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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationWed, 23 Nov 2011 09:35:43 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/23/t132205899394jqtfgsmolvxqj.htm/, Retrieved Fri, 29 Mar 2024 11:46:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146527, Retrieved Fri, 29 Mar 2024 11:46:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W12
Estimated Impact80
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [(Partial) Autocorrelation Function] [Autocorrelatie pr...] [2011-11-23 14:35:43] [659094c92b72720b61457cd096818e91] [Current]
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Dataseries X:
31,5
31,29
31,3
31,06
31,09
31,11
31,13
31,1
31,03
30,74
30,83
30,82
30,8
30,74
30,71
30,58
30,71
30,7
30,7
30,72
30,68
30,78
30,84
30,8
30,8
30,88
30,87
30,92
30,82
30,75
30,75
30,75
30,63
30,52
30,58
30,6
30,6
30,63
30,56
30,61
30,53
30,6
30,6
30,63
30,66
30,34
30,32
30,3
30,3
30,08
29,96
29,91
29,83
29,89
29,85
30,06
29,83
29,95
30,02
30,03




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146527&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146527&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146527&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' @ jenkins.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.903566.99890
20.8360396.47590
30.7514925.8210
40.6857125.31151e-06
50.6235574.835e-06
60.5373324.16225.1e-05
70.4432493.43340.000543
80.3477422.69360.004576
90.2685272.080.020903
100.2209931.71180.046049
110.1814961.40590.082462
120.1496631.15930.125467
130.1189560.92140.180258
140.1016980.78770.216972
150.0805630.6240.267484
160.1000610.77510.22067
170.0995390.7710.22186
180.092190.71410.238966
190.0844580.65420.257739
200.0676040.52370.301224
210.0571580.44270.329772
220.0300710.23290.408305
230.0063390.04910.480501
24-0.019758-0.1530.439439
25-0.042078-0.32590.372803
26-0.075033-0.58120.28164
27-0.107345-0.83150.204497
28-0.137294-1.06350.145914
29-0.149534-1.15830.125669
30-0.151251-1.17160.122998
31-0.158577-1.22830.112059
32-0.164275-1.27250.104058
33-0.155443-1.20410.116648
34-0.137778-1.06720.145074
35-0.125552-0.97250.167348
36-0.116885-0.90540.18444
37-0.12026-0.93150.177656
38-0.134157-1.03920.151446
39-0.143461-1.11120.135448
40-0.167958-1.3010.099117
41-0.178511-1.38270.085935
42-0.204728-1.58580.059019
43-0.239727-1.85690.034117
44-0.279711-2.16660.017122
45-0.335645-2.59990.005861
46-0.354069-2.74260.004012
47-0.365004-2.82730.003185
48-0.379795-2.94190.002315
49-0.397281-3.07730.001573
50-0.39578-3.06570.001627
51-0.386389-2.9930.002004
52-0.356704-2.7630.003796
53-0.307416-2.38120.010222
54-0.269843-2.09020.020423
55-0.221647-1.71690.045581
56-0.19882-1.54010.064402
57-0.152538-1.18160.121022
58-0.101018-0.78250.218504
59-0.05673-0.43940.330966
