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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 10:27:51 -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/t1228843708zd9rt7uzzdp8iya.htm/, Retrieved Sun, 19 May 2024 10:20:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31609, Retrieved Sun, 19 May 2024 10:20:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Spectral Analysis] [20.3] [2008-12-09 17:27:51] [0458bd763b171003ec052ce63099d477] [Current]
Feedback Forum
2008-12-14 21:08:38 [Vincent Vanden Poel] [reply
Je hebt de vraag grotendeels correct beantwoord. Het is echter wel belangrijk om ook processen te herkennen aan de hand van de ACF ipv de vuistregel. De ACF grafiek die we bekomen door het ingeven van de waarden van de modelvergelijking toont ons een verloop dat aansluit bij dat van een AR proces. Indien we het eerste staafje van onze ACF uitrekken is dit verloop bijna exact gelijk aan dat van het AR proces.
Het bepalen van de orde heb je wel juist gedaan.
2008-12-16 19:28:08 [Peter Van Doninck] [reply
Het klopt niet dat er hier aan de linkerkant dominantie aanwezig is! Wanneer de grafiek buiten het 95% betrouwbaarheidsinterval ligt, hebben we te maken met voorspelbaarheid. In dit geval is de tijdreeks stationair. Nu kunnen we heiruit een AR proces afleiden, wat de student correct zegt.
2008-12-16 19:36:01 [Peter Van Doninck] [reply
Het klopt dat er een AR proces aanwezig is. Maar het klopt echter niet dat we voor de orde van p gaan kijken naar de lags op 12, 24, 36 enz bij de pacf. Dit zouden we wel moeten doen indien we P zouden moeten zoeken. In de pacf is p trouwens gelijk aan 2, dus we hebben te maken met een AR2 proces!
Voor het MA proces kijken we naar de pacf. Er is hier een dalende seizoenaliteit. In de acf zien we dat enkel lag 12 significant is, vandaar dat we een SMA1 proces hebben.
2008-12-17 07:59:54 [ee5aee65e0c44ac54c8097a6e28e37f4] [reply
Mischien had je ook beter kunnen illustreren aan de hand van 'Time series (old or new)'

Post a new message
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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31609&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31609&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31609&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)0.5
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0028 (360)0.057564
0.0056 (180)1.069301
0.0083 (120)0.220896
0.0111 (90)1.481315
0.0139 (72)0.995928
0.0167 (60)1.648276
0.0194 (51.4286)14.564678
0.0222 (45)1.840394
0.025 (40)12.766487
0.0278 (36)6.105788
0.0306 (32.7273)1.015385
0.0333 (30)0.399904
0.0361 (27.6923)29.526143
0.0389 (25.7143)18.248319
0.0417 (24)3.141788
0.0444 (22.5)10.236947
0.0472 (21.1765)6.590284
0.05 (20)1.145137
0.0528 (18.9474)4.348657
0.0556 (18)4.977999
0.0583 (17.1429)6.398841
0.0611 (16.3636)3.751172
0.0639 (15.6522)2.750313
0.0667 (15)0.533473
0.0694 (14.4)0.00977
0.0722 (13.8462)0.034506
0.075 (13.3333)0.835831
0.0778 (12.8571)0.166592
0.0806 (12.4138)0.261723
0.0833 (12)0.079353
0.0861 (11.6129)0.062316
0.0889 (11.25)0.609494
0.0917 (10.9091)0.130312
0.0944 (10.5882)0.02373
0.0972 (10.2857)0.078748
0.1 (10)2.109489
0.1028 (9.7297)7.511028
0.1056 (9.4737)0.502386
0.1083 (9.2308)2.636419
0.1111 (9)0.092986
0.1139 (8.7805)2.780718
0.1167 (8.5714)1.884332
0.1194 (8.3721)1.066026
0.1222 (8.1818)1.546977
0.125 (8)2.761493
0.1278 (7.8261)1.443971
0.1306 (7.6596)0.494138
0.1333 (7.5)4.404072
0.1361 (7.3469)1.28824
0.1389 (7.2)0.407265
0.1417 (7.0588)2.086069
0.1444 (6.9231)1.529735
0.1472 (6.7925)1.827748
0.15 (6.6667)2.541578
0.1528 (6.5455)0.581608
