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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationTue, 28 Dec 2010 19:22:02 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/28/t1293564003qqgm9a5wu4u6pew.htm/, Retrieved Sat, 04 May 2024 22:26:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116508, Retrieved Sat, 04 May 2024 22:26:03 +0000
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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)
-       [Structural Time Series Models] [Paper: analyse (m...] [2010-12-28 19:22:02] [35c3410767ea63f72c8afa35bf7b6164] [Current]
-         [Structural Time Series Models] [Paper: analyse (1...] [2010-12-28 19:26:09] [a48e3f697f1471e9c9650f8bf805cc06]
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Dataseries X:
49915
47469
45652
43492
41087
42931
67256
72316
65624
59450
52851
51214
44092
43752
40320
40551
38329
39530
59648
61031
55560
43877
38510
36085
35994
32617
30001
27894
26083
28817
48742
49915
40264
34276
30426
30793
29855
28081
26820
25782
22654
27373
43675
45096
38145
34017
31537
33814
36531
36935
36497
35110
33137
37407
53963
56602
49694
43957
41723
45599
42503
42153
39098
37449
34748
36548
53639
55289
47774
42156
38019




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116508&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116508&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116508&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
14991549915000
24746948054.9102584259-1908.51207570129-585.910258425918-0.625488600724794
34565245445.8356412282-2397.35536871778206.164358771802-0.149024366962252
44349243332.3434749779-2187.19975647116159.6565250221010.0621313834064608
54108741106.6751007528-2215.08493897911-19.6751007527871-0.00795648533898918
64293142052.439594292864.9362536785892878.560405707210.65680299294174
76725662050.983969099914488.87152981315205.016030900074.15121258854616
87231674531.934715514713035.1133053156-2215.93471551473-0.418188136631675
96562470219.9507997024477.10632617661-4595.95079970239-3.61273968604251
105945060738.6466338554-6730.69668451185-1288.64663385539-2.07352969680377
115285152451.8762318613-7856.89447658363399.123768138654-0.323981888124756
125121449691.5549776427-4168.214520065421522.445022357281.06115163246103
134409244728.4748478281-4742.05998035167-636.474847828119-0.165575580733713
144375243191.9849351941-2419.20916876936560.0150648058850.678694001099109
154032040188.5198269027-2827.23959030123131.480173097352-0.116793903281184
164055138604.222274751-1960.674520234941946.777725248980.253193330939974
173832938299.0407172673-799.62212651428429.95928273266810.333835783979233
183953043672.16302633543495.66126032296-4142.163026335381.23296670253431
195964853673.29170220488021.824396518835974.708297795171.30306317905240
206103159842.36962268836730.772612042231188.63037731172-0.371467468909485
215556059281.74483831191648.19613009143-3721.74483831189-1.46205080255301
224387747941.0967737009-7405.47656194947-4064.09677370087-2.60471367136971
233851039063.8369982592-8430.9988421114-553.836998259239-0.295022567138393
243608533352.9072516004-6537.606297349892732.092748399630.54485842900725
253599435089.7448842835-777.408143156459904.2551157165061.66203973610960
263261732448.5817439652-2076.48232482017168.418256034769-0.374255606161042
273000129617.9250730681-2596.69665383055383.074926931942-0.149313923462349
282789426136.2778234155-3205.523122965111757.72217658450-0.176113986265837
292608326954.1109883542-423.976910562849-871.1109883542150.801730521601201
