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Description of Statistical Computation

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 computationFri, 17 Dec 2010 16:42:30 +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/17/t12926040327vcnf0lrbl0ks1a.htm/, Retrieved Thu, 02 May 2024 20:24:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111574, Retrieved Thu, 02 May 2024 20:24:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact324

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Structural Time Series Models] [HPC Retail Sales] [2008-03-06 16:52:55] [74be16979710d4c4e7c6647856088456]
- R  D    [Structural Time Series Models] [HPC Retail Sales] [2008-03-08 11:33:35] [74be16979710d4c4e7c6647856088456]
-  M D      [Structural Time Series Models] [WS8 Structural Ti...] [2010-11-29 10:27:42] [f4dc4aa51d65be851b8508203d9f6001]
-    D          [Structural Time Series Models] [Structural Time S...] [2010-12-17 16:42:30] [7a87ed98a7b21a29d6a45388a9b7b229] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
989236
1008380
1207763
1368839
1469798
1498721
1761769
1653214
1599104
1421179
1163995
1037735
1015407
1039210
1258049
1469445
1552346
1549144
1785895
1662335
1629440
1467430
1202209
1076982
1039367
1063449
1335135
1491602
1591972
1641248
1898849
1798580
1762444
1622044
1368955
1262973
1195650
1269530
1479279
1607819
1712466
1721766
1949843
1821326
1757802
1590367
1260647
1149235
1016367
1027885
1262159
1520854
1544144
1564709
1821776
1741365
1623386
1498658
1241822
1136029

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111574&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111574&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111574&T=0

As an alternative you can also use a QR Code:  
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'RServer@AstonUniversity' @ vre.aston.ac.uk






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1989236989236000
210083801007464.8239676318304.4583479359915.1760323714560.205158156588241
312077631190887.15417499164849.20203265816875.84582501491.68381616733103
413688391371096.55868827178472.562432723-2257.558688265920.14847010537782
514697981475942.25957356113401.039471187-6144.2595735563-0.712754757498346
614987211503786.8173673137693.4894229754-5065.81736731116-0.828882468346857
717617691741127.72496455214372.61100493420641.27503545321.93433688951141
816532141681601.15695943-27997.9408651255-28387.1569594327-2.65354152616664
915991041596784.5114017-78275.31559761832319.48859830071-0.550450693824062
1014211791427148.81367717-159118.311904447-5969.81367716915-0.885091652012392
1111639951169751.58806709-246083.610723971-5756.5880670883-0.952120316062697
1210377351025502.96921664-155971.64956547512232.03078335750.98657085251419
1310154071006998.77809958-34428.921999068408.221900424871.33218656308679
1410392101050488.3929653934586.3292676019-11278.3929653890.763051783989928
1512580491233257.84531859160152.95891237824791.15468141071.38987413167301
1614694451459806.03739443216956.5956768249638.962605572710.622455115941462
1715523461555364.24688723113678.637191466-3018.24688723112-1.12989323953066
1815491441596435.2106385251863.3106968983-47291.2106385222-0.676935426438004
