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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 computationWed, 25 Jul 2012 07:36:13 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jul/25/t1343216246g3rduzmn0b2ha71.htm/, Retrieved Fri, 03 May 2024 19:36:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=168862, Retrieved Fri, 03 May 2024 19:36:11 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [Workshop 5: Time ...] [2010-12-07 12:18:30] [eb6e95800005ec22b7fd76eead8d8a59]
- RMPD    [Structural Time Series Models] [Berekening 5 (3EP)] [2012-07-25 11:36:13] [0b94335bf72158573fe52322b9537409] [Current]
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Dataseries X:
-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
-2
-3
1
-2
-1
1
-3
-4
-9
-9
-7
-14
-12
-16
-20
-12
-12
-10
-10




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168862&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168862&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168862&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'Gertrude Mary Cox' @ cox.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1-6-6000
2-3-3.295311794072860.1541809648937280.1541809649898780.567724040537412
3-3-3.152528577055910.1540475521744010.154047552174401-0.00388462012066034
4-7-6.639077934397430.1315126178862110.131512617886211-1.24811656697748
5-9-8.807456337185690.1188351831415170.118835183141517-0.788656374335559
6-11-10.81887706465450.1073189229517580.107318922951758-0.730494777640384
7-13-12.81167956278970.09604554427700940.0960455442770096-0.720155459204117
8-11-11.29586832201990.1036245861975410.1036245861975410.486848850212971
9-9-9.361270945997730.1133466157250990.1133466157250990.627848575699433
10-17-16.14325606770860.0769275272648870.0769275272648868-2.36441537724866
11-22-21.33572950335610.04924235518222980.0492423551822297-1.80686409606999
12-25-24.58531552143610.03200105965747520.032001059657475-1.13114854181923
13-20-21.6468783999326-0.1136701865402491.250372051699851.21681548135372
14-24-23.6522776091292-0.163149055780822-0.16314905568682-0.546524297791949
15-24-23.8342222282825-0.163250017633501-0.1632500176335-0.00642075697783268
16-22-22.0992062642295-0.157803974815287-0.1578039748152870.650190167252608
17-19-19.2563368749429-0.15010413227821-0.150104132278211.02789324245148
18-18-18.0386275819789-0.146651239806656-0.1466512398066570.468553796590533
19-17-17.0148358377357-0.143708914635162-0.1437089146351620.400942743496158
20-11-11.6203625481336-0.129824385377695-0.1298243853776951.89713570962085
21-11-10.9768620482406-0.127890511297907-0.1278905112979080.264906223879469
22-12-11.7790841195685-0.129572618887485-0.129572618887485-0.230995052470251
23-10-10.1175088513171-0.125115752726133-0.1251157527261330.613563699477685
24-15-14.3133668139927-0.135219731591339-0.13521973159134-1.39444322823682
25-15-15.9075451322845-0.1005341538309871.10587569219219-0.554818701167186
26-15-15.0251253792492-0.0838054104594263-0.08380541043972960.303201333439785
27-13-13.1826632079259-0.077079548988096-0.07707954898809580.658461864478055
28-8-8.56720093939353-0.0683142446653316-0.06831424466533171.60683043219609
