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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 computationMon, 26 Nov 2012 16:40:52 -0500
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/Nov/26/t13539660752o6er3r6d68rp3w.htm/, Retrieved Tue, 30 Apr 2024 04:41:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=193666, Retrieved Tue, 30 Apr 2024 04:41:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact101
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMPD  [Central Tendency] [] [2011-12-06 20:01:16] [b98453cac15ba1066b407e146608df68]
- RMP       [Structural Time Series Models] [structural time s...] [2012-11-26 21:40:52] [239167cccea8953a8e1721fd6db07280] [Current]
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Dataseries X:
867.887509505211
-2250.28069676838
33618.3570412959
9954.34468238836
354.191730842355
18882.406400463
20229.4310915672
268402.416151187
-113346.926055862
-45016.394227939
35069.861367254
58531.0957290091
-77256.3771198791
-31473.594568955
-52391.0075132882
32854.9847569661
101107.732845397
-176275.960398033
79531.884415102
-176414.251561376
151290.579462589
167731.594163443
143237.122434691
80251.9665265577
118735.726273623
75035.8259037494
19198.3085437346
-36364.5639276314
-36170.5787440905
-109567.395064155
-100783.336097857
-149267.403931369
38947.3510583149
58613.0600994635
16074.4602044407
-41563.0049150659
-15970.5964777959
-47563.9548420802
59595.3577179922
65897.8405390448
-166489.283203891
46312.3269884632
-15952.8722863516
-87780.6523566012
134744.172737777
75232.8122408289
24408.7558471514
-15406.1403381955
-3766.75348767364
27197.2239951006
-46777.2890031503
-82472.8212609495
-35154.7184801844
-46946.870011609
-43641.5364941684
-54920.7084991732
54905.4038222157
-10509.5840707596
-13706.8046976985
-42347.6087628011
-28990.4687708701




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ yule.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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193666&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193666&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193666&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 time5 seconds
R Server'George Udny Yule' @ yule.wessa.net







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1867.887509505211867.887509505211000
2-2250.28069676838482.135137691015-128.584123938065-128.584124082563-0.0336588434170022
333618.35704129595827.87280138251239.996322969321239.996322969320.351730048858743
49954.344682388367380.491566960431302.520811491041302.520811491050.0170903372715027
5354.1917308423556728.8280946165976.823430851881976.823430851879-0.0993969702204615
618882.4064004639813.38566221591277.92830753011277.92830753010.105303005820063
720229.431091567212699.07940890711478.898987425231478.898987425230.0814684163085219
8268402.41615118764503.40644820697070.61321541137070.613215411322.63468433830274
9-113346.92605586234717.00777195343384.912026244823384.91202624481-2.01426689415987
10-45016.39422793922176.64189911861937.159489964851937.15948996485-0.913467306676191
1135069.86136725425701.77917473312069.490972102322069.490972102320.0958383396219359
1258531.095729009132597.18550602172440.715230501262440.715230501260.306677427551755
13-77256.377119879131748.48835608012205.75720332678-24263.3292415882-1.00516658066521
14-31473.59456895521903.71685895361402.388623296561402.38862401665-0.719008512428302
15-52391.007513288210487.607215225601.232481607484601.232481607483-0.826393105169983