1917858951725616.81096116117714.65126857160278.18903884380.72094603575268
2016623351706520.011008871195.99598397061-44185.0110088708-1.27568394604374
2116294401628079.48332224-66624.21406145891360.51667775942-0.742514535171335
2214674301465088.59365848-148692.7052420632341.40634152317-0.898509045970153
2312022091221073.46751818-229874.489388055-18864.4675181832-0.888806448412663
2410769821064615.55352724-167362.5099498812366.44647276410.684409797630143
2510393671020007.1367768-62890.790601232119359.86322319541.14547865516439
2610634491083917.5365834345164.8794267508-20468.53658343021.185080709421
2713351351309673.38194462196678.19822977525461.61805538131.66334635408133
2814916021472031.75864276167735.58470341219570.2413572367-0.317588360261953
2915919721588490.14551138124610.6680682073481.85448862488-0.471632508292719
3016412481707721.93334476120088.897975009-66473.9333447636-0.0495148007978715
3118988491823942.98877171116835.55884599574906.0112282916-0.0356191897324393
3217985801848904.6589369139552.8558076856-50324.6589369119-0.846106047608183
3317624441764562.08133564-64662.476808368-2118.08133564485-1.14098031432421
3416220441609137.65111193-141007.30103544212906.3488880725-0.83584892020799
3513689551396424.86450519-201320.55315407-27469.8645051933-0.660328170259007
3612629731250238.41963702-154962.6147731712734.58036298030.507591915967803
3711956501178211.66189516-85223.319199346417438.33810484320.764564637363084
3812695301299013.7493517188010.0568999051-29483.74935170641.89658182688081
3914792791446327.56839184137524.81897776332951.43160816450.542615428927656
4016078191581536.34651634135585.95307974226282.6534836635-0.0212684448479848
4117124661711511.77715323130893.192539172954.222846766093-0.0513357024751949
4217217661799806.9935678195297.5878839816-78040.9935678123-0.389706535103795
4319498431871248.3194654775353.37577624278594.6805345342-0.21837085052715
4418213261867719.921462839396.032132246-46393.9214628335-0.722108632902278
4517578021761259.23649648-87478.384271377-3457.23649648099-1.06061136852694
4615903671572182.40923038-172429.18015538918184.5907696164-0.930079379400444
4712606471297721.38495309-257731.673197424-37074.3849530888-0.933906473497344
4811492351126798.59856733-185181.56477563922436.40143266620.794472369105847
4910163671019680.90166342-119917.971686716-3313.901663416360.715242109788243
5010278851050169.307884615746.21322480324-22284.30788461061.37533144544749
5112621591213280.5680722136714.03059765348878.43192781.434508435879
5215208541481908.87526815246666.66942935338945.12473185331.20554623439595
5315441441559351.85250321105621.747152111-15207.8525032085-1.54342577943302
5415647091647632.0650319291182.5317806887-82923.0650319214-0.158059884367885
5518217761739555.7374544991799.808890211482220.26254551260.00675873584822836
5617413651781923.5752391650619.5636596885-40558.575239164-0.450848752998997
5716233861634953.41940773-113991.416630682-11567.4194077305-1.80221286015641
5814986581463629.86899661-161752.95503977835028.1310033859-0.522916605514228
5912418221286066.64976003-174921.488185682-44244.6497600334-0.144171435539331
6011360291113060.38478289-173326.69079535422968.61521711290.0174653046580764

