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 computationTue, 15 Dec 2009 09:50:03 -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/15/t1260895863jh8p51lgsqm5yik.htm/, Retrieved Wed, 08 May 2024 18:34:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68036, Retrieved Wed, 08 May 2024 18:34:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [(Partial) Autocorrelation Function] [Identifying Integ...] [2009-11-22 12:16:10] [b98453cac15ba1066b407e146608df68]
-   PD          [(Partial) Autocorrelation Function] [] [2009-12-15 16:50:03] [4672b66a35a4d755714bdcf00037725e] [Current]
Feedback Forum

Post a new message
Dataseries X:
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68036&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]3 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=68036&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68036&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.3652312.58260.00639
20.1320420.93370.177479
3-0.069899-0.49430.311643
4-0.204883-1.44870.076826
5-0.228199-1.61360.056453
6-0.40702-2.87810.002936
7-0.242258-1.7130.046452
8-0.207109-1.46450.074661
9-0.103161-0.72950.234563
10-0.005178-0.03660.48547
110.1817821.28540.102288
120.6511734.60451.4e-05
130.2600611.83890.035935
140.1139420.80570.212118
15-0.039416-0.27870.390806
16-0.153832-1.08780.140959
17-0.164404-1.16250.125274
18-0.305984-2.16360.017648
19-0.156843-1.1090.136358
20-0.156802-1.10880.13642
21-0.094159-0.66580.254298
220.0281860.19930.421415
230.1574761.11350.135404
240.4745893.35580.000759
250.1898831.34270.09272
260.0549080.38830.349735
27-0.005878-0.04160.483507
28-0.071468-0.50540.307765
29-0.103189-0.72970.234503
30-0.208994-1.47780.072865
31-0.108685-0.76850.222896
32-0.13159-0.93050.178297
33-0.126068-0.89140.188483
34-0.027476-0.19430.423371
350.0434010.30690.380101
360.2795861.9770.026786
370.1035630.73230.233701
380.0066270.04690.481406
39-0.038604-0.2730.392999
40-0.030039-0.21240.416326
41-0.067125-0.47460.318553
42-0.07904-0.55890.289364
43-0.025774-0.18220.428062
44-0.024317-0.17190.432086
45-0.02723-0.19250.424047
46-0.034038-0.24070.405391
47-0.026861-0.18990.425063
480.0952390.67340.251884
490.0378330.26750.395086
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 & 0.365231 & 2.5826 & 0.00639 \tabularnewline
2 & 0.132042 & 0.9337 & 0.177479 \tabularnewline
3 & -0.069899 & -0.4943 & 0.311643 \tabularnewline
4 & -0.204883 & -1.4487 & 0.076826 \tabularnewline
5 & -0.228199 & -1.6136 & 0.056453 \tabularnewline
6 & -0.40702 & -2.8781 & 0.002936 \tabularnewline
7 & -0.242258 & -1.713 & 0.046452 \tabularnewline
