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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 16 Dec 2008 12:30:19 -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/2008/Dec/16/t1229455905xoq8l2nid9hvuvi.htm/, Retrieved Wed, 15 May 2024 10:28:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34144, Retrieved Wed, 15 May 2024 10:28:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordspaper autocor D,d 1,1 werk
Estimated Impact211
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [Paper: autocorrel...] [2008-12-05 10:20:24] [27f46dbe13ae2811dfd3a6f3c54d4d50]
F   PD  [(Partial) Autocorrelation Function] [Paper: autocorrel...] [2008-12-05 10:26:40] [27f46dbe13ae2811dfd3a6f3c54d4d50]
F   PD    [(Partial) Autocorrelation Function] [Paper: werklooshe...] [2008-12-05 10:43:32] [74be16979710d4c4e7c6647856088456]
-             [(Partial) Autocorrelation Function] [paper autocor D,d...] [2008-12-16 19:30:19] [e9c861930c027d1bae8828281431911e] [Current]
-    D          [(Partial) Autocorrelation Function] [paper auto D,d 1,...] [2008-12-18 14:18:44] [5de5fb433ddcb9578e0fa830f795b7e9]
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Dataseries X:
95.20
95.00
94.00
92.20
91.00
91.20
103.40
105.00
104.60
103.80
101.80
102.40
103.80
103.40
102.00
101.80
100.20
101.40
113.80
116.00
115.60
113.00
109.40
111.00
112.40
112.20
111.00
108.80
107.40
108.60
118.80
122.20
122.60
122.20
118.80
119.00
118.20
117.80
116.80
114.60
113.40
113.80
124.20
125.80
125.60
122.40
119.00
119.40
118.60
118.00
116.00
114.80
114.60
114.60
124.00
125.20
124.00
117.60
113.20
111.40
112.20
109.80
106.40
105.20
102.20
99.80
111.00
113.00
108.40
105.40
102.00
102.80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34144&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]2 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=34144&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34144&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.0043910.03370.486603
20.0220890.16970.432925
30.0060560.04650.481529
4-0.032179-0.24720.402816
5-0.056531-0.43420.332855
6-0.022048-0.16940.433048
7-0.042612-0.32730.372296
80.0053480.04110.483684
90.1381561.06120.146462
10-0.18081-1.38880.085053
110.0223510.17170.432139
12-0.257354-1.97680.026373
13-0.097089-0.74580.229389
140.1158470.88980.188583
150.0109390.0840.466661
160.0202780.15580.438378
17-0.087321-0.67070.252505
180.1537581.1810.121163
190.0728740.55980.288883
200.0835780.6420.261687
21-0.01736-0.13330.447189
220.0051260.03940.484364
230.1212620.93140.177712
24-0.13259-1.01840.156312
25-0.08443-0.64850.259583
26-0.213391-1.63910.053259
270.0664810.51070.305749
28-0.078534-0.60320.274333
290.1044420.80220.212819
30-0.126135-0.96890.168285
31-0.081025-0.62240.268049
320.0571070.43860.331259
