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 computationThu, 16 Dec 2010 17:52:22 +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/16/t129252187584mrtnu6bizjuq6.htm/, Retrieved Fri, 03 May 2024 08:00:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=111111, Retrieved Fri, 03 May 2024 08:00:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [STSM peer review] [2010-12-16 17:52:22] [4c854bb223ec27caaa7bcfc5e77b0dbd] [Current]
Feedback Forum

Post a new message
Dataseries X:
286602
283042
276687
277915
277128
277103
275037
270150
267140
264993
287259
291186
292300
288186
281477
282656
280190
280408
276836
275216
274352
271311
289802
290726
292300
278506
269826
265861
269034
264176
255198
253353
246057
235372
258556
260993
254663
250643
243422
247105
248541
245039
237080
237085
225554
226839
247934
248333
246969
245098
246263
255765
264319
268347
273046
273963
267430
271993
292710
295881
294563




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111111&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111111&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111111&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 time6 seconds
R Server'George Udny Yule' @ 72.249.76.132







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1286602286602000
2283042283653.514678328-194.918781431049-611.514678327863-0.513504172651212
3276687278738.112107994-633.581801757586-2051.11210799353-1.10580595409501
4277915277701.909912795-680.252271222706213.090087204625-0.0997065198244274
5277128277271.530240242-645.890768061875-143.5302402419800.0602327365463566
6277103277213.666234932-554.779819817128-110.6662349318740.139143721593626
7275037275809.967354789-696.861674374174-772.967354788608-0.198553808025926
8270150271748.631096895-1287.72185557428-1598.63109689547-0.78068783645142
9267140267979.819544199-1736.67874160150-839.819544198809-0.572582134226973
10264993265323.003050931-1906.33467108155-330.003050931516-0.211571373760679
11287259280417.1309134021265.666843094086841.869086597513.89954991137942
12291186290454.5055914382914.69562417399731.4944085622162.0088718445796
13292300291827.6026693142635.81462614077472.397330685744-0.381768914671608
14288186289105.3061682421630.43337354587-919.30616824152-1.17241415668180
15281477285177.447902346601.232352478222-3700.44790234588-1.19525698085119
16282656283202.099905819121.719278756493-546.099905818812-0.580525201913526
17280190281322.896910550-253.224981554856-1132.89691054965-0.451681847842913
18280408280363.258527809-385.76640759498444.7414721908378-0.158669731712760
19276836277419.915821799-865.538410338143-583.915821798573-0.574248363255685
20275216275491.15769903-1065.00033327702-275.157699030219-0.238969163696083
21274352274611.958751139-1030.13291846558-259.9587511394430.0417967307084539
22271311276026.198911086-571.326758062151-4715.198911086080.55005764334406
23289802282777.257880196802.0263124372577024.742119803611.64583404226181
24290726288224.9158514381670.532245177412501.084148562351.04459985922816
25292300289964.1175762451683.347354447582335.882423754780.015828751956963
26278506281998.089648172-124.045506568646-3492.08964817203-2.15946615518098
27269826274827.818024539-1432.84780051521-5001.81802453924-1.54256078982195
28265861267747.948348433-2481.0253160722-1886.94834843271-1.25987164650344
29269034267801.884705637-2008.27966367891232.115294363170.569696858211719
30264176264104.828719529-2323.8807713108071.1712804712921-0.37826232203378
31255198257203.49419422-3179.21790478733-2005.49419421973-1.02322729611630
