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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, 02 Dec 2008 07:50:38 -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/02/t12282294779hpge7a99nvpvsw.htm/, Retrieved Fri, 17 May 2024 03:20:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27888, Retrieved Fri, 17 May 2024 03:20:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [(Partial) Autocorrelation Function] [Stefan Temmerman] [2008-12-02 14:50:38] [30f7cb12a8cb61e43b87da59ece37a2f] [Current]
Feedback Forum
2008-12-06 14:41:07 [Natalie De Wilde] [reply
Met d=1 te stellen proberen we de lange termijn trend weg te werken. Hierna zien we dat er nog steeds een seizoenale trend is, deze kunnen we wegwerken door D=1. Hierdoor verdwijnen de pieken op 12,24,36. Als we goed kijken naar deze pieken, zien we dat ook hier een langzaam dalend patroon is. Nadat d=1 en D=1 is er geen lange termijn trend en geen seizoenale trend meer, we hebben de tijdreeks stationair gemaakt. Ook omdat bijna alle waarden binnen het 95% betrouwbaarheidsinterval liggen.
Goed, we zien hier inderdaad dat de VRM dezelfde resultaten geeft als de ACF. We moeten er wel rekening mee houden dat dit een zeer ruwe manier van berekenen is,het is eenvoudig, we kunnen beter ACF gebruiken, maar dit is een goede controle.
De Trim Var zorgt ervoor dat de meest extreme variabelen weggelaten worden, de outliers hebben dan (geen)minder invloed op de tijdreeks.
2008-12-07 10:42:04 [Lana Van Wesemael] [reply
time lag van 36 had ook goed geweest voor maandcijfers. Ook hier kan men best een seasonality van 12 gebruiken want het zijn maandcijfers. Opvallend is dat de piek van elke golf op maand 12, 24 en 36 ligt. Wat dus duidelijk wijst op seizoenaliteit.

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Dataseries X:
112
118
132
129
121
135
148
148
136
119
104
118
115
126
141
135
125
149
170
170
158
133
114
140
145
150
178
163
172
178
199
199
184
162
146
166
171
180
193
181
183
218
230
242
209
191
172
194
196
196
236
235
229
243
264
272
237
211
180
201
204
188
235
227
234
264
302
293
259
229
203
229
242
233
267
269
270
315
364
347
312
274
237
278
284
277
317
313
318
374
413
405
355
306
271
306
315
301
356
348
355
422
465
467
404
347
305
336
340
318
362
348
363
435
491
505
404
359
310
337
360
342
406
396
420
472
548
559
463
407
362
405
417
391
419
461
472
535
622
606
508
461
390
432




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27888&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27888&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27888&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.95370311.44440
20.89891610.7870
30.85080210.20960
40.8084259.70110
50.7788999.34680
60.7564429.07730
70.7376028.85120
80.7271318.72560
90.7336498.80380
100.7442558.93110
110.7580279.09630
120.7619439.14330
130.7165048.59810
140.6630437.95650