0.1556 (6.4286)0.640041
0.1583 (6.3158)0.354925
0.1611 (6.2069)0.041893
0.1639 (6.1017)0.246845
0.1667 (6)0.001917
0.1694 (5.9016)0.047417
0.1722 (5.8065)0.266618
0.175 (5.7143)0.018036
0.1778 (5.625)0.255299
0.1806 (5.5385)0.536108
0.1833 (5.4545)0.907431
0.1861 (5.3731)0.109349
0.1889 (5.2941)1.068629
0.1917 (5.2174)0.315716
0.1944 (5.1429)5.500412
0.1972 (5.0704)0.278307
0.2 (5)1.697187
0.2028 (4.9315)3.67589
0.2056 (4.8649)7.05649
0.2083 (4.8)4.592939
0.2111 (4.7368)0.587473
0.2139 (4.6753)2.068199
0.2167 (4.6154)1.642435
0.2194 (4.557)1.211529
0.2222 (4.5)0.365791
0.225 (4.4444)0.408188
0.2278 (4.3902)0.823555
0.2306 (4.3373)1.102988
0.2333 (4.2857)0.288742
0.2361 (4.2353)0.282547
0.2389 (4.186)0.008686
0.2417 (4.1379)1.972778
0.2444 (4.0909)0.059989
0.2472 (4.0449)0.165035
0.25 (4)0.022804
0.2528 (3.956)0.269391
0.2556 (3.913)0.052386
0.2583 (3.871)0.817169
0.2611 (3.8298)0.109156
0.2639 (3.7895)0.857574
0.2667 (3.75)0.854041
0.2694 (3.7113)4.952492
0.2722 (3.6735)0.965341
0.275 (3.6364)1.409417
0.2778 (3.6)0.052283
0.2806 (3.5644)0.016725
0.2833 (3.5294)1.605788
0.2861 (3.4951)7.08246
0.2889 (3.4615)0.107544
0.2917 (3.4286)1.354278
0.2944 (3.3962)1.166439
0.2972 (3.3645)0.596559
0.3 (3.3333)0.522582
0.3028 (3.3028)0.661809
0.3056 (3.2727)1.12578
0.3083 (3.2432)0.863734
0.3111 (3.2143)0.797993
0.3139 (3.1858)1.358446
0.3167 (3.1579)0.223895
0.3194 (3.1304)0.085736
0.3222 (3.1034)1.264808
0.325 (3.0769)0.247023
0.3278 (3.0508)0.188419
0.3306 (3.0252)0.337802
0.3333 (3)0.043553
0.3361 (2.9752)0.034062
0.3389 (2.9508)0.018071
0.3417 (2.9268)0.344637
0.3444 (2.9032)0.060212
0.3472 (2.88)0.69594
0.35 (2.8571)2.590298
0.3528 (2.8346)1.002245
0.3556 (2.8125)1.35004
0.3583 (2.7907)2.291366
0.3611 (2.7692)2.001674
0.3639 (2.7481)7.119634
0.3667 (2.7273)0.569299
0.3694 (2.7068)0.577886
0.3722 (2.6866)2.447876
0.375 (2.6667)0.716116
0.3778 (2.6471)0.754038
0.3806 (2.6277)4.874199
0.3833 (2.6087)1.824984
0.3861 (2.5899)0.549589
0.3889 (2.5714)1.235879
0.3917 (2.5532)4.102519
0.3944 (2.5352)2.003635
0.3972 (2.5175)0.620427
0.4 (2.5)0.204581
0.4028 (2.4828)0.515653
0.4056 (2.4658)0.019598
0.4083 (2.449)0.154699
0.4111 (2.4324)0.626278
0.4139 (2.4161)0.139812
0.4167 (2.4)0.167326
0.4194 (2.3841)0.084877
0.4222 (2.3684)0.196339
0.425 (2.3529)0.182845
0.4278 (2.3377)0.190421
0.4306 (2.3226)1.683037
0.4333 (2.3077)1.275025
0.4361 (2.293)0.342482
0.4389 (2.2785)1.607396
0.4417 (2.2642)1.564525
0.4444 (2.25)0.621786
0.4472 (2.236)4.467569
0.45 (2.2222)0.658739
0.4528 (2.2086)2.469759
0.4556 (2.1951)10.543687
0.4583 (2.1818)2.885492
0.4611 (2.1687)1.395165
0.4639 (2.1557)1.616309
0.4667 (2.1429)2.382695
0.4694 (2.1302)0.116625
0.4722 (2.1176)14.787816
0.475 (2.1053)0.485626
0.4778 (2.093)2.266653
0.4806 (2.0809)3.693014
0.4833 (2.069)0.066857
0.4861 (2.0571)0.987105
0.4889 (2.0455)0.06478
0.4917 (2.0339)0.528923
0.4944 (2.0225)0.340026
0.4972 (2.0112)0.36196
0.5 (2)0.070405

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 0.5 \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) & 0.057564 \tabularnewline
0.0056 (180) & 1.069301 \tabularnewline
0.0083 (120) & 0.220896 \tabularnewline
0.0111 (90) & 1.481315 \tabularnewline
0.0139 (72) & 0.995928 \tabularnewline
0.0167 (60) & 1.648276 \tabularnewline
0.0194 (51.4286) & 14.564678 \tabularnewline
0.0222 (45) & 1.840394 \tabularnewline
0.025 (40) & 12.766487 \tabularnewline
0.0278 (36) & 6.105788 \tabularnewline
0.0306 (32.7273) & 1.015385 \tabularnewline
0.0333 (30) & 0.399904 \tabularnewline
0.0361 (27.6923) & 29.526143 \tabularnewline
0.0389 (25.7143) & 18.248319 \tabularnewline
