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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationWed, 28 Nov 2012 10:13:59 -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/2012/Nov/28/t1354115783mr59mhi4x9zszxu.htm/, Retrieved Fri, 29 Mar 2024 15:04:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=194173, Retrieved Fri, 29 Mar 2024 15:04:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [STSM ] [2012-11-28 15:13:59] [64435dfec13c3cda39d1733fd4b6eb52] [Current]
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Dataseries X:
54.3
55.9
63.9
64
60.7
67.8
70.5
76.6
76.2
71.8
67.8
69.7
76.7
74.2
75.8
84.3
84.9
84.4
89.4
88.5
76.5
71.4
72.1
75.8
66.6
71.7
75.4
80.9
80.7
85
91.5
87.7
95.3
102.4
114.2
111.7
113.7
118.8
129
136.4
155
166
168.7
145.5
127.3
91.5
69
54
56.3
54.2
59.3
63.4
73.3
86.7
81.3
89.6
85.3
92.4
96.8
93.6
97.6
94.2
99.9
106.4
96
94.9
94.8
95.9
96.2
103.1
106.9
114.2
118.2
123.9
137.1
146.2
136.4
133.2
135.9
127.1
128.5
126.6
132.6
130.9




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 5 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194173&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194173&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194173&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 time5 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
154.354.3000
255.955.6528957538061.329638883922960.01162843512773050.244182411767075
363.963.21455106579956.38744776294528-0.003124093741765020.86748984538436
46464.54924311073982.248432092388150.00526977113022229-0.700950632898699
560.761.2916313885406-2.273329873980940.00725201835561575-0.760540076715445
667.866.93205327949344.227206460204290.007524648566013351.0930672251612
770.570.55788880309933.733220313758570.00749601090311243-0.0830639146293572
876.676.36680264293255.438209044494080.007524306438245070.286692714869682
976.276.74283728538671.280160982164290.00752329432929318-0.699172706032201
1071.872.4034293180019-3.335721738574510.00753040470628784-0.77615726826237
1167.867.9175178203661-4.280481969216920.00753094711094032-0.15886073394289
1269.769.09867859334460.2056865263029960.007530704729587190.754345913701614
1376.775.16771035444994.948078022863470.9045848663838850.861916924649272
1474.274.77697883235841.09963499479116-0.165066803609587-0.616666082860674
1575.875.9567200665641.16586005024422-0.1653052678980160.0109625782932496
1684.383.76783662953596.61391101017096-0.182364739658710.911212214021849
1784.985.59877490674592.68820556276126-0.179358359741552-0.660011917228858
1884.484.9430173066845-0.0585949382913024-0.179451314826684-0.461870893766136
1989.489.11876020064253.41972400572855-0.1791480864575670.584874002760128
2088.589.05767067084670.560534437885692-0.179227634576789-0.480770484971255
2176.577.9480262356249-9.02530871722435-0.1792409565361-1.61185243937049
2271.471.3187488891535-7.05722297033667-0.1792453488325010.330932161176523
2372.171.4930400502287-1.11729446068149-0.1792508936555650.998794584238847
2475.875.42977633818493.03406319150497-0.179251369417840.698047718084126
2566.667.0316916994275-6.268723051164450.799628987099629-1.64197256209659
2671.770.79712029398851.250714522111470.03879726773496851.22700705507484
2775.475.04505502011173.724035707014880.03240805900159080.411249881091446
2880.980.66643494373385.280388872687780.02891318104084240.260701610140643
2980.781.18610665561151.372103278240060.0310588978003664-0.657109280167184
308584.73250364537513.158097592673810.0311022284405750.300312886932576
3191.591.11784881446155.809082402354450.03126791188385370.445759629548489
3287.788.5767197493064-1.049855465620920.0311311026678382-1.15332511220963
3395.394.50968870316524.685809671227850.03113681738141670.964447851439359
34102.4102.0576894530187.036797415635950.03113305581088910.395316848963787
