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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 computationWed, 08 Dec 2010 15:45:34 +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/08/t12918247105ulu57gexvf37ma.htm/, Retrieved Fri, 03 May 2024 03:56:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106980, Retrieved Fri, 03 May 2024 03:56:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
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Dataseries X:
186448
190530
194207
190855
200779
204428
207617
212071
214239
215883
223484
221529
225247
226699
231406
232324
237192
236727
240698
240688
245283
243556
247826
245798
250479
249216
251896
247616
249994
246552
248771
247551
249745
245742
249019
245841
248771
244723
246878
246014
248496
244351
248016
246509
249426
247840
251035
250161
254278
250801
253985
249174
251287
247947
249992
243805
255812
250417
253033
248705
253950
251484
251093
245996
252721
248019
250464
245571
252690
250183
253639
254436
265280
268705
270643
271480




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106980&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106980&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106980&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1186448186448000
2190530189443.2064788391029.33220419497890.0207857548050.78251421709684
3194207192177.6124648631813.076906997381363.11206947771.19727220457306
4190855191178.419501414367.997511965863726.732141889124-1.83451990864378
5200779198822.7049438963969.89691894923-55.64647017103784.36671979599958
6204428203897.8163569824508.1880655856175.6771377132010.675983271386587
7207617207341.3452192003983.15050013976632.88765731804-0.6728272749546
8212071212275.9340280504455.45675943443-520.6443521822080.591445455685734
9214239215377.1000183623803.47772783333-719.381390605238-0.837915511501245
10215883216768.7592257602621.69110652560-135.938302770319-1.45949284190488
11223484221608.5133916473705.80559190981168.663806567371.37130233416204
12221529223102.8149105692619.75285702308-864.77164899968-1.36439297924419
13225247225552.5729903652537.20477824852-252.541586212481-0.104653900094717
14226699227521.9373555482259.83846030852-645.369317087628-0.346615296785494
15231406229793.5942814742265.600412191411608.686883953170.00726734027529162
16232324232753.3878692562604.87643280511-648.5057198897760.426438434304928
17237192236619.7951583463218.62545272556178.3111815392680.774292654880965
18236727238311.6553647332473.9431491454-1106.97632942550-0.934477533450907
19240698239785.8745943821986.876142100771225.24823405856-0.613374915908075
20240688241610.5671889441907.76975114746-871.686006225396-0.0994716354603897
21245283244306.8943574682291.68662417526729.785055856760.483466684295873
22243556245259.7379136891639.14749308027-1285.03503799079-0.820104953725054
23247826246673.1157433891529.173844123591223.48490616425-0.138401057719906
24245798247302.3684370611090.58816800139-1222.71708360598-0.551613512587953
25250479249058.3532863011414.632833245101212.762220695870.407789110503336
26249216250462.9258003471409.73123856884-1243.78079086457-0.00616378383910533
27251896251009.246105002989.1784361211061156.60862949153-0.52911761446074
28247616250057.03427756443.3384024854603-1834.01172556649-1.18970800536626
29249994249202.121333231-394.1528392946721072.53393932131-0.550412172644179
30246552248002.276334087-786.640652953867-1198.46315895828-0.493658961900905
31248771247188.620236879-799.7993291111931590.82184838269-0.0165537198694503
32247551248161.92643514863.9342269878309-1165.116440079021.08647689789481
33249745248447.646702927171.9592869658261228.054517065070.135894324816302
34245742247586.468276386-331.291863425981-1521.60846938944-0.633021914959784
35249019247569.499834552-178.1910368431341351.282162489050.192593573910546
