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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 computationFri, 25 Nov 2011 05:59:24 -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/2011/Nov/25/t13222188242gkcqfeo35q3e51.htm/, Retrieved Mon, 24 Jun 2024 13:13:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=147288, Retrieved Mon, 24 Jun 2024 13:13:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [WS8] [2011-11-25 10:59:24] [84449ea5bbe6e767918d59f07903f9b5] [Current]
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Dataseries X:
89924
31795
27922
59954
52150
39964
34604
51106
52593
68794
47124
32315
42248
36088
52744
72586
92334
80761
71078
63713
57122
55243
62143
62708
62474
64250
71866
69886
58724
55298
52594
54854
54694
49298
44659
43657
47002
47042
48959
49750
54048
60067
68929
74617
75940
72762
75621
73008
74196
78878
83812
91624
89388
110410
113857
112060
117236
132810
137699
146409




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ yule.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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147288&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147288&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 time3 seconds
R Server'George Udny Yule' @ yule.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
18992489924000
23179534816.5994455412-3042.91316261991-3021.59944554125-2.8175579923738
32792230946.8534716997-3047.98627822669-3024.85347169969-0.0704822007056294
45995462842.3251182564-2795.70700802407-2888.325118256412.97700286780136
55215055057.6560692204-2837.05007745314-2907.65606922036-0.424792518274317
63996442907.4054573412-2923.992645727-2943.40545734124-0.792539801838628
73460437556.6243204692-2949.14224112532-2952.62432046922-0.206401189515555
85110653985.8468756821-2728.83012141393-2879.846875682091.64724680964498
95259355457.2672307886-2676.95340309379-2864.267230788580.356846618864642
106879471589.4285604265-2426.64793512883-2795.428560426491.59714214512064
114712449988.6041393838-2699.65456307119-2864.60413938378-1.62729049157642
123231535222.4777606691-2882.36055403943-2907.47776066909-1.02354392211762
134224817251.9763486509-2492.4914311702124996.0236513491-1.54166722728618
143608837806.1531496235-1680.62811713916-1718.15314962351.66219639173844
155274454433.2217559616-1386.71480061588-1689.22175596161.54916538751373
167258674242.2923491943-1028.55840606325-1656.292349194341.79273455774205
179233493958.634268475-661.124630682986-1624.634268474911.75382435989326
188076182401.9540425396-862.662186621986-1640.95404253958-0.92074291886644
197107872731.8921106667-1032.23152956679-1653.89211066673-0.743972800563073
206371365375.9959737759-1158.57511178006-1662.99597377592-0.533955004769785
215712258792.644272722-1270.74135406237-1670.64427272199-0.4578785962196
225524356914.4823849417-1283.70662644882-1671.48238494171-0.0512503427294081
236214363803.453720473-1104.03616412443-1660.453720472990.689313289802789
246270864366.2552220375-1066.37307021787-1658.255222037510.140538923437869
256247447635.7163414827-1186.5917552149414838.2836585173-1.45157895233364
266425065311.0660630474-552.176469775726-1061.066063047381.446424608922
277186672920.5919709932-356.711209565404-1054.591970993240.687310021967908
286988670941.8471302839-396.399696018871-1055.84713028388-0.136555056894514
295872459787.9636737842-664.930680265504-1063.96367378421-0.905399526207779
305529856363.9924346257-735.097360053845-1065.99243462574-0.23215324148588
