Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationMon, 10 Dec 2012 08:10:47 -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/10/t1355145411rvwiyid9flgml8y.htm/, Retrieved Thu, 28 Mar 2024 12:28:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=198136, Retrieved Thu, 28 Mar 2024 12:28:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Monthly US soldie...] [2010-11-02 12:07:39] [b98453cac15ba1066b407e146608df68]
- RMP   [Structural Time Series Models] [Soldiers] [2010-11-30 14:06:56] [b98453cac15ba1066b407e146608df68]
- R         [Structural Time Series Models] [paper decompositi...] [2012-12-10 13:10:47] [d0f95aac7f57db23d4da86d121b837fb] [Current]
Feedback Forum

Post a new message
Dataseries X:
37
30
47
35
30
43
82
40
47
19
52
136
80
42
54
66
81
63
137
72
107
58
36
52
79
77
54
84
48
96
83
66
61
53
30
74
69
59
42
65
70
100
63
105
82
81
75
102
121
98
76
77
63
37
35
23
40
29
37
51
20
28
13
22
25
13
16
13
16
17
9
17
25
14
8
7
10
7
10
3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198136&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]4 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=198136&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198136&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 time4 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
13737000
23034.0671084683152-0.315647737605578-0.315647736427373-0.291557373517879
34739.27542647645080.1130180117236580.1130180117236590.578107229803196
43537.59882463083430.006090945639539310.00609094563953918-0.194826689667111
53034.6319916351207-0.138701841033797-0.138701841033797-0.332719357331009
64337.82933131547510.0002856514780399250.0002856514780394410.380389932390595
78254.73456194959090.6263475591569220.6263475591569271.95163537628377
84049.27553923120590.4201592630492240.420159263049225-0.708355608548318
94748.51401169043910.3827646169084840.382764616908483-0.138315762937479
101937.44183721206460.03933647401248960.0393364740124888-1.34590443528714
115242.94931818396530.1961707161967490.1961707161967490.644219298247049
1213678.09342474923871.161409344683561.161409344683564.12554663261248
138082.40512867082240.80364042060951-8.840044630468030.530695410877487
144265.05161545265650.05427328486420110.0542732963455695-1.77265794230896
155460.6291425143458-0.0882433308543582-0.0882433308543578-0.486103540577851
166662.6908737068595-0.0332820722718497-0.03328207227184710.244989299768335
178169.65998182284980.1173069798086540.1173069798086540.817044166011647
186367.17308679010860.06812745790561460.0681274579056192-0.307662324769699
1913793.43645761992040.5179943263371980.5179943263372123.1162063703195
207285.53136824514990.382947136914710.382947136914715-1.00607626554196
2110793.66083814308160.5010775949930050.5010775949930090.9275531513865
225880.45812736225280.2997695640990280.299769564099028-1.64344369578804
233663.92819497796110.05958395535652280.0595839553565231-2.02042797110162
245259.4900687927589-0.00312603724857599-0.00312603724857725-0.540347391451251
257965.1690061308232-0.2969582113994153.266540311842170.816165034938507
267769.9327176459754-0.163315952086191-0.1633159406837430.539272848318194
275463.6966200267842-0.286952606481319-0.286952606481318-0.689459782507756
288471.3619353166006-0.156428681746955-0.1564286817469520.929872417151113
294862.5185472531176-0.277017599763187-0.277017599763188-1.03081304137439
309674.9979214913174-0.120646338805327-0.120646338805321.52551249199436
318377.9573560353658-0.0861220408536572-0.08612204085364150.369942031745338
326673.4756554429748-0.132363329073147-0.132363329073143-0.529281927821184
336168.7937784892558-0.178117807681694-0.178117807681693-0.548659557440484
345362.8678232746454-0.234077740099448-0.234077740099449-0.693843430345268
353050.5756045527-0.348675410251912-0.348675410251913-1.45649856799668
367459.201717621918-0.264959389992083-0.2649593899920841.08452209063264
376961.189327537834-0.3403712424509913.744083655585860.306763104031148
385960.2507045208828-0.351987472511584-0.351987460882836-0.0662477604985646
394253.1654628941224-0.45275420241595-0.452754202415951-0.780050188218372
406557.5263499866064-0.394569173721769-0.3945691737217670.569637433888833
