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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 computationMon, 01 Dec 2008 12:56:04 -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/01/t1228161466ae770nseymydoue.htm/, Retrieved Sun, 10 Nov 2024 19:43:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27283, Retrieved Sun, 10 Nov 2024 19:43:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact286

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-01 17:48:47] [b943bd7078334192ff8343563ee31113]
- RMP       [Spectral Analysis] [Non Stationary Ti...] [2008-12-01 19:56:04] [620b6ad5c4696049e39cb73ce029682c] [Current]
F RMP         [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-01 20:00:36] [b943bd7078334192ff8343563ee31113]
- RMPD        [Cross Correlation Function] [Non Stationary Ti...] [2008-12-01 20:13:53] [b943bd7078334192ff8343563ee31113]
- RMPD          [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:27:10] [b943bd7078334192ff8343563ee31113]
-   PD            [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:29:06] [b943bd7078334192ff8343563ee31113]
-   P               [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:31:48] [b943bd7078334192ff8343563ee31113]
- RMP                 [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-01 20:34:07] [b943bd7078334192ff8343563ee31113]
- RMP                   [Spectral Analysis] [Non Stationary Ti...] [2008-12-01 20:37:58] [b943bd7078334192ff8343563ee31113]
- RMP                     [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-01 20:41:45] [b943bd7078334192ff8343563ee31113]
- RMPD                      [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:15:23] [b943bd7078334192ff8343563ee31113]
-   PD                        [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:17:05] [b943bd7078334192ff8343563ee31113]
-   P                           [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:19:06] [b943bd7078334192ff8343563ee31113]
- RMP                             [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-02 07:22:03] [b943bd7078334192ff8343563ee31113]
- RMP                               [Spectral Analysis] [Non Stationary Ti...] [2008-12-02 07:25:43] [b943bd7078334192ff8343563ee31113]
- RMP                                 [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-02 07:32:20] [b943bd7078334192ff8343563ee31113]
-   PD          [Cross Correlation Function] [Non Stationary Ti...] [2008-12-02 07:37:59] [b943bd7078334192ff8343563ee31113]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112
118
132
129
121
135
148
148
136
119
104
118
115
126
141
135
125
149
170
170
158
133
114
140
145
150
178
163
172
178
199
199
184
162
146
166
171
180
193
181
183
218
230
242
209
191
172
194
196
196
236
235
229
243
264
272
237
211
180
201
204
188
235
227
234
264
302
293
259
229
203
229
242
233
267
269
270
315
364
347
312
274
237
278
284
277
317
313
318
374
413
405