35114.2113.6712800052910.79615257172530.03113053992293290.632132788199808
36111.7112.9238850478891.314335378896280.0311313189694011-1.59436054642384
37113.7114.0725461841891.17916309365192-0.354654727612315-0.0235441888955331
38118.8118.4487958714023.62591106779740.05991069893132380.402600272988935
39129128.2810012466548.742148321690340.04960611821257150.85281349947598
40136.4136.4152094088238.243317883738790.0504792805447971-0.0836286765443845
41155153.94391320894615.86702947810150.0472172151960671.2818210519783
42166166.33116456875513.00870645156240.0471631680619227-0.480623984602833
43168.7169.7011806506015.091207960091510.0467775063330202-1.33131801079985
44145.5148.330533450786-16.64471669860190.0464396102097925-3.65487911756718
45127.3127.688186281442-19.92835440974580.0464370603720554-0.552141252759101
4691.593.0525269294973-32.00885593507150.0464521247224927-2.03132739035969
476968.1779150380521-26.14882259241380.04644906822085950.985360271175534
485452.7842490977251-17.31458593192770.04644850251923321.48547035898322
4956.353.777714097656-2.355080490219040.5422401398227952.58600276209511
5054.253.989087394392-0.364895184840919-0.03110467164169540.329034382727596
5159.358.78110141700863.88349738478876-0.0381164554194030.709276061447579
5263.463.36335324172894.45695298337362-0.03893889760737320.0961913555031562
5373.372.79933226803748.54526919026264-0.04037202352096330.687403232130544
5486.786.211205577228512.5427319736869-0.04031009888970950.67216935823443
5581.383.0483860150546-0.358166642588173-0.0408249200529714-2.16927188186462
5689.688.95918897532384.79119031279563-0.04075933937331040.865860459007658
5785.386.1654035825278-1.43907773848499-0.0407633029009632-1.04761496502711
5892.491.68429787477554.27616428660894-0.04076914162426730.961013716855632
5996.896.75444725604074.9283398303846-0.040769420304960.109662835194859
6093.694.429362616358-1.02959003057658-0.0407691077462413-1.00182149850508
6197.696.64685773908781.626113035278350.6016324313605690.456843990226146
6294.294.6283144993426-1.22584169358209-0.0765654908734921-0.472952590658363
6399.999.34128753625453.66449200849069-0.08340238848834390.817345179581761
64106.4106.1465294346146.24239310116854-0.08653384621252680.432578323245557
659697.6812648829564-5.83482456877369-0.0829483696800213-2.0306648521777
6694.994.6753546399883-3.51113947909708-0.082917883772230.390725411122072
6794.894.5181727358684-0.756136190624209-0.0828247726447560.463250919034791
6895.995.76503844593330.889135039079157-0.08280702652449350.276651112086007
6996.296.31922305824430.614008149125127-0.0828071747596534-0.0462623830580563
70103.1102.5699830029335.24400734143831-0.08281118072494080.778530937872914
71106.9107.0643156896474.62822814714216-0.0828109578760966-0.103542815959161
72114.2114.0288116213436.54722788940972-0.0828110431378320.322678387005867
73118.2117.7135872493044.204567751197370.796488087675678-0.40161703405431
74123.9123.7800093277975.67109987925144-0.06272018855355090.24371956023975
75137.1136.41605632072611.4045003088383-0.06967247309468390.959022711175982
76146.2146.42014980548710.2549460049565-0.0684613895499646-0.192951040360867
77136.4138.445749662299-4.71470197374378-0.064607223031978-2.51701659938666
78133.2133.310349902059-5.0602648002802-0.0646111548171201-0.0581060668742213
79135.9135.2079651818130.655046237868486-0.06444363724513060.961023801247411
80127.1128.017478009053-5.7892887798625-0.0645039188823223-1.08361007055046
81128.5127.943168020669-1.09502920199963-0.06450172543946920.78933627596768
82126.6126.682508922703-1.23107676709816-0.0645016233553823-0.0228762973969793
83132.6131.9571957572784.1127267105559-0.06450330052452990.89855660136647
84130.9131.4651362771220.330376239254459-0.0645031547834353-0.635999433604986

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 54.3 & 54.3 & 0 & 0 & 0 \tabularnewline