417062.1044147537634-0.34360563927063-0.3436056392706320.594750079697018
4210076.1680237099654-0.212868233469965-0.2128682334699591.73293648233913
436371.2077588744987-0.252364397715427-0.252364397715412-0.57283475820073
4410583.716784145225-0.152464752571454-0.1524647525714481.54266391815988
458283.0393997196763-0.15640294683904-0.156402946839037-0.0635256851394398
468182.2413689994438-0.161074340705346-0.161074340705344-0.0777035772676028
477579.5098014793877-0.179386210190529-0.179386210190526-0.31143553132203
4810287.8171010789431-0.119908844213833-0.1199088442138291.02853430230651
4912198.1776819174024-0.3793096879559334.172406550804751.38956317594774
509898.0252746964262-0.375826139151869-0.3758261225375970.0256752901354777
517689.5513253908031-0.471636486457162-0.471636486457159-0.949061240999819
527784.7142597425776-0.513397333758966-0.513397333758954-0.520171727264672
536376.4679979986347-0.576211521288825-0.576211521288825-0.929148216676307
543761.6153897904082-0.679051357237957-0.679051357237949-1.72302404684088
553551.5421476914966-0.741189246903016-0.74118924690301-1.13660581211524
562340.7466736898813-0.803861374442624-0.803861374442622-1.21823087130073
574040.2625459278629-0.801948470484995-0.8019484704849970.0387744145950826
582935.8754051750071-0.822793627867969-0.822793627867971-0.435015167393195
593736.0806287833306-0.816936800784508-0.8169368007845080.124779243972586
605141.405660220916-0.782464314722718-0.7824643147227170.745672599417945
612030.8153767838903-0.5899092288344456.48900150919837-1.279585966529
622829.5928933412231-0.597939928812293-0.597939920563781-0.0725787026247534
631323.1643183552676-0.654977398415994-0.654977398415999-0.688443432850374
642222.5639431529498-0.654545207506706-0.6545452075067080.00653550060775628
652523.3065338911663-0.645145844215529-0.6451458442155360.168379160131107
661319.3067220412691-0.665180437087382-0.665180437087384-0.405776123833527
671617.9072739523356-0.669211175911668-0.669211175911662-0.0889978050842206
681315.9132663149514-0.676071447352509-0.676071447352512-0.16076479784892
691615.7710514379218-0.673415469723601-0.6734154697236080.0648302157182754
701716.0530129291284-0.668791873285651-0.6687918732856560.116070036320855
71913.2647382267234-0.678852257083944-0.678852257083948-0.257571299026808
721714.474298716351-0.670013552461919-0.6700135524619240.229532515874097
732515.108449006495-0.6912306509923047.603537153833140.168326295847529
741414.5224713509079-0.690091593231922-0.6900915861942640.0121933502692135
75811.8921752132776-0.70626982489225-0.706269824892256-0.230287014259581
7679.88411968581251-0.715057227382575-0.715057227382578-0.156306743880956
77109.74499100932264-0.711750640282349-0.7117506402823570.0695565560216735
7878.5420505169198-0.714255871124857-0.714255871124858-0.0595069935749557
79108.89933968796462-0.709228708394633-0.7092287083946270.13004200098421
8036.52786353797613-0.716590430051621-0.716590430051623-0.201933369810557

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 37 & 37 & 0 & 0 & 0 \tabularnewline
2 & 30 & 34.0671084683152 & -0.315647737605578 & -0.315647736427373 & -0.291557373517879 \tabularnewline
3 & 47 & 39.2754264764508 & 0.113018011723658 & 0.113018011723659 & 0.578107229803196 \tabularnewline
4 & 35 & 37.5988246308343 & 0.00609094563953931 & 0.00609094563953918 & -0.194826689667111 \tabularnewline
5 & 30 & 34.6319916351207 & -0.138701841033797 & -0.138701841033797 & -0.332719357331009 \tabularnewline
6 & 43 & 37.8293313154751 & 0.000285651478039925 & 0.000285651478039441 & 0.380389932390595 \tabularnewline
7 & 82 & 54.7345619495909 & 0.626347559156922 & 0.626347559156927 & 1.95163537628377 \tabularnewline
8 & 40 & 49.2755392312059 & 0.420159263049224 & 0.420159263049225 & -0.708355608548318 \tabularnewline
9 & 47 & 48.5140116904391 & 0.382764616908484 & 0.382764616908483 & -0.138315762937479 \tabularnewline
10 & 19 & 37.4418372120646 & 0.0393364740124896 & 0.0393364740124888 & -1.34590443528714 \tabularnewline
11 & 52 & 42.9493181839653 & 0.196170716196749 & 0.196170716196749 & 0.644219298247049 \tabularnewline
12 & 136 & 78.0934247492387 & 1.16140934468356 & 1.16140934468356 & 4.12554663261248 \tabularnewline