33-0.064821-0.49790.310203
340.0027360.0210.491652
35-0.001351-0.01040.495878
360.0188430.14470.442705
370.0908220.69760.244077
380.1567911.20430.116634
39-0.127519-0.97950.165668
40-0.020409-0.15680.437983
41-0.005899-0.04530.482005
42-0.115047-0.88370.190224
430.075670.58120.281649
44-0.071734-0.5510.291859
45-0.048214-0.37030.356228
460.0315750.24250.404605
47-0.012768-0.09810.461105
48-0.036628-0.28130.389715
49-0.07448-0.57210.284716
50-0.039849-0.30610.380309
510.0305990.2350.407497
520.0839530.64490.26076
53-0.026274-0.20180.420377
540.0928160.71290.239349
550.0121720.09350.462915
560.0477570.36680.357529
57-0.001647-0.01270.494974
580.002230.01710.493195
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.004391 & 0.0337 & 0.486603 \tabularnewline
2 & 0.022089 & 0.1697 & 0.432925 \tabularnewline
3 & 0.006056 & 0.0465 & 0.481529 \tabularnewline
4 & -0.032179 & -0.2472 & 0.402816 \tabularnewline
5 & -0.056531 & -0.4342 & 0.332855 \tabularnewline
6 & -0.022048 & -0.1694 & 0.433048 \tabularnewline
7 & -0.042612 & -0.3273 & 0.372296 \tabularnewline
8 & 0.005348 & 0.0411 & 0.483684 \tabularnewline
9 & 0.138156 & 1.0612 & 0.146462 \tabularnewline
10 & -0.18081 & -1.3888 & 0.085053 \tabularnewline
11 & 0.022351 & 0.1717 & 0.432139 \tabularnewline
12 & -0.257354 & -1.9768 & 0.026373 \tabularnewline
13 & -0.097089 & -0.7458 & 0.229389 \tabularnewline
14 & 0.115847 & 0.8898 & 0.188583 \tabularnewline
15 & 0.010939 & 0.084 & 0.466661 \tabularnewline
16 & 0.020278 & 0.1558 & 0.438378 \tabularnewline
17 & -0.087321 & -0.6707 & 0.252505 \tabularnewline
18 & 0.153758 & 1.181 & 0.121163 \tabularnewline
19 & 0.072874 & 0.5598 & 0.288883 \tabularnewline
20 & 0.083578 & 0.642 & 0.261687 \tabularnewline
21 & -0.01736 & -0.1333 & 0.447189 \tabularnewline
22 & 0.005126 & 0.0394 & 0.484364 \tabularnewline
23 & 0.121262 & 0.9314 & 0.177712 \tabularnewline
24 & -0.13259 & -1.0184 & 0.156312 \tabularnewline
25 & -0.08443 & -0.6485 & 0.259583 \tabularnewline
26 & -0.213391 & -1.6391 & 0.053259 \tabularnewline
27 & 0.066481 & 0.5107 & 0.305749 \tabularnewline
28 & -0.078534 & -0.6032 & 0.274333 \tabularnewline
29 & 0.104442 & 0.8022 & 0.212819 \tabularnewline
30 & -0.126135 & -0.9689 & 0.168285 \tabularnewline
31 & -0.081025 & -0.6224 & 0.268049 \tabularnewline
32 & 0.057107 & 0.4386 & 0.331259 \tabularnewline
33 & -0.064821 & -0.4979 & 0.310203 \tabularnewline
34 & 0.002736 & 0.021 & 0.491652 \tabularnewline
35 & -0.001351 & -0.0104 & 0.495878 \tabularnewline
36 & 0.018843 & 0.1447 & 0.442705 \tabularnewline
37 & 0.090822 & 0.6976 & 0.244077 \tabularnewline
38 & 0.156791 & 1.2043 & 0.116634 \tabularnewline
39 & -0.127519 & -0.9795 & 0.165668 \tabularnewline
40 & -0.020409 & -0.1568 & 0.437983 \tabularnewline
41 & -0.005899 & -0.0453 & 0.482005 \tabularnewline
