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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 computationSat, 13 Dec 2014 11:03:44 +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/2014/Dec/13/t1418468631f3rqnahej0lqd4a.htm/, Retrieved Thu, 16 May 2024 14:41:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266979, Retrieved Thu, 16 May 2024 14:41:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact86
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [] [2014-12-13 11:03:44] [c7f962214140f976f2c4b1bb2571d9df] [Current]
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Dataseries X:
325.87
302.25
294.00
285.43
286.19
276.70
267.77
267.03
257.87
257.19
275.60
305.68
358.06
320.07
295.90
291.27
272.87
269.27
271.32
267.45
260.33
277.94
277.07
312.65
319.71
318.39
304.90
303.73
273.29
274.33
270.45
278.23
274.03
279.00
287.50
336.87
334.10
296.07
286.84
277.63
261.32
264.07
261.94
252.84
257.83
271.16
273.63
304.87
323.90
336.11
335.65
282.23
273.03
270.07
246.03
242.35
250.33
267.45
268.80
302.68
313.10
306.39
305.61
277.27
264.94
268.63
293.90
248.65
256.00
258.52
266.90
281.23
306.00
325.46
291.13
282.53
256.52
258.63
252.74
245.16
255.03
268.35
293.73
278.39




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266979&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 Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266979&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266979&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 Maurice George Kendall' @ kendall.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1325.87325.87000
2302.25303.678790366211-1.20998518872572-1.42879036621099-0.825781926786735
3294295.498193963847-1.26855056894888-1.49819396384663-0.430395483978173
4285.43286.979831463466-1.29602452945201-1.54983146346614-0.447967508090635
5286.19287.269520506702-1.28932710236163-1.079520506701550.0979736602320807
6276.7278.439952205323-1.32183034376678-1.7399522053229-0.465871395196214
7267.77269.392016329061-1.35498743958892-1.62201632906136-0.477351772957635
8267.03268.237678683261-1.35413037398679-1.207678683261130.0123968969790306
9257.87259.633673654315-1.38496536206275-1.76367365431527-0.447920668213041
10257.19258.436756222672-1.384168944301-1.2467562226720.0116181112636709
11275.6275.930937588601-1.30455276701125-0.3309375886008391.1663460285459
12305.68305.584963431764-1.174538633318480.09503656823621911.91267340101303
13358.06331.953781127993-2.3145250582165226.1062188720072.02920779216843
14320.07322.916969333536-2.46545004047705-2.84696933353607-0.358910416691993
15295.9300.275255917234-2.60731533032944-4.37525591723413-1.24088683917018
16291.27294.094432087012-2.614612712712-2.82443208701161-0.220614457172664
17272.87276.272087968859-2.64555195806119-3.40208796885947-0.938675329164297
18269.27271.696074816937-2.64985379031608-2.42607481693705-0.119151861391609
19271.32273.829263724809-2.63908162859017-2.509263724809260.295219141936122
20267.45269.818978596754-2.64215717712659-2.36897859675432-0.0846333847459974
21260.33263.372015368919-2.6506646625637-3.04201536891866-0.234839397751224
22277.94279.111675696513-2.60886940457601-1.171675696513041.1351246971243
23277.07280.115596245387-2.60000962644239-3.045596245387320.223046563767347
24312.65312.243828510498-2.576117372917160.4061714895014992.14176444323344
25319.71295.75681221323-2.3336318489648223.9531877867703-0.927415844930457
26318.39317.29215157198-2.024282156078351.097848428020311.36714095097586
27304.9309.839351954841-2.06023589424186-4.93935195484149-0.332804543726598
28303.73304.944939777184-2.06585074414573-1.21493977718357-0.174949636525183
29273.29278.53875001285-2.10105606771928-5.24875001285026-1.50204438524318
30274.33275.906911240917-2.1019242355892-1.57691124091714-0.032752502926713
31270.45272.325830488451-2.10445428257779-1.87583048845132-0.0912721746980876
32278.23278.408973250807-2.09044018048001-0.178973250806810.505220298778301