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 989236 & 989236 & 0 & 0 & 0 \tabularnewline
2 & 1008380 & 1007464.82396763 & 18304.4583479359 & 915.176032371456 & 0.205158156588241 \tabularnewline
3 & 1207763 & 1190887.15417499 & 164849.202032658 & 16875.8458250149 & 1.68381616733103 \tabularnewline
4 & 1368839 & 1371096.55868827 & 178472.562432723 & -2257.55868826592 & 0.14847010537782 \tabularnewline
5 & 1469798 & 1475942.25957356 & 113401.039471187 & -6144.2595735563 & -0.712754757498346 \tabularnewline
6 & 1498721 & 1503786.81736731 & 37693.4894229754 & -5065.81736731116 & -0.828882468346857 \tabularnewline
7 & 1761769 & 1741127.72496455 & 214372.611004934 & 20641.2750354532 & 1.93433688951141 \tabularnewline
8 & 1653214 & 1681601.15695943 & -27997.9408651255 & -28387.1569594327 & -2.65354152616664 \tabularnewline
9 & 1599104 & 1596784.5114017 & -78275.3155976183 & 2319.48859830071 & -0.550450693824062 \tabularnewline
10 & 1421179 & 1427148.81367717 & -159118.311904447 & -5969.81367716915 & -0.885091652012392 \tabularnewline
11 & 1163995 & 1169751.58806709 & -246083.610723971 & -5756.5880670883 & -0.952120316062697 \tabularnewline
12 & 1037735 & 1025502.96921664 & -155971.649565475 & 12232.0307833575 & 0.98657085251419 \tabularnewline
13 & 1015407 & 1006998.77809958 & -34428.92199906 & 8408.22190042487 & 1.33218656308679 \tabularnewline
14 & 1039210 & 1050488.39296539 & 34586.3292676019 & -11278.392965389 & 0.763051783989928 \tabularnewline
15 & 1258049 & 1233257.84531859 & 160152.958912378 & 24791.1546814107 & 1.38987413167301 \tabularnewline
16 & 1469445 & 1459806.03739443 & 216956.595676824 & 9638.96260557271 & 0.622455115941462 \tabularnewline
17 & 1552346 & 1555364.24688723 & 113678.637191466 & -3018.24688723112 & -1.12989323953066 \tabularnewline
18 & 1549144 & 1596435.21063852 & 51863.3106968983 & -47291.2106385222 & -0.676935426438004 \tabularnewline
19 & 1785895 & 1725616.81096116 & 117714.651268571 & 60278.1890388438 & 0.72094603575268 \tabularnewline
20 & 1662335 & 1706520.01100887 & 1195.99598397061 & -44185.0110088708 & -1.27568394604374 \tabularnewline
21 & 1629440 & 1628079.48332224 & -66624.2140614589 & 1360.51667775942 & -0.742514535171335 \tabularnewline
22 & 1467430 & 1465088.59365848 & -148692.705242063 & 2341.40634152317 & -0.898509045970153 \tabularnewline
23 & 1202209 & 1221073.46751818 & -229874.489388055 & -18864.4675181832 & -0.888806448412663 \tabularnewline
24 & 1076982 & 1064615.55352724 & -167362.50994988 & 12366.4464727641 & 0.684409797630143 \tabularnewline
25 & 1039367 & 1020007.1367768 & -62890.7906012321 & 19359.8632231954 & 1.14547865516439 \tabularnewline
26 & 1063449 & 1083917.53658343 & 45164.8794267508 & -20468.5365834302 & 1.185080709421 \tabularnewline
27 & 1335135 & 1309673.38194462 & 196678.198229775 & 25461.6180553813 & 1.66334635408133 \tabularnewline
28 & 1491602 & 1472031.75864276 & 167735.584703412 & 19570.2413572367 & -0.317588360261953 \tabularnewline
29 & 1591972 & 1588490.14551138 & 124610.668068207 & 3481.85448862488 & -0.471632508292719 \tabularnewline
30 & 1641248 & 1707721.93334476 & 120088.897975009 & -66473.9333447636 & -0.0495148007978715 \tabularnewline
