Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationTue, 28 Dec 2010 21:00:25 +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/28/t1293569883j9zj9zu9rlwtkn4.htm/, Retrieved Sun, 05 May 2024 07:52:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116550, Retrieved Sun, 05 May 2024 07:52:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Structural Time Series Models] [] [2010-12-24 11:19:06] [055a14fb8042f7ec27c73c5dfc3bfa50]
-    D    [Structural Time Series Models] [] [2010-12-28 21:00:25] [e8bffe463cbaa638f5c41694f8d1de39] [Current]
Feedback Forum

Post a new message
Dataseries X:
548604
563668
586111
604378
600991
544686
537034
551531
563250
574761
580112
575093
557560
564478
580523
596594
586570
536214
523597
536535
536322
532638
528222
516141
501866
506174
517945
533590
528379
477580
469357
490243
492622
507561
516922
514258
509846
527070
541657
564591
555362
498662
511038
525919
531673
548854
560576
557274
565742




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116550&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116550&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1548604548604000
2563668562016.947440278704.3455286454551651.052559722270.639639182814211
3586111580587.3701851851179.826513238995523.629814815531.32250295302630
4604378599693.4499050421327.170004504754684.550094957891.37853242285227
5600991601398.7338890131329.08392847948-407.7338890128370.0290542150589399
6544686556523.9876807291073.30169941725-11837.9876807288-3.54876999359405
7537034537049.222147274952.075417468482-15.2221472740840-1.57803770617811
8551531546147.113359071000.478874954435383.886640930470.625573455780406
9563250559557.272815741073.677341848063692.727184260240.953025681362728
10574761571790.0474261139.016559286202970.952573999940.856977807592458
11580112578528.6191844391171.601866579921583.380815561050.430020595573834
12575093575649.4319641691148.16509997577-556.431964169046-0.311078881348947
13557560571421.2971577011349.79472472095-13861.2971577006-0.471200136501134
14564478568188.4829153251283.03565245604-3710.48291532461-0.32323754592142
15580523576746.4516226861415.52973978163776.548377313810.533231188285758
16596594589423.7098811591520.440636003647170.290118840850.861826031391642
17586570581622.3794503721479.565658412864947.62054962772-0.715940513077779
18536214553065.4572339611377.66476117585-16851.4572339609-2.30570576608185
19523597530088.1128744851289.78744144588-6491.11287448514-1.86896203968085
20536535530412.3882944991286.061940858916122.61170550146-0.0740821968556601
21536322533617.2861861721293.815570365072704.713813828380.147239612346936
22532638532136.1223989021282.01949789657501.877601098182-0.213001426720579
23528222527642.9840289591260.65960189303579.015971040655-0.44324080235284
24516141518326.2664406721270.60730664961-2185.26644067168-0.811547659722004
25501866514950.1032257721325.25343203174-13084.1032257723-0.370839965838765
26506174513145.2695680851306.43455297191-6971.26956808448-0.233418623836777
27517945516861.073707661336.646018584461083.926292339950.178405386398126
28533590522681.8481197951377.6647406690210908.15188020550.341535753705118
29528379517987.6748276281346.8775245385910391.3251723717-0.466003285148121
30477580496454.696018571271.38380308250-18874.69601857-1.75634529924390