36245841247164.304510909-288.765448731972-1252.36481291801-0.139092154373678
37248771247168.396470154-146.1212565688311511.096331035720.179438389264937
38244723246571.440245203-365.720480239398-1707.56106426357-0.276233733695153
39246878245740.858205996-592.1460108763031282.39685633466-0.284827692172930
40246014246510.94874124271.3875458672191-922.6248127643080.834667887752284
41248496246803.954897304179.3337004533131622.796832302700.135788418324018
42244351246366.508090233-121.092671984742-1822.77901698428-0.377909849215498
43248016246717.387888836108.7967914997521151.135673449210.289183194615556
44246509247238.546209631309.652534835092-858.398719498760.252659775382279
45249426247649.624733798359.0553221955661744.682971119430.0621448194348233
46247840249127.567820517904.04897681852-1637.188625541510.685556226531153
47251035250017.681803927897.2614819336031021.67243713773-0.00853812376006289
48250161251013.288851379945.1640859416-883.0189866413960.0602575310043426
49254278252466.9847731631192.861150244981652.115408155450.311582885806666
50250801252896.363794556820.98122842145-1856.79866604542-0.467794233086307
51253985253242.64776461589.764290766845890.680008172866-0.290852093051691
52249174251477.009877241-557.51372822705-1567.01867943003-1.44318164656761
53251287249945.056688277-1032.146570738331646.42452347952-0.597049396448244
54247947249354.437514557-817.085868900304-1545.401125769650.270528704125709
55249992248589.953246446-791.4645215351741385.610425671760.0322295602262429
56243805246144.332072334-1597.17669878153-1822.45975495488-1.01351990485014
57255812250668.8927945721384.617788731043230.25898822483.75085346636858
58250417252114.6327303531414.38936376873-1716.731481538320.0374502009720471
59253033252233.897197885783.5559439985211203.78821063228-0.793536784997278
60248705252184.276552414377.729613412756-3218.93510955375-0.510496279468551
61253950251358.965626028-208.2510808320992966.94634505119-0.737115715825917
62251484252245.104472423324.80784031473-1103.066769072550.670544446038215
63251093250767.632863407-553.052013473135888.522283546821-1.10427577596664
64245996249405.437847183-947.171938567868-3156.60623958339-0.495770578870859
65252721249368.963667711-503.5864520880633067.472173956860.557994197731928
66248019248806.785549731-532.125464540649-769.477508439316-0.0358997394529611
67250464249012.097698266-172.9320629439111221.476435139470.451835867931494
68245571248899.736682055-143.42892803819-3347.663216151640.0371125265973846
69252690249312.794423238127.6263269359523203.321140236520.340965300935715
70250183250507.159023587647.216534960947-657.4809405097970.65360191076776
71253639251997.8561694531058.061692053991377.582885051490.516809543397047
72254436256164.3295357062572.11654074478-2699.609687537251.90455695061375
73265280261077.4325228393712.371495257873471.08343883721.43434730158373
74268705267906.3829715115230.40447943665-175.2151211304861.90956111585694
75270643271186.9145721184280.6543354536565.3588808731411-1.19470785988385
76271480274956.4023758524031.67374985382-3316.67903674716-0.31319717664437

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 186448 & 186448 & 0 & 0 & 0 \tabularnewline
2 & 190530 & 189443.206478839 & 1029.33220419497 & 890.020785754805 & 0.78251421709684 \tabularnewline
3 & 194207 & 192177.612464863 & 1813.07690699738 & 1363.1120694777 & 1.19727220457306 \tabularnewline
4 & 190855 & 191178.419501414 & 367.997511965863 & 726.732141889124 & -1.83451990864378 \tabularnewline
5 & 200779 & 198822.704943896 & 3969.89691894923 & -55.6464701710378 & 4.36671979599958 \tabularnewline
6 & 204428 & 203897.816356982 & 4508.1880655856 & 175.677137713201 & 0.675983271386587 \tabularnewline
7 & 207617 & 207341.345219200 & 3983.15050013976 & 632.88765731804 & -0.6728272749546 \tabularnewline