315259453661.4017228156-786.010306926011-1067.40172281563-0.165509283895469
325485455919.2787694264-705.957255973854-1065.278769426390.25599721031565
335469455758.9084107528-691.39006382206-1064.908410752810.0458746897753258
344929850366.013491962-818.70307821153-1068.01349196202-0.395233235706552
354465945729.4657809004-923.456950293918-1070.46578090035-0.320883076273444
364365744727.5147989292-925.637291737124-1070.51479892922-0.00659601517149821
374700236304.808828603-1080.6789863227410697.191171397-0.671284462503545
384704247873.8716786989-652.99372666793-831.8716786989480.995225183750228
394895949789.8021803445-579.522260455196-830.8021803445430.215735122696489
404975050580.2483055976-539.965592913193-830.2483055975960.115030647842126
415404854876.3500560173-399.078752789085-828.350056017340.406005963893263
426006760892.9057722992-210.613139717924-825.9057722992170.538542725875979
436892969751.552782131957.8849982728046-822.5527821318990.761195398467263
447461775437.534073061225.72139863535-820.5340730610370.472316003595253
457594076760.1524462238258.654962745937-820.1524462238310.0920421551756602
467276273583.311591289154.850187248873-821.311591288967-0.288245785726599
477562176441.4272255767237.016000586578-820.4272255767450.226786655920744
487300873829.3308167594149.936072196029-821.330816759375-0.238999048441227
497419666023.7796081872-63.73304738390018172.2203918128-0.700133805911435
507887879502.8305635425394.964574898335-624.8305635425371.08066557190714
518381284435.8256612386535.573220685396-623.8256612386090.380555123265106
529162492246.2648552216761.948526614375-622.264855221590.610017550647984
538938890010.8878337063668.305390845726-622.887833706328-0.251316111195416
54110410111028.7909119641306.45475694232-618.7909119638821.7061339601364
55113857114475.3736055711373.80275207887-618.3736055708950.179419491758059
56112060112678.9722511691273.71257330826-618.972251169268-0.265761031863365
57117236117854.2588293851397.27054347362-618.2588293851130.327054125189359
58132810133425.7493188921847.43394890496-615.749318892491.18810844365456
59137699138314.2280546671944.27355820792-615.2280546667520.254893175919128
60146409147023.1055528622160.2250233946-614.105552861910.566966646937518

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 89924 & 89924 & 0 & 0 & 0 \tabularnewline
2 & 31795 & 34816.5994455412 & -3042.91316261991 & -3021.59944554125 & -2.8175579923738 \tabularnewline
3 & 27922 & 30946.8534716997 & -3047.98627822669 & -3024.85347169969 & -0.0704822007056294 \tabularnewline
4 & 59954 & 62842.3251182564 & -2795.70700802407 & -2888.32511825641 & 2.97700286780136 \tabularnewline
5 & 52150 & 55057.6560692204 & -2837.05007745314 & -2907.65606922036 & -0.424792518274317 \tabularnewline
6 & 39964 & 42907.4054573412 & -2923.992645727 & -2943.40545734124 & -0.792539801838628 \tabularnewline
7 & 34604 & 37556.6243204692 & -2949.14224112532 & -2952.62432046922 & -0.206401189515555 \tabularnewline
8 & 51106 & 53985.8468756821 & -2728.83012141393 & -2879.84687568209 & 1.64724680964498 \tabularnewline
9 & 52593 & 55457.2672307886 & -2676.95340309379 & -2864.26723078858 & 0.356846618864642 \tabularnewline
10 & 68794 & 71589.4285604265 & -2426.64793512883 & -2795.42856042649 & 1.59714214512064 \tabularnewline
11 & 47124 & 49988.6041393838 & -2699.65456307119 & -2864.60413938378 & -1.62729049157642 \tabularnewline
12 & 32315 & 35222.4777606691 & -2882.36055403943 & -2907.47776066909 & -1.02354392211762 \tabularnewline
