Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationTue, 07 Dec 2010 13:08:42 +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/07/t1291727855s9eonrtxrdk9lgp.htm/, Retrieved Fri, 03 May 2024 17:08:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106267, Retrieved Fri, 03 May 2024 17:08:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSTSM
Estimated Impact123
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [Workshop 5] [2010-12-07 13:08:42] [0b94335bf72158573fe52322b9537409] [Current]
-    D    [Structural Time Series Models] [] [2010-12-09 18:45:14] [94f4aa1c01e87d8321fffb341ed4df07]
- R PD    [Structural Time Series Models] [STSM] [2011-12-22 12:07:47] [74be16979710d4c4e7c6647856088456]
Feedback Forum

Post a new message
Dataseries X:
-5
-1
-2
-5
-4
-6
-2
-2
-2
-2
2
1
-8
-1
1
-1
2
2
1
-1
-2
-2
-1
-8
-4
-6
-3
-3
-7
-9
-11
-13
-11
-9
-17
-22
-25
-20
-24
-24
-22
-19
-18
-17
-11
-11
-12
-10
-15
-15
-15
-13
-8
-13
-9
-7
-4
-4
-2
0




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106267&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106267&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106267&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1-5-5000
2-1-1.773829447951980.2112749122478410.200018893091620.976560021429156
3-2-2.024794207357870.1935440280577390.189023105177987-0.208563074895316
4-5-4.260699517888580.1040028363399670.159944881212317-1.12008103594118
5-4-4.159056140429490.1039025816896000.159924997706496-0.00108287981654410
6-6-5.589643593152310.02803981115652750.148940542983979-0.69937221675681
7-2-3.065591867384810.1680956463383690.1651744533570781.1299346823373
8-2-2.360352998963760.2014514892278840.1684044710152370.241672950238531
9-2-2.165889314037780.2009810423017200.168365557468544-0.00312687721026575
10-2-2.114848478060290.19021284447210.167594358917550-0.0667752583694587
1120.8495365767424910.4000486801249270.1807272714555321.23036638014196
1210.9313089978375260.3749478482870450.179345040483997-0.140656662573725
13-8-2.343051191620600.205662843995028-4.41674700122604-1.94395122561858
14-1-1.56415377744710.2593673210861570.417321873167690.211882082227049
1510.09822119727312480.3820105333691480.4296078735022210.608518389285963
16-1-0.9395304548822250.2584539237437430.425059319763131-0.62071273197226
1720.9985303723761150.4061077998262260.4277183986349830.733360809740196
1821.529558563865080.4172184373584950.4278516298935760.0544666643747583
1910.9218810759094320.3251126554739280.426966608008994-0.446370303482624
20-1-0.747506500266830.1443131268509190.425464189907409-0.867887544034985
21-2-1.962884346228710.02018192751518840.424548111850123-0.591226693573065
22-2-2.30233379007671-0.01284025292525330.424329742612866-0.156282871078509
23-1-1.650125360564410.04851347182740150.4246944403748850.288863270443312
24-8-6.69630223354873-0.4232919125186220.422170267236718-2.21196771806144
25-4-2.47243865503734-0.0204072275732784-3.059801517934082.22318682179074
