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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 computationThu, 16 Dec 2010 16:20:52 +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/16/t1292516332dwd3w63ysyjv68v.htm/, Retrieved Fri, 03 May 2024 10:58:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111064, Retrieved Fri, 03 May 2024 10:58:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

Tree of Dependent Computations

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] [Aantal openstaand...] [2010-12-16 16:14:12] [4f1a20f787b3465111b61213cdeef1a9]
-   P         [Spectral Analysis] [Aantal openstaand...] [2010-12-16 16:20:52] [f0b33ae54e73edcd25a3e2f31270d1c9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
27.951
29.781
32.914
33.488
35.652
36.488
35.387
35.676
34.844
32.447
31.068
29.010
29.812
30.951
32.974
32.936
34.012
32.946
31.948
30.599
27.691
25.073
23.406
22.248
22.896
25.317
26.558
26.471
27.543
26.198
24.725
25.005
23.462
20.780
19.815
19.761
21.454
23.899
24.939
23.580
24.562
24.696
23.785
23.812
21.917
19.713
19.282
18.788
21.453
24.482
27.474
27.264
27.349
30.632
29.429
30.084
26.290
24.379
23.335
21.346
21.106
24.514
28.353
30.805
31.348
34.556
33.855
34.787
32.529
29.998
29.257
28.155
30.466
35.704
39.327
39.351
42.234
43.630
43.722
43.121
37.985
37.135
34.646
33.026
35.087
38.846
42.013
43.908
42.868
44.423
44.167
43.636
44.382
42.142
43.452
36.912
42.413
45.344
44.873
47.510
49.554
47.369
45.998
48.140
48.441
44.928
40.454
38.661
37.246
36.843
36.424
37.594
38.144
38.737
34.560
36.080
33.508
35.462
33.374
32.110
35.533
35.532
37.903
36.763
40.399
44.164
44.496
43.110
43.880
43.930
44.327

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111064&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111064&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111064&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'George Udny Yule' @ 72.249.76.132






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)7.884241
0.0167 (60)1.749918
0.025 (40)3.786992
0.0333 (30)11.896782
0.0417 (24)14.590326
0.05 (20)0.735944
0.0583 (17.1429)3.755385
0.0667 (15)0.3104
0.075 (13.3333)3.784519
0.0833 (12)0.103077
0.0917 (10.9091)0.373118
0.1 (10)6.97015
0.1083 (9.2308)2.705687
0.1167 (8.5714)2.327486
0.125 (8)2.378539
0.1333 (7.5)0.061457
0.1417 (7.0588)3.450046
0.15 (6.6667)2.922274
0.1583 (6.3158)3.621463
0.1667 (6)0.172692
0.175 (5.7143)0.155086
0.1833 (5.4545)0.33548
0.1917 (5.2174)1.746064
0.2 (5)5.529884
0.2083 (4.8)1.767491
0.2167 (4.6154)2.364846
0.225 (4.4444)7.276574
