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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationMon, 15 Dec 2014 23:48:33 +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/15/t1418687559hk2rz6dpde4pcn7.htm/, Retrieved Thu, 16 May 2024 14:17:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269108, Retrieved Thu, 16 May 2024 14:17:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact44
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [] [2014-12-15 23:48:33] [6993448de96b8662e47595bfdf466bf3] [Current]
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Dataseries X:
4.35
12.7
18.1
17.85


17.1
19.1
16.1
13.35
18.4
14.7
10.6
12.6
16.2
13.6

14.1
14.5
16.15
14.75
14.8
12.45
12.65
17.35
8.6
18.4
16.1

17.75
15.25
17.65
16.35
17.65
13.6
14.35
14.75
18.25
9.9
16
18.25
16.85


18.95
15.6




17.1
16.1









15.4
15.4

13.35
19.1

7.6


19.1













14.75



19.25

13.6

12.75

9.85




15.25
11.9

16.35
12.4

18.15


17.75

12.35
15.6
19.3

17.1

18.4
19.05
18.55
19.1

12.85
9.5
4.5

13.6
11.7

13.35





17.6
14.05
16.1
13.35
11.85
11.95


13.2


7.7

















14.6




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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=269108&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]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=269108&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269108&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
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
14.354.35000
212.79.603007607475630.3953078585329260.4530083624026651.9699560175402
318.114.31227605395860.5938905370594060.6755289165518112.05818821043464
417.8516.19729130126450.6327729166931870.6265800194369480.657069040413001
517.116.64384837356530.628553837352060.608667814471435-0.0966510691992497
619.117.91007486384210.640758031578850.6618094010974030.333332867736157
716.116.90959638340540.6121876442995970.555983479852117-0.860423808228647
813.3514.96700419109210.570063971981590.513180975817392-1.34108009380148
918.416.74052581944260.5892459406824610.65497102098350.632120930503379
1014.715.6254962696480.5627250142639690.49786169148841-0.895467645159292
1110.612.90676629217860.5126330009309760.434826545898213-1.72448784604332
1212.612.69061469747520.5016943153762870.51843857511186-0.383045372588558
1316.216.14352139366990.249326519537353-2.627508697496742.00336571574786
1413.614.65875897635770.1914771064852750.0486960121121538-0.759182952421203
1514.114.29511608254820.179344134514690.229575798631088-0.276297426424353
1614.514.38941036404780.178119716748090.179501010200874-0.0440301919112674
1716.1515.3292792831840.186400036130830.1929321138128780.398868086668025
1814.7514.99550755788560.1815967841425420.185709353106525-0.273416828574458
1914.814.87795525087810.1790660741964470.170608840722667-0.157472694193676
2012.4513.63180627712360.1675547879185340.00359009986281451-0.750704173919925
2112.6513.03742347366980.1615560946005820.246598018793966-0.401450244675734
2217.3515.28891142115140.1777590222921410.3216111810332041.10130281990946
238.611.81196141155430.149734331626192-0.169670895506393-1.92603580784035
2418.415.25180006120120.1727869698991430.4077193178330351.73389793542594
2516.116.49384990241940.130584394301887-1.323492646693630.641332197401909
2617.7517.25462186491560.1437895775111570.04776492016861660.297927456852702
2715.2516.15692248020220.1252801286503590.0615618448828858-0.629462765709783
2817.6516.93315391990180.1316972802032590.1887639185264090.339099285983401
2916.3516.61954548973960.1284011009731130.0960553334538597-0.233840081879059
3017.6517.13868247609790.1308518944075310.1892036724697610.20573292403994
3113.615.26425871257810.119322673244176-0.00853172314088421-1.05690259830729
3214.3514.81665426396980.1162039105181160.00176376345121607-0.298932007345526