302881733937.79964261264682.1417449956-5120.79964261261.46613494810727
314874242505.88117738277355.449423821846236.118822617340.768965156121511
324991547606.18982985075802.456888257472308.81017014934-0.446898132348216
334026442698.495161203-1578.17968080328-2434.495161203-2.12317677200541
343427637913.0167580412-3788.43965364417-3637.01675804118-0.635865626585045
353042632318.9483593869-5032.14034101896-1892.94835938688-0.357789999243963
363079329861.0325490950-3260.16378515952931.9674509049580.510085292336623
372985527944.6865193557-2334.476006849301910.313480644270.266779165340143
382808126763.0827706027-1540.587764417051317.917229397320.228354119483739
392682025427.3438382166-1400.233114179291392.656161783370.040331658354731
402578224835.0568374816-847.448526610465946.9431625183610.159424443417562
412265425819.3665913805409.441124164234-3165.366591380520.362209378686596
422737332765.19645030754891.25038678277-5392.196450307521.28804971836422
434367537433.72511998974738.809272159716241.27488001034-0.0438297992020393
444509640069.83771024883299.286183225645026.16228975124-0.414172042334057
453814540244.80728155011158.92410154342-2099.80728155011-0.615752566302866
463401737902.810464905-1239.66534497966-3885.810464905-0.690023147959359
473153734644.3636038226-2622.29099215778-3107.36360382258-0.397788341007762
483381432934.157719665-1997.71760061051879.8422803349910.179793654454959
493653133968.267727452879.6621554371922562.732272547180.59818552619235
503693535099.4261595517799.6339607296481835.573840448260.207038055815206
513649735141.9142912602282.7378229703641355.08570873980-0.148605061734198
523511034899.7905536118-75.2888927711292210.209446388207-0.103140833765052
533313737795.49402260971954.96653353691-4658.49402260970.584835304048984
543740742466.88719952063811.37251798781-5059.88719952060.533829878715382
555396347190.50112745254434.012297939856772.498872547460.179012405974210
565660250896.43639195453937.19269597665705.56360804546-0.142913874456852
574969451468.27669907471639.83236233210-1774.27669907469-0.660927905622397
584395748267.7475260176-1664.87946479897-4310.74752601763-0.9507332654719
594172345313.1326125358-2545.29762762862-3590.13261253583-0.253325304533689
604559945066.0274832496-976.293511926042532.9725167503670.451620096662118
614250341079.2148478209-3032.421230623371423.78515217905-0.591784028094205
624215339241.9736353241-2216.740950243412911.026364675900.234553570577528
633909837323.8789318702-2013.316664919041774.121068129780.0584972040110666
643744937534.0867613161-499.512551163299-85.08676131605170.435879781063916
653474839775.05428769081368.48657138000-5027.054287690840.537931746119703
663654842079.2701009752006.50738575646-5531.2701009750.183526261792228
675363946329.90107934793535.346532247057309.098920652140.439587847351093
685528948919.24291023192891.171597489456369.75708976808-0.185278320732578
694777448789.9459489652834.151382728867-1015.94594896516-0.591773463809047
704215646880.6418009678-1034.44223846550-4724.64180096778-0.53761277971524
713801942992.6019574356-2978.10248868457-4973.60195743558-0.559299989947147

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 49915 & 49915 & 0 & 0 & 0 \tabularnewline
2 & 47469 & 48054.9102584259 & -1908.51207570129 & -585.910258425918 & -0.625488600724794 \tabularnewline
3 & 45652 & 45445.8356412282 & -2397.35536871778 & 206.164358771802 & -0.149024366962252 \tabularnewline
4 & 43492 & 43332.3434749779 & -2187.19975647116 & 159.656525022101 & 0.0621313834064608 \tabularnewline
5 & 41087 & 41106.6751007528 & -2215.08493897911 & -19.6751007527871 & -0.00795648533898918 \tabularnewline