31 & 1898849 & 1823942.98877171 & 116835.558845995 & 74906.0112282916 & -0.0356191897324393 \tabularnewline
32 & 1798580 & 1848904.65893691 & 39552.8558076856 & -50324.6589369119 & -0.846106047608183 \tabularnewline
33 & 1762444 & 1764562.08133564 & -64662.476808368 & -2118.08133564485 & -1.14098031432421 \tabularnewline
34 & 1622044 & 1609137.65111193 & -141007.301035442 & 12906.3488880725 & -0.83584892020799 \tabularnewline
35 & 1368955 & 1396424.86450519 & -201320.55315407 & -27469.8645051933 & -0.660328170259007 \tabularnewline
36 & 1262973 & 1250238.41963702 & -154962.61477317 & 12734.5803629803 & 0.507591915967803 \tabularnewline
37 & 1195650 & 1178211.66189516 & -85223.3191993464 & 17438.3381048432 & 0.764564637363084 \tabularnewline
38 & 1269530 & 1299013.74935171 & 88010.0568999051 & -29483.7493517064 & 1.89658182688081 \tabularnewline
39 & 1479279 & 1446327.56839184 & 137524.818977763 & 32951.4316081645 & 0.542615428927656 \tabularnewline
40 & 1607819 & 1581536.34651634 & 135585.953079742 & 26282.6534836635 & -0.0212684448479848 \tabularnewline
41 & 1712466 & 1711511.77715323 & 130893.192539172 & 954.222846766093 & -0.0513357024751949 \tabularnewline
42 & 1721766 & 1799806.99356781 & 95297.5878839816 & -78040.9935678123 & -0.389706535103795 \tabularnewline
43 & 1949843 & 1871248.31946547 & 75353.375776242 & 78594.6805345342 & -0.21837085052715 \tabularnewline
44 & 1821326 & 1867719.92146283 & 9396.032132246 & -46393.9214628335 & -0.722108632902278 \tabularnewline
45 & 1757802 & 1761259.23649648 & -87478.384271377 & -3457.23649648099 & -1.06061136852694 \tabularnewline
46 & 1590367 & 1572182.40923038 & -172429.180155389 & 18184.5907696164 & -0.930079379400444 \tabularnewline
47 & 1260647 & 1297721.38495309 & -257731.673197424 & -37074.3849530888 & -0.933906473497344 \tabularnewline
48 & 1149235 & 1126798.59856733 & -185181.564775639 & 22436.4014326662 & 0.794472369105847 \tabularnewline
49 & 1016367 & 1019680.90166342 & -119917.971686716 & -3313.90166341636 & 0.715242109788243 \tabularnewline
50 & 1027885 & 1050169.30788461 & 5746.21322480324 & -22284.3078846106 & 1.37533144544749 \tabularnewline
51 & 1262159 & 1213280.5680722 & 136714.030597653 & 48878.4319278 & 1.434508435879 \tabularnewline
52 & 1520854 & 1481908.87526815 & 246666.669429353 & 38945.1247318533 & 1.20554623439595 \tabularnewline
53 & 1544144 & 1559351.85250321 & 105621.747152111 & -15207.8525032085 & -1.54342577943302 \tabularnewline
54 & 1564709 & 1647632.06503192 & 91182.5317806887 & -82923.0650319214 & -0.158059884367885 \tabularnewline
55 & 1821776 & 1739555.73745449 & 91799.8088902114 & 82220.2625455126 & 0.00675873584822836 \tabularnewline
56 & 1741365 & 1781923.57523916 & 50619.5636596885 & -40558.575239164 & -0.450848752998997 \tabularnewline
57 & 1623386 & 1634953.41940773 & -113991.416630682 & -11567.4194077305 & -1.80221286015641 \tabularnewline
58 & 1498658 & 1463629.86899661 & -161752.955039778 & 35028.1310033859 & -0.522916605514228 \tabularnewline
59 & 1241822 & 1286066.64976003 & -174921.488185682 & -44244.6497600334 & -0.144171435539331 \tabularnewline
