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Author's title

Author*Unverified author*
R Software Module--
Title produced by software(Partial) Autocorrelation Function
Date of computationThu, 20 Dec 2012 14:29:27 -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/2012/Dec/20/t1356031785ljtz9rf0vhmomqo.htm/, Retrieved Fri, 29 Mar 2024 01:04:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203044, Retrieved Fri, 29 Mar 2024 01:04:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [(Partial) Autocorrelation Function] [Autocorrelatiefun...] [2012-11-10 16:56:48] [391561951b5d7f721cfaa4f5575ab127]
- R P     [(Partial) Autocorrelation Function] [] [2012-11-24 00:03:24] [74be16979710d4c4e7c6647856088456]
-   P       [(Partial) Autocorrelation Function] [Langetermijntrend...] [2012-11-24 09:07:33] [74be16979710d4c4e7c6647856088456]
-   P         [(Partial) Autocorrelation Function] [Seizoenale differ...] [2012-11-24 09:21:40] [74be16979710d4c4e7c6647856088456]
-  M              [(Partial) Autocorrelation Function] [] [2012-12-20 19:29:27] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
617
614
647
580
614
636
388
356
639
753
611
639
630
586
695
552
619
681
421
307
754
690
644
643
608
651
691
627
634
731
475
337
803
722
590
724
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
706
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858
775
785
1006
789
734
906
532
387
991
841
892
782
811
792
978
773
796
946
594
438
1023
868
791
760
779
852
1001
734
996
869
599
426
1138
1091
830
909




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203044&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203044&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203044&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'Herman Ole Andreas Wold' @ wold.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.546444-5.9610
20.0523450.5710.284533
30.1377311.50250.067812
4-0.252347-2.75280.003418
50.1300411.41860.079317
6-0.019067-0.2080.417792
7-0.110364-1.20390.115503
80.2202852.4030.008902
9-0.039861-0.43480.332235
10-0.102341-1.11640.133248
110.2031732.21640.014284
12-0.198515-2.16550.016171
13-0.059016-0.64380.260475
140.0765690.83530.202621
150.0202660.22110.412707
16-0.000277-0.0030.498798
17-0.005856-0.06390.474587
180.0949071.03530.151311
19-0.105584-1.15180.125859
200.0173160.18890.42525
210.0498910.54420.293645
22-0.138388-1.50960.066894
230.1337151.45870.073646
24-0.102799-1.12140.132187
250.0163480.17830.429379
260.1619031.76610.039968
27-0.200246-2.18440.015446
280.0399650.4360.331827
290.1417751.54660.06231
30-0.222695-2.42930.008311
310.114921.25360.106218
320.031810.3470.364599
