FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 01 Dec 2009 10:50:31 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/01/t1259689891oxec2lt1smv9nue.htm/, Retrieved Fri, 26 Apr 2024 02:22:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=62150, Retrieved Fri, 26 Apr 2024 02:22:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Structural Time Series Models] [] [2009-11-27 15:02:30] [b98453cac15ba1066b407e146608df68]
-    D      [Structural Time Series Models] [ws8] [2009-12-01 17:50:31] [a931a0a30926b49d162330b43e89b999] [Current]
-    D        [Structural Time Series Models] [verbetering workshop] [2009-12-05 16:00:54] [757146c69eaf0537be37c7b0c18216d8]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
325412
326011
328282
317480
317539
313737
312276
309391
302950
300316
304035
333476
337698
335932
323931
313927
314485
313218
309664
302963
298989
298423
310631
329765
335083
327616
309119
295916
291413
291542
284678
276475
272566
264981
263290
296806
303598
286994
276427
266424
267153
268381
262522
255542
253158
243803
250741
280445
285257
270976
261076
255603
260376
263903
264291
263276
262572
256167
264221
293860
300713
287224

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62150&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62150&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62150&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
1325412325412000
2326011325942.55084104627.752756355036068.44915895355620.0495217931639672
3328282327718.72094753176.5255332056774563.2790524688350.251364284016571
4317480319986.2585188027.48005821959097-2506.25851880216-1.17182663707953
5317539317443.820704185-5.7879503770284295.1792958145417-0.382385070780442
6313737314384.460827008-22.9290117275542-647.460827007662-0.457691395941157
7312276312519.657431044-34.0127038343482-243.657431043558-0.276031371176660
8309391309980.391879649-49.2462602436357-589.391879649354-0.375443784236939
9302950304397.933526114-82.6566969766221-1447.93352611425-0.82922368442539
10300316300840.562711304-103.476525562518-524.562711303572-0.520727406257012
11304035303054.478701094-89.6800411153306980.521298906120.347285143547759
12333476326654.12308346950.51895564382656821.876916530613.55004922769262
13337698335235.919206305-266.8622256577712462.080793694621.45510683699584
14335932336715.200068716-242.484768370612-783.2000687157710.241364074838444
15323931326237.26315566-433.235918536539-2306.26315566009-1.45975595457309
16313927318390.442015713-507.018859113401-4463.44201571332-1.10617165519554
17314485314626.291099368-522.396857989932-141.291099368494-0.488189608088228
18313218313748.761252682-523.648132440838-530.761252681949-0.0532020740281788
19309664310805.376437261-532.588714541077-1141.37643726096-0.362366830012397
20302963304558.933564481-555.255229640237-1595.93356448105-0.855544881056838
21298989300238.041429651-570.987028556055-1249.04142965143-0.563874815798923
22298423299128.510390822-573.350834141211-705.510390822258-0.0806688149030882
23310631310613.566440552-528.00973337962917.43355944757971.80596068903270
24329765322025.222928121-539.4544753219857739.777071879231.78781619906444
25335083329559.115401028-631.820253073065523.884598972291.25528891756047
