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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 computationFri, 10 Dec 2010 00:01:25 +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/10/t1291939247mksg2l3b26eoqnu.htm/, Retrieved Mon, 29 Apr 2024 16:02:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107432, Retrieved Mon, 29 Apr 2024 16:02:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact241
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Structural Time Series Models] [HPC Retail Sales] [2008-03-06 16:52:55] [74be16979710d4c4e7c6647856088456]
- R  D    [Structural Time Series Models] [HPC Retail Sales] [2008-03-08 11:33:35] [74be16979710d4c4e7c6647856088456]
-  M D      [Structural Time Series Models] [WS5] [2010-12-07 13:51:52] [fa854ea294f510d944d2dbf77761bfce]
-             [Structural Time Series Models] [ws5q5] [2010-12-08 19:32:28] [df61ce38492c371f14c407a12b3bb2eb]
-                 [Structural Time Series Models] [Workshop 5 assign...] [2010-12-10 00:01:25] [63a115f47699ab31b1a302b9539c58a2] [Current]
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Dataseries X:
13328
12873
14000
13477
14237
13674
13529
14058
12975
14326
14008
16193
14483
14011
15057
14884
15414
14440
14900
15074
14442
15307
14938
17193
15528
14765
15838
15723
16150
15486
15986
15983
15692
16490
15686
18897
16316
15636
17163
16534
16518
16375
16290
16352
15943
16362
16393
19051
16747
16320
17910
16961
17480
17049
16879
17473
16998
17307
17418
20169
17871
17226
19062
17804
19100
18522
18060
18869
18127
18871
18890
21263
19547
18450
20254
19240
20216
19420
19415
20018
18652
19978
19509
21971




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107432&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107432&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107432&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
11332813328000
21287313200.60963673793.82153253273492-327.609636737904-1.30910990853883
31400013460.252677626221.9988247230845539.7473223738391.31766721298443
41347713535.986921978626.277874817128-58.9869219785510.311902103707869
51423713789.380664371642.1622676227788447.6193356283611.58143733562182
61367413834.07859266142.3048950847059-160.0785926609670.0192400330340184
71352913756.194252922936.7695972831542-227.194252922852-0.93687537822856
81405813824.108149938338.0414014924584233.8918500617210.243932471769008
91297513582.498402565827.0307066217839-607.498402565783-2.18563596938166
101432613729.74698913131.8414502980676596.2530108690010.935635721837499
111400813869.994954267936.3416485498737138.0050457321040.839892802844782
121619314657.751419039468.7552130932521535.248580960585.79778378158836
131448314940.968715151573.377380178188-457.9687151515151.70441403489681
141401114973.305470069872.3109666910293-962.30547006981-0.329020889326419
151505714910.204235849966.7406429671612146.795764150072-1.01366963348165
161488414966.766587788966.2096087984396-82.7665877888551-0.0721892393503844
171541414983.385164048163.3971195434108430.614835951888-0.352185117886043
181444014841.901730363651.7598613125289-401.901730363601-1.49386943826633
191490014877.572516836450.878192210586422.4274831636239-0.11989603799183
201507414855.283067544147.0434594142997218.716932455922-0.550705464864121
211444214996.139014345951.7712115307658-554.1390143458650.707319375157739
221530715086.874503974553.6732623549166220.1254960254660.293174801681171
231493815227.86819776757.8172251877867-289.8681977670310.655220534435506
241719315465.188546523666.11922078117821727.811453476431.34613437870652
251552815699.357543743973.7857505155111-171.3575437439281.2638271906867
261476515768.897498343173.58717256472-1003.89749834307-0.0318833447756195
271583815770.225589140270.023411549570567.7744108598067-0.535995493635427
281572315767.794422100466.2590562552327-44.7944221004366-0.529671473757331
291615015725.550146570460.4288018101536424.449853429631-0.789148680241657