26-6-5.39863393853364-0.2963056220692040.227076767827891-1.14147690679270
27-3-3.85355688547178-0.1238160894563930.2362321888234540.795613255258799
28-3-3.42411593355113-0.0720718908795960.2369822161895620.240055167122520
29-7-6.2909567377552-0.3336084780854700.236008544837477-1.21197707982515
30-9-8.57618686486531-0.5164130665510530.235872289565711-0.846044928229822
31-11-10.6945181435295-0.666594501785750.235880962781929-0.694332626607876
32-13-12.7624135254065-0.7980672801466810.235914638849862-0.607321959013052
33-11-11.8229306027457-0.6349448154296070.2358676445074720.753005199039506
34-9-10.0494679889183-0.4087257822818980.2358052478393671.04368678808174
35-17-15.5244363743995-0.8847915830155580.235925824592226-2.19538214172400
36-22-20.7647120906744-1.294208376986230.236019881567877-1.88732936021310
37-25-22.2796429299010-1.31455686243474-2.64738560112261-0.102254673300952
38-20-21.0382647951490-1.073893764293340.2739941447422191.03195144432382
39-24-23.7262199305482-1.225691598222010.268287663068312-0.6977868616148
40-24-24.4412563749098-1.177649728123840.2687174726392950.221379194225524
41-22-23.1148409333013-0.9420358271250120.2689755469118041.08510043145046
42-19-20.4775029729330-0.605216677195740.2686515191548431.55075695758974
43-18-18.9788586751045-0.4072307810829950.268371659312920.911444137545692
44-17-17.8028295252642-0.2582283445910340.2681588820656540.68590172006441
45-11-12.98255127835890.2197385683217550.2675226345730072.20012799112367
46-11-11.6449152077150.3249544755335040.2673950066937460.484303382594108
47-12-12.02826736610110.2582867513824500.26746819508178-0.306860201057517
48-10-10.64670519457810.3640155187778320.2673633692245240.48664142956986
49-15-11.46096266649680.254134965817154-3.1478320920414-0.537337054801445
50-15-14.3034361992511-0.03669328858493630.253927830966327-1.26926913357884
51-15-15.0225581156584-0.1008738056285140.252028191059991-0.295170460468173
52-13-13.72525669635780.03072322138386180.252912837456880.606034797341179
53-8-9.626945620454320.4136339470974180.2530983862949851.76245497856273
54-13-12.2334991923580.1293161105190660.253417687881719-1.30841836457253
55-9-9.972850706340340.3299568287658380.2531267972834880.923311794412384
56-7-7.856223157281950.4981504104040750.2528862324034450.774002599067476
57-4-5.036554335128460.716692465912620.2525967273964911.00571473779508
58-4-4.269573287355730.7214264981885710.2525910236579850.0217860000541891
59-2-2.579577833775390.8126049073741420.2524916585152990.419608067124001
600-0.6347450099735350.9191897559862140.2523867734691110.490514508071339

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & -5 & -5 & 0 & 0 & 0 \tabularnewline
2 & -1 & -1.77382944795198 & 0.211274912247841 & 0.20001889309162 & 0.976560021429156 \tabularnewline
3 & -2 & -2.02479420735787 & 0.193544028057739 & 0.189023105177987 & -0.208563074895316 \tabularnewline
4 & -5 & -4.26069951788858 & 0.104002836339967 & 0.159944881212317 & -1.12008103594118 \tabularnewline
