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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_spectrum.wasp
Title produced by softwareSpectral Analysis
Date of computationTue, 09 Dec 2008 09:08:47 -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/t1228839019psrgcqn742cjruz.htm/, Retrieved Sun, 19 May 2024 12:41:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31551, Retrieved Sun, 19 May 2024 12:41:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact228

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Spectral Analysis] [] [2008-12-09 16:08:47] [e02910eed3830f1815f587e12f46cbdb] [Current]
Feedback Forum
2008-12-10 13:36:15 [407693b66d7f2e0b350979005057872d] [reply] 
Dit antwoord is volledig correct. We zien bij de autocorrelatie een langzaam dalend patroon dat wijst op een lange termijn trend. We hebben hier voor d=0 en D=0. We gaan de tijdreeks stationair maken. Hier hebben we d gelijkgesteld an1 en D gelijkgesteld aan 0. We kunnen nog wel seizonaliteit opsporen maar we zien een veel minder dalend verloop dan in het begin.
Als we d gelijkstellen aan 1 en D aan 1 dan zien we dat er geen seizonaliteit meer is en de lange termijn trend is ook weggewerkt. We hebben de tijdreeks stationair gemaakt

2008-12-13 11:10:10 [Nicolaj Wuyts] [reply] 
Deze stap is correct uitgevoerd. Bij de ACF kan je misschien best 60 lags laten weergeven dan 35
2008-12-14 14:50:02 [Toon Wouters] [reply] 
Bij de cumulative periodogram kon je nog besluiten dat er nog golfbewegingen te verklaren zijn omdat ze buiten het 95% betrouwbaarheidsinterval liggen. En deze mogelijk te verklaren zijn via de ARMA-processen. Indien de curve boven het interval ligt, kan verklaard worden door RA-processen en onder de curve via MA-processen. Maar dit is zeker niet optimaal.
2008-12-15 17:51:31 [Käthe Vanderheggen] [reply] 
We merken inderdaad een verbetering op maar toch ziet de reeks er niet uit als een diagonaal en ligt nog deels buiten het betrouwbaarheidsinterval. Dit wijst erop dat niet alles kan worden verklaard. Er is een zeer grote kans dat we dit in de ARMA processen zullen kunnen verklaren. Bij het cumulatief periodogram geldt de volgende vuistregel: indien het cumulatief periodogram van de tijdreeks een afwijking vertoont aan de bovenkant van de diagonaal, dan is het zeer waarschijnlijk dat we een AR proces zullen hebben. Dit is hier het geval. Wanneer we echter een afwijking onderaan hebben, duidt dit op een MA proces.
2008-12-16 20:14:47 [Laura Reussens] [reply] 
Zoals de student zegt, zijn zowel de LT-trend als de seizoenaliteit volledig verdwenen. We kunnen dus zeggen dat de tijdreeks stationair is.
Maar, wanneer we echter niets meer zouden kunnen verklaren, zou het cumulatief periodogram een diagonaal moeten vormen die tussen de betrouwbaarheidsintervallen blijft. Dit is hier niet het geval. Aangezien het periodogram een afwijking vertoond langs de bovenkant van de intervallen, kunnen we de voorspelbaarheid die zich nog steeds in de tijdreeks aanwezig is, verklaren aan de hand van een AR-proces.

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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31551&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31551&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31551&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 time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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=31551&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=31551&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31551&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')