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.90356 & 6.9989 & 0 \tabularnewline
2 & 0.836039 & 6.4759 & 0 \tabularnewline
3 & 0.751492 & 5.821 & 0 \tabularnewline
4 & 0.685712 & 5.3115 & 1e-06 \tabularnewline
5 & 0.623557 & 4.83 & 5e-06 \tabularnewline
6 & 0.537332 & 4.1622 & 5.1e-05 \tabularnewline
7 & 0.443249 & 3.4334 & 0.000543 \tabularnewline
8 & 0.347742 & 2.6936 & 0.004576 \tabularnewline
9 & 0.268527 & 2.08 & 0.020903 \tabularnewline
10 & 0.220993 & 1.7118 & 0.046049 \tabularnewline
11 & 0.181496 & 1.4059 & 0.082462 \tabularnewline
12 & 0.149663 & 1.1593 & 0.125467 \tabularnewline
13 & 0.118956 & 0.9214 & 0.180258 \tabularnewline
14 & 0.101698 & 0.7877 & 0.216972 \tabularnewline
15 & 0.080563 & 0.624 & 0.267484 \tabularnewline
16 & 0.100061 & 0.7751 & 0.22067 \tabularnewline
17 & 0.099539 & 0.771 & 0.22186 \tabularnewline
18 & 0.09219 & 0.7141 & 0.238966 \tabularnewline
19 & 0.084458 & 0.6542 & 0.257739 \tabularnewline
20 & 0.067604 & 0.5237 & 0.301224 \tabularnewline
21 & 0.057158 & 0.4427 & 0.329772 \tabularnewline
22 & 0.030071 & 0.2329 & 0.408305 \tabularnewline
23 & 0.006339 & 0.0491 & 0.480501 \tabularnewline
24 & -0.019758 & -0.153 & 0.439439 \tabularnewline
25 & -0.042078 & -0.3259 & 0.372803 \tabularnewline
26 & -0.075033 & -0.5812 & 0.28164 \tabularnewline
27 & -0.107345 & -0.8315 & 0.204497 \tabularnewline
28 & -0.137294 & -1.0635 & 0.145914 \tabularnewline
29 & -0.149534 & -1.1583 & 0.125669 \tabularnewline
30 & -0.151251 & -1.1716 & 0.122998 \tabularnewline
31 & -0.158577 & -1.2283 & 0.112059 \tabularnewline
32 & -0.164275 & -1.2725 & 0.104058 \tabularnewline
33 & -0.155443 & -1.2041 & 0.116648 \tabularnewline
34 & -0.137778 & -1.0672 & 0.145074 \tabularnewline
35 & -0.125552 & -0.9725 & 0.167348 \tabularnewline
36 & -0.116885 & -0.9054 & 0.18444 \tabularnewline
37 & -0.12026 & -0.9315 & 0.177656 \tabularnewline
38 & -0.134157 & -1.0392 & 0.151446 \tabularnewline
39 & -0.143461 & -1.1112 & 0.135448 \tabularnewline
40 & -0.167958 & -1.301 & 0.099117 \tabularnewline
41 & -0.178511 & -1.3827 & 0.085935 \tabularnewline
42 & -0.204728 & -1.5858 & 0.059019 \tabularnewline
43 & -0.239727 & -1.8569 & 0.034117 \tabularnewline
44 & -0.279711 & -2.1666 & 0.017122 \tabularnewline
45 & -0.335645 & -2.5999 & 0.005861 \tabularnewline
46 & -0.354069 & -2.7426 & 0.004012 \tabularnewline
47 & -0.365004 & -2.8273 & 0.003185 \tabularnewline
48 & -0.379795 & -2.9419 & 0.002315 \tabularnewline
49 & -0.397281 & -3.0773 & 0.001573 \tabularnewline
50 & -0.39578 & -3.0657 & 0.001627 \tabularnewline
51 & -0.386389 & -2.993 & 0.002004 \tabularnewline
52 & -0.356704 & -2.763 & 0.003796 \tabularnewline
53 & -0.307416 & -2.3812 & 0.010222 \tabularnewline
54 & -0.269843 & -2.0902 & 0.020423 \tabularnewline
55 & -0.221647 & -1.7169 & 0.045581 \tabularnewline