31469357480367.358159711218.61067102278-11010.3581597097-1.33207411105833
32490243482446.8494430231221.442512798947796.150556977270.0660522630845694
33492622487522.8479682931235.286116051625099.152031707460.295784921494092
34507561500922.0965361941278.324527071966638.903463805740.933572815125066
35516922511150.7341835751297.221094349755771.265816425090.686378408821981
36514258515156.2127083481292.52187393446-898.2127083475120.208071963458438
37509846520906.7565931351271.51687832713-11060.75659313490.346934361529854
38527070532181.7555314341307.98800886166-5111.755531433570.75607371720059
39541657540702.4992097961373.12762803159954.5007902039150.539284885910175
40564591549486.778808431433.8918016326915104.22119156960.563200775250767
41555362542173.0038574751386.6428849874413188.9961425245-0.670534840718818
42498662520851.2293134061305.85520934167-22189.2293134055-1.74299882216345
43511038520502.2012406611300.94174224817-9464.20124066087-0.127006889914247
44525919519501.2477261231293.943440327156417.75227387652-0.176646543200523
45531673526930.573053611313.483106144624742.426946389630.470848519105573
46548854540039.1385149521346.547949807138814.8614850480.904969652727832
47560576552145.3798737631359.868896910958430.6201262370.824863991198845
48557274558852.5380533091352.93998815335-1578.538053309250.410785419128755
49565742575097.1209182931324.98151124578-9355.120918292651.14821707539112

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 548604 & 548604 & 0 & 0 & 0 \tabularnewline
2 & 563668 & 562016.947440278 & 704.345528645455 & 1651.05255972227 & 0.639639182814211 \tabularnewline
3 & 586111 & 580587.370185185 & 1179.82651323899 & 5523.62981481553 & 1.32250295302630 \tabularnewline
4 & 604378 & 599693.449905042 & 1327.17000450475 & 4684.55009495789 & 1.37853242285227 \tabularnewline
5 & 600991 & 601398.733889013 & 1329.08392847948 & -407.733889012837 & 0.0290542150589399 \tabularnewline
6 & 544686 & 556523.987680729 & 1073.30169941725 & -11837.9876807288 & -3.54876999359405 \tabularnewline
7 & 537034 & 537049.222147274 & 952.075417468482 & -15.2221472740840 & -1.57803770617811 \tabularnewline
8 & 551531 & 546147.11335907 & 1000.47887495443 & 5383.88664093047 & 0.625573455780406 \tabularnewline
9 & 563250 & 559557.27281574 & 1073.67734184806 & 3692.72718426024 & 0.953025681362728 \tabularnewline
10 & 574761 & 571790.047426 & 1139.01655928620 & 2970.95257399994 & 0.856977807592458 \tabularnewline
11 & 580112 & 578528.619184439 & 1171.60186657992 & 1583.38081556105 & 0.430020595573834 \tabularnewline
12 & 575093 & 575649.431964169 & 1148.16509997577 & -556.431964169046 & -0.311078881348947 \tabularnewline
13 & 557560 & 571421.297157701 & 1349.79472472095 & -13861.2971577006 & -0.471200136501134 \tabularnewline
14 & 564478 & 568188.482915325 & 1283.03565245604 & -3710.48291532461 & -0.32323754592142 \tabularnewline
15 & 580523 & 576746.451622686 & 1415.5297397816 & 3776.54837731381 & 0.533231188285758 \tabularnewline
16 & 596594 & 589423.709881159 & 1520.44063600364 & 7170.29011884085 & 0.861826031391642 \tabularnewline
17 & 586570 & 581622.379450372 & 1479.56565841286 & 4947.62054962772 & -0.715940513077779 \tabularnewline
18 & 536214 & 553065.457233961 & 1377.66476117585 & -16851.4572339609 & -2.30570576608185 \tabularnewline
