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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_autocorrelation.wasp
Title produced by software(Partial) Autocorrelation Function
Date of computationTue, 12 Jan 2010 05:08:28 -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/2010/Jan/12/t1263298172ky1xr8i9t1ec05f.htm/, Retrieved Fri, 01 Nov 2024 00:18:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=71995, Retrieved Fri, 01 Nov 2024 00:18:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2009-12-17 19:09:08] [b98453cac15ba1066b407e146608df68]
- RMP   [(Partial) Autocorrelation Function] [] [2009-12-17 19:26:45] [b98453cac15ba1066b407e146608df68]
-   P       [(Partial) Autocorrelation Function] [ACF bij d=0 en D=0] [2010-01-12 12:08:28] [a25640248f5f3c4d92f02a597edd3aef] [Current]
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Dataseries X:
277
260.6
291.6
275.4
275.3
231.7
238.8
274.2
277.8
299.1
286.6
232.3
294.1
267.5
309.7
280.7
287.3
235.7
256.4
289
290.8
321.9
291.8
241.4
295.5
258.2
306.1
281.5
283.1
237.4
274.8
299.3
300.4
340.9
318.8
265.7
322.7
281.6
323.5
312.6
310.8
262.8
273.8
320
310.3
342.2
320.1
265.6
327
300.7
346.4
317.3
326.2
270.7
278.2
324.6
321.8
343.5
354
278.2
330.2
307.3
375.9
335.3
339.3
280.3
293.7
341.2
345.1
368.7
369.4
288.4
341
319.1
374.2
344.5
337.3
281
282.2
321
325.4
366.3
380.3
300.7
359.3
327.6
383.6
352.4
329.4
294.5
333.5
334.3
358
396.1
387
307.2
363.9
344.7
397.6
376.8
337.1
299.3
323.1
329.1
347
462
436.5
360.4
415.5
382.1
432.2
424.3
386.7
354.5
375.8
368
402.4
426.5
433.3
338.5
416.8
381.1
445.7
412.4
394
348.2
380.1
373.7
393.6
434.2
430.7
344.5
411.9
370.5
437.3
411.3
385.5
341.3
384.2
373.2
415.8
448.6
454.3
350.3
419.1
398
456.1
430.1
399.8
362.7
384.9
385.3
432.3
468.9
442.7
370.2
439.4
393.9
468.7
438.8
430.1
366.3
391
380.9
431.4
465.4
471.5
387.5
446.4
421.5
504.8
492.1
421.3
396.7
428
421.9
465.6
525.8
499.9
435.3
479.5
473
554.4
489.6
462.2
420.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71995&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71995&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71995&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Autocorrelation Function
Time lag kACF(k)T-STATP-value
10.79082410.78540
20.73474710.02060
30.6308028.6030
40.6603649.00620
50.708939.66850
60.77040710.50690
70.6677779.10730
80.5883328.02380
90.5170547.05170
100.5892958.03690
110.6215298.47650
120.78123210.65460
130.5995948.17740
140.5554377.57520
150.460656.28240
160.4872496.64520
170.5398327.36230
180.5947388.11120
190.5038046.8710
200.4364675.95260
210.3722365.07660
220.4463576.08750
230.4742726.46820
240.6273138.55540
250.4609556.28660
260.4203345.73260
270.3286874.48276e-06
280.3521794.80312e-06
290.4071975.55340
300.453226.18110