32253353253381.570478368-3299.2713841071-28.5704783683416-0.143704090850896
33246057248384.476653014-3616.38993146270-2327.47665301379-0.379863530546178
34235372243648.865106564-3825.38359246229-8276.86510656376-0.250373649485884
35258556248979.766908410-2117.60316727919576.233091590422.04668896015447
36260993255068.423107095-589.4085469147425924.576892905241.84078304131215
37254663251037.498183637-1231.037268367923625.5018163629-0.778868184343224
38250643250527.036653019-1096.54167628592115.9633469809070.161087811175728
39243422247730.699337801-1412.43090814126-4308.69933780114-0.375139009225978
40247105248642.866147849-981.209418361088-1537.866147849000.516878030877219
41248541247027.331471033-1099.160172459651513.66852896716-0.142032433025296
42245039244050.07569262-1449.09026577852988.924307379717-0.420166870291771
43237080239692.625931415-1991.14701737445-2612.6259314146-0.64916543320341
44237085236430.49346715-2227.95474970988654.506532849932-0.283464343975813
45225554229940.029080625-3021.8753196366-4386.02908062471-0.950570012871678
46226839234615.251741445-1589.01479578791-7776.251741445471.71599627009908
47247934238931.841920532-490.6905617792959002.158079468261.31711125399326
48248333240720.334200147-66.99031349206947612.665799853060.510186904837453
49246969242754.735810031324.1513543978604214.264189969390.472008393862723
50245098244328.766295623556.904166872985769.2337043774970.278817456230623
51246263249469.0936537881408.2801782797-3206.093653787851.01476386798951
52255765255350.0999386042237.72036605097414.9000613960930.993370973336029
53264319260783.5575788702831.004442045263535.442421130310.713581227538113
54268347265445.5823494293171.472951531492901.417650570690.409102347320942
55273046272785.3814658063946.95829275335260.6185341939560.929579390203477
56273963273978.8191540893434.81370984221-15.8191540891989-0.613160401588959
57267430275520.9199336633082.95113374645-8090.91993366284-0.421175038917083
58271993280665.5445867713465.97178352948-8672.544586771420.458685689751345
59292710284488.0323698353532.163194881178221.967630165410.0794080017422295
60295881288639.6820494503647.189672795537241.317950549640.138399093199395
61294563291496.4363597773500.269126413783066.56364022347-0.176832484645321

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 286602 & 286602 & 0 & 0 & 0 \tabularnewline
2 & 283042 & 283653.514678328 & -194.918781431049 & -611.514678327863 & -0.513504172651212 \tabularnewline
3 & 276687 & 278738.112107994 & -633.581801757586 & -2051.11210799353 & -1.10580595409501 \tabularnewline
4 & 277915 & 277701.909912795 & -680.252271222706 & 213.090087204625 & -0.0997065198244274 \tabularnewline
5 & 277128 & 277271.530240242 & -645.890768061875 & -143.530240241980 & 0.0602327365463566 \tabularnewline
6 & 277103 & 277213.666234932 & -554.779819817128 & -110.666234931874 & 0.139143721593626 \tabularnewline
7 & 275037 & 275809.967354789 & -696.861674374174 & -772.967354788608 & -0.198553808025926 \tabularnewline
8 & 270150 & 271748.631096895 & -1287.72185557428 & -1598.63109689547 & -0.78068783645142 \tabularnewline
9 & 267140 & 267979.819544199 & -1736.67874160150 & -839.819544198809 & -0.572582134226973 \tabularnewline
10 & 264993 & 265323.003050931 & -1906.33467108155 & -330.003050931516 & -0.211571373760679 \tabularnewline
11 & 287259 & 280417.130913402 & 1265.66684309408 & 6841.86908659751 & 3.89954991137942 \tabularnewline
12 & 291186 & 290454.505591438 & 2914.69562417399 & 731.494408562216 & 2.0088718445796 \tabularnewline
