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Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationWed, 29 Dec 2010 13:54:31 +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/29/t1293630769bkxzrmbp0e79zs4.htm/, Retrieved Fri, 03 May 2024 07:08:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116842, Retrieved Fri, 03 May 2024 07:08:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [] [2010-12-29 13:54:31] [0956ee981dded61b2e7128dae94e5715] [Current]
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Dataseries X:
1203.6
1180.59
1156.85
1191.5
1191.33
1234.18
1220.33
1228.81
1207.01
1249.48
1248.29
1280.08
1280.66
1294.87
1310.61
1270.09
1270.2
1276.66
1303.82
1335.85
1377.94
1400.63
1418.3
1438.24
1406.82
1420.86
1482.37
1530.62
1503.35
1455.27
1473.99
1526.75
1549.38
1481.14
1468.36
1378.55
1330.63
1322.7
1385.59
1400.38
1280
1267.38
1282.83
1166.36
968.75
896.24
903.25
825.88
735.09
797.87
872.81
919.14
919.32
987.48
1020.62
1057.08
1036.19
1095.63
1115.1
1073.87
1104.49
1169.43
1186.69
1089.41
1030.71
1101.6
1049.33
1141.2
1183.26
1180.55




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ 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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116842&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116842&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116842&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ 72.249.76.132







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
11203.61203.6000
21180.591181.83054196833-1.47498088467055-1.24054196832557-0.284024198566593
31156.851158.40276492714-3.12916107787666-1.55276492713600-0.462323929741867
41191.51192.014240198130.669401288963926-0.5142401981336060.760616874849795
51191.331192.706119345750.672235173313777-1.376119345753910.000459285838405934
61234.181234.702916563166.58002256633772-0.5229165631573830.835829612692212
71220.331221.972925493253.58378469172501-1.64292549324595-0.387630878363085
81228.811229.811949431794.28068175819037-1.001949431786300.0849579864893268
91207.011208.57725073455-0.0503146153421739-1.56725073455134-0.507481825158163
101249.481249.908594435267.14287248709373-0.4285944352647530.82086059574743
111248.291249.740237348875.8517222871768-1.45023734886888-0.144761539281487
121280.081280.8229019040110.3546672278062-0.7429019040067770.498938923335298
131280.661275.210635474587.646717735135335.44936452542237-0.368327514523855
141294.871294.547499385239.718380819999190.3225006147715850.196293489974706
151310.611311.5565908546011.0353690801396-0.9465908546040940.143751476310473
161270.091270.902944795471.67084497884017-0.812944795468013-1.01702690110898
171270.21270.951844940531.37662636397690-0.75184494052717-0.0319219051988098
181276.661275.838733832332.01395506064450.821266167674290.0690879403785712
191303.821304.037844682686.77107288975171-0.2178446826765580.515363787841715
201335.851334.8944560431211.14856800978610.9555439568842280.474041356286752
211377.941378.5565084674817.0595064661659-0.6165084674798320.639922229899437
221400.631400.0701146183417.86942125375790.5598853816637950.0876659464967215
231418.31419.2901788979518.1150641760275-0.9901788979490440.0265860692238078
241438.241437.8553830544218.19690306283940.3846169455814900.0088557807557456
251406.821413.6207945918510.5832916706126-6.80079459184968-0.901442063586917
261420.861420.595493041469.938276985560370.264506958542139-0.0649279143585996
271482.371479.0504895883018.73755282183573.319510411696060.954465066061165
281530.621529.9119800308424.57501852810370.7080199691557540.630843765579274