0.2333 (4.2857)2.255134
0.2417 (4.1379)2.663382
0.25 (4)0.446157
0.2583 (3.871)1.605928
0.2667 (3.75)6.03798
0.275 (3.6364)5.773616
0.2833 (3.5294)11.305357
0.2917 (3.4286)14.368826
0.3 (3.3333)6.066396
0.3083 (3.2432)6.05586
0.3167 (3.1579)3.376762
0.325 (3.0769)0.291312
0.3333 (3)0.129885
0.3417 (2.9268)1.035659
0.35 (2.8571)1.004173
0.3583 (2.7907)0.651979
0.3667 (2.7273)1.002055
0.375 (2.6667)5.183136
0.3833 (2.6087)22.901362
0.3917 (2.5532)23.119439
0.4 (2.5)1.694801
0.4083 (2.449)2.384632
0.4167 (2.4)1.0404
0.425 (2.3529)1.500043
0.4333 (2.3077)8.373396
0.4417 (2.2642)1.397034
0.45 (2.2222)4.528527
0.4583 (2.1818)18.537754
0.4667 (2.1429)23.24217
0.475 (2.1053)6.739628
0.4833 (2.069)5.794878
0.4917 (2.0339)0.465878
0.5 (2)0.381752

\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) & 7.884241 \tabularnewline
0.0167 (60) & 1.749918 \tabularnewline
0.025 (40) & 3.786992 \tabularnewline
0.0333 (30) & 11.896782 \tabularnewline
0.0417 (24) & 14.590326 \tabularnewline
0.05 (20) & 0.735944 \tabularnewline
0.0583 (17.1429) & 3.755385 \tabularnewline
0.0667 (15) & 0.3104 \tabularnewline
0.075 (13.3333) & 3.784519 \tabularnewline
0.0833 (12) & 0.103077 \tabularnewline
0.0917 (10.9091) & 0.373118 \tabularnewline
0.1 (10) & 6.97015 \tabularnewline
0.1083 (9.2308) & 2.705687 \tabularnewline
0.1167 (8.5714) & 2.327486 \tabularnewline
0.125 (8) & 2.378539 \tabularnewline
0.1333 (7.5) & 0.061457 \tabularnewline
0.1417 (7.0588) & 3.450046 \tabularnewline
0.15 (6.6667) & 2.922274 \tabularnewline
0.1583 (6.3158) & 3.621463 \tabularnewline
0.1667 (6) & 0.172692 \tabularnewline
0.175 (5.7143) & 0.155086 \tabularnewline
0.1833 (5.4545) & 0.33548 \tabularnewline
0.1917 (5.2174) & 1.746064 \tabularnewline
0.2 (5) & 5.529884 \tabularnewline
0.2083 (4.8) & 1.767491 \tabularnewline
0.2167 (4.6154) & 2.364846 \tabularnewline
0.225 (4.4444) & 7.276574 \tabularnewline
0.2333 (4.2857) & 2.255134 \tabularnewline
0.2417 (4.1379) & 2.663382 \tabularnewline
0.25 (4) & 0.446157 \tabularnewline
0.2583 (3.871) & 1.605928 \tabularnewline
0.2667 (3.75) & 6.03798 \tabularnewline
0.275 (3.6364) & 5.773616 \tabularnewline
0.2833 (3.5294) & 11.305357 \tabularnewline
0.2917 (3.4286) & 14.368826 \tabularnewline
0.3 (3.3333) & 6.066396 \tabularnewline
0.3083 (3.2432) & 6.05586 \tabularnewline
0.3167 (3.1579) & 3.376762 \tabularnewline
0.325 (3.0769) & 0.291312 \tabularnewline
0.3333 (3) & 0.129885 \tabularnewline
0.3417 (2.9268) & 1.035659 \tabularnewline
0.35 (2.8571) & 1.004173 \tabularnewline
0.3583 (2.7907) & 0.651979 \tabularnewline