2 & 55.9 & 55.652895753806 & 1.32963888392296 & 0.0116284351277305 & 0.244182411767075 \tabularnewline
3 & 63.9 & 63.2145510657995 & 6.38744776294528 & -0.00312409374176502 & 0.86748984538436 \tabularnewline
4 & 64 & 64.5492431107398 & 2.24843209238815 & 0.00526977113022229 & -0.700950632898699 \tabularnewline
5 & 60.7 & 61.2916313885406 & -2.27332987398094 & 0.00725201835561575 & -0.760540076715445 \tabularnewline
6 & 67.8 & 66.9320532794934 & 4.22720646020429 & 0.00752464856601335 & 1.0930672251612 \tabularnewline
7 & 70.5 & 70.5578888030993 & 3.73322031375857 & 0.00749601090311243 & -0.0830639146293572 \tabularnewline
8 & 76.6 & 76.3668026429325 & 5.43820904449408 & 0.00752430643824507 & 0.286692714869682 \tabularnewline
9 & 76.2 & 76.7428372853867 & 1.28016098216429 & 0.00752329432929318 & -0.699172706032201 \tabularnewline
10 & 71.8 & 72.4034293180019 & -3.33572173857451 & 0.00753040470628784 & -0.77615726826237 \tabularnewline
11 & 67.8 & 67.9175178203661 & -4.28048196921692 & 0.00753094711094032 & -0.15886073394289 \tabularnewline
12 & 69.7 & 69.0986785933446 & 0.205686526302996 & 0.00753070472958719 & 0.754345913701614 \tabularnewline
13 & 76.7 & 75.1677103544499 & 4.94807802286347 & 0.904584866383885 & 0.861916924649272 \tabularnewline
14 & 74.2 & 74.7769788323584 & 1.09963499479116 & -0.165066803609587 & -0.616666082860674 \tabularnewline
15 & 75.8 & 75.956720066564 & 1.16586005024422 & -0.165305267898016 & 0.0109625782932496 \tabularnewline
16 & 84.3 & 83.7678366295359 & 6.61391101017096 & -0.18236473965871 & 0.911212214021849 \tabularnewline
17 & 84.9 & 85.5987749067459 & 2.68820556276126 & -0.179358359741552 & -0.660011917228858 \tabularnewline
18 & 84.4 & 84.9430173066845 & -0.0585949382913024 & -0.179451314826684 & -0.461870893766136 \tabularnewline
19 & 89.4 & 89.1187602006425 & 3.41972400572855 & -0.179148086457567 & 0.584874002760128 \tabularnewline
20 & 88.5 & 89.0576706708467 & 0.560534437885692 & -0.179227634576789 & -0.480770484971255 \tabularnewline
21 & 76.5 & 77.9480262356249 & -9.02530871722435 & -0.1792409565361 & -1.61185243937049 \tabularnewline
22 & 71.4 & 71.3187488891535 & -7.05722297033667 & -0.179245348832501 & 0.330932161176523 \tabularnewline
23 & 72.1 & 71.4930400502287 & -1.11729446068149 & -0.179250893655565 & 0.998794584238847 \tabularnewline
24 & 75.8 & 75.4297763381849 & 3.03406319150497 & -0.17925136941784 & 0.698047718084126 \tabularnewline
25 & 66.6 & 67.0316916994275 & -6.26872305116445 & 0.799628987099629 & -1.64197256209659 \tabularnewline
26 & 71.7 & 70.7971202939885 & 1.25071452211147 & 0.0387972677349685 & 1.22700705507484 \tabularnewline
27 & 75.4 & 75.0450550201117 & 3.72403570701488 & 0.0324080590015908 & 0.411249881091446 \tabularnewline
28 & 80.9 & 80.6664349437338 & 5.28038887268778 & 0.0289131810408424 & 0.260701610140643 \tabularnewline
29 & 80.7 & 81.1861066556115 & 1.37210327824006 & 0.0310588978003664 & -0.657109280167184 \tabularnewline
30 & 85 & 84.7325036453751 & 3.15809759267381 & 0.031102228440575 & 0.300312886932576 \tabularnewline
31 & 91.5 & 91.1178488144615 & 5.80908240235445 & 0.0312679118838537 & 0.445759629548489 \tabularnewline
32 & 87.7 & 88.5767197493064 & -1.04985546562092 & 0.0311311026678382 & -1.15332511220963 \tabularnewline
33 & 95.3 & 94.5096887031652 & 4.68580967122785 & 0.0311368173814167 & 0.964447851439359 \tabularnewline
34 & 102.4 & 102.057689453018 & 7.03679741563595 & 0.0311330558108891 & 0.395316848963787 \tabularnewline
35 & 114.2 & 113.67128000529 & 10.7961525717253 & 0.0311305399229329 & 0.632132788199808 \tabularnewline
36 & 111.7 & 112.923885047889 & 1.31433537889628 & 0.0311313189694011 & -1.59436054642384 \tabularnewline
37 & 113.7 & 114.072546184189 & 1.17916309365192 & -0.354654727612315 & -0.0235441888955331 \tabularnewline