6 & 42931 & 42052.4395942928 & 64.9362536785892 & 878.56040570721 & 0.65680299294174 \tabularnewline
7 & 67256 & 62050.9839690999 & 14488.8715298131 & 5205.01603090007 & 4.15121258854616 \tabularnewline
8 & 72316 & 74531.9347155147 & 13035.1133053156 & -2215.93471551473 & -0.418188136631675 \tabularnewline
9 & 65624 & 70219.9507997024 & 477.10632617661 & -4595.95079970239 & -3.61273968604251 \tabularnewline
10 & 59450 & 60738.6466338554 & -6730.69668451185 & -1288.64663385539 & -2.07352969680377 \tabularnewline
11 & 52851 & 52451.8762318613 & -7856.89447658363 & 399.123768138654 & -0.323981888124756 \tabularnewline
12 & 51214 & 49691.5549776427 & -4168.21452006542 & 1522.44502235728 & 1.06115163246103 \tabularnewline
13 & 44092 & 44728.4748478281 & -4742.05998035167 & -636.474847828119 & -0.165575580733713 \tabularnewline
14 & 43752 & 43191.9849351941 & -2419.20916876936 & 560.015064805885 & 0.678694001099109 \tabularnewline
15 & 40320 & 40188.5198269027 & -2827.23959030123 & 131.480173097352 & -0.116793903281184 \tabularnewline
16 & 40551 & 38604.222274751 & -1960.67452023494 & 1946.77772524898 & 0.253193330939974 \tabularnewline
17 & 38329 & 38299.0407172673 & -799.622126514284 & 29.9592827326681 & 0.333835783979233 \tabularnewline
18 & 39530 & 43672.1630263354 & 3495.66126032296 & -4142.16302633538 & 1.23296670253431 \tabularnewline
19 & 59648 & 53673.2917022048 & 8021.82439651883 & 5974.70829779517 & 1.30306317905240 \tabularnewline
20 & 61031 & 59842.3696226883 & 6730.77261204223 & 1188.63037731172 & -0.371467468909485 \tabularnewline
21 & 55560 & 59281.7448383119 & 1648.19613009143 & -3721.74483831189 & -1.46205080255301 \tabularnewline
22 & 43877 & 47941.0967737009 & -7405.47656194947 & -4064.09677370087 & -2.60471367136971 \tabularnewline
23 & 38510 & 39063.8369982592 & -8430.9988421114 & -553.836998259239 & -0.295022567138393 \tabularnewline
24 & 36085 & 33352.9072516004 & -6537.60629734989 & 2732.09274839963 & 0.54485842900725 \tabularnewline
25 & 35994 & 35089.7448842835 & -777.408143156459 & 904.255115716506 & 1.66203973610960 \tabularnewline
26 & 32617 & 32448.5817439652 & -2076.48232482017 & 168.418256034769 & -0.374255606161042 \tabularnewline
27 & 30001 & 29617.9250730681 & -2596.69665383055 & 383.074926931942 & -0.149313923462349 \tabularnewline
28 & 27894 & 26136.2778234155 & -3205.52312296511 & 1757.72217658450 & -0.176113986265837 \tabularnewline
29 & 26083 & 26954.1109883542 & -423.976910562849 & -871.110988354215 & 0.801730521601201 \tabularnewline
30 & 28817 & 33937.7996426126 & 4682.1417449956 & -5120.7996426126 & 1.46613494810727 \tabularnewline
31 & 48742 & 42505.8811773827 & 7355.44942382184 & 6236.11882261734 & 0.768965156121511 \tabularnewline
32 & 49915 & 47606.1898298507 & 5802.45688825747 & 2308.81017014934 & -0.446898132348216 \tabularnewline
33 & 40264 & 42698.495161203 & -1578.17968080328 & -2434.495161203 & -2.12317677200541 \tabularnewline
34 & 34276 & 37913.0167580412 & -3788.43965364417 & -3637.01675804118 & -0.635865626585045 \tabularnewline
35 & 30426 & 32318.9483593869 & -5032.14034101896 & -1892.94835938688 & -0.357789999243963 \tabularnewline
36 & 30793 & 29861.0325490950 & -3260.16378515952 & 931.967450904958 & 0.510085292336623 \tabularnewline
37 & 29855 & 27944.6865193557 & -2334.47600684930 & 1910.31348064427 & 0.266779165340143 \tabularnewline
38 & 28081 & 26763.0827706027 & -1540.58776441705 & 1317.91722939732 & 0.228354119483739 \tabularnewline
39 & 26820 & 25427.3438382166 & -1400.23311417929 & 1392.65616178337 & 0.040331658354731 \tabularnewline
