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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_structuraltimeseries.wasp
Title produced by softwareStructural Time Series Models
Date of computationTue, 28 Dec 2010 19:24:09 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/28/t1293564119pxf8077ispsvx7c.htm/, Retrieved Sun, 05 May 2024 04:48:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116511, Retrieved Sun, 05 May 2024 04:48:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Structural Time Series Models] [Paper: analyse (m...] [2010-12-28 19:24:09] [35c3410767ea63f72c8afa35bf7b6164] [Current]
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Dataseries X:
3065
2997
2901
2815
2709
2711
3509
3369
3596
3448
3160
2934
2534
2266
2088
1932
1784
1851
2700
2580
2829
2298
2045
1824
1872
1801
1735
1639
1521
1758
2603
2540
3103
2801
2590
2324
2424
2288
2163
2082
1937
2155
2874
2836
3439
3278
3129
2959
3060
2898
2783
2632
2465
2689
3321
3359
4108
3407
3241
3013
3067
2965
2823
2718
2567
2658
3436
3375
3931
3371
3038




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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116511&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116511&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116511&T=0

As an alternative you can also use a QR Code:  

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

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







Structural Time Series Model
tObservedLevelSlopeSeasonalStand. Residuals
130653065000
229973008.52132984141-57.4308461652338-11.5213298414105-0.394571923099675
329012904.48245445651-92.0410946133205-3.482454456509-0.233214850986717
428152811.98042638843-92.40062911815433.01957361156934-0.00228395106446355
527092710.84711376416-99.0688472962668-1.84711376416367-0.0417410036872391
627112692.90041666764-37.112717630337718.0995833323590.390063775627983
735093360.9252125022502.450445333022148.0747874978043.39282560013221
833693494.63203290656220.254613650929-125.63203290656-1.77441480569011
935963598.04039785579130.84742838385-2.04039785578978-0.562189657734893
1034483492.23032542799-50.2163857782155-44.2303254279921-1.13851232294309
1131603198.12608032255-236.811707873242-38.1260803225456-1.17329512656562
1229342926.23880999051-263.6481050742927.76119000949463-0.168744903466494
1325342555.07420020928-345.745313209625-21.0742002092838-0.517493978489517
1422662254.63042018064-311.04258349015911.36957981936340.221450641719808
1520882062.4048966199-223.78038586020525.59510338009880.548037194003999
1619321885.12811360623-189.43627362702146.87188639377210.218798237261057
1717841768.46397035217-135.68042229851715.53602964782930.337110549454524
1818511949.3676426417196.8386750230845-98.36764264170811.4611662625695
1927002410.25787418582364.557413231091289.7421258141791.68429329247413
2025802728.76396020645330.663129715337-148.763960206453-0.213119576721193
2128292842.21808779584170.784291962522-13.2180877958423-1.00528997780698
2222982422.9319125651-263.520639190831-124.931912565101-2.73097136959565
2320452071.68499435855-328.076333395277-26.6849943585501-0.405921443073218
2418241770.94605818772-307.97529478701353.05394181227910.126419177550124
2518721813.71522837652-50.095109630941858.28477162348121.62591288219237
2618011812.27350932658-14.2792011961628-11.27350932658210.225515918419823
2717351715.18250347072-74.521735545023719.8174965292804-0.378270078091017
2816391588.69493438335-112.31913445952950.3050656166522-0.239052361931656
2915211559.68504954285-51.5234587913615-38.6850495428460.382337989611295
3017581890.44934070841226.430773552593-132.4493407084061.74536624628129
3126032312.76244695178368.780125196721290.2375530482240.89534009133089
3225402668.94970562274359.619627478365-128.949705622737-0.0576076578612994
3331032972.93319801753319.135257613662130.066801982469-0.254552555312155
3428012960.8509345405478.1318580864534-159.850934540542-1.51549629249334