8 & -0.207109 & -1.4645 & 0.074661 \tabularnewline
9 & -0.103161 & -0.7295 & 0.234563 \tabularnewline
10 & -0.005178 & -0.0366 & 0.48547 \tabularnewline
11 & 0.181782 & 1.2854 & 0.102288 \tabularnewline
12 & 0.651173 & 4.6045 & 1.4e-05 \tabularnewline
13 & 0.260061 & 1.8389 & 0.035935 \tabularnewline
14 & 0.113942 & 0.8057 & 0.212118 \tabularnewline
15 & -0.039416 & -0.2787 & 0.390806 \tabularnewline
16 & -0.153832 & -1.0878 & 0.140959 \tabularnewline
17 & -0.164404 & -1.1625 & 0.125274 \tabularnewline
18 & -0.305984 & -2.1636 & 0.017648 \tabularnewline
19 & -0.156843 & -1.109 & 0.136358 \tabularnewline
20 & -0.156802 & -1.1088 & 0.13642 \tabularnewline
21 & -0.094159 & -0.6658 & 0.254298 \tabularnewline
22 & 0.028186 & 0.1993 & 0.421415 \tabularnewline
23 & 0.157476 & 1.1135 & 0.135404 \tabularnewline
24 & 0.474589 & 3.3558 & 0.000759 \tabularnewline
25 & 0.189883 & 1.3427 & 0.09272 \tabularnewline
26 & 0.054908 & 0.3883 & 0.349735 \tabularnewline
27 & -0.005878 & -0.0416 & 0.483507 \tabularnewline
28 & -0.071468 & -0.5054 & 0.307765 \tabularnewline
29 & -0.103189 & -0.7297 & 0.234503 \tabularnewline
30 & -0.208994 & -1.4778 & 0.072865 \tabularnewline
31 & -0.108685 & -0.7685 & 0.222896 \tabularnewline
32 & -0.13159 & -0.9305 & 0.178297 \tabularnewline
33 & -0.126068 & -0.8914 & 0.188483 \tabularnewline
34 & -0.027476 & -0.1943 & 0.423371 \tabularnewline
35 & 0.043401 & 0.3069 & 0.380101 \tabularnewline
36 & 0.279586 & 1.977 & 0.026786 \tabularnewline
37 & 0.103563 & 0.7323 & 0.233701 \tabularnewline
38 & 0.006627 & 0.0469 & 0.481406 \tabularnewline
39 & -0.038604 & -0.273 & 0.392999 \tabularnewline
40 & -0.030039 & -0.2124 & 0.416326 \tabularnewline
41 & -0.067125 & -0.4746 & 0.318553 \tabularnewline
42 & -0.07904 & -0.5589 & 0.289364 \tabularnewline
43 & -0.025774 & -0.1822 & 0.428062 \tabularnewline
44 & -0.024317 & -0.1719 & 0.432086 \tabularnewline
45 & -0.02723 & -0.1925 & 0.424047 \tabularnewline
46 & -0.034038 & -0.2407 & 0.405391 \tabularnewline
47 & -0.026861 & -0.1899 & 0.425063 \tabularnewline
48 & 0.095239 & 0.6734 & 0.251884 \tabularnewline
49 & 0.037833 & 0.2675 & 0.395086 \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=68036&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]0.365231[/C][C]2.5826[/C][C]0.00639[/C][/ROW]
[ROW][C]2[/C][C]0.132042[/C][C]0.9337[/C][C]0.177479[/C][/ROW]
[ROW][C]3[/C][C]-0.069899[/C][C]-0.4943[/C][C]0.311643[/C][/ROW]
[ROW][C]4[/C][C]-0.204883[/C][C]-1.4487[/C][C]0.076826[/C][/ROW]
[ROW][C]5[/C][C]-0.228199[/C][C]-1.6136[/C][C]0.056453[/C][/ROW]
