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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 19:35:27 +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/t1293564807jcur2lex67a98l4.htm/, Retrieved Sun, 05 May 2024 03:01:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116525, Retrieved Sun, 05 May 2024 03:01:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [Paper] [2010-12-28 19:35:27] [d5e0edb7e0239841e94676417b2a1e2e] [Current]
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Dataseries X:
961
935
956
951
986
980
1031
1059
1036
1023
1030
1075
1151
1220
1290
1330
1419
1443
1516
1546
1579
1591
1603
1606
1616
1628
1594
1596
1526
1535
1581
1611
1571
1535
1498
1493
1480
1448
1462
1428
1315
1186
1230
1271
1243
1220
1214
1227
1262
1274
1272
1249
1266
1307
1345
1369
1374
1400
1425
1465
1510
1508
1512
1539
1569
1571
1650
1736
1700
1731
1752




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116525&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116525&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116525&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1961961000
2935936.438293083233-2.27637477957655-1.43829308323263-0.499108215241076
3956956.5209053369051.88090707857587-0.520905336905050.692943432588317
4951952.624393271530.522303979089565-1.62439327153079-0.172794216955631
5986986.3363405204999.23595056033624-0.3363405204988090.974877953007878
6980981.9232316196935.4538208472925-1.92323161969277-0.396897826292056
710311031.0223351320817.8752955290597-0.02233513207790171.26251599520245
810591060.3550211471521.1797372184675-1.355021147153450.330552661263599
910361038.522836210668.69191806663708-2.52283621065761-1.23930631232365
1010231024.536059720452.08557974162984-1.53605972044556-0.653029879979702
1110301030.987106577503.35937377700362-0.9871065775020660.125665013576204
1210751075.2445211722015.3030159167281-0.2445211721978511.17713119431908
1311511123.5254140601124.616035569711827.47458593989251.09031624085282
1412201220.1935428937344.5601500537191-0.1935428937346831.74420887730978
1512901289.1756603602451.6428892861240.8243396397565340.700164244363578
1613301333.0247122971249.3735462597942-3.02471229712164-0.222575238569513
1714191416.3824319009559.25835018119282.617568099051710.97174755754607
1814431447.5011931116451.0761606487051-4.50119311164243-0.80509743647965
1915161515.2079778722755.91144704277120.7920221277286520.475932948220083
2015461547.2784844449948.9798502867707-1.27848444498643-0.682380584106402
2115791580.8005376912744.4854994607685-1.80053769126774-0.442481985966224
2215911593.1115177885335.1303677775772-2.11151778853419-0.92108114172083
2316031604.8639201641128.3320520125587-1.86392016410777-0.669373640446721
2416061607.6046027514120.8967134286134-1.60460275140648-0.732125689047544
2516161610.1408085848115.62476594361425.85919141518533-0.561064670792634
2616281629.0212064012116.5433281641576-1.021206401214510.0850458557114716
2715941595.206891902562.01487705230139-1.20689190256321-1.43764506684695
2815961599.917293625842.79662476399651-3.917293625841160.0767551914209629
2915261526.13634724695-19.3957822855772-0.136347246953412-2.18190432396939
3015351537.31240326809-10.5385872992571-2.312403268092600.871616335450915
3115811576.335152449923.819212115856674.664847550078031.41333220373628
3216111610.7588876892412.68517572179940.2411123107564650.872841590170346
3315711574.92809426307-1.36985704441351-3.92809426307030-1.38378555078528