56 & -0.19882 & -1.5401 & 0.064402 \tabularnewline
57 & -0.152538 & -1.1816 & 0.121022 \tabularnewline
58 & -0.101018 & -0.7825 & 0.218504 \tabularnewline
59 & -0.05673 & -0.4394 & 0.330966 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146527&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]0.90356[/C][C]6.9989[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.836039[/C][C]6.4759[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.751492[/C][C]5.821[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.685712[/C][C]5.3115[/C][C]1e-06[/C][/ROW]
[ROW][C]5[/C][C]0.623557[/C][C]4.83[/C][C]5e-06[/C][/ROW]
[ROW][C]6[/C][C]0.537332[/C][C]4.1622[/C][C]5.1e-05[/C][/ROW]
[ROW][C]7[/C][C]0.443249[/C][C]3.4334[/C][C]0.000543[/C][/ROW]
[ROW][C]8[/C][C]0.347742[/C][C]2.6936[/C][C]0.004576[/C][/ROW]
[ROW][C]9[/C][C]0.268527[/C][C]2.08[/C][C]0.020903[/C][/ROW]
[ROW][C]10[/C][C]0.220993[/C][C]1.7118[/C][C]0.046049[/C][/ROW]
[ROW][C]11[/C][C]0.181496[/C][C]1.4059[/C][C]0.082462[/C][/ROW]
[ROW][C]12[/C][C]0.149663[/C][C]1.1593[/C][C]0.125467[/C][/ROW]
[ROW][C]13[/C][C]0.118956[/C][C]0.9214[/C][C]0.180258[/C][/ROW]
[ROW][C]14[/C][C]0.101698[/C][C]0.7877[/C][C]0.216972[/C][/ROW]
[ROW][C]15[/C][C]0.080563[/C][C]0.624[/C][C]0.267484[/C][/ROW]
[ROW][C]16[/C][C]0.100061[/C][C]0.7751[/C][C]0.22067[/C][/ROW]
[ROW][C]17[/C][C]0.099539[/C][C]0.771[/C][C]0.22186[/C][/ROW]
[ROW][C]18[/C][C]0.09219[/C][C]0.7141[/C][C]0.238966[/C][/ROW]
[ROW][C]19[/C][C]0.084458[/C][C]0.6542[/C][C]0.257739[/C][/ROW]
[ROW][C]20[/C][C]0.067604[/C][C]0.5237[/C][C]0.301224[/C][/ROW]
[ROW][C]21[/C][C]0.057158[/C][C]0.4427[/C][C]0.329772[/C][/ROW]
[ROW][C]22[/C][C]0.030071[/C][C]0.2329[/C][C]0.408305[/C][/ROW]
[ROW][C]23[/C][C]0.006339[/C][C]0.0491[/C][C]0.480501[/C][/ROW]
[ROW][C]24[/C][C]-0.019758[/C][C]-0.153[/C][C]0.439439[/C][/ROW]
[ROW][C]25[/C][C]-0.042078[/C][C]-0.3259[/C][C]0.372803[/C][/ROW]
[ROW][C]26[/C][C]-0.075033[/C][C]-0.5812[/C][C]0.28164[/C][/ROW]
[ROW][C]27[/C][C]-0.107345[/C][C]-0.8315[/C][C]0.204497[/C][/ROW]
[ROW][C]28[/C][C]-0.137294[/C][C]-1.0635[/C][C]0.145914[/C][/ROW]
[ROW][C]29[/C][C]-0.149534[/C][C]-1.1583[/C][C]0.125669[/C][/ROW]
[ROW][C]30[/C][C]-0.151251[/C][C]-1.1716[/C][C]0.122998[/C][/ROW]
[ROW][C]31[/C][C]-0.158577[/C][C]-1.2283[/C][C]0.112059[/C][/ROW]
[ROW][C]32[/C][C]-0.164275[/C][C]-1.2725[/C][C]0.104058[/C][/ROW]
[ROW][C]33[/C][C]-0.155443[/C][C]-1.2041[/C][C]0.116648[/C][/ROW]
[ROW][C]34[/C][C]-0.137778[/C][C]-1.0672[/C][C]0.145074[/C][/ROW]
[ROW][C]35[/C][C]-0.125552[/C][C]-0.9725[/C][C]0.167348[/C][/ROW]
[ROW][C]36[/C][C]-0.116885[/C][C]-0.9054[/C][C]0.18444[/C][/ROW]
[ROW][C]37[/C][C]-0.12026[/C][C]-0.9315[/C][C]0.177656[/C][/ROW]
[ROW][C]38[/C][C]-0.134157[/C][C]-1.0392[/C][C]0.151446[/C][/ROW]
[ROW][C]39[/C][C]-0.143461[/C][C]-1.1112[/C][C]0.135448[/C][/ROW]