[ROW][C]6[/C][C]-0.40702[/C][C]-2.8781[/C][C]0.002936[/C][/ROW]
[ROW][C]7[/C][C]-0.242258[/C][C]-1.713[/C][C]0.046452[/C][/ROW]
[ROW][C]8[/C][C]-0.207109[/C][C]-1.4645[/C][C]0.074661[/C][/ROW]
[ROW][C]9[/C][C]-0.103161[/C][C]-0.7295[/C][C]0.234563[/C][/ROW]
[ROW][C]10[/C][C]-0.005178[/C][C]-0.0366[/C][C]0.48547[/C][/ROW]
[ROW][C]11[/C][C]0.181782[/C][C]1.2854[/C][C]0.102288[/C][/ROW]
[ROW][C]12[/C][C]0.651173[/C][C]4.6045[/C][C]1.4e-05[/C][/ROW]
[ROW][C]13[/C][C]0.260061[/C][C]1.8389[/C][C]0.035935[/C][/ROW]
[ROW][C]14[/C][C]0.113942[/C][C]0.8057[/C][C]0.212118[/C][/ROW]
[ROW][C]15[/C][C]-0.039416[/C][C]-0.2787[/C][C]0.390806[/C][/ROW]
[ROW][C]16[/C][C]-0.153832[/C][C]-1.0878[/C][C]0.140959[/C][/ROW]
[ROW][C]17[/C][C]-0.164404[/C][C]-1.1625[/C][C]0.125274[/C][/ROW]
[ROW][C]18[/C][C]-0.305984[/C][C]-2.1636[/C][C]0.017648[/C][/ROW]
[ROW][C]19[/C][C]-0.156843[/C][C]-1.109[/C][C]0.136358[/C][/ROW]
[ROW][C]20[/C][C]-0.156802[/C][C]-1.1088[/C][C]0.13642[/C][/ROW]
[ROW][C]21[/C][C]-0.094159[/C][C]-0.6658[/C][C]0.254298[/C][/ROW]
[ROW][C]22[/C][C]0.028186[/C][C]0.1993[/C][C]0.421415[/C][/ROW]
[ROW][C]23[/C][C]0.157476[/C][C]1.1135[/C][C]0.135404[/C][/ROW]
[ROW][C]24[/C][C]0.474589[/C][C]3.3558[/C][C]0.000759[/C][/ROW]
[ROW][C]25[/C][C]0.189883[/C][C]1.3427[/C][C]0.09272[/C][/ROW]
[ROW][C]26[/C][C]0.054908[/C][C]0.3883[/C][C]0.349735[/C][/ROW]
[ROW][C]27[/C][C]-0.005878[/C][C]-0.0416[/C][C]0.483507[/C][/ROW]
[ROW][C]28[/C][C]-0.071468[/C][C]-0.5054[/C][C]0.307765[/C][/ROW]
[ROW][C]29[/C][C]-0.103189[/C][C]-0.7297[/C][C]0.234503[/C][/ROW]
[ROW][C]30[/C][C]-0.208994[/C][C]-1.4778[/C][C]0.072865[/C][/ROW]
[ROW][C]31[/C][C]-0.108685[/C][C]-0.7685[/C][C]0.222896[/C][/ROW]
[ROW][C]32[/C][C]-0.13159[/C][C]-0.9305[/C][C]0.178297[/C][/ROW]
[ROW][C]33[/C][C]-0.126068[/C][C]-0.8914[/C][C]0.188483[/C][/ROW]
[ROW][C]34[/C][C]-0.027476[/C][C]-0.1943[/C][C]0.423371[/C][/ROW]
[ROW][C]35[/C][C]0.043401[/C][C]0.3069[/C][C]0.380101[/C][/ROW]
[ROW][C]36[/C][C]0.279586[/C][C]1.977[/C][C]0.026786[/C][/ROW]
[ROW][C]37[/C][C]0.103563[/C][C]0.7323[/C][C]0.233701[/C][/ROW]
[ROW][C]38[/C][C]0.006627[/C][C]0.0469[/C][C]0.481406[/C][/ROW]
[ROW][C]39[/C][C]-0.038604[/C][C]-0.273[/C][C]0.392999[/C][/ROW]
[ROW][C]40[/C][C]-0.030039[/C][C]-0.2124[/C][C]0.416326[/C][/ROW]
[ROW][C]41[/C][C]-0.067125[/C][C]-0.4746[/C][C]0.318553[/C][/ROW]
[ROW][C]42[/C][C]-0.07904[/C][C]-0.5589[/C][C]0.289364[/C][/ROW]
[ROW][C]43[/C][C]-0.025774[/C][C]-0.1822[/C][C]0.428062[/C][/ROW]
[ROW][C]44[/C][C]-0.024317[/C][C]-0.1719[/C][C]0.432086[/C][/ROW]
[ROW][C]45[/C][C]-0.02723[/C][C]-0.1925[/C][C]0.424047[/C][/ROW]