33274.03277.869669114981-2.08777299113899-3.839669114980630.0957147265275405
34279279.080793091986-2.08175448905946-0.08079309198605570.203586003279826
35287.5291.405990018444-2.05494129728891-3.905990018443520.889252869781601
36336.87330.810882223231-2.083342019212956.059117776768872.55697368810418
37334.1317.915995897487-1.9768545673020316.1840041025131-0.695714974028655
38296.07296.58985048672-2.14018391947079-0.519850486719773-1.14193467621326
39286.84291.702768367892-2.15701524351733-4.86276836789159-0.168065902862845
40277.63277.77287775641-2.18290086931874-0.142877756410323-0.726624767003552
41261.32267.210149850906-2.19348094004628-5.89014985090559-0.517096324127104
42264.07265.098421090909-2.19337062843607-1.028421090909260.00504413204265151
43261.94264.414523102575-2.19117091634709-2.474523102574690.0931321132679066
44252.84254.109609279762-2.20322336534726-1.26960927976154-0.500605526908693
45257.83260.256454221097-2.19046778266027-2.426454221097050.515209202424614
46271.16270.873457946261-2.169328094445090.2865420537392210.79037602422078
47273.63281.079383375649-2.15189993382372-7.449383375649120.763649056917596
48304.87296.180305570104-2.173780228408048.689694429896051.06462692621008
49323.9303.572484377944-2.2325558699106820.32751562205630.604973638550989
50336.11333.214276627301-2.044139633977742.895723372699511.91058275137113
51335.65339.139227280113-1.99982417271895-3.48922728011320.487149616108964
52282.23288.286348492996-2.1176758568746-6.05634849299644-3.01438351971718
53273.03278.640454147249-2.12705911368596-5.61045414724862-0.46455095287076
54270.07271.25202286554-2.13331994948247-1.18202286554008-0.324617267406846
55246.03249.553252318633-2.1587641557679-3.52325231863261-1.2070886902222
56242.35244.008956866112-2.16338541278505-1.65895686611206-0.208870641152724
57250.33252.15148421664-2.14851462226124-1.821484216639770.635877464469657
58267.45266.174710536919-2.123869724580221.275289463081390.997983244757011
59268.8276.571799185098-2.11103121909949-7.771799185098340.772439003303865
60302.68292.985029745777-2.137876217151219.694970254223461.14366454516099
61313.1297.066706287434-2.1628464766247516.03329371256610.38956923037777
62306.39303.979415378325-2.123085807925222.410584621675090.548822913001875
63305.61303.785389352788-2.113449191579131.824610647211870.117909808024573
64277.27285.1543664206-2.15565738900346-7.88436642060049-1.01879403460234
65264.94271.350197358428-2.17080635093417-6.41019735842772-0.718817623397867
66268.63267.249599625007-2.172938657315771.38040037499318-0.119063914058756
67293.9292.745104700327-2.139903971536561.154895299672921.70695919048772
68248.65256.428916009443-2.18399311048711-7.77891600944283-2.10846641073666
69256258.228962729696-2.17845838174631-2.228962729696410.245818495459727
70258.52258.083325662824-2.175621048841940.436674337176270.125443670411192
71266.9274.232619058698-2.16241952433283-7.332619058698231.13026662295102
72281.23272.636605104842-2.163226648056768.5933948951580.0349794696949078
73306288.713954790405-2.2122035403945317.28604520959531.13600345551768
74325.46319.62213803502-2.09926304425415.837861964980172.01355704470544
75291.13291.802927830196-2.21430215775328-0.672927830195825-1.57259031644767
76282.53288.870715008268-2.21618664428492-6.34071500826836-0.0442617918299502
77256.52265.736565305545-2.24499772946761-9.21656530554479-1.29082056857534
78258.63260.578673285948-2.24811044432264-1.94867328594838-0.179720470267059
79252.74248.55689699167-2.259079997899524.18310300832973-0.602967813199033
80245.16252.109965074574-2.25189546880714-6.949965074574120.358574474710489
81255.03256.4457073148-2.24308322744251-1.415707314799650.406467522495235
82268.35268.080605843763-2.225549035141040.269394156236840.856338944554769
83293.73296.964517903892-2.21025255696025-3.23451790389191.91855765230024
84278.39275.612790306956-2.185307117362982.77720969304429-1.18222646274396