26327616326666.588822281-644.617825091323949.411177718565-0.329645300284093
27309119314118.819384524-794.790093684242-4999.81938452365-1.71829631337343
28295916303114.825186792-892.576431540558-7198.8251867916-1.51571341892716
29291413294177.456320278-936.38099634766-2764.45632027818-1.20466977238556
30291542291407.589022158-942.811519159777134.410977841569-0.274670469893185
31284678285795.125263775-957.554687138183-1117.12526377512-0.699316228857779
32276475278771.405241583-978.141342447736-2296.4052415833-0.908305506633994
33272566274508.135275656-990.302102731672-1942.13527565565-0.491951414355052
34264981270422.713778753-1001.49868001539-5441.71377875314-0.463557031641652
35263290267626.089017881-1005.31407252620-4336.08901788113-0.268634185383439
36296806283793.078293823-1034.2282590905913012.92170617742.57470227497034
37303598293129.320970829-1080.6289020562810468.67902917071.57351518540293
38286994285471.127444624-1103.640610728221522.87255537598-0.970935668730854
39276427279858.112439805-1144.26277097603-3431.11243980523-0.657801796744838
40266424273542.62937679-1188.01010664923-7118.62937678974-0.766155339360943
41267153270130.176656009-1200.75931559783-2977.17665600925-0.332625262009254
42268381267359.699037066-1206.726870332441021.30096293444-0.235117805719063
43262522262992.919536849-1216.59631580056-470.919536849454-0.473299442041557
44255542257929.397263980-1228.70437671734-2387.39726398050-0.576123204837344
45253158254454.899598956-1236.03022317791-1296.89959895595-0.336340294217171
46243803250362.364671481-1244.14280049282-6559.36467148068-0.427674492397063
47250741257031.440444633-1234.21333799261-6290.440444632841.18382262104702
48280445266336.422067546-1246.8788919919914108.57793245411.57987078392883
49285257270928.060782321-1256.8000400736214328.93921767920.878027098654857
50270976268845.370561896-1259.163113005852130.62943810352-0.122374520755582
51261076264450.422250399-1280.71886264754-3374.42225039899-0.460536676492489
52255603262408.423617773-1286.28569560455-6805.42361777327-0.112765499690225
53260376262351.837292276-1279.31811543432-1975.837292275950.183644742211955
54263903261637.353775415-1277.035798376212265.646224584990.0845747778931377
55264291262485.069912478-1270.196655580591805.930087522110.318263581732331
56263276263710.672990517-1262.7174509006-434.6729905171240.373832364138744
57262572263126.060137877-1260.78421610747-554.0601378773820.101553242562512
58256167264490.021168332-1254.91654979578-8323.021168332020.392855592228209
59264221270948.083393656-1248.20419905592-6727.083393656121.15377719506950
60293860278477.38456098-1253.6066393701615382.61543902021.31483654014780
61300713284007.174677601-1256.0876076161216705.82532239851.01617355692354
62287224284283.511451435-1252.056783041842940.488548564940.227438010041143

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 325412 & 325412 & 0 & 0 & 0 \tabularnewline
2 & 326011 & 325942.550841046 & 27.7527563550360 & 68.4491589535562 & 0.0495217931639672 \tabularnewline
3 & 328282 & 327718.720947531 & 76.5255332056774 & 563.279052468835 & 0.251364284016571 \tabularnewline
4 & 317480 & 319986.258518802 & 7.48005821959097 & -2506.25851880216 & -1.17182663707953 \tabularnewline