291503.351505.4337649505415.6634808200939-2.08376495053548-0.963662637039344
301455.271456.103129238393.85712254199394-0.833129238389272-1.27705335854543
311473.991472.582496715076.149891634063481.407503284926360.248027542212725
321526.751524.2785344479414.42295407070482.471465552061710.895025146735357
331549.381549.4383650303216.3731993238712-0.05836503032343990.210997924800498
341481.141483.127381893751.35429076178113-1.9873818937538-1.62496921053214
351468.361468.60415016739-1.52994286708432-0.244150167388990-0.312080844887497
361378.551379.40970929419-17.4434279596324-0.859709294190633-1.72170130499990
371330.631340.09292393723-21.3880618538749-9.46292393723279-0.451118795166033
381322.71323.57543919964-20.5138341225812-0.8754391996351940.0902442463882552
391385.591380.06514646780-6.569430566659265.524853532197831.51256578428503
401400.381397.76117241646-2.165235473370562.618827583541230.476059988298106
4112801284.23960953062-22.372626527401-4.23960953062272-2.18511249938945
421267.381266.07992115587-21.60820437400811.300078844126440.0826867743341093
431282.831280.91134873228-14.99663868075111.918651267723500.715244094821404
441166.361169.54167044699-32.4820818206898-3.1816704469876-1.89169962196002
45968.75971.730025609308-62.4784000181356-2.98002560930846-3.2453517183306
46896.24896.435677762127-64.8036881421995-0.195677762126545-0.251588995916415
47903.25896.326794186749-53.0650151784276.923205813250831.27015766709631
48825.88827.117635861972-55.9916476971527-1.23763586197186-0.316704900562764
49735.09748.617320251757-60.0573085461071-13.5273202517568-0.456862317864839
50797.87797.734431881375-40.41292405247730.1355681186246342.05604575055323
51872.81864.005074905056-21.11512383931688.804925094944282.09256909221330
52919.14908.016106417033-9.3061982335959411.12389358296661.27685535300450
53919.32922.265054996798-5.03549660036184-2.945054996798040.461805437371435
54987.48985.3269414975817.309651350079472.153058502418621.33538037188976
551020.621014.8190765513911.33088893629815.800923448613960.435030050251917
561057.081050.5177329662515.74819214271916.562267033747150.477902688790586
571036.191038.4751565802710.7104055367327-2.28515658026792-0.545053910784206
581095.631095.2195383743719.05548645263380.4104616256316160.902929730448005
591115.11106.9115197725417.72060588433248.18848022746418-0.144434962164476
601073.871075.521339332238.82681568371132-1.65133933223487-0.962748007605339
611104.491125.3589070086716.2394810504188-20.86890700866780.824107489298788
621169.431172.9618960739721.8911302851220-3.531896073973730.59671510432668
631186.691181.9974596278319.56747693963984.69254037216617-0.251846304781234
641089.411084.97465089641-1.556932449785124.43534910359214-2.28483253462047
651030.711037.89762562787-9.80451386639556-7.18762562786593-0.891833279370407
661101.61095.786272625002.459168660985185.813727374998191.32656148890715
671049.331048.34263486264-6.581181105204950.987365137363155-0.978023875229743
681141.21127.558622082728.9615078688042813.64137791727891.68156261293303
691183.261186.4260945833318.0022741912657-3.166094583331720.97816078291961
701180.551182.2247556223913.9798161313664-1.67475562239472-0.435232562037672

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 1203.6 & 1203.6 & 0 & 0 & 0 \tabularnewline
2 & 1180.59 & 1181.83054196833 & -1.47498088467055 & -1.24054196832557 & -0.284024198566593 \tabularnewline
3 & 1156.85 & 1158.40276492714 & -3.12916107787666 & -1.55276492713600 & -0.462323929741867 \tabularnewline
4 & 1191.5 & 1192.01424019813 & 0.669401288963926 & -0.514240198133606 & 0.760616874849795 \tabularnewline