38 & 118.8 & 118.448795871402 & 3.6259110677974 & 0.0599106989313238 & 0.402600272988935 \tabularnewline
39 & 129 & 128.281001246654 & 8.74214832169034 & 0.0496061182125715 & 0.85281349947598 \tabularnewline
40 & 136.4 & 136.415209408823 & 8.24331788373879 & 0.0504792805447971 & -0.0836286765443845 \tabularnewline
41 & 155 & 153.943913208946 & 15.8670294781015 & 0.047217215196067 & 1.2818210519783 \tabularnewline
42 & 166 & 166.331164568755 & 13.0087064515624 & 0.0471631680619227 & -0.480623984602833 \tabularnewline
43 & 168.7 & 169.701180650601 & 5.09120796009151 & 0.0467775063330202 & -1.33131801079985 \tabularnewline
44 & 145.5 & 148.330533450786 & -16.6447166986019 & 0.0464396102097925 & -3.65487911756718 \tabularnewline
45 & 127.3 & 127.688186281442 & -19.9283544097458 & 0.0464370603720554 & -0.552141252759101 \tabularnewline
46 & 91.5 & 93.0525269294973 & -32.0088559350715 & 0.0464521247224927 & -2.03132739035969 \tabularnewline
47 & 69 & 68.1779150380521 & -26.1488225924138 & 0.0464490682208595 & 0.985360271175534 \tabularnewline
48 & 54 & 52.7842490977251 & -17.3145859319277 & 0.0464485025192332 & 1.48547035898322 \tabularnewline
49 & 56.3 & 53.777714097656 & -2.35508049021904 & 0.542240139822795 & 2.58600276209511 \tabularnewline
50 & 54.2 & 53.989087394392 & -0.364895184840919 & -0.0311046716416954 & 0.329034382727596 \tabularnewline
51 & 59.3 & 58.7811014170086 & 3.88349738478876 & -0.038116455419403 & 0.709276061447579 \tabularnewline
52 & 63.4 & 63.3633532417289 & 4.45695298337362 & -0.0389388976073732 & 0.0961913555031562 \tabularnewline
53 & 73.3 & 72.7993322680374 & 8.54526919026264 & -0.0403720235209633 & 0.687403232130544 \tabularnewline
54 & 86.7 & 86.2112055772285 & 12.5427319736869 & -0.0403100988897095 & 0.67216935823443 \tabularnewline
55 & 81.3 & 83.0483860150546 & -0.358166642588173 & -0.0408249200529714 & -2.16927188186462 \tabularnewline
56 & 89.6 & 88.9591889753238 & 4.79119031279563 & -0.0407593393733104 & 0.865860459007658 \tabularnewline
57 & 85.3 & 86.1654035825278 & -1.43907773848499 & -0.0407633029009632 & -1.04761496502711 \tabularnewline
58 & 92.4 & 91.6842978747755 & 4.27616428660894 & -0.0407691416242673 & 0.961013716855632 \tabularnewline
59 & 96.8 & 96.7544472560407 & 4.9283398303846 & -0.04076942030496 & 0.109662835194859 \tabularnewline
60 & 93.6 & 94.429362616358 & -1.02959003057658 & -0.0407691077462413 & -1.00182149850508 \tabularnewline
61 & 97.6 & 96.6468577390878 & 1.62611303527835 & 0.601632431360569 & 0.456843990226146 \tabularnewline
62 & 94.2 & 94.6283144993426 & -1.22584169358209 & -0.0765654908734921 & -0.472952590658363 \tabularnewline
63 & 99.9 & 99.3412875362545 & 3.66449200849069 & -0.0834023884883439 & 0.817345179581761 \tabularnewline
64 & 106.4 & 106.146529434614 & 6.24239310116854 & -0.0865338462125268 & 0.432578323245557 \tabularnewline
65 & 96 & 97.6812648829564 & -5.83482456877369 & -0.0829483696800213 & -2.0306648521777 \tabularnewline
66 & 94.9 & 94.6753546399883 & -3.51113947909708 & -0.08291788377223 & 0.390725411122072 \tabularnewline
67 & 94.8 & 94.5181727358684 & -0.756136190624209 & -0.082824772644756 & 0.463250919034791 \tabularnewline
68 & 95.9 & 95.7650384459333 & 0.889135039079157 & -0.0828070265244935 & 0.276651112086007 \tabularnewline
69 & 96.2 & 96.3192230582443 & 0.614008149125127 & -0.0828071747596534 & -0.0462623830580563 \tabularnewline
70 & 103.1 & 102.569983002933 & 5.24400734143831 & -0.0828111807249408 & 0.778530937872914 \tabularnewline
71 & 106.9 & 107.064315689647 & 4.62822814714216 & -0.0828109578760966 & -0.103542815959161 \tabularnewline
72 & 114.2 & 114.028811621343 & 6.54722788940972 & -0.082811043137832 & 0.322678387005867 \tabularnewline
73 & 118.2 & 117.713587249304 & 4.20456775119737 & 0.796488087675678 & -0.40161703405431 \tabularnewline
