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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 computationWed, 22 Dec 2010 13:23:09 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/22/t1293024054g0jkra89gqatco4.htm/, Retrieved Mon, 06 May 2024 07:16:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114195, Retrieved Mon, 06 May 2024 07:16:24 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact127
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]
- RMP   [Spectral Analysis] [Unemployment] [2010-11-29 09:21:38] [b98453cac15ba1066b407e146608df68]
-    D    [Spectral Analysis] [Workshop 6 'Aanta...] [2010-12-14 17:12:41] [40c8b935cbad1b0be3c22a481f9723f7]
-           [Spectral Analysis] [] [2010-12-16 01:28:12] [bcc4ad4a6c0f95d5b548de29638ac6c2]
-   PD          [Spectral Analysis] [] [2010-12-22 13:23:09] [29eeba0e6ce2cd83aa315a4a7ff8c4aa] [Current]
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Dataseries X:
377
370
358
357
349
348
369
381
368
361
351
351
358
354
347
345
343
340
362
370
373
371
354
357
363
364
363
358
357
357
380
378
376
380
379
384
392
394
392
396
392
396
419
421
420
418
410
418
426
428
430
424
423
427
441
449
452
462
455
461
461
463
462
456
455
456
472
472
471
465
459
465
468
467
463
460
462
461
476
476
471
453
443
442
444
438
427
424
416
406
431
434
418
412
404
409
412
406
398
397
385
390
413
413
401
397
397
409
419
424
428
430
424
433
456
459
446
441
439
454
460
457
451
444
437
443
471
469
454
444
436




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114195&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114195&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114195&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0083 (120)102.342375
0.0167 (60)174.308542
0.025 (40)112.719333
0.0333 (30)34.855894
0.0417 (24)22.011384
0.05 (20)82.624583
0.0583 (17.1429)129.91905
0.0667 (15)9.837305
0.075 (13.3333)3.449464
0.0833 (12)3.452554
0.0917 (10.9091)5.828602
0.1 (10)21.657372
0.1083 (9.2308)25.839328
0.1167 (8.5714)33.353862
0.125 (8)3.603654
0.1333 (7.5)125.087393
0.1417 (7.0588)79.838663
0.15 (6.6667)0.447382
0.1583 (6.3158)9.781698
0.1667 (6)11.971312
0.175 (5.7143)19.547408
0.1833 (5.4545)4.209704
0.1917 (5.2174)1.476715
0.2 (5)23.894953
0.2083 (4.8)80.996395
0.2167 (4.6154)96.370496
0.225 (4.4444)61.704887
0.2333 (4.2857)14.405533
0.2417 (4.1379)7.746427
0.25 (4)5.5696
0.2583 (3.871)35.151341
0.2667 (3.75)59.931903
0.275 (3.6364)31.937736
0.2833 (3.5294)26.396478
0.2917 (3.4286)5.689315
0.3 (3.3333)32.006305
0.3083 (3.2432)6.839395
0.3167 (3.1579)19.027282
0.325 (3.0769)2.429305
0.3333 (3)5.742824
0.3417 (2.9268)36.022094
0.35 (2.8571)66.423395
0.3583 (2.7907)48.802964
0.3667 (2.7273)85.22923
0.375 (2.6667)85.430708
0.3833 (2.6087)35.384521
0.3917 (2.5532)17.961102
0.4 (2.5)6.609447
0.4083 (2.449)2.418361
0.4167 (2.4)0.781138
0.425 (2.3529)8.033233
0.4333 (2.3077)43.929867
0.4417 (2.2642)57.01715
0.45 (2.2222)67.203088
0.4583 (2.1818)1.077032
0.4667 (2.1429)10.647665
0.475 (2.1053)29.980935
0.4833 (2.069)44.678144
0.4917 (2.0339)2.033085
0.5 (2)0.906355