0.3667 (2.7273) & 1.002055 \tabularnewline
0.375 (2.6667) & 5.183136 \tabularnewline
0.3833 (2.6087) & 22.901362 \tabularnewline
0.3917 (2.5532) & 23.119439 \tabularnewline
0.4 (2.5) & 1.694801 \tabularnewline
0.4083 (2.449) & 2.384632 \tabularnewline
0.4167 (2.4) & 1.0404 \tabularnewline
0.425 (2.3529) & 1.500043 \tabularnewline
0.4333 (2.3077) & 8.373396 \tabularnewline
0.4417 (2.2642) & 1.397034 \tabularnewline
0.45 (2.2222) & 4.528527 \tabularnewline
0.4583 (2.1818) & 18.537754 \tabularnewline
0.4667 (2.1429) & 23.24217 \tabularnewline
0.475 (2.1053) & 6.739628 \tabularnewline
0.4833 (2.069) & 5.794878 \tabularnewline
0.4917 (2.0339) & 0.465878 \tabularnewline
0.5 (2) & 0.381752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111064&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]7.884241[/C][/ROW]
[ROW][C]0.0167 (60)[/C][C]1.749918[/C][/ROW]
[ROW][C]0.025 (40)[/C][C]3.786992[/C][/ROW]
[ROW][C]0.0333 (30)[/C][C]11.896782[/C][/ROW]
[ROW][C]0.0417 (24)[/C][C]14.590326[/C][/ROW]
[ROW][C]0.05 (20)[/C][C]0.735944[/C][/ROW]
[ROW][C]0.0583 (17.1429)[/C][C]3.755385[/C][/ROW]
[ROW][C]0.0667 (15)[/C][C]0.3104[/C][/ROW]
[ROW][C]0.075 (13.3333)[/C][C]3.784519[/C][/ROW]
[ROW][C]0.0833 (12)[/C][C]0.103077[/C][/ROW]
[ROW][C]0.0917 (10.9091)[/C][C]0.373118[/C][/ROW]
[ROW][C]0.1 (10)[/C][C]6.97015[/C][/ROW]
[ROW][C]0.1083 (9.2308)[/C][C]2.705687[/C][/ROW]
[ROW][C]0.1167 (8.5714)[/C][C]2.327486[/C][/ROW]
[ROW][C]0.125 (8)[/C][C]2.378539[/C][/ROW]
[ROW][C]0.1333 (7.5)[/C][C]0.061457[/C][/ROW]
[ROW][C]0.1417 (7.0588)[/C][C]3.450046[/C][/ROW]
[ROW][C]0.15 (6.6667)[/C][C]2.922274[/C][/ROW]
[ROW][C]0.1583 (6.3158)[/C][C]3.621463[/C][/ROW]
[ROW][C]0.1667 (6)[/C][C]0.172692[/C][/ROW]
[ROW][C]0.175 (5.7143)[/C][C]0.155086[/C][/ROW]
[ROW][C]0.1833 (5.4545)[/C][C]0.33548[/C][/ROW]
[ROW][C]0.1917 (5.2174)[/C][C]1.746064[/C][/ROW]
[ROW][C]0.2 (5)[/C][C]5.529884[/C][/ROW]
[ROW][C]0.2083 (4.8)[/C][C]1.767491[/C][/ROW]
[ROW][C]0.2167 (4.6154)[/C][C]2.364846[/C][/ROW]
[ROW][C]0.225 (4.4444)[/C][C]7.276574[/C][/ROW]
[ROW][C]0.2333 (4.2857)[/C][C]2.255134[/C][/ROW]
[ROW][C]0.2417 (4.1379)[/C][C]2.663382[/C][/ROW]
[ROW][C]0.25 (4)[/C][C]0.446157[/C][/ROW]
[ROW][C]0.2583 (3.871)[/C][C]1.605928[/C][/ROW]
[ROW][C]0.2667 (3.75)[/C][C]6.03798[/C][/ROW]
[ROW][C]0.275 (3.6364)[/C][C]5.773616[/C][/ROW]
[ROW][C]0.2833 (3.5294)[/C][C]11.305357[/C][/ROW]
[ROW][C]0.2917 (3.4286)[/C][C]14.368826[/C][/ROW]
[ROW][C]0.3 (3.3333)[/C][C]6.066396[/C][/ROW]
[ROW][C]0.3083 (3.2432)[/C][C]6.05586[/C][/ROW]
[ROW][C]0.3167 (3.1579)[/C][C]3.376762[/C][/ROW]