301548615780.155551067860.1118070078565-294.15555106783-0.0425744359084186
311598615877.229190655862.1179397652223108.7708093441510.272498047473189
321598315928.548414462661.539014449832554.4515855374259-0.080045018674125
331569216100.192253544667.3476244206017-408.1922535446310.816983219827962
341649016281.836470198773.282935704625208.1635298013040.846801007906598
351568616325.101779372471.7437757984775-639.101779372384-0.222074109652116
361889716660.862906361385.18381455101682236.137093638731.95349648855418
371631616722.821186274684.001356143972-406.821186274629-0.172023175770423
381563616713.577098998579.2168401989263-1077.57709899848-0.690276606771244
391716316831.775704409681.2428623161003331.2242955903970.28759250194718
401653416796.036142030375.0810464605809-262.036142030262-0.859207161801417
411651816595.763351627160.4295338298941-77.7633516271351-2.01772615679465
421637516599.693555723657.4074952253095-224.693555723638-0.414444665990574
431629016513.574055126349.7271504264102-223.574055126299-1.05580417219991
441635216484.458773923445.5213984997473-132.458773923353-0.581262823896788
451594316491.132290829143.4596829296471-548.132290829068-0.286538996885463
461636216429.665229881137.9215767276276-67.66522988113-0.773355953674206
471639316668.180402153948.4615484439636-275.1804021539161.47741619524434
481905116787.462485491852.1734542063232263.537514508210.521645127149997
491674716927.772204648156.7927429729416-180.7722046480870.649524986414088
501632017113.104187634963.5443813423608-793.1041876349240.947300972692673
511791017270.620848608568.4980147386156639.3791513915480.691871245273978
521696117247.865518912163.6694078159669-286.865518912085-0.670858742767283
531748017325.068199196864.3876898548985154.9318008031660.0993984412830568
541704917312.027943269960.2710376907534-263.027943269908-0.568791384738454
551687917242.323408941353.3581125867458-363.323408941296-0.955697432450974
561747317351.463582285556.3226245407205121.5364177145260.410503251553979
571699817478.672203174560.0841652725418-480.6722031745440.521762647600326
581730717568.384525028261.6536534916854-261.3845250281650.218014324565491
591741817693.239267771664.9966171301543-275.2392677715860.464905000473736
602016917860.159533255270.38299528764092308.840466744830.749746310477573
611787118029.545663498575.6143967610804-158.545663498480.72843192824773
621722618110.440497746875.8935798972956-884.4404977467530.0388555961946465
631906218234.470422182778.4411890649875827.5295778173340.354112665061781
641780418242.099462812774.6892922338283-438.09946281268-0.520666569347948
651910018466.823586569682.6460233575957633.1764134303851.10276756279848
661852218650.023008316287.9815990619847-128.0230083161970.73907938964685
671806018689.526141939585.4088319075327-629.526141939464-0.35643001941373
681886918776.59630809785.496982398194892.40369190296530.0122184598281389
691812718804.521191629582.44351504601-677.521191629486-0.423459023475086
701887118980.913685941787.4236961553463-109.9136859417350.690942602132287
711889019161.226992806692.3453763200119-271.2269928065640.683055885564242
722126319208.340579649989.94954400921222054.65942035008-0.332602323904371
731954719420.026758559496.3971823762235126.9732414406260.895246517153252
741845019505.233763196995.804423108994-1055.23376319688-0.0822976503927405
752025419548.793830308993.0361720161932705.206169691117-0.384204563290023
761924019679.906316471595.0543701994513-439.9063164714720.279966476091825
772021619740.470289187593.2257284919133475.529710812537-0.253563785388247
781942019722.554470476787.3320878930281-302.554470476721-0.81706657661076
791941519854.626327844489.7046991187274-439.6263278443520.32893991248899
802001819957.113472231790.382538836777460.88652776826080.0939909063552975
811865219856.404677492580.2503853612168-1204.40467749255-1.40517489469044
821997819952.881466250581.11061641514625.11853374949520.11931478439592