1632854.984756966114393.1575132824795.604117869243795.6041178692450.228414178405465
17101107.73284539727731.71307402471492.434753584411492.434753584420.924021815061962
18-176275.960398033316.700765591786-29.0098286270242-29.0098286270187-2.25824451512009
1979531.88441510210817.3381036684497.47252970816497.4725297081580.868665773764188
20-176414.251561376-12536.1648656564-638.288208341031-638.288208341026-2.07060096354289
21151290.5794625896835.67346633311271.26299803763271.2629980376321.82254753694878
22167731.59416344325737.76618888371081.299073016451081.299073016461.77564787964596
23143237.12243469139691.47106157111617.649314669411617.649314669421.28077720379748
2480251.966526557745317.94019519031778.00210742741778.00210742740.415551869814646
25118735.72627362352762.20711502771995.93536944317-21955.28905542561.05779316057466
2675035.825903749456715.51415077592068.430616343362068.430609284130.203612127549494
2719198.308543734654503.62309560981915.561985218021915.56198521802-0.465119948473153
28-36364.563927631447058.99425671771592.796784386641592.79678438663-1.05990664119725
29-36170.578744090540420.08930073411318.40672637431318.4067263743-0.969241436163834
30-109567.39506415527702.7769171124865.641593793778865.64159379379-1.71517306419433
31-100783.33609785716989.6403668657503.804776792514503.804776792519-1.46597719861144
32-149267.4039313693092.6670443737767.41756166268367.4175616626907-1.88615204328821
3338947.35105831496141.54072467201155.107447504905155.1074475049010.403407564198154
3458613.060099463510522.4080400068275.843443728617275.8434437286190.589927166576592
3516074.460204440711191.8507338121286.776756230746286.7767562307480.0566273104233811
36-41563.00491506597396.0976591097176.438112151472176.438112151475-0.604672401901499
37-15970.59647779596411.81448088498145.892815036309-1604.8209666728-0.250259560008362
38-47563.95484208022466.9904409892541.002639268820841.0026361663814-0.615758384449737
3959595.35771799226689.08144556856145.529848401583145.5298484015840.648055805604832
4065897.840539044811037.4397091987248.037858529108248.0378585291040.670056365754829
41-166489.283203891-1085.49373156325-46.5090771682974-46.5090771683089-2.02671385233897
4246312.32698846322085.6396919200528.31981819569328.3198181957030.541191538800866
43-15952.8722863516917.685717854961.131777462493521.13177746250445-0.206396993693554
44-87780.6523566012-4807.19275866092-126.112894848137-126.112894848127-1.01261777883752
45134744.1727377773885.2315743451365.594436192171565.5944361921711.59733112229586
4675232.81224082898343.07783402122159.046602649276159.0466026492790.814321210688312
4724408.75584715149452.3122092113178.842181243876178.8421812438790.180198808957868
48-15406.14033819558141.77311559246148.446645022188148.44664502219-0.288750709949241
49-3766.753487673647817.51174780277138.992484765951-1528.91732977798-0.120937216469998
5027197.22399510069064.86832035272160.725113938186160.7251128744880.218863341042955
51-46777.28900315036035.031903699499.368161426810899.368161426814-0.643941291192813
52-82472.82126094951198.015491461596.228829848232976.22882984822569-1.01771019548593
53-35154.7184801844-779.129454254367-30.5003141436965-30.5003141437091-0.417463225964831
54-46946.870011609-3275.44489119386-75.3333163763473-75.333316376336-0.529601187669513
55-43641.5364941684-5460.69990868224-113.010489610491-113.010489610475-0.462187646004049
56-54920.7084991732-8108.87273695363-157.4870218677-157.487021867688-0.566136994558455
5754905.4038222157-5064.57656837232-102.283863411682-102.2838634116820.728588209068161