5 & 1191.33 & 1192.70611934575 & 0.672235173313777 & -1.37611934575391 & 0.000459285838405934 \tabularnewline
6 & 1234.18 & 1234.70291656316 & 6.58002256633772 & -0.522916563157383 & 0.835829612692212 \tabularnewline
7 & 1220.33 & 1221.97292549325 & 3.58378469172501 & -1.64292549324595 & -0.387630878363085 \tabularnewline
8 & 1228.81 & 1229.81194943179 & 4.28068175819037 & -1.00194943178630 & 0.0849579864893268 \tabularnewline
9 & 1207.01 & 1208.57725073455 & -0.0503146153421739 & -1.56725073455134 & -0.507481825158163 \tabularnewline
10 & 1249.48 & 1249.90859443526 & 7.14287248709373 & -0.428594435264753 & 0.82086059574743 \tabularnewline
11 & 1248.29 & 1249.74023734887 & 5.8517222871768 & -1.45023734886888 & -0.144761539281487 \tabularnewline
12 & 1280.08 & 1280.82290190401 & 10.3546672278062 & -0.742901904006777 & 0.498938923335298 \tabularnewline
13 & 1280.66 & 1275.21063547458 & 7.64671773513533 & 5.44936452542237 & -0.368327514523855 \tabularnewline
14 & 1294.87 & 1294.54749938523 & 9.71838081999919 & 0.322500614771585 & 0.196293489974706 \tabularnewline
15 & 1310.61 & 1311.55659085460 & 11.0353690801396 & -0.946590854604094 & 0.143751476310473 \tabularnewline
16 & 1270.09 & 1270.90294479547 & 1.67084497884017 & -0.812944795468013 & -1.01702690110898 \tabularnewline
17 & 1270.2 & 1270.95184494053 & 1.37662636397690 & -0.75184494052717 & -0.0319219051988098 \tabularnewline
18 & 1276.66 & 1275.83873383233 & 2.0139550606445 & 0.82126616767429 & 0.0690879403785712 \tabularnewline
19 & 1303.82 & 1304.03784468268 & 6.77107288975171 & -0.217844682676558 & 0.515363787841715 \tabularnewline
20 & 1335.85 & 1334.89445604312 & 11.1485680097861 & 0.955543956884228 & 0.474041356286752 \tabularnewline
21 & 1377.94 & 1378.55650846748 & 17.0595064661659 & -0.616508467479832 & 0.639922229899437 \tabularnewline
22 & 1400.63 & 1400.07011461834 & 17.8694212537579 & 0.559885381663795 & 0.0876659464967215 \tabularnewline
23 & 1418.3 & 1419.29017889795 & 18.1150641760275 & -0.990178897949044 & 0.0265860692238078 \tabularnewline
24 & 1438.24 & 1437.85538305442 & 18.1969030628394 & 0.384616945581490 & 0.0088557807557456 \tabularnewline
25 & 1406.82 & 1413.62079459185 & 10.5832916706126 & -6.80079459184968 & -0.901442063586917 \tabularnewline
26 & 1420.86 & 1420.59549304146 & 9.93827698556037 & 0.264506958542139 & -0.0649279143585996 \tabularnewline
27 & 1482.37 & 1479.05048958830 & 18.7375528218357 & 3.31951041169606 & 0.954465066061165 \tabularnewline
28 & 1530.62 & 1529.91198003084 & 24.5750185281037 & 0.708019969155754 & 0.630843765579274 \tabularnewline
29 & 1503.35 & 1505.43376495054 & 15.6634808200939 & -2.08376495053548 & -0.963662637039344 \tabularnewline
30 & 1455.27 & 1456.10312923839 & 3.85712254199394 & -0.833129238389272 & -1.27705335854543 \tabularnewline
31 & 1473.99 & 1472.58249671507 & 6.14989163406348 & 1.40750328492636 & 0.248027542212725 \tabularnewline
32 & 1526.75 & 1524.27853444794 & 14.4229540707048 & 2.47146555206171 & 0.895025146735357 \tabularnewline
33 & 1549.38 & 1549.43836503032 & 16.3731993238712 & -0.0583650303234399 & 0.210997924800498 \tabularnewline
34 & 1481.14 & 1483.12738189375 & 1.35429076178113 & -1.9873818937538 & -1.62496921053214 \tabularnewline
35 & 1468.36 & 1468.60415016739 & -1.52994286708432 & -0.244150167388990 & -0.312080844887497 \tabularnewline
36 & 1378.55 & 1379.40970929419 & -17.4434279596324 & -0.859709294190633 & -1.72170130499990 \tabularnewline
37 & 1330.63 & 1340.09292393723 & -21.3880618538749 & -9.46292393723279 & -0.451118795166033 \tabularnewline
38 & 1322.7 & 1323.57543919964 & -20.5138341225812 & -0.875439199635194 & 0.0902442463882552 \tabularnewline