13 & 80 & 82.4051286708224 & 0.80364042060951 & -8.84004463046803 & 0.530695410877487 \tabularnewline
14 & 42 & 65.0516154526565 & 0.0542732848642011 & 0.0542732963455695 & -1.77265794230896 \tabularnewline
15 & 54 & 60.6291425143458 & -0.0882433308543582 & -0.0882433308543578 & -0.486103540577851 \tabularnewline
16 & 66 & 62.6908737068595 & -0.0332820722718497 & -0.0332820722718471 & 0.244989299768335 \tabularnewline
17 & 81 & 69.6599818228498 & 0.117306979808654 & 0.117306979808654 & 0.817044166011647 \tabularnewline
18 & 63 & 67.1730867901086 & 0.0681274579056146 & 0.0681274579056192 & -0.307662324769699 \tabularnewline
19 & 137 & 93.4364576199204 & 0.517994326337198 & 0.517994326337212 & 3.1162063703195 \tabularnewline
20 & 72 & 85.5313682451499 & 0.38294713691471 & 0.382947136914715 & -1.00607626554196 \tabularnewline
21 & 107 & 93.6608381430816 & 0.501077594993005 & 0.501077594993009 & 0.9275531513865 \tabularnewline
22 & 58 & 80.4581273622528 & 0.299769564099028 & 0.299769564099028 & -1.64344369578804 \tabularnewline
23 & 36 & 63.9281949779611 & 0.0595839553565228 & 0.0595839553565231 & -2.02042797110162 \tabularnewline
24 & 52 & 59.4900687927589 & -0.00312603724857599 & -0.00312603724857725 & -0.540347391451251 \tabularnewline
25 & 79 & 65.1690061308232 & -0.296958211399415 & 3.26654031184217 & 0.816165034938507 \tabularnewline
26 & 77 & 69.9327176459754 & -0.163315952086191 & -0.163315940683743 & 0.539272848318194 \tabularnewline
27 & 54 & 63.6966200267842 & -0.286952606481319 & -0.286952606481318 & -0.689459782507756 \tabularnewline
28 & 84 & 71.3619353166006 & -0.156428681746955 & -0.156428681746952 & 0.929872417151113 \tabularnewline
29 & 48 & 62.5185472531176 & -0.277017599763187 & -0.277017599763188 & -1.03081304137439 \tabularnewline
30 & 96 & 74.9979214913174 & -0.120646338805327 & -0.12064633880532 & 1.52551249199436 \tabularnewline
31 & 83 & 77.9573560353658 & -0.0861220408536572 & -0.0861220408536415 & 0.369942031745338 \tabularnewline
32 & 66 & 73.4756554429748 & -0.132363329073147 & -0.132363329073143 & -0.529281927821184 \tabularnewline
33 & 61 & 68.7937784892558 & -0.178117807681694 & -0.178117807681693 & -0.548659557440484 \tabularnewline
34 & 53 & 62.8678232746454 & -0.234077740099448 & -0.234077740099449 & -0.693843430345268 \tabularnewline
35 & 30 & 50.5756045527 & -0.348675410251912 & -0.348675410251913 & -1.45649856799668 \tabularnewline
36 & 74 & 59.201717621918 & -0.264959389992083 & -0.264959389992084 & 1.08452209063264 \tabularnewline
37 & 69 & 61.189327537834 & -0.340371242450991 & 3.74408365558586 & 0.306763104031148 \tabularnewline
38 & 59 & 60.2507045208828 & -0.351987472511584 & -0.351987460882836 & -0.0662477604985646 \tabularnewline
39 & 42 & 53.1654628941224 & -0.45275420241595 & -0.452754202415951 & -0.780050188218372 \tabularnewline
40 & 65 & 57.5263499866064 & -0.394569173721769 & -0.394569173721767 & 0.569637433888833 \tabularnewline
41 & 70 & 62.1044147537634 & -0.34360563927063 & -0.343605639270632 & 0.594750079697018 \tabularnewline
42 & 100 & 76.1680237099654 & -0.212868233469965 & -0.212868233469959 & 1.73293648233913 \tabularnewline
43 & 63 & 71.2077588744987 & -0.252364397715427 & -0.252364397715412 & -0.57283475820073 \tabularnewline
44 & 105 & 83.716784145225 & -0.152464752571454 & -0.152464752571448 & 1.54266391815988 \tabularnewline
45 & 82 & 83.0393997196763 & -0.15640294683904 & -0.156402946839037 & -0.0635256851394398 \tabularnewline
46 & 81 & 82.2413689994438 & -0.161074340705346 & -0.161074340705344 & -0.0777035772676028 \tabularnewline
47 & 75 & 79.5098014793877 & -0.179386210190529 & -0.179386210190526 & -0.31143553132203 \tabularnewline
48 & 102 & 87.8171010789431 & -0.119908844213833 & -0.119908844213829 & 1.02853430230651 \tabularnewline
49 & 121 & 98.1776819174024 & -0.379309687955933 & 4.17240655080475 & 1.38956317594774 \tabularnewline
50 & 98 & 98.0252746964262 & -0.375826139151869 & -0.375826122537597 & 0.0256752901354777 \tabularnewline
51 & 76 & 89.5513253908031 & -0.471636486457162 & -0.471636486457159 & -0.949061240999819 \tabularnewline