831950919964.528393073577.428599412836-455.528393073551-0.510745644662623
842197120006.573339485175.55323614420811964.42666051494-0.260161641720041

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 13328 & 13328 & 0 & 0 & 0 \tabularnewline
2 & 12873 & 13200.6096367379 & 3.82153253273492 & -327.609636737904 & -1.30910990853883 \tabularnewline
3 & 14000 & 13460.2526776262 & 21.9988247230845 & 539.747322373839 & 1.31766721298443 \tabularnewline
4 & 13477 & 13535.9869219786 & 26.277874817128 & -58.986921978551 & 0.311902103707869 \tabularnewline
5 & 14237 & 13789.3806643716 & 42.1622676227788 & 447.619335628361 & 1.58143733562182 \tabularnewline
6 & 13674 & 13834.078592661 & 42.3048950847059 & -160.078592660967 & 0.0192400330340184 \tabularnewline
7 & 13529 & 13756.1942529229 & 36.7695972831542 & -227.194252922852 & -0.93687537822856 \tabularnewline
8 & 14058 & 13824.1081499383 & 38.0414014924584 & 233.891850061721 & 0.243932471769008 \tabularnewline
9 & 12975 & 13582.4984025658 & 27.0307066217839 & -607.498402565783 & -2.18563596938166 \tabularnewline
10 & 14326 & 13729.746989131 & 31.8414502980676 & 596.253010869001 & 0.935635721837499 \tabularnewline
11 & 14008 & 13869.9949542679 & 36.3416485498737 & 138.005045732104 & 0.839892802844782 \tabularnewline
12 & 16193 & 14657.7514190394 & 68.755213093252 & 1535.24858096058 & 5.79778378158836 \tabularnewline
13 & 14483 & 14940.9687151515 & 73.377380178188 & -457.968715151515 & 1.70441403489681 \tabularnewline
14 & 14011 & 14973.3054700698 & 72.3109666910293 & -962.30547006981 & -0.329020889326419 \tabularnewline
15 & 15057 & 14910.2042358499 & 66.7406429671612 & 146.795764150072 & -1.01366963348165 \tabularnewline
16 & 14884 & 14966.7665877889 & 66.2096087984396 & -82.7665877888551 & -0.0721892393503844 \tabularnewline
17 & 15414 & 14983.3851640481 & 63.3971195434108 & 430.614835951888 & -0.352185117886043 \tabularnewline
18 & 14440 & 14841.9017303636 & 51.7598613125289 & -401.901730363601 & -1.49386943826633 \tabularnewline
19 & 14900 & 14877.5725168364 & 50.8781922105864 & 22.4274831636239 & -0.11989603799183 \tabularnewline
20 & 15074 & 14855.2830675441 & 47.0434594142997 & 218.716932455922 & -0.550705464864121 \tabularnewline
21 & 14442 & 14996.1390143459 & 51.7712115307658 & -554.139014345865 & 0.707319375157739 \tabularnewline
22 & 15307 & 15086.8745039745 & 53.6732623549166 & 220.125496025466 & 0.293174801681171 \tabularnewline
23 & 14938 & 15227.868197767 & 57.8172251877867 & -289.868197767031 & 0.655220534435506 \tabularnewline
24 & 17193 & 15465.1885465236 & 66.1192207811782 & 1727.81145347643 & 1.34613437870652 \tabularnewline
25 & 15528 & 15699.3575437439 & 73.7857505155111 & -171.357543743928 & 1.2638271906867 \tabularnewline
26 & 14765 & 15768.8974983431 & 73.58717256472 & -1003.89749834307 & -0.0318833447756195 \tabularnewline
27 & 15838 & 15770.2255891402 & 70.0234115495705 & 67.7744108598067 & -0.535995493635427 \tabularnewline
28 & 15723 & 15767.7944221004 & 66.2590562552327 & -44.7944221004366 & -0.529671473757331 \tabularnewline
29 & 16150 & 15725.5501465704 & 60.4288018101536 & 424.449853429631 & -0.789148680241657 \tabularnewline
30 & 15486 & 15780.1555510678 & 60.1118070078565 & -294.15555106783 & -0.0425744359084186 \tabularnewline
31 & 15986 & 15877.2291906558 & 62.1179397652223 & 108.770809344151 & 0.272498047473189 \tabularnewline
32 & 15983 & 15928.5484144626 & 61.5390144498325 & 54.4515855374259 & -0.080045018674125 \tabularnewline
33 & 15692 & 16100.1922535446 & 67.3476244206017 & -408.192253544631 & 0.816983219827962 \tabularnewline
34 & 16490 & 16281.8364701987 & 73.282935704625 & 208.163529801304 & 0.846801007906598 \tabularnewline
35 & 15686 & 16325.1017793724 & 71.7437757984775 & -639.101779372384 & -0.222074109652116 \tabularnewline
36 & 18897 & 16660.8629063613 & 85.1838145510168 & 2236.13709363873 & 1.95349648855418 \tabularnewline
