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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationSat, 06 Dec 2008 11:27:45 -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/06/t1228588174zvytefur6dpn1dw.htm/, Retrieved Sat, 18 May 2024 05:11:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29797, Retrieved Sat, 18 May 2024 05:11:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact201

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
F RMP     [Spectral Analysis] [Spectraal analyse...] [2008-12-06 18:27:45] [09074fbe368d26382bb94e5bb318a104] [Current]
F RMP       [(Partial) Autocorrelation Function] [] [2008-12-07 18:09:45] [a4602103a5e123497aa555277d0e627b]
- RMP       [ARIMA Backward Selection] [ARMA] [2008-12-07 18:25:33] [a4602103a5e123497aa555277d0e627b]
- RMPD      [(Partial) Autocorrelation Function] [ACF omzet] [2008-12-07 18:33:42] [a4602103a5e123497aa555277d0e627b]
Feedback Forum
2008-12-13 12:59:42 [Li Tang Hu] [reply] 
na de differentiatie toe te passen, komen we uit op hetzelfde resultaat als de andere 2 methodes, de cumulatieve komt inderdaad nog een deel uit betrouwbaarheidsonterval. het vertoont bovendien een convex verloop, we kunnen nu al vermoeden dt er ARprocessen aanwezig zullen zijn
2008-12-14 14:03:00 [Angelique Van de Vijver] [reply] 
De student heeft in zijn berekening na differentiatie lambda gelijkgesteld aan 1. In voorgaande standarddeviation-mean plot hebben we afgeleid dat deze moest gelijkgesteld worden aan 0,5.
De student heeft goed het verloop laten zien van de verschillende differentiaties en goede conclusies gemaakt. De afwijking bevindt zich inderdaad aan de bovenkant. Dit wijst er inderdaad op dat we hier waarschijnlijk te maken hebben met een AR proces.
Op het raw periodogram voor differentiatie zien we duidelijk het langzaam dalend verloop en ook een duidelijke seizoenaliteit (telkens wederkerende pieken)
Op het cumulatief periodogram voor differentiatie zien we een steile lijn aan linkerkant wat dus wijst op een langetermijntrend. We zien ook dat de functie getrapt is wat dus de seizoenaliteit aangeeft. We kunnen ook zien dat 70% verklaard wordt door die langetermijnbeweging.

Op het raw perioddogram na differentiatie zien we dat het langzaam dalend patroon en de pieken verdwenen zijn. De langetermijntrend en de seizoenaliteit zijn dus weggewerkt.
Cumulatief periodogram: De steile getrapt lijn aan linkerkant is weggewerkt door differentiatie. De curve valt wel nog niet helemaal in het betrouwbaarheidsinterval, er zijn nog steeds golfbewegingen die je kan voorspellen. Dus er is nog verbetering mogelijk. Besluit: De parameters die leiden tot een min of meer stationaire tijdreeks zijn: lambda=0.5 ; d=1 ; D=1
2008-12-15 11:21:25 [Toon Wouters] [reply] 
Uit het cumulative periodogram kunnen we besluiten dat zowel de snelle stijging van de curve en het trapgewijsverloop van de curve verdwenen zijn. Indien de curve perfect op de diagonaal ligt, kan je niets meer verklaren, er is geen voorspelbaarheid. Indien de curve nog buiten het 95% betrouwbaarheidsinterval valt, zijn er nog golfbewegingen aanwezig die te verklaren zijn. Hier zijn er na de differentiatie nog voorspelbare golfbewegingen aanwezig. Ook de plaats waar de curve buiten het interval ligt kan een mogelijkheid zijn om deze te verklaren door ARMA-processen, maar is zeker niet optimaal. Indien de curve boven het 95 % betrouwbaarheidsinterval ligt (links), kan verklaard worden door RA-processen. Als de curve beneden het 95% betrouwbaarheidsinterval ligt (rechts), kan verklaard worden door MA-processen.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7
384.6
365.8
368.1
367.9
347
343.3
292.9
311.5
300.9
366.9
356.9
329.7
316.2
269
289.3
266.2
253.6
233.8
228.4
253.6
260.1
306.6
309.2
309.5
271
279.9
317.9
298.4
246.7
227.3
209.1
259.9
266
320.6
308.5
282.2
262.7
263.5
313.1
284.3
252.6
250.3
246.5
312.7
333.2
446.4
511.6
515.5
506.4
483.2
522.3
509.8
460.7
405.8
375
378.5
406.8
467.8
469.8
429.8
355.8
332.7
378
360.5
334.7
319.5
323.1
363.6
352.1
411.9
388.6
416.4
360.7
338
417.2
388.4
371.1
331.5
353.7
396.7
447
533.5
565.4
542.3
488.7
467.1
531.3
496.1
444
403.4
386.3
394.1
404.1
462.1
448.1
432.3
386.3
395.2
421.9
382.9
384.2
345.5
323.4
372.6
376
462.7
487
444.2
399.3
394.9
455.4
414
375.5
