Free Statistics

of Irreproducible Research!

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 computationSun, 27 Dec 2009 03:35:52 -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/27/t1261910190s633r8xs8xvkkxv.htm/, Retrieved Fri, 03 May 2024 03:24:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70820, Retrieved Fri, 03 May 2024 03:24:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [] [2009-12-27 10:35:52] [f6a332ba2d530c028d935c5a5bbb53af] [Current]
-   P     [(Partial) Autocorrelation Function] [] [2009-12-30 14:41:38] [d2d412c7f4d35ffbf5ee5ee89db327d4]
-           [(Partial) Autocorrelation Function] [] [2009-12-30 15:05:16] [d2d412c7f4d35ffbf5ee5ee89db327d4]
Feedback Forum

Post a new message
Dataseries X:
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485




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=70820&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=70820&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70820&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
1-0.403478-3.04620.001753
20.1874121.41490.081264
3-0.164473-1.24170.109708
4-0.077962-0.58860.279227
5-0.073668-0.55620.290131
60.1049310.79220.21576
7-0.106263-0.80230.212865
80.214371.61850.055543
9-0.010178-0.07680.46951
10-0.062872-0.47470.318418
110.0157450.11890.452899
12-0.197093-1.4880.071129
13-0.046191-0.34870.364287
14-0.013313-0.10050.460146
150.0626820.47320.318926
160.0193880.14640.44207
170.0803730.60680.273196
18-0.046486-0.3510.363457
19-0.003264-0.02460.490212
20-0.09231-0.69690.244342
210.1653911.24870.108444
22-0.254294-1.91990.029942
230.2761672.0850.020779
24-0.139607-1.0540.148163
250.1544981.16640.124148
26-0.006414-0.04840.480772
270.0229090.1730.431648
28-0.127048-0.95920.170757
290.1336611.00910.158592
30-0.124276-0.93830.176035
310.0343790.25960.39807
32-0.000909-0.00690.497274
33-0.09591-0.72410.235981
340.1272890.9610.170303
35-0.028234-0.21320.415981
36-0.048296-0.36460.358369
370.001980.0150.494061
38-0.059414-0.44860.327723
39-0.007108-0.05370.478695
400.0803130.60630.273345
41-0.055561-0.41950.338222
420.0438570.33110.370887
430.0196010.1480.44144
44-0.02047-0.15450.438863
450.0142840.10780.45725
460.0084360.06370.47472
470.0321670.24290.404495
48-0.047618-0.35950.360271
490.012690.09580.462005
500.073140.55220.291486
510.0004570.00350.498628
52-0.026634-0.20110.420674
53-0.028786-0.21730.414363
54-0.005152-0.03890.484554
55-0.007488-0.05650.477556
56-0.005349-0.04040.483963
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.403478 & -3.0462 & 0.001753 \tabularnewline