310.3751345.11610
320.3145074.28931.4e-05
330.2455353.34860.000491
340.311914.25391.7e-05
350.3432124.68083e-06
360.4818086.5710
370.3352834.57264e-06
380.2989324.07693.4e-05
390.2161442.94780.001805
400.237253.23570.000718
410.2879923.92776e-05
420.3307294.51056e-06
430.2557363.48780.000304
440.2024862.76150.003165
450.1352921.84510.033304
460.197852.69830.003805
470.2265213.08930.001157
480.3499034.7722e-06
490.2179622.97260.001672
500.1897722.58820.005206
510.1132441.54440.06209
520.1263341.7230.043279
530.1821882.48470.006924
540.218692.98250.001621
550.150342.05040.020866
560.1024011.39660.082104
570.0400490.54620.292794
580.0954281.30150.097354
590.1262251.72150.043413
600.2368113.22970.000733

\begin{tabular}{lllllllll}
\hline
Autocorrelation Function \tabularnewline
Time lag k & ACF(k) & T-STAT & P-value \tabularnewline
1 & 0.790824 & 10.7854 & 0 \tabularnewline
2 & 0.734747 & 10.0206 & 0 \tabularnewline
3 & 0.630802 & 8.603 & 0 \tabularnewline
4 & 0.660364 & 9.0062 & 0 \tabularnewline
5 & 0.70893 & 9.6685 & 0 \tabularnewline
6 & 0.770407 & 10.5069 & 0 \tabularnewline
7 & 0.667777 & 9.1073 & 0 \tabularnewline
8 & 0.588332 & 8.0238 & 0 \tabularnewline
9 & 0.517054 & 7.0517 & 0 \tabularnewline
10 & 0.589295 & 8.0369 & 0 \tabularnewline
11 & 0.621529 & 8.4765 & 0 \tabularnewline
12 & 0.781232 & 10.6546 & 0 \tabularnewline
13 & 0.599594 & 8.1774 & 0 \tabularnewline
14 & 0.555437 & 7.5752 & 0 \tabularnewline
15 & 0.46065 & 6.2824 & 0 \tabularnewline
16 & 0.487249 & 6.6452 & 0 \tabularnewline
17 & 0.539832 & 7.3623 & 0 \tabularnewline
18 & 0.594738 & 8.1112 & 0 \tabularnewline
19 & 0.503804 & 6.871 & 0 \tabularnewline
20 & 0.436467 & 5.9526 & 0 \tabularnewline
21 & 0.372236 & 5.0766 & 0 \tabularnewline
22 & 0.446357 & 6.0875 & 0 \tabularnewline
23 & 0.474272 & 6.4682 & 0 \tabularnewline
24 & 0.627313 & 8.5554 & 0 \tabularnewline
25 & 0.460955 & 6.2866 & 0 \tabularnewline
26 & 0.420334 & 5.7326 & 0 \tabularnewline
27 & 0.328687 & 4.4827 & 6e-06 \tabularnewline
28 & 0.352179 & 4.8031 & 2e-06 \tabularnewline
29 & 0.407197 & 5.5534 & 0 \tabularnewline
30 & 0.45322 & 6.1811 & 0 \tabularnewline
31 & 0.375134 & 5.1161 & 0 \tabularnewline
32 & 0.314507 & 4.2893 & 1.4e-05 \tabularnewline
33 & 0.245535 & 3.3486 & 0.000491 \tabularnewline
34 & 0.31191 & 4.2539 & 1.7e-05 \tabularnewline
35 & 0.343212 & 4.6808 & 3e-06 \tabularnewline
36 & 0.481808 & 6.571 & 0 \tabularnewline
37 & 0.335283 & 4.5726 & 4e-06 \tabularnewline
38 & 0.298932 & 4.0769 & 3.4e-05 \tabularnewline
39 & 0.216144 & 2.9478 & 0.001805 \tabularnewline
40 & 0.23725 & 3.2357 & 0.000718 \tabularnewline
41 & 0.287992 & 3.9277 & 6e-05 \tabularnewline
42 & 0.330729 & 4.5105 & 6e-06 \tabularnewline
43 & 0.255736 & 3.4878 & 0.000304 \tabularnewline
44 & 0.202486 & 2.7615 & 0.003165 \tabularnewline