60 & 1136029 & 1113060.38478289 & -173326.690795354 & 22968.6152171129 & 0.0174653046580764 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111574&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]989236[/C][C]989236[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]1008380[/C][C]1007464.82396763[/C][C]18304.4583479359[/C][C]915.176032371456[/C][C]0.205158156588241[/C][/ROW]
[ROW][C]3[/C][C]1207763[/C][C]1190887.15417499[/C][C]164849.202032658[/C][C]16875.8458250149[/C][C]1.68381616733103[/C][/ROW]
[ROW][C]4[/C][C]1368839[/C][C]1371096.55868827[/C][C]178472.562432723[/C][C]-2257.55868826592[/C][C]0.14847010537782[/C][/ROW]
[ROW][C]5[/C][C]1469798[/C][C]1475942.25957356[/C][C]113401.039471187[/C][C]-6144.2595735563[/C][C]-0.712754757498346[/C][/ROW]
[ROW][C]6[/C][C]1498721[/C][C]1503786.81736731[/C][C]37693.4894229754[/C][C]-5065.81736731116[/C][C]-0.828882468346857[/C][/ROW]
[ROW][C]7[/C][C]1761769[/C][C]1741127.72496455[/C][C]214372.611004934[/C][C]20641.2750354532[/C][C]1.93433688951141[/C][/ROW]
[ROW][C]8[/C][C]1653214[/C][C]1681601.15695943[/C][C]-27997.9408651255[/C][C]-28387.1569594327[/C][C]-2.65354152616664[/C][/ROW]
[ROW][C]9[/C][C]1599104[/C][C]1596784.5114017[/C][C]-78275.3155976183[/C][C]2319.48859830071[/C][C]-0.550450693824062[/C][/ROW]
[ROW][C]10[/C][C]1421179[/C][C]1427148.81367717[/C][C]-159118.311904447[/C][C]-5969.81367716915[/C][C]-0.885091652012392[/C][/ROW]
[ROW][C]11[/C][C]1163995[/C][C]1169751.58806709[/C][C]-246083.610723971[/C][C]-5756.5880670883[/C][C]-0.952120316062697[/C][/ROW]
[ROW][C]12[/C][C]1037735[/C][C]1025502.96921664[/C][C]-155971.649565475[/C][C]12232.0307833575[/C][C]0.98657085251419[/C][/ROW]
[ROW][C]13[/C][C]1015407[/C][C]1006998.77809958[/C][C]-34428.92199906[/C][C]8408.22190042487[/C][C]1.33218656308679[/C][/ROW]
[ROW][C]14[/C][C]1039210[/C][C]1050488.39296539[/C][C]34586.3292676019[/C][C]-11278.392965389[/C][C]0.763051783989928[/C][/ROW]
[ROW][C]15[/C][C]1258049[/C][C]1233257.84531859[/C][C]160152.958912378[/C][C]24791.1546814107[/C][C]1.38987413167301[/C][/ROW]
[ROW][C]16[/C][C]1469445[/C][C]1459806.03739443[/C][C]216956.595676824[/C][C]9638.96260557271[/C][C]0.622455115941462[/C][/ROW]
[ROW][C]17[/C][C]1552346[/C][C]1555364.24688723[/C][C]113678.637191466[/C][C]-3018.24688723112[/C][C]-1.12989323953066[/C][/ROW]
[ROW][C]18[/C][C]1549144[/C][C]1596435.21063852[/C][C]51863.3106968983[/C][C]-47291.2106385222[/C][C]-0.676935426438004[/C][/ROW]
[ROW][C]19[/C][C]1785895[/C][C]1725616.81096116[/C][C]117714.651268571[/C][C]60278.1890388438[/C][C]0.72094603575268[/C][/ROW]
[ROW][C]20[/C][C]1662335[/C][C]1706520.01100887[/C][C]1195.99598397061[/C][C]-44185.0110088708[/C][C]-1.27568394604374[/C][/ROW]
[ROW][C]21[/C][C]1629440[/C][C]1628079.48332224[/C][C]-66624.2140614589[/C][C]1360.51667775942[/C][C]-0.742514535171335[/C][/ROW]
[ROW][C]22[/C][C]1467430[/C][C]1465088.59365848[/C][C]-148692.705242063[/C][C]2341.40634152317[/C][C]-0.898509045970153[/C][/ROW]
[ROW][C]23[/C][C]1202209[/C][C]1221073.46751818[/C][C]-229874.489388055[/C][C]-18864.4675181832[/C][C]-0.888806448412663[/C][/ROW]
[ROW][C]24[/C][C]1076982[/C][C]1064615.55352724[/C][C]-167362.50994988[/C][C]12366.4464727641[/C][C]0.684409797630143[/C][/ROW]