2 & 0.187412 & 1.4149 & 0.081264 \tabularnewline
3 & -0.164473 & -1.2417 & 0.109708 \tabularnewline
4 & -0.077962 & -0.5886 & 0.279227 \tabularnewline
5 & -0.073668 & -0.5562 & 0.290131 \tabularnewline
6 & 0.104931 & 0.7922 & 0.21576 \tabularnewline
7 & -0.106263 & -0.8023 & 0.212865 \tabularnewline
8 & 0.21437 & 1.6185 & 0.055543 \tabularnewline
9 & -0.010178 & -0.0768 & 0.46951 \tabularnewline
10 & -0.062872 & -0.4747 & 0.318418 \tabularnewline
11 & 0.015745 & 0.1189 & 0.452899 \tabularnewline
12 & -0.197093 & -1.488 & 0.071129 \tabularnewline
13 & -0.046191 & -0.3487 & 0.364287 \tabularnewline
14 & -0.013313 & -0.1005 & 0.460146 \tabularnewline
15 & 0.062682 & 0.4732 & 0.318926 \tabularnewline
16 & 0.019388 & 0.1464 & 0.44207 \tabularnewline
17 & 0.080373 & 0.6068 & 0.273196 \tabularnewline
18 & -0.046486 & -0.351 & 0.363457 \tabularnewline
19 & -0.003264 & -0.0246 & 0.490212 \tabularnewline
20 & -0.09231 & -0.6969 & 0.244342 \tabularnewline
21 & 0.165391 & 1.2487 & 0.108444 \tabularnewline
22 & -0.254294 & -1.9199 & 0.029942 \tabularnewline
23 & 0.276167 & 2.085 & 0.020779 \tabularnewline
24 & -0.139607 & -1.054 & 0.148163 \tabularnewline
25 & 0.154498 & 1.1664 & 0.124148 \tabularnewline
26 & -0.006414 & -0.0484 & 0.480772 \tabularnewline
27 & 0.022909 & 0.173 & 0.431648 \tabularnewline
28 & -0.127048 & -0.9592 & 0.170757 \tabularnewline
29 & 0.133661 & 1.0091 & 0.158592 \tabularnewline
30 & -0.124276 & -0.9383 & 0.176035 \tabularnewline
31 & 0.034379 & 0.2596 & 0.39807 \tabularnewline
32 & -0.000909 & -0.0069 & 0.497274 \tabularnewline
33 & -0.09591 & -0.7241 & 0.235981 \tabularnewline
34 & 0.127289 & 0.961 & 0.170303 \tabularnewline
35 & -0.028234 & -0.2132 & 0.415981 \tabularnewline
36 & -0.048296 & -0.3646 & 0.358369 \tabularnewline
37 & 0.00198 & 0.015 & 0.494061 \tabularnewline
38 & -0.059414 & -0.4486 & 0.327723 \tabularnewline
39 & -0.007108 & -0.0537 & 0.478695 \tabularnewline
40 & 0.080313 & 0.6063 & 0.273345 \tabularnewline
41 & -0.055561 & -0.4195 & 0.338222 \tabularnewline
42 & 0.043857 & 0.3311 & 0.370887 \tabularnewline
43 & 0.019601 & 0.148 & 0.44144 \tabularnewline
44 & -0.02047 & -0.1545 & 0.438863 \tabularnewline
45 & 0.014284 & 0.1078 & 0.45725 \tabularnewline
46 & 0.008436 & 0.0637 & 0.47472 \tabularnewline
47 & 0.032167 & 0.2429 & 0.404495 \tabularnewline
48 & -0.047618 & -0.3595 & 0.360271 \tabularnewline
49 & 0.01269 & 0.0958 & 0.462005 \tabularnewline
50 & 0.07314 & 0.5522 & 0.291486 \tabularnewline
51 & 0.000457 & 0.0035 & 0.498628 \tabularnewline
52 & -0.026634 & -0.2011 & 0.420674 \tabularnewline