29-13-12.4135612713809-0.0746324262837686-0.0746324262837683-1.29377657594466
30-9-9.35499008038428-0.0694730984783462-0.06947309847834621.07295877617004
31-7-7.23124811522696-0.0658735315866788-0.06587353158667810.751061558833535
32-4-4.33963206788247-0.0610285297192763-0.06102852971927641.01278474407777
33-4-3.99464039624053-0.0603644851860612-0.06036448518606160.139040445685544
34-2-2.19469536083818-0.0573269323640216-0.05732693236402170.637057005963328
350-0.221117292882282-0.054016234521313-0.05401623452131310.695476205262507
36-2-1.74452838456907-0.056407683074419-0.05640768307442-0.503188564994313
37-3-3.1928777139759-0.03471715031745470.381888653892968-0.511671224677816
3810.5449538216902650.01286575572700130.01286575558686621.1978104168995
39-2-1.701924371930570.007021025616773710.00702102561677351-0.772696407803699
40-1-1.089817565694870.007858921092026660.007858921092026290.207166805321491
4110.7426803528553020.01012211646016460.01012211646016490.624744716730725
42-3-2.557584484363860.006077377597081940.00607737759708165-1.13346013814784
43-4-3.831151072891480.004518365086672730.0045183650866738-0.438143777023427
44-9-8.38183359293539-0.00102346338125297-0.00102346338125325-1.55967755714046
45-9-8.9248836342486-0.00168207260874693-0.00168207260874734-0.185587038195027
46-7-7.230201750948340.0003766491434460960.0003766491434459510.580825749856188
47-14-13.1861831607388-0.00684327315772499-0.00684327315772511-2.03942336292777
48-12-12.1374458645855-0.00556531395093032-0.005565313950931150.361424632834776
49-16-15.24481370429820.0303837974362755-0.334221771995932-1.12055238270558
50-20-19.472601345605-0.0122793992227488-0.0122793993124492-1.37423423457016
51-12-12.89204973082880.001262093724144340.001262093724144542.25476453703457
52-12-12.10814097489740.00212314340914960.00212314340914910.267938043310582
53-10-10.2547613745170.003947974801523180.003947974801523190.633801229424291
54-10-10.03358956437370.004158954428153780.004158954428153630.0743696053585824

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & -6 & -6 & 0 & 0 & 0 \tabularnewline
2 & -3 & -3.29531179407286 & 0.154180964893728 & 0.154180964989878 & 0.567724040537412 \tabularnewline
3 & -3 & -3.15252857705591 & 0.154047552174401 & 0.154047552174401 & -0.00388462012066034 \tabularnewline
4 & -7 & -6.63907793439743 & 0.131512617886211 & 0.131512617886211 & -1.24811656697748 \tabularnewline
5 & -9 & -8.80745633718569 & 0.118835183141517 & 0.118835183141517 & -0.788656374335559 \tabularnewline
6 & -11 & -10.8188770646545 & 0.107318922951758 & 0.107318922951758 & -0.730494777640384 \tabularnewline
7 & -13 & -12.8116795627897 & 0.0960455442770094 & 0.0960455442770096 & -0.720155459204117 \tabularnewline
8 & -11 & -11.2958683220199 & 0.103624586197541 & 0.103624586197541 & 0.486848850212971 \tabularnewline
9 & -9 & -9.36127094599773 & 0.113346615725099 & 0.113346615725099 & 0.627848575699433 \tabularnewline
10 & -17 & -16.1432560677086 & 0.076927527264887 & 0.0769275272648868 & -2.36441537724866 \tabularnewline
11 & -22 & -21.3357295033561 & 0.0492423551822298 & 0.0492423551822297 & -1.80686409606999 \tabularnewline