5 & 317539 & 317443.820704185 & -5.78795037702842 & 95.1792958145417 & -0.382385070780442 \tabularnewline
6 & 313737 & 314384.460827008 & -22.9290117275542 & -647.460827007662 & -0.457691395941157 \tabularnewline
7 & 312276 & 312519.657431044 & -34.0127038343482 & -243.657431043558 & -0.276031371176660 \tabularnewline
8 & 309391 & 309980.391879649 & -49.2462602436357 & -589.391879649354 & -0.375443784236939 \tabularnewline
9 & 302950 & 304397.933526114 & -82.6566969766221 & -1447.93352611425 & -0.82922368442539 \tabularnewline
10 & 300316 & 300840.562711304 & -103.476525562518 & -524.562711303572 & -0.520727406257012 \tabularnewline
11 & 304035 & 303054.478701094 & -89.6800411153306 & 980.52129890612 & 0.347285143547759 \tabularnewline
12 & 333476 & 326654.123083469 & 50.5189556438265 & 6821.87691653061 & 3.55004922769262 \tabularnewline
13 & 337698 & 335235.919206305 & -266.862225657771 & 2462.08079369462 & 1.45510683699584 \tabularnewline
14 & 335932 & 336715.200068716 & -242.484768370612 & -783.200068715771 & 0.241364074838444 \tabularnewline
15 & 323931 & 326237.26315566 & -433.235918536539 & -2306.26315566009 & -1.45975595457309 \tabularnewline
16 & 313927 & 318390.442015713 & -507.018859113401 & -4463.44201571332 & -1.10617165519554 \tabularnewline
17 & 314485 & 314626.291099368 & -522.396857989932 & -141.291099368494 & -0.488189608088228 \tabularnewline
18 & 313218 & 313748.761252682 & -523.648132440838 & -530.761252681949 & -0.0532020740281788 \tabularnewline
19 & 309664 & 310805.376437261 & -532.588714541077 & -1141.37643726096 & -0.362366830012397 \tabularnewline
20 & 302963 & 304558.933564481 & -555.255229640237 & -1595.93356448105 & -0.855544881056838 \tabularnewline
21 & 298989 & 300238.041429651 & -570.987028556055 & -1249.04142965143 & -0.563874815798923 \tabularnewline
22 & 298423 & 299128.510390822 & -573.350834141211 & -705.510390822258 & -0.0806688149030882 \tabularnewline
23 & 310631 & 310613.566440552 & -528.009733379629 & 17.4335594475797 & 1.80596068903270 \tabularnewline
24 & 329765 & 322025.222928121 & -539.454475321985 & 7739.77707187923 & 1.78781619906444 \tabularnewline
25 & 335083 & 329559.115401028 & -631.82025307306 & 5523.88459897229 & 1.25528891756047 \tabularnewline
26 & 327616 & 326666.588822281 & -644.617825091323 & 949.411177718565 & -0.329645300284093 \tabularnewline
27 & 309119 & 314118.819384524 & -794.790093684242 & -4999.81938452365 & -1.71829631337343 \tabularnewline
28 & 295916 & 303114.825186792 & -892.576431540558 & -7198.8251867916 & -1.51571341892716 \tabularnewline
29 & 291413 & 294177.456320278 & -936.38099634766 & -2764.45632027818 & -1.20466977238556 \tabularnewline
30 & 291542 & 291407.589022158 & -942.811519159777 & 134.410977841569 & -0.274670469893185 \tabularnewline
31 & 284678 & 285795.125263775 & -957.554687138183 & -1117.12526377512 & -0.699316228857779 \tabularnewline
32 & 276475 & 278771.405241583 & -978.141342447736 & -2296.4052415833 & -0.908305506633994 \tabularnewline
33 & 272566 & 274508.135275656 & -990.302102731672 & -1942.13527565565 & -0.491951414355052 \tabularnewline
34 & 264981 & 270422.713778753 & -1001.49868001539 & -5441.71377875314 & -0.463557031641652 \tabularnewline
35 & 263290 & 267626.089017881 & -1005.31407252620 & -4336.08901788113 & -0.268634185383439 \tabularnewline