347
339.4
385.8
378.8
451.8
446.1
422.5
383.1
352.8
445.3
367.5
355.1
326.2
319.8
331.8
340.9
394.1
417.2
369.9
349.2
321.4
405.7
342.9
316.5
284.2
270.9
288.8
278.8
324.4
310.9
299
273
279.3
359.2
305
282.1
250.3
246.5
257.9
266.5
315.9
318.4
295.4
266.4
245.8
362.8
324.9
294.2
289.5
295.2
290.3
272
307.4
328.7
292.9
249.1
230.4
361.5
321.7
277.2
260.7
251
257.6
241.8
287.5
292.3
274.7
254.2
230
339
318.2
287
295.8
284
271
262.7
340.6
379.4
373.3
355.2
338.4
466.9
451
422
429.2
425.9
460.7
463.6
541.4
544.2
517.5
469.4
439.4
549
533
506.1
484
457
481.5
469.5
544.7
541.2
521.5
469.7
434.4
542.6
517.3
485.7
465.8
447
426.6
411.6
467.5
484.5
451.2
417.4
379.9
484.7
455
420.8
416.5
376.3
405.6
405.8
500.8
514
475.5
430.1
414.4
538
526
488.5
520.2
504.4
568.5
610.6
818
830.9
835.9
782
762.3
856.9
820.9
769.6
752.2
724.4
723.1
719.5
817.4
803.3
752.5
689
630.4
765.5
757.7
732.2
702.6
683.3
709.5
702.2
784.8
810.9
755.6
656.8
615.1
745.3
694.1
675.7
643.7
622.1
634.6
588
689.7
673.9
647.9
568.8
545.7
632.6
643.8
593.1
579.7
546
562.9
572.5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29797&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29797&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29797&T=0

As an alternative you can also use a QR Code:  
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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0028 (360)28.47367
0.0056 (180)414.292161
0.0083 (120)104.659583
0.0111 (90)527.62959
0.0139 (72)436.831196
0.0167 (60)631.528207
0.0194 (51.4286)5839.526931
0.0222 (45)1169.573349
0.025 (40)5072.18807
0.0278 (36)2213.515735
0.0306 (32.7273)852.336707
0.0333 (30)530.526269
0.0361 (27.6923)11261.18092
0.0389 (25.7143)6978.078336
0.0417 (24)459.614366
0.0444 (22.5)3692.814056
0.0472 (21.1765)2628.95551
0.05 (20)775.979553
0.0528 (18.9474)2893.995714
0.0556 (18)2214.011437
0.0583 (17.1429)3355.14256
0.0611 (16.3636)1307.491068
0.0639 (15.6522)1376.503128
0.0667 (15)267.588572
0.0694 (14.4)51.710806
0.0722 (13.8462)0.898643
0.075 (13.3333)261.375885
0.0778 (12.8571)119.199203
0.0806 (12.4138)87.080052
0.0833 (12)19.728341
0.0861 (11.6129)20.250833
0.0889 (11.25)412.746472
0.0917 (10.9091)55.508656
0.0944 (10.5882)1.792884
0.0972 (10.2857)67.226566
0.1 (10)1059.920249
0.1028 (9.7297)3108.735703
0.1056 (9.4737)139.152789
0.1083 (9.2308)635.633722
0.1111 (9)1.215956
0.1139 (8.7805)1017.652401
0.1167 (8.5714)518.062615
0.1194 (8.3721)975.699483
0.1222 (8.1818)1066.396239
0.125 (8)1180.319748
0.1278 (7.8261)351.203644
0.1306 (7.6596)286.661143
0.1333 (7.5)1571.981167
0.1361 (7.3469)725.70512
0.1389 (7.2)60.092625
0.1417 (7.0588)900.764046
0.1444 (6.9231)667.595856
0.1472 (6.7925)993.521882
0.15 (6.6667)475.721172
0.1528 (6.5455)195.122165
0.1556 (6.4286)98.909622
0.1583 (6.3158)97.311996
0.1611 (6.2069)164.320589
0.1639 (6.1017)98.431157
0.1667 (6)33.698325
0.1694 (5.9016)50.550402
0.1722 (5.8065)375.472754
0.175 (5.7143)8.511937
0.1778 (5.625)160.861268
0.1806 (5.5385)127.439707
0.1833 (5.4545)551.137581
0.1861 (5.3731)297.839469
0.1889 (5.2941)260.703525
0.1917 (5.2174)7.981103
0.1944 (5.1429)1564.389383
0.1972 (5.0704)239.758911
0.2 (5)625.813898
0.2028 (4.9315)2321.90262
0.2056 (4.8649)2869.556434
0.2083 (4.8)1573.859437
0.2111 (4.7368)108.639417
0.2139 (4.6753)935.298211
0.2167 (4.6154)842.467548
0.2194 (4.557)227.504124
0.2222 (4.5)148.088231
0.225 (4.4444)95.643432
0.2278 (4.3902)341.770836
0.2306 (4.3373)536.17233
0.2333 (4.2857)107.567867
0.2361 (4.2353)130.38183
0.2389 (4.186)8.213225
0.2417 (4.1379)745.338556
0.2444 (4.0909)29.698788
0.2472 (4.0449)43.691722
0.25 (4)41.908876
0.2528 (3.956)54.567587
0.2556 (3.913)38.196879
0.2583 (3.871)255.528431
0.2611 (3.8298)16.929041
0.2639 (3.7895)221.37186
0.2667 (3.75)278.820051
0.2694 (3.7113)1154.124681
0.2722 (3.6735)358.15741
0.275 (3.6364)801.474987
0.2778 (3.6)75.938049
0.2806 (3.5644)142.783243
0.2833 (3.5294)356.177064
0.2861 (3.4951)3060.81221
0.2889 (3.4615)20.760888
0.2917 (3.4286)182.723581
0.2944 (3.3962)370.419856
0.2972 (3.3645)63.884539
0.3 (3.3333)117.921087
0.3028 (3.3028)315.866478
0.3056 (3.2727)379.132894
0.3083 (3.2432)345.283894
0.3111 (3.2143)424.96728
0.3139 (3.1858)409.982604
0.3167 (3.1579)145.028319
0.3194 (3.1304)15.430093
0.3222 (3.1034)399.788866
0.325 (3.0769)31.899729