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 325.87 & 325.87 & 0 & 0 & 0 \tabularnewline
2 & 302.25 & 303.678790366211 & -1.20998518872572 & -1.42879036621099 & -0.825781926786735 \tabularnewline
3 & 294 & 295.498193963847 & -1.26855056894888 & -1.49819396384663 & -0.430395483978173 \tabularnewline
4 & 285.43 & 286.979831463466 & -1.29602452945201 & -1.54983146346614 & -0.447967508090635 \tabularnewline
5 & 286.19 & 287.269520506702 & -1.28932710236163 & -1.07952050670155 & 0.0979736602320807 \tabularnewline
6 & 276.7 & 278.439952205323 & -1.32183034376678 & -1.7399522053229 & -0.465871395196214 \tabularnewline
7 & 267.77 & 269.392016329061 & -1.35498743958892 & -1.62201632906136 & -0.477351772957635 \tabularnewline
8 & 267.03 & 268.237678683261 & -1.35413037398679 & -1.20767868326113 & 0.0123968969790306 \tabularnewline
9 & 257.87 & 259.633673654315 & -1.38496536206275 & -1.76367365431527 & -0.447920668213041 \tabularnewline
10 & 257.19 & 258.436756222672 & -1.384168944301 & -1.246756222672 & 0.0116181112636709 \tabularnewline
11 & 275.6 & 275.930937588601 & -1.30455276701125 & -0.330937588600839 & 1.1663460285459 \tabularnewline
12 & 305.68 & 305.584963431764 & -1.17453863331848 & 0.0950365682362191 & 1.91267340101303 \tabularnewline
13 & 358.06 & 331.953781127993 & -2.31452505821652 & 26.106218872007 & 2.02920779216843 \tabularnewline
14 & 320.07 & 322.916969333536 & -2.46545004047705 & -2.84696933353607 & -0.358910416691993 \tabularnewline
15 & 295.9 & 300.275255917234 & -2.60731533032944 & -4.37525591723413 & -1.24088683917018 \tabularnewline
16 & 291.27 & 294.094432087012 & -2.614612712712 & -2.82443208701161 & -0.220614457172664 \tabularnewline
17 & 272.87 & 276.272087968859 & -2.64555195806119 & -3.40208796885947 & -0.938675329164297 \tabularnewline
18 & 269.27 & 271.696074816937 & -2.64985379031608 & -2.42607481693705 & -0.119151861391609 \tabularnewline
19 & 271.32 & 273.829263724809 & -2.63908162859017 & -2.50926372480926 & 0.295219141936122 \tabularnewline
20 & 267.45 & 269.818978596754 & -2.64215717712659 & -2.36897859675432 & -0.0846333847459974 \tabularnewline
21 & 260.33 & 263.372015368919 & -2.6506646625637 & -3.04201536891866 & -0.234839397751224 \tabularnewline
22 & 277.94 & 279.111675696513 & -2.60886940457601 & -1.17167569651304 & 1.1351246971243 \tabularnewline
23 & 277.07 & 280.115596245387 & -2.60000962644239 & -3.04559624538732 & 0.223046563767347 \tabularnewline
24 & 312.65 & 312.243828510498 & -2.57611737291716 & 0.406171489501499 & 2.14176444323344 \tabularnewline
25 & 319.71 & 295.75681221323 & -2.33363184896482 & 23.9531877867703 & -0.927415844930457 \tabularnewline
26 & 318.39 & 317.29215157198 & -2.02428215607835 & 1.09784842802031 & 1.36714095097586 \tabularnewline
27 & 304.9 & 309.839351954841 & -2.06023589424186 & -4.93935195484149 & -0.332804543726598 \tabularnewline
28 & 303.73 & 304.944939777184 & -2.06585074414573 & -1.21493977718357 & -0.174949636525183 \tabularnewline
29 & 273.29 & 278.53875001285 & -2.10105606771928 & -5.24875001285026 & -1.50204438524318 \tabularnewline
30 & 274.33 & 275.906911240917 & -2.1019242355892 & -1.57691124091714 & -0.032752502926713 \tabularnewline
31 & 270.45 & 272.325830488451 & -2.10445428257779 & -1.87583048845132 & -0.0912721746980876 \tabularnewline
32 & 278.23 & 278.408973250807 & -2.09044018048001 & -0.17897325080681 & 0.505220298778301 \tabularnewline
33 & 274.03 & 277.869669114981 & -2.08777299113899 & -3.83966911498063 & 0.0957147265275405 \tabularnewline
34 & 279 & 279.080793091986 & -2.08175448905946 & -0.0807930919860557 & 0.203586003279826 \tabularnewline
35 & 287.5 & 291.405990018444 & -2.05494129728891 & -3.90599001844352 & 0.889252869781601 \tabularnewline
36 & 336.87 & 330.810882223231 & -2.08334201921295 & 6.05911777676887 & 2.55697368810418 \tabularnewline
37 & 334.1 & 317.915995897487 & -1.97685456730203 & 16.1840041025131 & -0.695714974028655 \tabularnewline