40 & 25782 & 24835.0568374816 & -847.448526610465 & 946.943162518361 & 0.159424443417562 \tabularnewline
41 & 22654 & 25819.3665913805 & 409.441124164234 & -3165.36659138052 & 0.362209378686596 \tabularnewline
42 & 27373 & 32765.1964503075 & 4891.25038678277 & -5392.19645030752 & 1.28804971836422 \tabularnewline
43 & 43675 & 37433.7251199897 & 4738.80927215971 & 6241.27488001034 & -0.0438297992020393 \tabularnewline
44 & 45096 & 40069.8377102488 & 3299.28618322564 & 5026.16228975124 & -0.414172042334057 \tabularnewline
45 & 38145 & 40244.8072815501 & 1158.92410154342 & -2099.80728155011 & -0.615752566302866 \tabularnewline
46 & 34017 & 37902.810464905 & -1239.66534497966 & -3885.810464905 & -0.690023147959359 \tabularnewline
47 & 31537 & 34644.3636038226 & -2622.29099215778 & -3107.36360382258 & -0.397788341007762 \tabularnewline
48 & 33814 & 32934.157719665 & -1997.71760061051 & 879.842280334991 & 0.179793654454959 \tabularnewline
49 & 36531 & 33968.2677274528 & 79.662155437192 & 2562.73227254718 & 0.59818552619235 \tabularnewline
50 & 36935 & 35099.4261595517 & 799.633960729648 & 1835.57384044826 & 0.207038055815206 \tabularnewline
51 & 36497 & 35141.9142912602 & 282.737822970364 & 1355.08570873980 & -0.148605061734198 \tabularnewline
52 & 35110 & 34899.7905536118 & -75.2888927711292 & 210.209446388207 & -0.103140833765052 \tabularnewline
53 & 33137 & 37795.4940226097 & 1954.96653353691 & -4658.4940226097 & 0.584835304048984 \tabularnewline
54 & 37407 & 42466.8871995206 & 3811.37251798781 & -5059.8871995206 & 0.533829878715382 \tabularnewline
55 & 53963 & 47190.5011274525 & 4434.01229793985 & 6772.49887254746 & 0.179012405974210 \tabularnewline
56 & 56602 & 50896.4363919545 & 3937.1926959766 & 5705.56360804546 & -0.142913874456852 \tabularnewline
57 & 49694 & 51468.2766990747 & 1639.83236233210 & -1774.27669907469 & -0.660927905622397 \tabularnewline
58 & 43957 & 48267.7475260176 & -1664.87946479897 & -4310.74752601763 & -0.9507332654719 \tabularnewline
59 & 41723 & 45313.1326125358 & -2545.29762762862 & -3590.13261253583 & -0.253325304533689 \tabularnewline
60 & 45599 & 45066.0274832496 & -976.293511926042 & 532.972516750367 & 0.451620096662118 \tabularnewline
61 & 42503 & 41079.2148478209 & -3032.42123062337 & 1423.78515217905 & -0.591784028094205 \tabularnewline
62 & 42153 & 39241.9736353241 & -2216.74095024341 & 2911.02636467590 & 0.234553570577528 \tabularnewline
63 & 39098 & 37323.8789318702 & -2013.31666491904 & 1774.12106812978 & 0.0584972040110666 \tabularnewline
64 & 37449 & 37534.0867613161 & -499.512551163299 & -85.0867613160517 & 0.435879781063916 \tabularnewline
65 & 34748 & 39775.0542876908 & 1368.48657138000 & -5027.05428769084 & 0.537931746119703 \tabularnewline
66 & 36548 & 42079.270100975 & 2006.50738575646 & -5531.270100975 & 0.183526261792228 \tabularnewline
67 & 53639 & 46329.9010793479 & 3535.34653224705 & 7309.09892065214 & 0.439587847351093 \tabularnewline
68 & 55289 & 48919.2429102319 & 2891.17159748945 & 6369.75708976808 & -0.185278320732578 \tabularnewline
69 & 47774 & 48789.9459489652 & 834.151382728867 & -1015.94594896516 & -0.591773463809047 \tabularnewline
70 & 42156 & 46880.6418009678 & -1034.44223846550 & -4724.64180096778 & -0.53761277971524 \tabularnewline
71 & 38019 & 42992.6019574356 & -2978.10248868457 & -4973.60195743558 & -0.559299989947147 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116508&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]49915[/C][C]49915[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]47469[/C][C]48054.9102584259[/C][C]-1908.51207570129[/C][C]-585.910258425918[/C][C]-0.625488600724794[/C][/ROW]