37 & 16316 & 16722.8211862746 & 84.001356143972 & -406.821186274629 & -0.172023175770423 \tabularnewline
38 & 15636 & 16713.5770989985 & 79.2168401989263 & -1077.57709899848 & -0.690276606771244 \tabularnewline
39 & 17163 & 16831.7757044096 & 81.2428623161003 & 331.224295590397 & 0.28759250194718 \tabularnewline
40 & 16534 & 16796.0361420303 & 75.0810464605809 & -262.036142030262 & -0.859207161801417 \tabularnewline
41 & 16518 & 16595.7633516271 & 60.4295338298941 & -77.7633516271351 & -2.01772615679465 \tabularnewline
42 & 16375 & 16599.6935557236 & 57.4074952253095 & -224.693555723638 & -0.414444665990574 \tabularnewline
43 & 16290 & 16513.5740551263 & 49.7271504264102 & -223.574055126299 & -1.05580417219991 \tabularnewline
44 & 16352 & 16484.4587739234 & 45.5213984997473 & -132.458773923353 & -0.581262823896788 \tabularnewline
45 & 15943 & 16491.1322908291 & 43.4596829296471 & -548.132290829068 & -0.286538996885463 \tabularnewline
46 & 16362 & 16429.6652298811 & 37.9215767276276 & -67.66522988113 & -0.773355953674206 \tabularnewline
47 & 16393 & 16668.1804021539 & 48.4615484439636 & -275.180402153916 & 1.47741619524434 \tabularnewline
48 & 19051 & 16787.4624854918 & 52.173454206323 & 2263.53751450821 & 0.521645127149997 \tabularnewline
49 & 16747 & 16927.7722046481 & 56.7927429729416 & -180.772204648087 & 0.649524986414088 \tabularnewline
50 & 16320 & 17113.1041876349 & 63.5443813423608 & -793.104187634924 & 0.947300972692673 \tabularnewline
51 & 17910 & 17270.6208486085 & 68.4980147386156 & 639.379151391548 & 0.691871245273978 \tabularnewline
52 & 16961 & 17247.8655189121 & 63.6694078159669 & -286.865518912085 & -0.670858742767283 \tabularnewline
53 & 17480 & 17325.0681991968 & 64.3876898548985 & 154.931800803166 & 0.0993984412830568 \tabularnewline
54 & 17049 & 17312.0279432699 & 60.2710376907534 & -263.027943269908 & -0.568791384738454 \tabularnewline
55 & 16879 & 17242.3234089413 & 53.3581125867458 & -363.323408941296 & -0.955697432450974 \tabularnewline
56 & 17473 & 17351.4635822855 & 56.3226245407205 & 121.536417714526 & 0.410503251553979 \tabularnewline
57 & 16998 & 17478.6722031745 & 60.0841652725418 & -480.672203174544 & 0.521762647600326 \tabularnewline
58 & 17307 & 17568.3845250282 & 61.6536534916854 & -261.384525028165 & 0.218014324565491 \tabularnewline
59 & 17418 & 17693.2392677716 & 64.9966171301543 & -275.239267771586 & 0.464905000473736 \tabularnewline
60 & 20169 & 17860.1595332552 & 70.3829952876409 & 2308.84046674483 & 0.749746310477573 \tabularnewline
61 & 17871 & 18029.5456634985 & 75.6143967610804 & -158.54566349848 & 0.72843192824773 \tabularnewline
62 & 17226 & 18110.4404977468 & 75.8935798972956 & -884.440497746753 & 0.0388555961946465 \tabularnewline
63 & 19062 & 18234.4704221827 & 78.4411890649875 & 827.529577817334 & 0.354112665061781 \tabularnewline
64 & 17804 & 18242.0994628127 & 74.6892922338283 & -438.09946281268 & -0.520666569347948 \tabularnewline
65 & 19100 & 18466.8235865696 & 82.6460233575957 & 633.176413430385 & 1.10276756279848 \tabularnewline
66 & 18522 & 18650.0230083162 & 87.9815990619847 & -128.023008316197 & 0.73907938964685 \tabularnewline
67 & 18060 & 18689.5261419395 & 85.4088319075327 & -629.526141939464 & -0.35643001941373 \tabularnewline
68 & 18869 & 18776.596308097 & 85.4969823981948 & 92.4036919029653 & 0.0122184598281389 \tabularnewline
69 & 18127 & 18804.5211916295 & 82.44351504601 & -677.521191629486 & -0.423459023475086 \tabularnewline
70 & 18871 & 18980.9136859417 & 87.4236961553463 & -109.913685941735 & 0.690942602132287 \tabularnewline
71 & 18890 & 19161.2269928066 & 92.3453763200119 & -271.226992806564 & 0.683055885564242 \tabularnewline
72 & 21263 & 19208.3405796499 & 89.9495440092122 & 2054.65942035008 & -0.332602323904371 \tabularnewline
73 & 19547 & 19420.0267585594 & 96.3971823762235 & 126.973241440626 & 0.895246517153252 \tabularnewline