8 & 212071 & 212275.934028050 & 4455.45675943443 & -520.644352182208 & 0.591445455685734 \tabularnewline
9 & 214239 & 215377.100018362 & 3803.47772783333 & -719.381390605238 & -0.837915511501245 \tabularnewline
10 & 215883 & 216768.759225760 & 2621.69110652560 & -135.938302770319 & -1.45949284190488 \tabularnewline
11 & 223484 & 221608.513391647 & 3705.8055919098 & 1168.66380656737 & 1.37130233416204 \tabularnewline
12 & 221529 & 223102.814910569 & 2619.75285702308 & -864.77164899968 & -1.36439297924419 \tabularnewline
13 & 225247 & 225552.572990365 & 2537.20477824852 & -252.541586212481 & -0.104653900094717 \tabularnewline
14 & 226699 & 227521.937355548 & 2259.83846030852 & -645.369317087628 & -0.346615296785494 \tabularnewline
15 & 231406 & 229793.594281474 & 2265.60041219141 & 1608.68688395317 & 0.00726734027529162 \tabularnewline
16 & 232324 & 232753.387869256 & 2604.87643280511 & -648.505719889776 & 0.426438434304928 \tabularnewline
17 & 237192 & 236619.795158346 & 3218.62545272556 & 178.311181539268 & 0.774292654880965 \tabularnewline
18 & 236727 & 238311.655364733 & 2473.9431491454 & -1106.97632942550 & -0.934477533450907 \tabularnewline
19 & 240698 & 239785.874594382 & 1986.87614210077 & 1225.24823405856 & -0.613374915908075 \tabularnewline
20 & 240688 & 241610.567188944 & 1907.76975114746 & -871.686006225396 & -0.0994716354603897 \tabularnewline
21 & 245283 & 244306.894357468 & 2291.68662417526 & 729.78505585676 & 0.483466684295873 \tabularnewline
22 & 243556 & 245259.737913689 & 1639.14749308027 & -1285.03503799079 & -0.820104953725054 \tabularnewline
23 & 247826 & 246673.115743389 & 1529.17384412359 & 1223.48490616425 & -0.138401057719906 \tabularnewline
24 & 245798 & 247302.368437061 & 1090.58816800139 & -1222.71708360598 & -0.551613512587953 \tabularnewline
25 & 250479 & 249058.353286301 & 1414.63283324510 & 1212.76222069587 & 0.407789110503336 \tabularnewline
26 & 249216 & 250462.925800347 & 1409.73123856884 & -1243.78079086457 & -0.00616378383910533 \tabularnewline
27 & 251896 & 251009.246105002 & 989.178436121106 & 1156.60862949153 & -0.52911761446074 \tabularnewline
28 & 247616 & 250057.034277564 & 43.3384024854603 & -1834.01172556649 & -1.18970800536626 \tabularnewline
29 & 249994 & 249202.121333231 & -394.152839294672 & 1072.53393932131 & -0.550412172644179 \tabularnewline
30 & 246552 & 248002.276334087 & -786.640652953867 & -1198.46315895828 & -0.493658961900905 \tabularnewline
31 & 248771 & 247188.620236879 & -799.799329111193 & 1590.82184838269 & -0.0165537198694503 \tabularnewline
32 & 247551 & 248161.926435148 & 63.9342269878309 & -1165.11644007902 & 1.08647689789481 \tabularnewline
33 & 249745 & 248447.646702927 & 171.959286965826 & 1228.05451706507 & 0.135894324816302 \tabularnewline
34 & 245742 & 247586.468276386 & -331.291863425981 & -1521.60846938944 & -0.633021914959784 \tabularnewline
35 & 249019 & 247569.499834552 & -178.191036843134 & 1351.28216248905 & 0.192593573910546 \tabularnewline
36 & 245841 & 247164.304510909 & -288.765448731972 & -1252.36481291801 & -0.139092154373678 \tabularnewline
37 & 248771 & 247168.396470154 & -146.121256568831 & 1511.09633103572 & 0.179438389264937 \tabularnewline
38 & 244723 & 246571.440245203 & -365.720480239398 & -1707.56106426357 & -0.276233733695153 \tabularnewline
39 & 246878 & 245740.858205996 & -592.146010876303 & 1282.39685633466 & -0.284827692172930 \tabularnewline
40 & 246014 & 246510.948741242 & 71.3875458672191 & -922.624812764308 & 0.834667887752284 \tabularnewline
41 & 248496 & 246803.954897304 & 179.333700453313 & 1622.79683230270 & 0.135788418324018 \tabularnewline
42 & 244351 & 246366.508090233 & -121.092671984742 & -1822.77901698428 & -0.377909849215498 \tabularnewline
43 & 248016 & 246717.387888836 & 108.796791499752 & 1151.13567344921 & 0.289183194615556 \tabularnewline