52 & 77 & 84.7142597425776 & -0.513397333758966 & -0.513397333758954 & -0.520171727264672 \tabularnewline
53 & 63 & 76.4679979986347 & -0.576211521288825 & -0.576211521288825 & -0.929148216676307 \tabularnewline
54 & 37 & 61.6153897904082 & -0.679051357237957 & -0.679051357237949 & -1.72302404684088 \tabularnewline
55 & 35 & 51.5421476914966 & -0.741189246903016 & -0.74118924690301 & -1.13660581211524 \tabularnewline
56 & 23 & 40.7466736898813 & -0.803861374442624 & -0.803861374442622 & -1.21823087130073 \tabularnewline
57 & 40 & 40.2625459278629 & -0.801948470484995 & -0.801948470484997 & 0.0387744145950826 \tabularnewline
58 & 29 & 35.8754051750071 & -0.822793627867969 & -0.822793627867971 & -0.435015167393195 \tabularnewline
59 & 37 & 36.0806287833306 & -0.816936800784508 & -0.816936800784508 & 0.124779243972586 \tabularnewline
60 & 51 & 41.405660220916 & -0.782464314722718 & -0.782464314722717 & 0.745672599417945 \tabularnewline
61 & 20 & 30.8153767838903 & -0.589909228834445 & 6.48900150919837 & -1.279585966529 \tabularnewline
62 & 28 & 29.5928933412231 & -0.597939928812293 & -0.597939920563781 & -0.0725787026247534 \tabularnewline
63 & 13 & 23.1643183552676 & -0.654977398415994 & -0.654977398415999 & -0.688443432850374 \tabularnewline
64 & 22 & 22.5639431529498 & -0.654545207506706 & -0.654545207506708 & 0.00653550060775628 \tabularnewline
65 & 25 & 23.3065338911663 & -0.645145844215529 & -0.645145844215536 & 0.168379160131107 \tabularnewline
66 & 13 & 19.3067220412691 & -0.665180437087382 & -0.665180437087384 & -0.405776123833527 \tabularnewline
67 & 16 & 17.9072739523356 & -0.669211175911668 & -0.669211175911662 & -0.0889978050842206 \tabularnewline
68 & 13 & 15.9132663149514 & -0.676071447352509 & -0.676071447352512 & -0.16076479784892 \tabularnewline
69 & 16 & 15.7710514379218 & -0.673415469723601 & -0.673415469723608 & 0.0648302157182754 \tabularnewline
70 & 17 & 16.0530129291284 & -0.668791873285651 & -0.668791873285656 & 0.116070036320855 \tabularnewline
71 & 9 & 13.2647382267234 & -0.678852257083944 & -0.678852257083948 & -0.257571299026808 \tabularnewline
72 & 17 & 14.474298716351 & -0.670013552461919 & -0.670013552461924 & 0.229532515874097 \tabularnewline
73 & 25 & 15.108449006495 & -0.691230650992304 & 7.60353715383314 & 0.168326295847529 \tabularnewline
74 & 14 & 14.5224713509079 & -0.690091593231922 & -0.690091586194264 & 0.0121933502692135 \tabularnewline
75 & 8 & 11.8921752132776 & -0.70626982489225 & -0.706269824892256 & -0.230287014259581 \tabularnewline
76 & 7 & 9.88411968581251 & -0.715057227382575 & -0.715057227382578 & -0.156306743880956 \tabularnewline
77 & 10 & 9.74499100932264 & -0.711750640282349 & -0.711750640282357 & 0.0695565560216735 \tabularnewline
78 & 7 & 8.5420505169198 & -0.714255871124857 & -0.714255871124858 & -0.0595069935749557 \tabularnewline
79 & 10 & 8.89933968796462 & -0.709228708394633 & -0.709228708394627 & 0.13004200098421 \tabularnewline
80 & 3 & 6.52786353797613 & -0.716590430051621 & -0.716590430051623 & -0.201933369810557 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=198136&T=1

[TABLE]
[ROW][C]Structural Time Series Model[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Level[/C][C]Slope[/C][C]Seasonal[/C][C]Stand. Residuals[/C][/ROW]
[ROW][C]1[/C][C]37[/C][C]37[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]30[/C][C]34.0671084683152[/C][C]-0.315647737605578[/C][C]-0.315647736427373[/C][C]-0.291557373517879[/C][/ROW]
[ROW][C]3[/C][C]47[/C][C]39.2754264764508[/C][C]0.113018011723658[/C][C]0.113018011723659[/C][C]0.578107229803196[/C][/ROW]
[ROW][C]4[/C][C]35[/C][C]37.5988246308343[/C][C]0.00609094563953931[/C][C]0.00609094563953918[/C][C]-0.194826689667111[/C][/ROW]
[ROW][C]5[/C][C]30[/C][C]34.6319916351207[/C][C]-0.138701841033797[/C][C]-0.138701841033797[/C][C]-0.332719357331009[/C][/ROW]
[ROW][C]6[/C][C]43[/C][C]37.8293313154751[/C][C]0.000285651478039925[/C][C]0.000285651478039441[/C][C]0.380389932390595[/C][/ROW]
[ROW][C]7[/C][C]82[/C][C]54.7345619495909[/C][C]0.626347559156922[/C][C]0.626347559156927[/C][C]1.95163537628377[/C][/ROW]
[ROW][C]8[/C][C]40[/C][C]49.2755392312059[/C][C]0.420159263049224[/C][C]0.420159263049225[/C][C]-0.708355608548318[/C][/ROW]