0.0417 (24) & 3.141788 \tabularnewline
0.0444 (22.5) & 10.236947 \tabularnewline
0.0472 (21.1765) & 6.590284 \tabularnewline
0.05 (20) & 1.145137 \tabularnewline
0.0528 (18.9474) & 4.348657 \tabularnewline
0.0556 (18) & 4.977999 \tabularnewline
0.0583 (17.1429) & 6.398841 \tabularnewline
0.0611 (16.3636) & 3.751172 \tabularnewline
0.0639 (15.6522) & 2.750313 \tabularnewline
0.0667 (15) & 0.533473 \tabularnewline
0.0694 (14.4) & 0.00977 \tabularnewline
0.0722 (13.8462) & 0.034506 \tabularnewline
0.075 (13.3333) & 0.835831 \tabularnewline
0.0778 (12.8571) & 0.166592 \tabularnewline
0.0806 (12.4138) & 0.261723 \tabularnewline
0.0833 (12) & 0.079353 \tabularnewline
0.0861 (11.6129) & 0.062316 \tabularnewline
0.0889 (11.25) & 0.609494 \tabularnewline
0.0917 (10.9091) & 0.130312 \tabularnewline
0.0944 (10.5882) & 0.02373 \tabularnewline
0.0972 (10.2857) & 0.078748 \tabularnewline
0.1 (10) & 2.109489 \tabularnewline
0.1028 (9.7297) & 7.511028 \tabularnewline
0.1056 (9.4737) & 0.502386 \tabularnewline
0.1083 (9.2308) & 2.636419 \tabularnewline
0.1111 (9) & 0.092986 \tabularnewline
0.1139 (8.7805) & 2.780718 \tabularnewline
0.1167 (8.5714) & 1.884332 \tabularnewline
0.1194 (8.3721) & 1.066026 \tabularnewline
0.1222 (8.1818) & 1.546977 \tabularnewline
0.125 (8) & 2.761493 \tabularnewline
0.1278 (7.8261) & 1.443971 \tabularnewline
0.1306 (7.6596) & 0.494138 \tabularnewline
0.1333 (7.5) & 4.404072 \tabularnewline
0.1361 (7.3469) & 1.28824 \tabularnewline
0.1389 (7.2) & 0.407265 \tabularnewline
0.1417 (7.0588) & 2.086069 \tabularnewline
0.1444 (6.9231) & 1.529735 \tabularnewline
0.1472 (6.7925) & 1.827748 \tabularnewline
0.15 (6.6667) & 2.541578 \tabularnewline
0.1528 (6.5455) & 0.581608 \tabularnewline
0.1556 (6.4286) & 0.640041 \tabularnewline
0.1583 (6.3158) & 0.354925 \tabularnewline
0.1611 (6.2069) & 0.041893 \tabularnewline
0.1639 (6.1017) & 0.246845 \tabularnewline
0.1667 (6) & 0.001917 \tabularnewline
0.1694 (5.9016) & 0.047417 \tabularnewline
0.1722 (5.8065) & 0.266618 \tabularnewline
0.175 (5.7143) & 0.018036 \tabularnewline
0.1778 (5.625) & 0.255299 \tabularnewline
0.1806 (5.5385) & 0.536108 \tabularnewline
0.1833 (5.4545) & 0.907431 \tabularnewline
0.1861 (5.3731) & 0.109349 \tabularnewline
0.1889 (5.2941) & 1.068629 \tabularnewline
0.1917 (5.2174) & 0.315716 \tabularnewline
0.1944 (5.1429) & 5.500412 \tabularnewline
0.1972 (5.0704) & 0.278307 \tabularnewline
0.2 (5) & 1.697187 \tabularnewline
0.2028 (4.9315) & 3.67589 \tabularnewline
0.2056 (4.8649) & 7.05649 \tabularnewline
0.2083 (4.8) & 4.592939 \tabularnewline
0.2111 (4.7368) & 0.587473 \tabularnewline
0.2139 (4.6753) & 2.068199 \tabularnewline
0.2167 (4.6154) & 1.642435 \tabularnewline
0.2194 (4.557) & 1.211529 \tabularnewline
0.2222 (4.5) & 0.365791 \tabularnewline
0.225 (4.4444) & 0.408188 \tabularnewline
0.2278 (4.3902) & 0.823555 \tabularnewline
0.2306 (4.3373) & 1.102988 \tabularnewline
0.2333 (4.2857) & 0.288742 \tabularnewline
0.2361 (4.2353) & 0.282547 \tabularnewline
0.2389 (4.186) & 0.008686 \tabularnewline
0.2417 (4.1379) & 1.972778 \tabularnewline
0.2444 (4.0909) & 0.059989 \tabularnewline
0.2472 (4.0449) & 0.165035 \tabularnewline
0.25 (4) & 0.022804 \tabularnewline
0.2528 (3.956) & 0.269391 \tabularnewline
0.2556 (3.913) & 0.052386 \tabularnewline
0.2583 (3.871) & 0.817169 \tabularnewline
0.2611 (3.8298) & 0.109156 \tabularnewline
0.2639 (3.7895) & 0.857574 \tabularnewline
0.2667 (3.75) & 0.854041 \tabularnewline
0.2694 (3.7113) & 4.952492 \tabularnewline
0.2722 (3.6735) & 0.965341 \tabularnewline
0.275 (3.6364) & 1.409417 \tabularnewline
0.2778 (3.6) & 0.052283 \tabularnewline