45 & 0.135292 & 1.8451 & 0.033304 \tabularnewline
46 & 0.19785 & 2.6983 & 0.003805 \tabularnewline
47 & 0.226521 & 3.0893 & 0.001157 \tabularnewline
48 & 0.349903 & 4.772 & 2e-06 \tabularnewline
49 & 0.217962 & 2.9726 & 0.001672 \tabularnewline
50 & 0.189772 & 2.5882 & 0.005206 \tabularnewline
51 & 0.113244 & 1.5444 & 0.06209 \tabularnewline
52 & 0.126334 & 1.723 & 0.043279 \tabularnewline
53 & 0.182188 & 2.4847 & 0.006924 \tabularnewline
54 & 0.21869 & 2.9825 & 0.001621 \tabularnewline
55 & 0.15034 & 2.0504 & 0.020866 \tabularnewline
56 & 0.102401 & 1.3966 & 0.082104 \tabularnewline
57 & 0.040049 & 0.5462 & 0.292794 \tabularnewline
58 & 0.095428 & 1.3015 & 0.097354 \tabularnewline
59 & 0.126225 & 1.7215 & 0.043413 \tabularnewline
60 & 0.236811 & 3.2297 & 0.000733 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71995&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]0.790824[/C][C]10.7854[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.734747[/C][C]10.0206[/C][C]0[/C][/ROW]
[ROW][C]3[/C][C]0.630802[/C][C]8.603[/C][C]0[/C][/ROW]
[ROW][C]4[/C][C]0.660364[/C][C]9.0062[/C][C]0[/C][/ROW]
[ROW][C]5[/C][C]0.70893[/C][C]9.6685[/C][C]0[/C][/ROW]
[ROW][C]6[/C][C]0.770407[/C][C]10.5069[/C][C]0[/C][/ROW]
[ROW][C]7[/C][C]0.667777[/C][C]9.1073[/C][C]0[/C][/ROW]
[ROW][C]8[/C][C]0.588332[/C][C]8.0238[/C][C]0[/C][/ROW]
[ROW][C]9[/C][C]0.517054[/C][C]7.0517[/C][C]0[/C][/ROW]
[ROW][C]10[/C][C]0.589295[/C][C]8.0369[/C][C]0[/C][/ROW]
[ROW][C]11[/C][C]0.621529[/C][C]8.4765[/C][C]0[/C][/ROW]
[ROW][C]12[/C][C]0.781232[/C][C]10.6546[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]0.599594[/C][C]8.1774[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]0.555437[/C][C]7.5752[/C][C]0[/C][/ROW]
[ROW][C]15[/C][C]0.46065[/C][C]6.2824[/C][C]0[/C][/ROW]
[ROW][C]16[/C][C]0.487249[/C][C]6.6452[/C][C]0[/C][/ROW]
[ROW][C]17[/C][C]0.539832[/C][C]7.3623[/C][C]0[/C][/ROW]
[ROW][C]18[/C][C]0.594738[/C][C]8.1112[/C][C]0[/C][/ROW]
[ROW][C]19[/C][C]0.503804[/C][C]6.871[/C][C]0[/C][/ROW]
[ROW][C]20[/C][C]0.436467[/C][C]5.9526[/C][C]0[/C][/ROW]
[ROW][C]21[/C][C]0.372236[/C][C]5.0766[/C][C]0[/C][/ROW]
[ROW][C]22[/C][C]0.446357[/C][C]6.0875[/C][C]0[/C][/ROW]
[ROW][C]23[/C][C]0.474272[/C][C]6.4682[/C][C]0[/C][/ROW]
[ROW][C]24[/C][C]0.627313[/C][C]8.5554[/C][C]0[/C][/ROW]
[ROW][C]25[/C][C]0.460955[/C][C]6.2866[/C][C]0[/C][/ROW]
[ROW][C]26[/C][C]0.420334[/C][C]5.7326[/C][C]0[/C][/ROW]
[ROW][C]27[/C][C]0.328687[/C][C]4.4827[/C][C]6e-06[/C][/ROW]
[ROW][C]28[/C][C]0.352179[/C][C]4.8031[/C][C]2e-06[/C][/ROW]
[ROW][C]29[/C][C]0.407197[/C][C]5.5534[/C][C]0[/C][/ROW]
[ROW][C]30[/C][C]0.45322[/C][C]6.1811[/C][C]0[/C][/ROW]
[ROW][C]31[/C][C]0.375134[/C][C]5.1161[/C][C]0[/C][/ROW]
[ROW][C]32[/C][C]0.314507[/C][C]4.2893[/C][C]1.4e-05[/C][/ROW]