44 & 246509 & 247238.546209631 & 309.652534835092 & -858.39871949876 & 0.252659775382279 \tabularnewline
45 & 249426 & 247649.624733798 & 359.055322195566 & 1744.68297111943 & 0.0621448194348233 \tabularnewline
46 & 247840 & 249127.567820517 & 904.04897681852 & -1637.18862554151 & 0.685556226531153 \tabularnewline
47 & 251035 & 250017.681803927 & 897.261481933603 & 1021.67243713773 & -0.00853812376006289 \tabularnewline
48 & 250161 & 251013.288851379 & 945.1640859416 & -883.018986641396 & 0.0602575310043426 \tabularnewline
49 & 254278 & 252466.984773163 & 1192.86115024498 & 1652.11540815545 & 0.311582885806666 \tabularnewline
50 & 250801 & 252896.363794556 & 820.98122842145 & -1856.79866604542 & -0.467794233086307 \tabularnewline
51 & 253985 & 253242.64776461 & 589.764290766845 & 890.680008172866 & -0.290852093051691 \tabularnewline
52 & 249174 & 251477.009877241 & -557.51372822705 & -1567.01867943003 & -1.44318164656761 \tabularnewline
53 & 251287 & 249945.056688277 & -1032.14657073833 & 1646.42452347952 & -0.597049396448244 \tabularnewline
54 & 247947 & 249354.437514557 & -817.085868900304 & -1545.40112576965 & 0.270528704125709 \tabularnewline
55 & 249992 & 248589.953246446 & -791.464521535174 & 1385.61042567176 & 0.0322295602262429 \tabularnewline
56 & 243805 & 246144.332072334 & -1597.17669878153 & -1822.45975495488 & -1.01351990485014 \tabularnewline
57 & 255812 & 250668.892794572 & 1384.61778873104 & 3230.2589882248 & 3.75085346636858 \tabularnewline
58 & 250417 & 252114.632730353 & 1414.38936376873 & -1716.73148153832 & 0.0374502009720471 \tabularnewline
59 & 253033 & 252233.897197885 & 783.555943998521 & 1203.78821063228 & -0.793536784997278 \tabularnewline
60 & 248705 & 252184.276552414 & 377.729613412756 & -3218.93510955375 & -0.510496279468551 \tabularnewline
61 & 253950 & 251358.965626028 & -208.251080832099 & 2966.94634505119 & -0.737115715825917 \tabularnewline
62 & 251484 & 252245.104472423 & 324.80784031473 & -1103.06676907255 & 0.670544446038215 \tabularnewline
63 & 251093 & 250767.632863407 & -553.052013473135 & 888.522283546821 & -1.10427577596664 \tabularnewline
64 & 245996 & 249405.437847183 & -947.171938567868 & -3156.60623958339 & -0.495770578870859 \tabularnewline
65 & 252721 & 249368.963667711 & -503.586452088063 & 3067.47217395686 & 0.557994197731928 \tabularnewline
66 & 248019 & 248806.785549731 & -532.125464540649 & -769.477508439316 & -0.0358997394529611 \tabularnewline
67 & 250464 & 249012.097698266 & -172.932062943911 & 1221.47643513947 & 0.451835867931494 \tabularnewline
68 & 245571 & 248899.736682055 & -143.42892803819 & -3347.66321615164 & 0.0371125265973846 \tabularnewline
69 & 252690 & 249312.794423238 & 127.626326935952 & 3203.32114023652 & 0.340965300935715 \tabularnewline
70 & 250183 & 250507.159023587 & 647.216534960947 & -657.480940509797 & 0.65360191076776 \tabularnewline
71 & 253639 & 251997.856169453 & 1058.06169205399 & 1377.58288505149 & 0.516809543397047 \tabularnewline
72 & 254436 & 256164.329535706 & 2572.11654074478 & -2699.60968753725 & 1.90455695061375 \tabularnewline
73 & 265280 & 261077.432522839 & 3712.37149525787 & 3471.0834388372 & 1.43434730158373 \tabularnewline
74 & 268705 & 267906.382971511 & 5230.40447943665 & -175.215121130486 & 1.90956111585694 \tabularnewline
75 & 270643 & 271186.914572118 & 4280.65433545365 & 65.3588808731411 & -1.19470785988385 \tabularnewline
76 & 271480 & 274956.402375852 & 4031.67374985382 & -3316.67903674716 & -0.31319717664437 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106980&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]186448[/C][C]186448[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]190530[/C][C]189443.206478839[/C][C]1029.33220419497[/C][C]890.020785754805[/C][C]0.78251421709684[/C][/ROW]
[ROW][C]3[/C][C]194207[/C][C]192177.612464863[/C][C]1813.07690699738[/C][C]1363.1120694777[/C][C]1.19727220457306[/C][/ROW]