13 & 42248 & 17251.9763486509 & -2492.49143117021 & 24996.0236513491 & -1.54166722728618 \tabularnewline
14 & 36088 & 37806.1531496235 & -1680.62811713916 & -1718.1531496235 & 1.66219639173844 \tabularnewline
15 & 52744 & 54433.2217559616 & -1386.71480061588 & -1689.2217559616 & 1.54916538751373 \tabularnewline
16 & 72586 & 74242.2923491943 & -1028.55840606325 & -1656.29234919434 & 1.79273455774205 \tabularnewline
17 & 92334 & 93958.634268475 & -661.124630682986 & -1624.63426847491 & 1.75382435989326 \tabularnewline
18 & 80761 & 82401.9540425396 & -862.662186621986 & -1640.95404253958 & -0.92074291886644 \tabularnewline
19 & 71078 & 72731.8921106667 & -1032.23152956679 & -1653.89211066673 & -0.743972800563073 \tabularnewline
20 & 63713 & 65375.9959737759 & -1158.57511178006 & -1662.99597377592 & -0.533955004769785 \tabularnewline
21 & 57122 & 58792.644272722 & -1270.74135406237 & -1670.64427272199 & -0.4578785962196 \tabularnewline
22 & 55243 & 56914.4823849417 & -1283.70662644882 & -1671.48238494171 & -0.0512503427294081 \tabularnewline
23 & 62143 & 63803.453720473 & -1104.03616412443 & -1660.45372047299 & 0.689313289802789 \tabularnewline
24 & 62708 & 64366.2552220375 & -1066.37307021787 & -1658.25522203751 & 0.140538923437869 \tabularnewline
25 & 62474 & 47635.7163414827 & -1186.59175521494 & 14838.2836585173 & -1.45157895233364 \tabularnewline
26 & 64250 & 65311.0660630474 & -552.176469775726 & -1061.06606304738 & 1.446424608922 \tabularnewline
27 & 71866 & 72920.5919709932 & -356.711209565404 & -1054.59197099324 & 0.687310021967908 \tabularnewline
28 & 69886 & 70941.8471302839 & -396.399696018871 & -1055.84713028388 & -0.136555056894514 \tabularnewline
29 & 58724 & 59787.9636737842 & -664.930680265504 & -1063.96367378421 & -0.905399526207779 \tabularnewline
30 & 55298 & 56363.9924346257 & -735.097360053845 & -1065.99243462574 & -0.23215324148588 \tabularnewline
31 & 52594 & 53661.4017228156 & -786.010306926011 & -1067.40172281563 & -0.165509283895469 \tabularnewline
32 & 54854 & 55919.2787694264 & -705.957255973854 & -1065.27876942639 & 0.25599721031565 \tabularnewline
33 & 54694 & 55758.9084107528 & -691.39006382206 & -1064.90841075281 & 0.0458746897753258 \tabularnewline
34 & 49298 & 50366.013491962 & -818.70307821153 & -1068.01349196202 & -0.395233235706552 \tabularnewline
35 & 44659 & 45729.4657809004 & -923.456950293918 & -1070.46578090035 & -0.320883076273444 \tabularnewline
36 & 43657 & 44727.5147989292 & -925.637291737124 & -1070.51479892922 & -0.00659601517149821 \tabularnewline
37 & 47002 & 36304.808828603 & -1080.67898632274 & 10697.191171397 & -0.671284462503545 \tabularnewline
38 & 47042 & 47873.8716786989 & -652.99372666793 & -831.871678698948 & 0.995225183750228 \tabularnewline
39 & 48959 & 49789.8021803445 & -579.522260455196 & -830.802180344543 & 0.215735122696489 \tabularnewline
40 & 49750 & 50580.2483055976 & -539.965592913193 & -830.248305597596 & 0.115030647842126 \tabularnewline
41 & 54048 & 54876.3500560173 & -399.078752789085 & -828.35005601734 & 0.406005963893263 \tabularnewline
42 & 60067 & 60892.9057722992 & -210.613139717924 & -825.905772299217 & 0.538542725875979 \tabularnewline
43 & 68929 & 69751.5527821319 & 57.8849982728046 & -822.552782131899 & 0.761195398467263 \tabularnewline
44 & 74617 & 75437.534073061 & 225.72139863535 & -820.534073061037 & 0.472316003595253 \tabularnewline
45 & 75940 & 76760.1524462238 & 258.654962745937 & -820.152446223831 & 0.0920421551756602 \tabularnewline