5 & -4 & -4.15905614042949 & 0.103902581689600 & 0.159924997706496 & -0.00108287981654410 \tabularnewline
6 & -6 & -5.58964359315231 & 0.0280398111565275 & 0.148940542983979 & -0.69937221675681 \tabularnewline
7 & -2 & -3.06559186738481 & 0.168095646338369 & 0.165174453357078 & 1.1299346823373 \tabularnewline
8 & -2 & -2.36035299896376 & 0.201451489227884 & 0.168404471015237 & 0.241672950238531 \tabularnewline
9 & -2 & -2.16588931403778 & 0.200981042301720 & 0.168365557468544 & -0.00312687721026575 \tabularnewline
10 & -2 & -2.11484847806029 & 0.1902128444721 & 0.167594358917550 & -0.0667752583694587 \tabularnewline
11 & 2 & 0.849536576742491 & 0.400048680124927 & 0.180727271455532 & 1.23036638014196 \tabularnewline
12 & 1 & 0.931308997837526 & 0.374947848287045 & 0.179345040483997 & -0.140656662573725 \tabularnewline
13 & -8 & -2.34305119162060 & 0.205662843995028 & -4.41674700122604 & -1.94395122561858 \tabularnewline
14 & -1 & -1.5641537774471 & 0.259367321086157 & 0.41732187316769 & 0.211882082227049 \tabularnewline
15 & 1 & 0.0982211972731248 & 0.382010533369148 & 0.429607873502221 & 0.608518389285963 \tabularnewline
16 & -1 & -0.939530454882225 & 0.258453923743743 & 0.425059319763131 & -0.62071273197226 \tabularnewline
17 & 2 & 0.998530372376115 & 0.406107799826226 & 0.427718398634983 & 0.733360809740196 \tabularnewline
18 & 2 & 1.52955856386508 & 0.417218437358495 & 0.427851629893576 & 0.0544666643747583 \tabularnewline
19 & 1 & 0.921881075909432 & 0.325112655473928 & 0.426966608008994 & -0.446370303482624 \tabularnewline
20 & -1 & -0.74750650026683 & 0.144313126850919 & 0.425464189907409 & -0.867887544034985 \tabularnewline
21 & -2 & -1.96288434622871 & 0.0201819275151884 & 0.424548111850123 & -0.591226693573065 \tabularnewline
22 & -2 & -2.30233379007671 & -0.0128402529252533 & 0.424329742612866 & -0.156282871078509 \tabularnewline
23 & -1 & -1.65012536056441 & 0.0485134718274015 & 0.424694440374885 & 0.288863270443312 \tabularnewline
24 & -8 & -6.69630223354873 & -0.423291912518622 & 0.422170267236718 & -2.21196771806144 \tabularnewline
25 & -4 & -2.47243865503734 & -0.0204072275732784 & -3.05980151793408 & 2.22318682179074 \tabularnewline
26 & -6 & -5.39863393853364 & -0.296305622069204 & 0.227076767827891 & -1.14147690679270 \tabularnewline
27 & -3 & -3.85355688547178 & -0.123816089456393 & 0.236232188823454 & 0.795613255258799 \tabularnewline
28 & -3 & -3.42411593355113 & -0.072071890879596 & 0.236982216189562 & 0.240055167122520 \tabularnewline
29 & -7 & -6.2909567377552 & -0.333608478085470 & 0.236008544837477 & -1.21197707982515 \tabularnewline
30 & -9 & -8.57618686486531 & -0.516413066551053 & 0.235872289565711 & -0.846044928229822 \tabularnewline
31 & -11 & -10.6945181435295 & -0.66659450178575 & 0.235880962781929 & -0.694332626607876 \tabularnewline
32 & -13 & -12.7624135254065 & -0.798067280146681 & 0.235914638849862 & -0.607321959013052 \tabularnewline
33 & -11 & -11.8229306027457 & -0.634944815429607 & 0.235867644507472 & 0.753005199039506 \tabularnewline