3314.7514.76767760341960.1153154431890710.118842766609903-0.0871139973687186
3418.2516.42053384608020.1234904782068940.5585123089807940.810959495857334
359.913.27052631621320.106288208932683-0.664297659357888-1.72668352683977
361614.53100957703840.1110585098394160.5138449266401990.608813445732989
3718.2516.8356294595950.0568830982661435-0.4564197732748081.25738705864114
3816.8516.86788270511020.05651860933521720.000426596430264869-0.012069472118699
3918.9518.01902388483350.06924608720341710.07218847816216730.55973785543135
4015.616.73728457515920.0587331783922025-0.0445401655510719-0.70569767386224
4117.116.9291870007090.05950570690958370.06203861379517560.0700208835589312
4216.116.40937832274810.05667382968987180.165391102184572-0.305267394388992
4315.415.92139771320820.0542372307730764-0.0744675289103527-0.287235999785014
4415.415.69342445802460.0530283041084101-0.0617276080400839-0.148879902773839
4513.3514.51483695581090.0478587962111869-0.153436375377658-0.649836896865958
4619.116.53881985801280.05607847536767990.9382053002740961.0427495144617
477.612.37199976748630.0388996191032377-1.3032834268733-2.22843844560067
4819.115.61771580568170.04718744319456920.8447709598237771.69241308469701
4914.7515.46174507157440.0506968192403752-0.540617899775458-0.113685536578728
5019.2517.55079660283970.07333372803658340.1465236358510141.01993979029569
5113.615.47497226798380.052507789543666-0.185754730666198-1.1044592099979
5212.7514.07866119294280.042910434488521-0.16095449786142-0.757894923111181
539.8511.83909145716270.0317035732384396-0.133478901674062-1.20097262765236
5415.2513.46968850606090.0382703756162480.4766015637397030.842906764030925
5511.912.74772624190720.0354215636751825-0.227161800562937-0.401062452240781
5616.3514.60630838460840.04196432504600920.2548127286367260.962087037719859
5712.413.680067097250.0385536244294881-0.489232103381456-0.510991938513266
5818.1515.35414750252220.04426757637510461.459810666286220.863252833018887
5917.7517.43116967928990.0510627456054857-1.342017682198921.0729636861343
6012.3514.44401089305650.04615219694675920.392012489700753-1.60407842526703
6115.615.28889671448130.0359578093136979-0.3555442634495870.440293690712113
6219.317.26645870036650.05276687455002180.5327133927506330.984758096257615
6317.117.28339860981650.0524666916597953-0.155217225113418-0.0184743806064409
6418.417.87074915993470.05561961788709380.09952757898991010.280040486968155
6519.0518.63461148079680.0587065959658273-0.158160740516010.372806715636518
6618.5518.35117607048110.05746919548773990.476661881773266-0.180420672247451
6719.118.93241372558560.0591902277783429-0.2581745793079690.276375710583149
6812.8515.67170723419160.048747384871492-0.121946349156746-1.75225360588032
699.512.76808378545290.0396184683667323-0.866788730506634-1.55845871578931
704.57.800027397605130.02429225070943470.773355272123855-2.64358359657646
7113.611.23403516486230.0339590496645388-0.4082804313485651.80006636794884
7211.711.39276641186420.0340807226672830.2055553765858330.0658978526920336
7313.3512.62194950448080.0224573588586319-0.2622755879515230.652061791174383
7417.614.9794172759580.03865425706307150.7984996747514941.19535945520504
7514.0514.69203210468480.0362399970123083-0.385412744862462-0.168560845499709
7616.115.42854379704510.04001353635968610.1103192600250780.366827031465323
7713.3514.49081857593940.0361105701292619-0.3514681614552-0.514789135368381
7811.8512.93189070980320.03086804446140110.209246255575001-0.841257834445312
7911.9512.40168520961010.02920121038693920.00293001105630387-0.296105291135893
8013.212.72972740781890.03005021886734340.2280426664311790.15775089120459
817.710.40317732886910.0234651914125755-0.792698466003403-1.24413348878338
8214.612.25544364009320.02849607375947660.8617941664888080.965558685146177