36 & 296806 & 283793.078293823 & -1034.22825909059 & 13012.9217061774 & 2.57470227497034 \tabularnewline
37 & 303598 & 293129.320970829 & -1080.62890205628 & 10468.6790291707 & 1.57351518540293 \tabularnewline
38 & 286994 & 285471.127444624 & -1103.64061072822 & 1522.87255537598 & -0.970935668730854 \tabularnewline
39 & 276427 & 279858.112439805 & -1144.26277097603 & -3431.11243980523 & -0.657801796744838 \tabularnewline
40 & 266424 & 273542.62937679 & -1188.01010664923 & -7118.62937678974 & -0.766155339360943 \tabularnewline
41 & 267153 & 270130.176656009 & -1200.75931559783 & -2977.17665600925 & -0.332625262009254 \tabularnewline
42 & 268381 & 267359.699037066 & -1206.72687033244 & 1021.30096293444 & -0.235117805719063 \tabularnewline
43 & 262522 & 262992.919536849 & -1216.59631580056 & -470.919536849454 & -0.473299442041557 \tabularnewline
44 & 255542 & 257929.397263980 & -1228.70437671734 & -2387.39726398050 & -0.576123204837344 \tabularnewline
45 & 253158 & 254454.899598956 & -1236.03022317791 & -1296.89959895595 & -0.336340294217171 \tabularnewline
46 & 243803 & 250362.364671481 & -1244.14280049282 & -6559.36467148068 & -0.427674492397063 \tabularnewline
47 & 250741 & 257031.440444633 & -1234.21333799261 & -6290.44044463284 & 1.18382262104702 \tabularnewline
48 & 280445 & 266336.422067546 & -1246.87889199199 & 14108.5779324541 & 1.57987078392883 \tabularnewline
49 & 285257 & 270928.060782321 & -1256.80004007362 & 14328.9392176792 & 0.878027098654857 \tabularnewline
50 & 270976 & 268845.370561896 & -1259.16311300585 & 2130.62943810352 & -0.122374520755582 \tabularnewline
51 & 261076 & 264450.422250399 & -1280.71886264754 & -3374.42225039899 & -0.460536676492489 \tabularnewline
52 & 255603 & 262408.423617773 & -1286.28569560455 & -6805.42361777327 & -0.112765499690225 \tabularnewline
53 & 260376 & 262351.837292276 & -1279.31811543432 & -1975.83729227595 & 0.183644742211955 \tabularnewline
54 & 263903 & 261637.353775415 & -1277.03579837621 & 2265.64622458499 & 0.0845747778931377 \tabularnewline
55 & 264291 & 262485.069912478 & -1270.19665558059 & 1805.93008752211 & 0.318263581732331 \tabularnewline
56 & 263276 & 263710.672990517 & -1262.7174509006 & -434.672990517124 & 0.373832364138744 \tabularnewline
57 & 262572 & 263126.060137877 & -1260.78421610747 & -554.060137877382 & 0.101553242562512 \tabularnewline
58 & 256167 & 264490.021168332 & -1254.91654979578 & -8323.02116833202 & 0.392855592228209 \tabularnewline
59 & 264221 & 270948.083393656 & -1248.20419905592 & -6727.08339365612 & 1.15377719506950 \tabularnewline
60 & 293860 & 278477.38456098 & -1253.60663937016 & 15382.6154390202 & 1.31483654014780 \tabularnewline
61 & 300713 & 284007.174677601 & -1256.08760761612 & 16705.8253223985 & 1.01617355692354 \tabularnewline
62 & 287224 & 284283.511451435 & -1252.05678304184 & 2940.48854856494 & 0.227438010041143 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=62150&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]325412[/C][C]325412[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]326011[/C][C]325942.550841046[/C][C]27.7527563550360[/C][C]68.4491589535562[/C][C]0.0495217931639672[/C][/ROW]