34 & -9 & -10.0494679889183 & -0.408725782281898 & 0.235805247839367 & 1.04368678808174 \tabularnewline
35 & -17 & -15.5244363743995 & -0.884791583015558 & 0.235925824592226 & -2.19538214172400 \tabularnewline
36 & -22 & -20.7647120906744 & -1.29420837698623 & 0.236019881567877 & -1.88732936021310 \tabularnewline
37 & -25 & -22.2796429299010 & -1.31455686243474 & -2.64738560112261 & -0.102254673300952 \tabularnewline
38 & -20 & -21.0382647951490 & -1.07389376429334 & 0.273994144742219 & 1.03195144432382 \tabularnewline
39 & -24 & -23.7262199305482 & -1.22569159822201 & 0.268287663068312 & -0.6977868616148 \tabularnewline
40 & -24 & -24.4412563749098 & -1.17764972812384 & 0.268717472639295 & 0.221379194225524 \tabularnewline
41 & -22 & -23.1148409333013 & -0.942035827125012 & 0.268975546911804 & 1.08510043145046 \tabularnewline
42 & -19 & -20.4775029729330 & -0.60521667719574 & 0.268651519154843 & 1.55075695758974 \tabularnewline
43 & -18 & -18.9788586751045 & -0.407230781082995 & 0.26837165931292 & 0.911444137545692 \tabularnewline
44 & -17 & -17.8028295252642 & -0.258228344591034 & 0.268158882065654 & 0.68590172006441 \tabularnewline
45 & -11 & -12.9825512783589 & 0.219738568321755 & 0.267522634573007 & 2.20012799112367 \tabularnewline
46 & -11 & -11.644915207715 & 0.324954475533504 & 0.267395006693746 & 0.484303382594108 \tabularnewline
47 & -12 & -12.0282673661011 & 0.258286751382450 & 0.26746819508178 & -0.306860201057517 \tabularnewline
48 & -10 & -10.6467051945781 & 0.364015518777832 & 0.267363369224524 & 0.48664142956986 \tabularnewline
49 & -15 & -11.4609626664968 & 0.254134965817154 & -3.1478320920414 & -0.537337054801445 \tabularnewline
50 & -15 & -14.3034361992511 & -0.0366932885849363 & 0.253927830966327 & -1.26926913357884 \tabularnewline
51 & -15 & -15.0225581156584 & -0.100873805628514 & 0.252028191059991 & -0.295170460468173 \tabularnewline
52 & -13 & -13.7252566963578 & 0.0307232213838618 & 0.25291283745688 & 0.606034797341179 \tabularnewline
53 & -8 & -9.62694562045432 & 0.413633947097418 & 0.253098386294985 & 1.76245497856273 \tabularnewline
54 & -13 & -12.233499192358 & 0.129316110519066 & 0.253417687881719 & -1.30841836457253 \tabularnewline
55 & -9 & -9.97285070634034 & 0.329956828765838 & 0.253126797283488 & 0.923311794412384 \tabularnewline
56 & -7 & -7.85622315728195 & 0.498150410404075 & 0.252886232403445 & 0.774002599067476 \tabularnewline
57 & -4 & -5.03655433512846 & 0.71669246591262 & 0.252596727396491 & 1.00571473779508 \tabularnewline
58 & -4 & -4.26957328735573 & 0.721426498188571 & 0.252591023657985 & 0.0217860000541891 \tabularnewline
59 & -2 & -2.57957783377539 & 0.812604907374142 & 0.252491658515299 & 0.419608067124001 \tabularnewline
60 & 0 & -0.634745009973535 & 0.919189755986214 & 0.252386773469111 & 0.490514508071339 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106267&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]-5[/C][C]-5[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-1[/C][C]-1.77382944795198[/C][C]0.211274912247841[/C][C]0.20001889309162[/C][C]0.976560021429156[/C][/ROW]