53 & -0.028786 & -0.2173 & 0.414363 \tabularnewline
54 & -0.005152 & -0.0389 & 0.484554 \tabularnewline
55 & -0.007488 & -0.0565 & 0.477556 \tabularnewline
56 & -0.005349 & -0.0404 & 0.483963 \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=70820&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]-0.403478[/C][C]-3.0462[/C][C]0.001753[/C][/ROW]
[ROW][C]2[/C][C]0.187412[/C][C]1.4149[/C][C]0.081264[/C][/ROW]
[ROW][C]3[/C][C]-0.164473[/C][C]-1.2417[/C][C]0.109708[/C][/ROW]
[ROW][C]4[/C][C]-0.077962[/C][C]-0.5886[/C][C]0.279227[/C][/ROW]
[ROW][C]5[/C][C]-0.073668[/C][C]-0.5562[/C][C]0.290131[/C][/ROW]
[ROW][C]6[/C][C]0.104931[/C][C]0.7922[/C][C]0.21576[/C][/ROW]
[ROW][C]7[/C][C]-0.106263[/C][C]-0.8023[/C][C]0.212865[/C][/ROW]
[ROW][C]8[/C][C]0.21437[/C][C]1.6185[/C][C]0.055543[/C][/ROW]
[ROW][C]9[/C][C]-0.010178[/C][C]-0.0768[/C][C]0.46951[/C][/ROW]
[ROW][C]10[/C][C]-0.062872[/C][C]-0.4747[/C][C]0.318418[/C][/ROW]
[ROW][C]11[/C][C]0.015745[/C][C]0.1189[/C][C]0.452899[/C][/ROW]
[ROW][C]12[/C][C]-0.197093[/C][C]-1.488[/C][C]0.071129[/C][/ROW]
[ROW][C]13[/C][C]-0.046191[/C][C]-0.3487[/C][C]0.364287[/C][/ROW]
[ROW][C]14[/C][C]-0.013313[/C][C]-0.1005[/C][C]0.460146[/C][/ROW]
[ROW][C]15[/C][C]0.062682[/C][C]0.4732[/C][C]0.318926[/C][/ROW]
[ROW][C]16[/C][C]0.019388[/C][C]0.1464[/C][C]0.44207[/C][/ROW]
[ROW][C]17[/C][C]0.080373[/C][C]0.6068[/C][C]0.273196[/C][/ROW]
[ROW][C]18[/C][C]-0.046486[/C][C]-0.351[/C][C]0.363457[/C][/ROW]
[ROW][C]19[/C][C]-0.003264[/C][C]-0.0246[/C][C]0.490212[/C][/ROW]
[ROW][C]20[/C][C]-0.09231[/C][C]-0.6969[/C][C]0.244342[/C][/ROW]
[ROW][C]21[/C][C]0.165391[/C][C]1.2487[/C][C]0.108444[/C][/ROW]
[ROW][C]22[/C][C]-0.254294[/C][C]-1.9199[/C][C]0.029942[/C][/ROW]
[ROW][C]23[/C][C]0.276167[/C][C]2.085[/C][C]0.020779[/C][/ROW]
[ROW][C]24[/C][C]-0.139607[/C][C]-1.054[/C][C]0.148163[/C][/ROW]
[ROW][C]25[/C][C]0.154498[/C][C]1.1664[/C][C]0.124148[/C][/ROW]
[ROW][C]26[/C][C]-0.006414[/C][C]-0.0484[/C][C]0.480772[/C][/ROW]
[ROW][C]27[/C][C]0.022909[/C][C]0.173[/C][C]0.431648[/C][/ROW]
[ROW][C]28[/C][C]-0.127048[/C][C]-0.9592[/C][C]0.170757[/C][/ROW]
[ROW][C]29[/C][C]0.133661[/C][C]1.0091[/C][C]0.158592[/C][/ROW]
[ROW][C]30[/C][C]-0.124276[/C][C]-0.9383[/C][C]0.176035[/C][/ROW]
[ROW][C]31[/C][C]0.034379[/C][C]0.2596[/C][C]0.39807[/C][/ROW]
[ROW][C]32[/C][C]-0.000909[/C][C]-0.0069[/C][C]0.497274[/C][/ROW]
[ROW][C]33[/C][C]-0.09591[/C][C]-0.7241[/C][C]0.235981[/C][/ROW]
[ROW][C]34[/C][C]0.127289[/C][C]0.961[/C][C]0.170303[/C][/ROW]
[ROW][C]35[/C][C]-0.028234[/C][C]-0.2132[/C][C]0.415981[/C][/ROW]