[ROW][C]46[/C][C]-0.034038[/C][C]-0.2407[/C][C]0.405391[/C][/ROW]
[ROW][C]47[/C][C]-0.026861[/C][C]-0.1899[/C][C]0.425063[/C][/ROW]
[ROW][C]48[/C][C]0.095239[/C][C]0.6734[/C][C]0.251884[/C][/ROW]
[ROW][C]49[/C][C]0.037833[/C][C]0.2675[/C][C]0.395086[/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=68036&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68036&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
10.3652312.58260.00639
20.1320420.93370.177479
3-0.069899-0.49430.311643
4-0.204883-1.44870.076826
5-0.228199-1.61360.056453
6-0.40702-2.87810.002936
7-0.242258-1.7130.046452
8-0.207109-1.46450.074661
9-0.103161-0.72950.234563
10-0.005178-0.03660.48547
110.1817821.28540.102288
120.6511734.60451.4e-05
130.2600611.83890.035935
140.1139420.80570.212118
15-0.039416-0.27870.390806
16-0.153832-1.08780.140959
17-0.164404-1.16250.125274
18-0.305984-2.16360.017648
19-0.156843-1.1090.136358
20-0.156802-1.10880.13642
21-0.094159-0.66580.254298
220.0281860.19930.421415
230.1574761.11350.135404
240.4745893.35580.000759
250.1898831.34270.09272
260.0549080.38830.349735
27-0.005878-0.04160.483507
28-0.071468-0.50540.307765
29-0.103189-0.72970.234503
30-0.208994-1.47780.072865
31-0.108685-0.76850.222896
32-0.13159-0.93050.178297
33-0.126068-0.89140.188483
34-0.027476-0.19430.423371
350.0434010.30690.380101
360.2795861.9770.026786
370.1035630.73230.233701
380.0066270.04690.481406
39-0.038604-0.2730.392999
40-0.030039-0.21240.416326
41-0.067125-0.47460.318553
42-0.07904-0.55890.289364
43-0.025774-0.18220.428062
44-0.024317-0.17190.432086
45-0.02723-0.19250.424047
46-0.034038-0.24070.405391
47-0.026861-0.18990.425063
480.0952390.67340.251884
490.0378330.26750.395086
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.3652312.58260.00639
2-0.00156-0.0110.495623
3-0.135737-0.95980.170885
4-0.160002-1.13140.131645
5-0.102803-0.72690.23533
6-0.333486-2.35810.01116
7-0.03799-0.26860.394661
8-0.17218-1.21750.114564
9-0.129477-0.91550.182152
10-0.124159-0.87790.192089
110.0851270.60190.274967
120.5454943.85720.000164
13-0.28637-2.02490.024115
14-0.095463-0.6750.251384
150.016610.11750.453486
16-0.049132-0.34740.364869
17-0.034082-0.2410.405272
180.0326580.23090.409157
190.0219680.15530.438591
20-0.091028-0.64370.261368
21-0.045556-0.32210.374349
220.1830491.29440.100745
230.0124840.08830.465006
24-0.053551-0.37870.353271
25-0.024494-0.17320.431596
26-0.074568-0.52730.300167
270.0811480.57380.284338
280.1118470.79090.216375
29-0.020559-0.14540.4425
300.0062860.04440.482362
31-0.03857-0.27270.393093
320.001860.01320.49478
33-0.030067-0.21260.41625