[ROW][C]3[/C][C]45652[/C][C]45445.8356412282[/C][C]-2397.35536871778[/C][C]206.164358771802[/C][C]-0.149024366962252[/C][/ROW]
[ROW][C]4[/C][C]43492[/C][C]43332.3434749779[/C][C]-2187.19975647116[/C][C]159.656525022101[/C][C]0.0621313834064608[/C][/ROW]
[ROW][C]5[/C][C]41087[/C][C]41106.6751007528[/C][C]-2215.08493897911[/C][C]-19.6751007527871[/C][C]-0.00795648533898918[/C][/ROW]
[ROW][C]6[/C][C]42931[/C][C]42052.4395942928[/C][C]64.9362536785892[/C][C]878.56040570721[/C][C]0.65680299294174[/C][/ROW]
[ROW][C]7[/C][C]67256[/C][C]62050.9839690999[/C][C]14488.8715298131[/C][C]5205.01603090007[/C][C]4.15121258854616[/C][/ROW]
[ROW][C]8[/C][C]72316[/C][C]74531.9347155147[/C][C]13035.1133053156[/C][C]-2215.93471551473[/C][C]-0.418188136631675[/C][/ROW]
[ROW][C]9[/C][C]65624[/C][C]70219.9507997024[/C][C]477.10632617661[/C][C]-4595.95079970239[/C][C]-3.61273968604251[/C][/ROW]
[ROW][C]10[/C][C]59450[/C][C]60738.6466338554[/C][C]-6730.69668451185[/C][C]-1288.64663385539[/C][C]-2.07352969680377[/C][/ROW]
[ROW][C]11[/C][C]52851[/C][C]52451.8762318613[/C][C]-7856.89447658363[/C][C]399.123768138654[/C][C]-0.323981888124756[/C][/ROW]
[ROW][C]12[/C][C]51214[/C][C]49691.5549776427[/C][C]-4168.21452006542[/C][C]1522.44502235728[/C][C]1.06115163246103[/C][/ROW]
[ROW][C]13[/C][C]44092[/C][C]44728.4748478281[/C][C]-4742.05998035167[/C][C]-636.474847828119[/C][C]-0.165575580733713[/C][/ROW]
[ROW][C]14[/C][C]43752[/C][C]43191.9849351941[/C][C]-2419.20916876936[/C][C]560.015064805885[/C][C]0.678694001099109[/C][/ROW]
[ROW][C]15[/C][C]40320[/C][C]40188.5198269027[/C][C]-2827.23959030123[/C][C]131.480173097352[/C][C]-0.116793903281184[/C][/ROW]
[ROW][C]16[/C][C]40551[/C][C]38604.222274751[/C][C]-1960.67452023494[/C][C]1946.77772524898[/C][C]0.253193330939974[/C][/ROW]
[ROW][C]17[/C][C]38329[/C][C]38299.0407172673[/C][C]-799.622126514284[/C][C]29.9592827326681[/C][C]0.333835783979233[/C][/ROW]
[ROW][C]18[/C][C]39530[/C][C]43672.1630263354[/C][C]3495.66126032296[/C][C]-4142.16302633538[/C][C]1.23296670253431[/C][/ROW]
[ROW][C]19[/C][C]59648[/C][C]53673.2917022048[/C][C]8021.82439651883[/C][C]5974.70829779517[/C][C]1.30306317905240[/C][/ROW]
[ROW][C]20[/C][C]61031[/C][C]59842.3696226883[/C][C]6730.77261204223[/C][C]1188.63037731172[/C][C]-0.371467468909485[/C][/ROW]
[ROW][C]21[/C][C]55560[/C][C]59281.7448383119[/C][C]1648.19613009143[/C][C]-3721.74483831189[/C][C]-1.46205080255301[/C][/ROW]
[ROW][C]22[/C][C]43877[/C][C]47941.0967737009[/C][C]-7405.47656194947[/C][C]-4064.09677370087[/C][C]-2.60471367136971[/C][/ROW]
[ROW][C]23[/C][C]38510[/C][C]39063.8369982592[/C][C]-8430.9988421114[/C][C]-553.836998259239[/C][C]-0.295022567138393[/C][/ROW]
[ROW][C]24[/C][C]36085[/C][C]33352.9072516004[/C][C]-6537.60629734989[/C][C]2732.09274839963[/C][C]0.54485842900725[/C][/ROW]
[ROW][C]25[/C][C]35994[/C][C]35089.7448842835[/C][C]-777.408143156459[/C][C]904.255115716506[/C][C]1.66203973610960[/C][/ROW]
[ROW][C]26[/C][C]32617[/C][C]32448.5817439652[/C][C]-2076.48232482017[/C][C]168.418256034769[/C][C]-0.374255606161042[/C][/ROW]
[ROW][C]27[/C][C]30001[/C][C]29617.9250730681[/C][C]-2596.69665383055[/C][C]383.074926931942[/C][C]-0.149313923462349[/C][/ROW]
[ROW][C]28[/C][C]27894[/C][C]26136.2778234155[/C][C]-3205.52312296511[/C][C]1757.72217658450[/C][C]-0.176113986265837[/C][/ROW]
[ROW][C]29[/C][C]26083[/C][C]26954.1109883542[/C][C]-423.976910562849[/C][C]-871.110988354215[/C][C]0.801730521601201[/C][/ROW]