[ROW][C]36[/C][C]-0.048296[/C][C]-0.3646[/C][C]0.358369[/C][/ROW]
[ROW][C]37[/C][C]0.00198[/C][C]0.015[/C][C]0.494061[/C][/ROW]
[ROW][C]38[/C][C]-0.059414[/C][C]-0.4486[/C][C]0.327723[/C][/ROW]
[ROW][C]39[/C][C]-0.007108[/C][C]-0.0537[/C][C]0.478695[/C][/ROW]
[ROW][C]40[/C][C]0.080313[/C][C]0.6063[/C][C]0.273345[/C][/ROW]
[ROW][C]41[/C][C]-0.055561[/C][C]-0.4195[/C][C]0.338222[/C][/ROW]
[ROW][C]42[/C][C]0.043857[/C][C]0.3311[/C][C]0.370887[/C][/ROW]
[ROW][C]43[/C][C]0.019601[/C][C]0.148[/C][C]0.44144[/C][/ROW]
[ROW][C]44[/C][C]-0.02047[/C][C]-0.1545[/C][C]0.438863[/C][/ROW]
[ROW][C]45[/C][C]0.014284[/C][C]0.1078[/C][C]0.45725[/C][/ROW]
[ROW][C]46[/C][C]0.008436[/C][C]0.0637[/C][C]0.47472[/C][/ROW]
[ROW][C]47[/C][C]0.032167[/C][C]0.2429[/C][C]0.404495[/C][/ROW]
[ROW][C]48[/C][C]-0.047618[/C][C]-0.3595[/C][C]0.360271[/C][/ROW]
[ROW][C]49[/C][C]0.01269[/C][C]0.0958[/C][C]0.462005[/C][/ROW]
[ROW][C]50[/C][C]0.07314[/C][C]0.5522[/C][C]0.291486[/C][/ROW]
[ROW][C]51[/C][C]0.000457[/C][C]0.0035[/C][C]0.498628[/C][/ROW]
[ROW][C]52[/C][C]-0.026634[/C][C]-0.2011[/C][C]0.420674[/C][/ROW]
[ROW][C]53[/C][C]-0.028786[/C][C]-0.2173[/C][C]0.414363[/C][/ROW]
[ROW][C]54[/C][C]-0.005152[/C][C]-0.0389[/C][C]0.484554[/C][/ROW]
[ROW][C]55[/C][C]-0.007488[/C][C]-0.0565[/C][C]0.477556[/C][/ROW]
[ROW][C]56[/C][C]-0.005349[/C][C]-0.0404[/C][C]0.483963[/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=70820&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70820&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
1-0.403478-3.04620.001753
20.1874121.41490.081264
3-0.164473-1.24170.109708
4-0.077962-0.58860.279227
5-0.073668-0.55620.290131
60.1049310.79220.21576
7-0.106263-0.80230.212865
80.214371.61850.055543
9-0.010178-0.07680.46951
10-0.062872-0.47470.318418
110.0157450.11890.452899
12-0.197093-1.4880.071129
13-0.046191-0.34870.364287
14-0.013313-0.10050.460146
150.0626820.47320.318926
160.0193880.14640.44207
170.0803730.60680.273196
18-0.046486-0.3510.363457
19-0.003264-0.02460.490212
20-0.09231-0.69690.244342
210.1653911.24870.108444
22-0.254294-1.91990.029942
230.2761672.0850.020779
24-0.139607-1.0540.148163
250.1544981.16640.124148
26-0.006414-0.04840.480772
270.0229090.1730.431648
28-0.127048-0.95920.170757
290.1336611.00910.158592
30-0.124276-0.93830.176035
310.0343790.25960.39807
32-0.000909-0.00690.497274
33-0.09591-0.72410.235981
340.1272890.9610.170303
35-0.028234-0.21320.415981
36-0.048296-0.36460.358369
370.001980.0150.494061
38-0.059414-0.44860.327723
39-0.007108-0.05370.478695
400.0803130.60630.273345
41-0.055561-0.41950.338222