[ROW][C]4[/C][C]190855[/C][C]191178.419501414[/C][C]367.997511965863[/C][C]726.732141889124[/C][C]-1.83451990864378[/C][/ROW]
[ROW][C]5[/C][C]200779[/C][C]198822.704943896[/C][C]3969.89691894923[/C][C]-55.6464701710378[/C][C]4.36671979599958[/C][/ROW]
[ROW][C]6[/C][C]204428[/C][C]203897.816356982[/C][C]4508.1880655856[/C][C]175.677137713201[/C][C]0.675983271386587[/C][/ROW]
[ROW][C]7[/C][C]207617[/C][C]207341.345219200[/C][C]3983.15050013976[/C][C]632.88765731804[/C][C]-0.6728272749546[/C][/ROW]
[ROW][C]8[/C][C]212071[/C][C]212275.934028050[/C][C]4455.45675943443[/C][C]-520.644352182208[/C][C]0.591445455685734[/C][/ROW]
[ROW][C]9[/C][C]214239[/C][C]215377.100018362[/C][C]3803.47772783333[/C][C]-719.381390605238[/C][C]-0.837915511501245[/C][/ROW]
[ROW][C]10[/C][C]215883[/C][C]216768.759225760[/C][C]2621.69110652560[/C][C]-135.938302770319[/C][C]-1.45949284190488[/C][/ROW]
[ROW][C]11[/C][C]223484[/C][C]221608.513391647[/C][C]3705.8055919098[/C][C]1168.66380656737[/C][C]1.37130233416204[/C][/ROW]
[ROW][C]12[/C][C]221529[/C][C]223102.814910569[/C][C]2619.75285702308[/C][C]-864.77164899968[/C][C]-1.36439297924419[/C][/ROW]
[ROW][C]13[/C][C]225247[/C][C]225552.572990365[/C][C]2537.20477824852[/C][C]-252.541586212481[/C][C]-0.104653900094717[/C][/ROW]
[ROW][C]14[/C][C]226699[/C][C]227521.937355548[/C][C]2259.83846030852[/C][C]-645.369317087628[/C][C]-0.346615296785494[/C][/ROW]
[ROW][C]15[/C][C]231406[/C][C]229793.594281474[/C][C]2265.60041219141[/C][C]1608.68688395317[/C][C]0.00726734027529162[/C][/ROW]
[ROW][C]16[/C][C]232324[/C][C]232753.387869256[/C][C]2604.87643280511[/C][C]-648.505719889776[/C][C]0.426438434304928[/C][/ROW]
[ROW][C]17[/C][C]237192[/C][C]236619.795158346[/C][C]3218.62545272556[/C][C]178.311181539268[/C][C]0.774292654880965[/C][/ROW]
[ROW][C]18[/C][C]236727[/C][C]238311.655364733[/C][C]2473.9431491454[/C][C]-1106.97632942550[/C][C]-0.934477533450907[/C][/ROW]
[ROW][C]19[/C][C]240698[/C][C]239785.874594382[/C][C]1986.87614210077[/C][C]1225.24823405856[/C][C]-0.613374915908075[/C][/ROW]
[ROW][C]20[/C][C]240688[/C][C]241610.567188944[/C][C]1907.76975114746[/C][C]-871.686006225396[/C][C]-0.0994716354603897[/C][/ROW]
[ROW][C]21[/C][C]245283[/C][C]244306.894357468[/C][C]2291.68662417526[/C][C]729.78505585676[/C][C]0.483466684295873[/C][/ROW]
[ROW][C]22[/C][C]243556[/C][C]245259.737913689[/C][C]1639.14749308027[/C][C]-1285.03503799079[/C][C]-0.820104953725054[/C][/ROW]
[ROW][C]23[/C][C]247826[/C][C]246673.115743389[/C][C]1529.17384412359[/C][C]1223.48490616425[/C][C]-0.138401057719906[/C][/ROW]
[ROW][C]24[/C][C]245798[/C][C]247302.368437061[/C][C]1090.58816800139[/C][C]-1222.71708360598[/C][C]-0.551613512587953[/C][/ROW]
[ROW][C]25[/C][C]250479[/C][C]249058.353286301[/C][C]1414.63283324510[/C][C]1212.76222069587[/C][C]0.407789110503336[/C][/ROW]
[ROW][C]26[/C][C]249216[/C][C]250462.925800347[/C][C]1409.73123856884[/C][C]-1243.78079086457[/C][C]-0.00616378383910533[/C][/ROW]
[ROW][C]27[/C][C]251896[/C][C]251009.246105002[/C][C]989.178436121106[/C][C]1156.60862949153[/C][C]-0.52911761446074[/C][/ROW]
[ROW][C]28[/C][C]247616[/C][C]250057.034277564[/C][C]43.3384024854603[/C][C]-1834.01172556649[/C][C]-1.18970800536626[/C][/ROW]
[ROW][C]29[/C][C]249994[/C][C]249202.121333231[/C][C]-394.152839294672[/C][C]1072.53393932131[/C][C]-0.550412172644179[/C][/ROW]
[ROW][C]30[/C][C]246552[/C][C]248002.276334087[/C][C]-786.640652953867[/C][C]-1198.46315895828[/C][C]-0.493658961900905[/C][/ROW]
[ROW][C]31[/C][C]248771[/C][C]247188.620236879[/C][C]-799.799329111193[/C][C]1590.82184838269[/C][C]-0.0165537198694503[/C][/ROW]
[ROW][C]32[/C][C]247551[/C][C]248161.926435148[/C][C]63.9342269878309[/C][C]-1165.11644007902[/C][C]1.08647689789481[/C][/ROW]
[ROW][C]33[/C][C]249745[/C][C]248447.646702927[/C][C]171.959286965826[/C][C]1228.05451706507[/C][C]0.135894324816302[/C][/ROW]