[ROW][C]25[/C][C]1039367[/C][C]1020007.1367768[/C][C]-62890.7906012321[/C][C]19359.8632231954[/C][C]1.14547865516439[/C][/ROW]
[ROW][C]26[/C][C]1063449[/C][C]1083917.53658343[/C][C]45164.8794267508[/C][C]-20468.5365834302[/C][C]1.185080709421[/C][/ROW]
[ROW][C]27[/C][C]1335135[/C][C]1309673.38194462[/C][C]196678.198229775[/C][C]25461.6180553813[/C][C]1.66334635408133[/C][/ROW]
[ROW][C]28[/C][C]1491602[/C][C]1472031.75864276[/C][C]167735.584703412[/C][C]19570.2413572367[/C][C]-0.317588360261953[/C][/ROW]
[ROW][C]29[/C][C]1591972[/C][C]1588490.14551138[/C][C]124610.668068207[/C][C]3481.85448862488[/C][C]-0.471632508292719[/C][/ROW]
[ROW][C]30[/C][C]1641248[/C][C]1707721.93334476[/C][C]120088.897975009[/C][C]-66473.9333447636[/C][C]-0.0495148007978715[/C][/ROW]
[ROW][C]31[/C][C]1898849[/C][C]1823942.98877171[/C][C]116835.558845995[/C][C]74906.0112282916[/C][C]-0.0356191897324393[/C][/ROW]
[ROW][C]32[/C][C]1798580[/C][C]1848904.65893691[/C][C]39552.8558076856[/C][C]-50324.6589369119[/C][C]-0.846106047608183[/C][/ROW]
[ROW][C]33[/C][C]1762444[/C][C]1764562.08133564[/C][C]-64662.476808368[/C][C]-2118.08133564485[/C][C]-1.14098031432421[/C][/ROW]
[ROW][C]34[/C][C]1622044[/C][C]1609137.65111193[/C][C]-141007.301035442[/C][C]12906.3488880725[/C][C]-0.83584892020799[/C][/ROW]
[ROW][C]35[/C][C]1368955[/C][C]1396424.86450519[/C][C]-201320.55315407[/C][C]-27469.8645051933[/C][C]-0.660328170259007[/C][/ROW]
[ROW][C]36[/C][C]1262973[/C][C]1250238.41963702[/C][C]-154962.61477317[/C][C]12734.5803629803[/C][C]0.507591915967803[/C][/ROW]
[ROW][C]37[/C][C]1195650[/C][C]1178211.66189516[/C][C]-85223.3191993464[/C][C]17438.3381048432[/C][C]0.764564637363084[/C][/ROW]
[ROW][C]38[/C][C]1269530[/C][C]1299013.74935171[/C][C]88010.0568999051[/C][C]-29483.7493517064[/C][C]1.89658182688081[/C][/ROW]
[ROW][C]39[/C][C]1479279[/C][C]1446327.56839184[/C][C]137524.818977763[/C][C]32951.4316081645[/C][C]0.542615428927656[/C][/ROW]
[ROW][C]40[/C][C]1607819[/C][C]1581536.34651634[/C][C]135585.953079742[/C][C]26282.6534836635[/C][C]-0.0212684448479848[/C][/ROW]
[ROW][C]41[/C][C]1712466[/C][C]1711511.77715323[/C][C]130893.192539172[/C][C]954.222846766093[/C][C]-0.0513357024751949[/C][/ROW]
[ROW][C]42[/C][C]1721766[/C][C]1799806.99356781[/C][C]95297.5878839816[/C][C]-78040.9935678123[/C][C]-0.389706535103795[/C][/ROW]
[ROW][C]43[/C][C]1949843[/C][C]1871248.31946547[/C][C]75353.375776242[/C][C]78594.6805345342[/C][C]-0.21837085052715[/C][/ROW]
[ROW][C]44[/C][C]1821326[/C][C]1867719.92146283[/C][C]9396.032132246[/C][C]-46393.9214628335[/C][C]-0.722108632902278[/C][/ROW]
[ROW][C]45[/C][C]1757802[/C][C]1761259.23649648[/C][C]-87478.384271377[/C][C]-3457.23649648099[/C][C]-1.06061136852694[/C][/ROW]
[ROW][C]46[/C][C]1590367[/C][C]1572182.40923038[/C][C]-172429.180155389[/C][C]18184.5907696164[/C][C]-0.930079379400444[/C][/ROW]
[ROW][C]47[/C][C]1260647[/C][C]1297721.38495309[/C][C]-257731.673197424[/C][C]-37074.3849530888[/C][C]-0.933906473497344[/C][/ROW]
[ROW][C]48[/C][C]1149235[/C][C]1126798.59856733[/C][C]-185181.564775639[/C][C]22436.4014326662[/C][C]0.794472369105847[/C][/ROW]
[ROW][C]49[/C][C]1016367[/C][C]1019680.90166342[/C][C]-119917.971686716[/C][C]-3313.90166341636[/C][C]0.715242109788243[/C][/ROW]
