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Author's title

Author*Unverified author*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationMon, 12 Aug 2013 09:54:06 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Aug/12/t1376315686xw1ljyulnk6oy9f.htm/, Retrieved Sat, 27 Apr 2024 16:05:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=211034, Retrieved Sat, 27 Apr 2024 16:05:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsAnthony Van Dyck
Estimated Impact125
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Tijdreeks 1 - stap 2] [2013-08-12 11:07:04] [c4bfab449d963e708b9482b0c0d301bf]
-   P   [Univariate Data Series] [Tijdreeks A - Stap 2] [2013-08-12 11:17:51] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RMP     [Histogram] [Tijdreeks A - Stap 3] [2013-08-12 11:22:38] [fffbdc2eb6bf36a612a50d50ad291a0a]
- R P       [Histogram] [Tijdreeks A -stap 5] [2013-08-12 11:38:26] [c4bfab449d963e708b9482b0c0d301bf]
-   P         [Histogram] [Tijdreeks A -stap 5] [2013-08-12 11:42:06] [c4bfab449d963e708b9482b0c0d301bf]
- RMP           [Harrell-Davis Quantiles] [Tijdreeks A - sta...] [2013-08-12 12:35:57] [fffbdc2eb6bf36a612a50d50ad291a0a]
- R P             [Harrell-Davis Quantiles] [Tijdreeks A - sta...] [2013-08-12 12:48:29] [c4bfab449d963e708b9482b0c0d301bf]
- RMP                 [(Partial) Autocorrelation Function] [Tijdreeks A - sta...] [2013-08-12 13:54:06] [946b987ea445738c2c70467dba74cc4f] [Current]
- R                     [(Partial) Autocorrelation Function] [Tijdreeks A - sta...] [2013-08-12 14:00:03] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM                    [Standard Deviation Plot] [Tijdreeks A - sta...] [2013-08-12 14:05:51] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM                    [Standard Deviation-Mean Plot] [Tijdreeks A - sta...] [2013-08-12 14:17:35] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM                    [Classical Decomposition] [Tijdreeks A - sta...] [2013-08-12 14:36:54] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM                    [Exponential Smoothing] [Tijdreeks A - sta...] [2013-08-12 15:06:04] [c4bfab449d963e708b9482b0c0d301bf]
- RM                    [Univariate Data Series] [Tijdreeks A - Stap 2] [2013-08-12 15:48:08] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM D                  [Univariate Data Series] [Tijdreeks A - stap 1] [2013-08-12 15:56:05] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM D                  [Histogram] [Tijdreeks B - stap 2] [2013-08-12 15:59:35] [fffbdc2eb6bf36a612a50d50ad291a0a]
- RM D                  [Kernel Density Estimation] [Tijdreeks B - stap 4] [2013-08-12 16:02:09] [c4bfab449d963e708b9482b0c0d301bf]
- RM D                  [Harrell-Davis Quantiles] [Tijdreeks B - stap 5] [2013-08-12 16:14:20] [fffbdc2eb6bf36a612a50d50ad291a0a]
- R                       [Harrell-Davis Quantiles] [Tijdreeks B - stap 6] [2013-08-12 16:15:41] [fffbdc2eb6bf36a612a50d50ad291a0a]
-                           [Harrell-Davis Quantiles] [Tijdreeks B - stap 7] [2013-08-12 16:18:33] [fffbdc2eb6bf36a612a50d50ad291a0a]