[ROW][C]34[/C][C]245742[/C][C]247586.468276386[/C][C]-331.291863425981[/C][C]-1521.60846938944[/C][C]-0.633021914959784[/C][/ROW]
[ROW][C]35[/C][C]249019[/C][C]247569.499834552[/C][C]-178.191036843134[/C][C]1351.28216248905[/C][C]0.192593573910546[/C][/ROW]
[ROW][C]36[/C][C]245841[/C][C]247164.304510909[/C][C]-288.765448731972[/C][C]-1252.36481291801[/C][C]-0.139092154373678[/C][/ROW]
[ROW][C]37[/C][C]248771[/C][C]247168.396470154[/C][C]-146.121256568831[/C][C]1511.09633103572[/C][C]0.179438389264937[/C][/ROW]
[ROW][C]38[/C][C]244723[/C][C]246571.440245203[/C][C]-365.720480239398[/C][C]-1707.56106426357[/C][C]-0.276233733695153[/C][/ROW]
[ROW][C]39[/C][C]246878[/C][C]245740.858205996[/C][C]-592.146010876303[/C][C]1282.39685633466[/C][C]-0.284827692172930[/C][/ROW]
[ROW][C]40[/C][C]246014[/C][C]246510.948741242[/C][C]71.3875458672191[/C][C]-922.624812764308[/C][C]0.834667887752284[/C][/ROW]
[ROW][C]41[/C][C]248496[/C][C]246803.954897304[/C][C]179.333700453313[/C][C]1622.79683230270[/C][C]0.135788418324018[/C][/ROW]
[ROW][C]42[/C][C]244351[/C][C]246366.508090233[/C][C]-121.092671984742[/C][C]-1822.77901698428[/C][C]-0.377909849215498[/C][/ROW]
[ROW][C]43[/C][C]248016[/C][C]246717.387888836[/C][C]108.796791499752[/C][C]1151.13567344921[/C][C]0.289183194615556[/C][/ROW]
[ROW][C]44[/C][C]246509[/C][C]247238.546209631[/C][C]309.652534835092[/C][C]-858.39871949876[/C][C]0.252659775382279[/C][/ROW]
[ROW][C]45[/C][C]249426[/C][C]247649.624733798[/C][C]359.055322195566[/C][C]1744.68297111943[/C][C]0.0621448194348233[/C][/ROW]
[ROW][C]46[/C][C]247840[/C][C]249127.567820517[/C][C]904.04897681852[/C][C]-1637.18862554151[/C][C]0.685556226531153[/C][/ROW]
[ROW][C]47[/C][C]251035[/C][C]250017.681803927[/C][C]897.261481933603[/C][C]1021.67243713773[/C][C]-0.00853812376006289[/C][/ROW]
[ROW][C]48[/C][C]250161[/C][C]251013.288851379[/C][C]945.1640859416[/C][C]-883.018986641396[/C][C]0.0602575310043426[/C][/ROW]
[ROW][C]49[/C][C]254278[/C][C]252466.984773163[/C][C]1192.86115024498[/C][C]1652.11540815545[/C][C]0.311582885806666[/C][/ROW]
[ROW][C]50[/C][C]250801[/C][C]252896.363794556[/C][C]820.98122842145[/C][C]-1856.79866604542[/C][C]-0.467794233086307[/C][/ROW]
[ROW][C]51[/C][C]253985[/C][C]253242.64776461[/C][C]589.764290766845[/C][C]890.680008172866[/C][C]-0.290852093051691[/C][/ROW]
[ROW][C]52[/C][C]249174[/C][C]251477.009877241[/C][C]-557.51372822705[/C][C]-1567.01867943003[/C][C]-1.44318164656761[/C][/ROW]
[ROW][C]53[/C][C]251287[/C][C]249945.056688277[/C][C]-1032.14657073833[/C][C]1646.42452347952[/C][C]-0.597049396448244[/C][/ROW]
[ROW][C]54[/C][C]247947[/C][C]249354.437514557[/C][C]-817.085868900304[/C][C]-1545.40112576965[/C][C]0.270528704125709[/C][/ROW]
[ROW][C]55[/C][C]249992[/C][C]248589.953246446[/C][C]-791.464521535174[/C][C]1385.61042567176[/C][C]0.0322295602262429[/C][/ROW]
[ROW][C]56[/C][C]243805[/C][C]246144.332072334[/C][C]-1597.17669878153[/C][C]-1822.45975495488[/C][C]-1.01351990485014[/C][/ROW]
[ROW][C]57[/C][C]255812[/C][C]250668.892794572[/C][C]1384.61778873104[/C][C]3230.2589882248[/C][C]3.75085346636858[/C][/ROW]
[ROW][C]58[/C][C]250417[/C][C]252114.632730353[/C][C]1414.38936376873[/C][C]-1716.73148153832[/C][C]0.0374502009720471[/C][/ROW]
[ROW][C]59[/C][C]253033[/C][C]252233.897197885[/C][C]783.555943998521[/C][C]1203.78821063228[/C][C]-0.793536784997278[/C][/ROW]
[ROW][C]60[/C][C]248705[/C][C]252184.276552414[/C][C]377.729613412756[/C][C]-3218.93510955375[/C][C]-0.510496279468551[/C][/ROW]
[ROW][C]61[/C][C]253950[/C][C]251358.965626028[/C][C]-208.251080832099[/C][C]2966.94634505119[/C][C]-0.737115715825917[/C][/ROW]
[ROW][C]62[/C][C]251484[/C][C]252245.104472423[/C][C]324.80784031473[/C][C]-1103.06676907255[/C][C]0.670544446038215[/C][/ROW]
[ROW][C]63[/C][C]251093[/C][C]250767.632863407[/C][C]-553.052013473135[/C][C]888.522283546821[/C][C]-1.10427577596664[/C][/ROW]