[ROW][C]3[/C][C]328282[/C][C]327718.720947531[/C][C]76.5255332056774[/C][C]563.279052468835[/C][C]0.251364284016571[/C][/ROW]
[ROW][C]4[/C][C]317480[/C][C]319986.258518802[/C][C]7.48005821959097[/C][C]-2506.25851880216[/C][C]-1.17182663707953[/C][/ROW]
[ROW][C]5[/C][C]317539[/C][C]317443.820704185[/C][C]-5.78795037702842[/C][C]95.1792958145417[/C][C]-0.382385070780442[/C][/ROW]
[ROW][C]6[/C][C]313737[/C][C]314384.460827008[/C][C]-22.9290117275542[/C][C]-647.460827007662[/C][C]-0.457691395941157[/C][/ROW]
[ROW][C]7[/C][C]312276[/C][C]312519.657431044[/C][C]-34.0127038343482[/C][C]-243.657431043558[/C][C]-0.276031371176660[/C][/ROW]
[ROW][C]8[/C][C]309391[/C][C]309980.391879649[/C][C]-49.2462602436357[/C][C]-589.391879649354[/C][C]-0.375443784236939[/C][/ROW]
[ROW][C]9[/C][C]302950[/C][C]304397.933526114[/C][C]-82.6566969766221[/C][C]-1447.93352611425[/C][C]-0.82922368442539[/C][/ROW]
[ROW][C]10[/C][C]300316[/C][C]300840.562711304[/C][C]-103.476525562518[/C][C]-524.562711303572[/C][C]-0.520727406257012[/C][/ROW]
[ROW][C]11[/C][C]304035[/C][C]303054.478701094[/C][C]-89.6800411153306[/C][C]980.52129890612[/C][C]0.347285143547759[/C][/ROW]
[ROW][C]12[/C][C]333476[/C][C]326654.123083469[/C][C]50.5189556438265[/C][C]6821.87691653061[/C][C]3.55004922769262[/C][/ROW]
[ROW][C]13[/C][C]337698[/C][C]335235.919206305[/C][C]-266.862225657771[/C][C]2462.08079369462[/C][C]1.45510683699584[/C][/ROW]
[ROW][C]14[/C][C]335932[/C][C]336715.200068716[/C][C]-242.484768370612[/C][C]-783.200068715771[/C][C]0.241364074838444[/C][/ROW]
[ROW][C]15[/C][C]323931[/C][C]326237.26315566[/C][C]-433.235918536539[/C][C]-2306.26315566009[/C][C]-1.45975595457309[/C][/ROW]
[ROW][C]16[/C][C]313927[/C][C]318390.442015713[/C][C]-507.018859113401[/C][C]-4463.44201571332[/C][C]-1.10617165519554[/C][/ROW]
[ROW][C]17[/C][C]314485[/C][C]314626.291099368[/C][C]-522.396857989932[/C][C]-141.291099368494[/C][C]-0.488189608088228[/C][/ROW]
[ROW][C]18[/C][C]313218[/C][C]313748.761252682[/C][C]-523.648132440838[/C][C]-530.761252681949[/C][C]-0.0532020740281788[/C][/ROW]
[ROW][C]19[/C][C]309664[/C][C]310805.376437261[/C][C]-532.588714541077[/C][C]-1141.37643726096[/C][C]-0.362366830012397[/C][/ROW]
[ROW][C]20[/C][C]302963[/C][C]304558.933564481[/C][C]-555.255229640237[/C][C]-1595.93356448105[/C][C]-0.855544881056838[/C][/ROW]
[ROW][C]21[/C][C]298989[/C][C]300238.041429651[/C][C]-570.987028556055[/C][C]-1249.04142965143[/C][C]-0.563874815798923[/C][/ROW]
[ROW][C]22[/C][C]298423[/C][C]299128.510390822[/C][C]-573.350834141211[/C][C]-705.510390822258[/C][C]-0.0806688149030882[/C][/ROW]
[ROW][C]23[/C][C]310631[/C][C]310613.566440552[/C][C]-528.009733379629[/C][C]17.4335594475797[/C][C]1.80596068903270[/C][/ROW]
[ROW][C]24[/C][C]329765[/C][C]322025.222928121[/C][C]-539.454475321985[/C][C]7739.77707187923[/C][C]1.78781619906444[/C][/ROW]
[ROW][C]25[/C][C]335083[/C][C]329559.115401028[/C][C]-631.82025307306[/C][C]5523.88459897229[/C][C]1.25528891756047[/C][/ROW]
[ROW][C]26[/C][C]327616[/C][C]326666.588822281[/C][C]-644.617825091323[/C][C]949.411177718565[/C][C]-0.329645300284093[/C][/ROW]
[ROW][C]27[/C][C]309119[/C][C]314118.819384524[/C][C]-794.790093684242[/C][C]-4999.81938452365[/C][C]-1.71829631337343[/C][/ROW]