[ROW][C]50[/C][C]1027885[/C][C]1050169.30788461[/C][C]5746.21322480324[/C][C]-22284.3078846106[/C][C]1.37533144544749[/C][/ROW]
[ROW][C]51[/C][C]1262159[/C][C]1213280.5680722[/C][C]136714.030597653[/C][C]48878.4319278[/C][C]1.434508435879[/C][/ROW]
[ROW][C]52[/C][C]1520854[/C][C]1481908.87526815[/C][C]246666.669429353[/C][C]38945.1247318533[/C][C]1.20554623439595[/C][/ROW]
[ROW][C]53[/C][C]1544144[/C][C]1559351.85250321[/C][C]105621.747152111[/C][C]-15207.8525032085[/C][C]-1.54342577943302[/C][/ROW]
[ROW][C]54[/C][C]1564709[/C][C]1647632.06503192[/C][C]91182.5317806887[/C][C]-82923.0650319214[/C][C]-0.158059884367885[/C][/ROW]
[ROW][C]55[/C][C]1821776[/C][C]1739555.73745449[/C][C]91799.8088902114[/C][C]82220.2625455126[/C][C]0.00675873584822836[/C][/ROW]
[ROW][C]56[/C][C]1741365[/C][C]1781923.57523916[/C][C]50619.5636596885[/C][C]-40558.575239164[/C][C]-0.450848752998997[/C][/ROW]
[ROW][C]57[/C][C]1623386[/C][C]1634953.41940773[/C][C]-113991.416630682[/C][C]-11567.4194077305[/C][C]-1.80221286015641[/C][/ROW]
[ROW][C]58[/C][C]1498658[/C][C]1463629.86899661[/C][C]-161752.955039778[/C][C]35028.1310033859[/C][C]-0.522916605514228[/C][/ROW]
[ROW][C]59[/C][C]1241822[/C][C]1286066.64976003[/C][C]-174921.488185682[/C][C]-44244.6497600334[/C][C]-0.144171435539331[/C][/ROW]
[ROW][C]60[/C][C]1136029[/C][C]1113060.38478289[/C][C]-173326.690795354[/C][C]22968.6152171129[/C][C]0.0174653046580764[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111574&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111574&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1989236989236000
210083801007464.8239676318304.4583479359915.1760323714560.205158156588241
312077631190887.15417499164849.20203265816875.84582501491.68381616733103
413688391371096.55868827178472.562432723-2257.558688265920.14847010537782
514697981475942.25957356113401.039471187-6144.2595735563-0.712754757498346
614987211503786.8173673137693.4894229754-5065.81736731116-0.828882468346857
717617691741127.72496455214372.61100493420641.27503545321.93433688951141
816532141681601.15695943-27997.9408651255-28387.1569594327-2.65354152616664
915991041596784.5114017-78275.31559761832319.48859830071-0.550450693824062
1014211791427148.81367717-159118.311904447-5969.81367716915-0.885091652012392
1111639951169751.58806709-246083.610723971-5756.5880670883-0.952120316062697
1210377351025502.96921664-155971.64956547512232.03078335750.98657085251419
1310154071006998.77809958-34428.921999068408.221900424871.33218656308679
1410392101050488.3929653934586.3292676019-11278.3929653890.763051783989928
1512580491233257.84531859160152.95891237824791.15468141071.38987413167301
1614694451459806.03739443216956.5956768249638.962605572710.622455115941462
1715523461555364.24688723113678.637191466-3018.24688723112-1.12989323953066
1815491441596435.2106385251863.3106968983-47291.2106385222-0.676935426438004
1917858951725616.81096116117714.65126857160278.18903884380.72094603575268
2016623351706520.011008871195.99598397061-44185.0110088708-1.27568394604374
2116294401628079.48332224-66624.21406145891360.51667775942-0.742514535171335
2214674301465088.59365848-148692.7052420632341.40634152317-0.898509045970153