[ROW][C]33[/C][C]0.245535[/C][C]3.3486[/C][C]0.000491[/C][/ROW]
[ROW][C]34[/C][C]0.31191[/C][C]4.2539[/C][C]1.7e-05[/C][/ROW]
[ROW][C]35[/C][C]0.343212[/C][C]4.6808[/C][C]3e-06[/C][/ROW]
[ROW][C]36[/C][C]0.481808[/C][C]6.571[/C][C]0[/C][/ROW]
[ROW][C]37[/C][C]0.335283[/C][C]4.5726[/C][C]4e-06[/C][/ROW]
[ROW][C]38[/C][C]0.298932[/C][C]4.0769[/C][C]3.4e-05[/C][/ROW]
[ROW][C]39[/C][C]0.216144[/C][C]2.9478[/C][C]0.001805[/C][/ROW]
[ROW][C]40[/C][C]0.23725[/C][C]3.2357[/C][C]0.000718[/C][/ROW]
[ROW][C]41[/C][C]0.287992[/C][C]3.9277[/C][C]6e-05[/C][/ROW]
[ROW][C]42[/C][C]0.330729[/C][C]4.5105[/C][C]6e-06[/C][/ROW]
[ROW][C]43[/C][C]0.255736[/C][C]3.4878[/C][C]0.000304[/C][/ROW]
[ROW][C]44[/C][C]0.202486[/C][C]2.7615[/C][C]0.003165[/C][/ROW]
[ROW][C]45[/C][C]0.135292[/C][C]1.8451[/C][C]0.033304[/C][/ROW]
[ROW][C]46[/C][C]0.19785[/C][C]2.6983[/C][C]0.003805[/C][/ROW]
[ROW][C]47[/C][C]0.226521[/C][C]3.0893[/C][C]0.001157[/C][/ROW]
[ROW][C]48[/C][C]0.349903[/C][C]4.772[/C][C]2e-06[/C][/ROW]
[ROW][C]49[/C][C]0.217962[/C][C]2.9726[/C][C]0.001672[/C][/ROW]
[ROW][C]50[/C][C]0.189772[/C][C]2.5882[/C][C]0.005206[/C][/ROW]
[ROW][C]51[/C][C]0.113244[/C][C]1.5444[/C][C]0.06209[/C][/ROW]
[ROW][C]52[/C][C]0.126334[/C][C]1.723[/C][C]0.043279[/C][/ROW]
[ROW][C]53[/C][C]0.182188[/C][C]2.4847[/C][C]0.006924[/C][/ROW]
[ROW][C]54[/C][C]0.21869[/C][C]2.9825[/C][C]0.001621[/C][/ROW]
[ROW][C]55[/C][C]0.15034[/C][C]2.0504[/C][C]0.020866[/C][/ROW]
[ROW][C]56[/C][C]0.102401[/C][C]1.3966[/C][C]0.082104[/C][/ROW]
[ROW][C]57[/C][C]0.040049[/C][C]0.5462[/C][C]0.292794[/C][/ROW]
[ROW][C]58[/C][C]0.095428[/C][C]1.3015[/C][C]0.097354[/C][/ROW]
[ROW][C]59[/C][C]0.126225[/C][C]1.7215[/C][C]0.043413[/C][/ROW]
[ROW][C]60[/C][C]0.236811[/C][C]3.2297[/C][C]0.000733[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71995&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71995&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
10.79082410.78540
20.73474710.02060
30.6308028.6030
40.6603649.00620
50.708939.66850
60.77040710.50690
70.6677779.10730
80.5883328.02380
90.5170547.05170
100.5892958.03690
110.6215298.47650
120.78123210.65460
130.5995948.17740
140.5554377.57520
150.460656.28240
160.4872496.64520
170.5398327.36230
180.5947388.11120
190.5038046.8710
200.4364675.95260
210.3722365.07660
220.4463576.08750
230.4742726.46820
240.6273138.55540
250.4609556.28660
260.4203345.73260
270.3286874.48276e-06
280.3521794.80312e-06
290.4071975.55340
300.453226.18110
310.3751345.11610
320.3145074.28931.4e-05
330.2455353.34860.000491
340.311914.25391.7e-05
350.3432124.68083e-06
360.4818086.5710
370.3352834.57264e-06
380.2989324.07693.4e-05
390.2161442.94780.001805
400.237253.23570.000718
410.2879923.92776e-05
420.3307294.51056e-06
430.2557363.48780.000304
440.2024862.76150.003165