150.6183637.42040
160.5762096.91450
170.5438016.52560
180.5194566.23350
190.5007036.00840
200.4904035.88480
210.4981825.97820
220.5061676.0740
230.5167436.20090
240.520496.24590
250.4835245.80230
260.4373985.24880
270.4004074.80492e-06
280.3641314.36961.2e-05
290.3369824.04384.3e-05
300.3147233.77670.000116
310.2967753.56130.00025
320.2886163.46340.000351
330.2953553.54430.000266
340.3045473.65460.00018
350.3150963.78120.000114
360.3192933.83159.5e-05
370.2862113.43450.000388
380.2450162.94020.001911
390.2108962.53080.006228
400.1750952.10110.018686
410.145851.75020.041107
420.1248281.49790.06817
430.1064561.27750.101746
440.0990031.1880.118387
450.1037851.24540.107501
460.1112631.33520.091967
470.1204231.44510.075305
480.1247921.49750.068225
490.0957541.1490.126222
500.057950.69540.243962
510.0310640.37280.354936
520.0038060.04570.481815
53-0.01988-0.23860.405894
54-0.040854-0.49020.312353
55-0.058054-0.69670.243572
56-0.066082-0.7930.214546
57-0.061277-0.73530.23167
58-0.054916-0.6590.255475
59-0.050484-0.60580.272798
60-0.049553-0.59460.276511

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953703 & 11.4444 & 0 \tabularnewline
2 & 0.898916 & 10.787 & 0 \tabularnewline
3 & 0.850802 & 10.2096 & 0 \tabularnewline
4 & 0.808425 & 9.7011 & 0 \tabularnewline
5 & 0.778899 & 9.3468 & 0 \tabularnewline
6 & 0.756442 & 9.0773 & 0 \tabularnewline
7 & 0.737602 & 8.8512 & 0 \tabularnewline
8 & 0.727131 & 8.7256 & 0 \tabularnewline
9 & 0.733649 & 8.8038 & 0 \tabularnewline
10 & 0.744255 & 8.9311 & 0 \tabularnewline
11 & 0.758027 & 9.0963 & 0 \tabularnewline
12 & 0.761943 & 9.1433 & 0 \tabularnewline
13 & 0.716504 & 8.5981 & 0 \tabularnewline
14 & 0.663043 & 7.9565 & 0 \tabularnewline
15 & 0.618363 & 7.4204 & 0 \tabularnewline
16 & 0.576209 & 6.9145 & 0 \tabularnewline
17 & 0.543801 & 6.5256 & 0 \tabularnewline
18 & 0.519456 & 6.2335 & 0 \tabularnewline
19 & 0.500703 & 6.0084 & 0 \tabularnewline
20 & 0.490403 & 5.8848 & 0 \tabularnewline
21 & 0.498182 & 5.9782 & 0 \tabularnewline
22 & 0.506167 & 6.074 & 0 \tabularnewline
23 & 0.516743 & 6.2009 & 0 \tabularnewline
24 & 0.52049 & 6.2459 & 0 \tabularnewline
25 & 0.483524 & 5.8023 & 0 \tabularnewline
26 & 0.437398 & 5.2488 & 0 \tabularnewline
27 & 0.400407 & 4.8049 & 2e-06 \tabularnewline
28 & 0.364131 & 4.3696 & 1.2e-05 \tabularnewline
29 & 0.336982 & 4.0438 & 4.3e-05 \tabularnewline
30 & 0.314723 & 3.7767 & 0.000116 \tabularnewline
31 & 0.296775 & 3.5613 & 0.00025 \tabularnewline
32 & 0.288616 & 3.4634 & 0.000351 \tabularnewline
33 & 0.295355 & 3.5443 & 0.000266 \tabularnewline
34 & 0.304547 & 3.6546 & 0.00018 \tabularnewline
35 & 0.315096 & 3.7812 & 0.000114 \tabularnewline
36 & 0.319293 & 3.8315 & 9.5e-05 \tabularnewline
37 & 0.286211 & 3.4345 & 0.000388 \tabularnewline
38 & 0.245016 & 2.9402 & 0.001911 \tabularnewline
39 & 0.210896 & 2.5308 & 0.006228 \tabularnewline
