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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationTue, 09 Dec 2008 04:06:19 -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/09/t1228820865wr09qf2f0coo8qj.htm/, Retrieved Sat, 25 May 2024 12:07:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31292, Retrieved Sat, 25 May 2024 12:07:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159
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] [ARMA] [2008-12-08 20:13:06] [bb23d1cf0d54ffd7ecbf207517b23b9e]
F           [Spectral Analysis] [step 3] [2008-12-09 11:06:19] [f4914427e726625a358be9269a8b7d03] [Current]
Feedback Forum
2008-12-15 14:38:34 [Aurélie Van Impe] [reply
Hier was het de bedoeling dat je alle gevonden parameters (lambda, d en D) al zou invullen. Lambda ben je echter vergeten aan te passen. Die staat nog op 1 ipv op 0.5 zoals je gevonden had. Ook heb je niet gebruik gemaakt van het spectrum, zoals in de opgave stond. In plaats daarvan heb je het cumulatieve periodogram besproken. Ik zal even opsommen wat je uit het spectrum kan afleiden (dat is de lange tabel met links de frequenties en de periodes van de golven, en rechts de spectrumwaarden). Om te beginnen wil een kleine frequentie zeggen: een lange periode. Jij bent op zoek naar lange periodes voor een lange termijntrend, en naar kortere periodes voor seizoenaliteit. Je moet controleren of die er nog zijn. Je kan dit controleren als volgt: Voor lange periodes kijk je naar de golven met periode 12 of een veelvoud van 12. Vervolgens kijk je naar de bijbehorende spectrumwaarde. Indien deze waarde opvallend groter is dan de waarden die er net boven of net onder liggen, dan wil dit zeggen dat de golf met die periode en die frequentie dominant aanwezig is in de tijdreeks. Een kleine spectrumwaarde wil zeggen dat die golf wel aanwezig is, maar niet zo'n grote invloed heeft op de loop van de gegevens/grafiek. Indien je de berekening opnieuw zou doen met de juiste lambdawaarde, zou je merken dat er bij de maanden 12 en veelvouden van 12 geen opvallend hoge spectrumwaarden meer zijn. De lange termijntrend is dus weggewerkt. Je zou wel nog enkele grote spectrumwaarden zien, maar deze horen bij golfbewegingen met een periode die geen veelvoud van 12 is. Daar spreken we van conjunctuurcyclussen.

Voor de seizoenale trends moet je kijken naar de golven met periodes die een aantal keren in 12 kunnen, bijvoorbeeld 6 of 4 of 3. Bij deze golven zie je ook geen opvallend hoge spectrumwaarden meer. De seizoenaliteit is dus ook verdwenen met andere woorden.

Je moet inderdaad gebruik maken van armaprocessen om de laatste voorspelbare elementen uit de tijdreeks te halen.
2008-12-16 18:23:28 [Peter Van Doninck] [reply
De student heeft hier een verkeerde waarde voor lambda ingevuld! Deze moet gelijk zijn aan 0,5, zoals berekend in step 1. Het klopt ook niet dat de student beweert dat de tijdreeks niet stationair is! Door eenmaal niet seizoenaal en eenmaal seizoenaal te differentiëren is de tijdreeks wel degelijk stationair!

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Dataseries X:
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




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=31292&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=31292&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31292&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







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=31292&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=31292&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31292&T=1

As an alternative you can also use a 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



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')