38 & 296.07 & 296.58985048672 & -2.14018391947079 & -0.519850486719773 & -1.14193467621326 \tabularnewline
39 & 286.84 & 291.702768367892 & -2.15701524351733 & -4.86276836789159 & -0.168065902862845 \tabularnewline
40 & 277.63 & 277.77287775641 & -2.18290086931874 & -0.142877756410323 & -0.726624767003552 \tabularnewline
41 & 261.32 & 267.210149850906 & -2.19348094004628 & -5.89014985090559 & -0.517096324127104 \tabularnewline
42 & 264.07 & 265.098421090909 & -2.19337062843607 & -1.02842109090926 & 0.00504413204265151 \tabularnewline
43 & 261.94 & 264.414523102575 & -2.19117091634709 & -2.47452310257469 & 0.0931321132679066 \tabularnewline
44 & 252.84 & 254.109609279762 & -2.20322336534726 & -1.26960927976154 & -0.500605526908693 \tabularnewline
45 & 257.83 & 260.256454221097 & -2.19046778266027 & -2.42645422109705 & 0.515209202424614 \tabularnewline
46 & 271.16 & 270.873457946261 & -2.16932809444509 & 0.286542053739221 & 0.79037602422078 \tabularnewline
47 & 273.63 & 281.079383375649 & -2.15189993382372 & -7.44938337564912 & 0.763649056917596 \tabularnewline
48 & 304.87 & 296.180305570104 & -2.17378022840804 & 8.68969442989605 & 1.06462692621008 \tabularnewline
49 & 323.9 & 303.572484377944 & -2.23255586991068 & 20.3275156220563 & 0.604973638550989 \tabularnewline
50 & 336.11 & 333.214276627301 & -2.04413963397774 & 2.89572337269951 & 1.91058275137113 \tabularnewline
51 & 335.65 & 339.139227280113 & -1.99982417271895 & -3.4892272801132 & 0.487149616108964 \tabularnewline
52 & 282.23 & 288.286348492996 & -2.1176758568746 & -6.05634849299644 & -3.01438351971718 \tabularnewline
53 & 273.03 & 278.640454147249 & -2.12705911368596 & -5.61045414724862 & -0.46455095287076 \tabularnewline
54 & 270.07 & 271.25202286554 & -2.13331994948247 & -1.18202286554008 & -0.324617267406846 \tabularnewline
55 & 246.03 & 249.553252318633 & -2.1587641557679 & -3.52325231863261 & -1.2070886902222 \tabularnewline
56 & 242.35 & 244.008956866112 & -2.16338541278505 & -1.65895686611206 & -0.208870641152724 \tabularnewline
57 & 250.33 & 252.15148421664 & -2.14851462226124 & -1.82148421663977 & 0.635877464469657 \tabularnewline
58 & 267.45 & 266.174710536919 & -2.12386972458022 & 1.27528946308139 & 0.997983244757011 \tabularnewline
59 & 268.8 & 276.571799185098 & -2.11103121909949 & -7.77179918509834 & 0.772439003303865 \tabularnewline
60 & 302.68 & 292.985029745777 & -2.13787621715121 & 9.69497025422346 & 1.14366454516099 \tabularnewline
61 & 313.1 & 297.066706287434 & -2.16284647662475 & 16.0332937125661 & 0.38956923037777 \tabularnewline
62 & 306.39 & 303.979415378325 & -2.12308580792522 & 2.41058462167509 & 0.548822913001875 \tabularnewline
63 & 305.61 & 303.785389352788 & -2.11344919157913 & 1.82461064721187 & 0.117909808024573 \tabularnewline
64 & 277.27 & 285.1543664206 & -2.15565738900346 & -7.88436642060049 & -1.01879403460234 \tabularnewline
65 & 264.94 & 271.350197358428 & -2.17080635093417 & -6.41019735842772 & -0.718817623397867 \tabularnewline
66 & 268.63 & 267.249599625007 & -2.17293865731577 & 1.38040037499318 & -0.119063914058756 \tabularnewline
67 & 293.9 & 292.745104700327 & -2.13990397153656 & 1.15489529967292 & 1.70695919048772 \tabularnewline
68 & 248.65 & 256.428916009443 & -2.18399311048711 & -7.77891600944283 & -2.10846641073666 \tabularnewline
69 & 256 & 258.228962729696 & -2.17845838174631 & -2.22896272969641 & 0.245818495459727 \tabularnewline
70 & 258.52 & 258.083325662824 & -2.17562104884194 & 0.43667433717627 & 0.125443670411192 \tabularnewline
71 & 266.9 & 274.232619058698 & -2.16241952433283 & -7.33261905869823 & 1.13026662295102 \tabularnewline
72 & 281.23 & 272.636605104842 & -2.16322664805676 & 8.593394895158 & 0.0349794696949078 \tabularnewline
73 & 306 & 288.713954790405 & -2.21220354039453 & 17.2860452095953 & 1.13600345551768 \tabularnewline
74 & 325.46 & 319.62213803502 & -2.0992630442541 & 5.83786196498017 & 2.01355704470544 \tabularnewline