39 & 1385.59 & 1380.06514646780 & -6.56943056665926 & 5.52485353219783 & 1.51256578428503 \tabularnewline
40 & 1400.38 & 1397.76117241646 & -2.16523547337056 & 2.61882758354123 & 0.476059988298106 \tabularnewline
41 & 1280 & 1284.23960953062 & -22.372626527401 & -4.23960953062272 & -2.18511249938945 \tabularnewline
42 & 1267.38 & 1266.07992115587 & -21.6082043740081 & 1.30007884412644 & 0.0826867743341093 \tabularnewline
43 & 1282.83 & 1280.91134873228 & -14.9966386807511 & 1.91865126772350 & 0.715244094821404 \tabularnewline
44 & 1166.36 & 1169.54167044699 & -32.4820818206898 & -3.1816704469876 & -1.89169962196002 \tabularnewline
45 & 968.75 & 971.730025609308 & -62.4784000181356 & -2.98002560930846 & -3.2453517183306 \tabularnewline
46 & 896.24 & 896.435677762127 & -64.8036881421995 & -0.195677762126545 & -0.251588995916415 \tabularnewline
47 & 903.25 & 896.326794186749 & -53.065015178427 & 6.92320581325083 & 1.27015766709631 \tabularnewline
48 & 825.88 & 827.117635861972 & -55.9916476971527 & -1.23763586197186 & -0.316704900562764 \tabularnewline
49 & 735.09 & 748.617320251757 & -60.0573085461071 & -13.5273202517568 & -0.456862317864839 \tabularnewline
50 & 797.87 & 797.734431881375 & -40.4129240524773 & 0.135568118624634 & 2.05604575055323 \tabularnewline
51 & 872.81 & 864.005074905056 & -21.1151238393168 & 8.80492509494428 & 2.09256909221330 \tabularnewline
52 & 919.14 & 908.016106417033 & -9.30619823359594 & 11.1238935829666 & 1.27685535300450 \tabularnewline
53 & 919.32 & 922.265054996798 & -5.03549660036184 & -2.94505499679804 & 0.461805437371435 \tabularnewline
54 & 987.48 & 985.326941497581 & 7.30965135007947 & 2.15305850241862 & 1.33538037188976 \tabularnewline
55 & 1020.62 & 1014.81907655139 & 11.3308889362981 & 5.80092344861396 & 0.435030050251917 \tabularnewline
56 & 1057.08 & 1050.51773296625 & 15.7481921427191 & 6.56226703374715 & 0.477902688790586 \tabularnewline
57 & 1036.19 & 1038.47515658027 & 10.7104055367327 & -2.28515658026792 & -0.545053910784206 \tabularnewline
58 & 1095.63 & 1095.21953837437 & 19.0554864526338 & 0.410461625631616 & 0.902929730448005 \tabularnewline
59 & 1115.1 & 1106.91151977254 & 17.7206058843324 & 8.18848022746418 & -0.144434962164476 \tabularnewline
60 & 1073.87 & 1075.52133933223 & 8.82681568371132 & -1.65133933223487 & -0.962748007605339 \tabularnewline
61 & 1104.49 & 1125.35890700867 & 16.2394810504188 & -20.8689070086678 & 0.824107489298788 \tabularnewline
62 & 1169.43 & 1172.96189607397 & 21.8911302851220 & -3.53189607397373 & 0.59671510432668 \tabularnewline
63 & 1186.69 & 1181.99745962783 & 19.5674769396398 & 4.69254037216617 & -0.251846304781234 \tabularnewline
64 & 1089.41 & 1084.97465089641 & -1.55693244978512 & 4.43534910359214 & -2.28483253462047 \tabularnewline
65 & 1030.71 & 1037.89762562787 & -9.80451386639556 & -7.18762562786593 & -0.891833279370407 \tabularnewline
66 & 1101.6 & 1095.78627262500 & 2.45916866098518 & 5.81372737499819 & 1.32656148890715 \tabularnewline
67 & 1049.33 & 1048.34263486264 & -6.58118110520495 & 0.987365137363155 & -0.978023875229743 \tabularnewline
68 & 1141.2 & 1127.55862208272 & 8.96150786880428 & 13.6413779172789 & 1.68156261293303 \tabularnewline
69 & 1183.26 & 1186.42609458333 & 18.0022741912657 & -3.16609458333172 & 0.97816078291961 \tabularnewline
70 & 1180.55 & 1182.22475562239 & 13.9798161313664 & -1.67475562239472 & -0.435232562037672 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116842&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]1203.6[/C][C]1203.6[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]1180.59[/C][C]1181.83054196833[/C][C]-1.47498088467055[/C][C]-1.24054196832557[/C][C]-0.284024198566593[/C][/ROW]