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 4.35 & 4.35 & 0 & 0 & 0 \tabularnewline
2 & 12.7 & 9.60300760747563 & 0.395307858532926 & 0.453008362402665 & 1.9699560175402 \tabularnewline
3 & 18.1 & 14.3122760539586 & 0.593890537059406 & 0.675528916551811 & 2.05818821043464 \tabularnewline
4 & 17.85 & 16.1972913012645 & 0.632772916693187 & 0.626580019436948 & 0.657069040413001 \tabularnewline
5 & 17.1 & 16.6438483735653 & 0.62855383735206 & 0.608667814471435 & -0.0966510691992497 \tabularnewline
6 & 19.1 & 17.9100748638421 & 0.64075803157885 & 0.661809401097403 & 0.333332867736157 \tabularnewline
7 & 16.1 & 16.9095963834054 & 0.612187644299597 & 0.555983479852117 & -0.860423808228647 \tabularnewline
8 & 13.35 & 14.9670041910921 & 0.57006397198159 & 0.513180975817392 & -1.34108009380148 \tabularnewline
9 & 18.4 & 16.7405258194426 & 0.589245940682461 & 0.6549710209835 & 0.632120930503379 \tabularnewline
10 & 14.7 & 15.625496269648 & 0.562725014263969 & 0.49786169148841 & -0.895467645159292 \tabularnewline
11 & 10.6 & 12.9067662921786 & 0.512633000930976 & 0.434826545898213 & -1.72448784604332 \tabularnewline
12 & 12.6 & 12.6906146974752 & 0.501694315376287 & 0.51843857511186 & -0.383045372588558 \tabularnewline
13 & 16.2 & 16.1435213936699 & 0.249326519537353 & -2.62750869749674 & 2.00336571574786 \tabularnewline
14 & 13.6 & 14.6587589763577 & 0.191477106485275 & 0.0486960121121538 & -0.759182952421203 \tabularnewline
15 & 14.1 & 14.2951160825482 & 0.17934413451469 & 0.229575798631088 & -0.276297426424353 \tabularnewline
16 & 14.5 & 14.3894103640478 & 0.17811971674809 & 0.179501010200874 & -0.0440301919112674 \tabularnewline
17 & 16.15 & 15.329279283184 & 0.18640003613083 & 0.192932113812878 & 0.398868086668025 \tabularnewline
18 & 14.75 & 14.9955075578856 & 0.181596784142542 & 0.185709353106525 & -0.273416828574458 \tabularnewline
19 & 14.8 & 14.8779552508781 & 0.179066074196447 & 0.170608840722667 & -0.157472694193676 \tabularnewline
20 & 12.45 & 13.6318062771236 & 0.167554787918534 & 0.00359009986281451 & -0.750704173919925 \tabularnewline
21 & 12.65 & 13.0374234736698 & 0.161556094600582 & 0.246598018793966 & -0.401450244675734 \tabularnewline
22 & 17.35 & 15.2889114211514 & 0.177759022292141 & 0.321611181033204 & 1.10130281990946 \tabularnewline
23 & 8.6 & 11.8119614115543 & 0.149734331626192 & -0.169670895506393 & -1.92603580784035 \tabularnewline
24 & 18.4 & 15.2518000612012 & 0.172786969899143 & 0.407719317833035 & 1.73389793542594 \tabularnewline
25 & 16.1 & 16.4938499024194 & 0.130584394301887 & -1.32349264669363 & 0.641332197401909 \tabularnewline
26 & 17.75 & 17.2546218649156 & 0.143789577511157 & 0.0477649201686166 & 0.297927456852702 \tabularnewline
27 & 15.25 & 16.1569224802022 & 0.125280128650359 & 0.0615618448828858 & -0.629462765709783 \tabularnewline
28 & 17.65 & 16.9331539199018 & 0.131697280203259 & 0.188763918526409 & 0.339099285983401 \tabularnewline
29 & 16.35 & 16.6195454897396 & 0.128401100973113 & 0.0960553334538597 & -0.233840081879059 \tabularnewline
30 & 17.65 & 17.1386824760979 & 0.130851894407531 & 0.189203672469761 & 0.20573292403994 \tabularnewline
31 & 13.6 & 15.2642587125781 & 0.119322673244176 & -0.00853172314088421 & -1.05690259830729 \tabularnewline
32 & 14.35 & 14.8166542639698 & 0.116203910518116 & 0.00176376345121607 & -0.298932007345526 \tabularnewline
33 & 14.75 & 14.7676776034196 & 0.115315443189071 & 0.118842766609903 & -0.0871139973687186 \tabularnewline
34 & 18.25 & 16.4205338460802 & 0.123490478206894 & 0.558512308980794 & 0.810959495857334 \tabularnewline
35 & 9.9 & 13.2705263162132 & 0.106288208932683 & -0.664297659357888 & -1.72668352683977 \tabularnewline
36 & 16 & 14.5310095770384 & 0.111058509839416 & 0.513844926640199 & 0.608813445732989 \tabularnewline
37 & 18.25 & 16.835629459595 & 0.0568830982661435 & -0.456419773274808 & 1.25738705864114 \tabularnewline