75 & 291.13 & 291.802927830196 & -2.21430215775328 & -0.672927830195825 & -1.57259031644767 \tabularnewline
76 & 282.53 & 288.870715008268 & -2.21618664428492 & -6.34071500826836 & -0.0442617918299502 \tabularnewline
77 & 256.52 & 265.736565305545 & -2.24499772946761 & -9.21656530554479 & -1.29082056857534 \tabularnewline
78 & 258.63 & 260.578673285948 & -2.24811044432264 & -1.94867328594838 & -0.179720470267059 \tabularnewline
79 & 252.74 & 248.55689699167 & -2.25907999789952 & 4.18310300832973 & -0.602967813199033 \tabularnewline
80 & 245.16 & 252.109965074574 & -2.25189546880714 & -6.94996507457412 & 0.358574474710489 \tabularnewline
81 & 255.03 & 256.4457073148 & -2.24308322744251 & -1.41570731479965 & 0.406467522495235 \tabularnewline
82 & 268.35 & 268.080605843763 & -2.22554903514104 & 0.26939415623684 & 0.856338944554769 \tabularnewline
83 & 293.73 & 296.964517903892 & -2.21025255696025 & -3.2345179038919 & 1.91855765230024 \tabularnewline
84 & 278.39 & 275.612790306956 & -2.18530711736298 & 2.77720969304429 & -1.18222646274396 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266979&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]325.87[/C][C]325.87[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]302.25[/C][C]303.678790366211[/C][C]-1.20998518872572[/C][C]-1.42879036621099[/C][C]-0.825781926786735[/C][/ROW]
[ROW][C]3[/C][C]294[/C][C]295.498193963847[/C][C]-1.26855056894888[/C][C]-1.49819396384663[/C][C]-0.430395483978173[/C][/ROW]
[ROW][C]4[/C][C]285.43[/C][C]286.979831463466[/C][C]-1.29602452945201[/C][C]-1.54983146346614[/C][C]-0.447967508090635[/C][/ROW]
[ROW][C]5[/C][C]286.19[/C][C]287.269520506702[/C][C]-1.28932710236163[/C][C]-1.07952050670155[/C][C]0.0979736602320807[/C][/ROW]
[ROW][C]6[/C][C]276.7[/C][C]278.439952205323[/C][C]-1.32183034376678[/C][C]-1.7399522053229[/C][C]-0.465871395196214[/C][/ROW]
[ROW][C]7[/C][C]267.77[/C][C]269.392016329061[/C][C]-1.35498743958892[/C][C]-1.62201632906136[/C][C]-0.477351772957635[/C][/ROW]
[ROW][C]8[/C][C]267.03[/C][C]268.237678683261[/C][C]-1.35413037398679[/C][C]-1.20767868326113[/C][C]0.0123968969790306[/C][/ROW]
[ROW][C]9[/C][C]257.87[/C][C]259.633673654315[/C][C]-1.38496536206275[/C][C]-1.76367365431527[/C][C]-0.447920668213041[/C][/ROW]
[ROW][C]10[/C][C]257.19[/C][C]258.436756222672[/C][C]-1.384168944301[/C][C]-1.246756222672[/C][C]0.0116181112636709[/C][/ROW]
[ROW][C]11[/C][C]275.6[/C][C]275.930937588601[/C][C]-1.30455276701125[/C][C]-0.330937588600839[/C][C]1.1663460285459[/C][/ROW]
[ROW][C]12[/C][C]305.68[/C][C]305.584963431764[/C][C]-1.17453863331848[/C][C]0.0950365682362191[/C][C]1.91267340101303[/C][/ROW]
[ROW][C]13[/C][C]358.06[/C][C]331.953781127993[/C][C]-2.31452505821652[/C][C]26.106218872007[/C][C]2.02920779216843[/C][/ROW]
[ROW][C]14[/C][C]320.07[/C][C]322.916969333536[/C][C]-2.46545004047705[/C][C]-2.84696933353607[/C][C]-0.358910416691993[/C][/ROW]
[ROW][C]15[/C][C]295.9[/C][C]300.275255917234[/C][C]-2.60731533032944[/C][C]-4.37525591723413[/C][C]-1.24088683917018[/C][/ROW]
[ROW][C]16[/C][C]291.27[/C][C]294.094432087012[/C][C]-2.614612712712[/C][C]-2.82443208701161[/C][C]-0.220614457172664[/C][/ROW]
[ROW][C]17[/C][C]272.87[/C][C]276.272087968859[/C][C]-2.64555195806119[/C][C]-3.40208796885947[/C][C]-0.938675329164297[/C][/ROW]
[ROW][C]18[/C][C]269.27[/C][C]271.696074816937[/C][C]-2.64985379031608[/C][C]-2.42607481693705[/C][C]-0.119151861391609[/C][/ROW]
[ROW][C]19[/C][C]271.32[/C][C]273.829263724809[/C][C]-2.63908162859017[/C][C]-2.50926372480926[/C][C]0.295219141936122[/C][/ROW]
[ROW][C]20[/C][C]267.45[/C][C]269.818978596754[/C][C]-2.64215717712659[/C][C]-2.36897859675432[/C][C]-0.0846333847459974[/C][/ROW]
[ROW][C]21[/C][C]260.33[/C][C]263.372015368919[/C][C]-2.6506646625637[/C][C]-3.04201536891866[/C][C]-0.234839397751224[/C][/ROW]
[ROW][C]22[/C][C]277.94[/C][C]279.111675696513[/C][C]-2.60886940457601[/C][C]-1.17167569651304[/C][C]1.1351246971243[/C][/ROW]