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 1 \tabularnewline
Degree of seasonal differencing (D) & 1 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0083 (120) & 102.342375 \tabularnewline
0.0167 (60) & 174.308542 \tabularnewline
0.025 (40) & 112.719333 \tabularnewline
0.0333 (30) & 34.855894 \tabularnewline
0.0417 (24) & 22.011384 \tabularnewline
0.05 (20) & 82.624583 \tabularnewline
0.0583 (17.1429) & 129.91905 \tabularnewline
0.0667 (15) & 9.837305 \tabularnewline
0.075 (13.3333) & 3.449464 \tabularnewline
0.0833 (12) & 3.452554 \tabularnewline
0.0917 (10.9091) & 5.828602 \tabularnewline
0.1 (10) & 21.657372 \tabularnewline
0.1083 (9.2308) & 25.839328 \tabularnewline
0.1167 (8.5714) & 33.353862 \tabularnewline
0.125 (8) & 3.603654 \tabularnewline
0.1333 (7.5) & 125.087393 \tabularnewline
0.1417 (7.0588) & 79.838663 \tabularnewline
0.15 (6.6667) & 0.447382 \tabularnewline
0.1583 (6.3158) & 9.781698 \tabularnewline
0.1667 (6) & 11.971312 \tabularnewline
0.175 (5.7143) & 19.547408 \tabularnewline
0.1833 (5.4545) & 4.209704 \tabularnewline
0.1917 (5.2174) & 1.476715 \tabularnewline
0.2 (5) & 23.894953 \tabularnewline
0.2083 (4.8) & 80.996395 \tabularnewline
0.2167 (4.6154) & 96.370496 \tabularnewline
0.225 (4.4444) & 61.704887 \tabularnewline
0.2333 (4.2857) & 14.405533 \tabularnewline
0.2417 (4.1379) & 7.746427 \tabularnewline
0.25 (4) & 5.5696 \tabularnewline
0.2583 (3.871) & 35.151341 \tabularnewline
0.2667 (3.75) & 59.931903 \tabularnewline
0.275 (3.6364) & 31.937736 \tabularnewline
0.2833 (3.5294) & 26.396478 \tabularnewline
0.2917 (3.4286) & 5.689315 \tabularnewline
0.3 (3.3333) & 32.006305 \tabularnewline
0.3083 (3.2432) & 6.839395 \tabularnewline
0.3167 (3.1579) & 19.027282 \tabularnewline
0.325 (3.0769) & 2.429305 \tabularnewline
0.3333 (3) & 5.742824 \tabularnewline
0.3417 (2.9268) & 36.022094 \tabularnewline
0.35 (2.8571) & 66.423395 \tabularnewline
0.3583 (2.7907) & 48.802964 \tabularnewline
0.3667 (2.7273) & 85.22923 \tabularnewline
0.375 (2.6667) & 85.430708 \tabularnewline
0.3833 (2.6087) & 35.384521 \tabularnewline
0.3917 (2.5532) & 17.961102 \tabularnewline
0.4 (2.5) & 6.609447 \tabularnewline
0.4083 (2.449) & 2.418361 \tabularnewline
0.4167 (2.4) & 0.781138 \tabularnewline
0.425 (2.3529) & 8.033233 \tabularnewline
0.4333 (2.3077) & 43.929867 \tabularnewline
0.4417 (2.2642) & 57.01715 \tabularnewline
0.45 (2.2222) & 67.203088 \tabularnewline
0.4583 (2.1818) & 1.077032 \tabularnewline
0.4667 (2.1429) & 10.647665 \tabularnewline
0.475 (2.1053) & 29.980935 \tabularnewline
0.4833 (2.069) & 44.678144 \tabularnewline
0.4917 (2.0339) & 2.033085 \tabularnewline
0.5 (2) & 0.906355 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114195&T=1

[TABLE]
[ROW][C]Raw Periodogram[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda)[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d)[/C][C]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D)[/C][C]1[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0083 (120)[/C][C]102.342375[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]174.308542[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]112.719333[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]34.855894[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]22.011384[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]82.624583[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]129.91905[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]9.837305[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]3.449464[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]3.452554[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]5.828602[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]21.657372[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]25.839328[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]33.353862[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]3.603654[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]125.087393[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]79.838663[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]0.447382[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]9.781698[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]11.971312[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]19.547408[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]4.209704[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]1.476715[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]23.894953[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]80.996395[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]96.370496[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]61.704887[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]14.405533[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]7.746427[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]5.5696[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]35.151341[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]59.931903[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]31.937736[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]26.396478[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]5.689315[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]32.006305[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]6.839395[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]19.027282[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]2.429305[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]5.742824[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]36.022094[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]66.423395[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]48.802964[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]85.22923[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]85.430708[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]35.384521[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]17.961102[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]6.609447[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]2.418361[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]0.781138[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]8.033233[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]43.929867[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]57.01715[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]67.203088[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]1.077032[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]10.647665[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]29.980935[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]44.678144[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]2.033085[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.906355[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114195&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114195&T=1

As an alternative you can also use a QR Code:  

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

Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0083 (120)102.342375
0.0167 (60)174.308542
0.025 (40)112.719333
0.0333 (30)34.855894
0.0417 (24)22.011384
0.05 (20)82.624583
0.0583 (17.1429)129.91905
0.0667 (15)9.837305
0.075 (13.3333)3.449464
0.0833 (12)3.452554
0.0917 (10.9091)5.828602
0.1 (10)21.657372
0.1083 (9.2308)25.839328
0.1167 (8.5714)33.353862
0.125 (8)3.603654
0.1333 (7.5)125.087393
0.1417 (7.0588)79.838663
0.15 (6.6667)0.447382
0.1583 (6.3158)9.781698
0.1667 (6)11.971312
0.175 (5.7143)19.547408
0.1833 (5.4545)4.209704
0.1917 (5.2174)1.476715
0.2 (5)23.894953
0.2083 (4.8)80.996395
0.2167 (4.6154)96.370496
0.225 (4.4444)61.704887
0.2333 (4.2857)14.405533
0.2417 (4.1379)7.746427
0.25 (4)5.5696
0.2583 (3.871)35.151341
0.2667 (3.75)59.931903
0.275 (3.6364)31.937736
0.2833 (3.5294)26.396478
0.2917 (3.4286)5.689315
0.3 (3.3333)32.006305
0.3083 (3.2432)6.839395
0.3167 (3.1579)19.027282
0.325 (3.0769)2.429305
0.3333 (3)5.742824
0.3417 (2.9268)36.022094
0.35 (2.8571)66.423395
0.3583 (2.7907)48.802964
0.3667 (2.7273)85.22923
0.375 (2.6667)85.430708
0.3833 (2.6087)35.384521
0.3917 (2.5532)17.961102
0.4 (2.5)6.609447
0.4083 (2.449)2.418361
0.4167 (2.4)0.781138
0.425 (2.3529)8.033233
0.4333 (2.3077)43.929867
0.4417 (2.2642)57.01715
0.45 (2.2222)67.203088
0.4583 (2.1818)1.077032
0.4667 (2.1429)10.647665
0.475 (2.1053)29.980935
0.4833 (2.069)44.678144
0.4917 (2.0339)2.033085
0.5 (2)0.906355



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