355
306
271
306
315
301
356
348
355
422
465
467
404
347
305
336
340
318
362
348
363
435
491
505
404
359
310
337
360
342
406
396
420
472
548
559
463
407
362
405
417
391
419
461
472
535
622
606
508
461
390
432

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27283&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27283&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27283&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Raw Periodogram
ParameterValue
Box-Cox transformation parameter (lambda)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0069 (144)3792.028873
0.0139 (72)1238.009494
0.0208 (48)1826.626686
0.0278 (36)201.90456
0.0347 (28.8)331.907846
0.0417 (24)695.956872
0.0486 (20.5714)189.838038
0.0556 (18)632.668292
0.0625 (16)287.593613
0.0694 (14.4)1791.509224
0.0764 (13.0909)9958.986159
0.0833 (12)68001.700911
0.0903 (11.0769)6339.30519
0.0972 (10.2857)1529.925619
0.1042 (9.6)854.106417
0.1111 (9)454.283437
0.1181 (8.4706)125.530203
0.125 (8)30.347246
0.1319 (7.5789)70.029431
0.1389 (7.2)204.158401
0.1458 (6.8571)203.994506
0.1528 (6.5455)348.864801
0.1597 (6.2609)1597.138661
0.1667 (6)18608.352793
0.1736 (5.76)2154.647278
0.1806 (5.5385)608.650096
0.1875 (5.3333)615.202265
0.1944 (5.1429)120.078527
0.2014 (4.9655)130.147126
0.2083 (4.8)121.85189
0.2153 (4.6452)40.141534
0.2222 (4.5)217.826943
0.2292 (4.3636)68.288003
0.2361 (4.2353)214.055484
0.2431 (4.1143)331.595519
0.25 (4)3179.724197
0.2569 (3.8919)203.863339
0.2639 (3.7895)64.50686
0.2708 (3.6923)3.43721
0.2778 (3.6)31.782121
0.2847 (3.5122)6.688219
0.2917 (3.4286)16.986738
0.2986 (3.3488)42.173804
0.3056 (3.2727)29.803217
0.3125 (3.2)33.804933
0.3194 (3.1304)60.212446
0.3264 (3.0638)379.911387
0.3333 (3)2005.72132
0.3403 (2.9388)75.434588
0.3472 (2.88)140.072127
0.3542 (2.8235)9.294066
0.3611 (2.7692)15.430795
0.3681 (2.717)10.698128
0.375 (2.6667)4.21834
0.3819 (2.6182)35.411804
0.3889 (2.5714)16.11576
0.3958 (2.5263)11.881808
0.4028 (2.4828)183.988521
0.4097 (2.4407)159.788028
0.4167 (2.4)1276.34537
0.4236 (2.3607)113.356981
0.4306 (2.3226)208.3604
0.4375 (2.2857)105.674799
0.4444 (2.25)48.09594
0.4514 (2.2154)10.461349
0.4583 (2.1818)50.391079
0.4653 (2.1493)26.292831
0.4722 (2.1176)29.647284
0.4792 (2.087)24.120557
0.4861 (2.0571)8.778387
0.4931 (2.0282)8.689016
0.5 (2)25.907638

\begin{tabular}{lllllllll}
\hline
Raw Periodogram \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) & 1 \tabularnewline
Degree of non-seasonal differencing (d) & 0 \tabularnewline
Degree of seasonal differencing (D) & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Frequency (Period) & Spectrum \tabularnewline
0.0069 (144) & 3792.028873 \tabularnewline
0.0139 (72) & 1238.009494 \tabularnewline
0.0208 (48) & 1826.626686 \tabularnewline
0.0278 (36) & 201.90456 \tabularnewline
0.0347 (28.8) & 331.907846 \tabularnewline
0.0417 (24) & 695.956872 \tabularnewline
0.0486 (20.5714) & 189.838038 \tabularnewline
0.0556 (18) & 632.668292 \tabularnewline