38 & 16.85 & 16.8678827051102 & 0.0565186093352172 & 0.000426596430264869 & -0.012069472118699 \tabularnewline
39 & 18.95 & 18.0190238848335 & 0.0692460872034171 & 0.0721884781621673 & 0.55973785543135 \tabularnewline
40 & 15.6 & 16.7372845751592 & 0.0587331783922025 & -0.0445401655510719 & -0.70569767386224 \tabularnewline
41 & 17.1 & 16.929187000709 & 0.0595057069095837 & 0.0620386137951756 & 0.0700208835589312 \tabularnewline
42 & 16.1 & 16.4093783227481 & 0.0566738296898718 & 0.165391102184572 & -0.305267394388992 \tabularnewline
43 & 15.4 & 15.9213977132082 & 0.0542372307730764 & -0.0744675289103527 & -0.287235999785014 \tabularnewline
44 & 15.4 & 15.6934244580246 & 0.0530283041084101 & -0.0617276080400839 & -0.148879902773839 \tabularnewline
45 & 13.35 & 14.5148369558109 & 0.0478587962111869 & -0.153436375377658 & -0.649836896865958 \tabularnewline
46 & 19.1 & 16.5388198580128 & 0.0560784753676799 & 0.938205300274096 & 1.0427495144617 \tabularnewline
47 & 7.6 & 12.3719997674863 & 0.0388996191032377 & -1.3032834268733 & -2.22843844560067 \tabularnewline
48 & 19.1 & 15.6177158056817 & 0.0471874431945692 & 0.844770959823777 & 1.69241308469701 \tabularnewline
49 & 14.75 & 15.4617450715744 & 0.0506968192403752 & -0.540617899775458 & -0.113685536578728 \tabularnewline
50 & 19.25 & 17.5507966028397 & 0.0733337280365834 & 0.146523635851014 & 1.01993979029569 \tabularnewline
51 & 13.6 & 15.4749722679838 & 0.052507789543666 & -0.185754730666198 & -1.1044592099979 \tabularnewline
52 & 12.75 & 14.0786611929428 & 0.042910434488521 & -0.16095449786142 & -0.757894923111181 \tabularnewline
53 & 9.85 & 11.8390914571627 & 0.0317035732384396 & -0.133478901674062 & -1.20097262765236 \tabularnewline
54 & 15.25 & 13.4696885060609 & 0.038270375616248 & 0.476601563739703 & 0.842906764030925 \tabularnewline
55 & 11.9 & 12.7477262419072 & 0.0354215636751825 & -0.227161800562937 & -0.401062452240781 \tabularnewline
56 & 16.35 & 14.6063083846084 & 0.0419643250460092 & 0.254812728636726 & 0.962087037719859 \tabularnewline
57 & 12.4 & 13.68006709725 & 0.0385536244294881 & -0.489232103381456 & -0.510991938513266 \tabularnewline
58 & 18.15 & 15.3541475025222 & 0.0442675763751046 & 1.45981066628622 & 0.863252833018887 \tabularnewline
59 & 17.75 & 17.4311696792899 & 0.0510627456054857 & -1.34201768219892 & 1.0729636861343 \tabularnewline
60 & 12.35 & 14.4440108930565 & 0.0461521969467592 & 0.392012489700753 & -1.60407842526703 \tabularnewline
61 & 15.6 & 15.2888967144813 & 0.0359578093136979 & -0.355544263449587 & 0.440293690712113 \tabularnewline
62 & 19.3 & 17.2664587003665 & 0.0527668745500218 & 0.532713392750633 & 0.984758096257615 \tabularnewline
63 & 17.1 & 17.2833986098165 & 0.0524666916597953 & -0.155217225113418 & -0.0184743806064409 \tabularnewline
64 & 18.4 & 17.8707491599347 & 0.0556196178870938 & 0.0995275789899101 & 0.280040486968155 \tabularnewline
65 & 19.05 & 18.6346114807968 & 0.0587065959658273 & -0.15816074051601 & 0.372806715636518 \tabularnewline
66 & 18.55 & 18.3511760704811 & 0.0574691954877399 & 0.476661881773266 & -0.180420672247451 \tabularnewline
67 & 19.1 & 18.9324137255856 & 0.0591902277783429 & -0.258174579307969 & 0.276375710583149 \tabularnewline
68 & 12.85 & 15.6717072341916 & 0.048747384871492 & -0.121946349156746 & -1.75225360588032 \tabularnewline
69 & 9.5 & 12.7680837854529 & 0.0396184683667323 & -0.866788730506634 & -1.55845871578931 \tabularnewline
70 & 4.5 & 7.80002739760513 & 0.0242922507094347 & 0.773355272123855 & -2.64358359657646 \tabularnewline
71 & 13.6 & 11.2340351648623 & 0.0339590496645388 & -0.408280431348565 & 1.80006636794884 \tabularnewline
72 & 11.7 & 11.3927664118642 & 0.034080722667283 & 0.205555376585833 & 0.0658978526920336 \tabularnewline
73 & 13.35 & 12.6219495044808 & 0.0224573588586319 & -0.262275587951523 & 0.652061791174383 \tabularnewline