46 & 72762 & 73583.311591289 & 154.850187248873 & -821.311591288967 & -0.288245785726599 \tabularnewline
47 & 75621 & 76441.4272255767 & 237.016000586578 & -820.427225576745 & 0.226786655920744 \tabularnewline
48 & 73008 & 73829.3308167594 & 149.936072196029 & -821.330816759375 & -0.238999048441227 \tabularnewline
49 & 74196 & 66023.7796081872 & -63.7330473839001 & 8172.2203918128 & -0.700133805911435 \tabularnewline
50 & 78878 & 79502.8305635425 & 394.964574898335 & -624.830563542537 & 1.08066557190714 \tabularnewline
51 & 83812 & 84435.8256612386 & 535.573220685396 & -623.825661238609 & 0.380555123265106 \tabularnewline
52 & 91624 & 92246.2648552216 & 761.948526614375 & -622.26485522159 & 0.610017550647984 \tabularnewline
53 & 89388 & 90010.8878337063 & 668.305390845726 & -622.887833706328 & -0.251316111195416 \tabularnewline
54 & 110410 & 111028.790911964 & 1306.45475694232 & -618.790911963882 & 1.7061339601364 \tabularnewline
55 & 113857 & 114475.373605571 & 1373.80275207887 & -618.373605570895 & 0.179419491758059 \tabularnewline
56 & 112060 & 112678.972251169 & 1273.71257330826 & -618.972251169268 & -0.265761031863365 \tabularnewline
57 & 117236 & 117854.258829385 & 1397.27054347362 & -618.258829385113 & 0.327054125189359 \tabularnewline
58 & 132810 & 133425.749318892 & 1847.43394890496 & -615.74931889249 & 1.18810844365456 \tabularnewline
59 & 137699 & 138314.228054667 & 1944.27355820792 & -615.228054666752 & 0.254893175919128 \tabularnewline
60 & 146409 & 147023.105552862 & 2160.2250233946 & -614.10555286191 & 0.566966646937518 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=147288&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]89924[/C][C]89924[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]31795[/C][C]34816.5994455412[/C][C]-3042.91316261991[/C][C]-3021.59944554125[/C][C]-2.8175579923738[/C][/ROW]
[ROW][C]3[/C][C]27922[/C][C]30946.8534716997[/C][C]-3047.98627822669[/C][C]-3024.85347169969[/C][C]-0.0704822007056294[/C][/ROW]
[ROW][C]4[/C][C]59954[/C][C]62842.3251182564[/C][C]-2795.70700802407[/C][C]-2888.32511825641[/C][C]2.97700286780136[/C][/ROW]
[ROW][C]5[/C][C]52150[/C][C]55057.6560692204[/C][C]-2837.05007745314[/C][C]-2907.65606922036[/C][C]-0.424792518274317[/C][/ROW]
[ROW][C]6[/C][C]39964[/C][C]42907.4054573412[/C][C]-2923.992645727[/C][C]-2943.40545734124[/C][C]-0.792539801838628[/C][/ROW]
[ROW][C]7[/C][C]34604[/C][C]37556.6243204692[/C][C]-2949.14224112532[/C][C]-2952.62432046922[/C][C]-0.206401189515555[/C][/ROW]
[ROW][C]8[/C][C]51106[/C][C]53985.8468756821[/C][C]-2728.83012141393[/C][C]-2879.84687568209[/C][C]1.64724680964498[/C][/ROW]
[ROW][C]9[/C][C]52593[/C][C]55457.2672307886[/C][C]-2676.95340309379[/C][C]-2864.26723078858[/C][C]0.356846618864642[/C][/ROW]
[ROW][C]10[/C][C]68794[/C][C]71589.4285604265[/C][C]-2426.64793512883[/C][C]-2795.42856042649[/C][C]1.59714214512064[/C][/ROW]
[ROW][C]11[/C][C]47124[/C][C]49988.6041393838[/C][C]-2699.65456307119[/C][C]-2864.60413938378[/C][C]-1.62729049157642[/C][/ROW]
[ROW][C]12[/C][C]32315[/C][C]35222.4777606691[/C][C]-2882.36055403943[/C][C]-2907.47776066909[/C][C]-1.02354392211762[/C][/ROW]
[ROW][C]13[/C][C]42248[/C][C]17251.9763486509[/C][C]-2492.49143117021[/C][C]24996.0236513491[/C][C]-1.54166722728618[/C][/ROW]
[ROW][C]14[/C][C]36088[/C][C]37806.1531496235[/C][C]-1680.62811713916[/C][C]-1718.1531496235[/C][C]1.66219639173844[/C][/ROW]