34-0.028662-0.20270.420107
35-0.097965-0.69270.245846
36-0.093853-0.66360.254984
37-0.005501-0.03890.484563
380.0151330.1070.457606
39-0.157341-1.11260.135607
400.0275090.19450.423279
41-0.098439-0.69610.244804
420.0441610.31230.37807
43-0.031052-0.21960.41355
440.0697070.49290.31212
450.0325010.22980.409587
46-0.196652-1.39050.085262
47-0.08947-0.63260.264924
48-0.0253-0.17890.429372
490.0266760.18860.425574
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 & 0.365231 & 2.5826 & 0.00639 \tabularnewline
2 & -0.00156 & -0.011 & 0.495623 \tabularnewline
3 & -0.135737 & -0.9598 & 0.170885 \tabularnewline
4 & -0.160002 & -1.1314 & 0.131645 \tabularnewline
5 & -0.102803 & -0.7269 & 0.23533 \tabularnewline
6 & -0.333486 & -2.3581 & 0.01116 \tabularnewline
7 & -0.03799 & -0.2686 & 0.394661 \tabularnewline
8 & -0.17218 & -1.2175 & 0.114564 \tabularnewline
9 & -0.129477 & -0.9155 & 0.182152 \tabularnewline
10 & -0.124159 & -0.8779 & 0.192089 \tabularnewline
11 & 0.085127 & 0.6019 & 0.274967 \tabularnewline
12 & 0.545494 & 3.8572 & 0.000164 \tabularnewline
13 & -0.28637 & -2.0249 & 0.024115 \tabularnewline
14 & -0.095463 & -0.675 & 0.251384 \tabularnewline
15 & 0.01661 & 0.1175 & 0.453486 \tabularnewline
16 & -0.049132 & -0.3474 & 0.364869 \tabularnewline
17 & -0.034082 & -0.241 & 0.405272 \tabularnewline
18 & 0.032658 & 0.2309 & 0.409157 \tabularnewline
19 & 0.021968 & 0.1553 & 0.438591 \tabularnewline
20 & -0.091028 & -0.6437 & 0.261368 \tabularnewline
21 & -0.045556 & -0.3221 & 0.374349 \tabularnewline
22 & 0.183049 & 1.2944 & 0.100745 \tabularnewline
23 & 0.012484 & 0.0883 & 0.465006 \tabularnewline
24 & -0.053551 & -0.3787 & 0.353271 \tabularnewline
25 & -0.024494 & -0.1732 & 0.431596 \tabularnewline
26 & -0.074568 & -0.5273 & 0.300167 \tabularnewline
27 & 0.081148 & 0.5738 & 0.284338 \tabularnewline
28 & 0.111847 & 0.7909 & 0.216375 \tabularnewline
29 & -0.020559 & -0.1454 & 0.4425 \tabularnewline
30 & 0.006286 & 0.0444 & 0.482362 \tabularnewline
31 & -0.03857 & -0.2727 & 0.393093 \tabularnewline
32 & 0.00186 & 0.0132 & 0.49478 \tabularnewline
33 & -0.030067 & -0.2126 & 0.41625 \tabularnewline
34 & -0.028662 & -0.2027 & 0.420107 \tabularnewline
35 & -0.097965 & -0.6927 & 0.245846 \tabularnewline
36 & -0.093853 & -0.6636 & 0.254984 \tabularnewline
37 & -0.005501 & -0.0389 & 0.484563 \tabularnewline
38 & 0.015133 & 0.107 & 0.457606 \tabularnewline
39 & -0.157341 & -1.1126 & 0.135607 \tabularnewline
40 & 0.027509 & 0.1945 & 0.423279 \tabularnewline
41 & -0.098439 & -0.6961 & 0.244804 \tabularnewline
42 & 0.044161 & 0.3123 & 0.37807 \tabularnewline
