Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Module--
Title produced by softwareSpectral Analysis
Date of computationThu, 20 Dec 2012 14:32:43 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/20/t1356031973lzojs5j4tbkoewg.htm/, Retrieved Thu, 28 Mar 2024 22:16:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=203050, Retrieved Thu, 28 Mar 2024 22:16:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [(Partial) Autocorrelation Function] [Autocorrelatiefun...] [2012-11-10 16:56:48] [391561951b5d7f721cfaa4f5575ab127]
- R P     [(Partial) Autocorrelation Function] [] [2012-11-24 00:03:24] [74be16979710d4c4e7c6647856088456]
-   P       [(Partial) Autocorrelation Function] [Langetermijntrend...] [2012-11-24 09:07:33] [74be16979710d4c4e7c6647856088456]
- RMP         [Spectral Analysis] [Differentiatie_Cu...] [2012-11-24 09:54:01] [391561951b5d7f721cfaa4f5575ab127]
- RM              [Spectral Analysis] [] [2012-12-20 19:32:43] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
617
614
647
580
614
636
388
356
639
753
611
639
630
586
695
552
619
681
421
307
754
690
644
643
608
651
691
627
634
731
475
337
803
722
590
724
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
706
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858
775
785
1006
789
734
906
532
387
991
841
892
782
811
792
978
773
796
946
594
438
1023
868
791
760
779
852
1001
734
996
869
599
426
1138
1091
830
909




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203050&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203050&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203050&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 time2 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0074 (135)44.562167
0.0148 (67.5)415.933817
0.0222 (45)177.133342
0.0296 (33.75)25.985955
0.037 (27)68.962064
0.0444 (22.5)211.28046
0.0519 (19.2857)58.025079
0.0593 (16.875)690.921461
0.0667 (15)585.426063
0.0741 (13.5)688.179068
0.0815 (12.2727)34956.857406
0.0889 (11.25)5687.65271
0.0963 (10.3846)114.917383
0.1037 (9.6429)982.297356
0.1111 (9)1977.363675
0.1185 (8.4375)3147.514533
0.1259 (7.9412)190.350912
0.1333 (7.5)2010.719454
0.1407 (7.1053)3380.006325
0.1481 (6.75)1089.232785
0.1556 (6.4286)9021.839606
0.163 (6.1364)110700.677645
0.1704 (5.8696)136723.000842
0.1778 (5.625)15735.785636
0.1852 (5.4)898.478243
0.1926 (5.1923)2809.136396
0.2 (5)1921.849317
0.2074 (4.8214)779.280509
0.2148 (4.6552)2606.388482
0.2222 (4.5)1963.960389
0.2296 (4.3548)10714.719976
0.237 (4.2188)10865.85812
0.2444 (4.0909)153198.988043
0.2519 (3.9706)505360.307467
0.2593 (3.8571)9028.661945
0.2667 (3.75)5302.810029
0.2741 (3.6486)30.748147
0.2815 (3.5526)16836.255134
0.2889 (3.4615)1077.024329
0.2963 (3.375)34.131693
0.3037 (3.2927)1696.930587
0.3111 (3.2143)1699.374213
0.3185 (3.1395)24596.06418
0.3259 (3.0682)30111.268669
0.3333 (3)1042178.800736
0.3407 (2.9348)21070.113267
0.3481 (2.8723)143537.989536
0.3556 (2.8125)11865.492458
0.363 (2.7551)5219.398493
0.3704 (2.7)20542.080028
0.3778 (2.6471)3068.155859
0.3852 (2.5962)24152.185342
0.3926 (2.5472)7835.072862
0.4 (2.5)5124.504546
0.4074 (2.4545)9734.871717
0.4148 (2.4107)52136.278143