0.3278 (3.0508)62.383933
0.3306 (3.0252)118.884177
0.3333 (3)27.373487
0.3361 (2.9752)21.638867
0.3389 (2.9508)14.244087
0.3417 (2.9268)127.687918
0.3444 (2.9032)28.359501
0.3472 (2.88)112.571672
0.35 (2.8571)1019.932187
0.3528 (2.8346)473.066131
0.3556 (2.8125)489.421993
0.3583 (2.7907)473.937598
0.3611 (2.7692)560.319681
0.3639 (2.7481)2248.32203
0.3667 (2.7273)116.734055
0.3694 (2.7068)238.708351
0.3722 (2.6866)660.480161
0.375 (2.6667)246.379527
0.3778 (2.6471)540.346449
0.3806 (2.6277)1259.722361
0.3833 (2.6087)788.06859
0.3861 (2.5899)196.688116
0.3889 (2.5714)668.642704
0.3917 (2.5532)1188.229112
0.3944 (2.5352)933.439352
0.3972 (2.5175)62.193625
0.4 (2.5)13.350142
0.4028 (2.4828)94.248396
0.4056 (2.4658)50.198259
0.4083 (2.449)81.026515
0.4111 (2.4324)114.513619
0.4139 (2.4161)20.642128
0.4167 (2.4)146.287264
0.4194 (2.3841)44.979104
0.4222 (2.3684)31.638169
0.425 (2.3529)60.237249
0.4278 (2.3377)43.173649
0.4306 (2.3226)589.170987
0.4333 (2.3077)622.959985
0.4361 (2.293)8.900882
0.4389 (2.2785)771.085924
0.4417 (2.2642)1006.968599
0.4444 (2.25)304.823593
0.4472 (2.236)1605.527866
0.45 (2.2222)261.96916
0.4528 (2.2086)505.50468
0.4556 (2.1951)3999.710889
0.4583 (2.1818)718.42606
0.4611 (2.1687)751.190363
0.4639 (2.1557)678.418759
0.4667 (2.1429)933.95044
0.4694 (2.1302)43.074796
0.4722 (2.1176)5855.746814
0.475 (2.1053)32.815179
0.4778 (2.093)1311.654262
0.4806 (2.0809)1699.615978
0.4833 (2.069)159.171774
0.4861 (2.0571)456.965247
0.4889 (2.0455)60.234123
0.4917 (2.0339)167.225704
0.4944 (2.0225)180.46487
0.4972 (2.0112)97.224213
0.5 (2)24.253402

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 1 \tabularnewline
Degree of seasonal differencing (D) & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0028 (360) & 28.47367 \tabularnewline
0.0056 (180) & 414.292161 \tabularnewline
0.0083 (120) & 104.659583 \tabularnewline
0.0111 (90) & 527.62959 \tabularnewline
0.0139 (72) & 436.831196 \tabularnewline
0.0167 (60) & 631.528207 \tabularnewline
0.0194 (51.4286) & 5839.526931 \tabularnewline
0.0222 (45) & 1169.573349 \tabularnewline
0.025 (40) & 5072.18807 \tabularnewline
0.0278 (36) & 2213.515735 \tabularnewline
0.0306 (32.7273) & 852.336707 \tabularnewline
0.0333 (30) & 530.526269 \tabularnewline
0.0361 (27.6923) & 11261.18092 \tabularnewline
0.0389 (25.7143) & 6978.078336 \tabularnewline
0.0417 (24) & 459.614366 \tabularnewline
0.0444 (22.5) & 3692.814056 \tabularnewline
0.0472 (21.1765) & 2628.95551 \tabularnewline
0.05 (20) & 775.979553 \tabularnewline
0.0528 (18.9474) & 2893.995714 \tabularnewline
0.0556 (18) & 2214.011437 \tabularnewline
0.0583 (17.1429) & 3355.14256 \tabularnewline
0.0611 (16.3636) & 1307.491068 \tabularnewline
0.0639 (15.6522) & 1376.503128 \tabularnewline
0.0667 (15) & 267.588572 \tabularnewline
0.0694 (14.4) & 51.710806 \tabularnewline
0.0722 (13.8462) & 0.898643 \tabularnewline
0.075 (13.3333) & 261.375885 \tabularnewline
0.0778 (12.8571) & 119.199203 \tabularnewline
0.0806 (12.4138) & 87.080052 \tabularnewline
0.0833 (12) & 19.728341 \tabularnewline
0.0861 (11.6129) & 20.250833 \tabularnewline
0.0889 (11.25) & 412.746472 \tabularnewline
0.0917 (10.9091) & 55.508656 \tabularnewline
0.0944 (10.5882) & 1.792884 \tabularnewline
0.0972 (10.2857) & 67.226566 \tabularnewline
0.1 (10) & 1059.920249 \tabularnewline
0.1028 (9.7297) & 3108.735703 \tabularnewline
0.1056 (9.4737) & 139.152789 \tabularnewline
0.1083 (9.2308) & 635.633722 \tabularnewline
0.1111 (9) & 1.215956 \tabularnewline
0.1139 (8.7805) & 1017.652401 \tabularnewline
0.1167 (8.5714) & 518.062615 \tabularnewline
0.1194 (8.3721) & 975.699483 \tabularnewline
0.1222 (8.1818) & 1066.396239 \tabularnewline
0.125 (8) & 1180.319748 \tabularnewline
0.1278 (7.8261) & 351.203644 \tabularnewline
0.1306 (7.6596) & 286.661143 \tabularnewline
0.1333 (7.5) & 1571.981167 \tabularnewline
0.1361 (7.3469) & 725.70512 \tabularnewline
0.1389 (7.2) & 60.092625 \tabularnewline
0.1417 (7.0588) & 900.764046 \tabularnewline
0.1444 (6.9231) & 667.595856 \tabularnewline
0.1472 (6.7925) & 993.521882 \tabularnewline
0.15 (6.6667) & 475.721172 \tabularnewline
0.1528 (6.5455) & 195.122165 \tabularnewline
0.1556 (6.4286) & 98.909622 \tabularnewline
0.1583 (6.3158) & 97.311996 \tabularnewline
0.1611 (6.2069) & 164.320589 \tabularnewline
0.1639 (6.1017) & 98.431157 \tabularnewline