74 & 123.9 & 123.780009327797 & 5.67109987925144 & -0.0627201885535509 & 0.24371956023975 \tabularnewline
75 & 137.1 & 136.416056320726 & 11.4045003088383 & -0.0696724730946839 & 0.959022711175982 \tabularnewline
76 & 146.2 & 146.420149805487 & 10.2549460049565 & -0.0684613895499646 & -0.192951040360867 \tabularnewline
77 & 136.4 & 138.445749662299 & -4.71470197374378 & -0.064607223031978 & -2.51701659938666 \tabularnewline
78 & 133.2 & 133.310349902059 & -5.0602648002802 & -0.0646111548171201 & -0.0581060668742213 \tabularnewline
79 & 135.9 & 135.207965181813 & 0.655046237868486 & -0.0644436372451306 & 0.961023801247411 \tabularnewline
80 & 127.1 & 128.017478009053 & -5.7892887798625 & -0.0645039188823223 & -1.08361007055046 \tabularnewline
81 & 128.5 & 127.943168020669 & -1.09502920199963 & -0.0645017254394692 & 0.78933627596768 \tabularnewline
82 & 126.6 & 126.682508922703 & -1.23107676709816 & -0.0645016233553823 & -0.0228762973969793 \tabularnewline
83 & 132.6 & 131.957195757278 & 4.1127267105559 & -0.0645033005245299 & 0.89855660136647 \tabularnewline
84 & 130.9 & 131.465136277122 & 0.330376239254459 & -0.0645031547834353 & -0.635999433604986 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=194173&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]54.3[/C][C]54.3[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]55.9[/C][C]55.652895753806[/C][C]1.32963888392296[/C][C]0.0116284351277305[/C][C]0.244182411767075[/C][/ROW]
[ROW][C]3[/C][C]63.9[/C][C]63.2145510657995[/C][C]6.38744776294528[/C][C]-0.00312409374176502[/C][C]0.86748984538436[/C][/ROW]
[ROW][C]4[/C][C]64[/C][C]64.5492431107398[/C][C]2.24843209238815[/C][C]0.00526977113022229[/C][C]-0.700950632898699[/C][/ROW]
[ROW][C]5[/C][C]60.7[/C][C]61.2916313885406[/C][C]-2.27332987398094[/C][C]0.00725201835561575[/C][C]-0.760540076715445[/C][/ROW]
[ROW][C]6[/C][C]67.8[/C][C]66.9320532794934[/C][C]4.22720646020429[/C][C]0.00752464856601335[/C][C]1.0930672251612[/C][/ROW]
[ROW][C]7[/C][C]70.5[/C][C]70.5578888030993[/C][C]3.73322031375857[/C][C]0.00749601090311243[/C][C]-0.0830639146293572[/C][/ROW]
[ROW][C]8[/C][C]76.6[/C][C]76.3668026429325[/C][C]5.43820904449408[/C][C]0.00752430643824507[/C][C]0.286692714869682[/C][/ROW]
[ROW][C]9[/C][C]76.2[/C][C]76.7428372853867[/C][C]1.28016098216429[/C][C]0.00752329432929318[/C][C]-0.699172706032201[/C][/ROW]
[ROW][C]10[/C][C]71.8[/C][C]72.4034293180019[/C][C]-3.33572173857451[/C][C]0.00753040470628784[/C][C]-0.77615726826237[/C][/ROW]
[ROW][C]11[/C][C]67.8[/C][C]67.9175178203661[/C][C]-4.28048196921692[/C][C]0.00753094711094032[/C][C]-0.15886073394289[/C][/ROW]
[ROW][C]12[/C][C]69.7[/C][C]69.0986785933446[/C][C]0.205686526302996[/C][C]0.00753070472958719[/C][C]0.754345913701614[/C][/ROW]
[ROW][C]13[/C][C]76.7[/C][C]75.1677103544499[/C][C]4.94807802286347[/C][C]0.904584866383885[/C][C]0.861916924649272[/C][/ROW]
[ROW][C]14[/C][C]74.2[/C][C]74.7769788323584[/C][C]1.09963499479116[/C][C]-0.165066803609587[/C][C]-0.616666082860674[/C][/ROW]
[ROW][C]15[/C][C]75.8[/C][C]75.956720066564[/C][C]1.16586005024422[/C][C]-0.165305267898016[/C][C]0.0109625782932496[/C][/ROW]
[ROW][C]16[/C][C]84.3[/C][C]83.7678366295359[/C][C]6.61391101017096[/C][C]-0.18236473965871[/C][C]0.911212214021849[/C][/ROW]
[ROW][C]17[/C][C]84.9[/C][C]85.5987749067459[/C][C]2.68820556276126[/C][C]-0.179358359741552[/C][C]-0.660011917228858[/C][/ROW]
[ROW][C]18[/C][C]84.4[/C][C]84.9430173066845[/C][C]-0.0585949382913024[/C][C]-0.179451314826684[/C][C]-0.461870893766136[/C][/ROW]
[ROW][C]19[/C][C]89.4[/C][C]89.1187602006425[/C][C]3.41972400572855[/C][C]-0.179148086457567[/C][C]0.584874002760128[/C][/ROW]
[ROW][C]20[/C][C]88.5[/C][C]89.0576706708467[/C][C]0.560534437885692[/C][C]-0.179227634576789[/C][C]-0.480770484971255[/C][/ROW]
[ROW][C]21[/C][C]76.5[/C][C]77.9480262356249[/C][C]-9.02530871722435[/C][C]-0.1792409565361[/C][C]-1.61185243937049[/C][/ROW]