40 & 0.175095 & 2.1011 & 0.018686 \tabularnewline
41 & 0.14585 & 1.7502 & 0.041107 \tabularnewline
42 & 0.124828 & 1.4979 & 0.06817 \tabularnewline
43 & 0.106456 & 1.2775 & 0.101746 \tabularnewline
44 & 0.099003 & 1.188 & 0.118387 \tabularnewline
45 & 0.103785 & 1.2454 & 0.107501 \tabularnewline
46 & 0.111263 & 1.3352 & 0.091967 \tabularnewline
47 & 0.120423 & 1.4451 & 0.075305 \tabularnewline
48 & 0.124792 & 1.4975 & 0.068225 \tabularnewline
49 & 0.095754 & 1.149 & 0.126222 \tabularnewline
50 & 0.05795 & 0.6954 & 0.243962 \tabularnewline
51 & 0.031064 & 0.3728 & 0.354936 \tabularnewline
52 & 0.003806 & 0.0457 & 0.481815 \tabularnewline
53 & -0.01988 & -0.2386 & 0.405894 \tabularnewline
54 & -0.040854 & -0.4902 & 0.312353 \tabularnewline
55 & -0.058054 & -0.6967 & 0.243572 \tabularnewline
56 & -0.066082 & -0.793 & 0.214546 \tabularnewline
57 & -0.061277 & -0.7353 & 0.23167 \tabularnewline
58 & -0.054916 & -0.659 & 0.255475 \tabularnewline
59 & -0.050484 & -0.6058 & 0.272798 \tabularnewline
60 & -0.049553 & -0.5946 & 0.276511 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27888&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]0.953703[/C][C]11.4444[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.898916[/C][C]10.787[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.850802[/C][C]10.2096[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.808425[/C][C]9.7011[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.778899[/C][C]9.3468[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.756442[/C][C]9.0773[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.737602[/C][C]8.8512[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.727131[/C][C]8.7256[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.733649[/C][C]8.8038[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.744255[/C][C]8.9311[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.758027[/C][C]9.0963[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.761943[/C][C]9.1433[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.716504[/C][C]8.5981[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.663043[/C][C]7.9565[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.618363[/C][C]7.4204[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.576209[/C][C]6.9145[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.543801[/C][C]6.5256[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.519456[/C][C]6.2335[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.500703[/C][C]6.0084[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.490403[/C][C]5.8848[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.498182[/C][C]5.9782[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.506167[/C][C]6.074[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.516743[/C][C]6.2009[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.52049[/C][C]6.2459[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.483524[/C][C]5.8023[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.437398[/C][C]5.2488[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.400407[/C][C]4.8049[/C][C]2e-06[/C][/ROW]