[ROW][C]28[/C][C]295916[/C][C]303114.825186792[/C][C]-892.576431540558[/C][C]-7198.8251867916[/C][C]-1.51571341892716[/C][/ROW]
[ROW][C]29[/C][C]291413[/C][C]294177.456320278[/C][C]-936.38099634766[/C][C]-2764.45632027818[/C][C]-1.20466977238556[/C][/ROW]
[ROW][C]30[/C][C]291542[/C][C]291407.589022158[/C][C]-942.811519159777[/C][C]134.410977841569[/C][C]-0.274670469893185[/C][/ROW]
[ROW][C]31[/C][C]284678[/C][C]285795.125263775[/C][C]-957.554687138183[/C][C]-1117.12526377512[/C][C]-0.699316228857779[/C][/ROW]
[ROW][C]32[/C][C]276475[/C][C]278771.405241583[/C][C]-978.141342447736[/C][C]-2296.4052415833[/C][C]-0.908305506633994[/C][/ROW]
[ROW][C]33[/C][C]272566[/C][C]274508.135275656[/C][C]-990.302102731672[/C][C]-1942.13527565565[/C][C]-0.491951414355052[/C][/ROW]
[ROW][C]34[/C][C]264981[/C][C]270422.713778753[/C][C]-1001.49868001539[/C][C]-5441.71377875314[/C][C]-0.463557031641652[/C][/ROW]
[ROW][C]35[/C][C]263290[/C][C]267626.089017881[/C][C]-1005.31407252620[/C][C]-4336.08901788113[/C][C]-0.268634185383439[/C][/ROW]
[ROW][C]36[/C][C]296806[/C][C]283793.078293823[/C][C]-1034.22825909059[/C][C]13012.9217061774[/C][C]2.57470227497034[/C][/ROW]
[ROW][C]37[/C][C]303598[/C][C]293129.320970829[/C][C]-1080.62890205628[/C][C]10468.6790291707[/C][C]1.57351518540293[/C][/ROW]
[ROW][C]38[/C][C]286994[/C][C]285471.127444624[/C][C]-1103.64061072822[/C][C]1522.87255537598[/C][C]-0.970935668730854[/C][/ROW]
[ROW][C]39[/C][C]276427[/C][C]279858.112439805[/C][C]-1144.26277097603[/C][C]-3431.11243980523[/C][C]-0.657801796744838[/C][/ROW]
[ROW][C]40[/C][C]266424[/C][C]273542.62937679[/C][C]-1188.01010664923[/C][C]-7118.62937678974[/C][C]-0.766155339360943[/C][/ROW]
[ROW][C]41[/C][C]267153[/C][C]270130.176656009[/C][C]-1200.75931559783[/C][C]-2977.17665600925[/C][C]-0.332625262009254[/C][/ROW]
[ROW][C]42[/C][C]268381[/C][C]267359.699037066[/C][C]-1206.72687033244[/C][C]1021.30096293444[/C][C]-0.235117805719063[/C][/ROW]
[ROW][C]43[/C][C]262522[/C][C]262992.919536849[/C][C]-1216.59631580056[/C][C]-470.919536849454[/C][C]-0.473299442041557[/C][/ROW]
[ROW][C]44[/C][C]255542[/C][C]257929.397263980[/C][C]-1228.70437671734[/C][C]-2387.39726398050[/C][C]-0.576123204837344[/C][/ROW]
[ROW][C]45[/C][C]253158[/C][C]254454.899598956[/C][C]-1236.03022317791[/C][C]-1296.89959895595[/C][C]-0.336340294217171[/C][/ROW]
[ROW][C]46[/C][C]243803[/C][C]250362.364671481[/C][C]-1244.14280049282[/C][C]-6559.36467148068[/C][C]-0.427674492397063[/C][/ROW]
[ROW][C]47[/C][C]250741[/C][C]257031.440444633[/C][C]-1234.21333799261[/C][C]-6290.44044463284[/C][C]1.18382262104702[/C][/ROW]
[ROW][C]48[/C][C]280445[/C][C]266336.422067546[/C][C]-1246.87889199199[/C][C]14108.5779324541[/C][C]1.57987078392883[/C][/ROW]
[ROW][C]49[/C][C]285257[/C][C]270928.060782321[/C][C]-1256.80004007362[/C][C]14328.9392176792[/C][C]0.878027098654857[/C][/ROW]
[ROW][C]50[/C][C]270976[/C][C]268845.370561896[/C][C]-1259.16311300585[/C][C]2130.62943810352[/C][C]-0.122374520755582[/C][/ROW]
[ROW][C]51[/C][C]261076[/C][C]264450.422250399[/C][C]-1280.71886264754[/C][C]-3374.42225039899[/C][C]-0.460536676492489[/C][/ROW]
[ROW][C]52[/C][C]255603[/C][C]262408.423617773[/C][C]-1286.28569560455[/C][C]-6805.42361777327[/C][C]-0.112765499690225[/C][/ROW]