[ROW][C]22[/C][C]71.4[/C][C]71.3187488891535[/C][C]-7.05722297033667[/C][C]-0.179245348832501[/C][C]0.330932161176523[/C][/ROW]
[ROW][C]23[/C][C]72.1[/C][C]71.4930400502287[/C][C]-1.11729446068149[/C][C]-0.179250893655565[/C][C]0.998794584238847[/C][/ROW]
[ROW][C]24[/C][C]75.8[/C][C]75.4297763381849[/C][C]3.03406319150497[/C][C]-0.17925136941784[/C][C]0.698047718084126[/C][/ROW]
[ROW][C]25[/C][C]66.6[/C][C]67.0316916994275[/C][C]-6.26872305116445[/C][C]0.799628987099629[/C][C]-1.64197256209659[/C][/ROW]
[ROW][C]26[/C][C]71.7[/C][C]70.7971202939885[/C][C]1.25071452211147[/C][C]0.0387972677349685[/C][C]1.22700705507484[/C][/ROW]
[ROW][C]27[/C][C]75.4[/C][C]75.0450550201117[/C][C]3.72403570701488[/C][C]0.0324080590015908[/C][C]0.411249881091446[/C][/ROW]
[ROW][C]28[/C][C]80.9[/C][C]80.6664349437338[/C][C]5.28038887268778[/C][C]0.0289131810408424[/C][C]0.260701610140643[/C][/ROW]
[ROW][C]29[/C][C]80.7[/C][C]81.1861066556115[/C][C]1.37210327824006[/C][C]0.0310588978003664[/C][C]-0.657109280167184[/C][/ROW]
[ROW][C]30[/C][C]85[/C][C]84.7325036453751[/C][C]3.15809759267381[/C][C]0.031102228440575[/C][C]0.300312886932576[/C][/ROW]
[ROW][C]31[/C][C]91.5[/C][C]91.1178488144615[/C][C]5.80908240235445[/C][C]0.0312679118838537[/C][C]0.445759629548489[/C][/ROW]
[ROW][C]32[/C][C]87.7[/C][C]88.5767197493064[/C][C]-1.04985546562092[/C][C]0.0311311026678382[/C][C]-1.15332511220963[/C][/ROW]
[ROW][C]33[/C][C]95.3[/C][C]94.5096887031652[/C][C]4.68580967122785[/C][C]0.0311368173814167[/C][C]0.964447851439359[/C][/ROW]
[ROW][C]34[/C][C]102.4[/C][C]102.057689453018[/C][C]7.03679741563595[/C][C]0.0311330558108891[/C][C]0.395316848963787[/C][/ROW]
[ROW][C]35[/C][C]114.2[/C][C]113.67128000529[/C][C]10.7961525717253[/C][C]0.0311305399229329[/C][C]0.632132788199808[/C][/ROW]
[ROW][C]36[/C][C]111.7[/C][C]112.923885047889[/C][C]1.31433537889628[/C][C]0.0311313189694011[/C][C]-1.59436054642384[/C][/ROW]
[ROW][C]37[/C][C]113.7[/C][C]114.072546184189[/C][C]1.17916309365192[/C][C]-0.354654727612315[/C][C]-0.0235441888955331[/C][/ROW]
[ROW][C]38[/C][C]118.8[/C][C]118.448795871402[/C][C]3.6259110677974[/C][C]0.0599106989313238[/C][C]0.402600272988935[/C][/ROW]
[ROW][C]39[/C][C]129[/C][C]128.281001246654[/C][C]8.74214832169034[/C][C]0.0496061182125715[/C][C]0.85281349947598[/C][/ROW]
[ROW][C]40[/C][C]136.4[/C][C]136.415209408823[/C][C]8.24331788373879[/C][C]0.0504792805447971[/C][C]-0.0836286765443845[/C][/ROW]
[ROW][C]41[/C][C]155[/C][C]153.943913208946[/C][C]15.8670294781015[/C][C]0.047217215196067[/C][C]1.2818210519783[/C][/ROW]
[ROW][C]42[/C][C]166[/C][C]166.331164568755[/C][C]13.0087064515624[/C][C]0.0471631680619227[/C][C]-0.480623984602833[/C][/ROW]
[ROW][C]43[/C][C]168.7[/C][C]169.701180650601[/C][C]5.09120796009151[/C][C]0.0467775063330202[/C][C]-1.33131801079985[/C][/ROW]
[ROW][C]44[/C][C]145.5[/C][C]148.330533450786[/C][C]-16.6447166986019[/C][C]0.0464396102097925[/C][C]-3.65487911756718[/C][/ROW]
[ROW][C]45[/C][C]127.3[/C][C]127.688186281442[/C][C]-19.9283544097458[/C][C]0.0464370603720554[/C][C]-0.552141252759101[/C][/ROW]
[ROW][C]46[/C][C]91.5[/C][C]93.0525269294973[/C][C]-32.0088559350715[/C][C]0.0464521247224927[/C][C]-2.03132739035969[/C][/ROW]
[ROW][C]47[/C][C]69[/C][C]68.1779150380521[/C][C]-26.1488225924138[/C][C]0.0464490682208595[/C][C]0.985360271175534[/C][/ROW]
[ROW][C]48[/C][C]54[/C][C]52.7842490977251[/C][C]-17.3145859319277[/C][C]0.0464485025192332[/C][C]1.48547035898322[/C][/ROW]
[ROW][C]49[/C][C]56.3[/C][C]53.777714097656[/C][C]-2.35508049021904[/C][C]0.542240139822795[/C][C]2.58600276209511[/C][/ROW]
[ROW][C]50[/C][C]54.2[/C][C]53.989087394392[/C][C]-0.364895184840919[/C][C]-0.0311046716416954[/C][C]0.329034382727596[/C][/ROW]
[ROW][C]51[/C][C]59.3[/C][C]58.7811014170086[/C][C]3.88349738478876[/C][C]-0.038116455419403[/C][C]0.709276061447579[/C][/ROW]