58-10509.5840707596-5427.09970764403-106.69469859575-106.694698595748-0.0603195145012887
59-13706.8046976985-5927.39911827395-113.254777129653-113.254777129653-0.0928900608170904
60-42347.6087628011-7776.66624250811-141.713995934645-141.713995934641-0.416987561775341
61-28990.4687708701-8796.93347975583-155.8842095042111714.72630184939-0.263025734938178

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 867.887509505211 & 867.887509505211 & 0 & 0 & 0 \tabularnewline
2 & -2250.28069676838 & 482.135137691015 & -128.584123938065 & -128.584124082563 & -0.0336588434170022 \tabularnewline
3 & 33618.3570412959 & 5827.8728013825 & 1239.99632296932 & 1239.99632296932 & 0.351730048858743 \tabularnewline
4 & 9954.34468238836 & 7380.49156696043 & 1302.52081149104 & 1302.52081149105 & 0.0170903372715027 \tabularnewline
5 & 354.191730842355 & 6728.8280946165 & 976.823430851881 & 976.823430851879 & -0.0993969702204615 \tabularnewline
6 & 18882.406400463 & 9813.3856622159 & 1277.9283075301 & 1277.9283075301 & 0.105303005820063 \tabularnewline
7 & 20229.4310915672 & 12699.0794089071 & 1478.89898742523 & 1478.89898742523 & 0.0814684163085219 \tabularnewline
8 & 268402.416151187 & 64503.4064482069 & 7070.6132154113 & 7070.61321541132 & 2.63468433830274 \tabularnewline
9 & -113346.926055862 & 34717.0077719534 & 3384.91202624482 & 3384.91202624481 & -2.01426689415987 \tabularnewline
10 & -45016.394227939 & 22176.6418991186 & 1937.15948996485 & 1937.15948996485 & -0.913467306676191 \tabularnewline
11 & 35069.861367254 & 25701.7791747331 & 2069.49097210232 & 2069.49097210232 & 0.0958383396219359 \tabularnewline
12 & 58531.0957290091 & 32597.1855060217 & 2440.71523050126 & 2440.71523050126 & 0.306677427551755 \tabularnewline
13 & -77256.3771198791 & 31748.4883560801 & 2205.75720332678 & -24263.3292415882 & -1.00516658066521 \tabularnewline
14 & -31473.594568955 & 21903.7168589536 & 1402.38862329656 & 1402.38862401665 & -0.719008512428302 \tabularnewline
15 & -52391.0075132882 & 10487.607215225 & 601.232481607484 & 601.232481607483 & -0.826393105169983 \tabularnewline
16 & 32854.9847569661 & 14393.1575132824 & 795.604117869243 & 795.604117869245 & 0.228414178405465 \tabularnewline
17 & 101107.732845397 & 27731.7130740247 & 1492.43475358441 & 1492.43475358442 & 0.924021815061962 \tabularnewline
18 & -176275.960398033 & 316.700765591786 & -29.0098286270242 & -29.0098286270187 & -2.25824451512009 \tabularnewline
19 & 79531.884415102 & 10817.3381036684 & 497.47252970816 & 497.472529708158 & 0.868665773764188 \tabularnewline
20 & -176414.251561376 & -12536.1648656564 & -638.288208341031 & -638.288208341026 & -2.07060096354289 \tabularnewline
21 & 151290.579462589 & 6835.67346633311 & 271.26299803763 & 271.262998037632 & 1.82254753694878 \tabularnewline
22 & 167731.594163443 & 25737.7661888837 & 1081.29907301645 & 1081.29907301646 & 1.77564787964596 \tabularnewline
23 & 143237.122434691 & 39691.4710615711 & 1617.64931466941 & 1617.64931466942 & 1.28077720379748 \tabularnewline
24 & 80251.9665265577 & 45317.9401951903 & 1778.0021074274 & 1778.0021074274 & 0.415551869814646 \tabularnewline
25 & 118735.726273623 & 52762.2071150277 & 1995.93536944317 & -21955.2890554256 & 1.05779316057466 \tabularnewline
26 & 75035.8259037494 & 56715.5141507759 & 2068.43061634336 & 2068.43060928413 & 0.203612127549494 \tabularnewline
27 & 19198.3085437346 & 54503.6230956098 & 1915.56198521802 & 1915.56198521802 & -0.465119948473153 \tabularnewline
28 & -36364.5639276314 & 47058.9942567177 & 1592.79678438664 & 1592.79678438663 & -1.05990664119725 \tabularnewline