450.1352921.84510.033304
460.197852.69830.003805
470.2265213.08930.001157
480.3499034.7722e-06
490.2179622.97260.001672
500.1897722.58820.005206
510.1132441.54440.06209
520.1263341.7230.043279
530.1821882.48470.006924
540.218692.98250.001621
550.150342.05040.020866
560.1024011.39660.082104
570.0400490.54620.292794
580.0954281.30150.097354
590.1262251.72150.043413
600.2368113.22970.000733







Partial Autocorrelation Function
Time lag kPACF(k)T-STATP-value
10.79082410.78540
20.2918993.9814.9e-05
3-0.033516-0.45710.324067
40.2898023.95245.5e-05
50.331214.51716e-06
60.2724493.71570.000134
7-0.245094-3.34260.000502
8-0.182078-2.48320.006953
90.0048950.06680.473425
100.293664.0054.5e-05
110.0249250.33990.367147
120.4996986.8150
13-0.548126-7.47540
14-0.084651-1.15450.12489
15-0.005796-0.07910.468539
16-0.040258-0.5490.291816
170.0146930.20040.420701
18-0.002759-0.03760.485012
190.0980041.33660.091494
200.0339320.46280.322036
210.0863721.1780.120158
220.0456670.62280.267083
23-0.06068-0.82760.20449
240.1506672.05480.020647
25-0.219883-2.99880.001541
26-0.119558-1.63060.052339
27-0.05466-0.74550.228465
280.0136980.18680.426002
290.056680.7730.220249
30-0.031038-0.42330.336284
310.1521372.07490.019687
320.0270610.36910.356252
33-0.028913-0.39430.346896
34-0.06094-0.83110.203488
350.0254560.34720.364426
36-0.029974-0.40880.34158
37-0.069795-0.95190.171197
38-0.034814-0.47480.317742
390.0296250.4040.343328
400.0433360.5910.27761
41-0.051903-0.70790.239958
420.0379890.51810.302504
43-0.036677-0.50020.308759
440.0487920.66540.253299
450.0022530.03070.487762
46-0.065798-0.89740.185341
470.0102440.13970.444522
48-0.042695-0.58230.280539
490.0102210.13940.444646
500.0104480.14250.44342
510.0042380.05780.476983
52-0.051428-0.70140.241969
530.0448520.61170.270743
540.0149260.20360.419457
55-0.036777-0.50160.308281
56-0.023131-0.31550.376382
570.034870.47560.317471
58-0.013919-0.18980.424826
59-0.001684-0.0230.490851
60-0.022367-0.3050.380337

\begin{tabular}{lllllllll}
\hline
Partial Autocorrelation Function \tabularnewline
Time lag k & PACF(k) & T-STAT & P-value \tabularnewline
1 & 0.790824 & 10.7854 & 0 \tabularnewline
2 & 0.291899 & 3.981 & 4.9e-05 \tabularnewline
3 & -0.033516 & -0.4571 & 0.324067 \tabularnewline
4 & 0.289802 & 3.9524 & 5.5e-05 \tabularnewline
5 & 0.33121 & 4.5171 & 6e-06 \tabularnewline
6 & 0.272449 & 3.7157 & 0.000134 \tabularnewline
7 & -0.245094 & -3.3426 & 0.000502 \tabularnewline
8 & -0.182078 & -2.4832 & 0.006953 \tabularnewline
9 & 0.004895 & 0.0668 & 0.473425 \tabularnewline
10 & 0.29366 & 4.005 & 4.5e-05 \tabularnewline
11 & 0.024925 & 0.3399 & 0.367147 \tabularnewline
12 & 0.499698 & 6.815 & 0 \tabularnewline
13 & -0.548126 & -7.4754 & 0 \tabularnewline
14 & -0.084651 & -1.1545 & 0.12489 \tabularnewline