[ROW][C]3[/C][C]1156.85[/C][C]1158.40276492714[/C][C]-3.12916107787666[/C][C]-1.55276492713600[/C][C]-0.462323929741867[/C][/ROW]
[ROW][C]4[/C][C]1191.5[/C][C]1192.01424019813[/C][C]0.669401288963926[/C][C]-0.514240198133606[/C][C]0.760616874849795[/C][/ROW]
[ROW][C]5[/C][C]1191.33[/C][C]1192.70611934575[/C][C]0.672235173313777[/C][C]-1.37611934575391[/C][C]0.000459285838405934[/C][/ROW]
[ROW][C]6[/C][C]1234.18[/C][C]1234.70291656316[/C][C]6.58002256633772[/C][C]-0.522916563157383[/C][C]0.835829612692212[/C][/ROW]
[ROW][C]7[/C][C]1220.33[/C][C]1221.97292549325[/C][C]3.58378469172501[/C][C]-1.64292549324595[/C][C]-0.387630878363085[/C][/ROW]
[ROW][C]8[/C][C]1228.81[/C][C]1229.81194943179[/C][C]4.28068175819037[/C][C]-1.00194943178630[/C][C]0.0849579864893268[/C][/ROW]
[ROW][C]9[/C][C]1207.01[/C][C]1208.57725073455[/C][C]-0.0503146153421739[/C][C]-1.56725073455134[/C][C]-0.507481825158163[/C][/ROW]
[ROW][C]10[/C][C]1249.48[/C][C]1249.90859443526[/C][C]7.14287248709373[/C][C]-0.428594435264753[/C][C]0.82086059574743[/C][/ROW]
[ROW][C]11[/C][C]1248.29[/C][C]1249.74023734887[/C][C]5.8517222871768[/C][C]-1.45023734886888[/C][C]-0.144761539281487[/C][/ROW]
[ROW][C]12[/C][C]1280.08[/C][C]1280.82290190401[/C][C]10.3546672278062[/C][C]-0.742901904006777[/C][C]0.498938923335298[/C][/ROW]
[ROW][C]13[/C][C]1280.66[/C][C]1275.21063547458[/C][C]7.64671773513533[/C][C]5.44936452542237[/C][C]-0.368327514523855[/C][/ROW]
[ROW][C]14[/C][C]1294.87[/C][C]1294.54749938523[/C][C]9.71838081999919[/C][C]0.322500614771585[/C][C]0.196293489974706[/C][/ROW]
[ROW][C]15[/C][C]1310.61[/C][C]1311.55659085460[/C][C]11.0353690801396[/C][C]-0.946590854604094[/C][C]0.143751476310473[/C][/ROW]
[ROW][C]16[/C][C]1270.09[/C][C]1270.90294479547[/C][C]1.67084497884017[/C][C]-0.812944795468013[/C][C]-1.01702690110898[/C][/ROW]
[ROW][C]17[/C][C]1270.2[/C][C]1270.95184494053[/C][C]1.37662636397690[/C][C]-0.75184494052717[/C][C]-0.0319219051988098[/C][/ROW]
[ROW][C]18[/C][C]1276.66[/C][C]1275.83873383233[/C][C]2.0139550606445[/C][C]0.82126616767429[/C][C]0.0690879403785712[/C][/ROW]
[ROW][C]19[/C][C]1303.82[/C][C]1304.03784468268[/C][C]6.77107288975171[/C][C]-0.217844682676558[/C][C]0.515363787841715[/C][/ROW]
[ROW][C]20[/C][C]1335.85[/C][C]1334.89445604312[/C][C]11.1485680097861[/C][C]0.955543956884228[/C][C]0.474041356286752[/C][/ROW]
[ROW][C]21[/C][C]1377.94[/C][C]1378.55650846748[/C][C]17.0595064661659[/C][C]-0.616508467479832[/C][C]0.639922229899437[/C][/ROW]
[ROW][C]22[/C][C]1400.63[/C][C]1400.07011461834[/C][C]17.8694212537579[/C][C]0.559885381663795[/C][C]0.0876659464967215[/C][/ROW]
[ROW][C]23[/C][C]1418.3[/C][C]1419.29017889795[/C][C]18.1150641760275[/C][C]-0.990178897949044[/C][C]0.0265860692238078[/C][/ROW]
[ROW][C]24[/C][C]1438.24[/C][C]1437.85538305442[/C][C]18.1969030628394[/C][C]0.384616945581490[/C][C]0.0088557807557456[/C][/ROW]
[ROW][C]25[/C][C]1406.82[/C][C]1413.62079459185[/C][C]10.5832916706126[/C][C]-6.80079459184968[/C][C]-0.901442063586917[/C][/ROW]
[ROW][C]26[/C][C]1420.86[/C][C]1420.59549304146[/C][C]9.93827698556037[/C][C]0.264506958542139[/C][C]-0.0649279143585996[/C][/ROW]
[ROW][C]27[/C][C]1482.37[/C][C]1479.05048958830[/C][C]18.7375528218357[/C][C]3.31951041169606[/C][C]0.954465066061165[/C][/ROW]
[ROW][C]28[/C][C]1530.62[/C][C]1529.91198003084[/C][C]24.5750185281037[/C][C]0.708019969155754[/C][C]0.630843765579274[/C][/ROW]
[ROW][C]29[/C][C]1503.35[/C][C]1505.43376495054[/C][C]15.6634808200939[/C][C]-2.08376495053548[/C][C]-0.963662637039344[/C][/ROW]