0.2806 (3.5644) & 0.016725 \tabularnewline
0.2833 (3.5294) & 1.605788 \tabularnewline
0.2861 (3.4951) & 7.08246 \tabularnewline
0.2889 (3.4615) & 0.107544 \tabularnewline
0.2917 (3.4286) & 1.354278 \tabularnewline
0.2944 (3.3962) & 1.166439 \tabularnewline
0.2972 (3.3645) & 0.596559 \tabularnewline
0.3 (3.3333) & 0.522582 \tabularnewline
0.3028 (3.3028) & 0.661809 \tabularnewline
0.3056 (3.2727) & 1.12578 \tabularnewline
0.3083 (3.2432) & 0.863734 \tabularnewline
0.3111 (3.2143) & 0.797993 \tabularnewline
0.3139 (3.1858) & 1.358446 \tabularnewline
0.3167 (3.1579) & 0.223895 \tabularnewline
0.3194 (3.1304) & 0.085736 \tabularnewline
0.3222 (3.1034) & 1.264808 \tabularnewline
0.325 (3.0769) & 0.247023 \tabularnewline
0.3278 (3.0508) & 0.188419 \tabularnewline
0.3306 (3.0252) & 0.337802 \tabularnewline
0.3333 (3) & 0.043553 \tabularnewline
0.3361 (2.9752) & 0.034062 \tabularnewline
0.3389 (2.9508) & 0.018071 \tabularnewline
0.3417 (2.9268) & 0.344637 \tabularnewline
0.3444 (2.9032) & 0.060212 \tabularnewline
0.3472 (2.88) & 0.69594 \tabularnewline
0.35 (2.8571) & 2.590298 \tabularnewline
0.3528 (2.8346) & 1.002245 \tabularnewline
0.3556 (2.8125) & 1.35004 \tabularnewline
0.3583 (2.7907) & 2.291366 \tabularnewline
0.3611 (2.7692) & 2.001674 \tabularnewline
0.3639 (2.7481) & 7.119634 \tabularnewline
0.3667 (2.7273) & 0.569299 \tabularnewline
0.3694 (2.7068) & 0.577886 \tabularnewline
0.3722 (2.6866) & 2.447876 \tabularnewline
0.375 (2.6667) & 0.716116 \tabularnewline
0.3778 (2.6471) & 0.754038 \tabularnewline
0.3806 (2.6277) & 4.874199 \tabularnewline
0.3833 (2.6087) & 1.824984 \tabularnewline
0.3861 (2.5899) & 0.549589 \tabularnewline
0.3889 (2.5714) & 1.235879 \tabularnewline
0.3917 (2.5532) & 4.102519 \tabularnewline
0.3944 (2.5352) & 2.003635 \tabularnewline
0.3972 (2.5175) & 0.620427 \tabularnewline
0.4 (2.5) & 0.204581 \tabularnewline
0.4028 (2.4828) & 0.515653 \tabularnewline
0.4056 (2.4658) & 0.019598 \tabularnewline
0.4083 (2.449) & 0.154699 \tabularnewline
0.4111 (2.4324) & 0.626278 \tabularnewline
0.4139 (2.4161) & 0.139812 \tabularnewline
0.4167 (2.4) & 0.167326 \tabularnewline
0.4194 (2.3841) & 0.084877 \tabularnewline
0.4222 (2.3684) & 0.196339 \tabularnewline
0.425 (2.3529) & 0.182845 \tabularnewline
0.4278 (2.3377) & 0.190421 \tabularnewline
0.4306 (2.3226) & 1.683037 \tabularnewline
0.4333 (2.3077) & 1.275025 \tabularnewline
0.4361 (2.293) & 0.342482 \tabularnewline
0.4389 (2.2785) & 1.607396 \tabularnewline
0.4417 (2.2642) & 1.564525 \tabularnewline
0.4444 (2.25) & 0.621786 \tabularnewline
0.4472 (2.236) & 4.467569 \tabularnewline
0.45 (2.2222) & 0.658739 \tabularnewline
0.4528 (2.2086) & 2.469759 \tabularnewline
0.4556 (2.1951) & 10.543687 \tabularnewline
0.4583 (2.1818) & 2.885492 \tabularnewline
0.4611 (2.1687) & 1.395165 \tabularnewline
0.4639 (2.1557) & 1.616309 \tabularnewline
0.4667 (2.1429) & 2.382695 \tabularnewline
0.4694 (2.1302) & 0.116625 \tabularnewline
0.4722 (2.1176) & 14.787816 \tabularnewline
0.475 (2.1053) & 0.485626 \tabularnewline
0.4778 (2.093) & 2.266653 \tabularnewline
0.4806 (2.0809) & 3.693014 \tabularnewline
0.4833 (2.069) & 0.066857 \tabularnewline
0.4861 (2.0571) & 0.987105 \tabularnewline
0.4889 (2.0455) & 0.06478 \tabularnewline
0.4917 (2.0339) & 0.528923 \tabularnewline
0.4944 (2.0225) & 0.340026 \tabularnewline
0.4972 (2.0112) & 0.36196 \tabularnewline
0.5 (2) & 0.070405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31609&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]0.5[/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]0.057564[/C][/ROW]
[ROW][C]0.0056 (180)[/C][C]1.069301[/C][/ROW]