42 & -0.115047 & -0.8837 & 0.190224 \tabularnewline
43 & 0.07567 & 0.5812 & 0.281649 \tabularnewline
44 & -0.071734 & -0.551 & 0.291859 \tabularnewline
45 & -0.048214 & -0.3703 & 0.356228 \tabularnewline
46 & 0.031575 & 0.2425 & 0.404605 \tabularnewline
47 & -0.012768 & -0.0981 & 0.461105 \tabularnewline
48 & -0.036628 & -0.2813 & 0.389715 \tabularnewline
49 & -0.07448 & -0.5721 & 0.284716 \tabularnewline
50 & -0.039849 & -0.3061 & 0.380309 \tabularnewline
51 & 0.030599 & 0.235 & 0.407497 \tabularnewline
52 & 0.083953 & 0.6449 & 0.26076 \tabularnewline
53 & -0.026274 & -0.2018 & 0.420377 \tabularnewline
54 & 0.092816 & 0.7129 & 0.239349 \tabularnewline
55 & 0.012172 & 0.0935 & 0.462915 \tabularnewline
56 & 0.047757 & 0.3668 & 0.357529 \tabularnewline
57 & -0.001647 & -0.0127 & 0.494974 \tabularnewline
58 & 0.00223 & 0.0171 & 0.493195 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34144&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]0.004391[/C][C]0.0337[/C][C]0.486603[/C][/ROW]
[ROW][C]2[/C][C]0.022089[/C][C]0.1697[/C][C]0.432925[/C][/ROW]
[ROW][C]3[/C][C]0.006056[/C][C]0.0465[/C][C]0.481529[/C][/ROW]
[ROW][C]4[/C][C]-0.032179[/C][C]-0.2472[/C][C]0.402816[/C][/ROW]
[ROW][C]5[/C][C]-0.056531[/C][C]-0.4342[/C][C]0.332855[/C][/ROW]
[ROW][C]6[/C][C]-0.022048[/C][C]-0.1694[/C][C]0.433048[/C][/ROW]
[ROW][C]7[/C][C]-0.042612[/C][C]-0.3273[/C][C]0.372296[/C][/ROW]
[ROW][C]8[/C][C]0.005348[/C][C]0.0411[/C][C]0.483684[/C][/ROW]
[ROW][C]9[/C][C]0.138156[/C][C]1.0612[/C][C]0.146462[/C][/ROW]
[ROW][C]10[/C][C]-0.18081[/C][C]-1.3888[/C][C]0.085053[/C][/ROW]
[ROW][C]11[/C][C]0.022351[/C][C]0.1717[/C][C]0.432139[/C][/ROW]
[ROW][C]12[/C][C]-0.257354[/C][C]-1.9768[/C][C]0.026373[/C][/ROW]
[ROW][C]13[/C][C]-0.097089[/C][C]-0.7458[/C][C]0.229389[/C][/ROW]
[ROW][C]14[/C][C]0.115847[/C][C]0.8898[/C][C]0.188583[/C][/ROW]
[ROW][C]15[/C][C]0.010939[/C][C]0.084[/C][C]0.466661[/C][/ROW]
[ROW][C]16[/C][C]0.020278[/C][C]0.1558[/C][C]0.438378[/C][/ROW]
[ROW][C]17[/C][C]-0.087321[/C][C]-0.6707[/C][C]0.252505[/C][/ROW]
[ROW][C]18[/C][C]0.153758[/C][C]1.181[/C][C]0.121163[/C][/ROW]
[ROW][C]19[/C][C]0.072874[/C][C]0.5598[/C][C]0.288883[/C][/ROW]
[ROW][C]20[/C][C]0.083578[/C][C]0.642[/C][C]0.261687[/C][/ROW]
[ROW][C]21[/C][C]-0.01736[/C][C]-0.1333[/C][C]0.447189[/C][/ROW]
[ROW][C]22[/C][C]0.005126[/C][C]0.0394[/C][C]0.484364[/C][/ROW]
[ROW][C]23[/C][C]0.121262[/C][C]0.9314[/C][C]0.177712[/C][/ROW]
[ROW][C]24[/C][C]-0.13259[/C][C]-1.0184[/C][C]0.156312[/C][/ROW]
[ROW][C]25[/C][C]-0.08443[/C][C]-0.6485[/C][C]0.259583[/C][/ROW]
[ROW][C]26[/C][C]-0.213391[/C][C]-1.6391[/C][C]0.053259[/C][/ROW]
[ROW][C]27[/C][C]0.066481[/C][C]0.5107[/C][C]0.305749[/C][/ROW]
[ROW][C]28[/C][C]-0.078534[/C][C]-0.6032[/C][C]0.274333[/C][/ROW]
[ROW][C]29[/C][C]0.104442[/C][C]0.8022[/C][C]0.212819[/C][/ROW]