[ROW][C]28[/C][C]0.364131[/C][C]4.3696[/C][C]1.2e-05[/C][/ROW]
[ROW][C]29[/C][C]0.336982[/C][C]4.0438[/C][C]4.3e-05[/C][/ROW]
[ROW][C]30[/C][C]0.314723[/C][C]3.7767[/C][C]0.000116[/C][/ROW]
[ROW][C]31[/C][C]0.296775[/C][C]3.5613[/C][C]0.00025[/C][/ROW]
[ROW][C]32[/C][C]0.288616[/C][C]3.4634[/C][C]0.000351[/C][/ROW]
[ROW][C]33[/C][C]0.295355[/C][C]3.5443[/C][C]0.000266[/C][/ROW]
[ROW][C]34[/C][C]0.304547[/C][C]3.6546[/C][C]0.00018[/C][/ROW]
[ROW][C]35[/C][C]0.315096[/C][C]3.7812[/C][C]0.000114[/C][/ROW]
[ROW][C]36[/C][C]0.319293[/C][C]3.8315[/C][C]9.5e-05[/C][/ROW]
[ROW][C]37[/C][C]0.286211[/C][C]3.4345[/C][C]0.000388[/C][/ROW]
[ROW][C]38[/C][C]0.245016[/C][C]2.9402[/C][C]0.001911[/C][/ROW]
[ROW][C]39[/C][C]0.210896[/C][C]2.5308[/C][C]0.006228[/C][/ROW]
[ROW][C]40[/C][C]0.175095[/C][C]2.1011[/C][C]0.018686[/C][/ROW]
[ROW][C]41[/C][C]0.14585[/C][C]1.7502[/C][C]0.041107[/C][/ROW]
[ROW][C]42[/C][C]0.124828[/C][C]1.4979[/C][C]0.06817[/C][/ROW]
[ROW][C]43[/C][C]0.106456[/C][C]1.2775[/C][C]0.101746[/C][/ROW]
[ROW][C]44[/C][C]0.099003[/C][C]1.188[/C][C]0.118387[/C][/ROW]
[ROW][C]45[/C][C]0.103785[/C][C]1.2454[/C][C]0.107501[/C][/ROW]
[ROW][C]46[/C][C]0.111263[/C][C]1.3352[/C][C]0.091967[/C][/ROW]
[ROW][C]47[/C][C]0.120423[/C][C]1.4451[/C][C]0.075305[/C][/ROW]
[ROW][C]48[/C][C]0.124792[/C][C]1.4975[/C][C]0.068225[/C][/ROW]
[ROW][C]49[/C][C]0.095754[/C][C]1.149[/C][C]0.126222[/C][/ROW]
[ROW][C]50[/C][C]0.05795[/C][C]0.6954[/C][C]0.243962[/C][/ROW]
[ROW][C]51[/C][C]0.031064[/C][C]0.3728[/C][C]0.354936[/C][/ROW]
[ROW][C]52[/C][C]0.003806[/C][C]0.0457[/C][C]0.481815[/C][/ROW]
[ROW][C]53[/C][C]-0.01988[/C][C]-0.2386[/C][C]0.405894[/C][/ROW]
[ROW][C]54[/C][C]-0.040854[/C][C]-0.4902[/C][C]0.312353[/C][/ROW]
[ROW][C]55[/C][C]-0.058054[/C][C]-0.6967[/C][C]0.243572[/C][/ROW]
[ROW][C]56[/C][C]-0.066082[/C][C]-0.793[/C][C]0.214546[/C][/ROW]
[ROW][C]57[/C][C]-0.061277[/C][C]-0.7353[/C][C]0.23167[/C][/ROW]
[ROW][C]58[/C][C]-0.054916[/C][C]-0.659[/C][C]0.255475[/C][/ROW]
[ROW][C]59[/C][C]-0.050484[/C][C]-0.6058[/C][C]0.272798[/C][/ROW]
[ROW][C]60[/C][C]-0.049553[/C][C]-0.5946[/C][C]0.276511[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27888&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27888&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
10.95370311.44440
20.89891610.7870
30.85080210.20960
40.8084259.70110
50.7788999.34680
60.7564429.07730
70.7376028.85120
80.7271318.72560
90.7336498.80380
100.7442558.93110
110.7580279.09630
120.7619439.14330
130.7165048.59810
140.6630437.95650
150.6183637.42040
160.5762096.91450
170.5438016.52560
180.5194566.23350
190.5007036.00840
200.4904035.88480