0.1667 (6) & 33.698325 \tabularnewline
0.1694 (5.9016) & 50.550402 \tabularnewline
0.1722 (5.8065) & 375.472754 \tabularnewline
0.175 (5.7143) & 8.511937 \tabularnewline
0.1778 (5.625) & 160.861268 \tabularnewline
0.1806 (5.5385) & 127.439707 \tabularnewline
0.1833 (5.4545) & 551.137581 \tabularnewline
0.1861 (5.3731) & 297.839469 \tabularnewline
0.1889 (5.2941) & 260.703525 \tabularnewline
0.1917 (5.2174) & 7.981103 \tabularnewline
0.1944 (5.1429) & 1564.389383 \tabularnewline
0.1972 (5.0704) & 239.758911 \tabularnewline
0.2 (5) & 625.813898 \tabularnewline
0.2028 (4.9315) & 2321.90262 \tabularnewline
0.2056 (4.8649) & 2869.556434 \tabularnewline
0.2083 (4.8) & 1573.859437 \tabularnewline
0.2111 (4.7368) & 108.639417 \tabularnewline
0.2139 (4.6753) & 935.298211 \tabularnewline
0.2167 (4.6154) & 842.467548 \tabularnewline
0.2194 (4.557) & 227.504124 \tabularnewline
0.2222 (4.5) & 148.088231 \tabularnewline
0.225 (4.4444) & 95.643432 \tabularnewline
0.2278 (4.3902) & 341.770836 \tabularnewline
0.2306 (4.3373) & 536.17233 \tabularnewline
0.2333 (4.2857) & 107.567867 \tabularnewline
0.2361 (4.2353) & 130.38183 \tabularnewline
0.2389 (4.186) & 8.213225 \tabularnewline
0.2417 (4.1379) & 745.338556 \tabularnewline
0.2444 (4.0909) & 29.698788 \tabularnewline
0.2472 (4.0449) & 43.691722 \tabularnewline
0.25 (4) & 41.908876 \tabularnewline
0.2528 (3.956) & 54.567587 \tabularnewline
0.2556 (3.913) & 38.196879 \tabularnewline
0.2583 (3.871) & 255.528431 \tabularnewline
0.2611 (3.8298) & 16.929041 \tabularnewline
0.2639 (3.7895) & 221.37186 \tabularnewline
0.2667 (3.75) & 278.820051 \tabularnewline
0.2694 (3.7113) & 1154.124681 \tabularnewline
0.2722 (3.6735) & 358.15741 \tabularnewline
0.275 (3.6364) & 801.474987 \tabularnewline
0.2778 (3.6) & 75.938049 \tabularnewline
0.2806 (3.5644) & 142.783243 \tabularnewline
0.2833 (3.5294) & 356.177064 \tabularnewline
0.2861 (3.4951) & 3060.81221 \tabularnewline
0.2889 (3.4615) & 20.760888 \tabularnewline
0.2917 (3.4286) & 182.723581 \tabularnewline
0.2944 (3.3962) & 370.419856 \tabularnewline
0.2972 (3.3645) & 63.884539 \tabularnewline
0.3 (3.3333) & 117.921087 \tabularnewline
0.3028 (3.3028) & 315.866478 \tabularnewline
0.3056 (3.2727) & 379.132894 \tabularnewline
0.3083 (3.2432) & 345.283894 \tabularnewline
0.3111 (3.2143) & 424.96728 \tabularnewline
0.3139 (3.1858) & 409.982604 \tabularnewline
0.3167 (3.1579) & 145.028319 \tabularnewline
0.3194 (3.1304) & 15.430093 \tabularnewline
0.3222 (3.1034) & 399.788866 \tabularnewline
0.325 (3.0769) & 31.899729 \tabularnewline
0.3278 (3.0508) & 62.383933 \tabularnewline
0.3306 (3.0252) & 118.884177 \tabularnewline
0.3333 (3) & 27.373487 \tabularnewline
0.3361 (2.9752) & 21.638867 \tabularnewline
0.3389 (2.9508) & 14.244087 \tabularnewline
0.3417 (2.9268) & 127.687918 \tabularnewline
0.3444 (2.9032) & 28.359501 \tabularnewline
0.3472 (2.88) & 112.571672 \tabularnewline
0.35 (2.8571) & 1019.932187 \tabularnewline
0.3528 (2.8346) & 473.066131 \tabularnewline
0.3556 (2.8125) & 489.421993 \tabularnewline
0.3583 (2.7907) & 473.937598 \tabularnewline
0.3611 (2.7692) & 560.319681 \tabularnewline
0.3639 (2.7481) & 2248.32203 \tabularnewline
0.3667 (2.7273) & 116.734055 \tabularnewline
0.3694 (2.7068) & 238.708351 \tabularnewline
0.3722 (2.6866) & 660.480161 \tabularnewline
0.375 (2.6667) & 246.379527 \tabularnewline
0.3778 (2.6471) & 540.346449 \tabularnewline
0.3806 (2.6277) & 1259.722361 \tabularnewline
0.3833 (2.6087) & 788.06859 \tabularnewline
0.3861 (2.5899) & 196.688116 \tabularnewline
0.3889 (2.5714) & 668.642704 \tabularnewline
0.3917 (2.5532) & 1188.229112 \tabularnewline
0.3944 (2.5352) & 933.439352 \tabularnewline
0.3972 (2.5175) & 62.193625 \tabularnewline
0.4 (2.5) & 13.350142 \tabularnewline
0.4028 (2.4828) & 94.248396 \tabularnewline
0.4056 (2.4658) & 50.198259 \tabularnewline
0.4083 (2.449) & 81.026515 \tabularnewline
0.4111 (2.4324) & 114.513619 \tabularnewline
0.4139 (2.4161) & 20.642128 \tabularnewline
0.4167 (2.4) & 146.287264 \tabularnewline
0.4194 (2.3841) & 44.979104 \tabularnewline
0.4222 (2.3684) & 31.638169 \tabularnewline
0.425 (2.3529) & 60.237249 \tabularnewline
0.4278 (2.3377) & 43.173649 \tabularnewline
0.4306 (2.3226) & 589.170987 \tabularnewline
0.4333 (2.3077) & 622.959985 \tabularnewline
