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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 computationMon, 05 Dec 2011 12:25:59 -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/2011/Dec/05/t1323106067d74uatmvw0trp62.htm/, Retrieved Fri, 01 Nov 2024 00:59:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151094, Retrieved Fri, 01 Nov 2024 00:59:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [WS9 VRM] [2011-12-04 11:55:08] [abc1cbe561c2c4615f632bb3153b1275]
- RMP   [Spectral Analysis] [WS9 spectrum] [2011-12-04 12:49:46] [abc1cbe561c2c4615f632bb3153b1275]
-   PD      [Spectral Analysis] [WS 9 - spectral a...] [2011-12-05 17:25:59] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataseries X:
23187
14727
43080
32519
39657
33614
28671
34243
27336
22916
24537
26128
22602
15744
41086
39690
43129
37863
35953
29133
24693
22205
21725
27192
21790
13253
37702
30364
32609
30212
29965
28352
25814
22414
20506
28806
22228
13971
36845
35338
35022
34777
26887
23970
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835
20205
17789
20520
22518
15572
11509
25447
24090
27786
26195
20516
22759
19028
16971
20036
22485
18730
14538
27561
25985
34670
32066
27186
29586
21359
21553
19573
24256
22380




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151094&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151094&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151094&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'Gwilym Jenkins' @ jenkins.wessa.net







Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)0
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0074 (135)0.000115
0.0148 (67.5)0.00039
0.0222 (45)0.001902
0.0296 (33.75)0.005702
0.037 (27)0.00984
0.0444 (22.5)0.015523
0.0519 (19.2857)0.003545
0.0593 (16.875)0.000663
0.0667 (15)0.001134
0.0741 (13.5)0.00342
0.0815 (12.2727)0.000367
0.0889 (11.25)0.000433
0.0963 (10.3846)0.000527
0.1037 (9.6429)0.00167
0.1111 (9)0.004183
0.1185 (8.4375)0.024878
0.1259 (7.9412)0.035414
0.1333 (7.5)0.009475
0.1407 (7.1053)0.018836
0.1481 (6.75)0.005288
0.1556 (6.4286)0.000574
0.163 (6.1364)0.001211
0.1704 (5.8696)0.000142
0.1778 (5.625)0.000655
0.1852 (5.4)0.000542
0.1926 (5.1923)0.009055
0.2 (5)0.000793
0.2074 (4.8214)0.066739
0.2148 (4.6552)0.008859
0.2222 (4.5)0.017318
0.2296 (4.3548)0.006941
0.237 (4.2188)0.02125
0.2444 (4.0909)0.002002
0.2519 (3.9706)0.001797
0.2593 (3.8571)0.00862
0.2667 (3.75)0.018277
0.2741 (3.6486)0.00164
0.2815 (3.5526)0.015668
0.2889 (3.4615)0.004277
0.2963 (3.375)0.0061
0.3037 (3.2927)0.00038
0.3111 (3.2143)0.002769
0.3185 (3.1395)0.01667
0.3259 (3.0682)0.000796
0.3333 (3)0.003302
0.3407 (2.9348)0.009628
0.3481 (2.8723)0.237224
0.3556 (2.8125)0.006581
0.363 (2.7551)0.001216
0.3704 (2.7)0.006446
0.3778 (2.6471)0.033875
0.3852 (2.5962)0.032004
0.3926 (2.5472)0.031035
0.4 (2.5)0.040441
0.4074 (2.4545)0.01397
0.4148 (2.4107)0.000556
0.4222 (2.3684)0.002172
0.4296 (2.3276)0.048263
0.437 (2.2881)0.022512
0.4444 (2.25)0.038826
0.4519 (2.2131)0.042329
0.4593 (2.1774)0.076892
0.4667 (2.1429)0.008034
0.4741 (2.1094)0.090397
0.4815 (2.0769)0.085004
0.4889 (2.0455)0.028575
0.4963 (2.0149)0.000815