33-0.173765-1.89560.030222
340.1712711.86830.032087
35-0.018598-0.20290.419789
36-0.05327-0.58110.281132
370.1191781.30010.098043
38-0.159262-1.73730.042457
390.1092541.19180.117852
40-0.021928-0.23920.40568
41-0.088893-0.96970.167079
420.062490.68170.248383
430.0333270.36360.358417
440.0129110.14080.444115
45-0.036709-0.40050.344771
460.0379430.41390.339842
470.0115480.1260.449981
48-0.131641-1.4360.076808

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & -0.546444 & -5.961 & 0 \tabularnewline
2 & 0.052345 & 0.571 & 0.284533 \tabularnewline
3 & 0.137731 & 1.5025 & 0.067812 \tabularnewline
4 & -0.252347 & -2.7528 & 0.003418 \tabularnewline
5 & 0.130041 & 1.4186 & 0.079317 \tabularnewline
6 & -0.019067 & -0.208 & 0.417792 \tabularnewline
7 & -0.110364 & -1.2039 & 0.115503 \tabularnewline
8 & 0.220285 & 2.403 & 0.008902 \tabularnewline
9 & -0.039861 & -0.4348 & 0.332235 \tabularnewline
10 & -0.102341 & -1.1164 & 0.133248 \tabularnewline
11 & 0.203173 & 2.2164 & 0.014284 \tabularnewline
12 & -0.198515 & -2.1655 & 0.016171 \tabularnewline
13 & -0.059016 & -0.6438 & 0.260475 \tabularnewline
14 & 0.076569 & 0.8353 & 0.202621 \tabularnewline
15 & 0.020266 & 0.2211 & 0.412707 \tabularnewline
16 & -0.000277 & -0.003 & 0.498798 \tabularnewline
17 & -0.005856 & -0.0639 & 0.474587 \tabularnewline
18 & 0.094907 & 1.0353 & 0.151311 \tabularnewline
19 & -0.105584 & -1.1518 & 0.125859 \tabularnewline
20 & 0.017316 & 0.1889 & 0.42525 \tabularnewline
21 & 0.049891 & 0.5442 & 0.293645 \tabularnewline
22 & -0.138388 & -1.5096 & 0.066894 \tabularnewline
23 & 0.133715 & 1.4587 & 0.073646 \tabularnewline
24 & -0.102799 & -1.1214 & 0.132187 \tabularnewline
25 & 0.016348 & 0.1783 & 0.429379 \tabularnewline
26 & 0.161903 & 1.7661 & 0.039968 \tabularnewline
27 & -0.200246 & -2.1844 & 0.015446 \tabularnewline
28 & 0.039965 & 0.436 & 0.331827 \tabularnewline
29 & 0.141775 & 1.5466 & 0.06231 \tabularnewline
30 & -0.222695 & -2.4293 & 0.008311 \tabularnewline
31 & 0.11492 & 1.2536 & 0.106218 \tabularnewline
32 & 0.03181 & 0.347 & 0.364599 \tabularnewline
33 & -0.173765 & -1.8956 & 0.030222 \tabularnewline
34 & 0.171271 & 1.8683 & 0.032087 \tabularnewline
35 & -0.018598 & -0.2029 & 0.419789 \tabularnewline
36 & -0.05327 & -0.5811 & 0.281132 \tabularnewline
37 & 0.119178 & 1.3001 & 0.098043 \tabularnewline
38 & -0.159262 & -1.7373 & 0.042457 \tabularnewline
39 & 0.109254 & 1.1918 & 0.117852 \tabularnewline
40 & -0.021928 & -0.2392 & 0.40568 \tabularnewline
41 & -0.088893 & -0.9697 & 0.167079 \tabularnewline
42 & 0.06249 & 0.6817 & 0.248383 \tabularnewline
43 & 0.033327 & 0.3636 & 0.358417 \tabularnewline