3415351537.57609053635-11.7945013977784-2.57609053635208-1.02640195154334
3514981499.49920631234-19.4097065379955-1.49920631233638-0.749814275253908
3614931492.37303268138-15.8558119902990.6269673186218190.350092537472794
3714801475.05430200280-16.27707444797914.94569799719625-0.0433772342277661
3814481446.67049618222-19.72053084541651.32950381777925-0.326431159583033
3914621461.85270255144-9.682725860785460.1472974485554040.992772385235179
4014281428.28978373195-16.5890962198329-0.289783731945483-0.678791871948481
4113151322.11398647155-42.4875884672512-7.11398647154654-2.54628934253845
4211861195.57292617751-66.7794317357355-9.57292617750833-2.39054537875425
4312301220.13881620159-40.38167953497279.861183798405542.59859029667091
4412711263.54006076648-16.16952281509107.459939233519472.38370025756123
4512431246.58987670696-16.395128349875-3.58987670695951-0.0222122520143006
4612201221.47681180011-18.91475317103-1.47681180010925-0.248084376934295
4712141215.24296723906-15.2498243490977-1.242967239059040.36084984568892
4812271224.68496850432-8.125744503854792.315031495682480.702234398576933
4912621252.253371816282.158017608796479.746628183715081.04144267450171
5012741275.682340024548.23213147249949-1.682340024544750.583172495751679
5112721273.453759755805.22911195984318-1.45375975579564-0.296713112341198
5212491245.81723425674-4.257195871336923.18276574326016-0.933210584713405
5312661262.799306509631.872617295359623.200693490367470.602682430644237
5413071318.3597588367317.3627980171068-11.35975883673401.52433229881749
5513451342.0612499901219.19156320810272.938750009876070.180024785351115
5613691362.0064092585019.40898237321076.993590741503510.0214053063621615
5713741377.1263227066618.1715075646823-3.12632270665660-0.121838533672427
5814001401.4194779404719.9378559517536-1.419477940469840.17391803019349
5914251427.1764730511121.6166500044912-2.176473051109640.165287869637088
6014651464.0630429340326.01453691087560.9369570659669780.433764151234548
6115101501.6574088987529.35018143807848.342591101247870.334575383573677
6215081510.4396804857123.4642753438675-2.43968048571409-0.56942788806412
6315121511.8172459425517.12992243671080.182754057446914-0.625238911494709
6415391536.0723218315819.18354794777382.927678168420370.202173286452353
6515691569.1765765433223.1964785388394-0.1765765433233480.394579951374799
6615711583.9901966624720.7806479673288-12.9901966624666-0.237722109364262
6716501644.2500418838932.15742274734245.749958116106391.11992954661253
6817361725.4193426019146.281433551893710.58065739809321.39054652026512
6917001709.3808046561828.3215536995056-9.38080465618261-1.76830337762832
7017311732.7382491560626.8908706126999-1.73824915605955-0.140867939939903
7117521755.6875686650025.7552284609808-3.68756866499811-0.111808362882112

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 961 & 961 & 0 & 0 & 0 \tabularnewline
2 & 935 & 936.438293083233 & -2.27637477957655 & -1.43829308323263 & -0.499108215241076 \tabularnewline
3 & 956 & 956.520905336905 & 1.88090707857587 & -0.52090533690505 & 0.692943432588317 \tabularnewline
4 & 951 & 952.62439327153 & 0.522303979089565 & -1.62439327153079 & -0.172794216955631 \tabularnewline
5 & 986 & 986.336340520499 & 9.23595056033624 & -0.336340520498809 & 0.974877953007878 \tabularnewline
6 & 980 & 981.923231619693 & 5.4538208472925 & -1.92323161969277 & -0.396897826292056 \tabularnewline
7 & 1031 & 1031.02233513208 & 17.8752955290597 & -0.0223351320779017 & 1.26251599520245 \tabularnewline