[ROW][C]15[/C][C]52744[/C][C]54433.2217559616[/C][C]-1386.71480061588[/C][C]-1689.2217559616[/C][C]1.54916538751373[/C][/ROW]
[ROW][C]16[/C][C]72586[/C][C]74242.2923491943[/C][C]-1028.55840606325[/C][C]-1656.29234919434[/C][C]1.79273455774205[/C][/ROW]
[ROW][C]17[/C][C]92334[/C][C]93958.634268475[/C][C]-661.124630682986[/C][C]-1624.63426847491[/C][C]1.75382435989326[/C][/ROW]
[ROW][C]18[/C][C]80761[/C][C]82401.9540425396[/C][C]-862.662186621986[/C][C]-1640.95404253958[/C][C]-0.92074291886644[/C][/ROW]
[ROW][C]19[/C][C]71078[/C][C]72731.8921106667[/C][C]-1032.23152956679[/C][C]-1653.89211066673[/C][C]-0.743972800563073[/C][/ROW]
[ROW][C]20[/C][C]63713[/C][C]65375.9959737759[/C][C]-1158.57511178006[/C][C]-1662.99597377592[/C][C]-0.533955004769785[/C][/ROW]
[ROW][C]21[/C][C]57122[/C][C]58792.644272722[/C][C]-1270.74135406237[/C][C]-1670.64427272199[/C][C]-0.4578785962196[/C][/ROW]
[ROW][C]22[/C][C]55243[/C][C]56914.4823849417[/C][C]-1283.70662644882[/C][C]-1671.48238494171[/C][C]-0.0512503427294081[/C][/ROW]
[ROW][C]23[/C][C]62143[/C][C]63803.453720473[/C][C]-1104.03616412443[/C][C]-1660.45372047299[/C][C]0.689313289802789[/C][/ROW]
[ROW][C]24[/C][C]62708[/C][C]64366.2552220375[/C][C]-1066.37307021787[/C][C]-1658.25522203751[/C][C]0.140538923437869[/C][/ROW]
[ROW][C]25[/C][C]62474[/C][C]47635.7163414827[/C][C]-1186.59175521494[/C][C]14838.2836585173[/C][C]-1.45157895233364[/C][/ROW]
[ROW][C]26[/C][C]64250[/C][C]65311.0660630474[/C][C]-552.176469775726[/C][C]-1061.06606304738[/C][C]1.446424608922[/C][/ROW]
[ROW][C]27[/C][C]71866[/C][C]72920.5919709932[/C][C]-356.711209565404[/C][C]-1054.59197099324[/C][C]0.687310021967908[/C][/ROW]
[ROW][C]28[/C][C]69886[/C][C]70941.8471302839[/C][C]-396.399696018871[/C][C]-1055.84713028388[/C][C]-0.136555056894514[/C][/ROW]
[ROW][C]29[/C][C]58724[/C][C]59787.9636737842[/C][C]-664.930680265504[/C][C]-1063.96367378421[/C][C]-0.905399526207779[/C][/ROW]
[ROW][C]30[/C][C]55298[/C][C]56363.9924346257[/C][C]-735.097360053845[/C][C]-1065.99243462574[/C][C]-0.23215324148588[/C][/ROW]
[ROW][C]31[/C][C]52594[/C][C]53661.4017228156[/C][C]-786.010306926011[/C][C]-1067.40172281563[/C][C]-0.165509283895469[/C][/ROW]
[ROW][C]32[/C][C]54854[/C][C]55919.2787694264[/C][C]-705.957255973854[/C][C]-1065.27876942639[/C][C]0.25599721031565[/C][/ROW]
[ROW][C]33[/C][C]54694[/C][C]55758.9084107528[/C][C]-691.39006382206[/C][C]-1064.90841075281[/C][C]0.0458746897753258[/C][/ROW]
[ROW][C]34[/C][C]49298[/C][C]50366.013491962[/C][C]-818.70307821153[/C][C]-1068.01349196202[/C][C]-0.395233235706552[/C][/ROW]
[ROW][C]35[/C][C]44659[/C][C]45729.4657809004[/C][C]-923.456950293918[/C][C]-1070.46578090035[/C][C]-0.320883076273444[/C][/ROW]
[ROW][C]36[/C][C]43657[/C][C]44727.5147989292[/C][C]-925.637291737124[/C][C]-1070.51479892922[/C][C]-0.00659601517149821[/C][/ROW]
[ROW][C]37[/C][C]47002[/C][C]36304.808828603[/C][C]-1080.67898632274[/C][C]10697.191171397[/C][C]-0.671284462503545[/C][/ROW]
[ROW][C]38[/C][C]47042[/C][C]47873.8716786989[/C][C]-652.99372666793[/C][C]-831.871678698948[/C][C]0.995225183750228[/C][/ROW]
[ROW][C]39[/C][C]48959[/C][C]49789.8021803445[/C][C]-579.522260455196[/C][C]-830.802180344543[/C][C]0.215735122696489[/C][/ROW]
[ROW][C]40[/C][C]49750[/C][C]50580.2483055976[/C][C]-539.965592913193[/C][C]-830.248305597596[/C][C]0.115030647842126[/C][/ROW]
[ROW][C]41[/C][C]54048[/C][C]54876.3500560173[/C][C]-399.078752789085[/C][C]-828.35005601734[/C][C]0.406005963893263[/C][/ROW]
[ROW][C]42[/C][C]60067[/C][C]60892.9057722992[/C][C]-210.613139717924[/C][C]-825.905772299217[/C][C]0.538542725875979[/C][/ROW]