43 & -0.031052 & -0.2196 & 0.41355 \tabularnewline
44 & 0.069707 & 0.4929 & 0.31212 \tabularnewline
45 & 0.032501 & 0.2298 & 0.409587 \tabularnewline
46 & -0.196652 & -1.3905 & 0.085262 \tabularnewline
47 & -0.08947 & -0.6326 & 0.264924 \tabularnewline
48 & -0.0253 & -0.1789 & 0.429372 \tabularnewline
49 & 0.026676 & 0.1886 & 0.425574 \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=68036&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]0.365231[/C][C]2.5826[/C][C]0.00639[/C][/ROW]
[ROW][C]2[/C][C]-0.00156[/C][C]-0.011[/C][C]0.495623[/C][/ROW]
[ROW][C]3[/C][C]-0.135737[/C][C]-0.9598[/C][C]0.170885[/C][/ROW]
[ROW][C]4[/C][C]-0.160002[/C][C]-1.1314[/C][C]0.131645[/C][/ROW]
[ROW][C]5[/C][C]-0.102803[/C][C]-0.7269[/C][C]0.23533[/C][/ROW]
[ROW][C]6[/C][C]-0.333486[/C][C]-2.3581[/C][C]0.01116[/C][/ROW]
[ROW][C]7[/C][C]-0.03799[/C][C]-0.2686[/C][C]0.394661[/C][/ROW]
[ROW][C]8[/C][C]-0.17218[/C][C]-1.2175[/C][C]0.114564[/C][/ROW]
[ROW][C]9[/C][C]-0.129477[/C][C]-0.9155[/C][C]0.182152[/C][/ROW]
[ROW][C]10[/C][C]-0.124159[/C][C]-0.8779[/C][C]0.192089[/C][/ROW]
[ROW][C]11[/C][C]0.085127[/C][C]0.6019[/C][C]0.274967[/C][/ROW]
[ROW][C]12[/C][C]0.545494[/C][C]3.8572[/C][C]0.000164[/C][/ROW]
[ROW][C]13[/C][C]-0.28637[/C][C]-2.0249[/C][C]0.024115[/C][/ROW]
[ROW][C]14[/C][C]-0.095463[/C][C]-0.675[/C][C]0.251384[/C][/ROW]
[ROW][C]15[/C][C]0.01661[/C][C]0.1175[/C][C]0.453486[/C][/ROW]
[ROW][C]16[/C][C]-0.049132[/C][C]-0.3474[/C][C]0.364869[/C][/ROW]
[ROW][C]17[/C][C]-0.034082[/C][C]-0.241[/C][C]0.405272[/C][/ROW]
[ROW][C]18[/C][C]0.032658[/C][C]0.2309[/C][C]0.409157[/C][/ROW]
[ROW][C]19[/C][C]0.021968[/C][C]0.1553[/C][C]0.438591[/C][/ROW]
[ROW][C]20[/C][C]-0.091028[/C][C]-0.6437[/C][C]0.261368[/C][/ROW]
[ROW][C]21[/C][C]-0.045556[/C][C]-0.3221[/C][C]0.374349[/C][/ROW]
[ROW][C]22[/C][C]0.183049[/C][C]1.2944[/C][C]0.100745[/C][/ROW]
[ROW][C]23[/C][C]0.012484[/C][C]0.0883[/C][C]0.465006[/C][/ROW]
[ROW][C]24[/C][C]-0.053551[/C][C]-0.3787[/C][C]0.353271[/C][/ROW]
[ROW][C]25[/C][C]-0.024494[/C][C]-0.1732[/C][C]0.431596[/C][/ROW]
[ROW][C]26[/C][C]-0.074568[/C][C]-0.5273[/C][C]0.300167[/C][/ROW]
[ROW][C]27[/C][C]0.081148[/C][C]0.5738[/C][C]0.284338[/C][/ROW]
[ROW][C]28[/C][C]0.111847[/C][C]0.7909[/C][C]0.216375[/C][/ROW]
[ROW][C]29[/C][C]-0.020559[/C][C]-0.1454[/C][C]0.4425[/C][/ROW]
[ROW][C]30[/C][C]0.006286[/C][C]0.0444[/C][C]0.482362[/C][/ROW]
[ROW][C]31[/C][C]-0.03857[/C][C]-0.2727[/C][C]0.393093[/C][/ROW]
[ROW][C]32[/C][C]0.00186[/C][C]0.0132[/C][C]0.49478[/C][/ROW]
[ROW][C]33[/C][C]-0.030067[/C][C]-0.2126[/C][C]0.41625[/C][/ROW]