29 & -36170.5787440905 & 40420.0893007341 & 1318.4067263743 & 1318.4067263743 & -0.969241436163834 \tabularnewline
30 & -109567.395064155 & 27702.7769171124 & 865.641593793778 & 865.64159379379 & -1.71517306419433 \tabularnewline
31 & -100783.336097857 & 16989.6403668657 & 503.804776792514 & 503.804776792519 & -1.46597719861144 \tabularnewline
32 & -149267.403931369 & 3092.66704437377 & 67.417561662683 & 67.4175616626907 & -1.88615204328821 \tabularnewline
33 & 38947.3510583149 & 6141.54072467201 & 155.107447504905 & 155.107447504901 & 0.403407564198154 \tabularnewline
34 & 58613.0600994635 & 10522.4080400068 & 275.843443728617 & 275.843443728619 & 0.589927166576592 \tabularnewline
35 & 16074.4602044407 & 11191.8507338121 & 286.776756230746 & 286.776756230748 & 0.0566273104233811 \tabularnewline
36 & -41563.0049150659 & 7396.0976591097 & 176.438112151472 & 176.438112151475 & -0.604672401901499 \tabularnewline
37 & -15970.5964777959 & 6411.81448088498 & 145.892815036309 & -1604.8209666728 & -0.250259560008362 \tabularnewline
38 & -47563.9548420802 & 2466.99044098925 & 41.0026392688208 & 41.0026361663814 & -0.615758384449737 \tabularnewline
39 & 59595.3577179922 & 6689.08144556856 & 145.529848401583 & 145.529848401584 & 0.648055805604832 \tabularnewline
40 & 65897.8405390448 & 11037.4397091987 & 248.037858529108 & 248.037858529104 & 0.670056365754829 \tabularnewline
41 & -166489.283203891 & -1085.49373156325 & -46.5090771682974 & -46.5090771683089 & -2.02671385233897 \tabularnewline
42 & 46312.3269884632 & 2085.63969192005 & 28.319818195693 & 28.319818195703 & 0.541191538800866 \tabularnewline
43 & -15952.8722863516 & 917.68571785496 & 1.13177746249352 & 1.13177746250445 & -0.206396993693554 \tabularnewline
44 & -87780.6523566012 & -4807.19275866092 & -126.112894848137 & -126.112894848127 & -1.01261777883752 \tabularnewline
45 & 134744.172737777 & 3885.23157434513 & 65.5944361921715 & 65.594436192171 & 1.59733112229586 \tabularnewline
46 & 75232.8122408289 & 8343.07783402122 & 159.046602649276 & 159.046602649279 & 0.814321210688312 \tabularnewline
47 & 24408.7558471514 & 9452.3122092113 & 178.842181243876 & 178.842181243879 & 0.180198808957868 \tabularnewline
48 & -15406.1403381955 & 8141.77311559246 & 148.446645022188 & 148.44664502219 & -0.288750709949241 \tabularnewline
49 & -3766.75348767364 & 7817.51174780277 & 138.992484765951 & -1528.91732977798 & -0.120937216469998 \tabularnewline
50 & 27197.2239951006 & 9064.86832035272 & 160.725113938186 & 160.725112874488 & 0.218863341042955 \tabularnewline
51 & -46777.2890031503 & 6035.0319036994 & 99.3681614268108 & 99.368161426814 & -0.643941291192813 \tabularnewline
52 & -82472.8212609495 & 1198.01549146159 & 6.22882984823297 & 6.22882984822569 & -1.01771019548593 \tabularnewline
53 & -35154.7184801844 & -779.129454254367 & -30.5003141436965 & -30.5003141437091 & -0.417463225964831 \tabularnewline
54 & -46946.870011609 & -3275.44489119386 & -75.3333163763473 & -75.333316376336 & -0.529601187669513 \tabularnewline
55 & -43641.5364941684 & -5460.69990868224 & -113.010489610491 & -113.010489610475 & -0.462187646004049 \tabularnewline
56 & -54920.7084991732 & -8108.87273695363 & -157.4870218677 & -157.487021867688 & -0.566136994558455 \tabularnewline
57 & 54905.4038222157 & -5064.57656837232 & -102.283863411682 & -102.283863411682 & 0.728588209068161 \tabularnewline
58 & -10509.5840707596 & -5427.09970764403 & -106.69469859575 & -106.694698595748 & -0.0603195145012887 \tabularnewline