19 & 523597 & 530088.112874485 & 1289.78744144588 & -6491.11287448514 & -1.86896203968085 \tabularnewline
20 & 536535 & 530412.388294499 & 1286.06194085891 & 6122.61170550146 & -0.0740821968556601 \tabularnewline
21 & 536322 & 533617.286186172 & 1293.81557036507 & 2704.71381382838 & 0.147239612346936 \tabularnewline
22 & 532638 & 532136.122398902 & 1282.01949789657 & 501.877601098182 & -0.213001426720579 \tabularnewline
23 & 528222 & 527642.984028959 & 1260.65960189303 & 579.015971040655 & -0.44324080235284 \tabularnewline
24 & 516141 & 518326.266440672 & 1270.60730664961 & -2185.26644067168 & -0.811547659722004 \tabularnewline
25 & 501866 & 514950.103225772 & 1325.25343203174 & -13084.1032257723 & -0.370839965838765 \tabularnewline
26 & 506174 & 513145.269568085 & 1306.43455297191 & -6971.26956808448 & -0.233418623836777 \tabularnewline
27 & 517945 & 516861.07370766 & 1336.64601858446 & 1083.92629233995 & 0.178405386398126 \tabularnewline
28 & 533590 & 522681.848119795 & 1377.66474066902 & 10908.1518802055 & 0.341535753705118 \tabularnewline
29 & 528379 & 517987.674827628 & 1346.87752453859 & 10391.3251723717 & -0.466003285148121 \tabularnewline
30 & 477580 & 496454.69601857 & 1271.38380308250 & -18874.69601857 & -1.75634529924390 \tabularnewline
31 & 469357 & 480367.35815971 & 1218.61067102278 & -11010.3581597097 & -1.33207411105833 \tabularnewline
32 & 490243 & 482446.849443023 & 1221.44251279894 & 7796.15055697727 & 0.0660522630845694 \tabularnewline
33 & 492622 & 487522.847968293 & 1235.28611605162 & 5099.15203170746 & 0.295784921494092 \tabularnewline
34 & 507561 & 500922.096536194 & 1278.32452707196 & 6638.90346380574 & 0.933572815125066 \tabularnewline
35 & 516922 & 511150.734183575 & 1297.22109434975 & 5771.26581642509 & 0.686378408821981 \tabularnewline
36 & 514258 & 515156.212708348 & 1292.52187393446 & -898.212708347512 & 0.208071963458438 \tabularnewline
37 & 509846 & 520906.756593135 & 1271.51687832713 & -11060.7565931349 & 0.346934361529854 \tabularnewline
38 & 527070 & 532181.755531434 & 1307.98800886166 & -5111.75553143357 & 0.75607371720059 \tabularnewline
39 & 541657 & 540702.499209796 & 1373.12762803159 & 954.500790203915 & 0.539284885910175 \tabularnewline
40 & 564591 & 549486.77880843 & 1433.89180163269 & 15104.2211915696 & 0.563200775250767 \tabularnewline
41 & 555362 & 542173.003857475 & 1386.64288498744 & 13188.9961425245 & -0.670534840718818 \tabularnewline
42 & 498662 & 520851.229313406 & 1305.85520934167 & -22189.2293134055 & -1.74299882216345 \tabularnewline
43 & 511038 & 520502.201240661 & 1300.94174224817 & -9464.20124066087 & -0.127006889914247 \tabularnewline
44 & 525919 & 519501.247726123 & 1293.94344032715 & 6417.75227387652 & -0.176646543200523 \tabularnewline
45 & 531673 & 526930.57305361 & 1313.48310614462 & 4742.42694638963 & 0.470848519105573 \tabularnewline
46 & 548854 & 540039.138514952 & 1346.54794980713 & 8814.861485048 & 0.904969652727832 \tabularnewline
47 & 560576 & 552145.379873763 & 1359.86889691095 & 8430.620126237 & 0.824863991198845 \tabularnewline
48 & 557274 & 558852.538053309 & 1352.93998815335 & -1578.53805330925 & 0.410785419128755 \tabularnewline