420.0438570.33110.370887
430.0196010.1480.44144
44-0.02047-0.15450.438863
450.0142840.10780.45725
460.0084360.06370.47472
470.0321670.24290.404495
48-0.047618-0.35950.360271
490.012690.09580.462005
500.073140.55220.291486
510.0004570.00350.498628
52-0.026634-0.20110.420674
53-0.028786-0.21730.414363
54-0.005152-0.03890.484554
55-0.007488-0.05650.477556
56-0.005349-0.04040.483963
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.403478-3.04620.001753
20.0294040.2220.412554
3-0.094701-0.7150.238771
4-0.215547-1.62730.05459
5-0.203201-1.53410.065265
60.016260.12280.451365
7-0.107778-0.81370.2096
80.083750.63230.26486
90.1408551.06340.146035
10-0.055248-0.41710.339081
11-0.015073-0.11380.454899
12-0.167816-1.2670.105157
13-0.215072-1.62380.054973
14-0.193497-1.46090.074771
15-0.077903-0.58820.279376
16-0.118981-0.89830.186405
17-0.100976-0.76240.224497
18-0.048208-0.3640.358617
19-0.068464-0.51690.303617
20-0.115307-0.87050.193827
210.1984781.49850.069764
22-0.181314-1.36890.088202
230.0076840.0580.476969
24-0.05078-0.38340.351432
25-0.040949-0.30920.379164
260.000330.00250.49901
270.0327340.24710.402844
28-0.070871-0.53510.297343
290.013960.10540.458216
300.073630.55590.290229
31-0.073159-0.55230.291438
32-0.091237-0.68880.246864
33-0.100623-0.75970.225285
34-0.042529-0.32110.374661
35-0.004225-0.03190.487332
36-0.06504-0.4910.312642
37-0.066023-0.49850.310037
38-0.096473-0.72840.23469
390.0005030.00380.498493
400.0379870.28680.387654
41-0.027493-0.20760.418152
42-0.065703-0.4960.310885
430.0231360.17470.430979
44-0.121486-0.91720.181452
45-0.019797-0.14950.440858
46-0.067069-0.50640.307279
470.0725460.54770.293016
48-0.090821-0.68570.247847
49-0.0745-0.56250.288002
500.0211210.15950.436936
510.0737330.55670.289964
52-0.042997-0.32460.373329
53-0.049026-0.37010.356327
540.0223290.16860.433363
55-0.094767-0.71550.238619
56-0.028763-0.21720.41443
57NANANA
58NANANA
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.403478 & -3.0462 & 0.001753 \tabularnewline
2 & 0.029404 & 0.222 & 0.412554 \tabularnewline
3 & -0.094701 & -0.715 & 0.238771 \tabularnewline
4 & -0.215547 & -1.6273 & 0.05459 \tabularnewline
5 & -0.203201 & -1.5341 & 0.065265 \tabularnewline
6 & 0.01626 & 0.1228 & 0.451365 \tabularnewline
7 & -0.107778 & -0.8137 & 0.2096 \tabularnewline
8 & 0.08375 & 0.6323 & 0.26486 \tabularnewline
9 & 0.140855 & 1.0634 & 0.146035 \tabularnewline
10 & -0.055248 & -0.4171 & 0.339081 \tabularnewline
11 & -0.015073 & -0.1138 & 0.454899 \tabularnewline
12 & -0.167816 & -1.267 & 0.105157 \tabularnewline