74 & 17.6 & 14.979417275958 & 0.0386542570630715 & 0.798499674751494 & 1.19535945520504 \tabularnewline
75 & 14.05 & 14.6920321046848 & 0.0362399970123083 & -0.385412744862462 & -0.168560845499709 \tabularnewline
76 & 16.1 & 15.4285437970451 & 0.0400135363596861 & 0.110319260025078 & 0.366827031465323 \tabularnewline
77 & 13.35 & 14.4908185759394 & 0.0361105701292619 & -0.3514681614552 & -0.514789135368381 \tabularnewline
78 & 11.85 & 12.9318907098032 & 0.0308680444614011 & 0.209246255575001 & -0.841257834445312 \tabularnewline
79 & 11.95 & 12.4016852096101 & 0.0292012103869392 & 0.00293001105630387 & -0.296105291135893 \tabularnewline
80 & 13.2 & 12.7297274078189 & 0.0300502188673434 & 0.228042666431179 & 0.15775089120459 \tabularnewline
81 & 7.7 & 10.4031773288691 & 0.0234651914125755 & -0.792698466003403 & -1.24413348878338 \tabularnewline
82 & 14.6 & 12.2554436400932 & 0.0284960737594766 & 0.861794166488808 & 0.965558685146177 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269108&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]4.35[/C][C]4.35[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]12.7[/C][C]9.60300760747563[/C][C]0.395307858532926[/C][C]0.453008362402665[/C][C]1.9699560175402[/C][/ROW]
[ROW][C]3[/C][C]18.1[/C][C]14.3122760539586[/C][C]0.593890537059406[/C][C]0.675528916551811[/C][C]2.05818821043464[/C][/ROW]
[ROW][C]4[/C][C]17.85[/C][C]16.1972913012645[/C][C]0.632772916693187[/C][C]0.626580019436948[/C][C]0.657069040413001[/C][/ROW]
[ROW][C]5[/C][C]17.1[/C][C]16.6438483735653[/C][C]0.62855383735206[/C][C]0.608667814471435[/C][C]-0.0966510691992497[/C][/ROW]
[ROW][C]6[/C][C]19.1[/C][C]17.9100748638421[/C][C]0.64075803157885[/C][C]0.661809401097403[/C][C]0.333332867736157[/C][/ROW]
[ROW][C]7[/C][C]16.1[/C][C]16.9095963834054[/C][C]0.612187644299597[/C][C]0.555983479852117[/C][C]-0.860423808228647[/C][/ROW]
[ROW][C]8[/C][C]13.35[/C][C]14.9670041910921[/C][C]0.57006397198159[/C][C]0.513180975817392[/C][C]-1.34108009380148[/C][/ROW]
[ROW][C]9[/C][C]18.4[/C][C]16.7405258194426[/C][C]0.589245940682461[/C][C]0.6549710209835[/C][C]0.632120930503379[/C][/ROW]
[ROW][C]10[/C][C]14.7[/C][C]15.625496269648[/C][C]0.562725014263969[/C][C]0.49786169148841[/C][C]-0.895467645159292[/C][/ROW]
[ROW][C]11[/C][C]10.6[/C][C]12.9067662921786[/C][C]0.512633000930976[/C][C]0.434826545898213[/C][C]-1.72448784604332[/C][/ROW]
[ROW][C]12[/C][C]12.6[/C][C]12.6906146974752[/C][C]0.501694315376287[/C][C]0.51843857511186[/C][C]-0.383045372588558[/C][/ROW]
[ROW][C]13[/C][C]16.2[/C][C]16.1435213936699[/C][C]0.249326519537353[/C][C]-2.62750869749674[/C][C]2.00336571574786[/C][/ROW]
[ROW][C]14[/C][C]13.6[/C][C]14.6587589763577[/C][C]0.191477106485275[/C][C]0.0486960121121538[/C][C]-0.759182952421203[/C][/ROW]
[ROW][C]15[/C][C]14.1[/C][C]14.2951160825482[/C][C]0.17934413451469[/C][C]0.229575798631088[/C][C]-0.276297426424353[/C][/ROW]
[ROW][C]16[/C][C]14.5[/C][C]14.3894103640478[/C][C]0.17811971674809[/C][C]0.179501010200874[/C][C]-0.0440301919112674[/C][/ROW]
[ROW][C]17[/C][C]16.15[/C][C]15.329279283184[/C][C]0.18640003613083[/C][C]0.192932113812878[/C][C]0.398868086668025[/C][/ROW]
[ROW][C]18[/C][C]14.75[/C][C]14.9955075578856[/C][C]0.181596784142542[/C][C]0.185709353106525[/C][C]-0.273416828574458[/C][/ROW]
[ROW][C]19[/C][C]14.8[/C][C]14.8779552508781[/C][C]0.179066074196447[/C][C]0.170608840722667[/C][C]-0.157472694193676[/C][/ROW]
[ROW][C]20[/C][C]12.45[/C][C]13.6318062771236[/C][C]0.167554787918534[/C][C]0.00359009986281451[/C][C]-0.750704173919925[/C][/ROW]
[ROW][C]21[/C][C]12.65[/C][C]13.0374234736698[/C][C]0.161556094600582[/C][C]0.246598018793966[/C][C]-0.401450244675734[/C][/ROW]
[ROW][C]22[/C][C]17.35[/C][C]15.2889114211514[/C][C]0.177759022292141[/C][C]0.321611181033204[/C][C]1.10130281990946[/C][/ROW]
[ROW][C]23[/C][C]8.6[/C][C]11.8119614115543[/C][C]0.149734331626192[/C][C]-0.169670895506393[/C][C]-1.92603580784035[/C][/ROW]