[ROW][C]43[/C][C]68929[/C][C]69751.5527821319[/C][C]57.8849982728046[/C][C]-822.552782131899[/C][C]0.761195398467263[/C][/ROW]
[ROW][C]44[/C][C]74617[/C][C]75437.534073061[/C][C]225.72139863535[/C][C]-820.534073061037[/C][C]0.472316003595253[/C][/ROW]
[ROW][C]45[/C][C]75940[/C][C]76760.1524462238[/C][C]258.654962745937[/C][C]-820.152446223831[/C][C]0.0920421551756602[/C][/ROW]
[ROW][C]46[/C][C]72762[/C][C]73583.311591289[/C][C]154.850187248873[/C][C]-821.311591288967[/C][C]-0.288245785726599[/C][/ROW]
[ROW][C]47[/C][C]75621[/C][C]76441.4272255767[/C][C]237.016000586578[/C][C]-820.427225576745[/C][C]0.226786655920744[/C][/ROW]
[ROW][C]48[/C][C]73008[/C][C]73829.3308167594[/C][C]149.936072196029[/C][C]-821.330816759375[/C][C]-0.238999048441227[/C][/ROW]
[ROW][C]49[/C][C]74196[/C][C]66023.7796081872[/C][C]-63.7330473839001[/C][C]8172.2203918128[/C][C]-0.700133805911435[/C][/ROW]
[ROW][C]50[/C][C]78878[/C][C]79502.8305635425[/C][C]394.964574898335[/C][C]-624.830563542537[/C][C]1.08066557190714[/C][/ROW]
[ROW][C]51[/C][C]83812[/C][C]84435.8256612386[/C][C]535.573220685396[/C][C]-623.825661238609[/C][C]0.380555123265106[/C][/ROW]
[ROW][C]52[/C][C]91624[/C][C]92246.2648552216[/C][C]761.948526614375[/C][C]-622.26485522159[/C][C]0.610017550647984[/C][/ROW]
[ROW][C]53[/C][C]89388[/C][C]90010.8878337063[/C][C]668.305390845726[/C][C]-622.887833706328[/C][C]-0.251316111195416[/C][/ROW]
[ROW][C]54[/C][C]110410[/C][C]111028.790911964[/C][C]1306.45475694232[/C][C]-618.790911963882[/C][C]1.7061339601364[/C][/ROW]
[ROW][C]55[/C][C]113857[/C][C]114475.373605571[/C][C]1373.80275207887[/C][C]-618.373605570895[/C][C]0.179419491758059[/C][/ROW]
[ROW][C]56[/C][C]112060[/C][C]112678.972251169[/C][C]1273.71257330826[/C][C]-618.972251169268[/C][C]-0.265761031863365[/C][/ROW]
[ROW][C]57[/C][C]117236[/C][C]117854.258829385[/C][C]1397.27054347362[/C][C]-618.258829385113[/C][C]0.327054125189359[/C][/ROW]
[ROW][C]58[/C][C]132810[/C][C]133425.749318892[/C][C]1847.43394890496[/C][C]-615.74931889249[/C][C]1.18810844365456[/C][/ROW]
[ROW][C]59[/C][C]137699[/C][C]138314.228054667[/C][C]1944.27355820792[/C][C]-615.228054666752[/C][C]0.254893175919128[/C][/ROW]
[ROW][C]60[/C][C]146409[/C][C]147023.105552862[/C][C]2160.2250233946[/C][C]-614.10555286191[/C][C]0.566966646937518[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=147288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=147288&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
18992489924000
23179534816.5994455412-3042.91316261991-3021.59944554125-2.8175579923738
32792230946.8534716997-3047.98627822669-3024.85347169969-0.0704822007056294
45995462842.3251182564-2795.70700802407-2888.325118256412.97700286780136
55215055057.6560692204-2837.05007745314-2907.65606922036-0.424792518274317
63996442907.4054573412-2923.992645727-2943.40545734124-0.792539801838628
73460437556.6243204692-2949.14224112532-2952.62432046922-0.206401189515555
85110653985.8468756821-2728.83012141393-2879.846875682091.64724680964498
95259355457.2672307886-2676.95340309379-2864.267230788580.356846618864642
106879471589.4285604265-2426.64793512883-2795.428560426491.59714214512064
114712449988.6041393838-2699.65456307119-2864.60413938378-1.62729049157642
123231535222.4777606691-2882.36055403943-2907.47776066909-1.02354392211762
134224817251.9763486509-2492.4914311702124996.0236513491-1.54166722728618
143608837806.1531496235-1680.62811713916-1718.15314962351.66219639173844