8 & 1059 & 1060.35502114715 & 21.1797372184675 & -1.35502114715345 & 0.330552661263599 \tabularnewline
9 & 1036 & 1038.52283621066 & 8.69191806663708 & -2.52283621065761 & -1.23930631232365 \tabularnewline
10 & 1023 & 1024.53605972045 & 2.08557974162984 & -1.53605972044556 & -0.653029879979702 \tabularnewline
11 & 1030 & 1030.98710657750 & 3.35937377700362 & -0.987106577502066 & 0.125665013576204 \tabularnewline
12 & 1075 & 1075.24452117220 & 15.3030159167281 & -0.244521172197851 & 1.17713119431908 \tabularnewline
13 & 1151 & 1123.52541406011 & 24.6160355697118 & 27.4745859398925 & 1.09031624085282 \tabularnewline
14 & 1220 & 1220.19354289373 & 44.5601500537191 & -0.193542893734683 & 1.74420887730978 \tabularnewline
15 & 1290 & 1289.17566036024 & 51.642889286124 & 0.824339639756534 & 0.700164244363578 \tabularnewline
16 & 1330 & 1333.02471229712 & 49.3735462597942 & -3.02471229712164 & -0.222575238569513 \tabularnewline
17 & 1419 & 1416.38243190095 & 59.2583501811928 & 2.61756809905171 & 0.97174755754607 \tabularnewline
18 & 1443 & 1447.50119311164 & 51.0761606487051 & -4.50119311164243 & -0.80509743647965 \tabularnewline
19 & 1516 & 1515.20797787227 & 55.9114470427712 & 0.792022127728652 & 0.475932948220083 \tabularnewline
20 & 1546 & 1547.27848444499 & 48.9798502867707 & -1.27848444498643 & -0.682380584106402 \tabularnewline
21 & 1579 & 1580.80053769127 & 44.4854994607685 & -1.80053769126774 & -0.442481985966224 \tabularnewline
22 & 1591 & 1593.11151778853 & 35.1303677775772 & -2.11151778853419 & -0.92108114172083 \tabularnewline
23 & 1603 & 1604.86392016411 & 28.3320520125587 & -1.86392016410777 & -0.669373640446721 \tabularnewline
24 & 1606 & 1607.60460275141 & 20.8967134286134 & -1.60460275140648 & -0.732125689047544 \tabularnewline
25 & 1616 & 1610.14080858481 & 15.6247659436142 & 5.85919141518533 & -0.561064670792634 \tabularnewline
26 & 1628 & 1629.02120640121 & 16.5433281641576 & -1.02120640121451 & 0.0850458557114716 \tabularnewline
27 & 1594 & 1595.20689190256 & 2.01487705230139 & -1.20689190256321 & -1.43764506684695 \tabularnewline
28 & 1596 & 1599.91729362584 & 2.79662476399651 & -3.91729362584116 & 0.0767551914209629 \tabularnewline
29 & 1526 & 1526.13634724695 & -19.3957822855772 & -0.136347246953412 & -2.18190432396939 \tabularnewline
30 & 1535 & 1537.31240326809 & -10.5385872992571 & -2.31240326809260 & 0.871616335450915 \tabularnewline
31 & 1581 & 1576.33515244992 & 3.81921211585667 & 4.66484755007803 & 1.41333220373628 \tabularnewline
32 & 1611 & 1610.75888768924 & 12.6851757217994 & 0.241112310756465 & 0.872841590170346 \tabularnewline
33 & 1571 & 1574.92809426307 & -1.36985704441351 & -3.92809426307030 & -1.38378555078528 \tabularnewline
34 & 1535 & 1537.57609053635 & -11.7945013977784 & -2.57609053635208 & -1.02640195154334 \tabularnewline
35 & 1498 & 1499.49920631234 & -19.4097065379955 & -1.49920631233638 & -0.749814275253908 \tabularnewline
36 & 1493 & 1492.37303268138 & -15.855811990299 & 0.626967318621819 & 0.350092537472794 \tabularnewline
37 & 1480 & 1475.05430200280 & -16.2770744479791 & 4.94569799719625 & -0.0433772342277661 \tabularnewline
38 & 1448 & 1446.67049618222 & -19.7205308454165 & 1.32950381777925 & -0.326431159583033 \tabularnewline
39 & 1462 & 1461.85270255144 & -9.68272586078546 & 0.147297448555404 & 0.992772385235179 \tabularnewline
40 & 1428 & 1428.28978373195 & -16.5890962198329 & -0.289783731945483 & -0.678791871948481 \tabularnewline
41 & 1315 & 1322.11398647155 & -42.4875884672512 & -7.11398647154654 & -2.54628934253845 \tabularnewline