74 & 18450 & 19505.2337631969 & 95.804423108994 & -1055.23376319688 & -0.0822976503927405 \tabularnewline
75 & 20254 & 19548.7938303089 & 93.0361720161932 & 705.206169691117 & -0.384204563290023 \tabularnewline
76 & 19240 & 19679.9063164715 & 95.0543701994513 & -439.906316471472 & 0.279966476091825 \tabularnewline
77 & 20216 & 19740.4702891875 & 93.2257284919133 & 475.529710812537 & -0.253563785388247 \tabularnewline
78 & 19420 & 19722.5544704767 & 87.3320878930281 & -302.554470476721 & -0.81706657661076 \tabularnewline
79 & 19415 & 19854.6263278444 & 89.7046991187274 & -439.626327844352 & 0.32893991248899 \tabularnewline
80 & 20018 & 19957.1134722317 & 90.3825388367774 & 60.8865277682608 & 0.0939909063552975 \tabularnewline
81 & 18652 & 19856.4046774925 & 80.2503853612168 & -1204.40467749255 & -1.40517489469044 \tabularnewline
82 & 19978 & 19952.8814662505 & 81.110616415146 & 25.1185337494952 & 0.11931478439592 \tabularnewline
83 & 19509 & 19964.5283930735 & 77.428599412836 & -455.528393073551 & -0.510745644662623 \tabularnewline
84 & 21971 & 20006.5733394851 & 75.5532361442081 & 1964.42666051494 & -0.260161641720041 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107432&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]13328[/C][C]13328[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]12873[/C][C]13200.6096367379[/C][C]3.82153253273492[/C][C]-327.609636737904[/C][C]-1.30910990853883[/C][/ROW]
[ROW][C]3[/C][C]14000[/C][C]13460.2526776262[/C][C]21.9988247230845[/C][C]539.747322373839[/C][C]1.31766721298443[/C][/ROW]
[ROW][C]4[/C][C]13477[/C][C]13535.9869219786[/C][C]26.277874817128[/C][C]-58.986921978551[/C][C]0.311902103707869[/C][/ROW]
[ROW][C]5[/C][C]14237[/C][C]13789.3806643716[/C][C]42.1622676227788[/C][C]447.619335628361[/C][C]1.58143733562182[/C][/ROW]
[ROW][C]6[/C][C]13674[/C][C]13834.078592661[/C][C]42.3048950847059[/C][C]-160.078592660967[/C][C]0.0192400330340184[/C][/ROW]
[ROW][C]7[/C][C]13529[/C][C]13756.1942529229[/C][C]36.7695972831542[/C][C]-227.194252922852[/C][C]-0.93687537822856[/C][/ROW]
[ROW][C]8[/C][C]14058[/C][C]13824.1081499383[/C][C]38.0414014924584[/C][C]233.891850061721[/C][C]0.243932471769008[/C][/ROW]
[ROW][C]9[/C][C]12975[/C][C]13582.4984025658[/C][C]27.0307066217839[/C][C]-607.498402565783[/C][C]-2.18563596938166[/C][/ROW]
[ROW][C]10[/C][C]14326[/C][C]13729.746989131[/C][C]31.8414502980676[/C][C]596.253010869001[/C][C]0.935635721837499[/C][/ROW]
[ROW][C]11[/C][C]14008[/C][C]13869.9949542679[/C][C]36.3416485498737[/C][C]138.005045732104[/C][C]0.839892802844782[/C][/ROW]
[ROW][C]12[/C][C]16193[/C][C]14657.7514190394[/C][C]68.755213093252[/C][C]1535.24858096058[/C][C]5.79778378158836[/C][/ROW]
[ROW][C]13[/C][C]14483[/C][C]14940.9687151515[/C][C]73.377380178188[/C][C]-457.968715151515[/C][C]1.70441403489681[/C][/ROW]
[ROW][C]14[/C][C]14011[/C][C]14973.3054700698[/C][C]72.3109666910293[/C][C]-962.30547006981[/C][C]-0.329020889326419[/C][/ROW]
[ROW][C]15[/C][C]15057[/C][C]14910.2042358499[/C][C]66.7406429671612[/C][C]146.795764150072[/C][C]-1.01366963348165[/C][/ROW]
[ROW][C]16[/C][C]14884[/C][C]14966.7665877889[/C][C]66.2096087984396[/C][C]-82.7665877888551[/C][C]-0.0721892393503844[/C][/ROW]
[ROW][C]17[/C][C]15414[/C][C]14983.3851640481[/C][C]63.3971195434108[/C][C]430.614835951888[/C][C]-0.352185117886043[/C][/ROW]
[ROW][C]18[/C][C]14440[/C][C]14841.9017303636[/C][C]51.7598613125289[/C][C]-401.901730363601[/C][C]-1.49386943826633[/C][/ROW]
[ROW][C]19[/C][C]14900[/C][C]14877.5725168364[/C][C]50.8781922105864[/C][C]22.4274831636239[/C][C]-0.11989603799183[/C][/ROW]
[ROW][C]20[/C][C]15074[/C][C]14855.2830675441[/C][C]47.0434594142997[/C][C]218.716932455922[/C][C]-0.550705464864121[/C][/ROW]
[ROW][C]21[/C][C]14442[/C][C]14996.1390143459[/C][C]51.7712115307658[/C][C]-554.139014345865[/C][C]0.707319375157739[/C][/ROW]
[ROW][C]22[/C][C]15307[/C][C]15086.8745039745[/C][C]53.6732623549166[/C][C]220.125496025466[/C][C]0.293174801681171[/C][/ROW]