12 & -25 & -24.5853155214361 & 0.0320010596574752 & 0.032001059657475 & -1.13114854181923 \tabularnewline
13 & -20 & -21.6468783999326 & -0.113670186540249 & 1.25037205169985 & 1.21681548135372 \tabularnewline
14 & -24 & -23.6522776091292 & -0.163149055780822 & -0.16314905568682 & -0.546524297791949 \tabularnewline
15 & -24 & -23.8342222282825 & -0.163250017633501 & -0.1632500176335 & -0.00642075697783268 \tabularnewline
16 & -22 & -22.0992062642295 & -0.157803974815287 & -0.157803974815287 & 0.650190167252608 \tabularnewline
17 & -19 & -19.2563368749429 & -0.15010413227821 & -0.15010413227821 & 1.02789324245148 \tabularnewline
18 & -18 & -18.0386275819789 & -0.146651239806656 & -0.146651239806657 & 0.468553796590533 \tabularnewline
19 & -17 & -17.0148358377357 & -0.143708914635162 & -0.143708914635162 & 0.400942743496158 \tabularnewline
20 & -11 & -11.6203625481336 & -0.129824385377695 & -0.129824385377695 & 1.89713570962085 \tabularnewline
21 & -11 & -10.9768620482406 & -0.127890511297907 & -0.127890511297908 & 0.264906223879469 \tabularnewline
22 & -12 & -11.7790841195685 & -0.129572618887485 & -0.129572618887485 & -0.230995052470251 \tabularnewline
23 & -10 & -10.1175088513171 & -0.125115752726133 & -0.125115752726133 & 0.613563699477685 \tabularnewline
24 & -15 & -14.3133668139927 & -0.135219731591339 & -0.13521973159134 & -1.39444322823682 \tabularnewline
25 & -15 & -15.9075451322845 & -0.100534153830987 & 1.10587569219219 & -0.554818701167186 \tabularnewline
26 & -15 & -15.0251253792492 & -0.0838054104594263 & -0.0838054104397296 & 0.303201333439785 \tabularnewline
27 & -13 & -13.1826632079259 & -0.077079548988096 & -0.0770795489880958 & 0.658461864478055 \tabularnewline
28 & -8 & -8.56720093939353 & -0.0683142446653316 & -0.0683142446653317 & 1.60683043219609 \tabularnewline
29 & -13 & -12.4135612713809 & -0.0746324262837686 & -0.0746324262837683 & -1.29377657594466 \tabularnewline
30 & -9 & -9.35499008038428 & -0.0694730984783462 & -0.0694730984783462 & 1.07295877617004 \tabularnewline
31 & -7 & -7.23124811522696 & -0.0658735315866788 & -0.0658735315866781 & 0.751061558833535 \tabularnewline
32 & -4 & -4.33963206788247 & -0.0610285297192763 & -0.0610285297192764 & 1.01278474407777 \tabularnewline
33 & -4 & -3.99464039624053 & -0.0603644851860612 & -0.0603644851860616 & 0.139040445685544 \tabularnewline
34 & -2 & -2.19469536083818 & -0.0573269323640216 & -0.0573269323640217 & 0.637057005963328 \tabularnewline
35 & 0 & -0.221117292882282 & -0.054016234521313 & -0.0540162345213131 & 0.695476205262507 \tabularnewline
36 & -2 & -1.74452838456907 & -0.056407683074419 & -0.05640768307442 & -0.503188564994313 \tabularnewline
37 & -3 & -3.1928777139759 & -0.0347171503174547 & 0.381888653892968 & -0.511671224677816 \tabularnewline
38 & 1 & 0.544953821690265 & 0.0128657557270013 & 0.0128657555868662 & 1.1978104168995 \tabularnewline
39 & -2 & -1.70192437193057 & 0.00702102561677371 & 0.00702102561677351 & -0.772696407803699 \tabularnewline
40 & -1 & -1.08981756569487 & 0.00785892109202666 & 0.00785892109202629 & 0.207166805321491 \tabularnewline
41 & 1 & 0.742680352855302 & 0.0101221164601646 & 0.0101221164601649 & 0.624744716730725 \tabularnewline