13 & 292300 & 291827.602669314 & 2635.81462614077 & 472.397330685744 & -0.381768914671608 \tabularnewline
14 & 288186 & 289105.306168242 & 1630.43337354587 & -919.30616824152 & -1.17241415668180 \tabularnewline
15 & 281477 & 285177.447902346 & 601.232352478222 & -3700.44790234588 & -1.19525698085119 \tabularnewline
16 & 282656 & 283202.099905819 & 121.719278756493 & -546.099905818812 & -0.580525201913526 \tabularnewline
17 & 280190 & 281322.896910550 & -253.224981554856 & -1132.89691054965 & -0.451681847842913 \tabularnewline
18 & 280408 & 280363.258527809 & -385.766407594984 & 44.7414721908378 & -0.158669731712760 \tabularnewline
19 & 276836 & 277419.915821799 & -865.538410338143 & -583.915821798573 & -0.574248363255685 \tabularnewline
20 & 275216 & 275491.15769903 & -1065.00033327702 & -275.157699030219 & -0.238969163696083 \tabularnewline
21 & 274352 & 274611.958751139 & -1030.13291846558 & -259.958751139443 & 0.0417967307084539 \tabularnewline
22 & 271311 & 276026.198911086 & -571.326758062151 & -4715.19891108608 & 0.55005764334406 \tabularnewline
23 & 289802 & 282777.257880196 & 802.026312437257 & 7024.74211980361 & 1.64583404226181 \tabularnewline
24 & 290726 & 288224.915851438 & 1670.53224517741 & 2501.08414856235 & 1.04459985922816 \tabularnewline
25 & 292300 & 289964.117576245 & 1683.34735444758 & 2335.88242375478 & 0.015828751956963 \tabularnewline
26 & 278506 & 281998.089648172 & -124.045506568646 & -3492.08964817203 & -2.15946615518098 \tabularnewline
27 & 269826 & 274827.818024539 & -1432.84780051521 & -5001.81802453924 & -1.54256078982195 \tabularnewline
28 & 265861 & 267747.948348433 & -2481.0253160722 & -1886.94834843271 & -1.25987164650344 \tabularnewline
29 & 269034 & 267801.884705637 & -2008.2796636789 & 1232.11529436317 & 0.569696858211719 \tabularnewline
30 & 264176 & 264104.828719529 & -2323.88077131080 & 71.1712804712921 & -0.37826232203378 \tabularnewline
31 & 255198 & 257203.49419422 & -3179.21790478733 & -2005.49419421973 & -1.02322729611630 \tabularnewline
32 & 253353 & 253381.570478368 & -3299.2713841071 & -28.5704783683416 & -0.143704090850896 \tabularnewline
33 & 246057 & 248384.476653014 & -3616.38993146270 & -2327.47665301379 & -0.379863530546178 \tabularnewline
34 & 235372 & 243648.865106564 & -3825.38359246229 & -8276.86510656376 & -0.250373649485884 \tabularnewline
35 & 258556 & 248979.766908410 & -2117.6031672791 & 9576.23309159042 & 2.04668896015447 \tabularnewline
36 & 260993 & 255068.423107095 & -589.408546914742 & 5924.57689290524 & 1.84078304131215 \tabularnewline
37 & 254663 & 251037.498183637 & -1231.03726836792 & 3625.5018163629 & -0.778868184343224 \tabularnewline
38 & 250643 & 250527.036653019 & -1096.54167628592 & 115.963346980907 & 0.161087811175728 \tabularnewline
39 & 243422 & 247730.699337801 & -1412.43090814126 & -4308.69933780114 & -0.375139009225978 \tabularnewline
40 & 247105 & 248642.866147849 & -981.209418361088 & -1537.86614784900 & 0.516878030877219 \tabularnewline
41 & 248541 & 247027.331471033 & -1099.16017245965 & 1513.66852896716 & -0.142032433025296 \tabularnewline
42 & 245039 & 244050.07569262 & -1449.09026577852 & 988.924307379717 & -0.420166870291771 \tabularnewline
43 & 237080 & 239692.625931415 & -1991.14701737445 & -2612.6259314146 & -0.64916543320341 \tabularnewline
44 & 237085 & 236430.49346715 & -2227.95474970988 & 654.506532849932 & -0.283464343975813 \tabularnewline
45 & 225554 & 229940.029080625 & -3021.8753196366 & -4386.02908062471 & -0.950570012871678 \tabularnewline
46 & 226839 & 234615.251741445 & -1589.01479578791 & -7776.25174144547 & 1.71599627009908 \tabularnewline