42 & 1186 & 1195.57292617751 & -66.7794317357355 & -9.57292617750833 & -2.39054537875425 \tabularnewline
43 & 1230 & 1220.13881620159 & -40.3816795349727 & 9.86118379840554 & 2.59859029667091 \tabularnewline
44 & 1271 & 1263.54006076648 & -16.1695228150910 & 7.45993923351947 & 2.38370025756123 \tabularnewline
45 & 1243 & 1246.58987670696 & -16.395128349875 & -3.58987670695951 & -0.0222122520143006 \tabularnewline
46 & 1220 & 1221.47681180011 & -18.91475317103 & -1.47681180010925 & -0.248084376934295 \tabularnewline
47 & 1214 & 1215.24296723906 & -15.2498243490977 & -1.24296723905904 & 0.36084984568892 \tabularnewline
48 & 1227 & 1224.68496850432 & -8.12574450385479 & 2.31503149568248 & 0.702234398576933 \tabularnewline
49 & 1262 & 1252.25337181628 & 2.15801760879647 & 9.74662818371508 & 1.04144267450171 \tabularnewline
50 & 1274 & 1275.68234002454 & 8.23213147249949 & -1.68234002454475 & 0.583172495751679 \tabularnewline
51 & 1272 & 1273.45375975580 & 5.22911195984318 & -1.45375975579564 & -0.296713112341198 \tabularnewline
52 & 1249 & 1245.81723425674 & -4.25719587133692 & 3.18276574326016 & -0.933210584713405 \tabularnewline
53 & 1266 & 1262.79930650963 & 1.87261729535962 & 3.20069349036747 & 0.602682430644237 \tabularnewline
54 & 1307 & 1318.35975883673 & 17.3627980171068 & -11.3597588367340 & 1.52433229881749 \tabularnewline
55 & 1345 & 1342.06124999012 & 19.1915632081027 & 2.93875000987607 & 0.180024785351115 \tabularnewline
56 & 1369 & 1362.00640925850 & 19.4089823732107 & 6.99359074150351 & 0.0214053063621615 \tabularnewline
57 & 1374 & 1377.12632270666 & 18.1715075646823 & -3.12632270665660 & -0.121838533672427 \tabularnewline
58 & 1400 & 1401.41947794047 & 19.9378559517536 & -1.41947794046984 & 0.17391803019349 \tabularnewline
59 & 1425 & 1427.17647305111 & 21.6166500044912 & -2.17647305110964 & 0.165287869637088 \tabularnewline
60 & 1465 & 1464.06304293403 & 26.0145369108756 & 0.936957065966978 & 0.433764151234548 \tabularnewline
61 & 1510 & 1501.65740889875 & 29.3501814380784 & 8.34259110124787 & 0.334575383573677 \tabularnewline
62 & 1508 & 1510.43968048571 & 23.4642753438675 & -2.43968048571409 & -0.56942788806412 \tabularnewline
63 & 1512 & 1511.81724594255 & 17.1299224367108 & 0.182754057446914 & -0.625238911494709 \tabularnewline
64 & 1539 & 1536.07232183158 & 19.1835479477738 & 2.92767816842037 & 0.202173286452353 \tabularnewline
65 & 1569 & 1569.17657654332 & 23.1964785388394 & -0.176576543323348 & 0.394579951374799 \tabularnewline
66 & 1571 & 1583.99019666247 & 20.7806479673288 & -12.9901966624666 & -0.237722109364262 \tabularnewline
67 & 1650 & 1644.25004188389 & 32.1574227473424 & 5.74995811610639 & 1.11992954661253 \tabularnewline
68 & 1736 & 1725.41934260191 & 46.2814335518937 & 10.5806573980932 & 1.39054652026512 \tabularnewline
69 & 1700 & 1709.38080465618 & 28.3215536995056 & -9.38080465618261 & -1.76830337762832 \tabularnewline
70 & 1731 & 1732.73824915606 & 26.8908706126999 & -1.73824915605955 & -0.140867939939903 \tabularnewline
71 & 1752 & 1755.68756866500 & 25.7552284609808 & -3.68756866499811 & -0.111808362882112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116525&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]961[/C][C]961[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]935[/C][C]936.438293083233[/C][C]-2.27637477957655[/C][C]-1.43829308323263[/C][C]-0.499108215241076[/C][/ROW]
[ROW][C]3[/C][C]956[/C][C]956.520905336905[/C][C]1.88090707857587[/C][C]-0.52090533690505[/C][C]0.692943432588317[/C][/ROW]