0.0625 (16) & 287.593613 \tabularnewline
0.0694 (14.4) & 1791.509224 \tabularnewline
0.0764 (13.0909) & 9958.986159 \tabularnewline
0.0833 (12) & 68001.700911 \tabularnewline
0.0903 (11.0769) & 6339.30519 \tabularnewline
0.0972 (10.2857) & 1529.925619 \tabularnewline
0.1042 (9.6) & 854.106417 \tabularnewline
0.1111 (9) & 454.283437 \tabularnewline
0.1181 (8.4706) & 125.530203 \tabularnewline
0.125 (8) & 30.347246 \tabularnewline
0.1319 (7.5789) & 70.029431 \tabularnewline
0.1389 (7.2) & 204.158401 \tabularnewline
0.1458 (6.8571) & 203.994506 \tabularnewline
0.1528 (6.5455) & 348.864801 \tabularnewline
0.1597 (6.2609) & 1597.138661 \tabularnewline
0.1667 (6) & 18608.352793 \tabularnewline
0.1736 (5.76) & 2154.647278 \tabularnewline
0.1806 (5.5385) & 608.650096 \tabularnewline
0.1875 (5.3333) & 615.202265 \tabularnewline
0.1944 (5.1429) & 120.078527 \tabularnewline
0.2014 (4.9655) & 130.147126 \tabularnewline
0.2083 (4.8) & 121.85189 \tabularnewline
0.2153 (4.6452) & 40.141534 \tabularnewline
0.2222 (4.5) & 217.826943 \tabularnewline
0.2292 (4.3636) & 68.288003 \tabularnewline
0.2361 (4.2353) & 214.055484 \tabularnewline
0.2431 (4.1143) & 331.595519 \tabularnewline
0.25 (4) & 3179.724197 \tabularnewline
0.2569 (3.8919) & 203.863339 \tabularnewline
0.2639 (3.7895) & 64.50686 \tabularnewline
0.2708 (3.6923) & 3.43721 \tabularnewline
0.2778 (3.6) & 31.782121 \tabularnewline
0.2847 (3.5122) & 6.688219 \tabularnewline
0.2917 (3.4286) & 16.986738 \tabularnewline
0.2986 (3.3488) & 42.173804 \tabularnewline
0.3056 (3.2727) & 29.803217 \tabularnewline
0.3125 (3.2) & 33.804933 \tabularnewline
0.3194 (3.1304) & 60.212446 \tabularnewline
0.3264 (3.0638) & 379.911387 \tabularnewline
0.3333 (3) & 2005.72132 \tabularnewline
0.3403 (2.9388) & 75.434588 \tabularnewline
0.3472 (2.88) & 140.072127 \tabularnewline
0.3542 (2.8235) & 9.294066 \tabularnewline
0.3611 (2.7692) & 15.430795 \tabularnewline
0.3681 (2.717) & 10.698128 \tabularnewline
0.375 (2.6667) & 4.21834 \tabularnewline
0.3819 (2.6182) & 35.411804 \tabularnewline
0.3889 (2.5714) & 16.11576 \tabularnewline
0.3958 (2.5263) & 11.881808 \tabularnewline
0.4028 (2.4828) & 183.988521 \tabularnewline
0.4097 (2.4407) & 159.788028 \tabularnewline
0.4167 (2.4) & 1276.34537 \tabularnewline
0.4236 (2.3607) & 113.356981 \tabularnewline
0.4306 (2.3226) & 208.3604 \tabularnewline
0.4375 (2.2857) & 105.674799 \tabularnewline
0.4444 (2.25) & 48.09594 \tabularnewline
0.4514 (2.2154) & 10.461349 \tabularnewline
0.4583 (2.1818) & 50.391079 \tabularnewline
0.4653 (2.1493) & 26.292831 \tabularnewline
0.4722 (2.1176) & 29.647284 \tabularnewline
0.4792 (2.087) & 24.120557 \tabularnewline
0.4861 (2.0571) & 8.778387 \tabularnewline
0.4931 (2.0282) & 8.689016 \tabularnewline
0.5 (2) & 25.907638 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27283&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]0[/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]0.0069 (144)[/C][C]3792.028873[/C][/ROW]