[ROW][C]24[/C][C]18.4[/C][C]15.2518000612012[/C][C]0.172786969899143[/C][C]0.407719317833035[/C][C]1.73389793542594[/C][/ROW]
[ROW][C]25[/C][C]16.1[/C][C]16.4938499024194[/C][C]0.130584394301887[/C][C]-1.32349264669363[/C][C]0.641332197401909[/C][/ROW]
[ROW][C]26[/C][C]17.75[/C][C]17.2546218649156[/C][C]0.143789577511157[/C][C]0.0477649201686166[/C][C]0.297927456852702[/C][/ROW]
[ROW][C]27[/C][C]15.25[/C][C]16.1569224802022[/C][C]0.125280128650359[/C][C]0.0615618448828858[/C][C]-0.629462765709783[/C][/ROW]
[ROW][C]28[/C][C]17.65[/C][C]16.9331539199018[/C][C]0.131697280203259[/C][C]0.188763918526409[/C][C]0.339099285983401[/C][/ROW]
[ROW][C]29[/C][C]16.35[/C][C]16.6195454897396[/C][C]0.128401100973113[/C][C]0.0960553334538597[/C][C]-0.233840081879059[/C][/ROW]
[ROW][C]30[/C][C]17.65[/C][C]17.1386824760979[/C][C]0.130851894407531[/C][C]0.189203672469761[/C][C]0.20573292403994[/C][/ROW]
[ROW][C]31[/C][C]13.6[/C][C]15.2642587125781[/C][C]0.119322673244176[/C][C]-0.00853172314088421[/C][C]-1.05690259830729[/C][/ROW]
[ROW][C]32[/C][C]14.35[/C][C]14.8166542639698[/C][C]0.116203910518116[/C][C]0.00176376345121607[/C][C]-0.298932007345526[/C][/ROW]
[ROW][C]33[/C][C]14.75[/C][C]14.7676776034196[/C][C]0.115315443189071[/C][C]0.118842766609903[/C][C]-0.0871139973687186[/C][/ROW]
[ROW][C]34[/C][C]18.25[/C][C]16.4205338460802[/C][C]0.123490478206894[/C][C]0.558512308980794[/C][C]0.810959495857334[/C][/ROW]
[ROW][C]35[/C][C]9.9[/C][C]13.2705263162132[/C][C]0.106288208932683[/C][C]-0.664297659357888[/C][C]-1.72668352683977[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]14.5310095770384[/C][C]0.111058509839416[/C][C]0.513844926640199[/C][C]0.608813445732989[/C][/ROW]
[ROW][C]37[/C][C]18.25[/C][C]16.835629459595[/C][C]0.0568830982661435[/C][C]-0.456419773274808[/C][C]1.25738705864114[/C][/ROW]
[ROW][C]38[/C][C]16.85[/C][C]16.8678827051102[/C][C]0.0565186093352172[/C][C]0.000426596430264869[/C][C]-0.012069472118699[/C][/ROW]
[ROW][C]39[/C][C]18.95[/C][C]18.0190238848335[/C][C]0.0692460872034171[/C][C]0.0721884781621673[/C][C]0.55973785543135[/C][/ROW]
[ROW][C]40[/C][C]15.6[/C][C]16.7372845751592[/C][C]0.0587331783922025[/C][C]-0.0445401655510719[/C][C]-0.70569767386224[/C][/ROW]
[ROW][C]41[/C][C]17.1[/C][C]16.929187000709[/C][C]0.0595057069095837[/C][C]0.0620386137951756[/C][C]0.0700208835589312[/C][/ROW]
[ROW][C]42[/C][C]16.1[/C][C]16.4093783227481[/C][C]0.0566738296898718[/C][C]0.165391102184572[/C][C]-0.305267394388992[/C][/ROW]
[ROW][C]43[/C][C]15.4[/C][C]15.9213977132082[/C][C]0.0542372307730764[/C][C]-0.0744675289103527[/C][C]-0.287235999785014[/C][/ROW]
[ROW][C]44[/C][C]15.4[/C][C]15.6934244580246[/C][C]0.0530283041084101[/C][C]-0.0617276080400839[/C][C]-0.148879902773839[/C][/ROW]
[ROW][C]45[/C][C]13.35[/C][C]14.5148369558109[/C][C]0.0478587962111869[/C][C]-0.153436375377658[/C][C]-0.649836896865958[/C][/ROW]
[ROW][C]46[/C][C]19.1[/C][C]16.5388198580128[/C][C]0.0560784753676799[/C][C]0.938205300274096[/C][C]1.0427495144617[/C][/ROW]
[ROW][C]47[/C][C]7.6[/C][C]12.3719997674863[/C][C]0.0388996191032377[/C][C]-1.3032834268733[/C][C]-2.22843844560067[/C][/ROW]
[ROW][C]48[/C][C]19.1[/C][C]15.6177158056817[/C][C]0.0471874431945692[/C][C]0.844770959823777[/C][C]1.69241308469701[/C][/ROW]
[ROW][C]49[/C][C]14.75[/C][C]15.4617450715744[/C][C]0.0506968192403752[/C][C]-0.540617899775458[/C][C]-0.113685536578728[/C][/ROW]
[ROW][C]50[/C][C]19.25[/C][C]17.5507966028397[/C][C]0.0733337280365834[/C][C]0.146523635851014[/C][C]1.01993979029569[/C][/ROW]
[ROW][C]51[/C][C]13.6[/C][C]15.4749722679838[/C][C]0.052507789543666[/C][C]-0.185754730666198[/C][C]-1.1044592099979[/C][/ROW]
[ROW][C]52[/C][C]12.75[/C][C]14.0786611929428[/C][C]0.042910434488521[/C][C]-0.16095449786142[/C][C]-0.757894923111181[/C][/ROW]
[ROW][C]53[/C][C]9.85[/C][C]11.8390914571627[/C][C]0.0317035732384396[/C][C]-0.133478901674062[/C][C]-1.20097262765236[/C][/ROW]