[ROW][C]4[/C][C]951[/C][C]952.62439327153[/C][C]0.522303979089565[/C][C]-1.62439327153079[/C][C]-0.172794216955631[/C][/ROW]
[ROW][C]5[/C][C]986[/C][C]986.336340520499[/C][C]9.23595056033624[/C][C]-0.336340520498809[/C][C]0.974877953007878[/C][/ROW]
[ROW][C]6[/C][C]980[/C][C]981.923231619693[/C][C]5.4538208472925[/C][C]-1.92323161969277[/C][C]-0.396897826292056[/C][/ROW]
[ROW][C]7[/C][C]1031[/C][C]1031.02233513208[/C][C]17.8752955290597[/C][C]-0.0223351320779017[/C][C]1.26251599520245[/C][/ROW]
[ROW][C]8[/C][C]1059[/C][C]1060.35502114715[/C][C]21.1797372184675[/C][C]-1.35502114715345[/C][C]0.330552661263599[/C][/ROW]
[ROW][C]9[/C][C]1036[/C][C]1038.52283621066[/C][C]8.69191806663708[/C][C]-2.52283621065761[/C][C]-1.23930631232365[/C][/ROW]
[ROW][C]10[/C][C]1023[/C][C]1024.53605972045[/C][C]2.08557974162984[/C][C]-1.53605972044556[/C][C]-0.653029879979702[/C][/ROW]
[ROW][C]11[/C][C]1030[/C][C]1030.98710657750[/C][C]3.35937377700362[/C][C]-0.987106577502066[/C][C]0.125665013576204[/C][/ROW]
[ROW][C]12[/C][C]1075[/C][C]1075.24452117220[/C][C]15.3030159167281[/C][C]-0.244521172197851[/C][C]1.17713119431908[/C][/ROW]
[ROW][C]13[/C][C]1151[/C][C]1123.52541406011[/C][C]24.6160355697118[/C][C]27.4745859398925[/C][C]1.09031624085282[/C][/ROW]
[ROW][C]14[/C][C]1220[/C][C]1220.19354289373[/C][C]44.5601500537191[/C][C]-0.193542893734683[/C][C]1.74420887730978[/C][/ROW]
[ROW][C]15[/C][C]1290[/C][C]1289.17566036024[/C][C]51.642889286124[/C][C]0.824339639756534[/C][C]0.700164244363578[/C][/ROW]
[ROW][C]16[/C][C]1330[/C][C]1333.02471229712[/C][C]49.3735462597942[/C][C]-3.02471229712164[/C][C]-0.222575238569513[/C][/ROW]
[ROW][C]17[/C][C]1419[/C][C]1416.38243190095[/C][C]59.2583501811928[/C][C]2.61756809905171[/C][C]0.97174755754607[/C][/ROW]
[ROW][C]18[/C][C]1443[/C][C]1447.50119311164[/C][C]51.0761606487051[/C][C]-4.50119311164243[/C][C]-0.80509743647965[/C][/ROW]
[ROW][C]19[/C][C]1516[/C][C]1515.20797787227[/C][C]55.9114470427712[/C][C]0.792022127728652[/C][C]0.475932948220083[/C][/ROW]
[ROW][C]20[/C][C]1546[/C][C]1547.27848444499[/C][C]48.9798502867707[/C][C]-1.27848444498643[/C][C]-0.682380584106402[/C][/ROW]
[ROW][C]21[/C][C]1579[/C][C]1580.80053769127[/C][C]44.4854994607685[/C][C]-1.80053769126774[/C][C]-0.442481985966224[/C][/ROW]
[ROW][C]22[/C][C]1591[/C][C]1593.11151778853[/C][C]35.1303677775772[/C][C]-2.11151778853419[/C][C]-0.92108114172083[/C][/ROW]
[ROW][C]23[/C][C]1603[/C][C]1604.86392016411[/C][C]28.3320520125587[/C][C]-1.86392016410777[/C][C]-0.669373640446721[/C][/ROW]
[ROW][C]24[/C][C]1606[/C][C]1607.60460275141[/C][C]20.8967134286134[/C][C]-1.60460275140648[/C][C]-0.732125689047544[/C][/ROW]
[ROW][C]25[/C][C]1616[/C][C]1610.14080858481[/C][C]15.6247659436142[/C][C]5.85919141518533[/C][C]-0.561064670792634[/C][/ROW]
[ROW][C]26[/C][C]1628[/C][C]1629.02120640121[/C][C]16.5433281641576[/C][C]-1.02120640121451[/C][C]0.0850458557114716[/C][/ROW]
[ROW][C]27[/C][C]1594[/C][C]1595.20689190256[/C][C]2.01487705230139[/C][C]-1.20689190256321[/C][C]-1.43764506684695[/C][/ROW]
[ROW][C]28[/C][C]1596[/C][C]1599.91729362584[/C][C]2.79662476399651[/C][C]-3.91729362584116[/C][C]0.0767551914209629[/C][/ROW]
[ROW][C]29[/C][C]1526[/C][C]1526.13634724695[/C][C]-19.3957822855772[/C][C]-0.136347246953412[/C][C]-2.18190432396939[/C][/ROW]
[ROW][C]30[/C][C]1535[/C][C]1537.31240326809[/C][C]-10.5385872992571[/C][C]-2.31240326809260[/C][C]0.871616335450915[/C][/ROW]