[ROW][C]0.0139 (72)[/C][C]1238.009494[/C][/ROW]
[ROW][C]0.0208 (48)[/C][C]1826.626686[/C][/ROW]
[ROW][C]0.0278 (36)[/C][C]201.90456[/C][/ROW]
[ROW][C]0.0347 (28.8)[/C][C]331.907846[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]695.956872[/C][/ROW]
[ROW][C]0.0486 (20.5714)[/C][C]189.838038[/C][/ROW]
[ROW][C]0.0556 (18)[/C][C]632.668292[/C][/ROW]
[ROW][C]0.0625 (16)[/C][C]287.593613[/C][/ROW]
[ROW][C]0.0694 (14.4)[/C][C]1791.509224[/C][/ROW]
[ROW][C]0.0764 (13.0909)[/C][C]9958.986159[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]68001.700911[/C][/ROW]
[ROW][C]0.0903 (11.0769)[/C][C]6339.30519[/C][/ROW]
[ROW][C]0.0972 (10.2857)[/C][C]1529.925619[/C][/ROW]
[ROW][C]0.1042 (9.6)[/C][C]854.106417[/C][/ROW]
[ROW][C]0.1111 (9)[/C][C]454.283437[/C][/ROW]
[ROW][C]0.1181 (8.4706)[/C][C]125.530203[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]30.347246[/C][/ROW]
[ROW][C]0.1319 (7.5789)[/C][C]70.029431[/C][/ROW]
[ROW][C]0.1389 (7.2)[/C][C]204.158401[/C][/ROW]
[ROW][C]0.1458 (6.8571)[/C][C]203.994506[/C][/ROW]
[ROW][C]0.1528 (6.5455)[/C][C]348.864801[/C][/ROW]
[ROW][C]0.1597 (6.2609)[/C][C]1597.138661[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]18608.352793[/C][/ROW]
[ROW][C]0.1736 (5.76)[/C][C]2154.647278[/C][/ROW]
[ROW][C]0.1806 (5.5385)[/C][C]608.650096[/C][/ROW]
[ROW][C]0.1875 (5.3333)[/C][C]615.202265[/C][/ROW]
[ROW][C]0.1944 (5.1429)[/C][C]120.078527[/C][/ROW]
[ROW][C]0.2014 (4.9655)[/C][C]130.147126[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]121.85189[/C][/ROW]
[ROW][C]0.2153 (4.6452)[/C][C]40.141534[/C][/ROW]
[ROW][C]0.2222 (4.5)[/C][C]217.826943[/C][/ROW]
[ROW][C]0.2292 (4.3636)[/C][C]68.288003[/C][/ROW]
[ROW][C]0.2361 (4.2353)[/C][C]214.055484[/C][/ROW]
[ROW][C]0.2431 (4.1143)[/C][C]331.595519[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]3179.724197[/C][/ROW]
[ROW][C]0.2569 (3.8919)[/C][C]203.863339[/C][/ROW]
[ROW][C]0.2639 (3.7895)[/C][C]64.50686[/C][/ROW]
[ROW][C]0.2708 (3.6923)[/C][C]3.43721[/C][/ROW]
[ROW][C]0.2778 (3.6)[/C][C]31.782121[/C][/ROW]
[ROW][C]0.2847 (3.5122)[/C][C]6.688219[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]16.986738[/C][/ROW]
[ROW][C]0.2986 (3.3488)[/C][C]42.173804[/C][/ROW]
[ROW][C]0.3056 (3.2727)[/C][C]29.803217[/C][/ROW]
[ROW][C]0.3125 (3.2)[/C][C]33.804933[/C][/ROW]
[ROW][C]0.3194 (3.1304)[/C][C]60.212446[/C][/ROW]
[ROW][C]0.3264 (3.0638)[/C][C]379.911387[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]2005.72132[/C][/ROW]
[ROW][C]0.3403 (2.9388)[/C][C]75.434588[/C][/ROW]
[ROW][C]0.3472 (2.88)[/C][C]140.072127[/C][/ROW]
[ROW][C]0.3542 (2.8235)[/C][C]9.294066[/C][/ROW]
[ROW][C]0.3611 (2.7692)[/C][C]15.430795[/C][/ROW]
[ROW][C]0.3681 (2.717)[/C][C]10.698128[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]4.21834[/C][/ROW]
[ROW][C]0.3819 (2.6182)[/C][C]35.411804[/C][/ROW]
[ROW][C]0.3889 (2.5714)[/C][C]16.11576[/C][/ROW]
[ROW][C]0.3958 (2.5263)[/C][C]11.881808[/C][/ROW]