[ROW][C]30[/C][C]28817[/C][C]33937.7996426126[/C][C]4682.1417449956[/C][C]-5120.7996426126[/C][C]1.46613494810727[/C][/ROW]
[ROW][C]31[/C][C]48742[/C][C]42505.8811773827[/C][C]7355.44942382184[/C][C]6236.11882261734[/C][C]0.768965156121511[/C][/ROW]
[ROW][C]32[/C][C]49915[/C][C]47606.1898298507[/C][C]5802.45688825747[/C][C]2308.81017014934[/C][C]-0.446898132348216[/C][/ROW]
[ROW][C]33[/C][C]40264[/C][C]42698.495161203[/C][C]-1578.17968080328[/C][C]-2434.495161203[/C][C]-2.12317677200541[/C][/ROW]
[ROW][C]34[/C][C]34276[/C][C]37913.0167580412[/C][C]-3788.43965364417[/C][C]-3637.01675804118[/C][C]-0.635865626585045[/C][/ROW]
[ROW][C]35[/C][C]30426[/C][C]32318.9483593869[/C][C]-5032.14034101896[/C][C]-1892.94835938688[/C][C]-0.357789999243963[/C][/ROW]
[ROW][C]36[/C][C]30793[/C][C]29861.0325490950[/C][C]-3260.16378515952[/C][C]931.967450904958[/C][C]0.510085292336623[/C][/ROW]
[ROW][C]37[/C][C]29855[/C][C]27944.6865193557[/C][C]-2334.47600684930[/C][C]1910.31348064427[/C][C]0.266779165340143[/C][/ROW]
[ROW][C]38[/C][C]28081[/C][C]26763.0827706027[/C][C]-1540.58776441705[/C][C]1317.91722939732[/C][C]0.228354119483739[/C][/ROW]
[ROW][C]39[/C][C]26820[/C][C]25427.3438382166[/C][C]-1400.23311417929[/C][C]1392.65616178337[/C][C]0.040331658354731[/C][/ROW]
[ROW][C]40[/C][C]25782[/C][C]24835.0568374816[/C][C]-847.448526610465[/C][C]946.943162518361[/C][C]0.159424443417562[/C][/ROW]
[ROW][C]41[/C][C]22654[/C][C]25819.3665913805[/C][C]409.441124164234[/C][C]-3165.36659138052[/C][C]0.362209378686596[/C][/ROW]
[ROW][C]42[/C][C]27373[/C][C]32765.1964503075[/C][C]4891.25038678277[/C][C]-5392.19645030752[/C][C]1.28804971836422[/C][/ROW]
[ROW][C]43[/C][C]43675[/C][C]37433.7251199897[/C][C]4738.80927215971[/C][C]6241.27488001034[/C][C]-0.0438297992020393[/C][/ROW]
[ROW][C]44[/C][C]45096[/C][C]40069.8377102488[/C][C]3299.28618322564[/C][C]5026.16228975124[/C][C]-0.414172042334057[/C][/ROW]
[ROW][C]45[/C][C]38145[/C][C]40244.8072815501[/C][C]1158.92410154342[/C][C]-2099.80728155011[/C][C]-0.615752566302866[/C][/ROW]
[ROW][C]46[/C][C]34017[/C][C]37902.810464905[/C][C]-1239.66534497966[/C][C]-3885.810464905[/C][C]-0.690023147959359[/C][/ROW]
[ROW][C]47[/C][C]31537[/C][C]34644.3636038226[/C][C]-2622.29099215778[/C][C]-3107.36360382258[/C][C]-0.397788341007762[/C][/ROW]
[ROW][C]48[/C][C]33814[/C][C]32934.157719665[/C][C]-1997.71760061051[/C][C]879.842280334991[/C][C]0.179793654454959[/C][/ROW]
[ROW][C]49[/C][C]36531[/C][C]33968.2677274528[/C][C]79.662155437192[/C][C]2562.73227254718[/C][C]0.59818552619235[/C][/ROW]
[ROW][C]50[/C][C]36935[/C][C]35099.4261595517[/C][C]799.633960729648[/C][C]1835.57384044826[/C][C]0.207038055815206[/C][/ROW]
[ROW][C]51[/C][C]36497[/C][C]35141.9142912602[/C][C]282.737822970364[/C][C]1355.08570873980[/C][C]-0.148605061734198[/C][/ROW]
[ROW][C]52[/C][C]35110[/C][C]34899.7905536118[/C][C]-75.2888927711292[/C][C]210.209446388207[/C][C]-0.103140833765052[/C][/ROW]
[ROW][C]53[/C][C]33137[/C][C]37795.4940226097[/C][C]1954.96653353691[/C][C]-4658.4940226097[/C][C]0.584835304048984[/C][/ROW]
[ROW][C]54[/C][C]37407[/C][C]42466.8871995206[/C][C]3811.37251798781[/C][C]-5059.8871995206[/C][C]0.533829878715382[/C][/ROW]
[ROW][C]55[/C][C]53963[/C][C]47190.5011274525[/C][C]4434.01229793985[/C][C]6772.49887254746[/C][C]0.179012405974210[/C][/ROW]
[ROW][C]56[/C][C]56602[/C][C]50896.4363919545[/C][C]3937.1926959766[/C][C]5705.56360804546[/C][C]-0.142913874456852[/C][/ROW]
[ROW][C]57[/C][C]49694[/C][C]51468.2766990747[/C][C]1639.83236233210[/C][C]-1774.27669907469[/C][C]-0.660927905622397[/C][/ROW]