[ROW][C]31[/C][C]1581[/C][C]1576.33515244992[/C][C]3.81921211585667[/C][C]4.66484755007803[/C][C]1.41333220373628[/C][/ROW]
[ROW][C]32[/C][C]1611[/C][C]1610.75888768924[/C][C]12.6851757217994[/C][C]0.241112310756465[/C][C]0.872841590170346[/C][/ROW]
[ROW][C]33[/C][C]1571[/C][C]1574.92809426307[/C][C]-1.36985704441351[/C][C]-3.92809426307030[/C][C]-1.38378555078528[/C][/ROW]
[ROW][C]34[/C][C]1535[/C][C]1537.57609053635[/C][C]-11.7945013977784[/C][C]-2.57609053635208[/C][C]-1.02640195154334[/C][/ROW]
[ROW][C]35[/C][C]1498[/C][C]1499.49920631234[/C][C]-19.4097065379955[/C][C]-1.49920631233638[/C][C]-0.749814275253908[/C][/ROW]
[ROW][C]36[/C][C]1493[/C][C]1492.37303268138[/C][C]-15.855811990299[/C][C]0.626967318621819[/C][C]0.350092537472794[/C][/ROW]
[ROW][C]37[/C][C]1480[/C][C]1475.05430200280[/C][C]-16.2770744479791[/C][C]4.94569799719625[/C][C]-0.0433772342277661[/C][/ROW]
[ROW][C]38[/C][C]1448[/C][C]1446.67049618222[/C][C]-19.7205308454165[/C][C]1.32950381777925[/C][C]-0.326431159583033[/C][/ROW]
[ROW][C]39[/C][C]1462[/C][C]1461.85270255144[/C][C]-9.68272586078546[/C][C]0.147297448555404[/C][C]0.992772385235179[/C][/ROW]
[ROW][C]40[/C][C]1428[/C][C]1428.28978373195[/C][C]-16.5890962198329[/C][C]-0.289783731945483[/C][C]-0.678791871948481[/C][/ROW]
[ROW][C]41[/C][C]1315[/C][C]1322.11398647155[/C][C]-42.4875884672512[/C][C]-7.11398647154654[/C][C]-2.54628934253845[/C][/ROW]
[ROW][C]42[/C][C]1186[/C][C]1195.57292617751[/C][C]-66.7794317357355[/C][C]-9.57292617750833[/C][C]-2.39054537875425[/C][/ROW]
[ROW][C]43[/C][C]1230[/C][C]1220.13881620159[/C][C]-40.3816795349727[/C][C]9.86118379840554[/C][C]2.59859029667091[/C][/ROW]
[ROW][C]44[/C][C]1271[/C][C]1263.54006076648[/C][C]-16.1695228150910[/C][C]7.45993923351947[/C][C]2.38370025756123[/C][/ROW]
[ROW][C]45[/C][C]1243[/C][C]1246.58987670696[/C][C]-16.395128349875[/C][C]-3.58987670695951[/C][C]-0.0222122520143006[/C][/ROW]
[ROW][C]46[/C][C]1220[/C][C]1221.47681180011[/C][C]-18.91475317103[/C][C]-1.47681180010925[/C][C]-0.248084376934295[/C][/ROW]
[ROW][C]47[/C][C]1214[/C][C]1215.24296723906[/C][C]-15.2498243490977[/C][C]-1.24296723905904[/C][C]0.36084984568892[/C][/ROW]
[ROW][C]48[/C][C]1227[/C][C]1224.68496850432[/C][C]-8.12574450385479[/C][C]2.31503149568248[/C][C]0.702234398576933[/C][/ROW]
[ROW][C]49[/C][C]1262[/C][C]1252.25337181628[/C][C]2.15801760879647[/C][C]9.74662818371508[/C][C]1.04144267450171[/C][/ROW]
[ROW][C]50[/C][C]1274[/C][C]1275.68234002454[/C][C]8.23213147249949[/C][C]-1.68234002454475[/C][C]0.583172495751679[/C][/ROW]
[ROW][C]51[/C][C]1272[/C][C]1273.45375975580[/C][C]5.22911195984318[/C][C]-1.45375975579564[/C][C]-0.296713112341198[/C][/ROW]
[ROW][C]52[/C][C]1249[/C][C]1245.81723425674[/C][C]-4.25719587133692[/C][C]3.18276574326016[/C][C]-0.933210584713405[/C][/ROW]
[ROW][C]53[/C][C]1266[/C][C]1262.79930650963[/C][C]1.87261729535962[/C][C]3.20069349036747[/C][C]0.602682430644237[/C][/ROW]
[ROW][C]54[/C][C]1307[/C][C]1318.35975883673[/C][C]17.3627980171068[/C][C]-11.3597588367340[/C][C]1.52433229881749[/C][/ROW]
[ROW][C]55[/C][C]1345[/C][C]1342.06124999012[/C][C]19.1915632081027[/C][C]2.93875000987607[/C][C]0.180024785351115[/C][/ROW]
[ROW][C]56[/C][C]1369[/C][C]1362.00640925850[/C][C]19.4089823732107[/C][C]6.99359074150351[/C][C]0.0214053063621615[/C][/ROW]
[ROW][C]57[/C][C]1374[/C][C]1377.12632270666[/C][C]18.1715075646823[/C][C]-3.12632270665660[/C][C]-0.121838533672427[/C][/ROW]
[ROW][C]58[/C][C]1400[/C][C]1401.41947794047[/C][C]19.9378559517536[/C][C]-1.41947794046984[/C][C]0.17391803019349[/C][/ROW]