[ROW][C]0.4028 (2.4828)[/C][C]183.988521[/C][/ROW]
[ROW][C]0.4097 (2.4407)[/C][C]159.788028[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]1276.34537[/C][/ROW]
[ROW][C]0.4236 (2.3607)[/C][C]113.356981[/C][/ROW]
[ROW][C]0.4306 (2.3226)[/C][C]208.3604[/C][/ROW]
[ROW][C]0.4375 (2.2857)[/C][C]105.674799[/C][/ROW]
[ROW][C]0.4444 (2.25)[/C][C]48.09594[/C][/ROW]
[ROW][C]0.4514 (2.2154)[/C][C]10.461349[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]50.391079[/C][/ROW]
[ROW][C]0.4653 (2.1493)[/C][C]26.292831[/C][/ROW]
[ROW][C]0.4722 (2.1176)[/C][C]29.647284[/C][/ROW]
[ROW][C]0.4792 (2.087)[/C][C]24.120557[/C][/ROW]
[ROW][C]0.4861 (2.0571)[/C][C]8.778387[/C][/ROW]
[ROW][C]0.4931 (2.0282)[/C][C]8.689016[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]25.907638[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27283&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27283&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)1
Degree of non-seasonal differencing (d)0
Degree of seasonal differencing (D)0
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0069 (144)3792.028873
0.0139 (72)1238.009494
0.0208 (48)1826.626686
0.0278 (36)201.90456
0.0347 (28.8)331.907846
0.0417 (24)695.956872
0.0486 (20.5714)189.838038
0.0556 (18)632.668292
0.0625 (16)287.593613
0.0694 (14.4)1791.509224
0.0764 (13.0909)9958.986159
0.0833 (12)68001.700911
0.0903 (11.0769)6339.30519
0.0972 (10.2857)1529.925619
0.1042 (9.6)854.106417
0.1111 (9)454.283437
0.1181 (8.4706)125.530203
0.125 (8)30.347246
0.1319 (7.5789)70.029431
0.1389 (7.2)204.158401
0.1458 (6.8571)203.994506
0.1528 (6.5455)348.864801
0.1597 (6.2609)1597.138661
0.1667 (6)18608.352793
0.1736 (5.76)2154.647278
0.1806 (5.5385)608.650096
0.1875 (5.3333)615.202265
0.1944 (5.1429)120.078527
0.2014 (4.9655)130.147126
0.2083 (4.8)121.85189
0.2153 (4.6452)40.141534
0.2222 (4.5)217.826943
0.2292 (4.3636)68.288003
0.2361 (4.2353)214.055484
0.2431 (4.1143)331.595519
0.25 (4)3179.724197
0.2569 (3.8919)203.863339
0.2639 (3.7895)64.50686
0.2708 (3.6923)3.43721
0.2778 (3.6)31.782121
0.2847 (3.5122)6.688219
0.2917 (3.4286)16.986738
0.2986 (3.3488)42.173804
0.3056 (3.2727)29.803217
0.3125 (3.2)33.804933
0.3194 (3.1304)60.212446
0.3264 (3.0638)379.911387
0.3333 (3)2005.72132
0.3403 (2.9388)75.434588
0.3472 (2.88)140.072127
0.3542 (2.8235)9.294066
0.3611 (2.7692)15.430795
0.3681 (2.717)10.698128
0.375 (2.6667)4.21834
0.3819 (2.6182)35.411804
0.3889 (2.5714)16.11576
0.3958 (2.5263)11.881808
0.4028 (2.4828)183.988521
0.4097 (2.4407)159.788028
0.4167 (2.4)1276.34537
0.4236 (2.3607)113.356981
0.4306 (2.3226)208.3604
0.4375 (2.2857)105.674799
0.4444 (2.25)48.09594
0.4514 (2.2154)10.461349
0.4583 (2.1818)50.391079
0.4653 (2.1493)26.292831
0.4722 (2.1176)29.647284
0.4792 (2.087)24.120557
0.4861 (2.0571)8.778387
0.4931 (2.0282)8.689016
0.5 (2)25.907638


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; 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')