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Dataseries X:
36439
36368
36290
36147
37615
37543
36439
35705
35777
35777
35848
35998
35998
35335
35043
35335
36368
36218
34822
33640
33419
32977
33276
33640
33497
33198
32614
33198
33718
33568
31873
31139
30405
29814
29743
30184
29593
29372
29151
30405
30548
29814
27826
26943
25547
24955
25247
25689
25689
25326
25247
26430
27385
26943
25468
24735
23189
22234
22968
23702
23702
22747
22676
23922
24735
24442
22968
22013
19947
19142
19434
20688
20759
18921
19584
21201
21935
21493
19506
18109
16492
15238
15751
16855
16563
14946
15459
17076
17960
17447
15459
14576
13251
11854
12075
13179
13322
11997
12218
14063
14504
13764
11042
9646
7801
5963
6554
7359
7217
5813
6625
8613
9496
9055
7288
5892
4417
2721
3021
3534




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211034&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211034&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211034&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 time5 seconds
R Server'George Udny Yule' @ yule.wessa.net







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.97090510.63570
20.93607910.25420
30.9019589.88050
40.8732699.56620
50.8459979.26740
60.8213678.99760
70.8018738.78410
80.7839968.58820
90.7650768.3810
100.7455148.16670
110.7257927.95070
120.7036077.70760
130.6726687.36870
140.6367776.97550
150.6011326.58510
160.570036.24440
170.5413585.93030
180.5153575.64550
190.4962835.43650
200.4797175.2550
210.4632095.07421e-06
220.4465544.89172e-06
230.4302344.7133e-06
240.4114924.50778e-06
250.3852184.21992.4e-05
260.3537043.87468.7e-05
270.3232973.54150.000284
280.2961373.2440.000763
290.2712682.97160.00179
300.2482872.71980.003751
310.2310612.53110.006331
320.2153682.35920.009964
330.1996892.18750.015323
340.1843412.01940.022839
350.1690781.85220.03323
360.1522971.66830.048929
370.1304681.42920.077771
380.1037621.13670.128973
390.0768880.84230.200656
400.0518560.56810.28553
410.0300650.32930.371235
420.0118450.12980.448488
43-0.000504-0.00550.4978
44-0.011506-0.1260.449957
45-0.02153-0.23590.406974
46-0.031446-0.34450.365548
47-0.042088-0.46110.322797
48-0.053259-0.58340.280352
49-0.069407-0.76030.224279
50-0.089858-0.98430.163463
51-0.110541-1.21090.114154
52-0.130433-1.42880.077827
53-0.147324-1.61390.054593
54-0.161484-1.7690.03972
55-0.17154-1.87910.031327
56-0.180922-1.98190.024888
57-0.189233-2.07290.020159
58-0.196641-2.15410.016616
59-0.204319-2.23820.013526
60-0.213718-2.34120.010437

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.970905 & 10.6357 & 0 \tabularnewline
2 & 0.936079 & 10.2542 & 0 \tabularnewline
3 & 0.901958 & 9.8805 & 0 \tabularnewline
4 & 0.873269 & 9.5662 & 0 \tabularnewline
5 & 0.845997 & 9.2674 & 0 \tabularnewline
6 & 0.821367 & 8.9976 & 0 \tabularnewline
7 & 0.801873 & 8.7841 & 0 \tabularnewline
8 & 0.783996 & 8.5882 & 0 \tabularnewline
9 & 0.765076 & 8.381 & 0 \tabularnewline
10 & 0.745514 & 8.1667 & 0 \tabularnewline
11 & 0.725792 & 7.9507 & 0 \tabularnewline
12 & 0.703607 & 7.7076 & 0 \tabularnewline
13 & 0.672668 & 7.3687 & 0 \tabularnewline