42 & -3 & -2.55758448436386 & 0.00607737759708194 & 0.00607737759708165 & -1.13346013814784 \tabularnewline
43 & -4 & -3.83115107289148 & 0.00451836508667273 & 0.0045183650866738 & -0.438143777023427 \tabularnewline
44 & -9 & -8.38183359293539 & -0.00102346338125297 & -0.00102346338125325 & -1.55967755714046 \tabularnewline
45 & -9 & -8.9248836342486 & -0.00168207260874693 & -0.00168207260874734 & -0.185587038195027 \tabularnewline
46 & -7 & -7.23020175094834 & 0.000376649143446096 & 0.000376649143445951 & 0.580825749856188 \tabularnewline
47 & -14 & -13.1861831607388 & -0.00684327315772499 & -0.00684327315772511 & -2.03942336292777 \tabularnewline
48 & -12 & -12.1374458645855 & -0.00556531395093032 & -0.00556531395093115 & 0.361424632834776 \tabularnewline
49 & -16 & -15.2448137042982 & 0.0303837974362755 & -0.334221771995932 & -1.12055238270558 \tabularnewline
50 & -20 & -19.472601345605 & -0.0122793992227488 & -0.0122793993124492 & -1.37423423457016 \tabularnewline
51 & -12 & -12.8920497308288 & 0.00126209372414434 & 0.00126209372414454 & 2.25476453703457 \tabularnewline
52 & -12 & -12.1081409748974 & 0.0021231434091496 & 0.0021231434091491 & 0.267938043310582 \tabularnewline
53 & -10 & -10.254761374517 & 0.00394797480152318 & 0.00394797480152319 & 0.633801229424291 \tabularnewline
54 & -10 & -10.0335895643737 & 0.00415895442815378 & 0.00415895442815363 & 0.0743696053585824 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=168862&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]-6[/C][C]-6[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-3[/C][C]-3.29531179407286[/C][C]0.154180964893728[/C][C]0.154180964989878[/C][C]0.567724040537412[/C][/ROW]
[ROW][C]3[/C][C]-3[/C][C]-3.15252857705591[/C][C]0.154047552174401[/C][C]0.154047552174401[/C][C]-0.00388462012066034[/C][/ROW]
[ROW][C]4[/C][C]-7[/C][C]-6.63907793439743[/C][C]0.131512617886211[/C][C]0.131512617886211[/C][C]-1.24811656697748[/C][/ROW]
[ROW][C]5[/C][C]-9[/C][C]-8.80745633718569[/C][C]0.118835183141517[/C][C]0.118835183141517[/C][C]-0.788656374335559[/C][/ROW]
[ROW][C]6[/C][C]-11[/C][C]-10.8188770646545[/C][C]0.107318922951758[/C][C]0.107318922951758[/C][C]-0.730494777640384[/C][/ROW]
[ROW][C]7[/C][C]-13[/C][C]-12.8116795627897[/C][C]0.0960455442770094[/C][C]0.0960455442770096[/C][C]-0.720155459204117[/C][/ROW]
[ROW][C]8[/C][C]-11[/C][C]-11.2958683220199[/C][C]0.103624586197541[/C][C]0.103624586197541[/C][C]0.486848850212971[/C][/ROW]
[ROW][C]9[/C][C]-9[/C][C]-9.36127094599773[/C][C]0.113346615725099[/C][C]0.113346615725099[/C][C]0.627848575699433[/C][/ROW]
[ROW][C]10[/C][C]-17[/C][C]-16.1432560677086[/C][C]0.076927527264887[/C][C]0.0769275272648868[/C][C]-2.36441537724866[/C][/ROW]
[ROW][C]11[/C][C]-22[/C][C]-21.3357295033561[/C][C]0.0492423551822298[/C][C]0.0492423551822297[/C][C]-1.80686409606999[/C][/ROW]
[ROW][C]12[/C][C]-25[/C][C]-24.5853155214361[/C][C]0.0320010596574752[/C][C]0.032001059657475[/C][C]-1.13114854181923[/C][/ROW]
[ROW][C]13[/C][C]-20[/C][C]-21.6468783999326[/C][C]-0.113670186540249[/C][C]1.25037205169985[/C][C]1.21681548135372[/C][/ROW]
[ROW][C]14[/C][C]-24[/C][C]-23.6522776091292[/C][C]-0.163149055780822[/C][C]-0.16314905568682[/C][C]-0.546524297791949[/C][/ROW]