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 0 \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
0.0074 (135) & 0.000115 \tabularnewline
0.0148 (67.5) & 0.00039 \tabularnewline
0.0222 (45) & 0.001902 \tabularnewline
0.0296 (33.75) & 0.005702 \tabularnewline
0.037 (27) & 0.00984 \tabularnewline
0.0444 (22.5) & 0.015523 \tabularnewline
0.0519 (19.2857) & 0.003545 \tabularnewline
0.0593 (16.875) & 0.000663 \tabularnewline
0.0667 (15) & 0.001134 \tabularnewline
0.0741 (13.5) & 0.00342 \tabularnewline
0.0815 (12.2727) & 0.000367 \tabularnewline
0.0889 (11.25) & 0.000433 \tabularnewline
0.0963 (10.3846) & 0.000527 \tabularnewline
0.1037 (9.6429) & 0.00167 \tabularnewline
0.1111 (9) & 0.004183 \tabularnewline
0.1185 (8.4375) & 0.024878 \tabularnewline
0.1259 (7.9412) & 0.035414 \tabularnewline
0.1333 (7.5) & 0.009475 \tabularnewline
0.1407 (7.1053) & 0.018836 \tabularnewline
0.1481 (6.75) & 0.005288 \tabularnewline
0.1556 (6.4286) & 0.000574 \tabularnewline
0.163 (6.1364) & 0.001211 \tabularnewline
0.1704 (5.8696) & 0.000142 \tabularnewline
0.1778 (5.625) & 0.000655 \tabularnewline
0.1852 (5.4) & 0.000542 \tabularnewline
0.1926 (5.1923) & 0.009055 \tabularnewline
0.2 (5) & 0.000793 \tabularnewline
0.2074 (4.8214) & 0.066739 \tabularnewline
0.2148 (4.6552) & 0.008859 \tabularnewline
0.2222 (4.5) & 0.017318 \tabularnewline
0.2296 (4.3548) & 0.006941 \tabularnewline
0.237 (4.2188) & 0.02125 \tabularnewline
0.2444 (4.0909) & 0.002002 \tabularnewline
0.2519 (3.9706) & 0.001797 \tabularnewline
0.2593 (3.8571) & 0.00862 \tabularnewline
0.2667 (3.75) & 0.018277 \tabularnewline
0.2741 (3.6486) & 0.00164 \tabularnewline
0.2815 (3.5526) & 0.015668 \tabularnewline
0.2889 (3.4615) & 0.004277 \tabularnewline
0.2963 (3.375) & 0.0061 \tabularnewline
0.3037 (3.2927) & 0.00038 \tabularnewline
0.3111 (3.2143) & 0.002769 \tabularnewline
0.3185 (3.1395) & 0.01667 \tabularnewline
0.3259 (3.0682) & 0.000796 \tabularnewline
0.3333 (3) & 0.003302 \tabularnewline
0.3407 (2.9348) & 0.009628 \tabularnewline
0.3481 (2.8723) & 0.237224 \tabularnewline
0.3556 (2.8125) & 0.006581 \tabularnewline
0.363 (2.7551) & 0.001216 \tabularnewline
0.3704 (2.7) & 0.006446 \tabularnewline
0.3778 (2.6471) & 0.033875 \tabularnewline
0.3852 (2.5962) & 0.032004 \tabularnewline
0.3926 (2.5472) & 0.031035 \tabularnewline
0.4 (2.5) & 0.040441 \tabularnewline
0.4074 (2.4545) & 0.01397 \tabularnewline
0.4148 (2.4107) & 0.000556 \tabularnewline
0.4222 (2.3684) & 0.002172 \tabularnewline
0.4296 (2.3276) & 0.048263 \tabularnewline
0.437 (2.2881) & 0.022512 \tabularnewline
0.4444 (2.25) & 0.038826 \tabularnewline
0.4519 (2.2131) & 0.042329 \tabularnewline
0.4593 (2.1774) & 0.076892 \tabularnewline
0.4667 (2.1429) & 0.008034 \tabularnewline
0.4741 (2.1094) & 0.090397 \tabularnewline
0.4815 (2.0769) & 0.085004 \tabularnewline
0.4889 (2.0455) & 0.028575 \tabularnewline
0.4963 (2.0149) & 0.000815 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151094&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[/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]0.0074 (135)[/C][C]0.000115[/C][/ROW]
[ROW][C]0.0148 (67.5)[/C][C]0.00039[/C][/ROW]
[ROW][C]0.0222 (45)[/C][C]0.001902[/C][/ROW]
[ROW][C]0.0296 (33.75)[/C][C]0.005702[/C][/ROW]
[ROW][C]0.037 (27)[/C][C]0.00984[/C][/ROW]