[ROW][C]58[/C][C]43957[/C][C]48267.7475260176[/C][C]-1664.87946479897[/C][C]-4310.74752601763[/C][C]-0.9507332654719[/C][/ROW]
[ROW][C]59[/C][C]41723[/C][C]45313.1326125358[/C][C]-2545.29762762862[/C][C]-3590.13261253583[/C][C]-0.253325304533689[/C][/ROW]
[ROW][C]60[/C][C]45599[/C][C]45066.0274832496[/C][C]-976.293511926042[/C][C]532.972516750367[/C][C]0.451620096662118[/C][/ROW]
[ROW][C]61[/C][C]42503[/C][C]41079.2148478209[/C][C]-3032.42123062337[/C][C]1423.78515217905[/C][C]-0.591784028094205[/C][/ROW]
[ROW][C]62[/C][C]42153[/C][C]39241.9736353241[/C][C]-2216.74095024341[/C][C]2911.02636467590[/C][C]0.234553570577528[/C][/ROW]
[ROW][C]63[/C][C]39098[/C][C]37323.8789318702[/C][C]-2013.31666491904[/C][C]1774.12106812978[/C][C]0.0584972040110666[/C][/ROW]
[ROW][C]64[/C][C]37449[/C][C]37534.0867613161[/C][C]-499.512551163299[/C][C]-85.0867613160517[/C][C]0.435879781063916[/C][/ROW]
[ROW][C]65[/C][C]34748[/C][C]39775.0542876908[/C][C]1368.48657138000[/C][C]-5027.05428769084[/C][C]0.537931746119703[/C][/ROW]
[ROW][C]66[/C][C]36548[/C][C]42079.270100975[/C][C]2006.50738575646[/C][C]-5531.270100975[/C][C]0.183526261792228[/C][/ROW]
[ROW][C]67[/C][C]53639[/C][C]46329.9010793479[/C][C]3535.34653224705[/C][C]7309.09892065214[/C][C]0.439587847351093[/C][/ROW]
[ROW][C]68[/C][C]55289[/C][C]48919.2429102319[/C][C]2891.17159748945[/C][C]6369.75708976808[/C][C]-0.185278320732578[/C][/ROW]
[ROW][C]69[/C][C]47774[/C][C]48789.9459489652[/C][C]834.151382728867[/C][C]-1015.94594896516[/C][C]-0.591773463809047[/C][/ROW]
[ROW][C]70[/C][C]42156[/C][C]46880.6418009678[/C][C]-1034.44223846550[/C][C]-4724.64180096778[/C][C]-0.53761277971524[/C][/ROW]
[ROW][C]71[/C][C]38019[/C][C]42992.6019574356[/C][C]-2978.10248868457[/C][C]-4973.60195743558[/C][C]-0.559299989947147[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116508&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116508&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
14991549915000
24746948054.9102584259-1908.51207570129-585.910258425918-0.625488600724794
34565245445.8356412282-2397.35536871778206.164358771802-0.149024366962252
44349243332.3434749779-2187.19975647116159.6565250221010.0621313834064608
54108741106.6751007528-2215.08493897911-19.6751007527871-0.00795648533898918
64293142052.439594292864.9362536785892878.560405707210.65680299294174
76725662050.983969099914488.87152981315205.016030900074.15121258854616
87231674531.934715514713035.1133053156-2215.93471551473-0.418188136631675
96562470219.9507997024477.10632617661-4595.95079970239-3.61273968604251
105945060738.6466338554-6730.69668451185-1288.64663385539-2.07352969680377
115285152451.8762318613-7856.89447658363399.123768138654-0.323981888124756
125121449691.5549776427-4168.214520065421522.445022357281.06115163246103
134409244728.4748478281-4742.05998035167-636.474847828119-0.165575580733713
144375243191.9849351941-2419.20916876936560.0150648058850.678694001099109
154032040188.5198269027-2827.23959030123131.480173097352-0.116793903281184
164055138604.222274751-1960.674520234941946.777725248980.253193330939974
173832938299.0407172673-799.62212651428429.95928273266810.333835783979233
183953043672.16302633543495.66126032296-4142.163026335381.23296670253431
195964853673.29170220488021.824396518835974.708297795171.30306317905240
206103159842.36962268836730.772612042231188.63037731172-0.371467468909485
215556059281.74483831191648.19613009143-3721.74483831189-1.46205080255301
224387747941.0967737009-7405.47656194947-4064.09677370087-2.60471367136971
233851039063.8369982592-8430.9988421114-553.836998259239-0.295022567138393
243608533352.9072516004-6537.606297349892732.092748399630.54485842900725