[ROW][C]3[/C][C]-2[/C][C]-2.02479420735787[/C][C]0.193544028057739[/C][C]0.189023105177987[/C][C]-0.208563074895316[/C][/ROW]
[ROW][C]4[/C][C]-5[/C][C]-4.26069951788858[/C][C]0.104002836339967[/C][C]0.159944881212317[/C][C]-1.12008103594118[/C][/ROW]
[ROW][C]5[/C][C]-4[/C][C]-4.15905614042949[/C][C]0.103902581689600[/C][C]0.159924997706496[/C][C]-0.00108287981654410[/C][/ROW]
[ROW][C]6[/C][C]-6[/C][C]-5.58964359315231[/C][C]0.0280398111565275[/C][C]0.148940542983979[/C][C]-0.69937221675681[/C][/ROW]
[ROW][C]7[/C][C]-2[/C][C]-3.06559186738481[/C][C]0.168095646338369[/C][C]0.165174453357078[/C][C]1.1299346823373[/C][/ROW]
[ROW][C]8[/C][C]-2[/C][C]-2.36035299896376[/C][C]0.201451489227884[/C][C]0.168404471015237[/C][C]0.241672950238531[/C][/ROW]
[ROW][C]9[/C][C]-2[/C][C]-2.16588931403778[/C][C]0.200981042301720[/C][C]0.168365557468544[/C][C]-0.00312687721026575[/C][/ROW]
[ROW][C]10[/C][C]-2[/C][C]-2.11484847806029[/C][C]0.1902128444721[/C][C]0.167594358917550[/C][C]-0.0667752583694587[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]0.849536576742491[/C][C]0.400048680124927[/C][C]0.180727271455532[/C][C]1.23036638014196[/C][/ROW]
[ROW][C]12[/C][C]1[/C][C]0.931308997837526[/C][C]0.374947848287045[/C][C]0.179345040483997[/C][C]-0.140656662573725[/C][/ROW]
[ROW][C]13[/C][C]-8[/C][C]-2.34305119162060[/C][C]0.205662843995028[/C][C]-4.41674700122604[/C][C]-1.94395122561858[/C][/ROW]
[ROW][C]14[/C][C]-1[/C][C]-1.5641537774471[/C][C]0.259367321086157[/C][C]0.41732187316769[/C][C]0.211882082227049[/C][/ROW]
[ROW][C]15[/C][C]1[/C][C]0.0982211972731248[/C][C]0.382010533369148[/C][C]0.429607873502221[/C][C]0.608518389285963[/C][/ROW]
[ROW][C]16[/C][C]-1[/C][C]-0.939530454882225[/C][C]0.258453923743743[/C][C]0.425059319763131[/C][C]-0.62071273197226[/C][/ROW]
[ROW][C]17[/C][C]2[/C][C]0.998530372376115[/C][C]0.406107799826226[/C][C]0.427718398634983[/C][C]0.733360809740196[/C][/ROW]
[ROW][C]18[/C][C]2[/C][C]1.52955856386508[/C][C]0.417218437358495[/C][C]0.427851629893576[/C][C]0.0544666643747583[/C][/ROW]
[ROW][C]19[/C][C]1[/C][C]0.921881075909432[/C][C]0.325112655473928[/C][C]0.426966608008994[/C][C]-0.446370303482624[/C][/ROW]
[ROW][C]20[/C][C]-1[/C][C]-0.74750650026683[/C][C]0.144313126850919[/C][C]0.425464189907409[/C][C]-0.867887544034985[/C][/ROW]
[ROW][C]21[/C][C]-2[/C][C]-1.96288434622871[/C][C]0.0201819275151884[/C][C]0.424548111850123[/C][C]-0.591226693573065[/C][/ROW]
[ROW][C]22[/C][C]-2[/C][C]-2.30233379007671[/C][C]-0.0128402529252533[/C][C]0.424329742612866[/C][C]-0.156282871078509[/C][/ROW]
[ROW][C]23[/C][C]-1[/C][C]-1.65012536056441[/C][C]0.0485134718274015[/C][C]0.424694440374885[/C][C]0.288863270443312[/C][/ROW]
[ROW][C]24[/C][C]-8[/C][C]-6.69630223354873[/C][C]-0.423291912518622[/C][C]0.422170267236718[/C][C]-2.21196771806144[/C][/ROW]
[ROW][C]25[/C][C]-4[/C][C]-2.47243865503734[/C][C]-0.0204072275732784[/C][C]-3.05980151793408[/C][C]2.22318682179074[/C][/ROW]