44 & 0.012911 & 0.1408 & 0.444115 \tabularnewline
45 & -0.036709 & -0.4005 & 0.344771 \tabularnewline
46 & 0.037943 & 0.4139 & 0.339842 \tabularnewline
47 & 0.011548 & 0.126 & 0.449981 \tabularnewline
48 & -0.131641 & -1.436 & 0.076808 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203044&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]-0.546444[/C][C]-5.961[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.052345[/C][C]0.571[/C][C]0.284533[/C][/ROW]
[ROW][C]3[/C][C]0.137731[/C][C]1.5025[/C][C]0.067812[/C][/ROW]
[ROW][C]4[/C][C]-0.252347[/C][C]-2.7528[/C][C]0.003418[/C][/ROW]
[ROW][C]5[/C][C]0.130041[/C][C]1.4186[/C][C]0.079317[/C][/ROW]
[ROW][C]6[/C][C]-0.019067[/C][C]-0.208[/C][C]0.417792[/C][/ROW]
[ROW][C]7[/C][C]-0.110364[/C][C]-1.2039[/C][C]0.115503[/C][/ROW]
[ROW][C]8[/C][C]0.220285[/C][C]2.403[/C][C]0.008902[/C][/ROW]
[ROW][C]9[/C][C]-0.039861[/C][C]-0.4348[/C][C]0.332235[/C][/ROW]
[ROW][C]10[/C][C]-0.102341[/C][C]-1.1164[/C][C]0.133248[/C][/ROW]
[ROW][C]11[/C][C]0.203173[/C][C]2.2164[/C][C]0.014284[/C][/ROW]
[ROW][C]12[/C][C]-0.198515[/C][C]-2.1655[/C][C]0.016171[/C][/ROW]
[ROW][C]13[/C][C]-0.059016[/C][C]-0.6438[/C][C]0.260475[/C][/ROW]
[ROW][C]14[/C][C]0.076569[/C][C]0.8353[/C][C]0.202621[/C][/ROW]
[ROW][C]15[/C][C]0.020266[/C][C]0.2211[/C][C]0.412707[/C][/ROW]
[ROW][C]16[/C][C]-0.000277[/C][C]-0.003[/C][C]0.498798[/C][/ROW]
[ROW][C]17[/C][C]-0.005856[/C][C]-0.0639[/C][C]0.474587[/C][/ROW]
[ROW][C]18[/C][C]0.094907[/C][C]1.0353[/C][C]0.151311[/C][/ROW]
[ROW][C]19[/C][C]-0.105584[/C][C]-1.1518[/C][C]0.125859[/C][/ROW]
[ROW][C]20[/C][C]0.017316[/C][C]0.1889[/C][C]0.42525[/C][/ROW]
[ROW][C]21[/C][C]0.049891[/C][C]0.5442[/C][C]0.293645[/C][/ROW]
[ROW][C]22[/C][C]-0.138388[/C][C]-1.5096[/C][C]0.066894[/C][/ROW]
[ROW][C]23[/C][C]0.133715[/C][C]1.4587[/C][C]0.073646[/C][/ROW]
[ROW][C]24[/C][C]-0.102799[/C][C]-1.1214[/C][C]0.132187[/C][/ROW]
[ROW][C]25[/C][C]0.016348[/C][C]0.1783[/C][C]0.429379[/C][/ROW]
[ROW][C]26[/C][C]0.161903[/C][C]1.7661[/C][C]0.039968[/C][/ROW]
[ROW][C]27[/C][C]-0.200246[/C][C]-2.1844[/C][C]0.015446[/C][/ROW]
[ROW][C]28[/C][C]0.039965[/C][C]0.436[/C][C]0.331827[/C][/ROW]
[ROW][C]29[/C][C]0.141775[/C][C]1.5466[/C][C]0.06231[/C][/ROW]
[ROW][C]30[/C][C]-0.222695[/C][C]-2.4293[/C][C]0.008311[/C][/ROW]
[ROW][C]31[/C][C]0.11492[/C][C]1.2536[/C][C]0.106218[/C][/ROW]
[ROW][C]32[/C][C]0.03181[/C][C]0.347[/C][C]0.364599[/C][/ROW]
[ROW][C]33[/C][C]-0.173765[/C][C]-1.8956[/C][C]0.030222[/C][/ROW]
[ROW][C]34[/C][C]0.171271[/C][C]1.8683[/C][C]0.032087[/C][/ROW]
[ROW][C]35[/C][C]-0.018598[/C][C]-0.2029[/C][C]0.419789[/C][/ROW]
[ROW][C]36[/C][C]-0.05327[/C][C]-0.5811[/C][C]0.281132[/C][/ROW]