59 & -13706.8046976985 & -5927.39911827395 & -113.254777129653 & -113.254777129653 & -0.0928900608170904 \tabularnewline
60 & -42347.6087628011 & -7776.66624250811 & -141.713995934645 & -141.713995934641 & -0.416987561775341 \tabularnewline
61 & -28990.4687708701 & -8796.93347975583 & -155.884209504211 & 1714.72630184939 & -0.263025734938178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=193666&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]867.887509505211[/C][C]867.887509505211[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]-2250.28069676838[/C][C]482.135137691015[/C][C]-128.584123938065[/C][C]-128.584124082563[/C][C]-0.0336588434170022[/C][/ROW]
[ROW][C]3[/C][C]33618.3570412959[/C][C]5827.8728013825[/C][C]1239.99632296932[/C][C]1239.99632296932[/C][C]0.351730048858743[/C][/ROW]
[ROW][C]4[/C][C]9954.34468238836[/C][C]7380.49156696043[/C][C]1302.52081149104[/C][C]1302.52081149105[/C][C]0.0170903372715027[/C][/ROW]
[ROW][C]5[/C][C]354.191730842355[/C][C]6728.8280946165[/C][C]976.823430851881[/C][C]976.823430851879[/C][C]-0.0993969702204615[/C][/ROW]
[ROW][C]6[/C][C]18882.406400463[/C][C]9813.3856622159[/C][C]1277.9283075301[/C][C]1277.9283075301[/C][C]0.105303005820063[/C][/ROW]
[ROW][C]7[/C][C]20229.4310915672[/C][C]12699.0794089071[/C][C]1478.89898742523[/C][C]1478.89898742523[/C][C]0.0814684163085219[/C][/ROW]
[ROW][C]8[/C][C]268402.416151187[/C][C]64503.4064482069[/C][C]7070.6132154113[/C][C]7070.61321541132[/C][C]2.63468433830274[/C][/ROW]
[ROW][C]9[/C][C]-113346.926055862[/C][C]34717.0077719534[/C][C]3384.91202624482[/C][C]3384.91202624481[/C][C]-2.01426689415987[/C][/ROW]
[ROW][C]10[/C][C]-45016.394227939[/C][C]22176.6418991186[/C][C]1937.15948996485[/C][C]1937.15948996485[/C][C]-0.913467306676191[/C][/ROW]
[ROW][C]11[/C][C]35069.861367254[/C][C]25701.7791747331[/C][C]2069.49097210232[/C][C]2069.49097210232[/C][C]0.0958383396219359[/C][/ROW]
[ROW][C]12[/C][C]58531.0957290091[/C][C]32597.1855060217[/C][C]2440.71523050126[/C][C]2440.71523050126[/C][C]0.306677427551755[/C][/ROW]
[ROW][C]13[/C][C]-77256.3771198791[/C][C]31748.4883560801[/C][C]2205.75720332678[/C][C]-24263.3292415882[/C][C]-1.00516658066521[/C][/ROW]
[ROW][C]14[/C][C]-31473.594568955[/C][C]21903.7168589536[/C][C]1402.38862329656[/C][C]1402.38862401665[/C][C]-0.719008512428302[/C][/ROW]
[ROW][C]15[/C][C]-52391.0075132882[/C][C]10487.607215225[/C][C]601.232481607484[/C][C]601.232481607483[/C][C]-0.826393105169983[/C][/ROW]
[ROW][C]16[/C][C]32854.9847569661[/C][C]14393.1575132824[/C][C]795.604117869243[/C][C]795.604117869245[/C][C]0.228414178405465[/C][/ROW]
[ROW][C]17[/C][C]101107.732845397[/C][C]27731.7130740247[/C][C]1492.43475358441[/C][C]1492.43475358442[/C][C]0.924021815061962[/C][/ROW]
[ROW][C]18[/C][C]-176275.960398033[/C][C]316.700765591786[/C][C]-29.0098286270242[/C][C]-29.0098286270187[/C][C]-2.25824451512009[/C][/ROW]
[ROW][C]19[/C][C]79531.884415102[/C][C]10817.3381036684[/C][C]497.47252970816[/C][C]497.472529708158[/C][C]0.868665773764188[/C][/ROW]
[ROW][C]20[/C][C]-176414.251561376[/C][C]-12536.1648656564[/C][C]-638.288208341031[/C][C]-638.288208341026[/C][C]-2.07060096354289[/C][/ROW]
[ROW][C]21[/C][C]151290.579462589[/C][C]6835.67346633311[/C][C]271.26299803763[/C][C]271.262998037632[/C][C]1.82254753694878[/C][/ROW]
[ROW][C]22[/C][C]167731.594163443[/C][C]25737.7661888837[/C][C]1081.29907301645[/C][C]1081.29907301646[/C][C]1.77564787964596[/C][/ROW]
[ROW][C]23[/C][C]143237.122434691[/C][C]39691.4710615711[/C][C]1617.64931466941[/C][C]1617.64931466942[/C][C]1.28077720379748[/C][/ROW]