[ROW][C]23[/C][C]277.07[/C][C]280.115596245387[/C][C]-2.60000962644239[/C][C]-3.04559624538732[/C][C]0.223046563767347[/C][/ROW]
[ROW][C]24[/C][C]312.65[/C][C]312.243828510498[/C][C]-2.57611737291716[/C][C]0.406171489501499[/C][C]2.14176444323344[/C][/ROW]
[ROW][C]25[/C][C]319.71[/C][C]295.75681221323[/C][C]-2.33363184896482[/C][C]23.9531877867703[/C][C]-0.927415844930457[/C][/ROW]
[ROW][C]26[/C][C]318.39[/C][C]317.29215157198[/C][C]-2.02428215607835[/C][C]1.09784842802031[/C][C]1.36714095097586[/C][/ROW]
[ROW][C]27[/C][C]304.9[/C][C]309.839351954841[/C][C]-2.06023589424186[/C][C]-4.93935195484149[/C][C]-0.332804543726598[/C][/ROW]
[ROW][C]28[/C][C]303.73[/C][C]304.944939777184[/C][C]-2.06585074414573[/C][C]-1.21493977718357[/C][C]-0.174949636525183[/C][/ROW]
[ROW][C]29[/C][C]273.29[/C][C]278.53875001285[/C][C]-2.10105606771928[/C][C]-5.24875001285026[/C][C]-1.50204438524318[/C][/ROW]
[ROW][C]30[/C][C]274.33[/C][C]275.906911240917[/C][C]-2.1019242355892[/C][C]-1.57691124091714[/C][C]-0.032752502926713[/C][/ROW]
[ROW][C]31[/C][C]270.45[/C][C]272.325830488451[/C][C]-2.10445428257779[/C][C]-1.87583048845132[/C][C]-0.0912721746980876[/C][/ROW]
[ROW][C]32[/C][C]278.23[/C][C]278.408973250807[/C][C]-2.09044018048001[/C][C]-0.17897325080681[/C][C]0.505220298778301[/C][/ROW]
[ROW][C]33[/C][C]274.03[/C][C]277.869669114981[/C][C]-2.08777299113899[/C][C]-3.83966911498063[/C][C]0.0957147265275405[/C][/ROW]
[ROW][C]34[/C][C]279[/C][C]279.080793091986[/C][C]-2.08175448905946[/C][C]-0.0807930919860557[/C][C]0.203586003279826[/C][/ROW]
[ROW][C]35[/C][C]287.5[/C][C]291.405990018444[/C][C]-2.05494129728891[/C][C]-3.90599001844352[/C][C]0.889252869781601[/C][/ROW]
[ROW][C]36[/C][C]336.87[/C][C]330.810882223231[/C][C]-2.08334201921295[/C][C]6.05911777676887[/C][C]2.55697368810418[/C][/ROW]
[ROW][C]37[/C][C]334.1[/C][C]317.915995897487[/C][C]-1.97685456730203[/C][C]16.1840041025131[/C][C]-0.695714974028655[/C][/ROW]
[ROW][C]38[/C][C]296.07[/C][C]296.58985048672[/C][C]-2.14018391947079[/C][C]-0.519850486719773[/C][C]-1.14193467621326[/C][/ROW]
[ROW][C]39[/C][C]286.84[/C][C]291.702768367892[/C][C]-2.15701524351733[/C][C]-4.86276836789159[/C][C]-0.168065902862845[/C][/ROW]
[ROW][C]40[/C][C]277.63[/C][C]277.77287775641[/C][C]-2.18290086931874[/C][C]-0.142877756410323[/C][C]-0.726624767003552[/C][/ROW]
[ROW][C]41[/C][C]261.32[/C][C]267.210149850906[/C][C]-2.19348094004628[/C][C]-5.89014985090559[/C][C]-0.517096324127104[/C][/ROW]
[ROW][C]42[/C][C]264.07[/C][C]265.098421090909[/C][C]-2.19337062843607[/C][C]-1.02842109090926[/C][C]0.00504413204265151[/C][/ROW]
[ROW][C]43[/C][C]261.94[/C][C]264.414523102575[/C][C]-2.19117091634709[/C][C]-2.47452310257469[/C][C]0.0931321132679066[/C][/ROW]
[ROW][C]44[/C][C]252.84[/C][C]254.109609279762[/C][C]-2.20322336534726[/C][C]-1.26960927976154[/C][C]-0.500605526908693[/C][/ROW]
[ROW][C]45[/C][C]257.83[/C][C]260.256454221097[/C][C]-2.19046778266027[/C][C]-2.42645422109705[/C][C]0.515209202424614[/C][/ROW]
[ROW][C]46[/C][C]271.16[/C][C]270.873457946261[/C][C]-2.16932809444509[/C][C]0.286542053739221[/C][C]0.79037602422078[/C][/ROW]
[ROW][C]47[/C][C]273.63[/C][C]281.079383375649[/C][C]-2.15189993382372[/C][C]-7.44938337564912[/C][C]0.763649056917596[/C][/ROW]
[ROW][C]48[/C][C]304.87[/C][C]296.180305570104[/C][C]-2.17378022840804[/C][C]8.68969442989605[/C][C]1.06462692621008[/C][/ROW]
[ROW][C]49[/C][C]323.9[/C][C]303.572484377944[/C][C]-2.23255586991068[/C][C]20.3275156220563[/C][C]0.604973638550989[/C][/ROW]
[ROW][C]50[/C][C]336.11[/C][C]333.214276627301[/C][C]-2.04413963397774[/C][C]2.89572337269951[/C][C]1.91058275137113[/C][/ROW]
[ROW][C]51[/C][C]335.65[/C][C]339.139227280113[/C][C]-1.99982417271895[/C][C]-3.4892272801132[/C][C]0.487149616108964[/C][/ROW]
[ROW][C]52[/C][C]282.23[/C][C]288.286348492996[/C][C]-2.1176758568746[/C][C]-6.05634849299644[/C][C]-3.01438351971718[/C][/ROW]
