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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 computationWed, 22 Dec 2010 13:46:56 +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/t1293025534ntdl7pvlyge356v.htm/, Retrieved Mon, 06 May 2024 02:29:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114208, Retrieved Mon, 06 May 2024 02:29:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD  [Variance Reduction Matrix] [WS9 - Variance Re...] [2010-12-04 11:04:59] [8ef49741e164ec6343c90c7935194465]
-   P     [Variance Reduction Matrix] [WS 9 VRM] [2010-12-05 14:01:21] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD      [(Partial) Autocorrelation Function] [paper ACF] [2010-12-10 10:47:04] [8214fe6d084e5ad7598b249a26cc9f06]
-   P         [(Partial) Autocorrelation Function] [paper acf met D=1] [2010-12-10 11:19:24] [8214fe6d084e5ad7598b249a26cc9f06]
- RMP           [Spectral Analysis] [paper - cum perio...] [2010-12-10 11:22:34] [8214fe6d084e5ad7598b249a26cc9f06]
-   P             [Spectral Analysis] [paper - cum perio...] [2010-12-10 11:27:22] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD              [Spectral Analysis] [cum periodogram 2 ] [2010-12-20 20:28:39] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                  [Spectral Analysis] [cum per 2 paper] [2010-12-22 13:46:56] [b47314d83d48c7bf812ec2bcd743b159] [Current]
-   PD                    [Spectral Analysis] [cum per 1 middeng...] [2010-12-22 19:06:59] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                       [Spectral Analysis] [cum per 2 middeng...] [2010-12-22 19:08:52] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                        [Spectral Analysis] [cum per 1 hoogges...] [2010-12-22 19:10:38] [8214fe6d084e5ad7598b249a26cc9f06]
-   P                           [Spectral Analysis] [cum per 2 hoogges...] [2010-12-22 19:12:39] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD                            [Standard Deviation-Mean Plot] [sdmp laaggeschoolden] [2010-12-22 19:15:16] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                              [Standard Deviation-Mean Plot] [sdmp middengescho...] [2010-12-22 19:17:33] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                [Standard Deviation-Mean Plot] [sdmp hooggeschoolden] [2010-12-22 19:20:25] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                [Standard Deviation-Mean Plot] [sdmp hooggeschoolden] [2010-12-22 19:20:25] [8214fe6d084e5ad7598b249a26cc9f06]
- RMPD                                [ARIMA Backward Selection] [arima backward se...] [2010-12-22 19:29:00] [8214fe6d084e5ad7598b249a26cc9f06]
-   PD                                  [ARIMA Backward Selection] [arima backward se...] [2010-12-22 19:34:28] [8214fe6d084e5ad7598b249a26cc9f06]
-    D                                    [ARIMA Backward Selection] [arima backward se...] [2010-12-22 22:09:56] [8214fe6d084e5ad7598b249a26cc9f06]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
104708
101817
97898
95559
92822
90848
101141
105841
93647
90923
89130
90212
93196
91861
90593
89895
88819
87924
96906
101217
98709
98139
95529
98577
100772
100180
99200
96251
94514
93780
105192
107682
99687
99436
102049
102673
105813
105056
103916
103513
101893
102503
113149
116696
108500
107800
105941
108742
111680
111270
110698
108517
107127
107088
116321
125045
116779
122887
120162
123198
123610
122293
121289
119393
117494
116693
125062
127281
120195
119804
117113
119240
115823
116281
113816
114632
112987
111633
116721
114850
112797
105368
102524
101327
102612
98873
95993
93244
90403
88539
98106
96963
90781
89253
87794
89810
90864
89025
87621
87718
83433
84535
92223
91052
88456
88706
89137
94066
99258
100673
102269
100833
99314
101764
108242
108148
104761
103772
103737
111043
109906
109335
107247
105690
102755
102280
110590
109122
102803
101424
99138