[ROW][C]0.325 (3.0769)[/C][C]0.291312[/C][/ROW]
[ROW][C]0.3333 (3)[/C][C]0.129885[/C][/ROW]
[ROW][C]0.3417 (2.9268)[/C][C]1.035659[/C][/ROW]
[ROW][C]0.35 (2.8571)[/C][C]1.004173[/C][/ROW]
[ROW][C]0.3583 (2.7907)[/C][C]0.651979[/C][/ROW]
[ROW][C]0.3667 (2.7273)[/C][C]1.002055[/C][/ROW]
[ROW][C]0.375 (2.6667)[/C][C]5.183136[/C][/ROW]
[ROW][C]0.3833 (2.6087)[/C][C]22.901362[/C][/ROW]
[ROW][C]0.3917 (2.5532)[/C][C]23.119439[/C][/ROW]
[ROW][C]0.4 (2.5)[/C][C]1.694801[/C][/ROW]
[ROW][C]0.4083 (2.449)[/C][C]2.384632[/C][/ROW]
[ROW][C]0.4167 (2.4)[/C][C]1.0404[/C][/ROW]
[ROW][C]0.425 (2.3529)[/C][C]1.500043[/C][/ROW]
[ROW][C]0.4333 (2.3077)[/C][C]8.373396[/C][/ROW]
[ROW][C]0.4417 (2.2642)[/C][C]1.397034[/C][/ROW]
[ROW][C]0.45 (2.2222)[/C][C]4.528527[/C][/ROW]
[ROW][C]0.4583 (2.1818)[/C][C]18.537754[/C][/ROW]
[ROW][C]0.4667 (2.1429)[/C][C]23.24217[/C][/ROW]
[ROW][C]0.475 (2.1053)[/C][C]6.739628[/C][/ROW]
[ROW][C]0.4833 (2.069)[/C][C]5.794878[/C][/ROW]
[ROW][C]0.4917 (2.0339)[/C][C]0.465878[/C][/ROW]
[ROW][C]0.5 (2)[/C][C]0.381752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111064&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111064&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)7.884241
0.0167 (60)1.749918
0.025 (40)3.786992
0.0333 (30)11.896782
0.0417 (24)14.590326
0.05 (20)0.735944
0.0583 (17.1429)3.755385
0.0667 (15)0.3104
0.075 (13.3333)3.784519
0.0833 (12)0.103077
0.0917 (10.9091)0.373118
0.1 (10)6.97015
0.1083 (9.2308)2.705687
0.1167 (8.5714)2.327486
0.125 (8)2.378539
0.1333 (7.5)0.061457
0.1417 (7.0588)3.450046
0.15 (6.6667)2.922274
0.1583 (6.3158)3.621463
0.1667 (6)0.172692
0.175 (5.7143)0.155086
0.1833 (5.4545)0.33548
0.1917 (5.2174)1.746064
0.2 (5)5.529884
0.2083 (4.8)1.767491
0.2167 (4.6154)2.364846
0.225 (4.4444)7.276574
0.2333 (4.2857)2.255134
0.2417 (4.1379)2.663382
0.25 (4)0.446157
0.2583 (3.871)1.605928
0.2667 (3.75)6.03798
0.275 (3.6364)5.773616
0.2833 (3.5294)11.305357
0.2917 (3.4286)14.368826
0.3 (3.3333)6.066396
0.3083 (3.2432)6.05586
0.3167 (3.1579)3.376762
0.325 (3.0769)0.291312
0.3333 (3)0.129885
0.3417 (2.9268)1.035659
0.35 (2.8571)1.004173
0.3583 (2.7907)0.651979
0.3667 (2.7273)1.002055
0.375 (2.6667)5.183136
0.3833 (2.6087)22.901362
0.3917 (2.5532)23.119439
0.4 (2.5)1.694801
0.4083 (2.449)2.384632
0.4167 (2.4)1.0404
0.425 (2.3529)1.500043
0.4333 (2.3077)8.373396
0.4417 (2.2642)1.397034
0.45 (2.2222)4.528527
0.4583 (2.1818)18.537754
0.4667 (2.1429)23.24217
0.475 (2.1053)6.739628
0.4833 (2.069)5.794878
0.4917 (2.0339)0.465878
0.5 (2)0.381752


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')