[ROW][C]23[/C][C]14938[/C][C]15227.868197767[/C][C]57.8172251877867[/C][C]-289.868197767031[/C][C]0.655220534435506[/C][/ROW]
[ROW][C]24[/C][C]17193[/C][C]15465.1885465236[/C][C]66.1192207811782[/C][C]1727.81145347643[/C][C]1.34613437870652[/C][/ROW]
[ROW][C]25[/C][C]15528[/C][C]15699.3575437439[/C][C]73.7857505155111[/C][C]-171.357543743928[/C][C]1.2638271906867[/C][/ROW]
[ROW][C]26[/C][C]14765[/C][C]15768.8974983431[/C][C]73.58717256472[/C][C]-1003.89749834307[/C][C]-0.0318833447756195[/C][/ROW]
[ROW][C]27[/C][C]15838[/C][C]15770.2255891402[/C][C]70.0234115495705[/C][C]67.7744108598067[/C][C]-0.535995493635427[/C][/ROW]
[ROW][C]28[/C][C]15723[/C][C]15767.7944221004[/C][C]66.2590562552327[/C][C]-44.7944221004366[/C][C]-0.529671473757331[/C][/ROW]
[ROW][C]29[/C][C]16150[/C][C]15725.5501465704[/C][C]60.4288018101536[/C][C]424.449853429631[/C][C]-0.789148680241657[/C][/ROW]
[ROW][C]30[/C][C]15486[/C][C]15780.1555510678[/C][C]60.1118070078565[/C][C]-294.15555106783[/C][C]-0.0425744359084186[/C][/ROW]
[ROW][C]31[/C][C]15986[/C][C]15877.2291906558[/C][C]62.1179397652223[/C][C]108.770809344151[/C][C]0.272498047473189[/C][/ROW]
[ROW][C]32[/C][C]15983[/C][C]15928.5484144626[/C][C]61.5390144498325[/C][C]54.4515855374259[/C][C]-0.080045018674125[/C][/ROW]
[ROW][C]33[/C][C]15692[/C][C]16100.1922535446[/C][C]67.3476244206017[/C][C]-408.192253544631[/C][C]0.816983219827962[/C][/ROW]
[ROW][C]34[/C][C]16490[/C][C]16281.8364701987[/C][C]73.282935704625[/C][C]208.163529801304[/C][C]0.846801007906598[/C][/ROW]
[ROW][C]35[/C][C]15686[/C][C]16325.1017793724[/C][C]71.7437757984775[/C][C]-639.101779372384[/C][C]-0.222074109652116[/C][/ROW]
[ROW][C]36[/C][C]18897[/C][C]16660.8629063613[/C][C]85.1838145510168[/C][C]2236.13709363873[/C][C]1.95349648855418[/C][/ROW]
[ROW][C]37[/C][C]16316[/C][C]16722.8211862746[/C][C]84.001356143972[/C][C]-406.821186274629[/C][C]-0.172023175770423[/C][/ROW]
[ROW][C]38[/C][C]15636[/C][C]16713.5770989985[/C][C]79.2168401989263[/C][C]-1077.57709899848[/C][C]-0.690276606771244[/C][/ROW]
[ROW][C]39[/C][C]17163[/C][C]16831.7757044096[/C][C]81.2428623161003[/C][C]331.224295590397[/C][C]0.28759250194718[/C][/ROW]
[ROW][C]40[/C][C]16534[/C][C]16796.0361420303[/C][C]75.0810464605809[/C][C]-262.036142030262[/C][C]-0.859207161801417[/C][/ROW]
[ROW][C]41[/C][C]16518[/C][C]16595.7633516271[/C][C]60.4295338298941[/C][C]-77.7633516271351[/C][C]-2.01772615679465[/C][/ROW]
[ROW][C]42[/C][C]16375[/C][C]16599.6935557236[/C][C]57.4074952253095[/C][C]-224.693555723638[/C][C]-0.414444665990574[/C][/ROW]
[ROW][C]43[/C][C]16290[/C][C]16513.5740551263[/C][C]49.7271504264102[/C][C]-223.574055126299[/C][C]-1.05580417219991[/C][/ROW]
[ROW][C]44[/C][C]16352[/C][C]16484.4587739234[/C][C]45.5213984997473[/C][C]-132.458773923353[/C][C]-0.581262823896788[/C][/ROW]
[ROW][C]45[/C][C]15943[/C][C]16491.1322908291[/C][C]43.4596829296471[/C][C]-548.132290829068[/C][C]-0.286538996885463[/C][/ROW]
[ROW][C]46[/C][C]16362[/C][C]16429.6652298811[/C][C]37.9215767276276[/C][C]-67.66522988113[/C][C]-0.773355953674206[/C][/ROW]
[ROW][C]47[/C][C]16393[/C][C]16668.1804021539[/C][C]48.4615484439636[/C][C]-275.180402153916[/C][C]1.47741619524434[/C][/ROW]
[ROW][C]48[/C][C]19051[/C][C]16787.4624854918[/C][C]52.173454206323[/C][C]2263.53751450821[/C][C]0.521645127149997[/C][/ROW]
[ROW][C]49[/C][C]16747[/C][C]16927.7722046481[/C][C]56.7927429729416[/C][C]-180.772204648087[/C][C]0.649524986414088[/C][/ROW]
[ROW][C]50[/C][C]16320[/C][C]17113.1041876349[/C][C]63.5443813423608[/C][C]-793.104187634924[/C][C]0.947300972692673[/C][/ROW]
[ROW][C]51[/C][C]17910[/C][C]17270.6208486085[/C][C]68.4980147386156[/C][C]639.379151391548[/C][C]0.691871245273978[/C][/ROW]
[ROW][C]52[/C][C]16961[/C][C]17247.8655189121[/C][C]63.6694078159669[/C][C]-286.865518912085[/C][C]-0.670858742767283[/C][/ROW]
[ROW][C]53[/C][C]17480[/C][C]17325.0681991968[/C][C]64.3876898548985[/C][C]154.931800803166[/C][C]0.0993984412830568[/C][/ROW]