[ROW][C]9[/C][C]47[/C][C]48.5140116904391[/C][C]0.382764616908484[/C][C]0.382764616908483[/C][C]-0.138315762937479[/C][/ROW]
[ROW][C]10[/C][C]19[/C][C]37.4418372120646[/C][C]0.0393364740124896[/C][C]0.0393364740124888[/C][C]-1.34590443528714[/C][/ROW]
[ROW][C]11[/C][C]52[/C][C]42.9493181839653[/C][C]0.196170716196749[/C][C]0.196170716196749[/C][C]0.644219298247049[/C][/ROW]
[ROW][C]12[/C][C]136[/C][C]78.0934247492387[/C][C]1.16140934468356[/C][C]1.16140934468356[/C][C]4.12554663261248[/C][/ROW]
[ROW][C]13[/C][C]80[/C][C]82.4051286708224[/C][C]0.80364042060951[/C][C]-8.84004463046803[/C][C]0.530695410877487[/C][/ROW]
[ROW][C]14[/C][C]42[/C][C]65.0516154526565[/C][C]0.0542732848642011[/C][C]0.0542732963455695[/C][C]-1.77265794230896[/C][/ROW]
[ROW][C]15[/C][C]54[/C][C]60.6291425143458[/C][C]-0.0882433308543582[/C][C]-0.0882433308543578[/C][C]-0.486103540577851[/C][/ROW]
[ROW][C]16[/C][C]66[/C][C]62.6908737068595[/C][C]-0.0332820722718497[/C][C]-0.0332820722718471[/C][C]0.244989299768335[/C][/ROW]
[ROW][C]17[/C][C]81[/C][C]69.6599818228498[/C][C]0.117306979808654[/C][C]0.117306979808654[/C][C]0.817044166011647[/C][/ROW]
[ROW][C]18[/C][C]63[/C][C]67.1730867901086[/C][C]0.0681274579056146[/C][C]0.0681274579056192[/C][C]-0.307662324769699[/C][/ROW]
[ROW][C]19[/C][C]137[/C][C]93.4364576199204[/C][C]0.517994326337198[/C][C]0.517994326337212[/C][C]3.1162063703195[/C][/ROW]
[ROW][C]20[/C][C]72[/C][C]85.5313682451499[/C][C]0.38294713691471[/C][C]0.382947136914715[/C][C]-1.00607626554196[/C][/ROW]
[ROW][C]21[/C][C]107[/C][C]93.6608381430816[/C][C]0.501077594993005[/C][C]0.501077594993009[/C][C]0.9275531513865[/C][/ROW]
[ROW][C]22[/C][C]58[/C][C]80.4581273622528[/C][C]0.299769564099028[/C][C]0.299769564099028[/C][C]-1.64344369578804[/C][/ROW]
[ROW][C]23[/C][C]36[/C][C]63.9281949779611[/C][C]0.0595839553565228[/C][C]0.0595839553565231[/C][C]-2.02042797110162[/C][/ROW]
[ROW][C]24[/C][C]52[/C][C]59.4900687927589[/C][C]-0.00312603724857599[/C][C]-0.00312603724857725[/C][C]-0.540347391451251[/C][/ROW]
[ROW][C]25[/C][C]79[/C][C]65.1690061308232[/C][C]-0.296958211399415[/C][C]3.26654031184217[/C][C]0.816165034938507[/C][/ROW]
[ROW][C]26[/C][C]77[/C][C]69.9327176459754[/C][C]-0.163315952086191[/C][C]-0.163315940683743[/C][C]0.539272848318194[/C][/ROW]
[ROW][C]27[/C][C]54[/C][C]63.6966200267842[/C][C]-0.286952606481319[/C][C]-0.286952606481318[/C][C]-0.689459782507756[/C][/ROW]
[ROW][C]28[/C][C]84[/C][C]71.3619353166006[/C][C]-0.156428681746955[/C][C]-0.156428681746952[/C][C]0.929872417151113[/C][/ROW]
[ROW][C]29[/C][C]48[/C][C]62.5185472531176[/C][C]-0.277017599763187[/C][C]-0.277017599763188[/C][C]-1.03081304137439[/C][/ROW]
[ROW][C]30[/C][C]96[/C][C]74.9979214913174[/C][C]-0.120646338805327[/C][C]-0.12064633880532[/C][C]1.52551249199436[/C][/ROW]
[ROW][C]31[/C][C]83[/C][C]77.9573560353658[/C][C]-0.0861220408536572[/C][C]-0.0861220408536415[/C][C]0.369942031745338[/C][/ROW]
[ROW][C]32[/C][C]66[/C][C]73.4756554429748[/C][C]-0.132363329073147[/C][C]-0.132363329073143[/C][C]-0.529281927821184[/C][/ROW]
[ROW][C]33[/C][C]61[/C][C]68.7937784892558[/C][C]-0.178117807681694[/C][C]-0.178117807681693[/C][C]-0.548659557440484[/C][/ROW]
[ROW][C]34[/C][C]53[/C][C]62.8678232746454[/C][C]-0.234077740099448[/C][C]-0.234077740099449[/C][C]-0.693843430345268[/C][/ROW]
[ROW][C]35[/C][C]30[/C][C]50.5756045527[/C][C]-0.348675410251912[/C][C]-0.348675410251913[/C][C]-1.45649856799668[/C][/ROW]
[ROW][C]36[/C][C]74[/C][C]59.201717621918[/C][C]-0.264959389992083[/C][C]-0.264959389992084[/C][C]1.08452209063264[/C][/ROW]
[ROW][C]37[/C][C]69[/C][C]61.189327537834[/C][C]-0.340371242450991[/C][C]3.74408365558586[/C][C]0.306763104031148[/C][/ROW]
[ROW][C]38[/C][C]59[/C][C]60.2507045208828[/C][C]-0.351987472511584[/C][C]-0.351987460882836[/C][C]-0.0662477604985646[/C][/ROW]
[ROW][C]39[/C][C]42[/C][C]53.1654628941224[/C][C]-0.45275420241595[/C][C]-0.452754202415951[/C][C]-0.780050188218372[/C][/ROW]
[ROW][C]40[/C][C]65[/C][C]57.5263499866064[/C][C]-0.394569173721769[/C][C]-0.394569173721767[/C][C]0.569637433888833[/C][/ROW]
[ROW][C]41[/C][C]70[/C][C]62.1044147537634[/C][C]-0.34360563927063[/C][C]-0.343605639270632[/C][C]0.594750079697018[/C][/ROW]