13 & -0.215072 & -1.6238 & 0.054973 \tabularnewline
14 & -0.193497 & -1.4609 & 0.074771 \tabularnewline
15 & -0.077903 & -0.5882 & 0.279376 \tabularnewline
16 & -0.118981 & -0.8983 & 0.186405 \tabularnewline
17 & -0.100976 & -0.7624 & 0.224497 \tabularnewline
18 & -0.048208 & -0.364 & 0.358617 \tabularnewline
19 & -0.068464 & -0.5169 & 0.303617 \tabularnewline
20 & -0.115307 & -0.8705 & 0.193827 \tabularnewline
21 & 0.198478 & 1.4985 & 0.069764 \tabularnewline
22 & -0.181314 & -1.3689 & 0.088202 \tabularnewline
23 & 0.007684 & 0.058 & 0.476969 \tabularnewline
24 & -0.05078 & -0.3834 & 0.351432 \tabularnewline
25 & -0.040949 & -0.3092 & 0.379164 \tabularnewline
26 & 0.00033 & 0.0025 & 0.49901 \tabularnewline
27 & 0.032734 & 0.2471 & 0.402844 \tabularnewline
28 & -0.070871 & -0.5351 & 0.297343 \tabularnewline
29 & 0.01396 & 0.1054 & 0.458216 \tabularnewline
30 & 0.07363 & 0.5559 & 0.290229 \tabularnewline
31 & -0.073159 & -0.5523 & 0.291438 \tabularnewline
32 & -0.091237 & -0.6888 & 0.246864 \tabularnewline
33 & -0.100623 & -0.7597 & 0.225285 \tabularnewline
34 & -0.042529 & -0.3211 & 0.374661 \tabularnewline
35 & -0.004225 & -0.0319 & 0.487332 \tabularnewline
36 & -0.06504 & -0.491 & 0.312642 \tabularnewline
37 & -0.066023 & -0.4985 & 0.310037 \tabularnewline
38 & -0.096473 & -0.7284 & 0.23469 \tabularnewline
39 & 0.000503 & 0.0038 & 0.498493 \tabularnewline
40 & 0.037987 & 0.2868 & 0.387654 \tabularnewline
41 & -0.027493 & -0.2076 & 0.418152 \tabularnewline
42 & -0.065703 & -0.496 & 0.310885 \tabularnewline
43 & 0.023136 & 0.1747 & 0.430979 \tabularnewline
44 & -0.121486 & -0.9172 & 0.181452 \tabularnewline
45 & -0.019797 & -0.1495 & 0.440858 \tabularnewline
46 & -0.067069 & -0.5064 & 0.307279 \tabularnewline
47 & 0.072546 & 0.5477 & 0.293016 \tabularnewline
48 & -0.090821 & -0.6857 & 0.247847 \tabularnewline
49 & -0.0745 & -0.5625 & 0.288002 \tabularnewline
50 & 0.021121 & 0.1595 & 0.436936 \tabularnewline
51 & 0.073733 & 0.5567 & 0.289964 \tabularnewline
52 & -0.042997 & -0.3246 & 0.373329 \tabularnewline
53 & -0.049026 & -0.3701 & 0.356327 \tabularnewline
54 & 0.022329 & 0.1686 & 0.433363 \tabularnewline
55 & -0.094767 & -0.7155 & 0.238619 \tabularnewline
56 & -0.028763 & -0.2172 & 0.41443 \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=70820&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]-0.403478[/C][C]-3.0462[/C][C]0.001753[/C][/ROW]
[ROW][C]2[/C][C]0.029404[/C][C]0.222[/C][C]0.412554[/C][/ROW]
[ROW][C]3[/C][C]-0.094701[/C][C]-0.715[/C][C]0.238771[/C][/ROW]
[ROW][C]4[/C][C]-0.215547[/C][C]-1.6273[/C][C]0.05459[/C][/ROW]