155274454433.2217559616-1386.71480061588-1689.22175596161.54916538751373
167258674242.2923491943-1028.55840606325-1656.292349194341.79273455774205
179233493958.634268475-661.124630682986-1624.634268474911.75382435989326
188076182401.9540425396-862.662186621986-1640.95404253958-0.92074291886644
197107872731.8921106667-1032.23152956679-1653.89211066673-0.743972800563073
206371365375.9959737759-1158.57511178006-1662.99597377592-0.533955004769785
215712258792.644272722-1270.74135406237-1670.64427272199-0.4578785962196
225524356914.4823849417-1283.70662644882-1671.48238494171-0.0512503427294081
236214363803.453720473-1104.03616412443-1660.453720472990.689313289802789
246270864366.2552220375-1066.37307021787-1658.255222037510.140538923437869
256247447635.7163414827-1186.5917552149414838.2836585173-1.45157895233364
266425065311.0660630474-552.176469775726-1061.066063047381.446424608922
277186672920.5919709932-356.711209565404-1054.591970993240.687310021967908
286988670941.8471302839-396.399696018871-1055.84713028388-0.136555056894514
295872459787.9636737842-664.930680265504-1063.96367378421-0.905399526207779
305529856363.9924346257-735.097360053845-1065.99243462574-0.23215324148588
315259453661.4017228156-786.010306926011-1067.40172281563-0.165509283895469
325485455919.2787694264-705.957255973854-1065.278769426390.25599721031565
335469455758.9084107528-691.39006382206-1064.908410752810.0458746897753258
344929850366.013491962-818.70307821153-1068.01349196202-0.395233235706552
354465945729.4657809004-923.456950293918-1070.46578090035-0.320883076273444
364365744727.5147989292-925.637291737124-1070.51479892922-0.00659601517149821
374700236304.808828603-1080.6789863227410697.191171397-0.671284462503545
384704247873.8716786989-652.99372666793-831.8716786989480.995225183750228
394895949789.8021803445-579.522260455196-830.8021803445430.215735122696489
404975050580.2483055976-539.965592913193-830.2483055975960.115030647842126
415404854876.3500560173-399.078752789085-828.350056017340.406005963893263
426006760892.9057722992-210.613139717924-825.9057722992170.538542725875979
436892969751.552782131957.8849982728046-822.5527821318990.761195398467263
447461775437.534073061225.72139863535-820.5340730610370.472316003595253
457594076760.1524462238258.654962745937-820.1524462238310.0920421551756602
467276273583.311591289154.850187248873-821.311591288967-0.288245785726599
477562176441.4272255767237.016000586578-820.4272255767450.226786655920744
487300873829.3308167594149.936072196029-821.330816759375-0.238999048441227
497419666023.7796081872-63.73304738390018172.2203918128-0.700133805911435
507887879502.8305635425394.964574898335-624.8305635425371.08066557190714
518381284435.8256612386535.573220685396-623.8256612386090.380555123265106
529162492246.2648552216761.948526614375-622.264855221590.610017550647984
538938890010.8878337063668.305390845726-622.887833706328-0.251316111195416
54110410111028.7909119641306.45475694232-618.7909119638821.7061339601364
55113857114475.3736055711373.80275207887-618.3736055708950.179419491758059
56112060112678.9722511691273.71257330826-618.972251169268-0.265761031863365
57117236117854.2588293851397.27054347362-618.2588293851130.327054125189359
58132810133425.7493188921847.43394890496-615.749318892491.18810844365456
59137699138314.2280546671944.27355820792-615.2280546667520.254893175919128
60146409147023.1055528622160.2250233946-614.105552861910.566966646937518



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')