[ROW][C]42[/C][C]100[/C][C]76.1680237099654[/C][C]-0.212868233469965[/C][C]-0.212868233469959[/C][C]1.73293648233913[/C][/ROW]
[ROW][C]43[/C][C]63[/C][C]71.2077588744987[/C][C]-0.252364397715427[/C][C]-0.252364397715412[/C][C]-0.57283475820073[/C][/ROW]
[ROW][C]44[/C][C]105[/C][C]83.716784145225[/C][C]-0.152464752571454[/C][C]-0.152464752571448[/C][C]1.54266391815988[/C][/ROW]
[ROW][C]45[/C][C]82[/C][C]83.0393997196763[/C][C]-0.15640294683904[/C][C]-0.156402946839037[/C][C]-0.0635256851394398[/C][/ROW]
[ROW][C]46[/C][C]81[/C][C]82.2413689994438[/C][C]-0.161074340705346[/C][C]-0.161074340705344[/C][C]-0.0777035772676028[/C][/ROW]
[ROW][C]47[/C][C]75[/C][C]79.5098014793877[/C][C]-0.179386210190529[/C][C]-0.179386210190526[/C][C]-0.31143553132203[/C][/ROW]
[ROW][C]48[/C][C]102[/C][C]87.8171010789431[/C][C]-0.119908844213833[/C][C]-0.119908844213829[/C][C]1.02853430230651[/C][/ROW]
[ROW][C]49[/C][C]121[/C][C]98.1776819174024[/C][C]-0.379309687955933[/C][C]4.17240655080475[/C][C]1.38956317594774[/C][/ROW]
[ROW][C]50[/C][C]98[/C][C]98.0252746964262[/C][C]-0.375826139151869[/C][C]-0.375826122537597[/C][C]0.0256752901354777[/C][/ROW]
[ROW][C]51[/C][C]76[/C][C]89.5513253908031[/C][C]-0.471636486457162[/C][C]-0.471636486457159[/C][C]-0.949061240999819[/C][/ROW]
[ROW][C]52[/C][C]77[/C][C]84.7142597425776[/C][C]-0.513397333758966[/C][C]-0.513397333758954[/C][C]-0.520171727264672[/C][/ROW]
[ROW][C]53[/C][C]63[/C][C]76.4679979986347[/C][C]-0.576211521288825[/C][C]-0.576211521288825[/C][C]-0.929148216676307[/C][/ROW]
[ROW][C]54[/C][C]37[/C][C]61.6153897904082[/C][C]-0.679051357237957[/C][C]-0.679051357237949[/C][C]-1.72302404684088[/C][/ROW]
[ROW][C]55[/C][C]35[/C][C]51.5421476914966[/C][C]-0.741189246903016[/C][C]-0.74118924690301[/C][C]-1.13660581211524[/C][/ROW]
[ROW][C]56[/C][C]23[/C][C]40.7466736898813[/C][C]-0.803861374442624[/C][C]-0.803861374442622[/C][C]-1.21823087130073[/C][/ROW]
[ROW][C]57[/C][C]40[/C][C]40.2625459278629[/C][C]-0.801948470484995[/C][C]-0.801948470484997[/C][C]0.0387744145950826[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]35.8754051750071[/C][C]-0.822793627867969[/C][C]-0.822793627867971[/C][C]-0.435015167393195[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]36.0806287833306[/C][C]-0.816936800784508[/C][C]-0.816936800784508[/C][C]0.124779243972586[/C][/ROW]
[ROW][C]60[/C][C]51[/C][C]41.405660220916[/C][C]-0.782464314722718[/C][C]-0.782464314722717[/C][C]0.745672599417945[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]30.8153767838903[/C][C]-0.589909228834445[/C][C]6.48900150919837[/C][C]-1.279585966529[/C][/ROW]
[ROW][C]62[/C][C]28[/C][C]29.5928933412231[/C][C]-0.597939928812293[/C][C]-0.597939920563781[/C][C]-0.0725787026247534[/C][/ROW]
[ROW][C]63[/C][C]13[/C][C]23.1643183552676[/C][C]-0.654977398415994[/C][C]-0.654977398415999[/C][C]-0.688443432850374[/C][/ROW]
[ROW][C]64[/C][C]22[/C][C]22.5639431529498[/C][C]-0.654545207506706[/C][C]-0.654545207506708[/C][C]0.00653550060775628[/C][/ROW]
[ROW][C]65[/C][C]25[/C][C]23.3065338911663[/C][C]-0.645145844215529[/C][C]-0.645145844215536[/C][C]0.168379160131107[/C][/ROW]
[ROW][C]66[/C][C]13[/C][C]19.3067220412691[/C][C]-0.665180437087382[/C][C]-0.665180437087384[/C][C]-0.405776123833527[/C][/ROW]
[ROW][C]67[/C][C]16[/C][C]17.9072739523356[/C][C]-0.669211175911668[/C][C]-0.669211175911662[/C][C]-0.0889978050842206[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.9132663149514[/C][C]-0.676071447352509[/C][C]-0.676071447352512[/C][C]-0.16076479784892[/C][/ROW]
[ROW][C]69[/C][C]16[/C][C]15.7710514379218[/C][C]-0.673415469723601[/C][C]-0.673415469723608[/C][C]0.0648302157182754[/C][/ROW]
[ROW][C]70[/C][C]17[/C][C]16.0530129291284[/C][C]-0.668791873285651[/C][C]-0.668791873285656[/C][C]0.116070036320855[/C][/ROW]
[ROW][C]71[/C][C]9[/C][C]13.2647382267234[/C][C]-0.678852257083944[/C][C]-0.678852257083948[/C][C]-0.257571299026808[/C][/ROW]
[ROW][C]72[/C][C]17[/C][C]14.474298716351[/C][C]-0.670013552461919[/C][C]-0.670013552461924[/C][C]0.229532515874097[/C][/ROW]
[ROW][C]73[/C][C]25[/C][C]15.108449006495[/C][C]-0.691230650992304[/C][C]7.60353715383314[/C][C]0.168326295847529[/C][/ROW]