14 & 0.636777 & 6.9755 & 0 \tabularnewline
15 & 0.601132 & 6.5851 & 0 \tabularnewline
16 & 0.57003 & 6.2444 & 0 \tabularnewline
17 & 0.541358 & 5.9303 & 0 \tabularnewline
18 & 0.515357 & 5.6455 & 0 \tabularnewline
19 & 0.496283 & 5.4365 & 0 \tabularnewline
20 & 0.479717 & 5.255 & 0 \tabularnewline
21 & 0.463209 & 5.0742 & 1e-06 \tabularnewline
22 & 0.446554 & 4.8917 & 2e-06 \tabularnewline
23 & 0.430234 & 4.713 & 3e-06 \tabularnewline
24 & 0.411492 & 4.5077 & 8e-06 \tabularnewline
25 & 0.385218 & 4.2199 & 2.4e-05 \tabularnewline
26 & 0.353704 & 3.8746 & 8.7e-05 \tabularnewline
27 & 0.323297 & 3.5415 & 0.000284 \tabularnewline
28 & 0.296137 & 3.244 & 0.000763 \tabularnewline
29 & 0.271268 & 2.9716 & 0.00179 \tabularnewline
30 & 0.248287 & 2.7198 & 0.003751 \tabularnewline
31 & 0.231061 & 2.5311 & 0.006331 \tabularnewline
32 & 0.215368 & 2.3592 & 0.009964 \tabularnewline
33 & 0.199689 & 2.1875 & 0.015323 \tabularnewline
34 & 0.184341 & 2.0194 & 0.022839 \tabularnewline
35 & 0.169078 & 1.8522 & 0.03323 \tabularnewline
36 & 0.152297 & 1.6683 & 0.048929 \tabularnewline
37 & 0.130468 & 1.4292 & 0.077771 \tabularnewline
38 & 0.103762 & 1.1367 & 0.128973 \tabularnewline
39 & 0.076888 & 0.8423 & 0.200656 \tabularnewline
40 & 0.051856 & 0.5681 & 0.28553 \tabularnewline
41 & 0.030065 & 0.3293 & 0.371235 \tabularnewline
42 & 0.011845 & 0.1298 & 0.448488 \tabularnewline
43 & -0.000504 & -0.0055 & 0.4978 \tabularnewline
44 & -0.011506 & -0.126 & 0.449957 \tabularnewline
45 & -0.02153 & -0.2359 & 0.406974 \tabularnewline
46 & -0.031446 & -0.3445 & 0.365548 \tabularnewline
47 & -0.042088 & -0.4611 & 0.322797 \tabularnewline
48 & -0.053259 & -0.5834 & 0.280352 \tabularnewline
49 & -0.069407 & -0.7603 & 0.224279 \tabularnewline
50 & -0.089858 & -0.9843 & 0.163463 \tabularnewline
51 & -0.110541 & -1.2109 & 0.114154 \tabularnewline
52 & -0.130433 & -1.4288 & 0.077827 \tabularnewline
53 & -0.147324 & -1.6139 & 0.054593 \tabularnewline
54 & -0.161484 & -1.769 & 0.03972 \tabularnewline
55 & -0.17154 & -1.8791 & 0.031327 \tabularnewline
56 & -0.180922 & -1.9819 & 0.024888 \tabularnewline
57 & -0.189233 & -2.0729 & 0.020159 \tabularnewline
58 & -0.196641 & -2.1541 & 0.016616 \tabularnewline
59 & -0.204319 & -2.2382 & 0.013526 \tabularnewline
60 & -0.213718 & -2.3412 & 0.010437 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211034&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]0.970905[/C][C]10.6357[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.936079[/C][C]10.2542[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.901958[/C][C]9.8805[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.873269[/C][C]9.5662[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.845997[/C][C]9.2674[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.821367[/C][C]8.9976[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.801873[/C][C]8.7841[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.783996[/C][C]8.5882[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.765076[/C][C]8.381[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.745514[/C][C]8.1667[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