0.4222 (2.3684)27078.600026
0.4296 (2.3276)10954.265092
0.437 (2.2881)7630.320217
0.4444 (2.25)7400.455203
0.4519 (2.2131)5574.973673
0.4593 (2.1774)2860.564554
0.4667 (2.1429)4670.431652
0.4741 (2.1094)507.172203
0.4815 (2.0769)25324.196389
0.4889 (2.0455)36031.44235
0.4963 (2.0149)51680.464175

\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) & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0074 (135) & 44.562167 \tabularnewline
0.0148 (67.5) & 415.933817 \tabularnewline
0.0222 (45) & 177.133342 \tabularnewline
0.0296 (33.75) & 25.985955 \tabularnewline
0.037 (27) & 68.962064 \tabularnewline
0.0444 (22.5) & 211.28046 \tabularnewline
0.0519 (19.2857) & 58.025079 \tabularnewline
0.0593 (16.875) & 690.921461 \tabularnewline
0.0667 (15) & 585.426063 \tabularnewline
0.0741 (13.5) & 688.179068 \tabularnewline
0.0815 (12.2727) & 34956.857406 \tabularnewline
0.0889 (11.25) & 5687.65271 \tabularnewline
0.0963 (10.3846) & 114.917383 \tabularnewline
0.1037 (9.6429) & 982.297356 \tabularnewline
0.1111 (9) & 1977.363675 \tabularnewline
0.1185 (8.4375) & 3147.514533 \tabularnewline
0.1259 (7.9412) & 190.350912 \tabularnewline
0.1333 (7.5) & 2010.719454 \tabularnewline
0.1407 (7.1053) & 3380.006325 \tabularnewline
0.1481 (6.75) & 1089.232785 \tabularnewline
0.1556 (6.4286) & 9021.839606 \tabularnewline
0.163 (6.1364) & 110700.677645 \tabularnewline
0.1704 (5.8696) & 136723.000842 \tabularnewline
0.1778 (5.625) & 15735.785636 \tabularnewline
0.1852 (5.4) & 898.478243 \tabularnewline
0.1926 (5.1923) & 2809.136396 \tabularnewline
0.2 (5) & 1921.849317 \tabularnewline
0.2074 (4.8214) & 779.280509 \tabularnewline
0.2148 (4.6552) & 2606.388482 \tabularnewline
0.2222 (4.5) & 1963.960389 \tabularnewline
0.2296 (4.3548) & 10714.719976 \tabularnewline
0.237 (4.2188) & 10865.85812 \tabularnewline
0.2444 (4.0909) & 153198.988043 \tabularnewline
0.2519 (3.9706) & 505360.307467 \tabularnewline
0.2593 (3.8571) & 9028.661945 \tabularnewline
0.2667 (3.75) & 5302.810029 \tabularnewline
0.2741 (3.6486) & 30.748147 \tabularnewline
0.2815 (3.5526) & 16836.255134 \tabularnewline
0.2889 (3.4615) & 1077.024329 \tabularnewline
0.2963 (3.375) & 34.131693 \tabularnewline
0.3037 (3.2927) & 1696.930587 \tabularnewline
0.3111 (3.2143) & 1699.374213 \tabularnewline
0.3185 (3.1395) & 24596.06418 \tabularnewline
0.3259 (3.0682) & 30111.268669 \tabularnewline
0.3333 (3) & 1042178.800736 \tabularnewline
0.3407 (2.9348) & 21070.113267 \tabularnewline
0.3481 (2.8723) & 143537.989536 \tabularnewline
0.3556 (2.8125) & 11865.492458 \tabularnewline
0.363 (2.7551) & 5219.398493 \tabularnewline
0.3704 (2.7) & 20542.080028 \tabularnewline
0.3778 (2.6471) & 3068.155859 \tabularnewline
0.3852 (2.5962) & 24152.185342 \tabularnewline
0.3926 (2.5472) & 7835.072862 \tabularnewline
0.4 (2.5) & 5124.504546 \tabularnewline
0.4074 (2.4545) & 9734.871717 \tabularnewline
0.4148 (2.4107) & 52136.278143 \tabularnewline
0.4222 (2.3684) & 27078.600026 \tabularnewline
0.4296 (2.3276) & 10954.265092 \tabularnewline
0.437 (2.2881) & 7630.320217 \tabularnewline
0.4444 (2.25) & 7400.455203 \tabularnewline
0.4519 (2.2131) & 5574.973673 \tabularnewline