[ROW][C]64[/C][C]245996[/C][C]249405.437847183[/C][C]-947.171938567868[/C][C]-3156.60623958339[/C][C]-0.495770578870859[/C][/ROW]
[ROW][C]65[/C][C]252721[/C][C]249368.963667711[/C][C]-503.586452088063[/C][C]3067.47217395686[/C][C]0.557994197731928[/C][/ROW]
[ROW][C]66[/C][C]248019[/C][C]248806.785549731[/C][C]-532.125464540649[/C][C]-769.477508439316[/C][C]-0.0358997394529611[/C][/ROW]
[ROW][C]67[/C][C]250464[/C][C]249012.097698266[/C][C]-172.932062943911[/C][C]1221.47643513947[/C][C]0.451835867931494[/C][/ROW]
[ROW][C]68[/C][C]245571[/C][C]248899.736682055[/C][C]-143.42892803819[/C][C]-3347.66321615164[/C][C]0.0371125265973846[/C][/ROW]
[ROW][C]69[/C][C]252690[/C][C]249312.794423238[/C][C]127.626326935952[/C][C]3203.32114023652[/C][C]0.340965300935715[/C][/ROW]
[ROW][C]70[/C][C]250183[/C][C]250507.159023587[/C][C]647.216534960947[/C][C]-657.480940509797[/C][C]0.65360191076776[/C][/ROW]
[ROW][C]71[/C][C]253639[/C][C]251997.856169453[/C][C]1058.06169205399[/C][C]1377.58288505149[/C][C]0.516809543397047[/C][/ROW]
[ROW][C]72[/C][C]254436[/C][C]256164.329535706[/C][C]2572.11654074478[/C][C]-2699.60968753725[/C][C]1.90455695061375[/C][/ROW]
[ROW][C]73[/C][C]265280[/C][C]261077.432522839[/C][C]3712.37149525787[/C][C]3471.0834388372[/C][C]1.43434730158373[/C][/ROW]
[ROW][C]74[/C][C]268705[/C][C]267906.382971511[/C][C]5230.40447943665[/C][C]-175.215121130486[/C][C]1.90956111585694[/C][/ROW]
[ROW][C]75[/C][C]270643[/C][C]271186.914572118[/C][C]4280.65433545365[/C][C]65.3588808731411[/C][C]-1.19470785988385[/C][/ROW]
[ROW][C]76[/C][C]271480[/C][C]274956.402375852[/C][C]4031.67374985382[/C][C]-3316.67903674716[/C][C]-0.31319717664437[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106980&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106980&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
1186448186448000
2190530189443.2064788391029.33220419497890.0207857548050.78251421709684
3194207192177.6124648631813.076906997381363.11206947771.19727220457306
4190855191178.419501414367.997511965863726.732141889124-1.83451990864378
5200779198822.7049438963969.89691894923-55.64647017103784.36671979599958
6204428203897.8163569824508.1880655856175.6771377132010.675983271386587
7207617207341.3452192003983.15050013976632.88765731804-0.6728272749546
8212071212275.9340280504455.45675943443-520.6443521822080.591445455685734
9214239215377.1000183623803.47772783333-719.381390605238-0.837915511501245
10215883216768.7592257602621.69110652560-135.938302770319-1.45949284190488
11223484221608.5133916473705.80559190981168.663806567371.37130233416204
12221529223102.8149105692619.75285702308-864.77164899968-1.36439297924419
13225247225552.5729903652537.20477824852-252.541586212481-0.104653900094717
14226699227521.9373555482259.83846030852-645.369317087628-0.346615296785494
15231406229793.5942814742265.600412191411608.686883953170.00726734027529162
16232324232753.3878692562604.87643280511-648.5057198897760.426438434304928
17237192236619.7951583463218.62545272556178.3111815392680.774292654880965
18236727238311.6553647332473.9431491454-1106.97632942550-0.934477533450907
19240698239785.8745943821986.876142100771225.24823405856-0.613374915908075
20240688241610.5671889441907.76975114746-871.686006225396-0.0994716354603897
21245283244306.8943574682291.68662417526729.785055856760.483466684295873
22243556245259.7379136891639.14749308027-1285.03503799079-0.820104953725054
23247826246673.1157433891529.173844123591223.48490616425-0.138401057719906
24245798247302.3684370611090.58816800139-1222.71708360598-0.551613512587953
25250479249058.3532863011414.632833245101212.762220695870.407789110503336
26249216250462.9258003471409.73123856884-1243.78079086457-0.00616378383910533
27251896251009.246105002989.1784361211061156.60862949153-0.52911761446074