[ROW][C]15[/C][C]-24[/C][C]-23.8342222282825[/C][C]-0.163250017633501[/C][C]-0.1632500176335[/C][C]-0.00642075697783268[/C][/ROW]
[ROW][C]16[/C][C]-22[/C][C]-22.0992062642295[/C][C]-0.157803974815287[/C][C]-0.157803974815287[/C][C]0.650190167252608[/C][/ROW]
[ROW][C]17[/C][C]-19[/C][C]-19.2563368749429[/C][C]-0.15010413227821[/C][C]-0.15010413227821[/C][C]1.02789324245148[/C][/ROW]
[ROW][C]18[/C][C]-18[/C][C]-18.0386275819789[/C][C]-0.146651239806656[/C][C]-0.146651239806657[/C][C]0.468553796590533[/C][/ROW]
[ROW][C]19[/C][C]-17[/C][C]-17.0148358377357[/C][C]-0.143708914635162[/C][C]-0.143708914635162[/C][C]0.400942743496158[/C][/ROW]
[ROW][C]20[/C][C]-11[/C][C]-11.6203625481336[/C][C]-0.129824385377695[/C][C]-0.129824385377695[/C][C]1.89713570962085[/C][/ROW]
[ROW][C]21[/C][C]-11[/C][C]-10.9768620482406[/C][C]-0.127890511297907[/C][C]-0.127890511297908[/C][C]0.264906223879469[/C][/ROW]
[ROW][C]22[/C][C]-12[/C][C]-11.7790841195685[/C][C]-0.129572618887485[/C][C]-0.129572618887485[/C][C]-0.230995052470251[/C][/ROW]
[ROW][C]23[/C][C]-10[/C][C]-10.1175088513171[/C][C]-0.125115752726133[/C][C]-0.125115752726133[/C][C]0.613563699477685[/C][/ROW]
[ROW][C]24[/C][C]-15[/C][C]-14.3133668139927[/C][C]-0.135219731591339[/C][C]-0.13521973159134[/C][C]-1.39444322823682[/C][/ROW]
[ROW][C]25[/C][C]-15[/C][C]-15.9075451322845[/C][C]-0.100534153830987[/C][C]1.10587569219219[/C][C]-0.554818701167186[/C][/ROW]
[ROW][C]26[/C][C]-15[/C][C]-15.0251253792492[/C][C]-0.0838054104594263[/C][C]-0.0838054104397296[/C][C]0.303201333439785[/C][/ROW]
[ROW][C]27[/C][C]-13[/C][C]-13.1826632079259[/C][C]-0.077079548988096[/C][C]-0.0770795489880958[/C][C]0.658461864478055[/C][/ROW]
[ROW][C]28[/C][C]-8[/C][C]-8.56720093939353[/C][C]-0.0683142446653316[/C][C]-0.0683142446653317[/C][C]1.60683043219609[/C][/ROW]
[ROW][C]29[/C][C]-13[/C][C]-12.4135612713809[/C][C]-0.0746324262837686[/C][C]-0.0746324262837683[/C][C]-1.29377657594466[/C][/ROW]
[ROW][C]30[/C][C]-9[/C][C]-9.35499008038428[/C][C]-0.0694730984783462[/C][C]-0.0694730984783462[/C][C]1.07295877617004[/C][/ROW]
[ROW][C]31[/C][C]-7[/C][C]-7.23124811522696[/C][C]-0.0658735315866788[/C][C]-0.0658735315866781[/C][C]0.751061558833535[/C][/ROW]
[ROW][C]32[/C][C]-4[/C][C]-4.33963206788247[/C][C]-0.0610285297192763[/C][C]-0.0610285297192764[/C][C]1.01278474407777[/C][/ROW]
[ROW][C]33[/C][C]-4[/C][C]-3.99464039624053[/C][C]-0.0603644851860612[/C][C]-0.0603644851860616[/C][C]0.139040445685544[/C][/ROW]
[ROW][C]34[/C][C]-2[/C][C]-2.19469536083818[/C][C]-0.0573269323640216[/C][C]-0.0573269323640217[/C][C]0.637057005963328[/C][/ROW]
[ROW][C]35[/C][C]0[/C][C]-0.221117292882282[/C][C]-0.054016234521313[/C][C]-0.0540162345213131[/C][C]0.695476205262507[/C][/ROW]
[ROW][C]36[/C][C]-2[/C][C]-1.74452838456907[/C][C]-0.056407683074419[/C][C]-0.05640768307442[/C][C]-0.503188564994313[/C][/ROW]
[ROW][C]37[/C][C]-3[/C][C]-3.1928777139759[/C][C]-0.0347171503174547[/C][C]0.381888653892968[/C][C]-0.511671224677816[/C][/ROW]
[ROW][C]38[/C][C]1[/C][C]0.544953821690265[/C][C]0.0128657557270013[/C][C]0.0128657555868662[/C][C]1.1978104168995[/C][/ROW]