[ROW][C]30[/C][C]-0.126135[/C][C]-0.9689[/C][C]0.168285[/C][/ROW]
[ROW][C]31[/C][C]-0.081025[/C][C]-0.6224[/C][C]0.268049[/C][/ROW]
[ROW][C]32[/C][C]0.057107[/C][C]0.4386[/C][C]0.331259[/C][/ROW]
[ROW][C]33[/C][C]-0.064821[/C][C]-0.4979[/C][C]0.310203[/C][/ROW]
[ROW][C]34[/C][C]0.002736[/C][C]0.021[/C][C]0.491652[/C][/ROW]
[ROW][C]35[/C][C]-0.001351[/C][C]-0.0104[/C][C]0.495878[/C][/ROW]
[ROW][C]36[/C][C]0.018843[/C][C]0.1447[/C][C]0.442705[/C][/ROW]
[ROW][C]37[/C][C]0.090822[/C][C]0.6976[/C][C]0.244077[/C][/ROW]
[ROW][C]38[/C][C]0.156791[/C][C]1.2043[/C][C]0.116634[/C][/ROW]
[ROW][C]39[/C][C]-0.127519[/C][C]-0.9795[/C][C]0.165668[/C][/ROW]
[ROW][C]40[/C][C]-0.020409[/C][C]-0.1568[/C][C]0.437983[/C][/ROW]
[ROW][C]41[/C][C]-0.005899[/C][C]-0.0453[/C][C]0.482005[/C][/ROW]
[ROW][C]42[/C][C]-0.115047[/C][C]-0.8837[/C][C]0.190224[/C][/ROW]
[ROW][C]43[/C][C]0.07567[/C][C]0.5812[/C][C]0.281649[/C][/ROW]
[ROW][C]44[/C][C]-0.071734[/C][C]-0.551[/C][C]0.291859[/C][/ROW]
[ROW][C]45[/C][C]-0.048214[/C][C]-0.3703[/C][C]0.356228[/C][/ROW]
[ROW][C]46[/C][C]0.031575[/C][C]0.2425[/C][C]0.404605[/C][/ROW]
[ROW][C]47[/C][C]-0.012768[/C][C]-0.0981[/C][C]0.461105[/C][/ROW]
[ROW][C]48[/C][C]-0.036628[/C][C]-0.2813[/C][C]0.389715[/C][/ROW]
[ROW][C]49[/C][C]-0.07448[/C][C]-0.5721[/C][C]0.284716[/C][/ROW]
[ROW][C]50[/C][C]-0.039849[/C][C]-0.3061[/C][C]0.380309[/C][/ROW]
[ROW][C]51[/C][C]0.030599[/C][C]0.235[/C][C]0.407497[/C][/ROW]
[ROW][C]52[/C][C]0.083953[/C][C]0.6449[/C][C]0.26076[/C][/ROW]
[ROW][C]53[/C][C]-0.026274[/C][C]-0.2018[/C][C]0.420377[/C][/ROW]
[ROW][C]54[/C][C]0.092816[/C][C]0.7129[/C][C]0.239349[/C][/ROW]
[ROW][C]55[/C][C]0.012172[/C][C]0.0935[/C][C]0.462915[/C][/ROW]
[ROW][C]56[/C][C]0.047757[/C][C]0.3668[/C][C]0.357529[/C][/ROW]
[ROW][C]57[/C][C]-0.001647[/C][C]-0.0127[/C][C]0.494974[/C][/ROW]
[ROW][C]58[/C][C]0.00223[/C][C]0.0171[/C][C]0.493195[/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=34144&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34144&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
10.0043910.03370.486603
20.0220890.16970.432925
30.0060560.04650.481529
4-0.032179-0.24720.402816
5-0.056531-0.43420.332855
6-0.022048-0.16940.433048
7-0.042612-0.32730.372296
80.0053480.04110.483684
90.1381561.06120.146462
10-0.18081-1.38880.085053
110.0223510.17170.432139
12-0.257354-1.97680.026373
13-0.097089-0.74580.229389
140.1158470.88980.188583
150.0109390.0840.466661
160.0202780.15580.438378
17-0.087321-0.67070.252505
180.1537581.1810.121163
190.0728740.55980.288883
200.0835780.6420.261687
21-0.01736-0.13330.447189
220.0051260.03940.484364
230.1212620.93140.177712
24-0.13259-1.01840.156312
25-0.08443-0.64850.259583
26-0.213391-1.63910.053259
270.0664810.51070.305749
28-0.078534-0.60320.274333