[ROW][C]53[/C][C]260376[/C][C]262351.837292276[/C][C]-1279.31811543432[/C][C]-1975.83729227595[/C][C]0.183644742211955[/C][/ROW]
[ROW][C]54[/C][C]263903[/C][C]261637.353775415[/C][C]-1277.03579837621[/C][C]2265.64622458499[/C][C]0.0845747778931377[/C][/ROW]
[ROW][C]55[/C][C]264291[/C][C]262485.069912478[/C][C]-1270.19665558059[/C][C]1805.93008752211[/C][C]0.318263581732331[/C][/ROW]
[ROW][C]56[/C][C]263276[/C][C]263710.672990517[/C][C]-1262.7174509006[/C][C]-434.672990517124[/C][C]0.373832364138744[/C][/ROW]
[ROW][C]57[/C][C]262572[/C][C]263126.060137877[/C][C]-1260.78421610747[/C][C]-554.060137877382[/C][C]0.101553242562512[/C][/ROW]
[ROW][C]58[/C][C]256167[/C][C]264490.021168332[/C][C]-1254.91654979578[/C][C]-8323.02116833202[/C][C]0.392855592228209[/C][/ROW]
[ROW][C]59[/C][C]264221[/C][C]270948.083393656[/C][C]-1248.20419905592[/C][C]-6727.08339365612[/C][C]1.15377719506950[/C][/ROW]
[ROW][C]60[/C][C]293860[/C][C]278477.38456098[/C][C]-1253.60663937016[/C][C]15382.6154390202[/C][C]1.31483654014780[/C][/ROW]
[ROW][C]61[/C][C]300713[/C][C]284007.174677601[/C][C]-1256.08760761612[/C][C]16705.8253223985[/C][C]1.01617355692354[/C][/ROW]
[ROW][C]62[/C][C]287224[/C][C]284283.511451435[/C][C]-1252.05678304184[/C][C]2940.48854856494[/C][C]0.227438010041143[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=62150&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=62150&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
1325412325412000
2326011325942.55084104627.752756355036068.44915895355620.0495217931639672
3328282327718.72094753176.5255332056774563.2790524688350.251364284016571
4317480319986.2585188027.48005821959097-2506.25851880216-1.17182663707953
5317539317443.820704185-5.7879503770284295.1792958145417-0.382385070780442
6313737314384.460827008-22.9290117275542-647.460827007662-0.457691395941157
7312276312519.657431044-34.0127038343482-243.657431043558-0.276031371176660
8309391309980.391879649-49.2462602436357-589.391879649354-0.375443784236939
9302950304397.933526114-82.6566969766221-1447.93352611425-0.82922368442539
10300316300840.562711304-103.476525562518-524.562711303572-0.520727406257012
11304035303054.478701094-89.6800411153306980.521298906120.347285143547759
12333476326654.12308346950.51895564382656821.876916530613.55004922769262
13337698335235.919206305-266.8622256577712462.080793694621.45510683699584
14335932336715.200068716-242.484768370612-783.2000687157710.241364074838444
15323931326237.26315566-433.235918536539-2306.26315566009-1.45975595457309
16313927318390.442015713-507.018859113401-4463.44201571332-1.10617165519554
17314485314626.291099368-522.396857989932-141.291099368494-0.488189608088228
18313218313748.761252682-523.648132440838-530.761252681949-0.0532020740281788
19309664310805.376437261-532.588714541077-1141.37643726096-0.362366830012397
20302963304558.933564481-555.255229640237-1595.93356448105-0.855544881056838
21298989300238.041429651-570.987028556055-1249.04142965143-0.563874815798923
22298423299128.510390822-573.350834141211-705.510390822258-0.0806688149030882
23310631310613.566440552-528.00973337962917.43355944757971.80596068903270
24329765322025.222928121-539.4544753219857739.777071879231.78781619906444
25335083329559.115401028-631.820253073065523.884598972291.25528891756047