[ROW][C]74[/C][C]14[/C][C]14.5224713509079[/C][C]-0.690091593231922[/C][C]-0.690091586194264[/C][C]0.0121933502692135[/C][/ROW]
[ROW][C]75[/C][C]8[/C][C]11.8921752132776[/C][C]-0.70626982489225[/C][C]-0.706269824892256[/C][C]-0.230287014259581[/C][/ROW]
[ROW][C]76[/C][C]7[/C][C]9.88411968581251[/C][C]-0.715057227382575[/C][C]-0.715057227382578[/C][C]-0.156306743880956[/C][/ROW]
[ROW][C]77[/C][C]10[/C][C]9.74499100932264[/C][C]-0.711750640282349[/C][C]-0.711750640282357[/C][C]0.0695565560216735[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]8.5420505169198[/C][C]-0.714255871124857[/C][C]-0.714255871124858[/C][C]-0.0595069935749557[/C][/ROW]
[ROW][C]79[/C][C]10[/C][C]8.89933968796462[/C][C]-0.709228708394633[/C][C]-0.709228708394627[/C][C]0.13004200098421[/C][/ROW]
[ROW][C]80[/C][C]3[/C][C]6.52786353797613[/C][C]-0.716590430051621[/C][C]-0.716590430051623[/C][C]-0.201933369810557[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=198136&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=198136&T=1

As an alternative you can also use a QR Code:  

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

Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
13737000
23034.0671084683152-0.315647737605578-0.315647736427373-0.291557373517879
34739.27542647645080.1130180117236580.1130180117236590.578107229803196
43537.59882463083430.006090945639539310.00609094563953918-0.194826689667111
53034.6319916351207-0.138701841033797-0.138701841033797-0.332719357331009
64337.82933131547510.0002856514780399250.0002856514780394410.380389932390595
78254.73456194959090.6263475591569220.6263475591569271.95163537628377
84049.27553923120590.4201592630492240.420159263049225-0.708355608548318
94748.51401169043910.3827646169084840.382764616908483-0.138315762937479
101937.44183721206460.03933647401248960.0393364740124888-1.34590443528714
115242.94931818396530.1961707161967490.1961707161967490.644219298247049
1213678.09342474923871.161409344683561.161409344683564.12554663261248
138082.40512867082240.80364042060951-8.840044630468030.530695410877487
144265.05161545265650.05427328486420110.0542732963455695-1.77265794230896
155460.6291425143458-0.0882433308543582-0.0882433308543578-0.486103540577851
166662.6908737068595-0.0332820722718497-0.03328207227184710.244989299768335
178169.65998182284980.1173069798086540.1173069798086540.817044166011647
186367.17308679010860.06812745790561460.0681274579056192-0.307662324769699
1913793.43645761992040.5179943263371980.5179943263372123.1162063703195
207285.53136824514990.382947136914710.382947136914715-1.00607626554196
2110793.66083814308160.5010775949930050.5010775949930090.9275531513865
225880.45812736225280.2997695640990280.299769564099028-1.64344369578804
233663.92819497796110.05958395535652280.0595839553565231-2.02042797110162
245259.4900687927589-0.00312603724857599-0.00312603724857725-0.540347391451251
257965.1690061308232-0.2969582113994153.266540311842170.816165034938507
267769.9327176459754-0.163315952086191-0.1633159406837430.539272848318194
275463.6966200267842-0.286952606481319-0.286952606481318-0.689459782507756
288471.3619353166006-0.156428681746955-0.1564286817469520.929872417151113
294862.5185472531176-0.277017599763187-0.277017599763188-1.03081304137439
309674.9979214913174-0.120646338805327-0.120646338805321.52551249199436
318377.9573560353658-0.0861220408536572-0.08612204085364150.369942031745338
326673.4756554429748-0.132363329073147-0.132363329073143-0.529281927821184
336168.7937784892558-0.178117807681694-0.178117807681693-0.548659557440484
345362.8678232746454-0.234077740099448-0.234077740099449-0.693843430345268
353050.5756045527-0.348675410251912-0.348675410251913-1.45649856799668
367459.201717621918-0.264959389992083-0.2649593899920841.08452209063264
376961.189327537834-0.3403712424509913.744083655585860.306763104031148
385960.2507045208828-0.351987472511584-0.351987460882836-0.0662477604985646
394253.1654628941224-0.45275420241595-0.452754202415951-0.780050188218372
406557.5263499866064-0.394569173721769-0.3945691737217670.569637433888833
417062.1044147537634-0.34360563927063-0.3436056392706320.594750079697018
4210076.1680237099654-0.212868233469965-0.2128682334699591.73293648233913