[ROW][C]34[/C][C]-0.028662[/C][C]-0.2027[/C][C]0.420107[/C][/ROW]
[ROW][C]35[/C][C]-0.097965[/C][C]-0.6927[/C][C]0.245846[/C][/ROW]
[ROW][C]36[/C][C]-0.093853[/C][C]-0.6636[/C][C]0.254984[/C][/ROW]
[ROW][C]37[/C][C]-0.005501[/C][C]-0.0389[/C][C]0.484563[/C][/ROW]
[ROW][C]38[/C][C]0.015133[/C][C]0.107[/C][C]0.457606[/C][/ROW]
[ROW][C]39[/C][C]-0.157341[/C][C]-1.1126[/C][C]0.135607[/C][/ROW]
[ROW][C]40[/C][C]0.027509[/C][C]0.1945[/C][C]0.423279[/C][/ROW]
[ROW][C]41[/C][C]-0.098439[/C][C]-0.6961[/C][C]0.244804[/C][/ROW]
[ROW][C]42[/C][C]0.044161[/C][C]0.3123[/C][C]0.37807[/C][/ROW]
[ROW][C]43[/C][C]-0.031052[/C][C]-0.2196[/C][C]0.41355[/C][/ROW]
[ROW][C]44[/C][C]0.069707[/C][C]0.4929[/C][C]0.31212[/C][/ROW]
[ROW][C]45[/C][C]0.032501[/C][C]0.2298[/C][C]0.409587[/C][/ROW]
[ROW][C]46[/C][C]-0.196652[/C][C]-1.3905[/C][C]0.085262[/C][/ROW]
[ROW][C]47[/C][C]-0.08947[/C][C]-0.6326[/C][C]0.264924[/C][/ROW]
[ROW][C]48[/C][C]-0.0253[/C][C]-0.1789[/C][C]0.429372[/C][/ROW]
[ROW][C]49[/C][C]0.026676[/C][C]0.1886[/C][C]0.425574[/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=68036&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68036&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
10.3652312.58260.00639
2-0.00156-0.0110.495623
3-0.135737-0.95980.170885
4-0.160002-1.13140.131645
5-0.102803-0.72690.23533
6-0.333486-2.35810.01116
7-0.03799-0.26860.394661
8-0.17218-1.21750.114564
9-0.129477-0.91550.182152
10-0.124159-0.87790.192089
110.0851270.60190.274967
120.5454943.85720.000164
13-0.28637-2.02490.024115
14-0.095463-0.6750.251384
150.016610.11750.453486
16-0.049132-0.34740.364869
17-0.034082-0.2410.405272
180.0326580.23090.409157
190.0219680.15530.438591
20-0.091028-0.64370.261368
21-0.045556-0.32210.374349
220.1830491.29440.100745
230.0124840.08830.465006
24-0.053551-0.37870.353271
25-0.024494-0.17320.431596
26-0.074568-0.52730.300167
270.0811480.57380.284338
280.1118470.79090.216375
29-0.020559-0.14540.4425
300.0062860.04440.482362
31-0.03857-0.27270.393093
320.001860.01320.49478
33-0.030067-0.21260.41625
34-0.028662-0.20270.420107
35-0.097965-0.69270.245846
36-0.093853-0.66360.254984
37-0.005501-0.03890.484563
380.0151330.1070.457606
39-0.157341-1.11260.135607
400.0275090.19450.423279
41-0.098439-0.69610.244804
420.0441610.31230.37807
43-0.031052-0.21960.41355
440.0697070.49290.31212
450.0325010.22980.409587
46-0.196652-1.39050.085262
47-0.08947-0.63260.264924
48-0.0253-0.17890.429372
490.0266760.18860.425574
50NANANA
51NANANA
52NANANA
53NANANA
54NANANA
55NANANA
56NANANA
57NANANA
58NANANA
59NANANA
60NANANA



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