.725792[/C][C]7.9507[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.703607[/C][C]7.7076[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.672668[/C][C]7.3687[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.636777[/C][C]6.9755[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.601132[/C][C]6.5851[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.57003[/C][C]6.2444[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.541358[/C][C]5.9303[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.515357[/C][C]5.6455[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.496283[/C][C]5.4365[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.479717[/C][C]5.255[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.463209[/C][C]5.0742[/C][C]1e-06[/C][/ROW]
[ROW][C]22[/C][C]0.446554[/C][C]4.8917[/C][C]2e-06[/C][/ROW]
[ROW][C]23[/C][C]0.430234[/C][C]4.713[/C][C]3e-06[/C][/ROW]
[ROW][C]24[/C][C]0.411492[/C][C]4.5077[/C][C]8e-06[/C][/ROW]
[ROW][C]25[/C][C]0.385218[/C][C]4.2199[/C][C]2.4e-05[/C][/ROW]
[ROW][C]26[/C][C]0.353704[/C][C]3.8746[/C][C]8.7e-05[/C][/ROW]
[ROW][C]27[/C][C]0.323297[/C][C]3.5415[/C][C]0.000284[/C][/ROW]
[ROW][C]28[/C][C]0.296137[/C][C]3.244[/C][C]0.000763[/C][/ROW]
[ROW][C]29[/C][C]0.271268[/C][C]2.9716[/C][C]0.00179[/C][/ROW]
[ROW][C]30[/C][C]0.248287[/C][C]2.7198[/C][C]0.003751[/C][/ROW]
[ROW][C]31[/C][C]0.231061[/C][C]2.5311[/C][C]0.006331[/C][/ROW]
[ROW][C]32[/C][C]0.215368[/C][C]2.3592[/C][C]0.009964[/C][/ROW]
[ROW][C]33[/C][C]0.199689[/C][C]2.1875[/C][C]0.015323[/C][/ROW]
[ROW][C]34[/C][C]0.184341[/C][C]2.0194[/C][C]0.022839[/C][/ROW]
[ROW][C]35[/C][C]0.169078[/C][C]1.8522[/C][C]0.03323[/C][/ROW]
[ROW][C]36[/C][C]0.152297[/C][C]1.6683[/C][C]0.048929[/C][/ROW]
[ROW][C]37[/C][C]0.130468[/C][C]1.4292[/C][C]0.077771[/C][/ROW]
[ROW][C]38[/C][C]0.103762[/C][C]1.1367[/C][C]0.128973[/C][/ROW]
[ROW][C]39[/C][C]0.076888[/C][C]0.8423[/C][C]0.200656[/C][/ROW]
[ROW][C]40[/C][C]0.051856[/C][C]0.5681[/C][C]0.28553[/C][/ROW]
[ROW][C]41[/C][C]0.030065[/C][C]0.3293[/C][C]0.371235[/C][/ROW]
[ROW][C]42[/C][C]0.011845[/C][C]0.1298[/C][C]0.448488[/C][/ROW]
[ROW][C]43[/C][C]-0.000504[/C][C]-0.0055[/C][C]0.4978[/C][/ROW]
[ROW][C]44[/C][C]-0.011506[/C][C]-0.126[/C][C]0.449957[/C][/ROW]
[ROW][C]45[/C][C]-0.02153[/C][C]-0.2359[/C][C]0.406974[/C][/ROW]
[ROW][C]46[/C][C]-0.031446[/C][C]-0.3445[/C][C]0.365548[/C][/ROW]
[ROW][C]47[/C][C]-0.042088[/C][C]-0.4611[/C][C]0.322797[/C][/ROW]
[ROW][C]48[/C][C]-0.053259[/C][C]-0.5834[/C][C]0.280352[/C][/ROW]
[ROW][C]49[/C][C]-0.069407[/C][C]-0.7603[/C][C]0.224279[/C][/ROW]
[ROW][C]50[/C][C]-0.089858[/C][C]-0.9843[/C][C]0.163463[/C][/ROW]
[ROW][C]51[/C][C]-0.110541[/C][C]-1.2109[/C][C]0.114154[/C][/ROW]
[ROW][C]52[/C][C]-0.130433[/C][C]-1.4288[/C][C]0.077827[/C][/ROW]
[ROW][C]53[/C][C]-0.147324[/C][C]-1.6139[/C][C]0.054593[/C][/ROW]
[ROW][C]54[/C][C]-0.161484[/C][C]-1.769[/C][C]0.03972[/C][/ROW]
[ROW][C]55[/C][C]-0.17154[/C][C]-1.8791[/C][C]0.031327[/C][/ROW]
[ROW][C]56[/C][C]-0.180922[/C][C]-1.9819[/C][C]0.024888[/C][/ROW]
[ROW][C]57[/C][C]-0.189233[/C][C]-2.0729[/C][C]0.020159[/C][/ROW]