[ROW][C]30[/C][C]1455.27[/C][C]1456.10312923839[/C][C]3.85712254199394[/C][C]-0.833129238389272[/C][C]-1.27705335854543[/C][/ROW]
[ROW][C]31[/C][C]1473.99[/C][C]1472.58249671507[/C][C]6.14989163406348[/C][C]1.40750328492636[/C][C]0.248027542212725[/C][/ROW]
[ROW][C]32[/C][C]1526.75[/C][C]1524.27853444794[/C][C]14.4229540707048[/C][C]2.47146555206171[/C][C]0.895025146735357[/C][/ROW]
[ROW][C]33[/C][C]1549.38[/C][C]1549.43836503032[/C][C]16.3731993238712[/C][C]-0.0583650303234399[/C][C]0.210997924800498[/C][/ROW]
[ROW][C]34[/C][C]1481.14[/C][C]1483.12738189375[/C][C]1.35429076178113[/C][C]-1.9873818937538[/C][C]-1.62496921053214[/C][/ROW]
[ROW][C]35[/C][C]1468.36[/C][C]1468.60415016739[/C][C]-1.52994286708432[/C][C]-0.244150167388990[/C][C]-0.312080844887497[/C][/ROW]
[ROW][C]36[/C][C]1378.55[/C][C]1379.40970929419[/C][C]-17.4434279596324[/C][C]-0.859709294190633[/C][C]-1.72170130499990[/C][/ROW]
[ROW][C]37[/C][C]1330.63[/C][C]1340.09292393723[/C][C]-21.3880618538749[/C][C]-9.46292393723279[/C][C]-0.451118795166033[/C][/ROW]
[ROW][C]38[/C][C]1322.7[/C][C]1323.57543919964[/C][C]-20.5138341225812[/C][C]-0.875439199635194[/C][C]0.0902442463882552[/C][/ROW]
[ROW][C]39[/C][C]1385.59[/C][C]1380.06514646780[/C][C]-6.56943056665926[/C][C]5.52485353219783[/C][C]1.51256578428503[/C][/ROW]
[ROW][C]40[/C][C]1400.38[/C][C]1397.76117241646[/C][C]-2.16523547337056[/C][C]2.61882758354123[/C][C]0.476059988298106[/C][/ROW]
[ROW][C]41[/C][C]1280[/C][C]1284.23960953062[/C][C]-22.372626527401[/C][C]-4.23960953062272[/C][C]-2.18511249938945[/C][/ROW]
[ROW][C]42[/C][C]1267.38[/C][C]1266.07992115587[/C][C]-21.6082043740081[/C][C]1.30007884412644[/C][C]0.0826867743341093[/C][/ROW]
[ROW][C]43[/C][C]1282.83[/C][C]1280.91134873228[/C][C]-14.9966386807511[/C][C]1.91865126772350[/C][C]0.715244094821404[/C][/ROW]
[ROW][C]44[/C][C]1166.36[/C][C]1169.54167044699[/C][C]-32.4820818206898[/C][C]-3.1816704469876[/C][C]-1.89169962196002[/C][/ROW]
[ROW][C]45[/C][C]968.75[/C][C]971.730025609308[/C][C]-62.4784000181356[/C][C]-2.98002560930846[/C][C]-3.2453517183306[/C][/ROW]
[ROW][C]46[/C][C]896.24[/C][C]896.435677762127[/C][C]-64.8036881421995[/C][C]-0.195677762126545[/C][C]-0.251588995916415[/C][/ROW]
[ROW][C]47[/C][C]903.25[/C][C]896.326794186749[/C][C]-53.065015178427[/C][C]6.92320581325083[/C][C]1.27015766709631[/C][/ROW]
[ROW][C]48[/C][C]825.88[/C][C]827.117635861972[/C][C]-55.9916476971527[/C][C]-1.23763586197186[/C][C]-0.316704900562764[/C][/ROW]
[ROW][C]49[/C][C]735.09[/C][C]748.617320251757[/C][C]-60.0573085461071[/C][C]-13.5273202517568[/C][C]-0.456862317864839[/C][/ROW]
[ROW][C]50[/C][C]797.87[/C][C]797.734431881375[/C][C]-40.4129240524773[/C][C]0.135568118624634[/C][C]2.05604575055323[/C][/ROW]
[ROW][C]51[/C][C]872.81[/C][C]864.005074905056[/C][C]-21.1151238393168[/C][C]8.80492509494428[/C][C]2.09256909221330[/C][/ROW]
[ROW][C]52[/C][C]919.14[/C][C]908.016106417033[/C][C]-9.30619823359594[/C][C]11.1238935829666[/C][C]1.27685535300450[/C][/ROW]
[ROW][C]53[/C][C]919.32[/C][C]922.265054996798[/C][C]-5.03549660036184[/C][C]-2.94505499679804[/C][C]0.461805437371435[/C][/ROW]
[ROW][C]54[/C][C]987.48[/C][C]985.326941497581[/C][C]7.30965135007947[/C][C]2.15305850241862[/C][C]1.33538037188976[/C][/ROW]
[ROW][C]55[/C][C]1020.62[/C][C]1014.81907655139[/C][C]11.3308889362981[/C][C]5.80092344861396[/C][C]0.435030050251917[/C][/ROW]
[ROW][C]56[/C][C]1057.08[/C][C]1050.51773296625[/C][C]15.7481921427191[/C][C]6.56226703374715[/C][C]0.477902688790586[/C][/ROW]
[ROW][C]57[/C][C]1036.19[/C][C]1038.47515658027[/C][C]10.7104055367327[/C][C]-2.28515658026792[/C][C]-0.545053910784206[/C][/ROW]