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'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=114208&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=114208&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114208&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'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)16862966.602053
0.0167 (60)26088745.895164
0.025 (40)21255963.847173
0.0333 (30)6624930.37045
0.0417 (24)3153163.233852
0.05 (20)8774718.90475
0.0583 (17.1429)24746470.726692
0.0667 (15)1239355.131462
0.075 (13.3333)99372.390446
0.0833 (12)957212.792409
0.0917 (10.9091)4792269.11056
0.1 (10)2050193.594518
0.1083 (9.2308)2600463.735785
0.1167 (8.5714)11742497.741546
0.125 (8)775966.996842
0.1333 (7.5)3493114.361873
0.1417 (7.0588)9678141.528887
0.15 (6.6667)3098021.132181
0.1583 (6.3158)429731.382267
0.1667 (6)1112051.705875
0.175 (5.7143)775675.416268
0.1833 (5.4545)2583085.682156
0.1917 (5.2174)276285.771204
0.2 (5)18121752.292691
0.2083 (4.8)1139752.362693
0.2167 (4.6154)30386357.096737
0.225 (4.4444)4617022.577071
0.2333 (4.2857)4454731.351245
0.2417 (4.1379)389446.84359
0.25 (4)197762.806335
0.2583 (3.871)445377.630077
0.2667 (3.75)2012922.190994
0.275 (3.6364)2690441.072525
0.2833 (3.5294)24165310.605187
0.2917 (3.4286)2000639.001467
0.3 (3.3333)11237781.485669
0.3083 (3.2432)1139117.951997
0.3167 (3.1579)8848929.184598
0.325 (3.0769)170503.146185
0.3333 (3)3535869.642407
0.3417 (2.9268)1950678.668855
0.35 (2.8571)1832257.27055
0.3583 (2.7907)10571963.20755
0.3667 (2.7273)16534087.657318
0.375 (2.6667)9477656.342843
0.3833 (2.6087)10395447.491975
0.3917 (2.5532)7334685.085465
0.4 (2.5)4345208.318445
0.4083 (2.449)2129646.759365
0.4167 (2.4)1829227.858652
0.425 (2.3529)1293787.332246
0.4333 (2.3077)30910871.056077
0.4417 (2.2642)19729021.602674
0.45 (2.2222)20198422.586191
0.4583 (2.1818)23810004.642591
0.4667 (2.1429)5566302.819182
0.475 (2.1053)10172957.780301
0.4833 (2.069)24586800.381201
0.4917 (2.0339)2438884.753055
0.5 (2)242291.831558