436371.2077588744987-0.252364397715427-0.252364397715412-0.57283475820073
4410583.716784145225-0.152464752571454-0.1524647525714481.54266391815988
458283.0393997196763-0.15640294683904-0.156402946839037-0.0635256851394398
468182.2413689994438-0.161074340705346-0.161074340705344-0.0777035772676028
477579.5098014793877-0.179386210190529-0.179386210190526-0.31143553132203
4810287.8171010789431-0.119908844213833-0.1199088442138291.02853430230651
4912198.1776819174024-0.3793096879559334.172406550804751.38956317594774
509898.0252746964262-0.375826139151869-0.3758261225375970.0256752901354777
517689.5513253908031-0.471636486457162-0.471636486457159-0.949061240999819
527784.7142597425776-0.513397333758966-0.513397333758954-0.520171727264672
536376.4679979986347-0.576211521288825-0.576211521288825-0.929148216676307
543761.6153897904082-0.679051357237957-0.679051357237949-1.72302404684088
553551.5421476914966-0.741189246903016-0.74118924690301-1.13660581211524
562340.7466736898813-0.803861374442624-0.803861374442622-1.21823087130073
574040.2625459278629-0.801948470484995-0.8019484704849970.0387744145950826
582935.8754051750071-0.822793627867969-0.822793627867971-0.435015167393195
593736.0806287833306-0.816936800784508-0.8169368007845080.124779243972586
605141.405660220916-0.782464314722718-0.7824643147227170.745672599417945
612030.8153767838903-0.5899092288344456.48900150919837-1.279585966529
622829.5928933412231-0.597939928812293-0.597939920563781-0.0725787026247534
631323.1643183552676-0.654977398415994-0.654977398415999-0.688443432850374
642222.5639431529498-0.654545207506706-0.6545452075067080.00653550060775628
652523.3065338911663-0.645145844215529-0.6451458442155360.168379160131107
661319.3067220412691-0.665180437087382-0.665180437087384-0.405776123833527
671617.9072739523356-0.669211175911668-0.669211175911662-0.0889978050842206
681315.9132663149514-0.676071447352509-0.676071447352512-0.16076479784892
691615.7710514379218-0.673415469723601-0.6734154697236080.0648302157182754
701716.0530129291284-0.668791873285651-0.6687918732856560.116070036320855
71913.2647382267234-0.678852257083944-0.678852257083948-0.257571299026808
721714.474298716351-0.670013552461919-0.6700135524619240.229532515874097
732515.108449006495-0.6912306509923047.603537153833140.168326295847529
741414.5224713509079-0.690091593231922-0.6900915861942640.0121933502692135
75811.8921752132776-0.70626982489225-0.706269824892256-0.230287014259581
7679.88411968581251-0.715057227382575-0.715057227382578-0.156306743880956
77109.74499100932264-0.711750640282349-0.7117506402823570.0695565560216735
7878.5420505169198-0.714255871124857-0.714255871124858-0.0595069935749557
79108.89933968796462-0.709228708394633-0.7092287083946270.13004200098421
8036.52786353797613-0.716590430051621-0.716590430051623-0.201933369810557



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
nx <- length(x)
x <- ts(x,frequency=par1)
m <- StructTS(x,type='BSM')
m$coef
m$fitted
m$resid
mylevel <- as.numeric(m$fitted[,'level'])
myslope <- as.numeric(m$fitted[,'slope'])
myseas <- as.numeric(m$fitted[,'sea'])
myresid <- as.numeric(m$resid)
myfit <- mylevel+myseas
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(mylevel,main='Level')
spectrum(myseas,main='Seasonal')
spectrum(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(mylevel,main='Level')
cpgram(myseas,main='Seasonal')
cpgram(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b')
grid()
dev.off()
bitmap(file='test5.png')
op <- par(mfrow = c(2,2))
hist(m$resid,main='Residual Histogram')
plot(density(m$resid),main='Residual Kernel Density')
qqnorm(m$resid,main='Residual Normal QQ Plot')
qqline(m$resid)
plot(m$resid^2, myfit^2,main='Sq.Resid vs. Sq.Fit',xlab='Squared residuals',ylab='Squared Fit')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Structural Time Series Model',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Level',header=TRUE)
a<-table.element(a,'Slope',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Stand. Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,mylevel[i])
a<-table.element(a,myslope[i])
a<-table.element(a,myseas[i])
a<-table.element(a,myresid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')