[ROW][C]54[/C][C]17049[/C][C]17312.0279432699[/C][C]60.2710376907534[/C][C]-263.027943269908[/C][C]-0.568791384738454[/C][/ROW]
[ROW][C]55[/C][C]16879[/C][C]17242.3234089413[/C][C]53.3581125867458[/C][C]-363.323408941296[/C][C]-0.955697432450974[/C][/ROW]
[ROW][C]56[/C][C]17473[/C][C]17351.4635822855[/C][C]56.3226245407205[/C][C]121.536417714526[/C][C]0.410503251553979[/C][/ROW]
[ROW][C]57[/C][C]16998[/C][C]17478.6722031745[/C][C]60.0841652725418[/C][C]-480.672203174544[/C][C]0.521762647600326[/C][/ROW]
[ROW][C]58[/C][C]17307[/C][C]17568.3845250282[/C][C]61.6536534916854[/C][C]-261.384525028165[/C][C]0.218014324565491[/C][/ROW]
[ROW][C]59[/C][C]17418[/C][C]17693.2392677716[/C][C]64.9966171301543[/C][C]-275.239267771586[/C][C]0.464905000473736[/C][/ROW]
[ROW][C]60[/C][C]20169[/C][C]17860.1595332552[/C][C]70.3829952876409[/C][C]2308.84046674483[/C][C]0.749746310477573[/C][/ROW]
[ROW][C]61[/C][C]17871[/C][C]18029.5456634985[/C][C]75.6143967610804[/C][C]-158.54566349848[/C][C]0.72843192824773[/C][/ROW]
[ROW][C]62[/C][C]17226[/C][C]18110.4404977468[/C][C]75.8935798972956[/C][C]-884.440497746753[/C][C]0.0388555961946465[/C][/ROW]
[ROW][C]63[/C][C]19062[/C][C]18234.4704221827[/C][C]78.4411890649875[/C][C]827.529577817334[/C][C]0.354112665061781[/C][/ROW]
[ROW][C]64[/C][C]17804[/C][C]18242.0994628127[/C][C]74.6892922338283[/C][C]-438.09946281268[/C][C]-0.520666569347948[/C][/ROW]
[ROW][C]65[/C][C]19100[/C][C]18466.8235865696[/C][C]82.6460233575957[/C][C]633.176413430385[/C][C]1.10276756279848[/C][/ROW]
[ROW][C]66[/C][C]18522[/C][C]18650.0230083162[/C][C]87.9815990619847[/C][C]-128.023008316197[/C][C]0.73907938964685[/C][/ROW]
[ROW][C]67[/C][C]18060[/C][C]18689.5261419395[/C][C]85.4088319075327[/C][C]-629.526141939464[/C][C]-0.35643001941373[/C][/ROW]
[ROW][C]68[/C][C]18869[/C][C]18776.596308097[/C][C]85.4969823981948[/C][C]92.4036919029653[/C][C]0.0122184598281389[/C][/ROW]
[ROW][C]69[/C][C]18127[/C][C]18804.5211916295[/C][C]82.44351504601[/C][C]-677.521191629486[/C][C]-0.423459023475086[/C][/ROW]
[ROW][C]70[/C][C]18871[/C][C]18980.9136859417[/C][C]87.4236961553463[/C][C]-109.913685941735[/C][C]0.690942602132287[/C][/ROW]
[ROW][C]71[/C][C]18890[/C][C]19161.2269928066[/C][C]92.3453763200119[/C][C]-271.226992806564[/C][C]0.683055885564242[/C][/ROW]
[ROW][C]72[/C][C]21263[/C][C]19208.3405796499[/C][C]89.9495440092122[/C][C]2054.65942035008[/C][C]-0.332602323904371[/C][/ROW]
[ROW][C]73[/C][C]19547[/C][C]19420.0267585594[/C][C]96.3971823762235[/C][C]126.973241440626[/C][C]0.895246517153252[/C][/ROW]
[ROW][C]74[/C][C]18450[/C][C]19505.2337631969[/C][C]95.804423108994[/C][C]-1055.23376319688[/C][C]-0.0822976503927405[/C][/ROW]
[ROW][C]75[/C][C]20254[/C][C]19548.7938303089[/C][C]93.0361720161932[/C][C]705.206169691117[/C][C]-0.384204563290023[/C][/ROW]
[ROW][C]76[/C][C]19240[/C][C]19679.9063164715[/C][C]95.0543701994513[/C][C]-439.906316471472[/C][C]0.279966476091825[/C][/ROW]
[ROW][C]77[/C][C]20216[/C][C]19740.4702891875[/C][C]93.2257284919133[/C][C]475.529710812537[/C][C]-0.253563785388247[/C][/ROW]
[ROW][C]78[/C][C]19420[/C][C]19722.5544704767[/C][C]87.3320878930281[/C][C]-302.554470476721[/C][C]-0.81706657661076[/C][/ROW]
[ROW][C]79[/C][C]19415[/C][C]19854.6263278444[/C][C]89.7046991187274[/C][C]-439.626327844352[/C][C]0.32893991248899[/C][/ROW]
[ROW][C]80[/C][C]20018[/C][C]19957.1134722317[/C][C]90.3825388367774[/C][C]60.8865277682608[/C][C]0.0939909063552975[/C][/ROW]
[ROW][C]81[/C][C]18652[/C][C]19856.4046774925[/C][C]80.2503853612168[/C][C]-1204.40467749255[/C][C]-1.40517489469044[/C][/ROW]
[ROW][C]82[/C][C]19978[/C][C]19952.8814662505[/C][C]81.110616415146[/C][C]25.1185337494952[/C][C]0.11931478439592[/C][/ROW]
[ROW][C]83[/C][C]19509[/C][C]19964.5283930735[/C][C]77.428599412836[/C][C]-455.528393073551[/C][C]-0.510745644662623[/C][/ROW]