15 & -0.005796 & -0.0791 & 0.468539 \tabularnewline
16 & -0.040258 & -0.549 & 0.291816 \tabularnewline
17 & 0.014693 & 0.2004 & 0.420701 \tabularnewline
18 & -0.002759 & -0.0376 & 0.485012 \tabularnewline
19 & 0.098004 & 1.3366 & 0.091494 \tabularnewline
20 & 0.033932 & 0.4628 & 0.322036 \tabularnewline
21 & 0.086372 & 1.178 & 0.120158 \tabularnewline
22 & 0.045667 & 0.6228 & 0.267083 \tabularnewline
23 & -0.06068 & -0.8276 & 0.20449 \tabularnewline
24 & 0.150667 & 2.0548 & 0.020647 \tabularnewline
25 & -0.219883 & -2.9988 & 0.001541 \tabularnewline
26 & -0.119558 & -1.6306 & 0.052339 \tabularnewline
27 & -0.05466 & -0.7455 & 0.228465 \tabularnewline
28 & 0.013698 & 0.1868 & 0.426002 \tabularnewline
29 & 0.05668 & 0.773 & 0.220249 \tabularnewline
30 & -0.031038 & -0.4233 & 0.336284 \tabularnewline
31 & 0.152137 & 2.0749 & 0.019687 \tabularnewline
32 & 0.027061 & 0.3691 & 0.356252 \tabularnewline
33 & -0.028913 & -0.3943 & 0.346896 \tabularnewline
34 & -0.06094 & -0.8311 & 0.203488 \tabularnewline
35 & 0.025456 & 0.3472 & 0.364426 \tabularnewline
36 & -0.029974 & -0.4088 & 0.34158 \tabularnewline
37 & -0.069795 & -0.9519 & 0.171197 \tabularnewline
38 & -0.034814 & -0.4748 & 0.317742 \tabularnewline
39 & 0.029625 & 0.404 & 0.343328 \tabularnewline
40 & 0.043336 & 0.591 & 0.27761 \tabularnewline
41 & -0.051903 & -0.7079 & 0.239958 \tabularnewline
42 & 0.037989 & 0.5181 & 0.302504 \tabularnewline
43 & -0.036677 & -0.5002 & 0.308759 \tabularnewline
44 & 0.048792 & 0.6654 & 0.253299 \tabularnewline
45 & 0.002253 & 0.0307 & 0.487762 \tabularnewline
46 & -0.065798 & -0.8974 & 0.185341 \tabularnewline
47 & 0.010244 & 0.1397 & 0.444522 \tabularnewline
48 & -0.042695 & -0.5823 & 0.280539 \tabularnewline
49 & 0.010221 & 0.1394 & 0.444646 \tabularnewline
50 & 0.010448 & 0.1425 & 0.44342 \tabularnewline
51 & 0.004238 & 0.0578 & 0.476983 \tabularnewline
52 & -0.051428 & -0.7014 & 0.241969 \tabularnewline
53 & 0.044852 & 0.6117 & 0.270743 \tabularnewline
54 & 0.014926 & 0.2036 & 0.419457 \tabularnewline
55 & -0.036777 & -0.5016 & 0.308281 \tabularnewline
56 & -0.023131 & -0.3155 & 0.376382 \tabularnewline
57 & 0.03487 & 0.4756 & 0.317471 \tabularnewline
58 & -0.013919 & -0.1898 & 0.424826 \tabularnewline
59 & -0.001684 & -0.023 & 0.490851 \tabularnewline
60 & -0.022367 & -0.305 & 0.380337 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=71995&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]0.790824[/C][C]10.7854[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]0.291899[/C][C]3.981[/C][C]4.9e-05[/C][/ROW]
[ROW][C]3[/C][C]-0.033516[/C][C]-0.4571[/C][C]0.324067[/C][/ROW]
[ROW][C]4[/C][C]0.289802[/C][C]3.9524[/C][C]5.5e-05[/C][/ROW]
[ROW][C]5[/C][C]0.33121[/C][C]4.5171[/C][C]6e-06[/C][/ROW]
[ROW][C]6[/C][C]0.272449[/C][C]3.7157[/C][C]0.000134[/C][/ROW]