3525902685.13473316619-179.230373665122-95.1347331661929-1.61825202014122
3623242385.92658635877-266.434699894323-61.9265863587737-0.548616955098713
3724242327.87996012428-114.87443127559996.12003987572120.954707986502277
3822882257.33172597887-82.648765377334530.66827402112520.202594005573066
3921632112.02825671909-127.94694167986650.9717432809054-0.284613928451145
4020822020.28549144245-101.78265886141961.71450855755110.164995401597328
4119372046.81273470064-8.81664598509114-109.8127347006450.585039709485024
4221552295.95177730898177.766692944792-140.9517773089841.17196428997283
4328742589.36348269849261.323175068105284.6365173015090.525344853228414
4428362958.82413658518339.505870376773-122.8241365851790.491677046270253
4534393246.73503793894302.186193739311192.264962061064-0.23465905208662
4632783374.02365686944175.682184238808-96.0236568694404-0.795461686634786
4731293252.48431823018-39.2108882243069-123.484318230177-1.35127280967065
4829593100.15180750171-120.974293569908-141.151807501715-0.514423801137036
4930602972.14054452987-126.06364528980187.8594554701331-0.0320345741624389
5028982836.12378596156-133.25651550525861.8762140384404-0.0452095736285125
5127832714.89932819909-124.58929362607268.10067180090580.0544746343218403
5226322588.12644875065-126.161779417943.8735512493452-0.00990411744538079
5324652604.05022701716-23.6573808605812-139.0502270171590.645074161407301
5426892816.61139198726146.643517767402-127.6113919872591.07011712518994
5533213066.03864354455220.667824554741254.9613564554450.465318489748285
5633593453.71793609093340.978920306346-94.71793609093440.756556254003159
5741083868.98620739569394.518085458683239.0137926043140.336652662732684
5834073582.58900433025-96.2147637535746-175.589004330245-3.08569895407298
5932413349.92228909767-194.527004960755-108.922289097669-0.618238700894315
6030133156.33281984418-193.851538820364-143.332819844180.00424951123704307
6130672970.52202683791-188.05592264861496.47797316209210.0364631942862495
6229652868.42829301131-126.14496135982596.57170698869260.389131298758314
6328232733.38062645764-132.54338269666289.619373542362-0.0402215478615863
6427182676.60491289207-78.098927734114541.39508710792590.342707534470107
6525672733.2929907460118.878087622085-166.292990746010.610223872428589
6626582814.4711792292463.6936816447249-156.4711792292370.281689107048199
6734363195.8435886772292.023865959307240.1564113227981.43521013520164
6833753513.49534691749310.443191405403-138.4953469174890.115816452023226
6939313562.46723760569122.461057320644368.532762394312-1.1820397174037
7033713535.7279551683815.1900677394097-164.727955168382-0.674528766231616
7130383219.50169645456-223.055421458684-181.501696454564-1.49829686584636

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 3065 & 3065 & 0 & 0 & 0 \tabularnewline
2 & 2997 & 3008.52132984141 & -57.4308461652338 & -11.5213298414105 & -0.394571923099675 \tabularnewline
3 & 2901 & 2904.48245445651 & -92.0410946133205 & -3.482454456509 & -0.233214850986717 \tabularnewline
4 & 2815 & 2811.98042638843 & -92.4006291181543 & 3.01957361156934 & -0.00228395106446355 \tabularnewline
5 & 2709 & 2710.84711376416 & -99.0688472962668 & -1.84711376416367 & -0.0417410036872391 \tabularnewline
6 & 2711 & 2692.90041666764 & -37.1127176303377 & 18.099583332359 & 0.390063775627983 \tabularnewline
7 & 3509 & 3360.9252125022 & 502.450445333022 & 148.074787497804 & 3.39282560013221 \tabularnewline
8 & 3369 & 3494.63203290656 & 220.254613650929 & -125.63203290656 & -1.77441480569011 \tabularnewline
9 & 3596 & 3598.04039785579 & 130.84742838385 & -2.04039785578978 & -0.562189657734893 \tabularnewline
10 & 3448 & 3492.23032542799 & -50.2163857782155 & -44.2303254279921 & -1.13851232294309 \tabularnewline
11 & 3160 & 3198.12608032255 & -236.811707873242 & -38.1260803225456 & -1.17329512656562 \tabularnewline