[ROW][C]52[/C][C]63.4[/C][C]63.3633532417289[/C][C]4.45695298337362[/C][C]-0.0389388976073732[/C][C]0.0961913555031562[/C][/ROW]
[ROW][C]53[/C][C]73.3[/C][C]72.7993322680374[/C][C]8.54526919026264[/C][C]-0.0403720235209633[/C][C]0.687403232130544[/C][/ROW]
[ROW][C]54[/C][C]86.7[/C][C]86.2112055772285[/C][C]12.5427319736869[/C][C]-0.0403100988897095[/C][C]0.67216935823443[/C][/ROW]
[ROW][C]55[/C][C]81.3[/C][C]83.0483860150546[/C][C]-0.358166642588173[/C][C]-0.0408249200529714[/C][C]-2.16927188186462[/C][/ROW]
[ROW][C]56[/C][C]89.6[/C][C]88.9591889753238[/C][C]4.79119031279563[/C][C]-0.0407593393733104[/C][C]0.865860459007658[/C][/ROW]
[ROW][C]57[/C][C]85.3[/C][C]86.1654035825278[/C][C]-1.43907773848499[/C][C]-0.0407633029009632[/C][C]-1.04761496502711[/C][/ROW]
[ROW][C]58[/C][C]92.4[/C][C]91.6842978747755[/C][C]4.27616428660894[/C][C]-0.0407691416242673[/C][C]0.961013716855632[/C][/ROW]
[ROW][C]59[/C][C]96.8[/C][C]96.7544472560407[/C][C]4.9283398303846[/C][C]-0.04076942030496[/C][C]0.109662835194859[/C][/ROW]
[ROW][C]60[/C][C]93.6[/C][C]94.429362616358[/C][C]-1.02959003057658[/C][C]-0.0407691077462413[/C][C]-1.00182149850508[/C][/ROW]
[ROW][C]61[/C][C]97.6[/C][C]96.6468577390878[/C][C]1.62611303527835[/C][C]0.601632431360569[/C][C]0.456843990226146[/C][/ROW]
[ROW][C]62[/C][C]94.2[/C][C]94.6283144993426[/C][C]-1.22584169358209[/C][C]-0.0765654908734921[/C][C]-0.472952590658363[/C][/ROW]
[ROW][C]63[/C][C]99.9[/C][C]99.3412875362545[/C][C]3.66449200849069[/C][C]-0.0834023884883439[/C][C]0.817345179581761[/C][/ROW]
[ROW][C]64[/C][C]106.4[/C][C]106.146529434614[/C][C]6.24239310116854[/C][C]-0.0865338462125268[/C][C]0.432578323245557[/C][/ROW]
[ROW][C]65[/C][C]96[/C][C]97.6812648829564[/C][C]-5.83482456877369[/C][C]-0.0829483696800213[/C][C]-2.0306648521777[/C][/ROW]
[ROW][C]66[/C][C]94.9[/C][C]94.6753546399883[/C][C]-3.51113947909708[/C][C]-0.08291788377223[/C][C]0.390725411122072[/C][/ROW]
[ROW][C]67[/C][C]94.8[/C][C]94.5181727358684[/C][C]-0.756136190624209[/C][C]-0.082824772644756[/C][C]0.463250919034791[/C][/ROW]
[ROW][C]68[/C][C]95.9[/C][C]95.7650384459333[/C][C]0.889135039079157[/C][C]-0.0828070265244935[/C][C]0.276651112086007[/C][/ROW]
[ROW][C]69[/C][C]96.2[/C][C]96.3192230582443[/C][C]0.614008149125127[/C][C]-0.0828071747596534[/C][C]-0.0462623830580563[/C][/ROW]
[ROW][C]70[/C][C]103.1[/C][C]102.569983002933[/C][C]5.24400734143831[/C][C]-0.0828111807249408[/C][C]0.778530937872914[/C][/ROW]
[ROW][C]71[/C][C]106.9[/C][C]107.064315689647[/C][C]4.62822814714216[/C][C]-0.0828109578760966[/C][C]-0.103542815959161[/C][/ROW]
[ROW][C]72[/C][C]114.2[/C][C]114.028811621343[/C][C]6.54722788940972[/C][C]-0.082811043137832[/C][C]0.322678387005867[/C][/ROW]
[ROW][C]73[/C][C]118.2[/C][C]117.713587249304[/C][C]4.20456775119737[/C][C]0.796488087675678[/C][C]-0.40161703405431[/C][/ROW]
[ROW][C]74[/C][C]123.9[/C][C]123.780009327797[/C][C]5.67109987925144[/C][C]-0.0627201885535509[/C][C]0.24371956023975[/C][/ROW]
[ROW][C]75[/C][C]137.1[/C][C]136.416056320726[/C][C]11.4045003088383[/C][C]-0.0696724730946839[/C][C]0.959022711175982[/C][/ROW]
[ROW][C]76[/C][C]146.2[/C][C]146.420149805487[/C][C]10.2549460049565[/C][C]-0.0684613895499646[/C][C]-0.192951040360867[/C][/ROW]
[ROW][C]77[/C][C]136.4[/C][C]138.445749662299[/C][C]-4.71470197374378[/C][C]-0.064607223031978[/C][C]-2.51701659938666[/C][/ROW]
[ROW][C]78[/C][C]133.2[/C][C]133.310349902059[/C][C]-5.0602648002802[/C][C]-0.0646111548171201[/C][C]-0.0581060668742213[/C][/ROW]
[ROW][C]79[/C][C]135.9[/C][C]135.207965181813[/C][C]0.655046237868486[/C][C]-0.0644436372451306[/C][C]0.961023801247411[/C][/ROW]
[ROW][C]80[/C][C]127.1[/C][C]128.017478009053[/C][C]-5.7892887798625[/C][C]-0.0645039188823223[/C][C]-1.08361007055046[/C][/ROW]
[ROW][C]81[/C][C]128.5[/C][C]127.943168020669[/C][C]-1.09502920199963[/C][C]-0.0645017254394692[/C][C]0.78933627596768[/C][/ROW]