49 & 565742 & 575097.120918293 & 1324.98151124578 & -9355.12091829265 & 1.14821707539112 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116550&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]548604[/C][C]548604[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]563668[/C][C]562016.947440278[/C][C]704.345528645455[/C][C]1651.05255972227[/C][C]0.639639182814211[/C][/ROW]
[ROW][C]3[/C][C]586111[/C][C]580587.370185185[/C][C]1179.82651323899[/C][C]5523.62981481553[/C][C]1.32250295302630[/C][/ROW]
[ROW][C]4[/C][C]604378[/C][C]599693.449905042[/C][C]1327.17000450475[/C][C]4684.55009495789[/C][C]1.37853242285227[/C][/ROW]
[ROW][C]5[/C][C]600991[/C][C]601398.733889013[/C][C]1329.08392847948[/C][C]-407.733889012837[/C][C]0.0290542150589399[/C][/ROW]
[ROW][C]6[/C][C]544686[/C][C]556523.987680729[/C][C]1073.30169941725[/C][C]-11837.9876807288[/C][C]-3.54876999359405[/C][/ROW]
[ROW][C]7[/C][C]537034[/C][C]537049.222147274[/C][C]952.075417468482[/C][C]-15.2221472740840[/C][C]-1.57803770617811[/C][/ROW]
[ROW][C]8[/C][C]551531[/C][C]546147.11335907[/C][C]1000.47887495443[/C][C]5383.88664093047[/C][C]0.625573455780406[/C][/ROW]
[ROW][C]9[/C][C]563250[/C][C]559557.27281574[/C][C]1073.67734184806[/C][C]3692.72718426024[/C][C]0.953025681362728[/C][/ROW]
[ROW][C]10[/C][C]574761[/C][C]571790.047426[/C][C]1139.01655928620[/C][C]2970.95257399994[/C][C]0.856977807592458[/C][/ROW]
[ROW][C]11[/C][C]580112[/C][C]578528.619184439[/C][C]1171.60186657992[/C][C]1583.38081556105[/C][C]0.430020595573834[/C][/ROW]
[ROW][C]12[/C][C]575093[/C][C]575649.431964169[/C][C]1148.16509997577[/C][C]-556.431964169046[/C][C]-0.311078881348947[/C][/ROW]
[ROW][C]13[/C][C]557560[/C][C]571421.297157701[/C][C]1349.79472472095[/C][C]-13861.2971577006[/C][C]-0.471200136501134[/C][/ROW]
[ROW][C]14[/C][C]564478[/C][C]568188.482915325[/C][C]1283.03565245604[/C][C]-3710.48291532461[/C][C]-0.32323754592142[/C][/ROW]
[ROW][C]15[/C][C]580523[/C][C]576746.451622686[/C][C]1415.5297397816[/C][C]3776.54837731381[/C][C]0.533231188285758[/C][/ROW]
[ROW][C]16[/C][C]596594[/C][C]589423.709881159[/C][C]1520.44063600364[/C][C]7170.29011884085[/C][C]0.861826031391642[/C][/ROW]
[ROW][C]17[/C][C]586570[/C][C]581622.379450372[/C][C]1479.56565841286[/C][C]4947.62054962772[/C][C]-0.715940513077779[/C][/ROW]
[ROW][C]18[/C][C]536214[/C][C]553065.457233961[/C][C]1377.66476117585[/C][C]-16851.4572339609[/C][C]-2.30570576608185[/C][/ROW]
[ROW][C]19[/C][C]523597[/C][C]530088.112874485[/C][C]1289.78744144588[/C][C]-6491.11287448514[/C][C]-1.86896203968085[/C][/ROW]
[ROW][C]20[/C][C]536535[/C][C]530412.388294499[/C][C]1286.06194085891[/C][C]6122.61170550146[/C][C]-0.0740821968556601[/C][/ROW]
[ROW][C]21[/C][C]536322[/C][C]533617.286186172[/C][C]1293.81557036507[/C][C]2704.71381382838[/C][C]0.147239612346936[/C][/ROW]
[ROW][C]22[/C][C]532638[/C][C]532136.122398902[/C][C]1282.01949789657[/C][C]501.877601098182[/C][C]-0.213001426720579[/C][/ROW]
[ROW][C]23[/C][C]528222[/C][C]527642.984028959[/C][C]1260.65960189303[/C][C]579.015971040655[/C][C]-0.44324080235284[/C][/ROW]
[ROW][C]24[/C][C]516141[/C][C]518326.266440672[/C][C]1270.60730664961[/C][C]-2185.26644067168[/C][C]-0.811547659722004[/C][/ROW]
[ROW][C]25[/C][C]501866[/C][C]514950.103225772[/C][C]1325.25343203174[/C][C]-13084.1032257723[/C][C]-0.370839965838765[/C][/ROW]
[ROW][C]26[/C][C]506174[/C][C]513145.269568085[/C][C]1306.43455297191[/C][C]-6971.26956808448[/C][C]-0.233418623836777[/C][/ROW]