[ROW][C]5[/C][C]-0.203201[/C][C]-1.5341[/C][C]0.065265[/C][/ROW]
[ROW][C]6[/C][C]0.01626[/C][C]0.1228[/C][C]0.451365[/C][/ROW]
[ROW][C]7[/C][C]-0.107778[/C][C]-0.8137[/C][C]0.2096[/C][/ROW]
[ROW][C]8[/C][C]0.08375[/C][C]0.6323[/C][C]0.26486[/C][/ROW]
[ROW][C]9[/C][C]0.140855[/C][C]1.0634[/C][C]0.146035[/C][/ROW]
[ROW][C]10[/C][C]-0.055248[/C][C]-0.4171[/C][C]0.339081[/C][/ROW]
[ROW][C]11[/C][C]-0.015073[/C][C]-0.1138[/C][C]0.454899[/C][/ROW]
[ROW][C]12[/C][C]-0.167816[/C][C]-1.267[/C][C]0.105157[/C][/ROW]
[ROW][C]13[/C][C]-0.215072[/C][C]-1.6238[/C][C]0.054973[/C][/ROW]
[ROW][C]14[/C][C]-0.193497[/C][C]-1.4609[/C][C]0.074771[/C][/ROW]
[ROW][C]15[/C][C]-0.077903[/C][C]-0.5882[/C][C]0.279376[/C][/ROW]
[ROW][C]16[/C][C]-0.118981[/C][C]-0.8983[/C][C]0.186405[/C][/ROW]
[ROW][C]17[/C][C]-0.100976[/C][C]-0.7624[/C][C]0.224497[/C][/ROW]
[ROW][C]18[/C][C]-0.048208[/C][C]-0.364[/C][C]0.358617[/C][/ROW]
[ROW][C]19[/C][C]-0.068464[/C][C]-0.5169[/C][C]0.303617[/C][/ROW]
[ROW][C]20[/C][C]-0.115307[/C][C]-0.8705[/C][C]0.193827[/C][/ROW]
[ROW][C]21[/C][C]0.198478[/C][C]1.4985[/C][C]0.069764[/C][/ROW]
[ROW][C]22[/C][C]-0.181314[/C][C]-1.3689[/C][C]0.088202[/C][/ROW]
[ROW][C]23[/C][C]0.007684[/C][C]0.058[/C][C]0.476969[/C][/ROW]
[ROW][C]24[/C][C]-0.05078[/C][C]-0.3834[/C][C]0.351432[/C][/ROW]
[ROW][C]25[/C][C]-0.040949[/C][C]-0.3092[/C][C]0.379164[/C][/ROW]
[ROW][C]26[/C][C]0.00033[/C][C]0.0025[/C][C]0.49901[/C][/ROW]
[ROW][C]27[/C][C]0.032734[/C][C]0.2471[/C][C]0.402844[/C][/ROW]
[ROW][C]28[/C][C]-0.070871[/C][C]-0.5351[/C][C]0.297343[/C][/ROW]
[ROW][C]29[/C][C]0.01396[/C][C]0.1054[/C][C]0.458216[/C][/ROW]
[ROW][C]30[/C][C]0.07363[/C][C]0.5559[/C][C]0.290229[/C][/ROW]
[ROW][C]31[/C][C]-0.073159[/C][C]-0.5523[/C][C]0.291438[/C][/ROW]
[ROW][C]32[/C][C]-0.091237[/C][C]-0.6888[/C][C]0.246864[/C][/ROW]
[ROW][C]33[/C][C]-0.100623[/C][C]-0.7597[/C][C]0.225285[/C][/ROW]
[ROW][C]34[/C][C]-0.042529[/C][C]-0.3211[/C][C]0.374661[/C][/ROW]
[ROW][C]35[/C][C]-0.004225[/C][C]-0.0319[/C][C]0.487332[/C][/ROW]
[ROW][C]36[/C][C]-0.06504[/C][C]-0.491[/C][C]0.312642[/C][/ROW]
[ROW][C]37[/C][C]-0.066023[/C][C]-0.4985[/C][C]0.310037[/C][/ROW]
[ROW][C]38[/C][C]-0.096473[/C][C]-0.7284[/C][C]0.23469[/C][/ROW]
[ROW][C]39[/C][C]0.000503[/C][C]0.0038[/C][C]0.498493[/C][/ROW]
[ROW][C]40[/C][C]0.037987[/C][C]0.2868[/C][C]0.387654[/C][/ROW]
[ROW][C]41[/C][C]-0.027493[/C][C]-0.2076[/C][C]0.418152[/C][/ROW]
[ROW][C]42[/C][C]-0.065703[/C][C]-0.496[/C][C]0.310885[/C][/ROW]
[ROW][C]43[/C][C]0.023136[/C][C]0.1747[/C][C]0.430979[/C][/ROW]
