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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 computationTue, 09 Dec 2008 08:59:06 -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/t1228838378pndm8kmwmprlky7.htm/, Retrieved Fri, 17 May 2024 01:42:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31541, Retrieved Fri, 17 May 2024 01:42:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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] [3] [2008-12-09 15:59:06] [3452c99afdd85d4fde81272403cd85da] [Current]
Feedback Forum
2008-12-15 14:05:37 [Jonas Scheltjens] [reply] 
De student heeft enkel de link opgenomen in het document.
Wanneer we het raw periodogram beter bekijken zien we duidelijk dat er geen lange termijn trend aanwezig is. Dit wordt ons ook getoond in de cumulative periodogram. We nemen hier duidelijk waar dat er hier geen sprake is van een steil begin in de grafiek. We kunnen er dus met zekerheid vanuit gaan de keuze om de parameter d in te stellen op 1 goed is. We controleren nu parameter D. We zoeken dus naar seizoenaliteit. Uit het raw periodogram blijkt dat de seizoenaliteit sterk verminderd is ten opzichte van de eerste grafiek uit step 2. Ook dit zien we aan het cumulative periodogram. Het trapsgewijs verloop is duidelijk sterk verminderd. Toch kunnen we zien dat er nog steeds -een zeer lichte vorm- van het trapsgewijs verloop over blijft. Indien we de D veranderen en zetten we deze op 2 blijkt dat dit verergert. Bijgevolg is de parameter D het best ingesteld op 2. Voor extra uitleg: kijk naar de oplossingen voor Step 2, aangezien ik dit daar ook al heb besproken, daar dit 2 overlappende Steps zijn.
2008-12-15 14:06:32 [Jonas Scheltjens] [reply] 
hier ook de vermelding voor step 4, aangezien er geen link werd aangemaakt.

De Autocorrelation en de Partiële Autocorrelatie dienen berekend te worden aangezien we via deze methode om de ARMA processen kunnen detecteren door de juiste lambda waarde, de graad van de niet-seizoenale differentiatie d en de graad van de seizoenale differentiatie D in te vullen. Dit wil dus zeggen dat we met een stationaire reeks te werk kunnen gaan. Hierdoor zijn we in staat de waarden voor de parameters p, P, q en Q te bepalen.

De Autocorrelation-grafiek vertoont sterke gelijkenissen met de theoretische AR patronen. Aangezien we ook de orde van de het AR proces willen weten moeten we kijken naar de partiële correlatie. Hier is het de bedoeling dat we zien hoeveel verticale lijnen er buiten het betrouwbaarheidsinterval van de partiële autocorrelatie vallen in het eerste deel. We zien dat indien we een beetje “trekken” aan de 3de verticale lijn, we een orde 3 bekomen. We kunnen dus stellen dat de parameter p de waarde 3 heeft, zodanig dat we een over een AR 3 proces beschikken. Vervolgens gaan we de parameter P bepalen. Dit betekent dat we moeten onderzoeken of er al dan niet een SAR proces waar te nemen valt en aldus te kijken of er zich enige seizoenalteit voordoet en dus houden we hierbij vooral de lags 12,24,36 in het oog. We kunnen hier echter geen patroon in herkennen en dus is er hier geen sprake van een seizoenaal AR proces (SAR), waaruit volgt dat we de parameter P gelijk moeten stellen aan 0.
We moeten ook nakijken of er een MA proces te bespeuren valt. Dit houdt in dat we de theoretische MA patronen moeten vergelijken met de partiële autocorrelatie grafiek. In deze reeks kunnen we zien dat zich geen MA patroon voordoet in de partiële autocorrelatie grafiek, wat als gevolg meebrengt dat we de parameter q de waarde 0 toekennen. We moeten ook de parameter Q bepalen en dus gaan we kijken naar seizoenaliteit. Ook hier zijn de lags 12,24,36.. het meest belangrijk. Wat we kunnen waarnemen is de daling van de seizoenale partiële autocorrelatie coëfficiënten op deze lags. De orde van de SMA kunnen we zien aan het aantal significante seizoenale autocorrelatiecoëfficiënten. Hier is er slechts 1 seizoenale autocorrelatie coëfficiënt die significant verschillend is aanwezig is. We hebben hier dus te maken met een SMA 1 proces.
De waarden voor de processen zijn dus:
p=3; P=0; q=0; Q=1
2008-12-16 17:15:49 [Dave Bellekens] [reply] 
Je geeft enkel de link en de parameters, daardoor is het niet mogelijk om gerichte feedback te geven, aangezien je nie kan zien waar je dingen goed of fout interpreteert.

Post a new message

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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31541&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31541&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






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=31541&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=31541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31541&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)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


Figures (Output of Computation)

Input Parameters & R Code

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')