2312022091221073.46751818-229874.489388055-18864.4675181832-0.888806448412663
2410769821064615.55352724-167362.5099498812366.44647276410.684409797630143
2510393671020007.1367768-62890.790601232119359.86322319541.14547865516439
2610634491083917.5365834345164.8794267508-20468.53658343021.185080709421
2713351351309673.38194462196678.19822977525461.61805538131.66334635408133
2814916021472031.75864276167735.58470341219570.2413572367-0.317588360261953
2915919721588490.14551138124610.6680682073481.85448862488-0.471632508292719
3016412481707721.93334476120088.897975009-66473.9333447636-0.0495148007978715
3118988491823942.98877171116835.55884599574906.0112282916-0.0356191897324393
3217985801848904.6589369139552.8558076856-50324.6589369119-0.846106047608183
3317624441764562.08133564-64662.476808368-2118.08133564485-1.14098031432421
3416220441609137.65111193-141007.30103544212906.3488880725-0.83584892020799
3513689551396424.86450519-201320.55315407-27469.8645051933-0.660328170259007
3612629731250238.41963702-154962.6147731712734.58036298030.507591915967803
3711956501178211.66189516-85223.319199346417438.33810484320.764564637363084
3812695301299013.7493517188010.0568999051-29483.74935170641.89658182688081
3914792791446327.56839184137524.81897776332951.43160816450.542615428927656
4016078191581536.34651634135585.95307974226282.6534836635-0.0212684448479848
4117124661711511.77715323130893.192539172954.222846766093-0.0513357024751949
4217217661799806.9935678195297.5878839816-78040.9935678123-0.389706535103795
4319498431871248.3194654775353.37577624278594.6805345342-0.21837085052715
4418213261867719.921462839396.032132246-46393.9214628335-0.722108632902278
4517578021761259.23649648-87478.384271377-3457.23649648099-1.06061136852694
4615903671572182.40923038-172429.18015538918184.5907696164-0.930079379400444
4712606471297721.38495309-257731.673197424-37074.3849530888-0.933906473497344
4811492351126798.59856733-185181.56477563922436.40143266620.794472369105847
4910163671019680.90166342-119917.971686716-3313.901663416360.715242109788243
5010278851050169.307884615746.21322480324-22284.30788461061.37533144544749
5112621591213280.5680722136714.03059765348878.43192781.434508435879
5215208541481908.87526815246666.66942935338945.12473185331.20554623439595
5315441441559351.85250321105621.747152111-15207.8525032085-1.54342577943302
5415647091647632.0650319291182.5317806887-82923.0650319214-0.158059884367885
5518217761739555.7374544991799.808890211482220.26254551260.00675873584822836
5617413651781923.5752391650619.5636596885-40558.575239164-0.450848752998997
5716233861634953.41940773-113991.416630682-11567.4194077305-1.80221286015641
5814986581463629.86899661-161752.95503977835028.1310033859-0.522916605514228
5912418221286066.64976003-174921.488185682-44244.6497600334-0.144171435539331
6011360291113060.38478289-173326.69079535422968.61521711290.0174653046580764


Figures (Output of Computation)

Input Parameters & R Code

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$resid)
myfit <- mylevel+myseas
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time')
grid()
dev.off()
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='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')