[ROW][C]59[/C][C]1425[/C][C]1427.17647305111[/C][C]21.6166500044912[/C][C]-2.17647305110964[/C][C]0.165287869637088[/C][/ROW]
[ROW][C]60[/C][C]1465[/C][C]1464.06304293403[/C][C]26.0145369108756[/C][C]0.936957065966978[/C][C]0.433764151234548[/C][/ROW]
[ROW][C]61[/C][C]1510[/C][C]1501.65740889875[/C][C]29.3501814380784[/C][C]8.34259110124787[/C][C]0.334575383573677[/C][/ROW]
[ROW][C]62[/C][C]1508[/C][C]1510.43968048571[/C][C]23.4642753438675[/C][C]-2.43968048571409[/C][C]-0.56942788806412[/C][/ROW]
[ROW][C]63[/C][C]1512[/C][C]1511.81724594255[/C][C]17.1299224367108[/C][C]0.182754057446914[/C][C]-0.625238911494709[/C][/ROW]
[ROW][C]64[/C][C]1539[/C][C]1536.07232183158[/C][C]19.1835479477738[/C][C]2.92767816842037[/C][C]0.202173286452353[/C][/ROW]
[ROW][C]65[/C][C]1569[/C][C]1569.17657654332[/C][C]23.1964785388394[/C][C]-0.176576543323348[/C][C]0.394579951374799[/C][/ROW]
[ROW][C]66[/C][C]1571[/C][C]1583.99019666247[/C][C]20.7806479673288[/C][C]-12.9901966624666[/C][C]-0.237722109364262[/C][/ROW]
[ROW][C]67[/C][C]1650[/C][C]1644.25004188389[/C][C]32.1574227473424[/C][C]5.74995811610639[/C][C]1.11992954661253[/C][/ROW]
[ROW][C]68[/C][C]1736[/C][C]1725.41934260191[/C][C]46.2814335518937[/C][C]10.5806573980932[/C][C]1.39054652026512[/C][/ROW]
[ROW][C]69[/C][C]1700[/C][C]1709.38080465618[/C][C]28.3215536995056[/C][C]-9.38080465618261[/C][C]-1.76830337762832[/C][/ROW]
[ROW][C]70[/C][C]1731[/C][C]1732.73824915606[/C][C]26.8908706126999[/C][C]-1.73824915605955[/C][C]-0.140867939939903[/C][/ROW]
[ROW][C]71[/C][C]1752[/C][C]1755.68756866500[/C][C]25.7552284609808[/C][C]-3.68756866499811[/C][C]-0.111808362882112[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116525&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116525&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
1961961000
2935936.438293083233-2.27637477957655-1.43829308323263-0.499108215241076
3956956.5209053369051.88090707857587-0.520905336905050.692943432588317
4951952.624393271530.522303979089565-1.62439327153079-0.172794216955631
5986986.3363405204999.23595056033624-0.3363405204988090.974877953007878
6980981.9232316196935.4538208472925-1.92323161969277-0.396897826292056
710311031.0223351320817.8752955290597-0.02233513207790171.26251599520245
810591060.3550211471521.1797372184675-1.355021147153450.330552661263599
910361038.522836210668.69191806663708-2.52283621065761-1.23930631232365
1010231024.536059720452.08557974162984-1.53605972044556-0.653029879979702
1110301030.987106577503.35937377700362-0.9871065775020660.125665013576204
1210751075.2445211722015.3030159167281-0.2445211721978511.17713119431908
1311511123.5254140601124.616035569711827.47458593989251.09031624085282
1412201220.1935428937344.5601500537191-0.1935428937346831.74420887730978
1512901289.1756603602451.6428892861240.8243396397565340.700164244363578
1613301333.0247122971249.3735462597942-3.02471229712164-0.222575238569513
1714191416.3824319009559.25835018119282.617568099051710.97174755754607
1814431447.5011931116451.0761606487051-4.50119311164243-0.80509743647965
1915161515.2079778722755.91144704277120.7920221277286520.475932948220083
2015461547.2784844449948.9798502867707-1.27848444498643-0.682380584106402
2115791580.8005376912744.4854994607685-1.80053769126774-0.442481985966224
2215911593.1115177885335.1303677775772-2.11151778853419-0.92108114172083
2316031604.8639201641128.3320520125587-1.86392016410777-0.669373640446721
2416061607.6046027514120.8967134286134-1.60460275140648-0.732125689047544