[ROW][C]0.0083 (120)[/C][C]0.220896[/C][/ROW]
[ROW][C]0.0111 (90)[/C][C]1.481315[/C][/ROW]
[ROW][C]0.0139 (72)[/C][C]0.995928[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]1.648276[/C][/ROW]
[ROW][C]0.0194 (51.4286)[/C][C]14.564678[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]1.840394[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]12.766487[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]6.105788[/C][/ROW]
[ROW][C]0.0306 (32.7273)[/C][C]1.015385[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]0.399904[/C][/ROW]
[ROW][C]0.0361 (27.6923)[/C][C]29.526143[/C][/ROW]
[ROW][C]0.0389 (25.7143)[/C][C]18.248319[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]3.141788[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]10.236947[/C][/ROW]
[ROW][C]0.0472 (21.1765)[/C][C]6.590284[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]1.145137[/C][/ROW]
[ROW][C]0.0528 (18.9474)[/C][C]4.348657[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]4.977999[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]6.398841[/C][/ROW]
[ROW][C]0.0611 (16.3636)[/C][C]3.751172[/C][/ROW]
[ROW][C]0.0639 (15.6522)[/C][C]2.750313[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]0.533473[/C][/ROW]
[ROW][C]0.0694 (14.4)[/C][C]0.00977[/C][/ROW]
[ROW][C]0.0722 (13.8462)[/C][C]0.034506[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]0.835831[/C][/ROW]
[ROW][C]0.0778 (12.8571)[/C][C]0.166592[/C][/ROW]
[ROW][C]0.0806 (12.4138)[/C][C]0.261723[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]0.079353[/C][/ROW]
[ROW][C]0.0861 (11.6129)[/C][C]0.062316[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]0.609494[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]0.130312[/C][/ROW]
[ROW][C]0.0944 (10.5882)[/C][C]0.02373[/C][/ROW]
[ROW][C]0.0972 (10.2857)[/C][C]0.078748[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]2.109489[/C][/ROW]
[ROW][C]0.1028 (9.7297)[/C][C]7.511028[/C][/ROW]
[ROW][C]0.1056 (9.4737)[/C][C]0.502386[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]2.636419[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]0.092986[/C][/ROW]
[ROW][C]0.1139 (8.7805)[/C][C]2.780718[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]1.884332[/C][/ROW]
[ROW][C]0.1194 (8.3721)[/C][C]1.066026[/C][/ROW]
[ROW][C]0.1222 (8.1818)[/C][C]1.546977[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]2.761493[/C][/ROW]
[ROW][C]0.1278 (7.8261)[/C][C]1.443971[/C][/ROW]
[ROW][C]0.1306 (7.6596)[/C][C]0.494138[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]4.404072[/C][/ROW]
[ROW][C]0.1361 (7.3469)[/C][C]1.28824[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]0.407265[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]2.086069[/C][/ROW]
[ROW][C]0.1444 (6.9231)[/C][C]1.529735[/C][/ROW]
[ROW][C]0.1472 (6.7925)[/C][C]1.827748[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]2.541578[/C][/ROW]
[ROW][C]0.1528 (6.5455)[/C][C]0.581608[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]0.640041[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]0.354925[/C][/ROW]
[ROW][C]0.1611 (6.2069)[/C][C]0.041893[/C][/ROW]
[ROW][C]0.1639 (6.1017)[/C][C]0.246845[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.001917[/C][/ROW]
[ROW][C]0.1694 (5.9016)[/C][C]0.047417[/C][/ROW]
[ROW][C]0.1722 (5.8065)[/C][C]0.266618[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]0.018036[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]0.255299[/C][/ROW]
[ROW][C]0.1806 (5.5385)[/C][C]0.536108[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]0.907431[/C][/ROW]
[ROW][C]0.1861 (5.3731)[/C][C]0.109349[/C][/ROW]