[ROW][C]40[/C][C]-0.167958[/C][C]-1.301[/C][C]0.099117[/C][/ROW]
[ROW][C]41[/C][C]-0.178511[/C][C]-1.3827[/C][C]0.085935[/C][/ROW]
[ROW][C]42[/C][C]-0.204728[/C][C]-1.5858[/C][C]0.059019[/C][/ROW]
[ROW][C]43[/C][C]-0.239727[/C][C]-1.8569[/C][C]0.034117[/C][/ROW]
[ROW][C]44[/C][C]-0.279711[/C][C]-2.1666[/C][C]0.017122[/C][/ROW]
[ROW][C]45[/C][C]-0.335645[/C][C]-2.5999[/C][C]0.005861[/C][/ROW]
[ROW][C]46[/C][C]-0.354069[/C][C]-2.7426[/C][C]0.004012[/C][/ROW]
[ROW][C]47[/C][C]-0.365004[/C][C]-2.8273[/C][C]0.003185[/C][/ROW]
[ROW][C]48[/C][C]-0.379795[/C][C]-2.9419[/C][C]0.002315[/C][/ROW]
[ROW][C]49[/C][C]-0.397281[/C][C]-3.0773[/C][C]0.001573[/C][/ROW]
[ROW][C]50[/C][C]-0.39578[/C][C]-3.0657[/C][C]0.001627[/C][/ROW]
[ROW][C]51[/C][C]-0.386389[/C][C]-2.993[/C][C]0.002004[/C][/ROW]
[ROW][C]52[/C][C]-0.356704[/C][C]-2.763[/C][C]0.003796[/C][/ROW]
[ROW][C]53[/C][C]-0.307416[/C][C]-2.3812[/C][C]0.010222[/C][/ROW]
[ROW][C]54[/C][C]-0.269843[/C][C]-2.0902[/C][C]0.020423[/C][/ROW]
[ROW][C]55[/C][C]-0.221647[/C][C]-1.7169[/C][C]0.045581[/C][/ROW]
[ROW][C]56[/C][C]-0.19882[/C][C]-1.5401[/C][C]0.064402[/C][/ROW]
[ROW][C]57[/C][C]-0.152538[/C][C]-1.1816[/C][C]0.121022[/C][/ROW]
[ROW][C]58[/C][C]-0.101018[/C][C]-0.7825[/C][C]0.218504[/C][/ROW]
[ROW][C]59[/C][C]-0.05673[/C][C]-0.4394[/C][C]0.330966[/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=146527&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146527&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
10.903566.99890
20.8360396.47590
30.7514925.8210
40.6857125.31151e-06
50.6235574.835e-06
60.5373324.16225.1e-05
70.4432493.43340.000543
80.3477422.69360.004576
90.2685272.080.020903
100.2209931.71180.046049
110.1814961.40590.082462
120.1496631.15930.125467
130.1189560.92140.180258
140.1016980.78770.216972
150.0805630.6240.267484
160.1000610.77510.22067
170.0995390.7710.22186
180.092190.71410.238966
190.0844580.65420.257739
200.0676040.52370.301224
210.0571580.44270.329772
220.0300710.23290.408305
230.0063390.04910.480501
24-0.019758-0.1530.439439
25-0.042078-0.32590.372803
26-0.075033-0.58120.28164
27-0.107345-0.83150.204497
28-0.137294-1.06350.145914
29-0.149534-1.15830.125669
30-0.151251-1.17160.122998
31-0.158577-1.22830.112059
32-0.164275-1.27250.104058
33-0.155443-1.20410.116648
34-0.137778-1.06720.145074
35-0.125552-0.97250.167348
36-0.116885-0.90540.18444
37-0.12026-0.93150.177656
38-0.134157-1.03920.151446
39-0.143461-1.11120.135448
40-0.167958-1.3010.099117
41-0.178511-1.38270.085935
42-0.204728-1.58580.059019
43-0.239727-1.85690.034117
44-0.279711-2.16660.017122
45-0.335645-2.59990.005861
46-0.354069-2.74260.004012
47-0.365004-2.82730.003185
48-0.379795-2.94190.002315
49-0.397281-3.07730.001573
50-0.39578-3.06570.001627
51-0.386389-2.9930.002004
52-0.356704-2.7630.003796
53-0.307416-2.38120.010222