[ROW][C]26[/C][C]-6[/C][C]-5.39863393853364[/C][C]-0.296305622069204[/C][C]0.227076767827891[/C][C]-1.14147690679270[/C][/ROW]
[ROW][C]27[/C][C]-3[/C][C]-3.85355688547178[/C][C]-0.123816089456393[/C][C]0.236232188823454[/C][C]0.795613255258799[/C][/ROW]
[ROW][C]28[/C][C]-3[/C][C]-3.42411593355113[/C][C]-0.072071890879596[/C][C]0.236982216189562[/C][C]0.240055167122520[/C][/ROW]
[ROW][C]29[/C][C]-7[/C][C]-6.2909567377552[/C][C]-0.333608478085470[/C][C]0.236008544837477[/C][C]-1.21197707982515[/C][/ROW]
[ROW][C]30[/C][C]-9[/C][C]-8.57618686486531[/C][C]-0.516413066551053[/C][C]0.235872289565711[/C][C]-0.846044928229822[/C][/ROW]
[ROW][C]31[/C][C]-11[/C][C]-10.6945181435295[/C][C]-0.66659450178575[/C][C]0.235880962781929[/C][C]-0.694332626607876[/C][/ROW]
[ROW][C]32[/C][C]-13[/C][C]-12.7624135254065[/C][C]-0.798067280146681[/C][C]0.235914638849862[/C][C]-0.607321959013052[/C][/ROW]
[ROW][C]33[/C][C]-11[/C][C]-11.8229306027457[/C][C]-0.634944815429607[/C][C]0.235867644507472[/C][C]0.753005199039506[/C][/ROW]
[ROW][C]34[/C][C]-9[/C][C]-10.0494679889183[/C][C]-0.408725782281898[/C][C]0.235805247839367[/C][C]1.04368678808174[/C][/ROW]
[ROW][C]35[/C][C]-17[/C][C]-15.5244363743995[/C][C]-0.884791583015558[/C][C]0.235925824592226[/C][C]-2.19538214172400[/C][/ROW]
[ROW][C]36[/C][C]-22[/C][C]-20.7647120906744[/C][C]-1.29420837698623[/C][C]0.236019881567877[/C][C]-1.88732936021310[/C][/ROW]
[ROW][C]37[/C][C]-25[/C][C]-22.2796429299010[/C][C]-1.31455686243474[/C][C]-2.64738560112261[/C][C]-0.102254673300952[/C][/ROW]
[ROW][C]38[/C][C]-20[/C][C]-21.0382647951490[/C][C]-1.07389376429334[/C][C]0.273994144742219[/C][C]1.03195144432382[/C][/ROW]
[ROW][C]39[/C][C]-24[/C][C]-23.7262199305482[/C][C]-1.22569159822201[/C][C]0.268287663068312[/C][C]-0.6977868616148[/C][/ROW]
[ROW][C]40[/C][C]-24[/C][C]-24.4412563749098[/C][C]-1.17764972812384[/C][C]0.268717472639295[/C][C]0.221379194225524[/C][/ROW]
[ROW][C]41[/C][C]-22[/C][C]-23.1148409333013[/C][C]-0.942035827125012[/C][C]0.268975546911804[/C][C]1.08510043145046[/C][/ROW]
[ROW][C]42[/C][C]-19[/C][C]-20.4775029729330[/C][C]-0.60521667719574[/C][C]0.268651519154843[/C][C]1.55075695758974[/C][/ROW]
[ROW][C]43[/C][C]-18[/C][C]-18.9788586751045[/C][C]-0.407230781082995[/C][C]0.26837165931292[/C][C]0.911444137545692[/C][/ROW]
[ROW][C]44[/C][C]-17[/C][C]-17.8028295252642[/C][C]-0.258228344591034[/C][C]0.268158882065654[/C][C]0.68590172006441[/C][/ROW]
[ROW][C]45[/C][C]-11[/C][C]-12.9825512783589[/C][C]0.219738568321755[/C][C]0.267522634573007[/C][C]2.20012799112367[/C][/ROW]
[ROW][C]46[/C][C]-11[/C][C]-11.644915207715[/C][C]0.324954475533504[/C][C]0.267395006693746[/C][C]0.484303382594108[/C][/ROW]
[ROW][C]47[/C][C]-12[/C][C]-12.0282673661011[/C][C]0.258286751382450[/C][C]0.26746819508178[/C][C]-0.306860201057517[/C][/ROW]
[ROW][C]48[/C][C]-10[/C][C]-10.6467051945781[/C][C]0.364015518777832[/C][C]0.267363369224524[/C][C]0.48664142956986[/C][/ROW]
[ROW][C]49[/C][C]-15[/C][C]-11.4609626664968[/C][C]0.254134965817154[/C][C]-3.1478320920414[/C][C]-0.537337054801445[/C][/ROW]