47 & 247934 & 238931.841920532 & -490.690561779295 & 9002.15807946826 & 1.31711125399326 \tabularnewline
48 & 248333 & 240720.334200147 & -66.9903134920694 & 7612.66579985306 & 0.510186904837453 \tabularnewline
49 & 246969 & 242754.735810031 & 324.151354397860 & 4214.26418996939 & 0.472008393862723 \tabularnewline
50 & 245098 & 244328.766295623 & 556.904166872985 & 769.233704377497 & 0.278817456230623 \tabularnewline
51 & 246263 & 249469.093653788 & 1408.2801782797 & -3206.09365378785 & 1.01476386798951 \tabularnewline
52 & 255765 & 255350.099938604 & 2237.72036605097 & 414.900061396093 & 0.993370973336029 \tabularnewline
53 & 264319 & 260783.557578870 & 2831.00444204526 & 3535.44242113031 & 0.713581227538113 \tabularnewline
54 & 268347 & 265445.582349429 & 3171.47295153149 & 2901.41765057069 & 0.409102347320942 \tabularnewline
55 & 273046 & 272785.381465806 & 3946.95829275335 & 260.618534193956 & 0.929579390203477 \tabularnewline
56 & 273963 & 273978.819154089 & 3434.81370984221 & -15.8191540891989 & -0.613160401588959 \tabularnewline
57 & 267430 & 275520.919933663 & 3082.95113374645 & -8090.91993366284 & -0.421175038917083 \tabularnewline
58 & 271993 & 280665.544586771 & 3465.97178352948 & -8672.54458677142 & 0.458685689751345 \tabularnewline
59 & 292710 & 284488.032369835 & 3532.16319488117 & 8221.96763016541 & 0.0794080017422295 \tabularnewline
60 & 295881 & 288639.682049450 & 3647.18967279553 & 7241.31795054964 & 0.138399093199395 \tabularnewline
61 & 294563 & 291496.436359777 & 3500.26912641378 & 3066.56364022347 & -0.176832484645321 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=111111&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]286602[/C][C]286602[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]283042[/C][C]283653.514678328[/C][C]-194.918781431049[/C][C]-611.514678327863[/C][C]-0.513504172651212[/C][/ROW]
[ROW][C]3[/C][C]276687[/C][C]278738.112107994[/C][C]-633.581801757586[/C][C]-2051.11210799353[/C][C]-1.10580595409501[/C][/ROW]
[ROW][C]4[/C][C]277915[/C][C]277701.909912795[/C][C]-680.252271222706[/C][C]213.090087204625[/C][C]-0.0997065198244274[/C][/ROW]
[ROW][C]5[/C][C]277128[/C][C]277271.530240242[/C][C]-645.890768061875[/C][C]-143.530240241980[/C][C]0.0602327365463566[/C][/ROW]
[ROW][C]6[/C][C]277103[/C][C]277213.666234932[/C][C]-554.779819817128[/C][C]-110.666234931874[/C][C]0.139143721593626[/C][/ROW]
[ROW][C]7[/C][C]275037[/C][C]275809.967354789[/C][C]-696.861674374174[/C][C]-772.967354788608[/C][C]-0.198553808025926[/C][/ROW]
[ROW][C]8[/C][C]270150[/C][C]271748.631096895[/C][C]-1287.72185557428[/C][C]-1598.63109689547[/C][C]-0.78068783645142[/C][/ROW]
[ROW][C]9[/C][C]267140[/C][C]267979.819544199[/C][C]-1736.67874160150[/C][C]-839.819544198809[/C][C]-0.572582134226973[/C][/ROW]
[ROW][C]10[/C][C]264993[/C][C]265323.003050931[/C][C]-1906.33467108155[/C][C]-330.003050931516[/C][C]-0.211571373760679[/C][/ROW]
[ROW][C]11[/C][C]287259[/C][C]280417.130913402[/C][C]1265.66684309408[/C][C]6841.86908659751[/C][C]3.89954991137942[/C][/ROW]
[ROW][C]12[/C][C]291186[/C][C]290454.505591438[/C][C]2914.69562417399[/C][C]731.494408562216[/C][C]2.0088718445796[/C][/ROW]
[ROW][C]13[/C][C]292300[/C][C]291827.602669314[/C][C]2635.81462614077[/C][C]472.397330685744[/C][C]-0.381768914671608[/C][/ROW]
[ROW][C]14[/C][C]288186[/C][C]289105.306168242[/C][C]1630.43337354587[/C][C]-919.30616824152[/C][C]-1.17241415668180[/C][/ROW]
[ROW][C]15[/C][C]281477[/C][C]285177.447902346[/C][C]601.232352478222[/C][C]-3700.44790234588[/C][C]-1.19525698085119[/C][/ROW]