54-0.269843-2.09020.020423
55-0.221647-1.71690.045581
56-0.19882-1.54010.064402
57-0.152538-1.18160.121022
58-0.101018-0.78250.218504
59-0.05673-0.43940.330966
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.903566.99890
20.1068680.82780.205534
3-0.108839-0.84310.201271
40.0339230.26280.396816
50.0105380.08160.467608
6-0.176789-1.36940.087989
7-0.134146-1.03910.151466
8-0.064299-0.49810.310131
90.0079440.06150.475568
100.1258030.97450.166869
110.0591150.45790.324338
120.0315740.24460.403813
130.0175070.13560.446293
140.0425820.32980.371336
15-0.083015-0.6430.261326
160.1475991.14330.128728
17-0.069463-0.53810.296263
18-0.110321-0.85450.198102
190.0194660.15080.440327
20-0.039221-0.30380.381163
21-0.045743-0.35430.362168
22-0.086844-0.67270.251862
230.0025760.020.492074
240.0100240.07760.469185
250.0561660.43510.332539
26-0.087266-0.6760.250831
27-0.038406-0.29750.383561
280.0014230.0110.495622
290.0678870.52580.300466
300.0161240.12490.450512
31-0.025147-0.19480.423109
32-0.033373-0.25850.398451
330.0637960.49420.311499
340.0650010.50350.308231
35-0.109239-0.84620.200413
36-0.049747-0.38530.350673
37-0.086493-0.670.252722
38-0.080416-0.62290.267855
39-0.005847-0.04530.482012
40-0.098262-0.76110.224778
410.0111050.0860.46587
42-0.00974-0.07540.470056
43-0.053775-0.41650.33925
44-0.051381-0.3980.346024
45-0.142743-1.10570.13664
460.0743240.57570.283482
470.0743170.57570.283499
48-0.053442-0.4140.340189
49-0.069284-0.53670.296739
500.0693480.53720.29657
510.0049170.03810.484872
520.029740.23040.409296
530.1073540.83160.204477
54-0.059528-0.46110.323197
550.0208630.16160.436081
56-0.059285-0.45920.323869
570.0664290.51460.304375
580.0507150.39280.347918
59-0.007538-0.05840.476816
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.90356 & 6.9989 & 0 \tabularnewline
2 & 0.106868 & 0.8278 & 0.205534 \tabularnewline
3 & -0.108839 & -0.8431 & 0.201271 \tabularnewline
4 & 0.033923 & 0.2628 & 0.396816 \tabularnewline
5 & 0.010538 & 0.0816 & 0.467608 \tabularnewline
6 & -0.176789 & -1.3694 & 0.087989 \tabularnewline
7 & -0.134146 & -1.0391 & 0.151466 \tabularnewline
8 & -0.064299 & -0.4981 & 0.310131 \tabularnewline
9 & 0.007944 & 0.0615 & 0.475568 \tabularnewline
10 & 0.125803 & 0.9745 & 0.166869 \tabularnewline
11 & 0.059115 & 0.4579 & 0.324338 \tabularnewline
12 & 0.031574 & 0.2446 & 0.403813 \tabularnewline
13 & 0.017507 & 0.1356 & 0.446293 \tabularnewline
14 & 0.042582 & 0.3298 & 0.371336 \tabularnewline
15 & -0.083015 & -0.643 & 0.261326 \tabularnewline
16 & 0.147599 & 1.1433 & 0.128728 \tabularnewline
17 & -0.069463 & -0.5381 & 0.296263 \tabularnewline
18 & -0.110321 & -0.8545 & 0.198102 \tabularnewline
19 & 0.019466 & 0.1508 & 0.440327 \tabularnewline
20 & -0.039221 & -0.3038 & 0.381163 \tabularnewline
21 & -0.045743 & -0.3543 & 0.362168 \tabularnewline