[ROW][C]37[/C][C]0.119178[/C][C]1.3001[/C][C]0.098043[/C][/ROW]
[ROW][C]38[/C][C]-0.159262[/C][C]-1.7373[/C][C]0.042457[/C][/ROW]
[ROW][C]39[/C][C]0.109254[/C][C]1.1918[/C][C]0.117852[/C][/ROW]
[ROW][C]40[/C][C]-0.021928[/C][C]-0.2392[/C][C]0.40568[/C][/ROW]
[ROW][C]41[/C][C]-0.088893[/C][C]-0.9697[/C][C]0.167079[/C][/ROW]
[ROW][C]42[/C][C]0.06249[/C][C]0.6817[/C][C]0.248383[/C][/ROW]
[ROW][C]43[/C][C]0.033327[/C][C]0.3636[/C][C]0.358417[/C][/ROW]
[ROW][C]44[/C][C]0.012911[/C][C]0.1408[/C][C]0.444115[/C][/ROW]
[ROW][C]45[/C][C]-0.036709[/C][C]-0.4005[/C][C]0.344771[/C][/ROW]
[ROW][C]46[/C][C]0.037943[/C][C]0.4139[/C][C]0.339842[/C][/ROW]
[ROW][C]47[/C][C]0.011548[/C][C]0.126[/C][C]0.449981[/C][/ROW]
[ROW][C]48[/C][C]-0.131641[/C][C]-1.436[/C][C]0.076808[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203044&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203044&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Autocorrelation Function
Time lag kACF(k)T-STATP-value
1-0.546444-5.9610
20.0523450.5710.284533
30.1377311.50250.067812
4-0.252347-2.75280.003418
50.1300411.41860.079317
6-0.019067-0.2080.417792
7-0.110364-1.20390.115503
80.2202852.4030.008902
9-0.039861-0.43480.332235
10-0.102341-1.11640.133248
110.2031732.21640.014284
12-0.198515-2.16550.016171
13-0.059016-0.64380.260475
140.0765690.83530.202621
150.0202660.22110.412707
16-0.000277-0.0030.498798
17-0.005856-0.06390.474587
180.0949071.03530.151311
19-0.105584-1.15180.125859
200.0173160.18890.42525
210.0498910.54420.293645
22-0.138388-1.50960.066894
230.1337151.45870.073646
24-0.102799-1.12140.132187
250.0163480.17830.429379
260.1619031.76610.039968
27-0.200246-2.18440.015446
280.0399650.4360.331827
290.1417751.54660.06231
30-0.222695-2.42930.008311
310.114921.25360.106218
320.031810.3470.364599
33-0.173765-1.89560.030222
340.1712711.86830.032087
35-0.018598-0.20290.419789
36-0.05327-0.58110.281132
370.1191781.30010.098043
38-0.159262-1.73730.042457
390.1092541.19180.117852
40-0.021928-0.23920.40568
41-0.088893-0.96970.167079
420.062490.68170.248383
430.0333270.36360.358417
440.0129110.14080.444115
45-0.036709-0.40050.344771
460.0379430.41390.339842
470.0115480.1260.449981
48-0.131641-1.4360.076808







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.546444-5.9610
2-0.351093-3.830.000103
3-0.025166-0.27450.392077
4-0.234065-2.55330.005967
5-0.197253-2.15180.016718
6-0.157684-1.72010.044004
7-0.265257-2.89360.002265
8-0.054772-0.59750.275656
90.1323141.44340.075771
100.0176020.1920.42403
110.199492.17620.015759
120.1537131.67680.048103
13-0.092311-1.0070.15799
14-0.207284-2.26120.012782
150.0078010.08510.466163
16-0.006357-0.06930.472416