[ROW][C]54[/C][C]15.25[/C][C]13.4696885060609[/C][C]0.038270375616248[/C][C]0.476601563739703[/C][C]0.842906764030925[/C][/ROW]
[ROW][C]55[/C][C]11.9[/C][C]12.7477262419072[/C][C]0.0354215636751825[/C][C]-0.227161800562937[/C][C]-0.401062452240781[/C][/ROW]
[ROW][C]56[/C][C]16.35[/C][C]14.6063083846084[/C][C]0.0419643250460092[/C][C]0.254812728636726[/C][C]0.962087037719859[/C][/ROW]
[ROW][C]57[/C][C]12.4[/C][C]13.68006709725[/C][C]0.0385536244294881[/C][C]-0.489232103381456[/C][C]-0.510991938513266[/C][/ROW]
[ROW][C]58[/C][C]18.15[/C][C]15.3541475025222[/C][C]0.0442675763751046[/C][C]1.45981066628622[/C][C]0.863252833018887[/C][/ROW]
[ROW][C]59[/C][C]17.75[/C][C]17.4311696792899[/C][C]0.0510627456054857[/C][C]-1.34201768219892[/C][C]1.0729636861343[/C][/ROW]
[ROW][C]60[/C][C]12.35[/C][C]14.4440108930565[/C][C]0.0461521969467592[/C][C]0.392012489700753[/C][C]-1.60407842526703[/C][/ROW]
[ROW][C]61[/C][C]15.6[/C][C]15.2888967144813[/C][C]0.0359578093136979[/C][C]-0.355544263449587[/C][C]0.440293690712113[/C][/ROW]
[ROW][C]62[/C][C]19.3[/C][C]17.2664587003665[/C][C]0.0527668745500218[/C][C]0.532713392750633[/C][C]0.984758096257615[/C][/ROW]
[ROW][C]63[/C][C]17.1[/C][C]17.2833986098165[/C][C]0.0524666916597953[/C][C]-0.155217225113418[/C][C]-0.0184743806064409[/C][/ROW]
[ROW][C]64[/C][C]18.4[/C][C]17.8707491599347[/C][C]0.0556196178870938[/C][C]0.0995275789899101[/C][C]0.280040486968155[/C][/ROW]
[ROW][C]65[/C][C]19.05[/C][C]18.6346114807968[/C][C]0.0587065959658273[/C][C]-0.15816074051601[/C][C]0.372806715636518[/C][/ROW]
[ROW][C]66[/C][C]18.55[/C][C]18.3511760704811[/C][C]0.0574691954877399[/C][C]0.476661881773266[/C][C]-0.180420672247451[/C][/ROW]
[ROW][C]67[/C][C]19.1[/C][C]18.9324137255856[/C][C]0.0591902277783429[/C][C]-0.258174579307969[/C][C]0.276375710583149[/C][/ROW]
[ROW][C]68[/C][C]12.85[/C][C]15.6717072341916[/C][C]0.048747384871492[/C][C]-0.121946349156746[/C][C]-1.75225360588032[/C][/ROW]
[ROW][C]69[/C][C]9.5[/C][C]12.7680837854529[/C][C]0.0396184683667323[/C][C]-0.866788730506634[/C][C]-1.55845871578931[/C][/ROW]
[ROW][C]70[/C][C]4.5[/C][C]7.80002739760513[/C][C]0.0242922507094347[/C][C]0.773355272123855[/C][C]-2.64358359657646[/C][/ROW]
[ROW][C]71[/C][C]13.6[/C][C]11.2340351648623[/C][C]0.0339590496645388[/C][C]-0.408280431348565[/C][C]1.80006636794884[/C][/ROW]
[ROW][C]72[/C][C]11.7[/C][C]11.3927664118642[/C][C]0.034080722667283[/C][C]0.205555376585833[/C][C]0.0658978526920336[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]12.6219495044808[/C][C]0.0224573588586319[/C][C]-0.262275587951523[/C][C]0.652061791174383[/C][/ROW]
[ROW][C]74[/C][C]17.6[/C][C]14.979417275958[/C][C]0.0386542570630715[/C][C]0.798499674751494[/C][C]1.19535945520504[/C][/ROW]
[ROW][C]75[/C][C]14.05[/C][C]14.6920321046848[/C][C]0.0362399970123083[/C][C]-0.385412744862462[/C][C]-0.168560845499709[/C][/ROW]
[ROW][C]76[/C][C]16.1[/C][C]15.4285437970451[/C][C]0.0400135363596861[/C][C]0.110319260025078[/C][C]0.366827031465323[/C][/ROW]
[ROW][C]77[/C][C]13.35[/C][C]14.4908185759394[/C][C]0.0361105701292619[/C][C]-0.3514681614552[/C][C]-0.514789135368381[/C][/ROW]
[ROW][C]78[/C][C]11.85[/C][C]12.9318907098032[/C][C]0.0308680444614011[/C][C]0.209246255575001[/C][C]-0.841257834445312[/C][/ROW]
[ROW][C]79[/C][C]11.95[/C][C]12.4016852096101[/C][C]0.0292012103869392[/C][C]0.00293001105630387[/C][C]-0.296105291135893[/C][/ROW]
[ROW][C]80[/C][C]13.2[/C][C]12.7297274078189[/C][C]0.0300502188673434[/C][C]0.228042666431179[/C][C]0.15775089120459[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]10.4031773288691[/C][C]0.0234651914125755[/C][C]-0.792698466003403[/C][C]-1.24413348878338[/C][/ROW]
[ROW][C]82[/C][C]14.6[/C][C]12.2554436400932[/C][C]0.0284960737594766[/C][C]0.861794166488808[/C][C]0.965558685146177[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269108&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269108&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