290.1044420.80220.212819
30-0.126135-0.96890.168285
31-0.081025-0.62240.268049
320.0571070.43860.331259
33-0.064821-0.49790.310203
340.0027360.0210.491652
35-0.001351-0.01040.495878
360.0188430.14470.442705
370.0908220.69760.244077
380.1567911.20430.116634
39-0.127519-0.97950.165668
40-0.020409-0.15680.437983
41-0.005899-0.04530.482005
42-0.115047-0.88370.190224
430.075670.58120.281649
44-0.071734-0.5510.291859
45-0.048214-0.37030.356228
460.0315750.24250.404605
47-0.012768-0.09810.461105
48-0.036628-0.28130.389715
49-0.07448-0.57210.284716
50-0.039849-0.30610.380309
510.0305990.2350.407497
520.0839530.64490.26076
53-0.026274-0.20180.420377
540.0928160.71290.239349
550.0121720.09350.462915
560.0477570.36680.357529
57-0.001647-0.01270.494974
580.002230.01710.493195
59NANANA
60NANANA







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.0043910.03370.486603
20.022070.16950.432982
30.0058670.04510.482104
4-0.032735-0.25140.401173
5-0.056609-0.43480.332639
6-0.020339-0.15620.438194
7-0.039749-0.30530.380599
80.0061460.04720.481252
90.1375011.05620.147599
10-0.190004-1.45950.074872
110.0167770.12890.448951
12-0.271913-2.08860.020534
13-0.084339-0.64780.259806
140.1426191.09550.138879
15-0.000119-9e-040.499638
160.0218410.16780.43367
17-0.175159-1.34540.091818
180.1423471.09340.139333
190.1292820.9930.162375
200.0564480.43360.333085
210.0825040.63370.264355
22-0.132266-1.0160.1569
230.1188630.9130.182478
24-0.198331-1.52340.066499
25-0.107941-0.82910.205191
26-0.132876-1.02060.155797
270.0151270.11620.453948
28-0.013699-0.10520.458277
290.0102360.07860.468799
30-0.091418-0.70220.24266
31-0.014918-0.11460.454582
320.0670540.51510.30422
330.0196460.15090.440284
34-0.065791-0.50540.307597
350.0859470.66020.255856
36-0.144997-1.11370.134954
370.0510260.39190.348258
38-0.016922-0.130.448511
39-0.106672-0.81940.207939
400.0166280.12770.449403
41-0.136222-1.04630.149835
42-0.095946-0.7370.232028
430.0088190.06770.47311
440.0329880.25340.400426
450.0505450.38820.349616
46-0.067513-0.51860.302998
470.0284960.21890.413749
48-0.027082-0.2080.417966
49-0.053579-0.41150.341081
50-0.041979-0.32240.374127
51-0.040748-0.3130.377695
52-0.044928-0.34510.365625
530.0103340.07940.468502
54-0.005311-0.04080.483799
55-0.012976-0.09970.460473
56-0.024173-0.18570.426669
57-0.00545-0.04190.483375
580.0149650.11490.454438
59NANANA
60NANANA

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.004391 & 0.0337 & 0.486603 \tabularnewline
2 & 0.02207 & 0.1695 & 0.432982 \tabularnewline
3 & 0.005867 & 0.0451 & 0.482104 \tabularnewline
4 & -0.032735 & -0.2514 & 0.401173 \tabularnewline
5 & -0.056609 & -0.4348 & 0.332639 \tabularnewline
6 & -0.020339 & -0.1562 & 0.438194 \tabularnewline
7 & -0.039749 & -0.3053 & 0.380599 \tabularnewline
8 & 0.006146 & 0.0472 & 0.481252 \tabularnewline