[ROW][C]82[/C][C]126.6[/C][C]126.682508922703[/C][C]-1.23107676709816[/C][C]-0.0645016233553823[/C][C]-0.0228762973969793[/C][/ROW]
[ROW][C]83[/C][C]132.6[/C][C]131.957195757278[/C][C]4.1127267105559[/C][C]-0.0645033005245299[/C][C]0.89855660136647[/C][/ROW]
[ROW][C]84[/C][C]130.9[/C][C]131.465136277122[/C][C]0.330376239254459[/C][C]-0.0645031547834353[/C][C]-0.635999433604986[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=194173&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=194173&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
154.354.3000
255.955.6528957538061.329638883922960.01162843512773050.244182411767075
363.963.21455106579956.38744776294528-0.003124093741765020.86748984538436
46464.54924311073982.248432092388150.00526977113022229-0.700950632898699
560.761.2916313885406-2.273329873980940.00725201835561575-0.760540076715445
667.866.93205327949344.227206460204290.007524648566013351.0930672251612
770.570.55788880309933.733220313758570.00749601090311243-0.0830639146293572
876.676.36680264293255.438209044494080.007524306438245070.286692714869682
976.276.74283728538671.280160982164290.00752329432929318-0.699172706032201
1071.872.4034293180019-3.335721738574510.00753040470628784-0.77615726826237
1167.867.9175178203661-4.280481969216920.00753094711094032-0.15886073394289
1269.769.09867859334460.2056865263029960.007530704729587190.754345913701614
1376.775.16771035444994.948078022863470.9045848663838850.861916924649272
1474.274.77697883235841.09963499479116-0.165066803609587-0.616666082860674
1575.875.9567200665641.16586005024422-0.1653052678980160.0109625782932496
1684.383.76783662953596.61391101017096-0.182364739658710.911212214021849
1784.985.59877490674592.68820556276126-0.179358359741552-0.660011917228858
1884.484.9430173066845-0.0585949382913024-0.179451314826684-0.461870893766136
1989.489.11876020064253.41972400572855-0.1791480864575670.584874002760128
2088.589.05767067084670.560534437885692-0.179227634576789-0.480770484971255
2176.577.9480262356249-9.02530871722435-0.1792409565361-1.61185243937049
2271.471.3187488891535-7.05722297033667-0.1792453488325010.330932161176523
2372.171.4930400502287-1.11729446068149-0.1792508936555650.998794584238847
2475.875.42977633818493.03406319150497-0.179251369417840.698047718084126
2566.667.0316916994275-6.268723051164450.799628987099629-1.64197256209659
2671.770.79712029398851.250714522111470.03879726773496851.22700705507484
2775.475.04505502011173.724035707014880.03240805900159080.411249881091446
2880.980.66643494373385.280388872687780.02891318104084240.260701610140643
2980.781.18610665561151.372103278240060.0310588978003664-0.657109280167184
308584.73250364537513.158097592673810.0311022284405750.300312886932576
3191.591.11784881446155.809082402354450.03126791188385370.445759629548489
3287.788.5767197493064-1.049855465620920.0311311026678382-1.15332511220963
3395.394.50968870316524.685809671227850.03113681738141670.964447851439359
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38118.8118.4487958714023.62591106779740.05991069893132380.402600272988935
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41155153.94391320894615.86702947810150.0472172151960671.2818210519783
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79135.9135.2079651818130.655046237868486-0.06444363724513060.961023801247411
80127.1128.017478009053-5.7892887798625-0.0645039188823223-1.08361007055046
81128.5127.943168020669-1.09502920199963-0.06450172543946920.78933627596768
82126.6126.682508922703-1.23107676709816-0.0645016233553823-0.0228762973969793
83132.6131.9571957572784.1127267105559-0.06450330052452990.89855660136647
84130.9131.4651362771220.330376239254459-0.0645031547834353-0.635999433604986



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')