22 & -0.086844 & -0.6727 & 0.251862 \tabularnewline
23 & 0.002576 & 0.02 & 0.492074 \tabularnewline
24 & 0.010024 & 0.0776 & 0.469185 \tabularnewline
25 & 0.056166 & 0.4351 & 0.332539 \tabularnewline
26 & -0.087266 & -0.676 & 0.250831 \tabularnewline
27 & -0.038406 & -0.2975 & 0.383561 \tabularnewline
28 & 0.001423 & 0.011 & 0.495622 \tabularnewline
29 & 0.067887 & 0.5258 & 0.300466 \tabularnewline
30 & 0.016124 & 0.1249 & 0.450512 \tabularnewline
31 & -0.025147 & -0.1948 & 0.423109 \tabularnewline
32 & -0.033373 & -0.2585 & 0.398451 \tabularnewline
33 & 0.063796 & 0.4942 & 0.311499 \tabularnewline
34 & 0.065001 & 0.5035 & 0.308231 \tabularnewline
35 & -0.109239 & -0.8462 & 0.200413 \tabularnewline
36 & -0.049747 & -0.3853 & 0.350673 \tabularnewline
37 & -0.086493 & -0.67 & 0.252722 \tabularnewline
38 & -0.080416 & -0.6229 & 0.267855 \tabularnewline
39 & -0.005847 & -0.0453 & 0.482012 \tabularnewline
40 & -0.098262 & -0.7611 & 0.224778 \tabularnewline
41 & 0.011105 & 0.086 & 0.46587 \tabularnewline
42 & -0.00974 & -0.0754 & 0.470056 \tabularnewline
43 & -0.053775 & -0.4165 & 0.33925 \tabularnewline
44 & -0.051381 & -0.398 & 0.346024 \tabularnewline
45 & -0.142743 & -1.1057 & 0.13664 \tabularnewline
46 & 0.074324 & 0.5757 & 0.283482 \tabularnewline
47 & 0.074317 & 0.5757 & 0.283499 \tabularnewline
48 & -0.053442 & -0.414 & 0.340189 \tabularnewline
49 & -0.069284 & -0.5367 & 0.296739 \tabularnewline
50 & 0.069348 & 0.5372 & 0.29657 \tabularnewline
51 & 0.004917 & 0.0381 & 0.484872 \tabularnewline
52 & 0.02974 & 0.2304 & 0.409296 \tabularnewline
53 & 0.107354 & 0.8316 & 0.204477 \tabularnewline
54 & -0.059528 & -0.4611 & 0.323197 \tabularnewline
55 & 0.020863 & 0.1616 & 0.436081 \tabularnewline
56 & -0.059285 & -0.4592 & 0.323869 \tabularnewline
57 & 0.066429 & 0.5146 & 0.304375 \tabularnewline
58 & 0.050715 & 0.3928 & 0.347918 \tabularnewline
59 & -0.007538 & -0.0584 & 0.476816 \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146527&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]0.90356[/C][C]6.9989[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.106868[/C][C]0.8278[/C][C]0.205534[/C][/ROW]
[ROW][C]3[/C][C]-0.108839[/C][C]-0.8431[/C][C]0.201271[/C][/ROW]
[ROW][C]4[/C][C]0.033923[/C][C]0.2628[/C][C]0.396816[/C][/ROW]
[ROW][C]5[/C][C]0.010538[/C][C]0.0816[/C][C]0.467608[/C][/ROW]
[ROW][C]6[/C][C]-0.176789[/C][C]-1.3694[/C][C]0.087989[/C][/ROW]
[ROW][C]7[/C][C]-0.134146[/C][C]-1.0391[/C][C]0.151466[/C][/ROW]
[ROW][C]8[/C][C]-0.064299[/C][C]-0.4981[/C][C]0.310131[/C][/ROW]
[ROW][C]9[/C][C]0.007944[/C][C]0.0615[/C][C]0.475568[/C][/ROW]
[ROW][C]10[/C][C]0.125803[/C][C]0.9745[/C][C]0.166869[/C][/ROW]
[ROW][C]11[/C][C]0.059115[/C][C]0.4579[/C][C]0.324338[/C][/ROW]
[ROW][C]12[/C][C]0.031574[/C][C]0.2446[/C][C]0.403813[/C][/ROW]