9 & 0.137501 & 1.0562 & 0.147599 \tabularnewline
10 & -0.190004 & -1.4595 & 0.074872 \tabularnewline
11 & 0.016777 & 0.1289 & 0.448951 \tabularnewline
12 & -0.271913 & -2.0886 & 0.020534 \tabularnewline
13 & -0.084339 & -0.6478 & 0.259806 \tabularnewline
14 & 0.142619 & 1.0955 & 0.138879 \tabularnewline
15 & -0.000119 & -9e-04 & 0.499638 \tabularnewline
16 & 0.021841 & 0.1678 & 0.43367 \tabularnewline
17 & -0.175159 & -1.3454 & 0.091818 \tabularnewline
18 & 0.142347 & 1.0934 & 0.139333 \tabularnewline
19 & 0.129282 & 0.993 & 0.162375 \tabularnewline
20 & 0.056448 & 0.4336 & 0.333085 \tabularnewline
21 & 0.082504 & 0.6337 & 0.264355 \tabularnewline
22 & -0.132266 & -1.016 & 0.1569 \tabularnewline
23 & 0.118863 & 0.913 & 0.182478 \tabularnewline
24 & -0.198331 & -1.5234 & 0.066499 \tabularnewline
25 & -0.107941 & -0.8291 & 0.205191 \tabularnewline
26 & -0.132876 & -1.0206 & 0.155797 \tabularnewline
27 & 0.015127 & 0.1162 & 0.453948 \tabularnewline
28 & -0.013699 & -0.1052 & 0.458277 \tabularnewline
29 & 0.010236 & 0.0786 & 0.468799 \tabularnewline
30 & -0.091418 & -0.7022 & 0.24266 \tabularnewline
31 & -0.014918 & -0.1146 & 0.454582 \tabularnewline
32 & 0.067054 & 0.5151 & 0.30422 \tabularnewline
33 & 0.019646 & 0.1509 & 0.440284 \tabularnewline
34 & -0.065791 & -0.5054 & 0.307597 \tabularnewline
35 & 0.085947 & 0.6602 & 0.255856 \tabularnewline
36 & -0.144997 & -1.1137 & 0.134954 \tabularnewline
37 & 0.051026 & 0.3919 & 0.348258 \tabularnewline
38 & -0.016922 & -0.13 & 0.448511 \tabularnewline
39 & -0.106672 & -0.8194 & 0.207939 \tabularnewline
40 & 0.016628 & 0.1277 & 0.449403 \tabularnewline
41 & -0.136222 & -1.0463 & 0.149835 \tabularnewline
42 & -0.095946 & -0.737 & 0.232028 \tabularnewline
43 & 0.008819 & 0.0677 & 0.47311 \tabularnewline
44 & 0.032988 & 0.2534 & 0.400426 \tabularnewline
45 & 0.050545 & 0.3882 & 0.349616 \tabularnewline
46 & -0.067513 & -0.5186 & 0.302998 \tabularnewline
47 & 0.028496 & 0.2189 & 0.413749 \tabularnewline
48 & -0.027082 & -0.208 & 0.417966 \tabularnewline
49 & -0.053579 & -0.4115 & 0.341081 \tabularnewline
50 & -0.041979 & -0.3224 & 0.374127 \tabularnewline
51 & -0.040748 & -0.313 & 0.377695 \tabularnewline
52 & -0.044928 & -0.3451 & 0.365625 \tabularnewline
53 & 0.010334 & 0.0794 & 0.468502 \tabularnewline
54 & -0.005311 & -0.0408 & 0.483799 \tabularnewline
55 & -0.012976 & -0.0997 & 0.460473 \tabularnewline
56 & -0.024173 & -0.1857 & 0.426669 \tabularnewline
57 & -0.00545 & -0.0419 & 0.483375 \tabularnewline
58 & 0.014965 & 0.1149 & 0.454438 \tabularnewline
59 & NA & NA & NA \tabularnewline
60 & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34144&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]0.004391[/C][C]0.0337[/C][C]0.486603[/C][/ROW]