17-0.157395-1.7170.044292
180.0665290.72570.234711
19-0.025959-0.28320.388764
20-0.100316-1.09430.138012
210.1882032.05310.02113
220.0896970.97850.164912
230.0497770.5430.294073
24-0.012206-0.13320.447149
25-0.108872-1.18770.118667
26-0.088178-0.96190.169024
27-0.127504-1.39090.083425
28-0.179239-1.95530.026448
29-0.057495-0.62720.265866
30-0.078338-0.85460.197253
31-0.075362-0.82210.20633
320.0183650.20030.420779
33-0.082642-0.90150.184566
34-0.140311-1.53060.064259
350.0332920.36320.358559
360.0283360.30910.37889
37-0.022217-0.24240.404458
38-0.059388-0.64780.259167
390.1046211.14130.128023
404e-054e-040.499827
41-0.041509-0.45280.325755
420.0085150.09290.463074
43-0.021332-0.23270.408194
440.0458860.50060.308805
450.0558780.60960.271659
46-0.020062-0.21890.41357
470.0640330.69850.243107
480.0006810.00740.497043

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & -0.546444 & -5.961 & 0 \tabularnewline
2 & -0.351093 & -3.83 & 0.000103 \tabularnewline
3 & -0.025166 & -0.2745 & 0.392077 \tabularnewline
4 & -0.234065 & -2.5533 & 0.005967 \tabularnewline
5 & -0.197253 & -2.1518 & 0.016718 \tabularnewline
6 & -0.157684 & -1.7201 & 0.044004 \tabularnewline
7 & -0.265257 & -2.8936 & 0.002265 \tabularnewline
8 & -0.054772 & -0.5975 & 0.275656 \tabularnewline
9 & 0.132314 & 1.4434 & 0.075771 \tabularnewline
10 & 0.017602 & 0.192 & 0.42403 \tabularnewline
11 & 0.19949 & 2.1762 & 0.015759 \tabularnewline
12 & 0.153713 & 1.6768 & 0.048103 \tabularnewline
13 & -0.092311 & -1.007 & 0.15799 \tabularnewline
14 & -0.207284 & -2.2612 & 0.012782 \tabularnewline
15 & 0.007801 & 0.0851 & 0.466163 \tabularnewline
16 & -0.006357 & -0.0693 & 0.472416 \tabularnewline
17 & -0.157395 & -1.717 & 0.044292 \tabularnewline
18 & 0.066529 & 0.7257 & 0.234711 \tabularnewline
19 & -0.025959 & -0.2832 & 0.388764 \tabularnewline
20 & -0.100316 & -1.0943 & 0.138012 \tabularnewline
21 & 0.188203 & 2.0531 & 0.02113 \tabularnewline
22 & 0.089697 & 0.9785 & 0.164912 \tabularnewline
23 & 0.049777 & 0.543 & 0.294073 \tabularnewline
24 & -0.012206 & -0.1332 & 0.447149 \tabularnewline
25 & -0.108872 & -1.1877 & 0.118667 \tabularnewline
26 & -0.088178 & -0.9619 & 0.169024 \tabularnewline
27 & -0.127504 & -1.3909 & 0.083425 \tabularnewline
28 & -0.179239 & -1.9553 & 0.026448 \tabularnewline
29 & -0.057495 & -0.6272 & 0.265866 \tabularnewline
30 & -0.078338 & -0.8546 & 0.197253 \tabularnewline
31 & -0.075362 & -0.8221 & 0.20633 \tabularnewline
32 & 0.018365 & 0.2003 & 0.420779 \tabularnewline
33 & -0.082642 & -0.9015 & 0.184566 \tabularnewline
34 & -0.140311 & -1.5306 & 0.064259 \tabularnewline
35 & 0.033292 & 0.3632 & 0.358559 \tabularnewline