[ROW][C]13[/C][C]0.017507[/C][C]0.1356[/C][C]0.446293[/C][/ROW]
[ROW][C]14[/C][C]0.042582[/C][C]0.3298[/C][C]0.371336[/C][/ROW]
[ROW][C]15[/C][C]-0.083015[/C][C]-0.643[/C][C]0.261326[/C][/ROW]
[ROW][C]16[/C][C]0.147599[/C][C]1.1433[/C][C]0.128728[/C][/ROW]
[ROW][C]17[/C][C]-0.069463[/C][C]-0.5381[/C][C]0.296263[/C][/ROW]
[ROW][C]18[/C][C]-0.110321[/C][C]-0.8545[/C][C]0.198102[/C][/ROW]
[ROW][C]19[/C][C]0.019466[/C][C]0.1508[/C][C]0.440327[/C][/ROW]
[ROW][C]20[/C][C]-0.039221[/C][C]-0.3038[/C][C]0.381163[/C][/ROW]
[ROW][C]21[/C][C]-0.045743[/C][C]-0.3543[/C][C]0.362168[/C][/ROW]
[ROW][C]22[/C][C]-0.086844[/C][C]-0.6727[/C][C]0.251862[/C][/ROW]
[ROW][C]23[/C][C]0.002576[/C][C]0.02[/C][C]0.492074[/C][/ROW]
[ROW][C]24[/C][C]0.010024[/C][C]0.0776[/C][C]0.469185[/C][/ROW]
[ROW][C]25[/C][C]0.056166[/C][C]0.4351[/C][C]0.332539[/C][/ROW]
[ROW][C]26[/C][C]-0.087266[/C][C]-0.676[/C][C]0.250831[/C][/ROW]
[ROW][C]27[/C][C]-0.038406[/C][C]-0.2975[/C][C]0.383561[/C][/ROW]
[ROW][C]28[/C][C]0.001423[/C][C]0.011[/C][C]0.495622[/C][/ROW]
[ROW][C]29[/C][C]0.067887[/C][C]0.5258[/C][C]0.300466[/C][/ROW]
[ROW][C]30[/C][C]0.016124[/C][C]0.1249[/C][C]0.450512[/C][/ROW]
[ROW][C]31[/C][C]-0.025147[/C][C]-0.1948[/C][C]0.423109[/C][/ROW]
[ROW][C]32[/C][C]-0.033373[/C][C]-0.2585[/C][C]0.398451[/C][/ROW]
[ROW][C]33[/C][C]0.063796[/C][C]0.4942[/C][C]0.311499[/C][/ROW]
[ROW][C]34[/C][C]0.065001[/C][C]0.5035[/C][C]0.308231[/C][/ROW]
[ROW][C]35[/C][C]-0.109239[/C][C]-0.8462[/C][C]0.200413[/C][/ROW]
[ROW][C]36[/C][C]-0.049747[/C][C]-0.3853[/C][C]0.350673[/C][/ROW]
[ROW][C]37[/C][C]-0.086493[/C][C]-0.67[/C][C]0.252722[/C][/ROW]
[ROW][C]38[/C][C]-0.080416[/C][C]-0.6229[/C][C]0.267855[/C][/ROW]
[ROW][C]39[/C][C]-0.005847[/C][C]-0.0453[/C][C]0.482012[/C][/ROW]
[ROW][C]40[/C][C]-0.098262[/C][C]-0.7611[/C][C]0.224778[/C][/ROW]
[ROW][C]41[/C][C]0.011105[/C][C]0.086[/C][C]0.46587[/C][/ROW]
[ROW][C]42[/C][C]-0.00974[/C][C]-0.0754[/C][C]0.470056[/C][/ROW]
[ROW][C]43[/C][C]-0.053775[/C][C]-0.4165[/C][C]0.33925[/C][/ROW]
[ROW][C]44[/C][C]-0.051381[/C][C]-0.398[/C][C]0.346024[/C][/ROW]
[ROW][C]45[/C][C]-0.142743[/C][C]-1.1057[/C][C]0.13664[/C][/ROW]
[ROW][C]46[/C][C]0.074324[/C][C]0.5757[/C][C]0.283482[/C][/ROW]
[ROW][C]47[/C][C]0.074317[/C][C]0.5757[/C][C]0.283499[/C][/ROW]
[ROW][C]48[/C][C]-0.053442[/C][C]-0.414[/C][C]0.340189[/C][/ROW]
[ROW][C]49[/C][C]-0.069284[/C][C]-0.5367[/C][C]0.296739[/C][/ROW]
[ROW][C]50[/C][C]0.069348[/C][C]0.5372[/C][C]0.29657[/C][/ROW]
[ROW][C]51[/C][C]0.004917[/C][C]0.0381[/C][C]0.484872[/C][/ROW]
[ROW][C]52[/C][C]0.02974[/C][C]0.2304[/C][C]0.409296[/C][/ROW]
[ROW][C]53[/C][C]0.107354[/C][C]0.8316[/C][C]0.204477[/C][/ROW]
[ROW][C]54[/C][C]-0.059528[/C][C]-0.4611[/C][C]0.323197[/C][/ROW]
[ROW][C]55[/C][C]0.020863[/C][C]0.1616[/C][C]0.436081[/C][/ROW]
[ROW][C]56[/C][C]-0.059285[/C][C]-0.4592[/C][C]0.323869[/C][/ROW]