[ROW][C]16[/C][C]282656[/C][C]283202.099905819[/C][C]121.719278756493[/C][C]-546.099905818812[/C][C]-0.580525201913526[/C][/ROW]
[ROW][C]17[/C][C]280190[/C][C]281322.896910550[/C][C]-253.224981554856[/C][C]-1132.89691054965[/C][C]-0.451681847842913[/C][/ROW]
[ROW][C]18[/C][C]280408[/C][C]280363.258527809[/C][C]-385.766407594984[/C][C]44.7414721908378[/C][C]-0.158669731712760[/C][/ROW]
[ROW][C]19[/C][C]276836[/C][C]277419.915821799[/C][C]-865.538410338143[/C][C]-583.915821798573[/C][C]-0.574248363255685[/C][/ROW]
[ROW][C]20[/C][C]275216[/C][C]275491.15769903[/C][C]-1065.00033327702[/C][C]-275.157699030219[/C][C]-0.238969163696083[/C][/ROW]
[ROW][C]21[/C][C]274352[/C][C]274611.958751139[/C][C]-1030.13291846558[/C][C]-259.958751139443[/C][C]0.0417967307084539[/C][/ROW]
[ROW][C]22[/C][C]271311[/C][C]276026.198911086[/C][C]-571.326758062151[/C][C]-4715.19891108608[/C][C]0.55005764334406[/C][/ROW]
[ROW][C]23[/C][C]289802[/C][C]282777.257880196[/C][C]802.026312437257[/C][C]7024.74211980361[/C][C]1.64583404226181[/C][/ROW]
[ROW][C]24[/C][C]290726[/C][C]288224.915851438[/C][C]1670.53224517741[/C][C]2501.08414856235[/C][C]1.04459985922816[/C][/ROW]
[ROW][C]25[/C][C]292300[/C][C]289964.117576245[/C][C]1683.34735444758[/C][C]2335.88242375478[/C][C]0.015828751956963[/C][/ROW]
[ROW][C]26[/C][C]278506[/C][C]281998.089648172[/C][C]-124.045506568646[/C][C]-3492.08964817203[/C][C]-2.15946615518098[/C][/ROW]
[ROW][C]27[/C][C]269826[/C][C]274827.818024539[/C][C]-1432.84780051521[/C][C]-5001.81802453924[/C][C]-1.54256078982195[/C][/ROW]
[ROW][C]28[/C][C]265861[/C][C]267747.948348433[/C][C]-2481.0253160722[/C][C]-1886.94834843271[/C][C]-1.25987164650344[/C][/ROW]
[ROW][C]29[/C][C]269034[/C][C]267801.884705637[/C][C]-2008.2796636789[/C][C]1232.11529436317[/C][C]0.569696858211719[/C][/ROW]
[ROW][C]30[/C][C]264176[/C][C]264104.828719529[/C][C]-2323.88077131080[/C][C]71.1712804712921[/C][C]-0.37826232203378[/C][/ROW]
[ROW][C]31[/C][C]255198[/C][C]257203.49419422[/C][C]-3179.21790478733[/C][C]-2005.49419421973[/C][C]-1.02322729611630[/C][/ROW]
[ROW][C]32[/C][C]253353[/C][C]253381.570478368[/C][C]-3299.2713841071[/C][C]-28.5704783683416[/C][C]-0.143704090850896[/C][/ROW]
[ROW][C]33[/C][C]246057[/C][C]248384.476653014[/C][C]-3616.38993146270[/C][C]-2327.47665301379[/C][C]-0.379863530546178[/C][/ROW]
[ROW][C]34[/C][C]235372[/C][C]243648.865106564[/C][C]-3825.38359246229[/C][C]-8276.86510656376[/C][C]-0.250373649485884[/C][/ROW]
[ROW][C]35[/C][C]258556[/C][C]248979.766908410[/C][C]-2117.6031672791[/C][C]9576.23309159042[/C][C]2.04668896015447[/C][/ROW]
[ROW][C]36[/C][C]260993[/C][C]255068.423107095[/C][C]-589.408546914742[/C][C]5924.57689290524[/C][C]1.84078304131215[/C][/ROW]
[ROW][C]37[/C][C]254663[/C][C]251037.498183637[/C][C]-1231.03726836792[/C][C]3625.5018163629[/C][C]-0.778868184343224[/C][/ROW]
[ROW][C]38[/C][C]250643[/C][C]250527.036653019[/C][C]-1096.54167628592[/C][C]115.963346980907[/C][C]0.161087811175728[/C][/ROW]
[ROW][C]39[/C][C]243422[/C][C]247730.699337801[/C][C]-1412.43090814126[/C][C]-4308.69933780114[/C][C]-0.375139009225978[/C][/ROW]
[ROW][C]40[/C][C]247105[/C][C]248642.866147849[/C][C]-981.209418361088[/C][C]-1537.86614784900[/C][C]0.516878030877219[/C][/ROW]
[ROW][C]41[/C][C]248541[/C][C]247027.331471033[/C][C]-1099.16017245965[/C][C]1513.66852896716[/C][C]-0.142032433025296[/C][/ROW]
[ROW][C]42[/C][C]245039[/C][C]244050.07569262[/C][C]-1449.09026577852[/C][C]988.924307379717[/C][C]-0.420166870291771[/C][/ROW]
[ROW][C]43[/C][C]237080[/C][C]239692.625931415[/C][C]-1991.14701737445[/C][C]-2612.6259314146[/C][C]-0.64916543320341[/C][/ROW]