[ROW][C]0.1889 (5.2941)[/C][C]1.068629[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]0.315716[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]5.500412[/C][/ROW]
[ROW][C]0.1972 (5.0704)[/C][C]0.278307[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]1.697187[/C][/ROW]
[ROW][C]0.2028 (4.9315)[/C][C]3.67589[/C][/ROW]
[ROW][C]0.2056 (4.8649)[/C][C]7.05649[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]4.592939[/C][/ROW]
[ROW][C]0.2111 (4.7368)[/C][C]0.587473[/C][/ROW]
[ROW][C]0.2139 (4.6753)[/C][C]2.068199[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]1.642435[/C][/ROW]
[ROW][C]0.2194 (4.557)[/C][C]1.211529[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]0.365791[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]0.408188[/C][/ROW]
[ROW][C]0.2278 (4.3902)[/C][C]0.823555[/C][/ROW]
[ROW][C]0.2306 (4.3373)[/C][C]1.102988[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]0.288742[/C][/ROW]
[ROW][C]0.2361 (4.2353)[/C][C]0.282547[/C][/ROW]
[ROW][C]0.2389 (4.186)[/C][C]0.008686[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]1.972778[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]0.059989[/C][/ROW]
[ROW][C]0.2472 (4.0449)[/C][C]0.165035[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0.022804[/C][/ROW]
[ROW][C]0.2528 (3.956)[/C][C]0.269391[/C][/ROW]
[ROW][C]0.2556 (3.913)[/C][C]0.052386[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]0.817169[/C][/ROW]
[ROW][C]0.2611 (3.8298)[/C][C]0.109156[/C][/ROW]
[ROW][C]0.2639 (3.7895)[/C][C]0.857574[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]0.854041[/C][/ROW]
[ROW][C]0.2694 (3.7113)[/C][C]4.952492[/C][/ROW]
[ROW][C]0.2722 (3.6735)[/C][C]0.965341[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]1.409417[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]0.052283[/C][/ROW]
[ROW][C]0.2806 (3.5644)[/C][C]0.016725[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]1.605788[/C][/ROW]
[ROW][C]0.2861 (3.4951)[/C][C]7.08246[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]0.107544[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]1.354278[/C][/ROW]
[ROW][C]0.2944 (3.3962)[/C][C]1.166439[/C][/ROW]
[ROW][C]0.2972 (3.3645)[/C][C]0.596559[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]0.522582[/C][/ROW]
[ROW][C]0.3028 (3.3028)[/C][C]0.661809[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]1.12578[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]0.863734[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]0.797993[/C][/ROW]
[ROW][C]0.3139 (3.1858)[/C][C]1.358446[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]0.223895[/C][/ROW]
[ROW][C]0.3194 (3.1304)[/C][C]0.085736[/C][/ROW]
[ROW][C]0.3222 (3.1034)[/C][C]1.264808[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]0.247023[/C][/ROW]
[ROW][C]0.3278 (3.0508)[/C][C]0.188419[/C][/ROW]
[ROW][C]0.3306 (3.0252)[/C][C]0.337802[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.043553[/C][/ROW]
[ROW][C]0.3361 (2.9752)[/C][C]0.034062[/C][/ROW]
[ROW][C]0.3389 (2.9508)[/C][C]0.018071[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]0.344637[/C][/ROW]
[ROW][C]0.3444 (2.9032)[/C][C]0.060212[/C][/ROW]
[ROW][C]0.3472 (2.88)[/C][C]0.69594[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]2.590298[/C][/ROW]
[ROW][C]0.3528 (2.8346)[/C][C]1.002245[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]1.35004[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]2.291366[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]2.001674[/C][/ROW]
[ROW][C]0.3639 (2.7481)[/C][C]7.119634[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]0.569299[/C][/ROW]