0.4593 (2.1774) & 2860.564554 \tabularnewline
0.4667 (2.1429) & 4670.431652 \tabularnewline
0.4741 (2.1094) & 507.172203 \tabularnewline
0.4815 (2.0769) & 25324.196389 \tabularnewline
0.4889 (2.0455) & 36031.44235 \tabularnewline
0.4963 (2.0149) & 51680.464175 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=203050&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]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Frequency (Period)[/C][C]Spectrum[/C][/ROW]
[ROW][C]0.0074 (135)[/C][C]44.562167[/C][/ROW]
[ROW][C]0.0148 (67.5)[/C][C]415.933817[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]177.133342[/C][/ROW]
[ROW][C]0.0296 (33.75)[/C][C]25.985955[/C][/ROW]
[ROW][C]0.037 (27)[/C][C]68.962064[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]211.28046[/C][/ROW]
[ROW][C]0.0519 (19.2857)[/C][C]58.025079[/C][/ROW]
[ROW][C]0.0593 (16.875)[/C][C]690.921461[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]585.426063[/C][/ROW]
[ROW][C]0.0741 (13.5)[/C][C]688.179068[/C][/ROW]
[ROW][C]0.0815 (12.2727)[/C][C]34956.857406[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]5687.65271[/C][/ROW]
[ROW][C]0.0963 (10.3846)[/C][C]114.917383[/C][/ROW]
[ROW][C]0.1037 (9.6429)[/C][C]982.297356[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]1977.363675[/C][/ROW]
[ROW][C]0.1185 (8.4375)[/C][C]3147.514533[/C][/ROW]
[ROW][C]0.1259 (7.9412)[/C][C]190.350912[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]2010.719454[/C][/ROW]
[ROW][C]0.1407 (7.1053)[/C][C]3380.006325[/C][/ROW]
[ROW][C]0.1481 (6.75)[/C][C]1089.232785[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]9021.839606[/C][/ROW]
[ROW][C]0.163 (6.1364)[/C][C]110700.677645[/C][/ROW]
[ROW][C]0.1704 (5.8696)[/C][C]136723.000842[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]15735.785636[/C][/ROW]
[ROW][C]0.1852 (5.4)[/C][C]898.478243[/C][/ROW]
[ROW][C]0.1926 (5.1923)[/C][C]2809.136396[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]1921.849317[/C][/ROW]
[ROW][C]0.2074 (4.8214)[/C][C]779.280509[/C][/ROW]
[ROW][C]0.2148 (4.6552)[/C][C]2606.388482[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]1963.960389[/C][/ROW]
[ROW][C]0.2296 (4.3548)[/C][C]10714.719976[/C][/ROW]
[ROW][C]0.237 (4.2188)[/C][C]10865.85812[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]153198.988043[/C][/ROW]
[ROW][C]0.2519 (3.9706)[/C][C]505360.307467[/C][/ROW]
[ROW][C]0.2593 (3.8571)[/C][C]9028.661945[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]5302.810029[/C][/ROW]
[ROW][C]0.2741 (3.6486)[/C][C]30.748147[/C][/ROW]
[ROW][C]0.2815 (3.5526)[/C][C]16836.255134[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]1077.024329[/C][/ROW]
[ROW][C]0.2963 (3.375)[/C][C]34.131693[/C][/ROW]
[ROW][C]0.3037 (3.2927)[/C][C]1696.930587[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]1699.374213[/C][/ROW]
[ROW][C]0.3185 (3.1395)[/C][C]24596.06418[/C][/ROW]
[ROW][C]0.3259 (3.0682)[/C][C]30111.268669[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]1042178.800736[/C][/ROW]
[ROW][C]0.3407 (2.9348)[/C][C]21070.113267[/C][/ROW]
[ROW][C]0.3481 (2.8723)[/C][C]143537.989536[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]11865.492458[/C][/ROW]