[ROW][C]2[/C][C]0.02207[/C][C]0.1695[/C][C]0.432982[/C][/ROW]
[ROW][C]3[/C][C]0.005867[/C][C]0.0451[/C][C]0.482104[/C][/ROW]
[ROW][C]4[/C][C]-0.032735[/C][C]-0.2514[/C][C]0.401173[/C][/ROW]
[ROW][C]5[/C][C]-0.056609[/C][C]-0.4348[/C][C]0.332639[/C][/ROW]
[ROW][C]6[/C][C]-0.020339[/C][C]-0.1562[/C][C]0.438194[/C][/ROW]
[ROW][C]7[/C][C]-0.039749[/C][C]-0.3053[/C][C]0.380599[/C][/ROW]
[ROW][C]8[/C][C]0.006146[/C][C]0.0472[/C][C]0.481252[/C][/ROW]
[ROW][C]9[/C][C]0.137501[/C][C]1.0562[/C][C]0.147599[/C][/ROW]
[ROW][C]10[/C][C]-0.190004[/C][C]-1.4595[/C][C]0.074872[/C][/ROW]
[ROW][C]11[/C][C]0.016777[/C][C]0.1289[/C][C]0.448951[/C][/ROW]
[ROW][C]12[/C][C]-0.271913[/C][C]-2.0886[/C][C]0.020534[/C][/ROW]
[ROW][C]13[/C][C]-0.084339[/C][C]-0.6478[/C][C]0.259806[/C][/ROW]
[ROW][C]14[/C][C]0.142619[/C][C]1.0955[/C][C]0.138879[/C][/ROW]
[ROW][C]15[/C][C]-0.000119[/C][C]-9e-04[/C][C]0.499638[/C][/ROW]
[ROW][C]16[/C][C]0.021841[/C][C]0.1678[/C][C]0.43367[/C][/ROW]
[ROW][C]17[/C][C]-0.175159[/C][C]-1.3454[/C][C]0.091818[/C][/ROW]
[ROW][C]18[/C][C]0.142347[/C][C]1.0934[/C][C]0.139333[/C][/ROW]
[ROW][C]19[/C][C]0.129282[/C][C]0.993[/C][C]0.162375[/C][/ROW]
[ROW][C]20[/C][C]0.056448[/C][C]0.4336[/C][C]0.333085[/C][/ROW]
[ROW][C]21[/C][C]0.082504[/C][C]0.6337[/C][C]0.264355[/C][/ROW]
[ROW][C]22[/C][C]-0.132266[/C][C]-1.016[/C][C]0.1569[/C][/ROW]
[ROW][C]23[/C][C]0.118863[/C][C]0.913[/C][C]0.182478[/C][/ROW]
[ROW][C]24[/C][C]-0.198331[/C][C]-1.5234[/C][C]0.066499[/C][/ROW]
[ROW][C]25[/C][C]-0.107941[/C][C]-0.8291[/C][C]0.205191[/C][/ROW]
[ROW][C]26[/C][C]-0.132876[/C][C]-1.0206[/C][C]0.155797[/C][/ROW]
[ROW][C]27[/C][C]0.015127[/C][C]0.1162[/C][C]0.453948[/C][/ROW]
[ROW][C]28[/C][C]-0.013699[/C][C]-0.1052[/C][C]0.458277[/C][/ROW]
[ROW][C]29[/C][C]0.010236[/C][C]0.0786[/C][C]0.468799[/C][/ROW]
[ROW][C]30[/C][C]-0.091418[/C][C]-0.7022[/C][C]0.24266[/C][/ROW]
[ROW][C]31[/C][C]-0.014918[/C][C]-0.1146[/C][C]0.454582[/C][/ROW]
[ROW][C]32[/C][C]0.067054[/C][C]0.5151[/C][C]0.30422[/C][/ROW]
[ROW][C]33[/C][C]0.019646[/C][C]0.1509[/C][C]0.440284[/C][/ROW]
[ROW][C]34[/C][C]-0.065791[/C][C]-0.5054[/C][C]0.307597[/C][/ROW]
[ROW][C]35[/C][C]0.085947[/C][C]0.6602[/C][C]0.255856[/C][/ROW]
[ROW][C]36[/C][C]-0.144997[/C][C]-1.1137[/C][C]0.134954[/C][/ROW]
[ROW][C]37[/C][C]0.051026[/C][C]0.3919[/C][C]0.348258[/C][/ROW]
[ROW][C]38[/C][C]-0.016922[/C][C]-0.13[/C][C]0.448511[/C][/ROW]
[ROW][C]39[/C][C]-0.106672[/C][C]-0.8194[/C][C]0.207939[/C][/ROW]
[ROW][C]40[/C][C]0.016628[/C][C]0.1277[/C][C]0.449403[/C][/ROW]
[ROW][C]41[/C][C]-0.136222[/C][C]-1.0463[/C][C]0.149835[/C][/ROW]
[ROW][C]42[/C][C]-0.095946[/C][C]-0.737[/C][C]0.232028[/C][/ROW]
[ROW][C]43[/C][C]0.008819[/C][C]0.0677[/C][C]0.47311[/C][/ROW]
[ROW][C]44[/C][C]0.032988[/C][C]0.2534[/C][C]0.400426[/C][/ROW]
[ROW][C]45[/C][C]0.050545[/C][C]0.3882[/C][C]0.349616[/C][/ROW]