[ROW][C]0.0444 (22.5)[/C][C]0.015523[/C][/ROW]
[ROW][C]0.0519 (19.2857)[/C][C]0.003545[/C][/ROW]
[ROW][C]0.0593 (16.875)[/C][C]0.000663[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]0.001134[/C][/ROW]
[ROW][C]0.0741 (13.5)[/C][C]0.00342[/C][/ROW]
[ROW][C]0.0815 (12.2727)[/C][C]0.000367[/C][/ROW]
[ROW][C]0.0889 (11.25)[/C][C]0.000433[/C][/ROW]
[ROW][C]0.0963 (10.3846)[/C][C]0.000527[/C][/ROW]
[ROW][C]0.1037 (9.6429)[/C][C]0.00167[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]0.004183[/C][/ROW]
[ROW][C]0.1185 (8.4375)[/C][C]0.024878[/C][/ROW]
[ROW][C]0.1259 (7.9412)[/C][C]0.035414[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]0.009475[/C][/ROW]
[ROW][C]0.1407 (7.1053)[/C][C]0.018836[/C][/ROW]
[ROW][C]0.1481 (6.75)[/C][C]0.005288[/C][/ROW]
[ROW][C]0.1556 (6.4286)[/C][C]0.000574[/C][/ROW]
[ROW][C]0.163 (6.1364)[/C][C]0.001211[/C][/ROW]
[ROW][C]0.1704 (5.8696)[/C][C]0.000142[/C][/ROW]
[ROW][C]0.1778 (5.625)[/C][C]0.000655[/C][/ROW]
[ROW][C]0.1852 (5.4)[/C][C]0.000542[/C][/ROW]
[ROW][C]0.1926 (5.1923)[/C][C]0.009055[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]0.000793[/C][/ROW]
[ROW][C]0.2074 (4.8214)[/C][C]0.066739[/C][/ROW]
[ROW][C]0.2148 (4.6552)[/C][C]0.008859[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]0.017318[/C][/ROW]
[ROW][C]0.2296 (4.3548)[/C][C]0.006941[/C][/ROW]
[ROW][C]0.237 (4.2188)[/C][C]0.02125[/C][/ROW]
[ROW][C]0.2444 (4.0909)[/C][C]0.002002[/C][/ROW]
[ROW][C]0.2519 (3.9706)[/C][C]0.001797[/C][/ROW]
[ROW][C]0.2593 (3.8571)[/C][C]0.00862[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]0.018277[/C][/ROW]
[ROW][C]0.2741 (3.6486)[/C][C]0.00164[/C][/ROW]
[ROW][C]0.2815 (3.5526)[/C][C]0.015668[/C][/ROW]
[ROW][C]0.2889 (3.4615)[/C][C]0.004277[/C][/ROW]
[ROW][C]0.2963 (3.375)[/C][C]0.0061[/C][/ROW]
[ROW][C]0.3037 (3.2927)[/C][C]0.00038[/C][/ROW]
[ROW][C]0.3111 (3.2143)[/C][C]0.002769[/C][/ROW]
[ROW][C]0.3185 (3.1395)[/C][C]0.01667[/C][/ROW]
[ROW][C]0.3259 (3.0682)[/C][C]0.000796[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.003302[/C][/ROW]
[ROW][C]0.3407 (2.9348)[/C][C]0.009628[/C][/ROW]
[ROW][C]0.3481 (2.8723)[/C][C]0.237224[/C][/ROW]
[ROW][C]0.3556 (2.8125)[/C][C]0.006581[/C][/ROW]
[ROW][C]0.363 (2.7551)[/C][C]0.001216[/C][/ROW]
[ROW][C]0.3704 (2.7)[/C][C]0.006446[/C][/ROW]
[ROW][C]0.3778 (2.6471)[/C][C]0.033875[/C][/ROW]
[ROW][C]0.3852 (2.5962)[/C][C]0.032004[/C][/ROW]
[ROW][C]0.3926 (2.5472)[/C][C]0.031035[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]0.040441[/C][/ROW]
[ROW][C]0.4074 (2.4545)[/C][C]0.01397[/C][/ROW]
[ROW][C]0.4148 (2.4107)[/C][C]0.000556[/C][/ROW]
[ROW][C]0.4222 (2.3684)[/C][C]0.002172[/C][/ROW]
[ROW][C]0.4296 (2.3276)[/C][C]0.048263[/C][/ROW]
[ROW][C]0.437 (2.2881)[/C][C]0.022512[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]0.038826[/C][/ROW]
[ROW][C]0.4519 (2.2131)[/C][C]0.042329[/C][/ROW]
[ROW][C]0.4593 (2.1774)[/C][C]0.076892[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]0.008034[/C][/ROW]
[ROW][C]0.4741 (2.1094)[/C][C]0.090397[/C][/ROW]
[ROW][C]0.4815 (2.0769)[/C][C]0.085004[/C][/ROW]
[ROW][C]0.4889 (2.0455)[/C][C]0.028575[/C][/ROW]
[ROW][C]0.4963 (2.0149)[/C][C]0.000815[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151094&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151094&T=1