210.4981825.97820
220.5061676.0740
230.5167436.20090
240.520496.24590
250.4835245.80230
260.4373985.24880
270.4004074.80492e-06
280.3641314.36961.2e-05
290.3369824.04384.3e-05
300.3147233.77670.000116
310.2967753.56130.00025
320.2886163.46340.000351
330.2953553.54430.000266
340.3045473.65460.00018
350.3150963.78120.000114
360.3192933.83159.5e-05
370.2862113.43450.000388
380.2450162.94020.001911
390.2108962.53080.006228
400.1750952.10110.018686
410.145851.75020.041107
420.1248281.49790.06817
430.1064561.27750.101746
440.0990031.1880.118387
450.1037851.24540.107501
460.1112631.33520.091967
470.1204231.44510.075305
480.1247921.49750.068225
490.0957541.1490.126222
500.057950.69540.243962
510.0310640.37280.354936
520.0038060.04570.481815
53-0.01988-0.23860.405894
54-0.040854-0.49020.312353
55-0.058054-0.69670.243572
56-0.066082-0.7930.214546
57-0.061277-0.73530.23167
58-0.054916-0.6590.255475
59-0.050484-0.60580.272798
60-0.049553-0.59460.276511







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.95370311.44440
2-0.11757-1.41080.080225
30.0542330.65080.258109
40.0237560.28510.387999
50.1158221.38990.083357
60.0443680.53240.297631
70.0380340.45640.324392
80.0996221.19550.116935
90.2040962.44910.00776
100.0639090.76690.222195
110.1060351.27240.102636
12-0.042466-0.50960.305558
13-0.48543-5.82520
14-0.03435-0.41220.340402
150.0422250.50670.306572
16-0.044197-0.53040.298337
170.0276080.33130.370452
180.0371480.44580.328215
190.0416380.49970.309038
200.01440.17280.431526
210.0733120.87970.19023
22-0.033395-0.40070.344602
230.0609970.7320.232691
240.0310780.37290.354873
25-0.194374-2.33250.01053
26-0.035076-0.42090.337224
270.0364550.43750.331218
28-0.035175-0.42210.336789
290.0442550.53110.298099
30-0.044545-0.53450.296898
31-0.003337-0.040.484055
320.0341410.40970.341322
33-0.019607-0.23530.407161
340.0277220.33270.369936
350.0293540.35220.362583
36-0.003734-0.04480.482162
37-0.131797-1.58160.057972
38-0.002813-0.03380.486558
39-0.024864-0.29840.382928
40-0.058589-0.70310.241574
410.0056330.06760.473099
420.0379620.45550.324702
43-0.032237-0.38680.349721
440.0314020.37680.353431
45-0.048812-0.58570.279484
460.0109180.1310.447973
470.0288750.34650.364735
48-0.005721-0.06870.472681
49-0.08061-0.96730.167502
50-0.016264-0.19520.422768
510.0684660.82160.206333
520.0104990.1260.449958
53-0.037367-0.44840.327269
54-0.072253-0.8670.193683
550.0181230.21750.414072
56-0.020254-0.2430.404159
57-0.023257-0.27910.390288
58-0.021534-0.25840.39823
59-0.041996-0.5040.307532
600.0106470.12780.449259

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.953703 & 11.4444 & 0 \tabularnewline
2 & -0.11757 & -1.4108 & 0.080225 \tabularnewline
3 & 0.054233 & 0.6508 & 0.258109 \tabularnewline
4 & 0.023756 & 0.2851 & 0.387999 \tabularnewline
5 & 0.115822 & 1.3899 & 0.083357 \tabularnewline
6 & 0.044368 & 0.5324 & 0.297631 \tabularnewline