36 & 0.028336 & 0.3091 & 0.37889 \tabularnewline
37 & -0.022217 & -0.2424 & 0.404458 \tabularnewline
38 & -0.059388 & -0.6478 & 0.259167 \tabularnewline
39 & 0.104621 & 1.1413 & 0.128023 \tabularnewline
40 & 4e-05 & 4e-04 & 0.499827 \tabularnewline
41 & -0.041509 & -0.4528 & 0.325755 \tabularnewline
42 & 0.008515 & 0.0929 & 0.463074 \tabularnewline
43 & -0.021332 & -0.2327 & 0.408194 \tabularnewline
44 & 0.045886 & 0.5006 & 0.308805 \tabularnewline
45 & 0.055878 & 0.6096 & 0.271659 \tabularnewline
46 & -0.020062 & -0.2189 & 0.41357 \tabularnewline
47 & 0.064033 & 0.6985 & 0.243107 \tabularnewline
48 & 0.000681 & 0.0074 & 0.497043 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203044&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]-0.546444[/C][C]-5.961[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.351093[/C][C]-3.83[/C][C]0.000103[/C][/ROW]
[ROW][C]3[/C][C]-0.025166[/C][C]-0.2745[/C][C]0.392077[/C][/ROW]
[ROW][C]4[/C][C]-0.234065[/C][C]-2.5533[/C][C]0.005967[/C][/ROW]
[ROW][C]5[/C][C]-0.197253[/C][C]-2.1518[/C][C]0.016718[/C][/ROW]
[ROW][C]6[/C][C]-0.157684[/C][C]-1.7201[/C][C]0.044004[/C][/ROW]
[ROW][C]7[/C][C]-0.265257[/C][C]-2.8936[/C][C]0.002265[/C][/ROW]
[ROW][C]8[/C][C]-0.054772[/C][C]-0.5975[/C][C]0.275656[/C][/ROW]
[ROW][C]9[/C][C]0.132314[/C][C]1.4434[/C][C]0.075771[/C][/ROW]
[ROW][C]10[/C][C]0.017602[/C][C]0.192[/C][C]0.42403[/C][/ROW]
[ROW][C]11[/C][C]0.19949[/C][C]2.1762[/C][C]0.015759[/C][/ROW]
[ROW][C]12[/C][C]0.153713[/C][C]1.6768[/C][C]0.048103[/C][/ROW]
[ROW][C]13[/C][C]-0.092311[/C][C]-1.007[/C][C]0.15799[/C][/ROW]
[ROW][C]14[/C][C]-0.207284[/C][C]-2.2612[/C][C]0.012782[/C][/ROW]
[ROW][C]15[/C][C]0.007801[/C][C]0.0851[/C][C]0.466163[/C][/ROW]
[ROW][C]16[/C][C]-0.006357[/C][C]-0.0693[/C][C]0.472416[/C][/ROW]
[ROW][C]17[/C][C]-0.157395[/C][C]-1.717[/C][C]0.044292[/C][/ROW]
[ROW][C]18[/C][C]0.066529[/C][C]0.7257[/C][C]0.234711[/C][/ROW]
[ROW][C]19[/C][C]-0.025959[/C][C]-0.2832[/C][C]0.388764[/C][/ROW]
[ROW][C]20[/C][C]-0.100316[/C][C]-1.0943[/C][C]0.138012[/C][/ROW]
[ROW][C]21[/C][C]0.188203[/C][C]2.0531[/C][C]0.02113[/C][/ROW]
[ROW][C]22[/C][C]0.089697[/C][C]0.9785[/C][C]0.164912[/C][/ROW]
[ROW][C]23[/C][C]0.049777[/C][C]0.543[/C][C]0.294073[/C][/ROW]
[ROW][C]24[/C][C]-0.012206[/C][C]-0.1332[/C][C]0.447149[/C][/ROW]
[ROW][C]25[/C][C]-0.108872[/C][C]-1.1877[/C][C]0.118667[/C][/ROW]
[ROW][C]26[/C][C]-0.088178[/C][C]-0.9619[/C][C]0.169024[/C][/ROW]
[ROW][C]27[/C][C]-0.127504[/C][C]-1.3909[/C][C]0.083425[/C][/ROW]
[ROW][C]28[/C][C]-0.179239[/C][C]-1.9553[/C][C]0.026448[/C][/ROW]
[ROW][C]29[/C][C]-0.057495[/C][C]-0.6272[/C][C]0.265866[/C][/ROW]