[ROW][C]84[/C][C]21971[/C][C]20006.5733394851[/C][C]75.5532361442081[/C][C]1964.42666051494[/C][C]-0.260161641720041[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107432&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107432&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
11332813328000
21287313200.60963673793.82153253273492-327.609636737904-1.30910990853883
31400013460.252677626221.9988247230845539.7473223738391.31766721298443
41347713535.986921978626.277874817128-58.9869219785510.311902103707869
51423713789.380664371642.1622676227788447.6193356283611.58143733562182
61367413834.07859266142.3048950847059-160.0785926609670.0192400330340184
71352913756.194252922936.7695972831542-227.194252922852-0.93687537822856
81405813824.108149938338.0414014924584233.8918500617210.243932471769008
91297513582.498402565827.0307066217839-607.498402565783-2.18563596938166
101432613729.74698913131.8414502980676596.2530108690010.935635721837499
111400813869.994954267936.3416485498737138.0050457321040.839892802844782
121619314657.751419039468.7552130932521535.248580960585.79778378158836
131448314940.968715151573.377380178188-457.9687151515151.70441403489681
141401114973.305470069872.3109666910293-962.30547006981-0.329020889326419
151505714910.204235849966.7406429671612146.795764150072-1.01366963348165
161488414966.766587788966.2096087984396-82.7665877888551-0.0721892393503844
171541414983.385164048163.3971195434108430.614835951888-0.352185117886043
181444014841.901730363651.7598613125289-401.901730363601-1.49386943826633
191490014877.572516836450.878192210586422.4274831636239-0.11989603799183
201507414855.283067544147.0434594142997218.716932455922-0.550705464864121
211444214996.139014345951.7712115307658-554.1390143458650.707319375157739
221530715086.874503974553.6732623549166220.1254960254660.293174801681171
231493815227.86819776757.8172251877867-289.8681977670310.655220534435506
241719315465.188546523666.11922078117821727.811453476431.34613437870652
251552815699.357543743973.7857505155111-171.3575437439281.2638271906867
261476515768.897498343173.58717256472-1003.89749834307-0.0318833447756195
271583815770.225589140270.023411549570567.7744108598067-0.535995493635427
281572315767.794422100466.2590562552327-44.7944221004366-0.529671473757331
291615015725.550146570460.4288018101536424.449853429631-0.789148680241657
301548615780.155551067860.1118070078565-294.15555106783-0.0425744359084186
311598615877.229190655862.1179397652223108.7708093441510.272498047473189
321598315928.548414462661.539014449832554.4515855374259-0.080045018674125
331569216100.192253544667.3476244206017-408.1922535446310.816983219827962
341649016281.836470198773.282935704625208.1635298013040.846801007906598
351568616325.101779372471.7437757984775-639.101779372384-0.222074109652116
361889716660.862906361385.18381455101682236.137093638731.95349648855418
371631616722.821186274684.001356143972-406.821186274629-0.172023175770423
381563616713.577098998579.2168401989263-1077.57709899848-0.690276606771244
391716316831.775704409681.2428623161003331.2242955903970.28759250194718
401653416796.036142030375.0810464605809-262.036142030262-0.859207161801417
411651816595.763351627160.4295338298941-77.7633516271351-2.01772615679465
421637516599.693555723657.4074952253095-224.693555723638-0.414444665990574
431629016513.574055126349.7271504264102-223.574055126299-1.05580417219991
441635216484.458773923445.5213984997473-132.458773923353-0.581262823896788
451594316491.132290829143.4596829296471-548.132290829068-0.286538996885463
461636216429.665229881137.9215767276276-67.66522988113-0.773355953674206
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Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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$resid)
myfit <- mylevel+myseas
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time')
grid()
dev.off()
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='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')