2516161610.1408085848115.62476594361425.85919141518533-0.561064670792634
2616281629.0212064012116.5433281641576-1.021206401214510.0850458557114716
2715941595.206891902562.01487705230139-1.20689190256321-1.43764506684695
2815961599.917293625842.79662476399651-3.917293625841160.0767551914209629
2915261526.13634724695-19.3957822855772-0.136347246953412-2.18190432396939
3015351537.31240326809-10.5385872992571-2.312403268092600.871616335450915
3115811576.335152449923.819212115856674.664847550078031.41333220373628
3216111610.7588876892412.68517572179940.2411123107564650.872841590170346
3315711574.92809426307-1.36985704441351-3.92809426307030-1.38378555078528
3415351537.57609053635-11.7945013977784-2.57609053635208-1.02640195154334
3514981499.49920631234-19.4097065379955-1.49920631233638-0.749814275253908
3614931492.37303268138-15.8558119902990.6269673186218190.350092537472794
3714801475.05430200280-16.27707444797914.94569799719625-0.0433772342277661
3814481446.67049618222-19.72053084541651.32950381777925-0.326431159583033
3914621461.85270255144-9.682725860785460.1472974485554040.992772385235179
4014281428.28978373195-16.5890962198329-0.289783731945483-0.678791871948481
4113151322.11398647155-42.4875884672512-7.11398647154654-2.54628934253845
4211861195.57292617751-66.7794317357355-9.57292617750833-2.39054537875425
4312301220.13881620159-40.38167953497279.861183798405542.59859029667091
4412711263.54006076648-16.16952281509107.459939233519472.38370025756123
4512431246.58987670696-16.395128349875-3.58987670695951-0.0222122520143006
4612201221.47681180011-18.91475317103-1.47681180010925-0.248084376934295
4712141215.24296723906-15.2498243490977-1.242967239059040.36084984568892
4812271224.68496850432-8.125744503854792.315031495682480.702234398576933
4912621252.253371816282.158017608796479.746628183715081.04144267450171
5012741275.682340024548.23213147249949-1.682340024544750.583172495751679
5112721273.453759755805.22911195984318-1.45375975579564-0.296713112341198
5212491245.81723425674-4.257195871336923.18276574326016-0.933210584713405
5312661262.799306509631.872617295359623.200693490367470.602682430644237
5413071318.3597588367317.3627980171068-11.35975883673401.52433229881749
5513451342.0612499901219.19156320810272.938750009876070.180024785351115
5613691362.0064092585019.40898237321076.993590741503510.0214053063621615
5713741377.1263227066618.1715075646823-3.12632270665660-0.121838533672427
5814001401.4194779404719.9378559517536-1.419477940469840.17391803019349
5914251427.1764730511121.6166500044912-2.176473051109640.165287869637088
6014651464.0630429340326.01453691087560.9369570659669780.433764151234548
6115101501.6574088987529.35018143807848.342591101247870.334575383573677
6215081510.4396804857123.4642753438675-2.43968048571409-0.56942788806412
6315121511.8172459425517.12992243671080.182754057446914-0.625238911494709
6415391536.0723218315819.18354794777382.927678168420370.202173286452353
6515691569.1765765433223.1964785388394-0.1765765433233480.394579951374799
6615711583.9901966624720.7806479673288-12.9901966624666-0.237722109364262
6716501644.2500418838932.15742274734245.749958116106391.11992954661253
6817361725.4193426019146.281433551893710.58065739809321.39054652026512
6917001709.3808046561828.3215536995056-9.38080465618261-1.76830337762832
7017311732.7382491560626.8908706126999-1.73824915605955-0.140867939939903
7117521755.6875686650025.7552284609808-3.68756866499811-0.111808362882112



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')