7 & 0.038034 & 0.4564 & 0.324392 \tabularnewline
8 & 0.099622 & 1.1955 & 0.116935 \tabularnewline
9 & 0.204096 & 2.4491 & 0.00776 \tabularnewline
10 & 0.063909 & 0.7669 & 0.222195 \tabularnewline
11 & 0.106035 & 1.2724 & 0.102636 \tabularnewline
12 & -0.042466 & -0.5096 & 0.305558 \tabularnewline
13 & -0.48543 & -5.8252 & 0 \tabularnewline
14 & -0.03435 & -0.4122 & 0.340402 \tabularnewline
15 & 0.042225 & 0.5067 & 0.306572 \tabularnewline
16 & -0.044197 & -0.5304 & 0.298337 \tabularnewline
17 & 0.027608 & 0.3313 & 0.370452 \tabularnewline
18 & 0.037148 & 0.4458 & 0.328215 \tabularnewline
19 & 0.041638 & 0.4997 & 0.309038 \tabularnewline
20 & 0.0144 & 0.1728 & 0.431526 \tabularnewline
21 & 0.073312 & 0.8797 & 0.19023 \tabularnewline
22 & -0.033395 & -0.4007 & 0.344602 \tabularnewline
23 & 0.060997 & 0.732 & 0.232691 \tabularnewline
24 & 0.031078 & 0.3729 & 0.354873 \tabularnewline
25 & -0.194374 & -2.3325 & 0.01053 \tabularnewline
26 & -0.035076 & -0.4209 & 0.337224 \tabularnewline
27 & 0.036455 & 0.4375 & 0.331218 \tabularnewline
28 & -0.035175 & -0.4221 & 0.336789 \tabularnewline
29 & 0.044255 & 0.5311 & 0.298099 \tabularnewline
30 & -0.044545 & -0.5345 & 0.296898 \tabularnewline
31 & -0.003337 & -0.04 & 0.484055 \tabularnewline
32 & 0.034141 & 0.4097 & 0.341322 \tabularnewline
33 & -0.019607 & -0.2353 & 0.407161 \tabularnewline
34 & 0.027722 & 0.3327 & 0.369936 \tabularnewline
35 & 0.029354 & 0.3522 & 0.362583 \tabularnewline
36 & -0.003734 & -0.0448 & 0.482162 \tabularnewline
37 & -0.131797 & -1.5816 & 0.057972 \tabularnewline
38 & -0.002813 & -0.0338 & 0.486558 \tabularnewline
39 & -0.024864 & -0.2984 & 0.382928 \tabularnewline
40 & -0.058589 & -0.7031 & 0.241574 \tabularnewline
41 & 0.005633 & 0.0676 & 0.473099 \tabularnewline
42 & 0.037962 & 0.4555 & 0.324702 \tabularnewline
43 & -0.032237 & -0.3868 & 0.349721 \tabularnewline
44 & 0.031402 & 0.3768 & 0.353431 \tabularnewline
45 & -0.048812 & -0.5857 & 0.279484 \tabularnewline
46 & 0.010918 & 0.131 & 0.447973 \tabularnewline
47 & 0.028875 & 0.3465 & 0.364735 \tabularnewline
48 & -0.005721 & -0.0687 & 0.472681 \tabularnewline
49 & -0.08061 & -0.9673 & 0.167502 \tabularnewline
50 & -0.016264 & -0.1952 & 0.422768 \tabularnewline
51 & 0.068466 & 0.8216 & 0.206333 \tabularnewline
52 & 0.010499 & 0.126 & 0.449958 \tabularnewline
53 & -0.037367 & -0.4484 & 0.327269 \tabularnewline
54 & -0.072253 & -0.867 & 0.193683 \tabularnewline
55 & 0.018123 & 0.2175 & 0.414072 \tabularnewline
56 & -0.020254 & -0.243 & 0.404159 \tabularnewline
57 & -0.023257 & -0.2791 & 0.390288 \tabularnewline
58 & -0.021534 & -0.2584 & 0.39823 \tabularnewline
59 & -0.041996 & -0.504 & 0.307532 \tabularnewline
60 & 0.010647 & 0.1278 & 0.449259 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27888&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]0.953703[/C][C]11.4444[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.11757[/C][C]-1.4108[/C][C]0.080225[/C][/ROW]