[ROW][C]53[/C][C]273.03[/C][C]278.640454147249[/C][C]-2.12705911368596[/C][C]-5.61045414724862[/C][C]-0.46455095287076[/C][/ROW]
[ROW][C]54[/C][C]270.07[/C][C]271.25202286554[/C][C]-2.13331994948247[/C][C]-1.18202286554008[/C][C]-0.324617267406846[/C][/ROW]
[ROW][C]55[/C][C]246.03[/C][C]249.553252318633[/C][C]-2.1587641557679[/C][C]-3.52325231863261[/C][C]-1.2070886902222[/C][/ROW]
[ROW][C]56[/C][C]242.35[/C][C]244.008956866112[/C][C]-2.16338541278505[/C][C]-1.65895686611206[/C][C]-0.208870641152724[/C][/ROW]
[ROW][C]57[/C][C]250.33[/C][C]252.15148421664[/C][C]-2.14851462226124[/C][C]-1.82148421663977[/C][C]0.635877464469657[/C][/ROW]
[ROW][C]58[/C][C]267.45[/C][C]266.174710536919[/C][C]-2.12386972458022[/C][C]1.27528946308139[/C][C]0.997983244757011[/C][/ROW]
[ROW][C]59[/C][C]268.8[/C][C]276.571799185098[/C][C]-2.11103121909949[/C][C]-7.77179918509834[/C][C]0.772439003303865[/C][/ROW]
[ROW][C]60[/C][C]302.68[/C][C]292.985029745777[/C][C]-2.13787621715121[/C][C]9.69497025422346[/C][C]1.14366454516099[/C][/ROW]
[ROW][C]61[/C][C]313.1[/C][C]297.066706287434[/C][C]-2.16284647662475[/C][C]16.0332937125661[/C][C]0.38956923037777[/C][/ROW]
[ROW][C]62[/C][C]306.39[/C][C]303.979415378325[/C][C]-2.12308580792522[/C][C]2.41058462167509[/C][C]0.548822913001875[/C][/ROW]
[ROW][C]63[/C][C]305.61[/C][C]303.785389352788[/C][C]-2.11344919157913[/C][C]1.82461064721187[/C][C]0.117909808024573[/C][/ROW]
[ROW][C]64[/C][C]277.27[/C][C]285.1543664206[/C][C]-2.15565738900346[/C][C]-7.88436642060049[/C][C]-1.01879403460234[/C][/ROW]
[ROW][C]65[/C][C]264.94[/C][C]271.350197358428[/C][C]-2.17080635093417[/C][C]-6.41019735842772[/C][C]-0.718817623397867[/C][/ROW]
[ROW][C]66[/C][C]268.63[/C][C]267.249599625007[/C][C]-2.17293865731577[/C][C]1.38040037499318[/C][C]-0.119063914058756[/C][/ROW]
[ROW][C]67[/C][C]293.9[/C][C]292.745104700327[/C][C]-2.13990397153656[/C][C]1.15489529967292[/C][C]1.70695919048772[/C][/ROW]
[ROW][C]68[/C][C]248.65[/C][C]256.428916009443[/C][C]-2.18399311048711[/C][C]-7.77891600944283[/C][C]-2.10846641073666[/C][/ROW]
[ROW][C]69[/C][C]256[/C][C]258.228962729696[/C][C]-2.17845838174631[/C][C]-2.22896272969641[/C][C]0.245818495459727[/C][/ROW]
[ROW][C]70[/C][C]258.52[/C][C]258.083325662824[/C][C]-2.17562104884194[/C][C]0.43667433717627[/C][C]0.125443670411192[/C][/ROW]
[ROW][C]71[/C][C]266.9[/C][C]274.232619058698[/C][C]-2.16241952433283[/C][C]-7.33261905869823[/C][C]1.13026662295102[/C][/ROW]
[ROW][C]72[/C][C]281.23[/C][C]272.636605104842[/C][C]-2.16322664805676[/C][C]8.593394895158[/C][C]0.0349794696949078[/C][/ROW]
[ROW][C]73[/C][C]306[/C][C]288.713954790405[/C][C]-2.21220354039453[/C][C]17.2860452095953[/C][C]1.13600345551768[/C][/ROW]
[ROW][C]74[/C][C]325.46[/C][C]319.62213803502[/C][C]-2.0992630442541[/C][C]5.83786196498017[/C][C]2.01355704470544[/C][/ROW]
[ROW][C]75[/C][C]291.13[/C][C]291.802927830196[/C][C]-2.21430215775328[/C][C]-0.672927830195825[/C][C]-1.57259031644767[/C][/ROW]
[ROW][C]76[/C][C]282.53[/C][C]288.870715008268[/C][C]-2.21618664428492[/C][C]-6.34071500826836[/C][C]-0.0442617918299502[/C][/ROW]
[ROW][C]77[/C][C]256.52[/C][C]265.736565305545[/C][C]-2.24499772946761[/C][C]-9.21656530554479[/C][C]-1.29082056857534[/C][/ROW]
[ROW][C]78[/C][C]258.63[/C][C]260.578673285948[/C][C]-2.24811044432264[/C][C]-1.94867328594838[/C][C]-0.179720470267059[/C][/ROW]
[ROW][C]79[/C][C]252.74[/C][C]248.55689699167[/C][C]-2.25907999789952[/C][C]4.18310300832973[/C][C]-0.602967813199033[/C][/ROW]
[ROW][C]80[/C][C]245.16[/C][C]252.109965074574[/C][C]-2.25189546880714[/C][C]-6.94996507457412[/C][C]0.358574474710489[/C][/ROW]
[ROW][C]81[/C][C]255.03[/C][C]256.4457073148[/C][C]-2.24308322744251[/C][C]-1.41570731479965[/C][C]0.406467522495235[/C][/ROW]
[ROW][C]82[/C][C]268.35[/C][C]268.080605843763[/C][C]-2.22554903514104[/C][C]0.26939415623684[/C][C]0.856338944554769[/C][/ROW]
[ROW][C]83[/C][C]293.73[/C][C]296.964517903892[/C][C]-2.21025255696025[/C][C]-3.2345179038919[/C][C]1.91855765230024[/C][/ROW]