[ROW][C]24[/C][C]80251.9665265577[/C][C]45317.9401951903[/C][C]1778.0021074274[/C][C]1778.0021074274[/C][C]0.415551869814646[/C][/ROW]
[ROW][C]25[/C][C]118735.726273623[/C][C]52762.2071150277[/C][C]1995.93536944317[/C][C]-21955.2890554256[/C][C]1.05779316057466[/C][/ROW]
[ROW][C]26[/C][C]75035.8259037494[/C][C]56715.5141507759[/C][C]2068.43061634336[/C][C]2068.43060928413[/C][C]0.203612127549494[/C][/ROW]
[ROW][C]27[/C][C]19198.3085437346[/C][C]54503.6230956098[/C][C]1915.56198521802[/C][C]1915.56198521802[/C][C]-0.465119948473153[/C][/ROW]
[ROW][C]28[/C][C]-36364.5639276314[/C][C]47058.9942567177[/C][C]1592.79678438664[/C][C]1592.79678438663[/C][C]-1.05990664119725[/C][/ROW]
[ROW][C]29[/C][C]-36170.5787440905[/C][C]40420.0893007341[/C][C]1318.4067263743[/C][C]1318.4067263743[/C][C]-0.969241436163834[/C][/ROW]
[ROW][C]30[/C][C]-109567.395064155[/C][C]27702.7769171124[/C][C]865.641593793778[/C][C]865.64159379379[/C][C]-1.71517306419433[/C][/ROW]
[ROW][C]31[/C][C]-100783.336097857[/C][C]16989.6403668657[/C][C]503.804776792514[/C][C]503.804776792519[/C][C]-1.46597719861144[/C][/ROW]
[ROW][C]32[/C][C]-149267.403931369[/C][C]3092.66704437377[/C][C]67.417561662683[/C][C]67.4175616626907[/C][C]-1.88615204328821[/C][/ROW]
[ROW][C]33[/C][C]38947.3510583149[/C][C]6141.54072467201[/C][C]155.107447504905[/C][C]155.107447504901[/C][C]0.403407564198154[/C][/ROW]
[ROW][C]34[/C][C]58613.0600994635[/C][C]10522.4080400068[/C][C]275.843443728617[/C][C]275.843443728619[/C][C]0.589927166576592[/C][/ROW]
[ROW][C]35[/C][C]16074.4602044407[/C][C]11191.8507338121[/C][C]286.776756230746[/C][C]286.776756230748[/C][C]0.0566273104233811[/C][/ROW]
[ROW][C]36[/C][C]-41563.0049150659[/C][C]7396.0976591097[/C][C]176.438112151472[/C][C]176.438112151475[/C][C]-0.604672401901499[/C][/ROW]
[ROW][C]37[/C][C]-15970.5964777959[/C][C]6411.81448088498[/C][C]145.892815036309[/C][C]-1604.8209666728[/C][C]-0.250259560008362[/C][/ROW]
[ROW][C]38[/C][C]-47563.9548420802[/C][C]2466.99044098925[/C][C]41.0026392688208[/C][C]41.0026361663814[/C][C]-0.615758384449737[/C][/ROW]
[ROW][C]39[/C][C]59595.3577179922[/C][C]6689.08144556856[/C][C]145.529848401583[/C][C]145.529848401584[/C][C]0.648055805604832[/C][/ROW]
[ROW][C]40[/C][C]65897.8405390448[/C][C]11037.4397091987[/C][C]248.037858529108[/C][C]248.037858529104[/C][C]0.670056365754829[/C][/ROW]
[ROW][C]41[/C][C]-166489.283203891[/C][C]-1085.49373156325[/C][C]-46.5090771682974[/C][C]-46.5090771683089[/C][C]-2.02671385233897[/C][/ROW]
[ROW][C]42[/C][C]46312.3269884632[/C][C]2085.63969192005[/C][C]28.319818195693[/C][C]28.319818195703[/C][C]0.541191538800866[/C][/ROW]
[ROW][C]43[/C][C]-15952.8722863516[/C][C]917.68571785496[/C][C]1.13177746249352[/C][C]1.13177746250445[/C][C]-0.206396993693554[/C][/ROW]
[ROW][C]44[/C][C]-87780.6523566012[/C][C]-4807.19275866092[/C][C]-126.112894848137[/C][C]-126.112894848127[/C][C]-1.01261777883752[/C][/ROW]
[ROW][C]45[/C][C]134744.172737777[/C][C]3885.23157434513[/C][C]65.5944361921715[/C][C]65.594436192171[/C][C]1.59733112229586[/C][/ROW]
[ROW][C]46[/C][C]75232.8122408289[/C][C]8343.07783402122[/C][C]159.046602649276[/C][C]159.046602649279[/C][C]0.814321210688312[/C][/ROW]
[ROW][C]47[/C][C]24408.7558471514[/C][C]9452.3122092113[/C][C]178.842181243876[/C][C]178.842181243879[/C][C]0.180198808957868[/C][/ROW]
[ROW][C]48[/C][C]-15406.1403381955[/C][C]8141.77311559246[/C][C]148.446645022188[/C][C]148.44664502219[/C][C]-0.288750709949241[/C][/ROW]
[ROW][C]49[/C][C]-3766.75348767364[/C][C]7817.51174780277[/C][C]138.992484765951[/C][C]-1528.91732977798[/C][C]-0.120937216469998[/C][/ROW]