As an alternative you can also use a QR Code:  

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

Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)0
Degree of non-seasonal differencing (d)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0074 (135)0.000115
0.0148 (67.5)0.00039
0.0222 (45)0.001902
0.0296 (33.75)0.005702
0.037 (27)0.00984
0.0444 (22.5)0.015523
0.0519 (19.2857)0.003545
0.0593 (16.875)0.000663
0.0667 (15)0.001134
0.0741 (13.5)0.00342
0.0815 (12.2727)0.000367
0.0889 (11.25)0.000433
0.0963 (10.3846)0.000527
0.1037 (9.6429)0.00167
0.1111 (9)0.004183
0.1185 (8.4375)0.024878
0.1259 (7.9412)0.035414
0.1333 (7.5)0.009475
0.1407 (7.1053)0.018836
0.1481 (6.75)0.005288
0.1556 (6.4286)0.000574
0.163 (6.1364)0.001211
0.1704 (5.8696)0.000142
0.1778 (5.625)0.000655
0.1852 (5.4)0.000542
0.1926 (5.1923)0.009055
0.2 (5)0.000793
0.2074 (4.8214)0.066739
0.2148 (4.6552)0.008859
0.2222 (4.5)0.017318
0.2296 (4.3548)0.006941
0.237 (4.2188)0.02125
0.2444 (4.0909)0.002002
0.2519 (3.9706)0.001797
0.2593 (3.8571)0.00862
0.2667 (3.75)0.018277
0.2741 (3.6486)0.00164
0.2815 (3.5526)0.015668
0.2889 (3.4615)0.004277
0.2963 (3.375)0.0061
0.3037 (3.2927)0.00038
0.3111 (3.2143)0.002769
0.3185 (3.1395)0.01667
0.3259 (3.0682)0.000796
0.3333 (3)0.003302
0.3407 (2.9348)0.009628
0.3481 (2.8723)0.237224
0.3556 (2.8125)0.006581
0.363 (2.7551)0.001216
0.3704 (2.7)0.006446
0.3778 (2.6471)0.033875
0.3852 (2.5962)0.032004
0.3926 (2.5472)0.031035
0.4 (2.5)0.040441
0.4074 (2.4545)0.01397
0.4148 (2.4107)0.000556
0.4222 (2.3684)0.002172
0.4296 (2.3276)0.048263
0.437 (2.2881)0.022512
0.4444 (2.25)0.038826
0.4519 (2.2131)0.042329
0.4593 (2.1774)0.076892
0.4667 (2.1429)0.008034
0.4741 (2.1094)0.090397
0.4815 (2.0769)0.085004
0.4889 (2.0455)0.028575
0.4963 (2.0149)0.000815



Parameters (Session):
par1 = 36 ; par2 = 0.0 ; par3 = 0 ; par4 = 1 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = 0.0 ; 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')