[ROW][C]58[/C][C]-0.196641[/C][C]-2.1541[/C][C]0.016616[/C][/ROW]
[ROW][C]59[/C][C]-0.204319[/C][C]-2.2382[/C][C]0.013526[/C][/ROW]
[ROW][C]60[/C][C]-0.213718[/C][C]-2.3412[/C][C]0.010437[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211034&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211034&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
10.97090510.63570
20.93607910.25420
30.9019589.88050
40.8732699.56620
50.8459979.26740
60.8213678.99760
70.8018738.78410
80.7839968.58820
90.7650768.3810
100.7455148.16670
110.7257927.95070
120.7036077.70760
130.6726687.36870
140.6367776.97550
150.6011326.58510
160.570036.24440
170.5413585.93030
180.5153575.64550
190.4962835.43650
200.4797175.2550
210.4632095.07421e-06
220.4465544.89172e-06
230.4302344.7133e-06
240.4114924.50778e-06
250.3852184.21992.4e-05
260.3537043.87468.7e-05
270.3232973.54150.000284
280.2961373.2440.000763
290.2712682.97160.00179
300.2482872.71980.003751
310.2310612.53110.006331
320.2153682.35920.009964
330.1996892.18750.015323
340.1843412.01940.022839
350.1690781.85220.03323
360.1522971.66830.048929
370.1304681.42920.077771
380.1037621.13670.128973
390.0768880.84230.200656
400.0518560.56810.28553
410.0300650.32930.371235
420.0118450.12980.448488
43-0.000504-0.00550.4978
44-0.011506-0.1260.449957
45-0.02153-0.23590.406974
46-0.031446-0.34450.365548
47-0.042088-0.46110.322797
48-0.053259-0.58340.280352
49-0.069407-0.76030.224279
50-0.089858-0.98430.163463
51-0.110541-1.21090.114154
52-0.130433-1.42880.077827
53-0.147324-1.61390.054593
54-0.161484-1.7690.03972
55-0.17154-1.87910.031327
56-0.180922-1.98190.024888
57-0.189233-2.07290.020159
58-0.196641-2.15410.016616
59-0.204319-2.23820.013526
60-0.213718-2.34120.010437







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.97090510.63570
2-0.114681-1.25630.105729
30.0041010.04490.482122
40.0746550.81780.207546
5-0.008505-0.09320.462965
60.0310570.34020.367147
70.0773770.84760.199168
80.0034040.03730.485158
9-0.023327-0.25550.399375
10-0.001094-0.0120.495229
11-0.006365-0.06970.472265
12-0.051296-0.56190.287609
13-0.152897-1.67490.048278
14-0.078823-0.86350.194802
15-0.017262-0.18910.425168
160.0282240.30920.37886
17-0.006932-0.07590.469797
180.0090180.09880.460734
190.0860710.94290.173824
200.0055790.06110.475687
210.0006470.00710.49718
220.0227970.24970.401612
230.0100190.10980.456393
24-0.037829-0.41440.339663
25-0.102882-1.1270.130993
26-0.069699-0.76350.223328
27-0.000416-0.00460.498186
28-0.007965-0.08730.465308
29-0.017754-0.19450.423061
30-0.013452-0.14740.441546
310.0433670.47510.317803
32-0.023565-0.25810.39837
33-0.004003-0.04390.482548
340.0292660.32060.374539
35-0.001534-0.01680.493311
36-0.018685-0.20470.419081
37-0.044102-0.48310.314949
38-0.058006-0.63540.263179
39-0.019713-0.21590.414698
40-0.02455-0.26890.394222
410.0001970.00220.499142
420.0127680.13990.444499
430.034880.38210.351533
44-0.028257-0.30950.378723
450.017380.19040.424664
460.0185930.20370.419475
47-0.0166-0.18180.428006
480.0065620.07190.471408
49-0.045659-0.50020.308935
50-0.049879-0.54640.292902
51-0.011687-0.1280.449174