12 & 2934 & 2926.23880999051 & -263.648105074292 & 7.76119000949463 & -0.168744903466494 \tabularnewline
13 & 2534 & 2555.07420020928 & -345.745313209625 & -21.0742002092838 & -0.517493978489517 \tabularnewline
14 & 2266 & 2254.63042018064 & -311.042583490159 & 11.3695798193634 & 0.221450641719808 \tabularnewline
15 & 2088 & 2062.4048966199 & -223.780385860205 & 25.5951033800988 & 0.548037194003999 \tabularnewline
16 & 1932 & 1885.12811360623 & -189.436273627021 & 46.8718863937721 & 0.218798237261057 \tabularnewline
17 & 1784 & 1768.46397035217 & -135.680422298517 & 15.5360296478293 & 0.337110549454524 \tabularnewline
18 & 1851 & 1949.36764264171 & 96.8386750230845 & -98.3676426417081 & 1.4611662625695 \tabularnewline
19 & 2700 & 2410.25787418582 & 364.557413231091 & 289.742125814179 & 1.68429329247413 \tabularnewline
20 & 2580 & 2728.76396020645 & 330.663129715337 & -148.763960206453 & -0.213119576721193 \tabularnewline
21 & 2829 & 2842.21808779584 & 170.784291962522 & -13.2180877958423 & -1.00528997780698 \tabularnewline
22 & 2298 & 2422.9319125651 & -263.520639190831 & -124.931912565101 & -2.73097136959565 \tabularnewline
23 & 2045 & 2071.68499435855 & -328.076333395277 & -26.6849943585501 & -0.405921443073218 \tabularnewline
24 & 1824 & 1770.94605818772 & -307.975294787013 & 53.0539418122791 & 0.126419177550124 \tabularnewline
25 & 1872 & 1813.71522837652 & -50.0951096309418 & 58.2847716234812 & 1.62591288219237 \tabularnewline
26 & 1801 & 1812.27350932658 & -14.2792011961628 & -11.2735093265821 & 0.225515918419823 \tabularnewline
27 & 1735 & 1715.18250347072 & -74.5217355450237 & 19.8174965292804 & -0.378270078091017 \tabularnewline
28 & 1639 & 1588.69493438335 & -112.319134459529 & 50.3050656166522 & -0.239052361931656 \tabularnewline
29 & 1521 & 1559.68504954285 & -51.5234587913615 & -38.685049542846 & 0.382337989611295 \tabularnewline
30 & 1758 & 1890.44934070841 & 226.430773552593 & -132.449340708406 & 1.74536624628129 \tabularnewline
31 & 2603 & 2312.76244695178 & 368.780125196721 & 290.237553048224 & 0.89534009133089 \tabularnewline
32 & 2540 & 2668.94970562274 & 359.619627478365 & -128.949705622737 & -0.0576076578612994 \tabularnewline
33 & 3103 & 2972.93319801753 & 319.135257613662 & 130.066801982469 & -0.254552555312155 \tabularnewline
34 & 2801 & 2960.85093454054 & 78.1318580864534 & -159.850934540542 & -1.51549629249334 \tabularnewline
35 & 2590 & 2685.13473316619 & -179.230373665122 & -95.1347331661929 & -1.61825202014122 \tabularnewline
36 & 2324 & 2385.92658635877 & -266.434699894323 & -61.9265863587737 & -0.548616955098713 \tabularnewline
37 & 2424 & 2327.87996012428 & -114.874431275599 & 96.1200398757212 & 0.954707986502277 \tabularnewline
38 & 2288 & 2257.33172597887 & -82.6487653773345 & 30.6682740211252 & 0.202594005573066 \tabularnewline
39 & 2163 & 2112.02825671909 & -127.946941679866 & 50.9717432809054 & -0.284613928451145 \tabularnewline
40 & 2082 & 2020.28549144245 & -101.782658861419 & 61.7145085575511 & 0.164995401597328 \tabularnewline
41 & 1937 & 2046.81273470064 & -8.81664598509114 & -109.812734700645 & 0.585039709485024 \tabularnewline
42 & 2155 & 2295.95177730898 & 177.766692944792 & -140.951777308984 & 1.17196428997283 \tabularnewline
43 & 2874 & 2589.36348269849 & 261.323175068105 & 284.636517301509 & 0.525344853228414 \tabularnewline
44 & 2836 & 2958.82413658518 & 339.505870376773 & -122.824136585179 & 0.491677046270253 \tabularnewline
45 & 3439 & 3246.73503793894 & 302.186193739311 & 192.264962061064 & -0.23465905208662 \tabularnewline
46 & 3278 & 3374.02365686944 & 175.682184238808 & -96.0236568694404 & -0.795461686634786 \tabularnewline
47 & 3129 & 3252.48431823018 & -39.2108882243069 & -123.484318230177 & -1.35127280967065 \tabularnewline
48 & 2959 & 3100.15180750171 & -120.974293569908 & -141.151807501715 & -0.514423801137036 \tabularnewline
49 & 3060 & 2972.14054452987 & -126.063645289801 & 87.8594554701331 & -0.0320345741624389 \tabularnewline