[ROW][C]50[/C][C]-15[/C][C]-14.3034361992511[/C][C]-0.0366932885849363[/C][C]0.253927830966327[/C][C]-1.26926913357884[/C][/ROW]
[ROW][C]51[/C][C]-15[/C][C]-15.0225581156584[/C][C]-0.100873805628514[/C][C]0.252028191059991[/C][C]-0.295170460468173[/C][/ROW]
[ROW][C]52[/C][C]-13[/C][C]-13.7252566963578[/C][C]0.0307232213838618[/C][C]0.25291283745688[/C][C]0.606034797341179[/C][/ROW]
[ROW][C]53[/C][C]-8[/C][C]-9.62694562045432[/C][C]0.413633947097418[/C][C]0.253098386294985[/C][C]1.76245497856273[/C][/ROW]
[ROW][C]54[/C][C]-13[/C][C]-12.233499192358[/C][C]0.129316110519066[/C][C]0.253417687881719[/C][C]-1.30841836457253[/C][/ROW]
[ROW][C]55[/C][C]-9[/C][C]-9.97285070634034[/C][C]0.329956828765838[/C][C]0.253126797283488[/C][C]0.923311794412384[/C][/ROW]
[ROW][C]56[/C][C]-7[/C][C]-7.85622315728195[/C][C]0.498150410404075[/C][C]0.252886232403445[/C][C]0.774002599067476[/C][/ROW]
[ROW][C]57[/C][C]-4[/C][C]-5.03655433512846[/C][C]0.71669246591262[/C][C]0.252596727396491[/C][C]1.00571473779508[/C][/ROW]
[ROW][C]58[/C][C]-4[/C][C]-4.26957328735573[/C][C]0.721426498188571[/C][C]0.252591023657985[/C][C]0.0217860000541891[/C][/ROW]
[ROW][C]59[/C][C]-2[/C][C]-2.57957783377539[/C][C]0.812604907374142[/C][C]0.252491658515299[/C][C]0.419608067124001[/C][/ROW]
[ROW][C]60[/C][C]0[/C][C]-0.634745009973535[/C][C]0.919189755986214[/C][C]0.252386773469111[/C][C]0.490514508071339[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106267&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106267&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
1-5-5000
2-1-1.773829447951980.2112749122478410.200018893091620.976560021429156
3-2-2.024794207357870.1935440280577390.189023105177987-0.208563074895316
4-5-4.260699517888580.1040028363399670.159944881212317-1.12008103594118
5-4-4.159056140429490.1039025816896000.159924997706496-0.00108287981654410
6-6-5.589643593152310.02803981115652750.148940542983979-0.69937221675681
7-2-3.065591867384810.1680956463383690.1651744533570781.1299346823373
8-2-2.360352998963760.2014514892278840.1684044710152370.241672950238531
9-2-2.165889314037780.2009810423017200.168365557468544-0.00312687721026575
10-2-2.114848478060290.19021284447210.167594358917550-0.0667752583694587
1120.8495365767424910.4000486801249270.1807272714555321.23036638014196
1210.9313089978375260.3749478482870450.179345040483997-0.140656662573725
13-8-2.343051191620600.205662843995028-4.41674700122604-1.94395122561858
14-1-1.56415377744710.2593673210861570.417321873167690.211882082227049
1510.09822119727312480.3820105333691480.4296078735022210.608518389285963
16-1-0.9395304548822250.2584539237437430.425059319763131-0.62071273197226
1720.9985303723761150.4061077998262260.4277183986349830.733360809740196
1821.529558563865080.4172184373584950.4278516298935760.0544666643747583
1910.9218810759094320.3251126554739280.426966608008994-0.446370303482624
20-1-0.747506500266830.1443131268509190.425464189907409-0.867887544034985