[ROW][C]3[/C][C]0.054233[/C][C]0.6508[/C][C]0.258109[/C][/ROW]
[ROW][C]4[/C][C]0.023756[/C][C]0.2851[/C][C]0.387999[/C][/ROW]
[ROW][C]5[/C][C]0.115822[/C][C]1.3899[/C][C]0.083357[/C][/ROW]
[ROW][C]6[/C][C]0.044368[/C][C]0.5324[/C][C]0.297631[/C][/ROW]
[ROW][C]7[/C][C]0.038034[/C][C]0.4564[/C][C]0.324392[/C][/ROW]
[ROW][C]8[/C][C]0.099622[/C][C]1.1955[/C][C]0.116935[/C][/ROW]
[ROW][C]9[/C][C]0.204096[/C][C]2.4491[/C][C]0.00776[/C][/ROW]
[ROW][C]10[/C][C]0.063909[/C][C]0.7669[/C][C]0.222195[/C][/ROW]
[ROW][C]11[/C][C]0.106035[/C][C]1.2724[/C][C]0.102636[/C][/ROW]
[ROW][C]12[/C][C]-0.042466[/C][C]-0.5096[/C][C]0.305558[/C][/ROW]
[ROW][C]13[/C][C]-0.48543[/C][C]-5.8252[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]-0.03435[/C][C]-0.4122[/C][C]0.340402[/C][/ROW]
[ROW][C]15[/C][C]0.042225[/C][C]0.5067[/C][C]0.306572[/C][/ROW]
[ROW][C]16[/C][C]-0.044197[/C][C]-0.5304[/C][C]0.298337[/C][/ROW]
[ROW][C]17[/C][C]0.027608[/C][C]0.3313[/C][C]0.370452[/C][/ROW]
[ROW][C]18[/C][C]0.037148[/C][C]0.4458[/C][C]0.328215[/C][/ROW]
[ROW][C]19[/C][C]0.041638[/C][C]0.4997[/C][C]0.309038[/C][/ROW]
[ROW][C]20[/C][C]0.0144[/C][C]0.1728[/C][C]0.431526[/C][/ROW]
[ROW][C]21[/C][C]0.073312[/C][C]0.8797[/C][C]0.19023[/C][/ROW]
[ROW][C]22[/C][C]-0.033395[/C][C]-0.4007[/C][C]0.344602[/C][/ROW]
[ROW][C]23[/C][C]0.060997[/C][C]0.732[/C][C]0.232691[/C][/ROW]
[ROW][C]24[/C][C]0.031078[/C][C]0.3729[/C][C]0.354873[/C][/ROW]
[ROW][C]25[/C][C]-0.194374[/C][C]-2.3325[/C][C]0.01053[/C][/ROW]
[ROW][C]26[/C][C]-0.035076[/C][C]-0.4209[/C][C]0.337224[/C][/ROW]
[ROW][C]27[/C][C]0.036455[/C][C]0.4375[/C][C]0.331218[/C][/ROW]
[ROW][C]28[/C][C]-0.035175[/C][C]-0.4221[/C][C]0.336789[/C][/ROW]
[ROW][C]29[/C][C]0.044255[/C][C]0.5311[/C][C]0.298099[/C][/ROW]
[ROW][C]30[/C][C]-0.044545[/C][C]-0.5345[/C][C]0.296898[/C][/ROW]
[ROW][C]31[/C][C]-0.003337[/C][C]-0.04[/C][C]0.484055[/C][/ROW]
[ROW][C]32[/C][C]0.034141[/C][C]0.4097[/C][C]0.341322[/C][/ROW]
[ROW][C]33[/C][C]-0.019607[/C][C]-0.2353[/C][C]0.407161[/C][/ROW]
[ROW][C]34[/C][C]0.027722[/C][C]0.3327[/C][C]0.369936[/C][/ROW]
[ROW][C]35[/C][C]0.029354[/C][C]0.3522[/C][C]0.362583[/C][/ROW]
[ROW][C]36[/C][C]-0.003734[/C][C]-0.0448[/C][C]0.482162[/C][/ROW]
[ROW][C]37[/C][C]-0.131797[/C][C]-1.5816[/C][C]0.057972[/C][/ROW]
[ROW][C]38[/C][C]-0.002813[/C][C]-0.0338[/C][C]0.486558[/C][/ROW]
[ROW][C]39[/C][C]-0.024864[/C][C]-0.2984[/C][C]0.382928[/C][/ROW]
[ROW][C]40[/C][C]-0.058589[/C][C]-0.7031[/C][C]0.241574[/C][/ROW]
[ROW][C]41[/C][C]0.005633[/C][C]0.0676[/C][C]0.473099[/C][/ROW]
[ROW][C]42[/C][C]0.037962[/C][C]0.4555[/C][C]0.324702[/C][/ROW]
[ROW][C]43[/C][C]-0.032237[/C][C]-0.3868[/C][C]0.349721[/C][/ROW]
[ROW][C]44[/C][C]0.031402[/C][C]0.3768[/C][C]0.353431[/C][/ROW]
[ROW][C]45[/C][C]-0.048812[/C][C]-0.5857[/C][C]0.279484[/C][/ROW]