[ROW][C]7[/C][C]-0.245094[/C][C]-3.3426[/C][C]0.000502[/C][/ROW]
[ROW][C]8[/C][C]-0.182078[/C][C]-2.4832[/C][C]0.006953[/C][/ROW]
[ROW][C]9[/C][C]0.004895[/C][C]0.0668[/C][C]0.473425[/C][/ROW]
[ROW][C]10[/C][C]0.29366[/C][C]4.005[/C][C]4.5e-05[/C][/ROW]
[ROW][C]11[/C][C]0.024925[/C][C]0.3399[/C][C]0.367147[/C][/ROW]
[ROW][C]12[/C][C]0.499698[/C][C]6.815[/C][C]0[/C][/ROW]
[ROW][C]13[/C][C]-0.548126[/C][C]-7.4754[/C][C]0[/C][/ROW]
[ROW][C]14[/C][C]-0.084651[/C][C]-1.1545[/C][C]0.12489[/C][/ROW]
[ROW][C]15[/C][C]-0.005796[/C][C]-0.0791[/C][C]0.468539[/C][/ROW]
[ROW][C]16[/C][C]-0.040258[/C][C]-0.549[/C][C]0.291816[/C][/ROW]
[ROW][C]17[/C][C]0.014693[/C][C]0.2004[/C][C]0.420701[/C][/ROW]
[ROW][C]18[/C][C]-0.002759[/C][C]-0.0376[/C][C]0.485012[/C][/ROW]
[ROW][C]19[/C][C]0.098004[/C][C]1.3366[/C][C]0.091494[/C][/ROW]
[ROW][C]20[/C][C]0.033932[/C][C]0.4628[/C][C]0.322036[/C][/ROW]
[ROW][C]21[/C][C]0.086372[/C][C]1.178[/C][C]0.120158[/C][/ROW]
[ROW][C]22[/C][C]0.045667[/C][C]0.6228[/C][C]0.267083[/C][/ROW]
[ROW][C]23[/C][C]-0.06068[/C][C]-0.8276[/C][C]0.20449[/C][/ROW]
[ROW][C]24[/C][C]0.150667[/C][C]2.0548[/C][C]0.020647[/C][/ROW]
[ROW][C]25[/C][C]-0.219883[/C][C]-2.9988[/C][C]0.001541[/C][/ROW]
[ROW][C]26[/C][C]-0.119558[/C][C]-1.6306[/C][C]0.052339[/C][/ROW]
[ROW][C]27[/C][C]-0.05466[/C][C]-0.7455[/C][C]0.228465[/C][/ROW]
[ROW][C]28[/C][C]0.013698[/C][C]0.1868[/C][C]0.426002[/C][/ROW]
[ROW][C]29[/C][C]0.05668[/C][C]0.773[/C][C]0.220249[/C][/ROW]
[ROW][C]30[/C][C]-0.031038[/C][C]-0.4233[/C][C]0.336284[/C][/ROW]
[ROW][C]31[/C][C]0.152137[/C][C]2.0749[/C][C]0.019687[/C][/ROW]
[ROW][C]32[/C][C]0.027061[/C][C]0.3691[/C][C]0.356252[/C][/ROW]
[ROW][C]33[/C][C]-0.028913[/C][C]-0.3943[/C][C]0.346896[/C][/ROW]
[ROW][C]34[/C][C]-0.06094[/C][C]-0.8311[/C][C]0.203488[/C][/ROW]
[ROW][C]35[/C][C]0.025456[/C][C]0.3472[/C][C]0.364426[/C][/ROW]
[ROW][C]36[/C][C]-0.029974[/C][C]-0.4088[/C][C]0.34158[/C][/ROW]
[ROW][C]37[/C][C]-0.069795[/C][C]-0.9519[/C][C]0.171197[/C][/ROW]
[ROW][C]38[/C][C]-0.034814[/C][C]-0.4748[/C][C]0.317742[/C][/ROW]
[ROW][C]39[/C][C]0.029625[/C][C]0.404[/C][C]0.343328[/C][/ROW]
[ROW][C]40[/C][C]0.043336[/C][C]0.591[/C][C]0.27761[/C][/ROW]
[ROW][C]41[/C][C]-0.051903[/C][C]-0.7079[/C][C]0.239958[/C][/ROW]
[ROW][C]42[/C][C]0.037989[/C][C]0.5181[/C][C]0.302504[/C][/ROW]
[ROW][C]43[/C][C]-0.036677[/C][C]-0.5002[/C][C]0.308759[/C][/ROW]
[ROW][C]44[/C][C]0.048792[/C][C]0.6654[/C][C]0.253299[/C][/ROW]
[ROW][C]45[/C][C]0.002253[/C][C]0.0307[/C][C]0.487762[/C][/ROW]
[ROW][C]46[/C][C]-0.065798[/C][C]-0.8974[/C][C]0.185341[/C][/ROW]
[ROW][C]47[/C][C]0.010244[/C][C]0.1397[/C][C]0.444522[/C][/ROW]
[ROW][C]48[/C][C]-0.042695[/C][C]-0.5823[/C][C]0.280539[/C][/ROW]
[ROW][C]49[/C][C]0.010221[/C][C]0.1394[/C][C]0.444646[/C][/ROW]