[ROW][C]0.3694 (2.7068)[/C][C]0.577886[/C][/ROW]
[ROW][C]0.3722 (2.6866)[/C][C]2.447876[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]0.716116[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]0.754038[/C][/ROW]
[ROW][C]0.3806 (2.6277)[/C][C]4.874199[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]1.824984[/C][/ROW]
[ROW][C]0.3861 (2.5899)[/C][C]0.549589[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]1.235879[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]4.102519[/C][/ROW]
[ROW][C]0.3944 (2.5352)[/C][C]2.003635[/C][/ROW]
[ROW][C]0.3972 (2.5175)[/C][C]0.620427[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]0.204581[/C][/ROW]
[ROW][C]0.4028 (2.4828)[/C][C]0.515653[/C][/ROW]
[ROW][C]0.4056 (2.4658)[/C][C]0.019598[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]0.154699[/C][/ROW]
[ROW][C]0.4111 (2.4324)[/C][C]0.626278[/C][/ROW]
[ROW][C]0.4139 (2.4161)[/C][C]0.139812[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]0.167326[/C][/ROW]
[ROW][C]0.4194 (2.3841)[/C][C]0.084877[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]0.196339[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]0.182845[/C][/ROW]
[ROW][C]0.4278 (2.3377)[/C][C]0.190421[/C][/ROW]
[ROW][C]0.4306 (2.3226)[/C][C]1.683037[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]1.275025[/C][/ROW]
[ROW][C]0.4361 (2.293)[/C][C]0.342482[/C][/ROW]
[ROW][C]0.4389 (2.2785)[/C][C]1.607396[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]1.564525[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]0.621786[/C][/ROW]
[ROW][C]0.4472 (2.236)[/C][C]4.467569[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]0.658739[/C][/ROW]
[ROW][C]0.4528 (2.2086)[/C][C]2.469759[/C][/ROW]
[ROW][C]0.4556 (2.1951)[/C][C]10.543687[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]2.885492[/C][/ROW]
[ROW][C]0.4611 (2.1687)[/C][C]1.395165[/C][/ROW]
[ROW][C]0.4639 (2.1557)[/C][C]1.616309[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]2.382695[/C][/ROW]
[ROW][C]0.4694 (2.1302)[/C][C]0.116625[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]14.787816[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]0.485626[/C][/ROW]
[ROW][C]0.4778 (2.093)[/C][C]2.266653[/C][/ROW]
[ROW][C]0.4806 (2.0809)[/C][C]3.693014[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]0.066857[/C][/ROW]
[ROW][C]0.4861 (2.0571)[/C][C]0.987105[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]0.06478[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]0.528923[/C][/ROW]
[ROW][C]0.4944 (2.0225)[/C][C]0.340026[/C][/ROW]
[ROW][C]0.4972 (2.0112)[/C][C]0.36196[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.070405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31609&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31609&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)0.5
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0028 (360)0.057564
0.0056 (180)1.069301
0.0083 (120)0.220896
0.0111 (90)1.481315
0.0139 (72)0.995928
0.0167 (60)1.648276
0.0194 (51.4286)14.564678
0.0222 (45)1.840394
0.025 (40)12.766487
0.0278 (36)6.105788
0.0306 (32.7273)1.015385
0.0333 (30)0.399904
0.0361 (27.6923)29.526143
0.0389 (25.7143)18.248319
0.0417 (24)3.141788
0.0444 (22.5)10.236947
0.0472 (21.1765)6.590284
0.05 (20)1.145137
0.0528 (18.9474)4.348657
0.0556 (18)4.977999
0.0583 (17.1429)6.398841
0.0611 (16.3636)3.751172
0.0639 (15.6522)2.750313
0.0667 (15)0.533473
0.0694 (14.4)0.00977
0.0722 (13.8462)0.034506
0.075 (13.3333)0.835831
0.0778 (12.8571)0.166592
0.0806 (12.4138)0.261723
0.0833 (12)0.079353
0.0861 (11.6129)0.062316
0.0889 (11.25)0.609494