52-0.036323-0.39790.345706
53-0.004342-0.04760.481073
54-0.008729-0.09560.461992
55-0.004214-0.04620.481627
56-0.03985-0.43650.331618
570.0141620.15510.438485
580.0203720.22320.411894
59-0.010069-0.11030.456176
60-0.015475-0.16950.432838

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.970905 & 10.6357 & 0 \tabularnewline
2 & -0.114681 & -1.2563 & 0.105729 \tabularnewline
3 & 0.004101 & 0.0449 & 0.482122 \tabularnewline
4 & 0.074655 & 0.8178 & 0.207546 \tabularnewline
5 & -0.008505 & -0.0932 & 0.462965 \tabularnewline
6 & 0.031057 & 0.3402 & 0.367147 \tabularnewline
7 & 0.077377 & 0.8476 & 0.199168 \tabularnewline
8 & 0.003404 & 0.0373 & 0.485158 \tabularnewline
9 & -0.023327 & -0.2555 & 0.399375 \tabularnewline
10 & -0.001094 & -0.012 & 0.495229 \tabularnewline
11 & -0.006365 & -0.0697 & 0.472265 \tabularnewline
12 & -0.051296 & -0.5619 & 0.287609 \tabularnewline
13 & -0.152897 & -1.6749 & 0.048278 \tabularnewline
14 & -0.078823 & -0.8635 & 0.194802 \tabularnewline
15 & -0.017262 & -0.1891 & 0.425168 \tabularnewline
16 & 0.028224 & 0.3092 & 0.37886 \tabularnewline
17 & -0.006932 & -0.0759 & 0.469797 \tabularnewline
18 & 0.009018 & 0.0988 & 0.460734 \tabularnewline
19 & 0.086071 & 0.9429 & 0.173824 \tabularnewline
20 & 0.005579 & 0.0611 & 0.475687 \tabularnewline
21 & 0.000647 & 0.0071 & 0.49718 \tabularnewline
22 & 0.022797 & 0.2497 & 0.401612 \tabularnewline
23 & 0.010019 & 0.1098 & 0.456393 \tabularnewline
24 & -0.037829 & -0.4144 & 0.339663 \tabularnewline
25 & -0.102882 & -1.127 & 0.130993 \tabularnewline
26 & -0.069699 & -0.7635 & 0.223328 \tabularnewline
27 & -0.000416 & -0.0046 & 0.498186 \tabularnewline
28 & -0.007965 & -0.0873 & 0.465308 \tabularnewline
29 & -0.017754 & -0.1945 & 0.423061 \tabularnewline
30 & -0.013452 & -0.1474 & 0.441546 \tabularnewline
31 & 0.043367 & 0.4751 & 0.317803 \tabularnewline
32 & -0.023565 & -0.2581 & 0.39837 \tabularnewline
33 & -0.004003 & -0.0439 & 0.482548 \tabularnewline
34 & 0.029266 & 0.3206 & 0.374539 \tabularnewline
35 & -0.001534 & -0.0168 & 0.493311 \tabularnewline
36 & -0.018685 & -0.2047 & 0.419081 \tabularnewline
37 & -0.044102 & -0.4831 & 0.314949 \tabularnewline
38 & -0.058006 & -0.6354 & 0.263179 \tabularnewline
39 & -0.019713 & -0.2159 & 0.414698 \tabularnewline
40 & -0.02455 & -0.2689 & 0.394222 \tabularnewline
41 & 0.000197 & 0.0022 & 0.499142 \tabularnewline
42 & 0.012768 & 0.1399 & 0.444499 \tabularnewline
43 & 0.03488 & 0.3821 & 0.351533 \tabularnewline
44 & -0.028257 & -0.3095 & 0.378723 \tabularnewline
45 & 0.01738 & 0.1904 & 0.424664 \tabularnewline
46 & 0.018593 & 0.2037 & 0.419475 \tabularnewline
47 & -0.0166 & -0.1818 & 0.428006 \tabularnewline
48 & 0.006562 & 0.0719 & 0.471408 \tabularnewline
49 & -0.045659 & -0.5002 & 0.308935 \tabularnewline
50 & -0.049879 & -0.5464 & 0.292902 \tabularnewline
51 & -0.011687 & -0.128 & 0.449174 \tabularnewline
52 & -0.036323 & -0.3979 & 0.345706 \tabularnewline
53 & -0.004342 & -0.0476 & 0.481073 \tabularnewline
54 & -0.008729 & -0.0956 & 0.461992 \tabularnewline
55 & -0.004214 & -0.0462 & 0.481627 \tabularnewline
56 & -0.03985 & -0.4365 & 0.331618 \tabularnewline