[ROW][C]44[/C][C]-0.121486[/C][C]-0.9172[/C][C]0.181452[/C][/ROW]
[ROW][C]45[/C][C]-0.019797[/C][C]-0.1495[/C][C]0.440858[/C][/ROW]
[ROW][C]46[/C][C]-0.067069[/C][C]-0.5064[/C][C]0.307279[/C][/ROW]
[ROW][C]47[/C][C]0.072546[/C][C]0.5477[/C][C]0.293016[/C][/ROW]
[ROW][C]48[/C][C]-0.090821[/C][C]-0.6857[/C][C]0.247847[/C][/ROW]
[ROW][C]49[/C][C]-0.0745[/C][C]-0.5625[/C][C]0.288002[/C][/ROW]
[ROW][C]50[/C][C]0.021121[/C][C]0.1595[/C][C]0.436936[/C][/ROW]
[ROW][C]51[/C][C]0.073733[/C][C]0.5567[/C][C]0.289964[/C][/ROW]
[ROW][C]52[/C][C]-0.042997[/C][C]-0.3246[/C][C]0.373329[/C][/ROW]
[ROW][C]53[/C][C]-0.049026[/C][C]-0.3701[/C][C]0.356327[/C][/ROW]
[ROW][C]54[/C][C]0.022329[/C][C]0.1686[/C][C]0.433363[/C][/ROW]
[ROW][C]55[/C][C]-0.094767[/C][C]-0.7155[/C][C]0.238619[/C][/ROW]
[ROW][C]56[/C][C]-0.028763[/C][C]-0.2172[/C][C]0.41443[/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=70820&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70820&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
1-0.403478-3.04620.001753
20.0294040.2220.412554
3-0.094701-0.7150.238771
4-0.215547-1.62730.05459
5-0.203201-1.53410.065265
60.016260.12280.451365
7-0.107778-0.81370.2096
80.083750.63230.26486
90.1408551.06340.146035
10-0.055248-0.41710.339081
11-0.015073-0.11380.454899
12-0.167816-1.2670.105157
13-0.215072-1.62380.054973
14-0.193497-1.46090.074771
15-0.077903-0.58820.279376
16-0.118981-0.89830.186405
17-0.100976-0.76240.224497
18-0.048208-0.3640.358617
19-0.068464-0.51690.303617
20-0.115307-0.87050.193827
210.1984781.49850.069764
22-0.181314-1.36890.088202
230.0076840.0580.476969
24-0.05078-0.38340.351432
25-0.040949-0.30920.379164
260.000330.00250.49901
270.0327340.24710.402844
28-0.070871-0.53510.297343
290.013960.10540.458216
300.073630.55590.290229
31-0.073159-0.55230.291438
32-0.091237-0.68880.246864
33-0.100623-0.75970.225285
34-0.042529-0.32110.374661
35-0.004225-0.03190.487332
36-0.06504-0.4910.312642
37-0.066023-0.49850.310037
38-0.096473-0.72840.23469
390.0005030.00380.498493
400.0379870.28680.387654
41-0.027493-0.20760.418152
42-0.065703-0.4960.310885
430.0231360.17470.430979
44-0.121486-0.91720.181452
45-0.019797-0.14950.440858
46-0.067069-0.50640.307279
470.0725460.54770.293016
48-0.090821-0.68570.247847
49-0.0745-0.56250.288002
500.0211210.15950.436936
510.0737330.55670.289964
52-0.042997-0.32460.373329
53-0.049026-0.37010.356327
540.0223290.16860.433363
55-0.094767-0.71550.238619
56-0.028763-0.21720.41443
57NANANA
58NANANA
59NANANA
60NANANA



Parameters (Session):
par1 = 12 ;
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')