28247616250057.03427756443.3384024854603-1834.01172556649-1.18970800536626
29249994249202.121333231-394.1528392946721072.53393932131-0.550412172644179
30246552248002.276334087-786.640652953867-1198.46315895828-0.493658961900905
31248771247188.620236879-799.7993291111931590.82184838269-0.0165537198694503
32247551248161.92643514863.9342269878309-1165.116440079021.08647689789481
33249745248447.646702927171.9592869658261228.054517065070.135894324816302
34245742247586.468276386-331.291863425981-1521.60846938944-0.633021914959784
35249019247569.499834552-178.1910368431341351.282162489050.192593573910546
36245841247164.304510909-288.765448731972-1252.36481291801-0.139092154373678
37248771247168.396470154-146.1212565688311511.096331035720.179438389264937
38244723246571.440245203-365.720480239398-1707.56106426357-0.276233733695153
39246878245740.858205996-592.1460108763031282.39685633466-0.284827692172930
40246014246510.94874124271.3875458672191-922.6248127643080.834667887752284
41248496246803.954897304179.3337004533131622.796832302700.135788418324018
42244351246366.508090233-121.092671984742-1822.77901698428-0.377909849215498
43248016246717.387888836108.7967914997521151.135673449210.289183194615556
44246509247238.546209631309.652534835092-858.398719498760.252659775382279
45249426247649.624733798359.0553221955661744.682971119430.0621448194348233
46247840249127.567820517904.04897681852-1637.188625541510.685556226531153
47251035250017.681803927897.2614819336031021.67243713773-0.00853812376006289
48250161251013.288851379945.1640859416-883.0189866413960.0602575310043426
49254278252466.9847731631192.861150244981652.115408155450.311582885806666
50250801252896.363794556820.98122842145-1856.79866604542-0.467794233086307
51253985253242.64776461589.764290766845890.680008172866-0.290852093051691
52249174251477.009877241-557.51372822705-1567.01867943003-1.44318164656761
53251287249945.056688277-1032.146570738331646.42452347952-0.597049396448244
54247947249354.437514557-817.085868900304-1545.401125769650.270528704125709
55249992248589.953246446-791.4645215351741385.610425671760.0322295602262429
56243805246144.332072334-1597.17669878153-1822.45975495488-1.01351990485014
57255812250668.8927945721384.617788731043230.25898822483.75085346636858
58250417252114.6327303531414.38936376873-1716.731481538320.0374502009720471
59253033252233.897197885783.5559439985211203.78821063228-0.793536784997278
60248705252184.276552414377.729613412756-3218.93510955375-0.510496279468551
61253950251358.965626028-208.2510808320992966.94634505119-0.737115715825917
62251484252245.104472423324.80784031473-1103.066769072550.670544446038215
63251093250767.632863407-553.052013473135888.522283546821-1.10427577596664
64245996249405.437847183-947.171938567868-3156.60623958339-0.495770578870859
65252721249368.963667711-503.5864520880633067.472173956860.557994197731928
66248019248806.785549731-532.125464540649-769.477508439316-0.0358997394529611
67250464249012.097698266-172.9320629439111221.476435139470.451835867931494
68245571248899.736682055-143.42892803819-3347.663216151640.0371125265973846
69252690249312.794423238127.6263269359523203.321140236520.340965300935715
70250183250507.159023587647.216534960947-657.4809405097970.65360191076776
71253639251997.8561694531058.061692053991377.582885051490.516809543397047
72254436256164.3295357062572.11654074478-2699.609687537251.90455695061375
73265280261077.4325228393712.371495257873471.08343883721.43434730158373
74268705267906.3829715115230.40447943665-175.2151211304861.90956111585694
75270643271186.9145721184280.6543354536565.3588808731411-1.19470785988385
76271480274956.4023758524031.67374985382-3316.67903674716-0.31319717664437



Parameters (Session):
par1 = multiplicative ; par2 = 4 ;
Parameters (R input):
par1 = 4 ;
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')