[ROW][C]27[/C][C]517945[/C][C]516861.07370766[/C][C]1336.64601858446[/C][C]1083.92629233995[/C][C]0.178405386398126[/C][/ROW]
[ROW][C]28[/C][C]533590[/C][C]522681.848119795[/C][C]1377.66474066902[/C][C]10908.1518802055[/C][C]0.341535753705118[/C][/ROW]
[ROW][C]29[/C][C]528379[/C][C]517987.674827628[/C][C]1346.87752453859[/C][C]10391.3251723717[/C][C]-0.466003285148121[/C][/ROW]
[ROW][C]30[/C][C]477580[/C][C]496454.69601857[/C][C]1271.38380308250[/C][C]-18874.69601857[/C][C]-1.75634529924390[/C][/ROW]
[ROW][C]31[/C][C]469357[/C][C]480367.35815971[/C][C]1218.61067102278[/C][C]-11010.3581597097[/C][C]-1.33207411105833[/C][/ROW]
[ROW][C]32[/C][C]490243[/C][C]482446.849443023[/C][C]1221.44251279894[/C][C]7796.15055697727[/C][C]0.0660522630845694[/C][/ROW]
[ROW][C]33[/C][C]492622[/C][C]487522.847968293[/C][C]1235.28611605162[/C][C]5099.15203170746[/C][C]0.295784921494092[/C][/ROW]
[ROW][C]34[/C][C]507561[/C][C]500922.096536194[/C][C]1278.32452707196[/C][C]6638.90346380574[/C][C]0.933572815125066[/C][/ROW]
[ROW][C]35[/C][C]516922[/C][C]511150.734183575[/C][C]1297.22109434975[/C][C]5771.26581642509[/C][C]0.686378408821981[/C][/ROW]
[ROW][C]36[/C][C]514258[/C][C]515156.212708348[/C][C]1292.52187393446[/C][C]-898.212708347512[/C][C]0.208071963458438[/C][/ROW]
[ROW][C]37[/C][C]509846[/C][C]520906.756593135[/C][C]1271.51687832713[/C][C]-11060.7565931349[/C][C]0.346934361529854[/C][/ROW]
[ROW][C]38[/C][C]527070[/C][C]532181.755531434[/C][C]1307.98800886166[/C][C]-5111.75553143357[/C][C]0.75607371720059[/C][/ROW]
[ROW][C]39[/C][C]541657[/C][C]540702.499209796[/C][C]1373.12762803159[/C][C]954.500790203915[/C][C]0.539284885910175[/C][/ROW]
[ROW][C]40[/C][C]564591[/C][C]549486.77880843[/C][C]1433.89180163269[/C][C]15104.2211915696[/C][C]0.563200775250767[/C][/ROW]
[ROW][C]41[/C][C]555362[/C][C]542173.003857475[/C][C]1386.64288498744[/C][C]13188.9961425245[/C][C]-0.670534840718818[/C][/ROW]
[ROW][C]42[/C][C]498662[/C][C]520851.229313406[/C][C]1305.85520934167[/C][C]-22189.2293134055[/C][C]-1.74299882216345[/C][/ROW]
[ROW][C]43[/C][C]511038[/C][C]520502.201240661[/C][C]1300.94174224817[/C][C]-9464.20124066087[/C][C]-0.127006889914247[/C][/ROW]
[ROW][C]44[/C][C]525919[/C][C]519501.247726123[/C][C]1293.94344032715[/C][C]6417.75227387652[/C][C]-0.176646543200523[/C][/ROW]
[ROW][C]45[/C][C]531673[/C][C]526930.57305361[/C][C]1313.48310614462[/C][C]4742.42694638963[/C][C]0.470848519105573[/C][/ROW]
[ROW][C]46[/C][C]548854[/C][C]540039.138514952[/C][C]1346.54794980713[/C][C]8814.861485048[/C][C]0.904969652727832[/C][/ROW]
[ROW][C]47[/C][C]560576[/C][C]552145.379873763[/C][C]1359.86889691095[/C][C]8430.620126237[/C][C]0.824863991198845[/C][/ROW]
[ROW][C]48[/C][C]557274[/C][C]558852.538053309[/C][C]1352.93998815335[/C][C]-1578.53805330925[/C][C]0.410785419128755[/C][/ROW]
[ROW][C]49[/C][C]565742[/C][C]575097.120918293[/C][C]1324.98151124578[/C][C]-9355.12091829265[/C][C]1.14821707539112[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116550&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
1548604548604000
2563668562016.947440278704.3455286454551651.052559722270.639639182814211
3586111580587.3701851851179.826513238995523.629814815531.32250295302630
4604378599693.4499050421327.170004504754684.550094957891.37853242285227
5600991601398.7338890131329.08392847948-407.7338890128370.0290542150589399