[ROW][C]58[/C][C]1095.63[/C][C]1095.21953837437[/C][C]19.0554864526338[/C][C]0.410461625631616[/C][C]0.902929730448005[/C][/ROW]
[ROW][C]59[/C][C]1115.1[/C][C]1106.91151977254[/C][C]17.7206058843324[/C][C]8.18848022746418[/C][C]-0.144434962164476[/C][/ROW]
[ROW][C]60[/C][C]1073.87[/C][C]1075.52133933223[/C][C]8.82681568371132[/C][C]-1.65133933223487[/C][C]-0.962748007605339[/C][/ROW]
[ROW][C]61[/C][C]1104.49[/C][C]1125.35890700867[/C][C]16.2394810504188[/C][C]-20.8689070086678[/C][C]0.824107489298788[/C][/ROW]
[ROW][C]62[/C][C]1169.43[/C][C]1172.96189607397[/C][C]21.8911302851220[/C][C]-3.53189607397373[/C][C]0.59671510432668[/C][/ROW]
[ROW][C]63[/C][C]1186.69[/C][C]1181.99745962783[/C][C]19.5674769396398[/C][C]4.69254037216617[/C][C]-0.251846304781234[/C][/ROW]
[ROW][C]64[/C][C]1089.41[/C][C]1084.97465089641[/C][C]-1.55693244978512[/C][C]4.43534910359214[/C][C]-2.28483253462047[/C][/ROW]
[ROW][C]65[/C][C]1030.71[/C][C]1037.89762562787[/C][C]-9.80451386639556[/C][C]-7.18762562786593[/C][C]-0.891833279370407[/C][/ROW]
[ROW][C]66[/C][C]1101.6[/C][C]1095.78627262500[/C][C]2.45916866098518[/C][C]5.81372737499819[/C][C]1.32656148890715[/C][/ROW]
[ROW][C]67[/C][C]1049.33[/C][C]1048.34263486264[/C][C]-6.58118110520495[/C][C]0.987365137363155[/C][C]-0.978023875229743[/C][/ROW]
[ROW][C]68[/C][C]1141.2[/C][C]1127.55862208272[/C][C]8.96150786880428[/C][C]13.6413779172789[/C][C]1.68156261293303[/C][/ROW]
[ROW][C]69[/C][C]1183.26[/C][C]1186.42609458333[/C][C]18.0022741912657[/C][C]-3.16609458333172[/C][C]0.97816078291961[/C][/ROW]
[ROW][C]70[/C][C]1180.55[/C][C]1182.22475562239[/C][C]13.9798161313664[/C][C]-1.67475562239472[/C][C]-0.435232562037672[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116842&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116842&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
11203.61203.6000
21180.591181.83054196833-1.47498088467055-1.24054196832557-0.284024198566593
31156.851158.40276492714-3.12916107787666-1.55276492713600-0.462323929741867
41191.51192.014240198130.669401288963926-0.5142401981336060.760616874849795
51191.331192.706119345750.672235173313777-1.376119345753910.000459285838405934
61234.181234.702916563166.58002256633772-0.5229165631573830.835829612692212
71220.331221.972925493253.58378469172501-1.64292549324595-0.387630878363085
81228.811229.811949431794.28068175819037-1.001949431786300.0849579864893268
91207.011208.57725073455-0.0503146153421739-1.56725073455134-0.507481825158163
101249.481249.908594435267.14287248709373-0.4285944352647530.82086059574743
111248.291249.740237348875.8517222871768-1.45023734886888-0.144761539281487
121280.081280.8229019040110.3546672278062-0.7429019040067770.498938923335298
131280.661275.210635474587.646717735135335.44936452542237-0.368327514523855
141294.871294.547499385239.718380819999190.3225006147715850.196293489974706
151310.611311.5565908546011.0353690801396-0.9465908546040940.143751476310473
161270.091270.902944795471.67084497884017-0.812944795468013-1.01702690110898
171270.21270.951844940531.37662636397690-0.75184494052717-0.0319219051988098
181276.661275.838733832332.01395506064450.821266167674290.0690879403785712
191303.821304.037844682686.77107288975171-0.2178446826765580.515363787841715
201335.851334.8944560431211.14856800978610.9555439568842280.474041356286752
211377.941378.5565084674817.0595064661659-0.6165084674798320.639922229899437
221400.631400.0701146183417.86942125375790.5598853816637950.0876659464967215
231418.31419.2901788979518.1150641760275-0.9901788979490440.0265860692238078