0.4361 (2.293) & 8.900882 \tabularnewline
0.4389 (2.2785) & 771.085924 \tabularnewline
0.4417 (2.2642) & 1006.968599 \tabularnewline
0.4444 (2.25) & 304.823593 \tabularnewline
0.4472 (2.236) & 1605.527866 \tabularnewline
0.45 (2.2222) & 261.96916 \tabularnewline
0.4528 (2.2086) & 505.50468 \tabularnewline
0.4556 (2.1951) & 3999.710889 \tabularnewline
0.4583 (2.1818) & 718.42606 \tabularnewline
0.4611 (2.1687) & 751.190363 \tabularnewline
0.4639 (2.1557) & 678.418759 \tabularnewline
0.4667 (2.1429) & 933.95044 \tabularnewline
0.4694 (2.1302) & 43.074796 \tabularnewline
0.4722 (2.1176) & 5855.746814 \tabularnewline
0.475 (2.1053) & 32.815179 \tabularnewline
0.4778 (2.093) & 1311.654262 \tabularnewline
0.4806 (2.0809) & 1699.615978 \tabularnewline
0.4833 (2.069) & 159.171774 \tabularnewline
0.4861 (2.0571) & 456.965247 \tabularnewline
0.4889 (2.0455) & 60.234123 \tabularnewline
0.4917 (2.0339) & 167.225704 \tabularnewline
0.4944 (2.0225) & 180.46487 \tabularnewline
0.4972 (2.0112) & 97.224213 \tabularnewline
0.5 (2) & 24.253402 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29797&T=1

[TABLE]
[ROW][C]Raw Periodogram[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda)[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d)[/C][C]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D)[/C][C]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0028 (360)[/C][C]28.47367[/C][/ROW]
[ROW][C]0.0056 (180)[/C][C]414.292161[/C][/ROW]
[ROW][C]0.0083 (120)[/C][C]104.659583[/C][/ROW]
[ROW][C]0.0111 (90)[/C][C]527.62959[/C][/ROW]
[ROW][C]0.0139 (72)[/C][C]436.831196[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]631.528207[/C][/ROW]
[ROW][C]0.0194 (51.4286)[/C][C]5839.526931[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]1169.573349[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]5072.18807[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]2213.515735[/C][/ROW]
[ROW][C]0.0306 (32.7273)[/C][C]852.336707[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]530.526269[/C][/ROW]
[ROW][C]0.0361 (27.6923)[/C][C]11261.18092[/C][/ROW]
[ROW][C]0.0389 (25.7143)[/C][C]6978.078336[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]459.614366[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]3692.814056[/C][/ROW]
[ROW][C]0.0472 (21.1765)[/C][C]2628.95551[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]775.979553[/C][/ROW]
[ROW][C]0.0528 (18.9474)[/C][C]2893.995714[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]2214.011437[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]3355.14256[/C][/ROW]
[ROW][C]0.0611 (16.3636)[/C][C]1307.491068[/C][/ROW]
[ROW][C]0.0639 (15.6522)[/C][C]1376.503128[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]267.588572[/C][/ROW]
[ROW][C]0.0694 (14.4)[/C][C]51.710806[/C][/ROW]
[ROW][C]0.0722 (13.8462)[/C][C]0.898643[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]261.375885[/C][/ROW]
[ROW][C]0.0778 (12.8571)[/C][C]119.199203[/C][/ROW]
[ROW][C]0.0806 (12.4138)[/C][C]87.080052[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]19.728341[/C][/ROW]
[ROW][C]0.0861 (11.6129)[/C][C]20.250833[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]412.746472[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]55.508656[/C][/ROW]
[ROW][C]0.0944 (10.5882)[/C][C]1.792884[/C][/ROW]
[ROW][C]0.0972 (10.2857)[/C][C]67.226566[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]1059.920249[/C][/ROW]
[ROW][C]0.1028 (9.7297)[/C][C]3108.735703[/C][/ROW]
[ROW][C]0.1056 (9.4737)[/C][C]139.152789[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]635.633722[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]1.215956[/C][/ROW]
[ROW][C]0.1139 (8.7805)[/C][C]1017.652401[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]518.062615[/C][/ROW]
[ROW][C]0.1194 (8.3721)[/C][C]975.699483[/C][/ROW]
[ROW][C]0.1222 (8.1818)[/C][C]1066.396239[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]1180.319748[/C][/ROW]
[ROW][C]0.1278 (7.8261)[/C][C]351.203644[/C][/ROW]
[ROW][C]0.1306 (7.6596)[/C][C]286.661143[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]1571.981167[/C][/ROW]
[ROW][C]0.1361 (7.3469)[/C][C]725.70512[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]60.092625[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]900.764046[/C][/ROW]
[ROW][C]0.1444 (6.9231)[/C][C]667.595856[/C][/ROW]