[ROW][C]46[/C][C]0.010918[/C][C]0.131[/C][C]0.447973[/C][/ROW]
[ROW][C]47[/C][C]0.028875[/C][C]0.3465[/C][C]0.364735[/C][/ROW]
[ROW][C]48[/C][C]-0.005721[/C][C]-0.0687[/C][C]0.472681[/C][/ROW]
[ROW][C]49[/C][C]-0.08061[/C][C]-0.9673[/C][C]0.167502[/C][/ROW]
[ROW][C]50[/C][C]-0.016264[/C][C]-0.1952[/C][C]0.422768[/C][/ROW]
[ROW][C]51[/C][C]0.068466[/C][C]0.8216[/C][C]0.206333[/C][/ROW]
[ROW][C]52[/C][C]0.010499[/C][C]0.126[/C][C]0.449958[/C][/ROW]
[ROW][C]53[/C][C]-0.037367[/C][C]-0.4484[/C][C]0.327269[/C][/ROW]
[ROW][C]54[/C][C]-0.072253[/C][C]-0.867[/C][C]0.193683[/C][/ROW]
[ROW][C]55[/C][C]0.018123[/C][C]0.2175[/C][C]0.414072[/C][/ROW]
[ROW][C]56[/C][C]-0.020254[/C][C]-0.243[/C][C]0.404159[/C][/ROW]
[ROW][C]57[/C][C]-0.023257[/C][C]-0.2791[/C][C]0.390288[/C][/ROW]
[ROW][C]58[/C][C]-0.021534[/C][C]-0.2584[/C][C]0.39823[/C][/ROW]
[ROW][C]59[/C][C]-0.041996[/C][C]-0.504[/C][C]0.307532[/C][/ROW]
[ROW][C]60[/C][C]0.010647[/C][C]0.1278[/C][C]0.449259[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27888&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27888&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
10.95370311.44440
2-0.11757-1.41080.080225
30.0542330.65080.258109
40.0237560.28510.387999
50.1158221.38990.083357
60.0443680.53240.297631
70.0380340.45640.324392
80.0996221.19550.116935
90.2040962.44910.00776
100.0639090.76690.222195
110.1060351.27240.102636
12-0.042466-0.50960.305558
13-0.48543-5.82520
14-0.03435-0.41220.340402
150.0422250.50670.306572
16-0.044197-0.53040.298337
170.0276080.33130.370452
180.0371480.44580.328215
190.0416380.49970.309038
200.01440.17280.431526
210.0733120.87970.19023
22-0.033395-0.40070.344602
230.0609970.7320.232691
240.0310780.37290.354873
25-0.194374-2.33250.01053
26-0.035076-0.42090.337224
270.0364550.43750.331218
28-0.035175-0.42210.336789
290.0442550.53110.298099
30-0.044545-0.53450.296898
31-0.003337-0.040.484055
320.0341410.40970.341322
33-0.019607-0.23530.407161
340.0277220.33270.369936
350.0293540.35220.362583
36-0.003734-0.04480.482162
37-0.131797-1.58160.057972
38-0.002813-0.03380.486558
39-0.024864-0.29840.382928
40-0.058589-0.70310.241574
410.0056330.06760.473099
420.0379620.45550.324702
43-0.032237-0.38680.349721
440.0314020.37680.353431
45-0.048812-0.58570.279484
460.0109180.1310.447973
470.0288750.34650.364735
48-0.005721-0.06870.472681
49-0.08061-0.96730.167502
50-0.016264-0.19520.422768
510.0684660.82160.206333
520.0104990.1260.449958
53-0.037367-0.44840.327269
54-0.072253-0.8670.193683
550.0181230.21750.414072
56-0.020254-0.2430.404159
57-0.023257-0.27910.390288
58-0.021534-0.25840.39823
59-0.041996-0.5040.307532
600.0106470.12780.449259



Parameters (Session):
par1 = 60 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; par5 = 12 ;
Parameters (R input):
par1 = 60 ; par2 = 0.0 ; par3 = 0 ; par4 = 0 ; 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')