[ROW][C]57[/C][C]0.066429[/C][C]0.5146[/C][C]0.304375[/C][/ROW]
[ROW][C]58[/C][C]0.050715[/C][C]0.3928[/C][C]0.347918[/C][/ROW]
[ROW][C]59[/C][C]-0.007538[/C][C]-0.0584[/C][C]0.476816[/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=146527&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146527&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
10.903566.99890
20.1068680.82780.205534
3-0.108839-0.84310.201271
40.0339230.26280.396816
50.0105380.08160.467608
6-0.176789-1.36940.087989
7-0.134146-1.03910.151466
8-0.064299-0.49810.310131
90.0079440.06150.475568
100.1258030.97450.166869
110.0591150.45790.324338
120.0315740.24460.403813
130.0175070.13560.446293
140.0425820.32980.371336
15-0.083015-0.6430.261326
160.1475991.14330.128728
17-0.069463-0.53810.296263
18-0.110321-0.85450.198102
190.0194660.15080.440327
20-0.039221-0.30380.381163
21-0.045743-0.35430.362168
22-0.086844-0.67270.251862
230.0025760.020.492074
240.0100240.07760.469185
250.0561660.43510.332539
26-0.087266-0.6760.250831
27-0.038406-0.29750.383561
280.0014230.0110.495622
290.0678870.52580.300466
300.0161240.12490.450512
31-0.025147-0.19480.423109
32-0.033373-0.25850.398451
330.0637960.49420.311499
340.0650010.50350.308231
35-0.109239-0.84620.200413
36-0.049747-0.38530.350673
37-0.086493-0.670.252722
38-0.080416-0.62290.267855
39-0.005847-0.04530.482012
40-0.098262-0.76110.224778
410.0111050.0860.46587
42-0.00974-0.07540.470056
43-0.053775-0.41650.33925
44-0.051381-0.3980.346024
45-0.142743-1.10570.13664
460.0743240.57570.283482
470.0743170.57570.283499
48-0.053442-0.4140.340189
49-0.069284-0.53670.296739
500.0693480.53720.29657
510.0049170.03810.484872
520.029740.23040.409296
530.1073540.83160.204477
54-0.059528-0.46110.323197
550.0208630.16160.436081
56-0.059285-0.45920.323869
570.0664290.51460.304375
580.0507150.39280.347918
59-0.007538-0.05840.476816
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 ; par8 = ;
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 (par8 != '') par8 <- as.numeric(par8)
ox <- x
if (par8 == '') {
if (par2 == 0) {
x <- log(x)
} else {
x <- (x ^ par2 - 1) / par2
}
} else {
x <- log(x,base=par8)
}
if (par3 > 0) x <- diff(x,lag=1,difference=par3)
if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
bitmap(file='picts.png')
op <- par(mfrow=c(2,1))
plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
if (par8=='') {
mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
} else {
mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
}
plot(x,type='l', main=mytitle,xlab='time',ylab='value')
par(op)
dev.off()
bitmap(file='pic1.png')
racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
dev.off()
bitmap(file='pic2.png')
rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
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')