[ROW][C]46[/C][C]-0.067513[/C][C]-0.5186[/C][C]0.302998[/C][/ROW]
[ROW][C]47[/C][C]0.028496[/C][C]0.2189[/C][C]0.413749[/C][/ROW]
[ROW][C]48[/C][C]-0.027082[/C][C]-0.208[/C][C]0.417966[/C][/ROW]
[ROW][C]49[/C][C]-0.053579[/C][C]-0.4115[/C][C]0.341081[/C][/ROW]
[ROW][C]50[/C][C]-0.041979[/C][C]-0.3224[/C][C]0.374127[/C][/ROW]
[ROW][C]51[/C][C]-0.040748[/C][C]-0.313[/C][C]0.377695[/C][/ROW]
[ROW][C]52[/C][C]-0.044928[/C][C]-0.3451[/C][C]0.365625[/C][/ROW]
[ROW][C]53[/C][C]0.010334[/C][C]0.0794[/C][C]0.468502[/C][/ROW]
[ROW][C]54[/C][C]-0.005311[/C][C]-0.0408[/C][C]0.483799[/C][/ROW]
[ROW][C]55[/C][C]-0.012976[/C][C]-0.0997[/C][C]0.460473[/C][/ROW]
[ROW][C]56[/C][C]-0.024173[/C][C]-0.1857[/C][C]0.426669[/C][/ROW]
[ROW][C]57[/C][C]-0.00545[/C][C]-0.0419[/C][C]0.483375[/C][/ROW]
[ROW][C]58[/C][C]0.014965[/C][C]0.1149[/C][C]0.454438[/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=34144&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34144&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
10.0043910.03370.486603
20.022070.16950.432982
30.0058670.04510.482104
4-0.032735-0.25140.401173
5-0.056609-0.43480.332639
6-0.020339-0.15620.438194
7-0.039749-0.30530.380599
80.0061460.04720.481252
90.1375011.05620.147599
10-0.190004-1.45950.074872
110.0167770.12890.448951
12-0.271913-2.08860.020534
13-0.084339-0.64780.259806
140.1426191.09550.138879
15-0.000119-9e-040.499638
160.0218410.16780.43367
17-0.175159-1.34540.091818
180.1423471.09340.139333
190.1292820.9930.162375
200.0564480.43360.333085
210.0825040.63370.264355
22-0.132266-1.0160.1569
230.1188630.9130.182478
24-0.198331-1.52340.066499
25-0.107941-0.82910.205191
26-0.132876-1.02060.155797
270.0151270.11620.453948
28-0.013699-0.10520.458277
290.0102360.07860.468799
30-0.091418-0.70220.24266
31-0.014918-0.11460.454582
320.0670540.51510.30422
330.0196460.15090.440284
34-0.065791-0.50540.307597
350.0859470.66020.255856
36-0.144997-1.11370.134954
370.0510260.39190.348258
38-0.016922-0.130.448511
39-0.106672-0.81940.207939
400.0166280.12770.449403
41-0.136222-1.04630.149835
42-0.095946-0.7370.232028
430.0088190.06770.47311
440.0329880.25340.400426
450.0505450.38820.349616
46-0.067513-0.51860.302998
470.0284960.21890.413749
48-0.027082-0.2080.417966
49-0.053579-0.41150.341081
50-0.041979-0.32240.374127
51-0.040748-0.3130.377695
52-0.044928-0.34510.365625
530.0103340.07940.468502
54-0.005311-0.04080.483799
55-0.012976-0.09970.460473
56-0.024173-0.18570.426669
57-0.00545-0.04190.483375
580.0149650.11490.454438
59NANANA
60NANANA



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ;
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 (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='lags',ylab='ACF')
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')