[ROW][C]39[/C][C]-2[/C][C]-1.70192437193057[/C][C]0.00702102561677371[/C][C]0.00702102561677351[/C][C]-0.772696407803699[/C][/ROW]
[ROW][C]40[/C][C]-1[/C][C]-1.08981756569487[/C][C]0.00785892109202666[/C][C]0.00785892109202629[/C][C]0.207166805321491[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.742680352855302[/C][C]0.0101221164601646[/C][C]0.0101221164601649[/C][C]0.624744716730725[/C][/ROW]
[ROW][C]42[/C][C]-3[/C][C]-2.55758448436386[/C][C]0.00607737759708194[/C][C]0.00607737759708165[/C][C]-1.13346013814784[/C][/ROW]
[ROW][C]43[/C][C]-4[/C][C]-3.83115107289148[/C][C]0.00451836508667273[/C][C]0.0045183650866738[/C][C]-0.438143777023427[/C][/ROW]
[ROW][C]44[/C][C]-9[/C][C]-8.38183359293539[/C][C]-0.00102346338125297[/C][C]-0.00102346338125325[/C][C]-1.55967755714046[/C][/ROW]
[ROW][C]45[/C][C]-9[/C][C]-8.9248836342486[/C][C]-0.00168207260874693[/C][C]-0.00168207260874734[/C][C]-0.185587038195027[/C][/ROW]
[ROW][C]46[/C][C]-7[/C][C]-7.23020175094834[/C][C]0.000376649143446096[/C][C]0.000376649143445951[/C][C]0.580825749856188[/C][/ROW]
[ROW][C]47[/C][C]-14[/C][C]-13.1861831607388[/C][C]-0.00684327315772499[/C][C]-0.00684327315772511[/C][C]-2.03942336292777[/C][/ROW]
[ROW][C]48[/C][C]-12[/C][C]-12.1374458645855[/C][C]-0.00556531395093032[/C][C]-0.00556531395093115[/C][C]0.361424632834776[/C][/ROW]
[ROW][C]49[/C][C]-16[/C][C]-15.2448137042982[/C][C]0.0303837974362755[/C][C]-0.334221771995932[/C][C]-1.12055238270558[/C][/ROW]
[ROW][C]50[/C][C]-20[/C][C]-19.472601345605[/C][C]-0.0122793992227488[/C][C]-0.0122793993124492[/C][C]-1.37423423457016[/C][/ROW]
[ROW][C]51[/C][C]-12[/C][C]-12.8920497308288[/C][C]0.00126209372414434[/C][C]0.00126209372414454[/C][C]2.25476453703457[/C][/ROW]
[ROW][C]52[/C][C]-12[/C][C]-12.1081409748974[/C][C]0.0021231434091496[/C][C]0.0021231434091491[/C][C]0.267938043310582[/C][/ROW]
[ROW][C]53[/C][C]-10[/C][C]-10.254761374517[/C][C]0.00394797480152318[/C][C]0.00394797480152319[/C][C]0.633801229424291[/C][/ROW]
[ROW][C]54[/C][C]-10[/C][C]-10.0335895643737[/C][C]0.00415895442815378[/C][C]0.00415895442815363[/C][C]0.0743696053585824[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=168862&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=168862&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
1-6-6000
2-3-3.295311794072860.1541809648937280.1541809649898780.567724040537412
3-3-3.152528577055910.1540475521744010.154047552174401-0.00388462012066034
4-7-6.639077934397430.1315126178862110.131512617886211-1.24811656697748
5-9-8.807456337185690.1188351831415170.118835183141517-0.788656374335559
6-11-10.81887706465450.1073189229517580.107318922951758-0.730494777640384
7-13-12.81167956278970.09604554427700940.0960455442770096-0.720155459204117
8-11-11.29586832201990.1036245861975410.1036245861975410.486848850212971
9-9-9.361270945997730.1133466157250990.1133466157250990.627848575699433
10-17-16.14325606770860.0769275272648870.0769275272648868-2.36441537724866
11-22-21.33572950335610.04924235518222980.0492423551822297-1.80686409606999
12-25-24.58531552143610.03200105965747520.032001059657475-1.13114854181923
13-20-21.6468783999326-0.1136701865402491.250372051699851.21681548135372