57 & 0.014162 & 0.1551 & 0.438485 \tabularnewline
58 & 0.020372 & 0.2232 & 0.411894 \tabularnewline
59 & -0.010069 & -0.1103 & 0.456176 \tabularnewline
60 & -0.015475 & -0.1695 & 0.432838 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=211034&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]0.970905[/C][C]10.6357[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-0.114681[/C][C]-1.2563[/C][C]0.105729[/C][/ROW]
[ROW][C]3[/C][C]0.004101[/C][C]0.0449[/C][C]0.482122[/C][/ROW]
[ROW][C]4[/C][C]0.074655[/C][C]0.8178[/C][C]0.207546[/C][/ROW]
[ROW][C]5[/C][C]-0.008505[/C][C]-0.0932[/C][C]0.462965[/C][/ROW]
[ROW][C]6[/C][C]0.031057[/C][C]0.3402[/C][C]0.367147[/C][/ROW]
[ROW][C]7[/C][C]0.077377[/C][C]0.8476[/C][C]0.199168[/C][/ROW]
[ROW][C]8[/C][C]0.003404[/C][C]0.0373[/C][C]0.485158[/C][/ROW]
[ROW][C]9[/C][C]-0.023327[/C][C]-0.2555[/C][C]0.399375[/C][/ROW]
[ROW][C]10[/C][C]-0.001094[/C][C]-0.012[/C][C]0.495229[/C][/ROW]
[ROW][C]11[/C][C]-0.006365[/C][C]-0.0697[/C][C]0.472265[/C][/ROW]
[ROW][C]12[/C][C]-0.051296[/C][C]-0.5619[/C][C]0.287609[/C][/ROW]
[ROW][C]13[/C][C]-0.152897[/C][C]-1.6749[/C][C]0.048278[/C][/ROW]
[ROW][C]14[/C][C]-0.078823[/C][C]-0.8635[/C][C]0.194802[/C][/ROW]
[ROW][C]15[/C][C]-0.017262[/C][C]-0.1891[/C][C]0.425168[/C][/ROW]
[ROW][C]16[/C][C]0.028224[/C][C]0.3092[/C][C]0.37886[/C][/ROW]
[ROW][C]17[/C][C]-0.006932[/C][C]-0.0759[/C][C]0.469797[/C][/ROW]
[ROW][C]18[/C][C]0.009018[/C][C]0.0988[/C][C]0.460734[/C][/ROW]
[ROW][C]19[/C][C]0.086071[/C][C]0.9429[/C][C]0.173824[/C][/ROW]
[ROW][C]20[/C][C]0.005579[/C][C]0.0611[/C][C]0.475687[/C][/ROW]
[ROW][C]21[/C][C]0.000647[/C][C]0.0071[/C][C]0.49718[/C][/ROW]
[ROW][C]22[/C][C]0.022797[/C][C]0.2497[/C][C]0.401612[/C][/ROW]
[ROW][C]23[/C][C]0.010019[/C][C]0.1098[/C][C]0.456393[/C][/ROW]
[ROW][C]24[/C][C]-0.037829[/C][C]-0.4144[/C][C]0.339663[/C][/ROW]
[ROW][C]25[/C][C]-0.102882[/C][C]-1.127[/C][C]0.130993[/C][/ROW]
[ROW][C]26[/C][C]-0.069699[/C][C]-0.7635[/C][C]0.223328[/C][/ROW]
[ROW][C]27[/C][C]-0.000416[/C][C]-0.0046[/C][C]0.498186[/C][/ROW]
[ROW][C]28[/C][C]-0.007965[/C][C]-0.0873[/C][C]0.465308[/C][/ROW]
[ROW][C]29[/C][C]-0.017754[/C][C]-0.1945[/C][C]0.423061[/C][/ROW]
[ROW][C]30[/C][C]-0.013452[/C][C]-0.1474[/C][C]0.441546[/C][/ROW]
[ROW][C]31[/C][C]0.043367[/C][C]0.4751[/C][C]0.317803[/C][/ROW]
[ROW][C]32[/C][C]-0.023565[/C][C]-0.2581[/C][C]0.39837[/C][/ROW]
[ROW][C]33[/C][C]-0.004003[/C][C]-0.0439[/C][C]0.482548[/C][/ROW]
[ROW][C]34[/C][C]0.029266[/C][C]0.3206[/C][C]0.374539[/C][/ROW]
[ROW][C]35[/C][C]-0.001534[/C][C]-0.0168[/C][C]0.493311[/C][/ROW]
[ROW][C]36[/C][C]-0.018685[/C][C]-0.2047[/C][C]0.419081[/C][/ROW]
[ROW][C]37[/C][C]-0.044102[/C][C]-0.4831[/C][C]0.314949[/C][/ROW]
[ROW][C]38[/C][C]-0.058006[/C][C]-0.6354[/C][C]0.263179[/C][/ROW]
[ROW][C]39[/C][C]-0.019713[/C][C]-0.2159[/C][C]0.414698[/C][/ROW]
[ROW][C]40[/C][C]-0.02455[/C][C]-0.2689[/C][C]0.394222[/C][/ROW]
[ROW][C]41[/C][C]0.000197[/C][C]0.0022[/C][C]0.499142[/C][/ROW]
[ROW][C]42[/C][C]0.012768[/C][C]0.1399[/C][C]0.444499[/C][/ROW]
[ROW][C]43[/C][C]0.03488[/C][C]0.3821[/C][C]0.351533[/C][/ROW]