26327616326666.588822281-644.617825091323949.411177718565-0.329645300284093
27309119314118.819384524-794.790093684242-4999.81938452365-1.71829631337343
28295916303114.825186792-892.576431540558-7198.8251867916-1.51571341892716
29291413294177.456320278-936.38099634766-2764.45632027818-1.20466977238556
30291542291407.589022158-942.811519159777134.410977841569-0.274670469893185
31284678285795.125263775-957.554687138183-1117.12526377512-0.699316228857779
32276475278771.405241583-978.141342447736-2296.4052415833-0.908305506633994
33272566274508.135275656-990.302102731672-1942.13527565565-0.491951414355052
34264981270422.713778753-1001.49868001539-5441.71377875314-0.463557031641652
35263290267626.089017881-1005.31407252620-4336.08901788113-0.268634185383439
36296806283793.078293823-1034.2282590905913012.92170617742.57470227497034
37303598293129.320970829-1080.6289020562810468.67902917071.57351518540293
38286994285471.127444624-1103.640610728221522.87255537598-0.970935668730854
39276427279858.112439805-1144.26277097603-3431.11243980523-0.657801796744838
40266424273542.62937679-1188.01010664923-7118.62937678974-0.766155339360943
41267153270130.176656009-1200.75931559783-2977.17665600925-0.332625262009254
42268381267359.699037066-1206.726870332441021.30096293444-0.235117805719063
43262522262992.919536849-1216.59631580056-470.919536849454-0.473299442041557
44255542257929.397263980-1228.70437671734-2387.39726398050-0.576123204837344
45253158254454.899598956-1236.03022317791-1296.89959895595-0.336340294217171
46243803250362.364671481-1244.14280049282-6559.36467148068-0.427674492397063
47250741257031.440444633-1234.21333799261-6290.440444632841.18382262104702
48280445266336.422067546-1246.8788919919914108.57793245411.57987078392883
49285257270928.060782321-1256.8000400736214328.93921767920.878027098654857
50270976268845.370561896-1259.163113005852130.62943810352-0.122374520755582
51261076264450.422250399-1280.71886264754-3374.42225039899-0.460536676492489
52255603262408.423617773-1286.28569560455-6805.42361777327-0.112765499690225
53260376262351.837292276-1279.31811543432-1975.837292275950.183644742211955
54263903261637.353775415-1277.035798376212265.646224584990.0845747778931377
55264291262485.069912478-1270.196655580591805.930087522110.318263581732331
56263276263710.672990517-1262.7174509006-434.6729905171240.373832364138744
57262572263126.060137877-1260.78421610747-554.0601378773820.101553242562512
58256167264490.021168332-1254.91654979578-8323.021168332020.392855592228209
59264221270948.083393656-1248.20419905592-6727.083393656121.15377719506950
60293860278477.38456098-1253.6066393701615382.61543902021.31483654014780
61300713284007.174677601-1256.0876076161216705.82532239851.01617355692354
62287224284283.511451435-1252.056783041842940.488548564940.227438010041143


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$resid)
myfit <- mylevel+myseas
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(mylevel,main='Level')
spectrum(myseas,main='Seasonal')
spectrum(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(mylevel,main='Level')
cpgram(myseas,main='Seasonal')
cpgram(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test1.png')
plot(as.numeric(m$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')