253599435089.7448842835-777.408143156459904.2551157165061.66203973610960
263261732448.5817439652-2076.48232482017168.418256034769-0.374255606161042
273000129617.9250730681-2596.69665383055383.074926931942-0.149313923462349
282789426136.2778234155-3205.523122965111757.72217658450-0.176113986265837
292608326954.1109883542-423.976910562849-871.1109883542150.801730521601201
302881733937.79964261264682.1417449956-5120.79964261261.46613494810727
314874242505.88117738277355.449423821846236.118822617340.768965156121511
324991547606.18982985075802.456888257472308.81017014934-0.446898132348216
334026442698.495161203-1578.17968080328-2434.495161203-2.12317677200541
343427637913.0167580412-3788.43965364417-3637.01675804118-0.635865626585045
353042632318.9483593869-5032.14034101896-1892.94835938688-0.357789999243963
363079329861.0325490950-3260.16378515952931.9674509049580.510085292336623
372985527944.6865193557-2334.476006849301910.313480644270.266779165340143
382808126763.0827706027-1540.587764417051317.917229397320.228354119483739
392682025427.3438382166-1400.233114179291392.656161783370.040331658354731
402578224835.0568374816-847.448526610465946.9431625183610.159424443417562
412265425819.3665913805409.441124164234-3165.366591380520.362209378686596
422737332765.19645030754891.25038678277-5392.196450307521.28804971836422
434367537433.72511998974738.809272159716241.27488001034-0.0438297992020393
444509640069.83771024883299.286183225645026.16228975124-0.414172042334057
453814540244.80728155011158.92410154342-2099.80728155011-0.615752566302866
463401737902.810464905-1239.66534497966-3885.810464905-0.690023147959359
473153734644.3636038226-2622.29099215778-3107.36360382258-0.397788341007762
483381432934.157719665-1997.71760061051879.8422803349910.179793654454959
493653133968.267727452879.6621554371922562.732272547180.59818552619235
503693535099.4261595517799.6339607296481835.573840448260.207038055815206
513649735141.9142912602282.7378229703641355.08570873980-0.148605061734198
523511034899.7905536118-75.2888927711292210.209446388207-0.103140833765052
533313737795.49402260971954.96653353691-4658.49402260970.584835304048984
543740742466.88719952063811.37251798781-5059.88719952060.533829878715382
555396347190.50112745254434.012297939856772.498872547460.179012405974210
565660250896.43639195453937.19269597665705.56360804546-0.142913874456852
574969451468.27669907471639.83236233210-1774.27669907469-0.660927905622397
584395748267.7475260176-1664.87946479897-4310.74752601763-0.9507332654719
594172345313.1326125358-2545.29762762862-3590.13261253583-0.253325304533689
604559945066.0274832496-976.293511926042532.9725167503670.451620096662118
614250341079.2148478209-3032.421230623371423.78515217905-0.591784028094205
624215339241.9736353241-2216.740950243412911.026364675900.234553570577528
633909837323.8789318702-2013.316664919041774.121068129780.0584972040110666
643744937534.0867613161-499.512551163299-85.08676131605170.435879781063916
653474839775.05428769081368.48657138000-5027.054287690840.537931746119703
663654842079.2701009752006.50738575646-5531.2701009750.183526261792228
675363946329.90107934793535.346532247057309.098920652140.439587847351093
685528948919.24291023192891.171597489456369.75708976808-0.185278320732578
694777448789.9459489652834.151382728867-1015.94594896516-0.591773463809047
704215646880.6418009678-1034.44223846550-4724.64180096778-0.53761277971524
713801942992.6019574356-2978.10248868457-4973.60195743558-0.559299989947147



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')