[ROW][C]30[/C][C]-0.078338[/C][C]-0.8546[/C][C]0.197253[/C][/ROW]
[ROW][C]31[/C][C]-0.075362[/C][C]-0.8221[/C][C]0.20633[/C][/ROW]
[ROW][C]32[/C][C]0.018365[/C][C]0.2003[/C][C]0.420779[/C][/ROW]
[ROW][C]33[/C][C]-0.082642[/C][C]-0.9015[/C][C]0.184566[/C][/ROW]
[ROW][C]34[/C][C]-0.140311[/C][C]-1.5306[/C][C]0.064259[/C][/ROW]
[ROW][C]35[/C][C]0.033292[/C][C]0.3632[/C][C]0.358559[/C][/ROW]
[ROW][C]36[/C][C]0.028336[/C][C]0.3091[/C][C]0.37889[/C][/ROW]
[ROW][C]37[/C][C]-0.022217[/C][C]-0.2424[/C][C]0.404458[/C][/ROW]
[ROW][C]38[/C][C]-0.059388[/C][C]-0.6478[/C][C]0.259167[/C][/ROW]
[ROW][C]39[/C][C]0.104621[/C][C]1.1413[/C][C]0.128023[/C][/ROW]
[ROW][C]40[/C][C]4e-05[/C][C]4e-04[/C][C]0.499827[/C][/ROW]
[ROW][C]41[/C][C]-0.041509[/C][C]-0.4528[/C][C]0.325755[/C][/ROW]
[ROW][C]42[/C][C]0.008515[/C][C]0.0929[/C][C]0.463074[/C][/ROW]
[ROW][C]43[/C][C]-0.021332[/C][C]-0.2327[/C][C]0.408194[/C][/ROW]
[ROW][C]44[/C][C]0.045886[/C][C]0.5006[/C][C]0.308805[/C][/ROW]
[ROW][C]45[/C][C]0.055878[/C][C]0.6096[/C][C]0.271659[/C][/ROW]
[ROW][C]46[/C][C]-0.020062[/C][C]-0.2189[/C][C]0.41357[/C][/ROW]
[ROW][C]47[/C][C]0.064033[/C][C]0.6985[/C][C]0.243107[/C][/ROW]
[ROW][C]48[/C][C]0.000681[/C][C]0.0074[/C][C]0.497043[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203044&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203044&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
1-0.546444-5.9610
2-0.351093-3.830.000103
3-0.025166-0.27450.392077
4-0.234065-2.55330.005967
5-0.197253-2.15180.016718
6-0.157684-1.72010.044004
7-0.265257-2.89360.002265
8-0.054772-0.59750.275656
90.1323141.44340.075771
100.0176020.1920.42403
110.199492.17620.015759
120.1537131.67680.048103
13-0.092311-1.0070.15799
14-0.207284-2.26120.012782
150.0078010.08510.466163
16-0.006357-0.06930.472416
17-0.157395-1.7170.044292
180.0665290.72570.234711
19-0.025959-0.28320.388764
20-0.100316-1.09430.138012
210.1882032.05310.02113
220.0896970.97850.164912
230.0497770.5430.294073
24-0.012206-0.13320.447149
25-0.108872-1.18770.118667
26-0.088178-0.96190.169024
27-0.127504-1.39090.083425
28-0.179239-1.95530.026448
29-0.057495-0.62720.265866
30-0.078338-0.85460.197253
31-0.075362-0.82210.20633
320.0183650.20030.420779
33-0.082642-0.90150.184566
34-0.140311-1.53060.064259
350.0332920.36320.358559
360.0283360.30910.37889
37-0.022217-0.24240.404458
38-0.059388-0.64780.259167
390.1046211.14130.128023
404e-054e-040.499827
41-0.041509-0.45280.325755
420.0085150.09290.463074
43-0.021332-0.23270.408194
440.0458860.50060.308805
450.0558780.60960.271659
46-0.020062-0.21890.41357
470.0640330.69850.243107
480.0006810.00740.497043



Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')