6544686556523.9876807291073.30169941725-11837.9876807288-3.54876999359405
7537034537049.222147274952.075417468482-15.2221472740840-1.57803770617811
8551531546147.113359071000.478874954435383.886640930470.625573455780406
9563250559557.272815741073.677341848063692.727184260240.953025681362728
10574761571790.0474261139.016559286202970.952573999940.856977807592458
11580112578528.6191844391171.601866579921583.380815561050.430020595573834
12575093575649.4319641691148.16509997577-556.431964169046-0.311078881348947
13557560571421.2971577011349.79472472095-13861.2971577006-0.471200136501134
14564478568188.4829153251283.03565245604-3710.48291532461-0.32323754592142
15580523576746.4516226861415.52973978163776.548377313810.533231188285758
16596594589423.7098811591520.440636003647170.290118840850.861826031391642
17586570581622.3794503721479.565658412864947.62054962772-0.715940513077779
18536214553065.4572339611377.66476117585-16851.4572339609-2.30570576608185
19523597530088.1128744851289.78744144588-6491.11287448514-1.86896203968085
20536535530412.3882944991286.061940858916122.61170550146-0.0740821968556601
21536322533617.2861861721293.815570365072704.713813828380.147239612346936
22532638532136.1223989021282.01949789657501.877601098182-0.213001426720579
23528222527642.9840289591260.65960189303579.015971040655-0.44324080235284
24516141518326.2664406721270.60730664961-2185.26644067168-0.811547659722004
25501866514950.1032257721325.25343203174-13084.1032257723-0.370839965838765
26506174513145.2695680851306.43455297191-6971.26956808448-0.233418623836777
27517945516861.073707661336.646018584461083.926292339950.178405386398126
28533590522681.8481197951377.6647406690210908.15188020550.341535753705118
29528379517987.6748276281346.8775245385910391.3251723717-0.466003285148121
30477580496454.696018571271.38380308250-18874.69601857-1.75634529924390
31469357480367.358159711218.61067102278-11010.3581597097-1.33207411105833
32490243482446.8494430231221.442512798947796.150556977270.0660522630845694
33492622487522.8479682931235.286116051625099.152031707460.295784921494092
34507561500922.0965361941278.324527071966638.903463805740.933572815125066
35516922511150.7341835751297.221094349755771.265816425090.686378408821981
36514258515156.2127083481292.52187393446-898.2127083475120.208071963458438
37509846520906.7565931351271.51687832713-11060.75659313490.346934361529854
38527070532181.7555314341307.98800886166-5111.755531433570.75607371720059
39541657540702.4992097961373.12762803159954.5007902039150.539284885910175
40564591549486.778808431433.8918016326915104.22119156960.563200775250767
41555362542173.0038574751386.6428849874413188.9961425245-0.670534840718818
42498662520851.2293134061305.85520934167-22189.2293134055-1.74299882216345
43511038520502.2012406611300.94174224817-9464.20124066087-0.127006889914247
44525919519501.2477261231293.943440327156417.75227387652-0.176646543200523
45531673526930.573053611313.483106144624742.426946389630.470848519105573
46548854540039.1385149521346.547949807138814.8614850480.904969652727832
47560576552145.3798737631359.868896910958430.6201262370.824863991198845
48557274558852.5380533091352.93998815335-1578.538053309250.410785419128755
49565742575097.1209182931324.98151124578-9355.120918292651.14821707539112



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')