[ROW][C]44[/C][C]-0.028257[/C][C]-0.3095[/C][C]0.378723[/C][/ROW]
[ROW][C]45[/C][C]0.01738[/C][C]0.1904[/C][C]0.424664[/C][/ROW]
[ROW][C]46[/C][C]0.018593[/C][C]0.2037[/C][C]0.419475[/C][/ROW]
[ROW][C]47[/C][C]-0.0166[/C][C]-0.1818[/C][C]0.428006[/C][/ROW]
[ROW][C]48[/C][C]0.006562[/C][C]0.0719[/C][C]0.471408[/C][/ROW]
[ROW][C]49[/C][C]-0.045659[/C][C]-0.5002[/C][C]0.308935[/C][/ROW]
[ROW][C]50[/C][C]-0.049879[/C][C]-0.5464[/C][C]0.292902[/C][/ROW]
[ROW][C]51[/C][C]-0.011687[/C][C]-0.128[/C][C]0.449174[/C][/ROW]
[ROW][C]52[/C][C]-0.036323[/C][C]-0.3979[/C][C]0.345706[/C][/ROW]
[ROW][C]53[/C][C]-0.004342[/C][C]-0.0476[/C][C]0.481073[/C][/ROW]
[ROW][C]54[/C][C]-0.008729[/C][C]-0.0956[/C][C]0.461992[/C][/ROW]
[ROW][C]55[/C][C]-0.004214[/C][C]-0.0462[/C][C]0.481627[/C][/ROW]
[ROW][C]56[/C][C]-0.03985[/C][C]-0.4365[/C][C]0.331618[/C][/ROW]
[ROW][C]57[/C][C]0.014162[/C][C]0.1551[/C][C]0.438485[/C][/ROW]
[ROW][C]58[/C][C]0.020372[/C][C]0.2232[/C][C]0.411894[/C][/ROW]
[ROW][C]59[/C][C]-0.010069[/C][C]-0.1103[/C][C]0.456176[/C][/ROW]
[ROW][C]60[/C][C]-0.015475[/C][C]-0.1695[/C][C]0.432838[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=211034&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=211034&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
10.97090510.63570
2-0.114681-1.25630.105729
30.0041010.04490.482122
40.0746550.81780.207546
5-0.008505-0.09320.462965
60.0310570.34020.367147
70.0773770.84760.199168
80.0034040.03730.485158
9-0.023327-0.25550.399375
10-0.001094-0.0120.495229
11-0.006365-0.06970.472265
12-0.051296-0.56190.287609
13-0.152897-1.67490.048278
14-0.078823-0.86350.194802
15-0.017262-0.18910.425168
160.0282240.30920.37886
17-0.006932-0.07590.469797
180.0090180.09880.460734
190.0860710.94290.173824
200.0055790.06110.475687
210.0006470.00710.49718
220.0227970.24970.401612
230.0100190.10980.456393
24-0.037829-0.41440.339663
25-0.102882-1.1270.130993
26-0.069699-0.76350.223328
27-0.000416-0.00460.498186
28-0.007965-0.08730.465308
29-0.017754-0.19450.423061
30-0.013452-0.14740.441546
310.0433670.47510.317803
32-0.023565-0.25810.39837
33-0.004003-0.04390.482548
340.0292660.32060.374539
35-0.001534-0.01680.493311
36-0.018685-0.20470.419081
37-0.044102-0.48310.314949
38-0.058006-0.63540.263179
39-0.019713-0.21590.414698
40-0.02455-0.26890.394222
410.0001970.00220.499142
420.0127680.13990.444499
430.034880.38210.351533
44-0.028257-0.30950.378723
450.017380.19040.424664
460.0185930.20370.419475
47-0.0166-0.18180.428006
480.0065620.07190.471408
49-0.045659-0.50020.308935
50-0.049879-0.54640.292902
51-0.011687-0.1280.449174
52-0.036323-0.39790.345706
53-0.004342-0.04760.481073
54-0.008729-0.09560.461992
55-0.004214-0.04620.481627
56-0.03985-0.43650.331618
570.0141620.15510.438485
580.0203720.22320.411894
59-0.010069-0.11030.456176
60-0.015475-0.16950.432838



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 1 ; 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):
par8 <- ''
par7 <- '0.95'
par6 <- 'White Noise'
par5 <- '12'
par4 <- '0'
par3 <- '1'
par2 <- '1'
par1 <- '60'
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')