14-24-23.6522776091292-0.163149055780822-0.16314905568682-0.546524297791949
15-24-23.8342222282825-0.163250017633501-0.1632500176335-0.00642075697783268
16-22-22.0992062642295-0.157803974815287-0.1578039748152870.650190167252608
17-19-19.2563368749429-0.15010413227821-0.150104132278211.02789324245148
18-18-18.0386275819789-0.146651239806656-0.1466512398066570.468553796590533
19-17-17.0148358377357-0.143708914635162-0.1437089146351620.400942743496158
20-11-11.6203625481336-0.129824385377695-0.1298243853776951.89713570962085
21-11-10.9768620482406-0.127890511297907-0.1278905112979080.264906223879469
22-12-11.7790841195685-0.129572618887485-0.129572618887485-0.230995052470251
23-10-10.1175088513171-0.125115752726133-0.1251157527261330.613563699477685
24-15-14.3133668139927-0.135219731591339-0.13521973159134-1.39444322823682
25-15-15.9075451322845-0.1005341538309871.10587569219219-0.554818701167186
26-15-15.0251253792492-0.0838054104594263-0.08380541043972960.303201333439785
27-13-13.1826632079259-0.077079548988096-0.07707954898809580.658461864478055
28-8-8.56720093939353-0.0683142446653316-0.06831424466533171.60683043219609
29-13-12.4135612713809-0.0746324262837686-0.0746324262837683-1.29377657594466
30-9-9.35499008038428-0.0694730984783462-0.06947309847834621.07295877617004
31-7-7.23124811522696-0.0658735315866788-0.06587353158667810.751061558833535
32-4-4.33963206788247-0.0610285297192763-0.06102852971927641.01278474407777
33-4-3.99464039624053-0.0603644851860612-0.06036448518606160.139040445685544
34-2-2.19469536083818-0.0573269323640216-0.05732693236402170.637057005963328
350-0.221117292882282-0.054016234521313-0.05401623452131310.695476205262507
36-2-1.74452838456907-0.056407683074419-0.05640768307442-0.503188564994313
37-3-3.1928777139759-0.03471715031745470.381888653892968-0.511671224677816
3810.5449538216902650.01286575572700130.01286575558686621.1978104168995
39-2-1.701924371930570.007021025616773710.00702102561677351-0.772696407803699
40-1-1.089817565694870.007858921092026660.007858921092026290.207166805321491
4110.7426803528553020.01012211646016460.01012211646016490.624744716730725
42-3-2.557584484363860.006077377597081940.00607737759708165-1.13346013814784
43-4-3.831151072891480.004518365086672730.0045183650866738-0.438143777023427
44-9-8.38183359293539-0.00102346338125297-0.00102346338125325-1.55967755714046
45-9-8.9248836342486-0.00168207260874693-0.00168207260874734-0.185587038195027
46-7-7.230201750948340.0003766491434460960.0003766491434459510.580825749856188
47-14-13.1861831607388-0.00684327315772499-0.00684327315772511-2.03942336292777
48-12-12.1374458645855-0.00556531395093032-0.005565313950931150.361424632834776
49-16-15.24481370429820.0303837974362755-0.334221771995932-1.12055238270558
50-20-19.472601345605-0.0122793992227488-0.0122793993124492-1.37423423457016
51-12-12.89204973082880.001262093724144340.001262093724144542.25476453703457
52-12-12.10814097489740.00212314340914960.00212314340914910.267938043310582
53-10-10.2547613745170.003947974801523180.003947974801523190.633801229424291
54-10-10.03358956437370.004158954428153780.004158954428153630.0743696053585824



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')