0.0917 (10.9091)0.130312
0.0944 (10.5882)0.02373
0.0972 (10.2857)0.078748
0.1 (10)2.109489
0.1028 (9.7297)7.511028
0.1056 (9.4737)0.502386
0.1083 (9.2308)2.636419
0.1111 (9)0.092986
0.1139 (8.7805)2.780718
0.1167 (8.5714)1.884332
0.1194 (8.3721)1.066026
0.1222 (8.1818)1.546977
0.125 (8)2.761493
0.1278 (7.8261)1.443971
0.1306 (7.6596)0.494138
0.1333 (7.5)4.404072
0.1361 (7.3469)1.28824
0.1389 (7.2)0.407265
0.1417 (7.0588)2.086069
0.1444 (6.9231)1.529735
0.1472 (6.7925)1.827748
0.15 (6.6667)2.541578
0.1528 (6.5455)0.581608
0.1556 (6.4286)0.640041
0.1583 (6.3158)0.354925
0.1611 (6.2069)0.041893
0.1639 (6.1017)0.246845
0.1667 (6)0.001917
0.1694 (5.9016)0.047417
0.1722 (5.8065)0.266618
0.175 (5.7143)0.018036
0.1778 (5.625)0.255299
0.1806 (5.5385)0.536108
0.1833 (5.4545)0.907431
0.1861 (5.3731)0.109349
0.1889 (5.2941)1.068629
0.1917 (5.2174)0.315716
0.1944 (5.1429)5.500412
0.1972 (5.0704)0.278307
0.2 (5)1.697187
0.2028 (4.9315)3.67589
0.2056 (4.8649)7.05649
0.2083 (4.8)4.592939
0.2111 (4.7368)0.587473
0.2139 (4.6753)2.068199
0.2167 (4.6154)1.642435
0.2194 (4.557)1.211529
0.2222 (4.5)0.365791
0.225 (4.4444)0.408188
0.2278 (4.3902)0.823555
0.2306 (4.3373)1.102988
0.2333 (4.2857)0.288742
0.2361 (4.2353)0.282547
0.2389 (4.186)0.008686
0.2417 (4.1379)1.972778
0.2444 (4.0909)0.059989
0.2472 (4.0449)0.165035
0.25 (4)0.022804
0.2528 (3.956)0.269391
0.2556 (3.913)0.052386
0.2583 (3.871)0.817169
0.2611 (3.8298)0.109156
0.2639 (3.7895)0.857574
0.2667 (3.75)0.854041
0.2694 (3.7113)4.952492
0.2722 (3.6735)0.965341
0.275 (3.6364)1.409417
0.2778 (3.6)0.052283
0.2806 (3.5644)0.016725
0.2833 (3.5294)1.605788
0.2861 (3.4951)7.08246
0.2889 (3.4615)0.107544
0.2917 (3.4286)1.354278
0.2944 (3.3962)1.166439
0.2972 (3.3645)0.596559
0.3 (3.3333)0.522582
0.3028 (3.3028)0.661809
0.3056 (3.2727)1.12578
0.3083 (3.2432)0.863734
0.3111 (3.2143)0.797993
0.3139 (3.1858)1.358446
0.3167 (3.1579)0.223895
0.3194 (3.1304)0.085736
0.3222 (3.1034)1.264808
0.325 (3.0769)0.247023
0.3278 (3.0508)0.188419
0.3306 (3.0252)0.337802
0.3333 (3)0.043553
0.3361 (2.9752)0.034062
0.3389 (2.9508)0.018071
0.3417 (2.9268)0.344637
0.3444 (2.9032)0.060212
0.3472 (2.88)0.69594
0.35 (2.8571)2.590298
0.3528 (2.8346)1.002245
0.3556 (2.8125)1.35004
0.3583 (2.7907)2.291366
0.3611 (2.7692)2.001674
0.3639 (2.7481)7.119634
0.3667 (2.7273)0.569299
0.3694 (2.7068)0.577886
0.3722 (2.6866)2.447876
0.375 (2.6667)0.716116
0.3778 (2.6471)0.754038
0.3806 (2.6277)4.874199
0.3833 (2.6087)1.824984
0.3861 (2.5899)0.549589
0.3889 (2.5714)1.235879
0.3917 (2.5532)4.102519
0.3944 (2.5352)2.003635
0.3972 (2.5175)0.620427
0.4 (2.5)0.204581
0.4028 (2.4828)0.515653
0.4056 (2.4658)0.019598
0.4083 (2.449)0.154699
0.4111 (2.4324)0.626278
0.4139 (2.4161)0.139812
0.4167 (2.4)0.167326
0.4194 (2.3841)0.084877
0.4222 (2.3684)0.196339
0.425 (2.3529)0.182845
0.4278 (2.3377)0.190421
0.4306 (2.3226)1.683037
0.4333 (2.3077)1.275025
0.4361 (2.293)0.342482
0.4389 (2.2785)1.607396
0.4417 (2.2642)1.564525
0.4444 (2.25)0.621786
0.4472 (2.236)4.467569
0.45 (2.2222)0.658739
0.4528 (2.2086)2.469759
0.4556 (2.1951)10.543687
0.4583 (2.1818)2.885492
0.4611 (2.1687)1.395165
0.4639 (2.1557)1.616309
0.4667 (2.1429)2.382695
0.4694 (2.1302)0.116625
0.4722 (2.1176)14.787816
0.475 (2.1053)0.485626
0.4778 (2.093)2.266653
0.4806 (2.0809)3.693014
0.4833 (2.069)0.066857
0.4861 (2.0571)0.987105
0.4889 (2.0455)0.06478
0.4917 (2.0339)0.528923
0.4944 (2.0225)0.340026
0.4972 (2.0112)0.36196
0.5 (2)0.070405



Parameters (Session):
par1 = 0.5 ; par2 = 1 ; par3 = 1 ; par4 = 12 ;
Parameters (R input):
par1 = 0.5 ; 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')