[ROW][C]44[/C][C]237085[/C][C]236430.49346715[/C][C]-2227.95474970988[/C][C]654.506532849932[/C][C]-0.283464343975813[/C][/ROW]
[ROW][C]45[/C][C]225554[/C][C]229940.029080625[/C][C]-3021.8753196366[/C][C]-4386.02908062471[/C][C]-0.950570012871678[/C][/ROW]
[ROW][C]46[/C][C]226839[/C][C]234615.251741445[/C][C]-1589.01479578791[/C][C]-7776.25174144547[/C][C]1.71599627009908[/C][/ROW]
[ROW][C]47[/C][C]247934[/C][C]238931.841920532[/C][C]-490.690561779295[/C][C]9002.15807946826[/C][C]1.31711125399326[/C][/ROW]
[ROW][C]48[/C][C]248333[/C][C]240720.334200147[/C][C]-66.9903134920694[/C][C]7612.66579985306[/C][C]0.510186904837453[/C][/ROW]
[ROW][C]49[/C][C]246969[/C][C]242754.735810031[/C][C]324.151354397860[/C][C]4214.26418996939[/C][C]0.472008393862723[/C][/ROW]
[ROW][C]50[/C][C]245098[/C][C]244328.766295623[/C][C]556.904166872985[/C][C]769.233704377497[/C][C]0.278817456230623[/C][/ROW]
[ROW][C]51[/C][C]246263[/C][C]249469.093653788[/C][C]1408.2801782797[/C][C]-3206.09365378785[/C][C]1.01476386798951[/C][/ROW]
[ROW][C]52[/C][C]255765[/C][C]255350.099938604[/C][C]2237.72036605097[/C][C]414.900061396093[/C][C]0.993370973336029[/C][/ROW]
[ROW][C]53[/C][C]264319[/C][C]260783.557578870[/C][C]2831.00444204526[/C][C]3535.44242113031[/C][C]0.713581227538113[/C][/ROW]
[ROW][C]54[/C][C]268347[/C][C]265445.582349429[/C][C]3171.47295153149[/C][C]2901.41765057069[/C][C]0.409102347320942[/C][/ROW]
[ROW][C]55[/C][C]273046[/C][C]272785.381465806[/C][C]3946.95829275335[/C][C]260.618534193956[/C][C]0.929579390203477[/C][/ROW]
[ROW][C]56[/C][C]273963[/C][C]273978.819154089[/C][C]3434.81370984221[/C][C]-15.8191540891989[/C][C]-0.613160401588959[/C][/ROW]
[ROW][C]57[/C][C]267430[/C][C]275520.919933663[/C][C]3082.95113374645[/C][C]-8090.91993366284[/C][C]-0.421175038917083[/C][/ROW]
[ROW][C]58[/C][C]271993[/C][C]280665.544586771[/C][C]3465.97178352948[/C][C]-8672.54458677142[/C][C]0.458685689751345[/C][/ROW]
[ROW][C]59[/C][C]292710[/C][C]284488.032369835[/C][C]3532.16319488117[/C][C]8221.96763016541[/C][C]0.0794080017422295[/C][/ROW]
[ROW][C]60[/C][C]295881[/C][C]288639.682049450[/C][C]3647.18967279553[/C][C]7241.31795054964[/C][C]0.138399093199395[/C][/ROW]
[ROW][C]61[/C][C]294563[/C][C]291496.436359777[/C][C]3500.26912641378[/C][C]3066.56364022347[/C][C]-0.176832484645321[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=111111&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=111111&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
1286602286602000
2283042283653.514678328-194.918781431049-611.514678327863-0.513504172651212
3276687278738.112107994-633.581801757586-2051.11210799353-1.10580595409501
4277915277701.909912795-680.252271222706213.090087204625-0.0997065198244274
5277128277271.530240242-645.890768061875-143.5302402419800.0602327365463566
6277103277213.666234932-554.779819817128-110.6662349318740.139143721593626
7275037275809.967354789-696.861674374174-772.967354788608-0.198553808025926
8270150271748.631096895-1287.72185557428-1598.63109689547-0.78068783645142
9267140267979.819544199-1736.67874160150-839.819544198809-0.572582134226973
10264993265323.003050931-1906.33467108155-330.003050931516-0.211571373760679
11287259280417.1309134021265.666843094086841.869086597513.89954991137942
12291186290454.5055914382914.69562417399731.4944085622162.0088718445796
13292300291827.6026693142635.81462614077472.397330685744-0.381768914671608
14288186289105.3061682421630.43337354587-919.30616824152-1.17241415668180