[ROW][C]50[/C][C]27197.2239951006[/C][C]9064.86832035272[/C][C]160.725113938186[/C][C]160.725112874488[/C][C]0.218863341042955[/C][/ROW]
[ROW][C]51[/C][C]-46777.2890031503[/C][C]6035.0319036994[/C][C]99.3681614268108[/C][C]99.368161426814[/C][C]-0.643941291192813[/C][/ROW]
[ROW][C]52[/C][C]-82472.8212609495[/C][C]1198.01549146159[/C][C]6.22882984823297[/C][C]6.22882984822569[/C][C]-1.01771019548593[/C][/ROW]
[ROW][C]53[/C][C]-35154.7184801844[/C][C]-779.129454254367[/C][C]-30.5003141436965[/C][C]-30.5003141437091[/C][C]-0.417463225964831[/C][/ROW]
[ROW][C]54[/C][C]-46946.870011609[/C][C]-3275.44489119386[/C][C]-75.3333163763473[/C][C]-75.333316376336[/C][C]-0.529601187669513[/C][/ROW]
[ROW][C]55[/C][C]-43641.5364941684[/C][C]-5460.69990868224[/C][C]-113.010489610491[/C][C]-113.010489610475[/C][C]-0.462187646004049[/C][/ROW]
[ROW][C]56[/C][C]-54920.7084991732[/C][C]-8108.87273695363[/C][C]-157.4870218677[/C][C]-157.487021867688[/C][C]-0.566136994558455[/C][/ROW]
[ROW][C]57[/C][C]54905.4038222157[/C][C]-5064.57656837232[/C][C]-102.283863411682[/C][C]-102.283863411682[/C][C]0.728588209068161[/C][/ROW]
[ROW][C]58[/C][C]-10509.5840707596[/C][C]-5427.09970764403[/C][C]-106.69469859575[/C][C]-106.694698595748[/C][C]-0.0603195145012887[/C][/ROW]
[ROW][C]59[/C][C]-13706.8046976985[/C][C]-5927.39911827395[/C][C]-113.254777129653[/C][C]-113.254777129653[/C][C]-0.0928900608170904[/C][/ROW]
[ROW][C]60[/C][C]-42347.6087628011[/C][C]-7776.66624250811[/C][C]-141.713995934645[/C][C]-141.713995934641[/C][C]-0.416987561775341[/C][/ROW]
[ROW][C]61[/C][C]-28990.4687708701[/C][C]-8796.93347975583[/C][C]-155.884209504211[/C][C]1714.72630184939[/C][C]-0.263025734938178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=193666&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=193666&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
1867.887509505211867.887509505211000
2-2250.28069676838482.135137691015-128.584123938065-128.584124082563-0.0336588434170022
333618.35704129595827.87280138251239.996322969321239.996322969320.351730048858743
49954.344682388367380.491566960431302.520811491041302.520811491050.0170903372715027
5354.1917308423556728.8280946165976.823430851881976.823430851879-0.0993969702204615
618882.4064004639813.38566221591277.92830753011277.92830753010.105303005820063
720229.431091567212699.07940890711478.898987425231478.898987425230.0814684163085219
8268402.41615118764503.40644820697070.61321541137070.613215411322.63468433830274
9-113346.92605586234717.00777195343384.912026244823384.91202624481-2.01426689415987
10-45016.39422793922176.64189911861937.159489964851937.15948996485-0.913467306676191
1135069.86136725425701.77917473312069.490972102322069.490972102320.0958383396219359
1258531.095729009132597.18550602172440.715230501262440.715230501260.306677427551755
13-77256.377119879131748.48835608012205.75720332678-24263.3292415882-1.00516658066521
14-31473.59456895521903.71685895361402.388623296561402.38862401665-0.719008512428302
15-52391.007513288210487.607215225601.232481607484601.232481607483-0.826393105169983
1632854.984756966114393.1575132824795.604117869243795.6041178692450.228414178405465
17101107.73284539727731.71307402471492.434753584411492.434753584420.924021815061962
18-176275.960398033316.700765591786-29.0098286270242-29.0098286270187-2.25824451512009
1979531.88441510210817.3381036684497.47252970816497.4725297081580.868665773764188
20-176414.251561376-12536.1648656564-638.288208341031-638.288208341026-2.07060096354289