[ROW][C]0.1472 (6.7925)[/C][C]993.521882[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]475.721172[/C][/ROW]
[ROW][C]0.1528 (6.5455)[/C][C]195.122165[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]98.909622[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]97.311996[/C][/ROW]
[ROW][C]0.1611 (6.2069)[/C][C]164.320589[/C][/ROW]
[ROW][C]0.1639 (6.1017)[/C][C]98.431157[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]33.698325[/C][/ROW]
[ROW][C]0.1694 (5.9016)[/C][C]50.550402[/C][/ROW]
[ROW][C]0.1722 (5.8065)[/C][C]375.472754[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]8.511937[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]160.861268[/C][/ROW]
[ROW][C]0.1806 (5.5385)[/C][C]127.439707[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]551.137581[/C][/ROW]
[ROW][C]0.1861 (5.3731)[/C][C]297.839469[/C][/ROW]
[ROW][C]0.1889 (5.2941)[/C][C]260.703525[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]7.981103[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]1564.389383[/C][/ROW]
[ROW][C]0.1972 (5.0704)[/C][C]239.758911[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]625.813898[/C][/ROW]
[ROW][C]0.2028 (4.9315)[/C][C]2321.90262[/C][/ROW]
[ROW][C]0.2056 (4.8649)[/C][C]2869.556434[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]1573.859437[/C][/ROW]
[ROW][C]0.2111 (4.7368)[/C][C]108.639417[/C][/ROW]
[ROW][C]0.2139 (4.6753)[/C][C]935.298211[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]842.467548[/C][/ROW]
[ROW][C]0.2194 (4.557)[/C][C]227.504124[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]148.088231[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]95.643432[/C][/ROW]
[ROW][C]0.2278 (4.3902)[/C][C]341.770836[/C][/ROW]
[ROW][C]0.2306 (4.3373)[/C][C]536.17233[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]107.567867[/C][/ROW]
[ROW][C]0.2361 (4.2353)[/C][C]130.38183[/C][/ROW]
[ROW][C]0.2389 (4.186)[/C][C]8.213225[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]745.338556[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]29.698788[/C][/ROW]
[ROW][C]0.2472 (4.0449)[/C][C]43.691722[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]41.908876[/C][/ROW]
[ROW][C]0.2528 (3.956)[/C][C]54.567587[/C][/ROW]
[ROW][C]0.2556 (3.913)[/C][C]38.196879[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]255.528431[/C][/ROW]
[ROW][C]0.2611 (3.8298)[/C][C]16.929041[/C][/ROW]
[ROW][C]0.2639 (3.7895)[/C][C]221.37186[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]278.820051[/C][/ROW]
[ROW][C]0.2694 (3.7113)[/C][C]1154.124681[/C][/ROW]
[ROW][C]0.2722 (3.6735)[/C][C]358.15741[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]801.474987[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]75.938049[/C][/ROW]
[ROW][C]0.2806 (3.5644)[/C][C]142.783243[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]356.177064[/C][/ROW]
[ROW][C]0.2861 (3.4951)[/C][C]3060.81221[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]20.760888[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]182.723581[/C][/ROW]
[ROW][C]0.2944 (3.3962)[/C][C]370.419856[/C][/ROW]
[ROW][C]0.2972 (3.3645)[/C][C]63.884539[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]117.921087[/C][/ROW]
[ROW][C]0.3028 (3.3028)[/C][C]315.866478[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]379.132894[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]345.283894[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]424.96728[/C][/ROW]
[ROW][C]0.3139 (3.1858)[/C][C]409.982604[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]145.028319[/C][/ROW]
[ROW][C]0.3194 (3.1304)[/C][C]15.430093[/C][/ROW]
[ROW][C]0.3222 (3.1034)[/C][C]399.788866[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]31.899729[/C][/ROW]
[ROW][C]0.3278 (3.0508)[/C][C]62.383933[/C][/ROW]
[ROW][C]0.3306 (3.0252)[/C][C]118.884177[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]27.373487[/C][/ROW]
[ROW][C]0.3361 (2.9752)[/C][C]21.638867[/C][/ROW]
[ROW][C]0.3389 (2.9508)[/C][C]14.244087[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]127.687918[/C][/ROW]
[ROW][C]0.3444 (2.9032)[/C][C]28.359501[/C][/ROW]
[ROW][C]0.3472 (2.88)[/C][C]112.571672[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]1019.932187[/C][/ROW]