14.354.35000
212.79.603007607475630.3953078585329260.4530083624026651.9699560175402
318.114.31227605395860.5938905370594060.6755289165518112.05818821043464
417.8516.19729130126450.6327729166931870.6265800194369480.657069040413001
517.116.64384837356530.628553837352060.608667814471435-0.0966510691992497
619.117.91007486384210.640758031578850.6618094010974030.333332867736157
716.116.90959638340540.6121876442995970.555983479852117-0.860423808228647
813.3514.96700419109210.570063971981590.513180975817392-1.34108009380148
918.416.74052581944260.5892459406824610.65497102098350.632120930503379
1014.715.6254962696480.5627250142639690.49786169148841-0.895467645159292
1110.612.90676629217860.5126330009309760.434826545898213-1.72448784604332
1212.612.69061469747520.5016943153762870.51843857511186-0.383045372588558
1316.216.14352139366990.249326519537353-2.627508697496742.00336571574786
1413.614.65875897635770.1914771064852750.0486960121121538-0.759182952421203
1514.114.29511608254820.179344134514690.229575798631088-0.276297426424353
1614.514.38941036404780.178119716748090.179501010200874-0.0440301919112674
1716.1515.3292792831840.186400036130830.1929321138128780.398868086668025
1814.7514.99550755788560.1815967841425420.185709353106525-0.273416828574458
1914.814.87795525087810.1790660741964470.170608840722667-0.157472694193676
2012.4513.63180627712360.1675547879185340.00359009986281451-0.750704173919925
2112.6513.03742347366980.1615560946005820.246598018793966-0.401450244675734
2217.3515.28891142115140.1777590222921410.3216111810332041.10130281990946
238.611.81196141155430.149734331626192-0.169670895506393-1.92603580784035
2418.415.25180006120120.1727869698991430.4077193178330351.73389793542594
2516.116.49384990241940.130584394301887-1.323492646693630.641332197401909
2617.7517.25462186491560.1437895775111570.04776492016861660.297927456852702
2715.2516.15692248020220.1252801286503590.0615618448828858-0.629462765709783
2817.6516.93315391990180.1316972802032590.1887639185264090.339099285983401
2916.3516.61954548973960.1284011009731130.0960553334538597-0.233840081879059
3017.6517.13868247609790.1308518944075310.1892036724697610.20573292403994
3113.615.26425871257810.119322673244176-0.00853172314088421-1.05690259830729
3214.3514.81665426396980.1162039105181160.00176376345121607-0.298932007345526
3314.7514.76767760341960.1153154431890710.118842766609903-0.0871139973687186
3418.2516.42053384608020.1234904782068940.5585123089807940.810959495857334
359.913.27052631621320.106288208932683-0.664297659357888-1.72668352683977
361614.53100957703840.1110585098394160.5138449266401990.608813445732989
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3816.8516.86788270511020.05651860933521720.000426596430264869-0.012069472118699
3918.9518.01902388483350.06924608720341710.07218847816216730.55973785543135
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477.612.37199976748630.0388996191032377-1.3032834268733-2.22843844560067
4819.115.61771580568170.04718744319456920.8447709598237771.69241308469701
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7211.711.39276641186420.0340807226672830.2055553765858330.0658978526920336
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7514.0514.69203210468480.0362399970123083-0.385412744862462-0.168560845499709
7616.115.42854379704510.04001353635968610.1103192600250780.366827031465323
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7811.8512.93189070980320.03086804446140110.209246255575001-0.841257834445312
7911.9512.40168520961010.02920121038693920.00293001105630387-0.296105291135893
8013.212.72972740781890.03005021886734340.2280426664311790.15775089120459
817.710.40317732886910.0234651914125755-0.792698466003403-1.24413348878338
8214.612.25544364009320.02849607375947660.8617941664888080.965558685146177



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')