[ROW][C]0.363 (2.7551)[/C][C]5219.398493[/C][/ROW]
[ROW][C]0.3704 (2.7)[/C][C]20542.080028[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]3068.155859[/C][/ROW]
[ROW][C]0.3852 (2.5962)[/C][C]24152.185342[/C][/ROW]
[ROW][C]0.3926 (2.5472)[/C][C]7835.072862[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]5124.504546[/C][/ROW]
[ROW][C]0.4074 (2.4545)[/C][C]9734.871717[/C][/ROW]
[ROW][C]0.4148 (2.4107)[/C][C]52136.278143[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]27078.600026[/C][/ROW]
[ROW][C]0.4296 (2.3276)[/C][C]10954.265092[/C][/ROW]
[ROW][C]0.437 (2.2881)[/C][C]7630.320217[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]7400.455203[/C][/ROW]
[ROW][C]0.4519 (2.2131)[/C][C]5574.973673[/C][/ROW]
[ROW][C]0.4593 (2.1774)[/C][C]2860.564554[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]4670.431652[/C][/ROW]
[ROW][C]0.4741 (2.1094)[/C][C]507.172203[/C][/ROW]
[ROW][C]0.4815 (2.0769)[/C][C]25324.196389[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]36031.44235[/C][/ROW]
[ROW][C]0.4963 (2.0149)[/C][C]51680.464175[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=203050&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=203050&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)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0074 (135)44.562167
0.0148 (67.5)415.933817
0.0222 (45)177.133342
0.0296 (33.75)25.985955
0.037 (27)68.962064
0.0444 (22.5)211.28046
0.0519 (19.2857)58.025079
0.0593 (16.875)690.921461
0.0667 (15)585.426063
0.0741 (13.5)688.179068
0.0815 (12.2727)34956.857406
0.0889 (11.25)5687.65271
0.0963 (10.3846)114.917383
0.1037 (9.6429)982.297356
0.1111 (9)1977.363675
0.1185 (8.4375)3147.514533
0.1259 (7.9412)190.350912
0.1333 (7.5)2010.719454
0.1407 (7.1053)3380.006325
0.1481 (6.75)1089.232785
0.1556 (6.4286)9021.839606
0.163 (6.1364)110700.677645
0.1704 (5.8696)136723.000842
0.1778 (5.625)15735.785636
0.1852 (5.4)898.478243
0.1926 (5.1923)2809.136396
0.2 (5)1921.849317
0.2074 (4.8214)779.280509
0.2148 (4.6552)2606.388482
0.2222 (4.5)1963.960389
0.2296 (4.3548)10714.719976
0.237 (4.2188)10865.85812
0.2444 (4.0909)153198.988043
0.2519 (3.9706)505360.307467
0.2593 (3.8571)9028.661945
0.2667 (3.75)5302.810029
0.2741 (3.6486)30.748147
0.2815 (3.5526)16836.255134
0.2889 (3.4615)1077.024329
0.2963 (3.375)34.131693
0.3037 (3.2927)1696.930587
0.3111 (3.2143)1699.374213
0.3185 (3.1395)24596.06418
0.3259 (3.0682)30111.268669
0.3333 (3)1042178.800736
0.3407 (2.9348)21070.113267
0.3481 (2.8723)143537.989536
0.3556 (2.8125)11865.492458
0.363 (2.7551)5219.398493
0.3704 (2.7)20542.080028
0.3778 (2.6471)3068.155859
0.3852 (2.5962)24152.185342
0.3926 (2.5472)7835.072862
0.4 (2.5)5124.504546
0.4074 (2.4545)9734.871717
0.4148 (2.4107)52136.278143
0.4222 (2.3684)27078.600026
0.4296 (2.3276)10954.265092
0.437 (2.2881)7630.320217
0.4444 (2.25)7400.455203
0.4519 (2.2131)5574.973673
0.4593 (2.1774)2860.564554
0.4667 (2.1429)4670.431652
0.4741 (2.1094)507.172203
0.4815 (2.0769)25324.196389
0.4889 (2.0455)36031.44235
0.4963 (2.0149)51680.464175



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')