[ROW][C]0.3528 (2.8346)[/C][C]473.066131[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]489.421993[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]473.937598[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]560.319681[/C][/ROW]
[ROW][C]0.3639 (2.7481)[/C][C]2248.32203[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]116.734055[/C][/ROW]
[ROW][C]0.3694 (2.7068)[/C][C]238.708351[/C][/ROW]
[ROW][C]0.3722 (2.6866)[/C][C]660.480161[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]246.379527[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]540.346449[/C][/ROW]
[ROW][C]0.3806 (2.6277)[/C][C]1259.722361[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]788.06859[/C][/ROW]
[ROW][C]0.3861 (2.5899)[/C][C]196.688116[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]668.642704[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]1188.229112[/C][/ROW]
[ROW][C]0.3944 (2.5352)[/C][C]933.439352[/C][/ROW]
[ROW][C]0.3972 (2.5175)[/C][C]62.193625[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]13.350142[/C][/ROW]
[ROW][C]0.4028 (2.4828)[/C][C]94.248396[/C][/ROW]
[ROW][C]0.4056 (2.4658)[/C][C]50.198259[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]81.026515[/C][/ROW]
[ROW][C]0.4111 (2.4324)[/C][C]114.513619[/C][/ROW]
[ROW][C]0.4139 (2.4161)[/C][C]20.642128[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]146.287264[/C][/ROW]
[ROW][C]0.4194 (2.3841)[/C][C]44.979104[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]31.638169[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]60.237249[/C][/ROW]
[ROW][C]0.4278 (2.3377)[/C][C]43.173649[/C][/ROW]
[ROW][C]0.4306 (2.3226)[/C][C]589.170987[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]622.959985[/C][/ROW]
[ROW][C]0.4361 (2.293)[/C][C]8.900882[/C][/ROW]
[ROW][C]0.4389 (2.2785)[/C][C]771.085924[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]1006.968599[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]304.823593[/C][/ROW]
[ROW][C]0.4472 (2.236)[/C][C]1605.527866[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]261.96916[/C][/ROW]
[ROW][C]0.4528 (2.2086)[/C][C]505.50468[/C][/ROW]
[ROW][C]0.4556 (2.1951)[/C][C]3999.710889[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]718.42606[/C][/ROW]
[ROW][C]0.4611 (2.1687)[/C][C]751.190363[/C][/ROW]
[ROW][C]0.4639 (2.1557)[/C][C]678.418759[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]933.95044[/C][/ROW]
[ROW][C]0.4694 (2.1302)[/C][C]43.074796[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]5855.746814[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]32.815179[/C][/ROW]
[ROW][C]0.4778 (2.093)[/C][C]1311.654262[/C][/ROW]
[ROW][C]0.4806 (2.0809)[/C][C]1699.615978[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]159.171774[/C][/ROW]
[ROW][C]0.4861 (2.0571)[/C][C]456.965247[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]60.234123[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]167.225704[/C][/ROW]
[ROW][C]0.4944 (2.0225)[/C][C]180.46487[/C][/ROW]
[ROW][C]0.4972 (2.0112)[/C][C]97.224213[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]24.253402[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29797&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29797&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0028 (360)28.47367
0.0056 (180)414.292161
0.0083 (120)104.659583
0.0111 (90)527.62959
0.0139 (72)436.831196
0.0167 (60)631.528207
0.0194 (51.4286)5839.526931
0.0222 (45)1169.573349
0.025 (40)5072.18807
0.0278 (36)2213.515735
0.0306 (32.7273)852.336707
0.0333 (30)530.526269
0.0361 (27.6923)11261.18092
0.0389 (25.7143)6978.078336
0.0417 (24)459.614366
0.0444 (22.5)3692.814056
0.0472 (21.1765)2628.95551
0.05 (20)775.979553
0.0528 (18.9474)2893.995714
0.0556 (18)2214.011437
0.0583 (17.1429)3355.14256
0.0611 (16.3636)1307.491068
0.0639 (15.6522)1376.503128
0.0667 (15)267.588572
0.0694 (14.4)51.710806
0.0722 (13.8462)0.898643
0.075 (13.3333)261.375885
0.0778 (12.8571)119.199203
0.0806 (12.4138)87.080052
0.0833 (12)19.728341
0.0861 (11.6129)20.250833
0.0889 (11.25)412.746472
0.0917 (10.9091)55.508656
0.0944 (10.5882)1.792884
0.0972 (10.2857)67.226566
0.1 (10)1059.920249
0.1028 (9.7297)3108.735703
0.1056 (9.4737)139.152789
0.1083 (9.2308)635.633722
0.1111 (9)1.215956
0.1139 (8.7805)1017.652401
0.1167 (8.5714)518.062615
0.1194 (8.3721)975.699483
0.1222 (8.1818)1066.396239
0.125 (8)1180.319748