15281477285177.447902346601.232352478222-3700.44790234588-1.19525698085119
16282656283202.099905819121.719278756493-546.099905818812-0.580525201913526
17280190281322.896910550-253.224981554856-1132.89691054965-0.451681847842913
18280408280363.258527809-385.76640759498444.7414721908378-0.158669731712760
19276836277419.915821799-865.538410338143-583.915821798573-0.574248363255685
20275216275491.15769903-1065.00033327702-275.157699030219-0.238969163696083
21274352274611.958751139-1030.13291846558-259.9587511394430.0417967307084539
22271311276026.198911086-571.326758062151-4715.198911086080.55005764334406
23289802282777.257880196802.0263124372577024.742119803611.64583404226181
24290726288224.9158514381670.532245177412501.084148562351.04459985922816
25292300289964.1175762451683.347354447582335.882423754780.015828751956963
26278506281998.089648172-124.045506568646-3492.08964817203-2.15946615518098
27269826274827.818024539-1432.84780051521-5001.81802453924-1.54256078982195
28265861267747.948348433-2481.0253160722-1886.94834843271-1.25987164650344
29269034267801.884705637-2008.27966367891232.115294363170.569696858211719
30264176264104.828719529-2323.8807713108071.1712804712921-0.37826232203378
31255198257203.49419422-3179.21790478733-2005.49419421973-1.02322729611630
32253353253381.570478368-3299.2713841071-28.5704783683416-0.143704090850896
33246057248384.476653014-3616.38993146270-2327.47665301379-0.379863530546178
34235372243648.865106564-3825.38359246229-8276.86510656376-0.250373649485884
35258556248979.766908410-2117.60316727919576.233091590422.04668896015447
36260993255068.423107095-589.4085469147425924.576892905241.84078304131215
37254663251037.498183637-1231.037268367923625.5018163629-0.778868184343224
38250643250527.036653019-1096.54167628592115.9633469809070.161087811175728
39243422247730.699337801-1412.43090814126-4308.69933780114-0.375139009225978
40247105248642.866147849-981.209418361088-1537.866147849000.516878030877219
41248541247027.331471033-1099.160172459651513.66852896716-0.142032433025296
42245039244050.07569262-1449.09026577852988.924307379717-0.420166870291771
43237080239692.625931415-1991.14701737445-2612.6259314146-0.64916543320341
44237085236430.49346715-2227.95474970988654.506532849932-0.283464343975813
45225554229940.029080625-3021.8753196366-4386.02908062471-0.950570012871678
46226839234615.251741445-1589.01479578791-7776.251741445471.71599627009908
47247934238931.841920532-490.6905617792959002.158079468261.31711125399326
48248333240720.334200147-66.99031349206947612.665799853060.510186904837453
49246969242754.735810031324.1513543978604214.264189969390.472008393862723
50245098244328.766295623556.904166872985769.2337043774970.278817456230623
51246263249469.0936537881408.2801782797-3206.093653787851.01476386798951
52255765255350.0999386042237.72036605097414.9000613960930.993370973336029
53264319260783.5575788702831.004442045263535.442421130310.713581227538113
54268347265445.5823494293171.472951531492901.417650570690.409102347320942
55273046272785.3814658063946.95829275335260.6185341939560.929579390203477
56273963273978.8191540893434.81370984221-15.8191540891989-0.613160401588959
57267430275520.9199336633082.95113374645-8090.91993366284-0.421175038917083
58271993280665.5445867713465.97178352948-8672.544586771420.458685689751345
59292710284488.0323698353532.163194881178221.967630165410.0794080017422295
60295881288639.6820494503647.189672795537241.317950549640.138399093199395
61294563291496.4363597773500.269126413783066.56364022347-0.176832484645321



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')