0.0501[/C][C]0.480117[/C][/ROW]
[ROW][C]43[/C][C]0.007418[/C][C]0.0575[/C][C]0.477184[/C][/ROW]
[ROW][C]44[/C][C]0.000808[/C][C]0.0063[/C][C]0.497513[/C][/ROW]
[ROW][C]45[/C][C]0.077199[/C][C]0.598[/C][C]0.276052[/C][/ROW]
[ROW][C]46[/C][C]0.045521[/C][C]0.3526[/C][C]0.362811[/C][/ROW]
[ROW][C]47[/C][C]-0.053922[/C][C]-0.4177[/C][C]0.338836[/C][/ROW]
[ROW][C]48[/C][C]-0.093957[/C][C]-0.7278[/C][C]0.234788[/C][/ROW]
[ROW][C]49[/C][C]-0.039601[/C][C]-0.3067[/C][C]0.380049[/C][/ROW]
[ROW][C]50[/C][C]-0.008528[/C][C]-0.0661[/C][C]0.473776[/C][/ROW]
[ROW][C]51[/C][C]-0.096372[/C][C]-0.7465[/C][C]0.229142[/C][/ROW]
[ROW][C]52[/C][C]-0.134247[/C][C]-1.0399[/C][C]0.151286[/C][/ROW]
[ROW][C]53[/C][C]-0.021666[/C][C]-0.1678[/C][C]0.433642[/C][/ROW]
[ROW][C]54[/C][C]0.131149[/C][C]1.0159[/C][C]0.156883[/C][/ROW]
[ROW][C]55[/C][C]0.03108[/C][C]0.2407[/C][C]0.405286[/C][/ROW]
[ROW][C]56[/C][C]-0.073319[/C][C]-0.5679[/C][C]0.286102[/C][/ROW]
[ROW][C]57[/C][C]-0.055796[/C][C]-0.4322[/C][C]0.333575[/C][/ROW]
[ROW][C]58[/C][C]-0.063059[/C][C]-0.4885[/C][C]0.313505[/C][/ROW]
[ROW][C]59[/C][C]-0.01038[/C][C]-0.0804[/C][C]0.468091[/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=64119&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64119&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
10.9663437.48530
2-0.414473-3.21050.001065
3-0.169267-1.31110.097404
4-0.09389-0.72730.234945
5-0.063509-0.49190.312279
60.0573630.44430.329202
70.033240.25750.398846
8-0.032492-0.25170.401073
90.1144430.88650.189452
100.0544820.4220.33726
11-0.094272-0.73020.234047
12-0.181183-1.40340.082821
13-0.093339-0.7230.236245
14-0.02705-0.20950.417373
15-0.014881-0.11530.454308
16-0.00662-0.05130.479637
17-0.051897-0.4020.344558
180.0350670.27160.393421
190.026940.20870.417705
20-0.069447-0.53790.296306
21-0.088014-0.68180.249008
22-0.121628-0.94210.174952
230.0030410.02360.490644
240.0163460.12660.449835
25-0.047601-0.36870.356818
260.0165460.12820.449225
27-0.062374-0.48310.315375
280.0310370.24040.405415
29-0.001672-0.01290.494856
30-0.120224-0.93120.177729
31-0.032981-0.25550.399616
320.0184110.14260.443538
330.0030820.02390.490517
340.0425420.32950.371452
350.0325340.2520.400947
360.0030520.02360.490609
370.088250.68360.248434
38-0.018694-0.14480.442674
39-0.121171-0.93860.175854
400.0439950.34080.367229
41-0.027869-0.21590.414911
42-0.006464-0.05010.480117
430.0074180.05750.477184
440.0008080.00630.497513
450.0771990.5980.276052
460.0455210.35260.362811
47-0.053922-0.41770.338836
48-0.093957-0.72780.234788
49-0.039601-0.30670.380049
50-0.008528-0.06610.473776
51-0.096372-0.74650.229142
52-0.134247-1.03990.151286
53-0.021666-0.16780.433642
540.1311491.01590.156883
550.031080.24070.405286
56-0.073319-0.56790.286102
57-0.055796-0.43220.333575
58-0.063059-0.48850.313505
59-0.01038-0.08040.468091
60NANANA



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