0.1278 (7.8261)351.203644
0.1306 (7.6596)286.661143
0.1333 (7.5)1571.981167
0.1361 (7.3469)725.70512
0.1389 (7.2)60.092625
0.1417 (7.0588)900.764046
0.1444 (6.9231)667.595856
0.1472 (6.7925)993.521882
0.15 (6.6667)475.721172
0.1528 (6.5455)195.122165
0.1556 (6.4286)98.909622
0.1583 (6.3158)97.311996
0.1611 (6.2069)164.320589
0.1639 (6.1017)98.431157
0.1667 (6)33.698325
0.1694 (5.9016)50.550402
0.1722 (5.8065)375.472754
0.175 (5.7143)8.511937
0.1778 (5.625)160.861268
0.1806 (5.5385)127.439707
0.1833 (5.4545)551.137581
0.1861 (5.3731)297.839469
0.1889 (5.2941)260.703525
0.1917 (5.2174)7.981103
0.1944 (5.1429)1564.389383
0.1972 (5.0704)239.758911
0.2 (5)625.813898
0.2028 (4.9315)2321.90262
0.2056 (4.8649)2869.556434
0.2083 (4.8)1573.859437
0.2111 (4.7368)108.639417
0.2139 (4.6753)935.298211
0.2167 (4.6154)842.467548
0.2194 (4.557)227.504124
0.2222 (4.5)148.088231
0.225 (4.4444)95.643432
0.2278 (4.3902)341.770836
0.2306 (4.3373)536.17233
0.2333 (4.2857)107.567867
0.2361 (4.2353)130.38183
0.2389 (4.186)8.213225
0.2417 (4.1379)745.338556
0.2444 (4.0909)29.698788
0.2472 (4.0449)43.691722
0.25 (4)41.908876
0.2528 (3.956)54.567587
0.2556 (3.913)38.196879
0.2583 (3.871)255.528431
0.2611 (3.8298)16.929041
0.2639 (3.7895)221.37186
0.2667 (3.75)278.820051
0.2694 (3.7113)1154.124681
0.2722 (3.6735)358.15741
0.275 (3.6364)801.474987
0.2778 (3.6)75.938049
0.2806 (3.5644)142.783243
0.2833 (3.5294)356.177064
0.2861 (3.4951)3060.81221
0.2889 (3.4615)20.760888
0.2917 (3.4286)182.723581
0.2944 (3.3962)370.419856
0.2972 (3.3645)63.884539
0.3 (3.3333)117.921087
0.3028 (3.3028)315.866478
0.3056 (3.2727)379.132894
0.3083 (3.2432)345.283894
0.3111 (3.2143)424.96728
0.3139 (3.1858)409.982604
0.3167 (3.1579)145.028319
0.3194 (3.1304)15.430093
0.3222 (3.1034)399.788866
0.325 (3.0769)31.899729
0.3278 (3.0508)62.383933
0.3306 (3.0252)118.884177
0.3333 (3)27.373487
0.3361 (2.9752)21.638867
0.3389 (2.9508)14.244087
0.3417 (2.9268)127.687918
0.3444 (2.9032)28.359501
0.3472 (2.88)112.571672
0.35 (2.8571)1019.932187
0.3528 (2.8346)473.066131
0.3556 (2.8125)489.421993
0.3583 (2.7907)473.937598
0.3611 (2.7692)560.319681
0.3639 (2.7481)2248.32203
0.3667 (2.7273)116.734055
0.3694 (2.7068)238.708351
0.3722 (2.6866)660.480161
0.375 (2.6667)246.379527
0.3778 (2.6471)540.346449
0.3806 (2.6277)1259.722361
0.3833 (2.6087)788.06859
0.3861 (2.5899)196.688116
0.3889 (2.5714)668.642704
0.3917 (2.5532)1188.229112
0.3944 (2.5352)933.439352
0.3972 (2.5175)62.193625
0.4 (2.5)13.350142
0.4028 (2.4828)94.248396
0.4056 (2.4658)50.198259
0.4083 (2.449)81.026515
0.4111 (2.4324)114.513619
0.4139 (2.4161)20.642128
0.4167 (2.4)146.287264
0.4194 (2.3841)44.979104
0.4222 (2.3684)31.638169
0.425 (2.3529)60.237249
0.4278 (2.3377)43.173649
0.4306 (2.3226)589.170987
0.4333 (2.3077)622.959985
0.4361 (2.293)8.900882
0.4389 (2.2785)771.085924
0.4417 (2.2642)1006.968599
0.4444 (2.25)304.823593
0.4472 (2.236)1605.527866
0.45 (2.2222)261.96916
0.4528 (2.2086)505.50468
0.4556 (2.1951)3999.710889
0.4583 (2.1818)718.42606
0.4611 (2.1687)751.190363
0.4639 (2.1557)678.418759
0.4667 (2.1429)933.95044
0.4694 (2.1302)43.074796
0.4722 (2.1176)5855.746814
0.475 (2.1053)32.815179
0.4778 (2.093)1311.654262
0.4806 (2.0809)1699.615978
0.4833 (2.069)159.171774
0.4861 (2.0571)456.965247
0.4889 (2.0455)60.234123
0.4917 (2.0339)167.225704
0.4944 (2.0225)180.46487
0.4972 (2.0112)97.224213
0.5 (2)24.253402


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
bitmap(file='test1.png')
r <- spectrum(x,main='Raw Periodogram')
dev.off()
bitmap(file='test2.png')
cpgram(x,main='Cumulative Periodogram')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Raw Periodogram',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda)',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d)',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D)',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Frequency (Period)',header=TRUE)
a<-table.element(a,'Spectrum',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(r$freq)) {
a<-table.row.start(a)
mylab <- round(r$freq[i],4)
mylab <- paste(mylab,' (',sep='')
mylab <- paste(mylab,round(1/r$freq[i],4),sep='')
mylab <- paste(mylab,')',sep='')
a<-table.element(a,mylab,header=TRUE)
a<-table.element(a,round(r$spec[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')