21151290.5794625896835.67346633311271.26299803763271.2629980376321.82254753694878
22167731.59416344325737.76618888371081.299073016451081.299073016461.77564787964596
23143237.12243469139691.47106157111617.649314669411617.649314669421.28077720379748
2480251.966526557745317.94019519031778.00210742741778.00210742740.415551869814646
25118735.72627362352762.20711502771995.93536944317-21955.28905542561.05779316057466
2675035.825903749456715.51415077592068.430616343362068.430609284130.203612127549494
2719198.308543734654503.62309560981915.561985218021915.56198521802-0.465119948473153
28-36364.563927631447058.99425671771592.796784386641592.79678438663-1.05990664119725
29-36170.578744090540420.08930073411318.40672637431318.4067263743-0.969241436163834
30-109567.39506415527702.7769171124865.641593793778865.64159379379-1.71517306419433
31-100783.33609785716989.6403668657503.804776792514503.804776792519-1.46597719861144
32-149267.4039313693092.6670443737767.41756166268367.4175616626907-1.88615204328821
3338947.35105831496141.54072467201155.107447504905155.1074475049010.403407564198154
3458613.060099463510522.4080400068275.843443728617275.8434437286190.589927166576592
3516074.460204440711191.8507338121286.776756230746286.7767562307480.0566273104233811
36-41563.00491506597396.0976591097176.438112151472176.438112151475-0.604672401901499
37-15970.59647779596411.81448088498145.892815036309-1604.8209666728-0.250259560008362
38-47563.95484208022466.9904409892541.002639268820841.0026361663814-0.615758384449737
3959595.35771799226689.08144556856145.529848401583145.5298484015840.648055805604832
4065897.840539044811037.4397091987248.037858529108248.0378585291040.670056365754829
41-166489.283203891-1085.49373156325-46.5090771682974-46.5090771683089-2.02671385233897
4246312.32698846322085.6396919200528.31981819569328.3198181957030.541191538800866
43-15952.8722863516917.685717854961.131777462493521.13177746250445-0.206396993693554
44-87780.6523566012-4807.19275866092-126.112894848137-126.112894848127-1.01261777883752
45134744.1727377773885.2315743451365.594436192171565.5944361921711.59733112229586
4675232.81224082898343.07783402122159.046602649276159.0466026492790.814321210688312
4724408.75584715149452.3122092113178.842181243876178.8421812438790.180198808957868
48-15406.14033819558141.77311559246148.446645022188148.44664502219-0.288750709949241
49-3766.753487673647817.51174780277138.992484765951-1528.91732977798-0.120937216469998
5027197.22399510069064.86832035272160.725113938186160.7251128744880.218863341042955
51-46777.28900315036035.031903699499.368161426810899.368161426814-0.643941291192813
52-82472.82126094951198.015491461596.228829848232976.22882984822569-1.01771019548593
53-35154.7184801844-779.129454254367-30.5003141436965-30.5003141437091-0.417463225964831
54-46946.870011609-3275.44489119386-75.3333163763473-75.333316376336-0.529601187669513
55-43641.5364941684-5460.69990868224-113.010489610491-113.010489610475-0.462187646004049
56-54920.7084991732-8108.87273695363-157.4870218677-157.487021867688-0.566136994558455
5754905.4038222157-5064.57656837232-102.283863411682-102.2838634116820.728588209068161
58-10509.5840707596-5427.09970764403-106.69469859575-106.694698595748-0.0603195145012887
59-13706.8046976985-5927.39911827395-113.254777129653-113.254777129653-0.0928900608170904
60-42347.6087628011-7776.66624250811-141.713995934645-141.713995934641-0.416987561775341
61-28990.4687708701-8796.93347975583-155.8842095042111714.72630184939-0.263025734938178



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')