[ROW][C]84[/C][C]278.39[/C][C]275.612790306956[/C][C]-2.18530711736298[/C][C]2.77720969304429[/C][C]-1.18222646274396[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266979&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266979&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
1325.87325.87000
2302.25303.678790366211-1.20998518872572-1.42879036621099-0.825781926786735
3294295.498193963847-1.26855056894888-1.49819396384663-0.430395483978173
4285.43286.979831463466-1.29602452945201-1.54983146346614-0.447967508090635
5286.19287.269520506702-1.28932710236163-1.079520506701550.0979736602320807
6276.7278.439952205323-1.32183034376678-1.7399522053229-0.465871395196214
7267.77269.392016329061-1.35498743958892-1.62201632906136-0.477351772957635
8267.03268.237678683261-1.35413037398679-1.207678683261130.0123968969790306
9257.87259.633673654315-1.38496536206275-1.76367365431527-0.447920668213041
10257.19258.436756222672-1.384168944301-1.2467562226720.0116181112636709
11275.6275.930937588601-1.30455276701125-0.3309375886008391.1663460285459
12305.68305.584963431764-1.174538633318480.09503656823621911.91267340101303
13358.06331.953781127993-2.3145250582165226.1062188720072.02920779216843
14320.07322.916969333536-2.46545004047705-2.84696933353607-0.358910416691993
15295.9300.275255917234-2.60731533032944-4.37525591723413-1.24088683917018
16291.27294.094432087012-2.614612712712-2.82443208701161-0.220614457172664
17272.87276.272087968859-2.64555195806119-3.40208796885947-0.938675329164297
18269.27271.696074816937-2.64985379031608-2.42607481693705-0.119151861391609
19271.32273.829263724809-2.63908162859017-2.509263724809260.295219141936122
20267.45269.818978596754-2.64215717712659-2.36897859675432-0.0846333847459974
21260.33263.372015368919-2.6506646625637-3.04201536891866-0.234839397751224
22277.94279.111675696513-2.60886940457601-1.171675696513041.1351246971243
23277.07280.115596245387-2.60000962644239-3.045596245387320.223046563767347
24312.65312.243828510498-2.576117372917160.4061714895014992.14176444323344
25319.71295.75681221323-2.3336318489648223.9531877867703-0.927415844930457
26318.39317.29215157198-2.024282156078351.097848428020311.36714095097586
27304.9309.839351954841-2.06023589424186-4.93935195484149-0.332804543726598
28303.73304.944939777184-2.06585074414573-1.21493977718357-0.174949636525183
29273.29278.53875001285-2.10105606771928-5.24875001285026-1.50204438524318
30274.33275.906911240917-2.1019242355892-1.57691124091714-0.032752502926713
31270.45272.325830488451-2.10445428257779-1.87583048845132-0.0912721746980876
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40277.63277.77287775641-2.18290086931874-0.142877756410323-0.726624767003552
41261.32267.210149850906-2.19348094004628-5.89014985090559-0.517096324127104
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66268.63267.249599625007-2.172938657315771.38040037499318-0.119063914058756
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68248.65256.428916009443-2.18399311048711-7.77891600944283-2.10846641073666
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75291.13291.802927830196-2.21430215775328-0.672927830195825-1.57259031644767
76282.53288.870715008268-2.21618664428492-6.34071500826836-0.0442617918299502
77256.52265.736565305545-2.24499772946761-9.21656530554479-1.29082056857534
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79252.74248.55689699167-2.259079997899524.18310300832973-0.602967813199033
80245.16252.109965074574-2.25189546880714-6.949965074574120.358574474710489
81255.03256.4457073148-2.24308322744251-1.415707314799650.406467522495235
82268.35268.080605843763-2.225549035141040.269394156236840.856338944554769
83293.73296.964517903892-2.21025255696025-3.23451790389191.91855765230024
84278.39275.612790306956-2.185307117362982.77720969304429-1.18222646274396



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')