\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) & 16862966.602053 \tabularnewline
0.0167 (60) & 26088745.895164 \tabularnewline
0.025 (40) & 21255963.847173 \tabularnewline
0.0333 (30) & 6624930.37045 \tabularnewline
0.0417 (24) & 3153163.233852 \tabularnewline
0.05 (20) & 8774718.90475 \tabularnewline
0.0583 (17.1429) & 24746470.726692 \tabularnewline
0.0667 (15) & 1239355.131462 \tabularnewline
0.075 (13.3333) & 99372.390446 \tabularnewline
0.0833 (12) & 957212.792409 \tabularnewline
0.0917 (10.9091) & 4792269.11056 \tabularnewline
0.1 (10) & 2050193.594518 \tabularnewline
0.1083 (9.2308) & 2600463.735785 \tabularnewline
0.1167 (8.5714) & 11742497.741546 \tabularnewline
0.125 (8) & 775966.996842 \tabularnewline
0.1333 (7.5) & 3493114.361873 \tabularnewline
0.1417 (7.0588) & 9678141.528887 \tabularnewline
0.15 (6.6667) & 3098021.132181 \tabularnewline
0.1583 (6.3158) & 429731.382267 \tabularnewline
0.1667 (6) & 1112051.705875 \tabularnewline
0.175 (5.7143) & 775675.416268 \tabularnewline
0.1833 (5.4545) & 2583085.682156 \tabularnewline
0.1917 (5.2174) & 276285.771204 \tabularnewline
0.2 (5) & 18121752.292691 \tabularnewline
0.2083 (4.8) & 1139752.362693 \tabularnewline
0.2167 (4.6154) & 30386357.096737 \tabularnewline
0.225 (4.4444) & 4617022.577071 \tabularnewline
0.2333 (4.2857) & 4454731.351245 \tabularnewline
0.2417 (4.1379) & 389446.84359 \tabularnewline
0.25 (4) & 197762.806335 \tabularnewline
0.2583 (3.871) & 445377.630077 \tabularnewline
0.2667 (3.75) & 2012922.190994 \tabularnewline
0.275 (3.6364) & 2690441.072525 \tabularnewline
0.2833 (3.5294) & 24165310.605187 \tabularnewline
0.2917 (3.4286) & 2000639.001467 \tabularnewline
0.3 (3.3333) & 11237781.485669 \tabularnewline
0.3083 (3.2432) & 1139117.951997 \tabularnewline
0.3167 (3.1579) & 8848929.184598 \tabularnewline
0.325 (3.0769) & 170503.146185 \tabularnewline
0.3333 (3) & 3535869.642407 \tabularnewline
0.3417 (2.9268) & 1950678.668855 \tabularnewline
0.35 (2.8571) & 1832257.27055 \tabularnewline
0.3583 (2.7907) & 10571963.20755 \tabularnewline
0.3667 (2.7273) & 16534087.657318 \tabularnewline
0.375 (2.6667) & 9477656.342843 \tabularnewline
0.3833 (2.6087) & 10395447.491975 \tabularnewline
0.3917 (2.5532) & 7334685.085465 \tabularnewline
0.4 (2.5) & 4345208.318445 \tabularnewline
0.4083 (2.449) & 2129646.759365 \tabularnewline
0.4167 (2.4) & 1829227.858652 \tabularnewline
0.425 (2.3529) & 1293787.332246 \tabularnewline
0.4333 (2.3077) & 30910871.056077 \tabularnewline
0.4417 (2.2642) & 19729021.602674 \tabularnewline
0.45 (2.2222) & 20198422.586191 \tabularnewline
0.4583 (2.1818) & 23810004.642591 \tabularnewline
0.4667 (2.1429) & 5566302.819182 \tabularnewline
0.475 (2.1053) & 10172957.780301 \tabularnewline
0.4833 (2.069) & 24586800.381201 \tabularnewline
0.4917 (2.0339) & 2438884.753055 \tabularnewline
0.5 (2) & 242291.831558 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114208&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]16862966.602053[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]26088745.895164[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]21255963.847173[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]6624930.37045[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]3153163.233852[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]8774718.90475[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]24746470.726692[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]1239355.131462[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]99372.390446[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]957212.792409[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]4792269.11056[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]2050193.594518[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]2600463.735785[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]11742497.741546[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]775966.996842[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]3493114.361873[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]9678141.528887[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]3098021.132181[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]429731.382267[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]1112051.705875[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]775675.416268[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]2583085.682156[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]276285.771204[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]18121752.292691[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]1139752.362693[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]30386357.096737[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]4617022.577071[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]4454731.351245[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]389446.84359[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]197762.806335[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]445377.630077[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]2012922.190994[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]2690441.072525[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]24165310.605187[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]2000639.001467[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]11237781.485669[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]1139117.951997[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]8848929.184598[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]170503.146185[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]3535869.642407[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]1950678.668855[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]1832257.27055[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]10571963.20755[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]16534087.657318[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]9477656.342843[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]10395447.491975[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]7334685.085465[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]4345208.318445[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]2129646.759365[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]1829227.858652[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]1293787.332246[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]30910871.056077[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]19729021.602674[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]20198422.586191[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]23810004.642591[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]5566302.819182[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]10172957.780301[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]24586800.381201[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]2438884.753055[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]242291.831558[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114208&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114208&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)1
Degree of seasonal differencing (D)1
Seasonal Period (s)12
Frequency (Period)Spectrum
0.0083 (120)16862966.602053
0.0167 (60)26088745.895164
0.025 (40)21255963.847173
0.0333 (30)6624930.37045
0.0417 (24)3153163.233852
0.05 (20)8774718.90475
0.0583 (17.1429)24746470.726692
0.0667 (15)1239355.131462
0.075 (13.3333)99372.390446
0.0833 (12)957212.792409
0.0917 (10.9091)4792269.11056
0.1 (10)2050193.594518
0.1083 (9.2308)2600463.735785
0.1167 (8.5714)11742497.741546
0.125 (8)775966.996842
0.1333 (7.5)3493114.361873
0.1417 (7.0588)9678141.528887
0.15 (6.6667)3098021.132181
0.1583 (6.3158)429731.382267
0.1667 (6)1112051.705875
0.175 (5.7143)775675.416268
0.1833 (5.4545)2583085.682156
0.1917 (5.2174)276285.771204
0.2 (5)18121752.292691
0.2083 (4.8)1139752.362693
0.2167 (4.6154)30386357.096737
0.225 (4.4444)4617022.577071
0.2333 (4.2857)4454731.351245
0.2417 (4.1379)389446.84359
0.25 (4)197762.806335
0.2583 (3.871)445377.630077
0.2667 (3.75)2012922.190994
0.275 (3.6364)2690441.072525
0.2833 (3.5294)24165310.605187
0.2917 (3.4286)2000639.001467
0.3 (3.3333)11237781.485669
0.3083 (3.2432)1139117.951997
0.3167 (3.1579)8848929.184598
0.325 (3.0769)170503.146185
0.3333 (3)3535869.642407
0.3417 (2.9268)1950678.668855
0.35 (2.8571)1832257.27055
0.3583 (2.7907)10571963.20755
0.3667 (2.7273)16534087.657318
0.375 (2.6667)9477656.342843
0.3833 (2.6087)10395447.491975
0.3917 (2.5532)7334685.085465
0.4 (2.5)4345208.318445
0.4083 (2.449)2129646.759365
0.4167 (2.4)1829227.858652
0.425 (2.3529)1293787.332246
0.4333 (2.3077)30910871.056077
0.4417 (2.2642)19729021.602674
0.45 (2.2222)20198422.586191
0.4583 (2.1818)23810004.642591
0.4667 (2.1429)5566302.819182
0.475 (2.1053)10172957.780301
0.4833 (2.069)24586800.381201
0.4917 (2.0339)2438884.753055
0.5 (2)242291.831558


Figures (Output of Computation)

Input Parameters & R Code

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')