[ROW][C]50[/C][C]0.010448[/C][C]0.1425[/C][C]0.44342[/C][/ROW]
[ROW][C]51[/C][C]0.004238[/C][C]0.0578[/C][C]0.476983[/C][/ROW]
[ROW][C]52[/C][C]-0.051428[/C][C]-0.7014[/C][C]0.241969[/C][/ROW]
[ROW][C]53[/C][C]0.044852[/C][C]0.6117[/C][C]0.270743[/C][/ROW]
[ROW][C]54[/C][C]0.014926[/C][C]0.2036[/C][C]0.419457[/C][/ROW]
[ROW][C]55[/C][C]-0.036777[/C][C]-0.5016[/C][C]0.308281[/C][/ROW]
[ROW][C]56[/C][C]-0.023131[/C][C]-0.3155[/C][C]0.376382[/C][/ROW]
[ROW][C]57[/C][C]0.03487[/C][C]0.4756[/C][C]0.317471[/C][/ROW]
[ROW][C]58[/C][C]-0.013919[/C][C]-0.1898[/C][C]0.424826[/C][/ROW]
[ROW][C]59[/C][C]-0.001684[/C][C]-0.023[/C][C]0.490851[/C][/ROW]
[ROW][C]60[/C][C]-0.022367[/C][C]-0.305[/C][C]0.380337[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=71995&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=71995&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
10.79082410.78540
20.2918993.9814.9e-05
3-0.033516-0.45710.324067
40.2898023.95245.5e-05
50.331214.51716e-06
60.2724493.71570.000134
7-0.245094-3.34260.000502
8-0.182078-2.48320.006953
90.0048950.06680.473425
100.293664.0054.5e-05
110.0249250.33990.367147
120.4996986.8150
13-0.548126-7.47540
14-0.084651-1.15450.12489
15-0.005796-0.07910.468539
16-0.040258-0.5490.291816
170.0146930.20040.420701
18-0.002759-0.03760.485012
190.0980041.33660.091494
200.0339320.46280.322036
210.0863721.1780.120158
220.0456670.62280.267083
23-0.06068-0.82760.20449
240.1506672.05480.020647
25-0.219883-2.99880.001541
26-0.119558-1.63060.052339
27-0.05466-0.74550.228465
280.0136980.18680.426002
290.056680.7730.220249
30-0.031038-0.42330.336284
310.1521372.07490.019687
320.0270610.36910.356252
33-0.028913-0.39430.346896
34-0.06094-0.83110.203488
350.0254560.34720.364426
36-0.029974-0.40880.34158
37-0.069795-0.95190.171197
38-0.034814-0.47480.317742
390.0296250.4040.343328
400.0433360.5910.27761
41-0.051903-0.70790.239958
420.0379890.51810.302504
43-0.036677-0.50020.308759
440.0487920.66540.253299
450.0022530.03070.487762
46-0.065798-0.89740.185341
470.0102440.13970.444522
48-0.042695-0.58230.280539
490.0102210.13940.444646
500.0104480.14250.44342
510.0042380.05780.476983
52-0.051428-0.70140.241969
530.0448520.61170.270743
540.0149260.20360.419457
55-0.036777-0.50160.308281
56-0.023131-0.31550.376382
570.034870.47560.317471
58-0.013919-0.18980.424826
59-0.001684-0.0230.490851
60-0.022367-0.3050.380337



Parameters (Session):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
Parameters (R input):
par1 = 60 ; par2 = 1 ; par3 = 0 ; par4 = 0 ; par5 = 12 ; par6 = MA ; par7 = 0.95 ;
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 (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='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
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')