241438.241437.8553830544218.19690306283940.3846169455814900.0088557807557456
251406.821413.6207945918510.5832916706126-6.80079459184968-0.901442063586917
261420.861420.595493041469.938276985560370.264506958542139-0.0649279143585996
271482.371479.0504895883018.73755282183573.319510411696060.954465066061165
281530.621529.9119800308424.57501852810370.7080199691557540.630843765579274
291503.351505.4337649505415.6634808200939-2.08376495053548-0.963662637039344
301455.271456.103129238393.85712254199394-0.833129238389272-1.27705335854543
311473.991472.582496715076.149891634063481.407503284926360.248027542212725
321526.751524.2785344479414.42295407070482.471465552061710.895025146735357
331549.381549.4383650303216.3731993238712-0.05836503032343990.210997924800498
341481.141483.127381893751.35429076178113-1.9873818937538-1.62496921053214
351468.361468.60415016739-1.52994286708432-0.244150167388990-0.312080844887497
361378.551379.40970929419-17.4434279596324-0.859709294190633-1.72170130499990
371330.631340.09292393723-21.3880618538749-9.46292393723279-0.451118795166033
381322.71323.57543919964-20.5138341225812-0.8754391996351940.0902442463882552
391385.591380.06514646780-6.569430566659265.524853532197831.51256578428503
401400.381397.76117241646-2.165235473370562.618827583541230.476059988298106
4112801284.23960953062-22.372626527401-4.23960953062272-2.18511249938945
421267.381266.07992115587-21.60820437400811.300078844126440.0826867743341093
431282.831280.91134873228-14.99663868075111.918651267723500.715244094821404
441166.361169.54167044699-32.4820818206898-3.1816704469876-1.89169962196002
45968.75971.730025609308-62.4784000181356-2.98002560930846-3.2453517183306
46896.24896.435677762127-64.8036881421995-0.195677762126545-0.251588995916415
47903.25896.326794186749-53.0650151784276.923205813250831.27015766709631
48825.88827.117635861972-55.9916476971527-1.23763586197186-0.316704900562764
49735.09748.617320251757-60.0573085461071-13.5273202517568-0.456862317864839
50797.87797.734431881375-40.41292405247730.1355681186246342.05604575055323
51872.81864.005074905056-21.11512383931688.804925094944282.09256909221330
52919.14908.016106417033-9.3061982335959411.12389358296661.27685535300450
53919.32922.265054996798-5.03549660036184-2.945054996798040.461805437371435
54987.48985.3269414975817.309651350079472.153058502418621.33538037188976
551020.621014.8190765513911.33088893629815.800923448613960.435030050251917
561057.081050.5177329662515.74819214271916.562267033747150.477902688790586
571036.191038.4751565802710.7104055367327-2.28515658026792-0.545053910784206
581095.631095.2195383743719.05548645263380.4104616256316160.902929730448005
591115.11106.9115197725417.72060588433248.18848022746418-0.144434962164476
601073.871075.521339332238.82681568371132-1.65133933223487-0.962748007605339
611104.491125.3589070086716.2394810504188-20.86890700866780.824107489298788
621169.431172.9618960739721.8911302851220-3.531896073973730.59671510432668
631186.691181.9974596278319.56747693963984.69254037216617-0.251846304781234
641089.411084.97465089641-1.556932449785124.43534910359214-2.28483253462047
651030.711037.89762562787-9.80451386639556-7.18762562786593-0.891833279370407
661101.61095.786272625002.459168660985185.813727374998191.32656148890715
671049.331048.34263486264-6.581181105204950.987365137363155-0.978023875229743
681141.21127.558622082728.9615078688042813.64137791727891.68156261293303
691183.261186.4260945833318.0022741912657-3.166094583331720.97816078291961
701180.551182.2247556223913.9798161313664-1.67475562239472-0.435232562037672



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')