21-2-1.962884346228710.02018192751518840.424548111850123-0.591226693573065
22-2-2.30233379007671-0.01284025292525330.424329742612866-0.156282871078509
23-1-1.650125360564410.04851347182740150.4246944403748850.288863270443312
24-8-6.69630223354873-0.4232919125186220.422170267236718-2.21196771806144
25-4-2.47243865503734-0.0204072275732784-3.059801517934082.22318682179074
26-6-5.39863393853364-0.2963056220692040.227076767827891-1.14147690679270
27-3-3.85355688547178-0.1238160894563930.2362321888234540.795613255258799
28-3-3.42411593355113-0.0720718908795960.2369822161895620.240055167122520
29-7-6.2909567377552-0.3336084780854700.236008544837477-1.21197707982515
30-9-8.57618686486531-0.5164130665510530.235872289565711-0.846044928229822
31-11-10.6945181435295-0.666594501785750.235880962781929-0.694332626607876
32-13-12.7624135254065-0.7980672801466810.235914638849862-0.607321959013052
33-11-11.8229306027457-0.6349448154296070.2358676445074720.753005199039506
34-9-10.0494679889183-0.4087257822818980.2358052478393671.04368678808174
35-17-15.5244363743995-0.8847915830155580.235925824592226-2.19538214172400
36-22-20.7647120906744-1.294208376986230.236019881567877-1.88732936021310
37-25-22.2796429299010-1.31455686243474-2.64738560112261-0.102254673300952
38-20-21.0382647951490-1.073893764293340.2739941447422191.03195144432382
39-24-23.7262199305482-1.225691598222010.268287663068312-0.6977868616148
40-24-24.4412563749098-1.177649728123840.2687174726392950.221379194225524
41-22-23.1148409333013-0.9420358271250120.2689755469118041.08510043145046
42-19-20.4775029729330-0.605216677195740.2686515191548431.55075695758974
43-18-18.9788586751045-0.4072307810829950.268371659312920.911444137545692
44-17-17.8028295252642-0.2582283445910340.2681588820656540.68590172006441
45-11-12.98255127835890.2197385683217550.2675226345730072.20012799112367
46-11-11.6449152077150.3249544755335040.2673950066937460.484303382594108
47-12-12.02826736610110.2582867513824500.26746819508178-0.306860201057517
48-10-10.64670519457810.3640155187778320.2673633692245240.48664142956986
49-15-11.46096266649680.254134965817154-3.1478320920414-0.537337054801445
50-15-14.3034361992511-0.03669328858493630.253927830966327-1.26926913357884
51-15-15.0225581156584-0.1008738056285140.252028191059991-0.295170460468173
52-13-13.72525669635780.03072322138386180.252912837456880.606034797341179
53-8-9.626945620454320.4136339470974180.2530983862949851.76245497856273
54-13-12.2334991923580.1293161105190660.253417687881719-1.30841836457253
55-9-9.972850706340340.3299568287658380.2531267972834880.923311794412384
56-7-7.856223157281950.4981504104040750.2528862324034450.774002599067476
57-4-5.036554335128460.716692465912620.2525967273964911.00571473779508
58-4-4.269573287355730.7214264981885710.2525910236579850.0217860000541891
59-2-2.579577833775390.8126049073741420.2524916585152990.419608067124001
600-0.6347450099735350.9191897559862140.2523867734691110.490514508071339



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')