50 & 2898 & 2836.12378596156 & -133.256515505258 & 61.8762140384404 & -0.0452095736285125 \tabularnewline
51 & 2783 & 2714.89932819909 & -124.589293626072 & 68.1006718009058 & 0.0544746343218403 \tabularnewline
52 & 2632 & 2588.12644875065 & -126.1617794179 & 43.8735512493452 & -0.00990411744538079 \tabularnewline
53 & 2465 & 2604.05022701716 & -23.6573808605812 & -139.050227017159 & 0.645074161407301 \tabularnewline
54 & 2689 & 2816.61139198726 & 146.643517767402 & -127.611391987259 & 1.07011712518994 \tabularnewline
55 & 3321 & 3066.03864354455 & 220.667824554741 & 254.961356455445 & 0.465318489748285 \tabularnewline
56 & 3359 & 3453.71793609093 & 340.978920306346 & -94.7179360909344 & 0.756556254003159 \tabularnewline
57 & 4108 & 3868.98620739569 & 394.518085458683 & 239.013792604314 & 0.336652662732684 \tabularnewline
58 & 3407 & 3582.58900433025 & -96.2147637535746 & -175.589004330245 & -3.08569895407298 \tabularnewline
59 & 3241 & 3349.92228909767 & -194.527004960755 & -108.922289097669 & -0.618238700894315 \tabularnewline
60 & 3013 & 3156.33281984418 & -193.851538820364 & -143.33281984418 & 0.00424951123704307 \tabularnewline
61 & 3067 & 2970.52202683791 & -188.055922648614 & 96.4779731620921 & 0.0364631942862495 \tabularnewline
62 & 2965 & 2868.42829301131 & -126.144961359825 & 96.5717069886926 & 0.389131298758314 \tabularnewline
63 & 2823 & 2733.38062645764 & -132.543382696662 & 89.619373542362 & -0.0402215478615863 \tabularnewline
64 & 2718 & 2676.60491289207 & -78.0989277341145 & 41.3950871079259 & 0.342707534470107 \tabularnewline
65 & 2567 & 2733.29299074601 & 18.878087622085 & -166.29299074601 & 0.610223872428589 \tabularnewline
66 & 2658 & 2814.47117922924 & 63.6936816447249 & -156.471179229237 & 0.281689107048199 \tabularnewline
67 & 3436 & 3195.8435886772 & 292.023865959307 & 240.156411322798 & 1.43521013520164 \tabularnewline
68 & 3375 & 3513.49534691749 & 310.443191405403 & -138.495346917489 & 0.115816452023226 \tabularnewline
69 & 3931 & 3562.46723760569 & 122.461057320644 & 368.532762394312 & -1.1820397174037 \tabularnewline
70 & 3371 & 3535.72795516838 & 15.1900677394097 & -164.727955168382 & -0.674528766231616 \tabularnewline
71 & 3038 & 3219.50169645456 & -223.055421458684 & -181.501696454564 & -1.49829686584636 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116511&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]3065[/C][C]3065[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]2997[/C][C]3008.52132984141[/C][C]-57.4308461652338[/C][C]-11.5213298414105[/C][C]-0.394571923099675[/C][/ROW]
[ROW][C]3[/C][C]2901[/C][C]2904.48245445651[/C][C]-92.0410946133205[/C][C]-3.482454456509[/C][C]-0.233214850986717[/C][/ROW]
[ROW][C]4[/C][C]2815[/C][C]2811.98042638843[/C][C]-92.4006291181543[/C][C]3.01957361156934[/C][C]-0.00228395106446355[/C][/ROW]
[ROW][C]5[/C][C]2709[/C][C]2710.84711376416[/C][C]-99.0688472962668[/C][C]-1.84711376416367[/C][C]-0.0417410036872391[/C][/ROW]
[ROW][C]6[/C][C]2711[/C][C]2692.90041666764[/C][C]-37.1127176303377[/C][C]18.099583332359[/C][C]0.390063775627983[/C][/ROW]
[ROW][C]7[/C][C]3509[/C][C]3360.9252125022[/C][C]502.450445333022[/C][C]148.074787497804[/C][C]3.39282560013221[/C][/ROW]
[ROW][C]8[/C][C]3369[/C][C]3494.63203290656[/C][C]220.254613650929[/C][C]-125.63203290656[/C][C]-1.77441480569011[/C][/ROW]
[ROW][C]9[/C][C]3596[/C][C]3598.04039785579[/C][C]130.84742838385[/C][C]-2.04039785578978[/C][C]-0.562189657734893[/C][/ROW]
[ROW][C]10[/C][C]3448[/C][C]3492.23032542799[/C][C]-50.2163857782155[/C][C]-44.2303254279921[/C][C]-1.13851232294309[/C][/ROW]
[ROW][C]11[/C][C]3160[/C][C]3198.12608032255[/C][C]-236.811707873242[/C][C]-38.1260803225456[/C][C]-1.17329512656562[/C][/ROW]
[ROW][C]12[/C][C]2934[/C][C]2926.23880999051[/C][C]-263.648105074292[/C][C]7.76119000949463[/C][C]-0.168744903466494[/C][/ROW]
[ROW][C]13[/C][C]2534[/C][C]2555.07420020928[/C][C]-345.745313209625[/C][C]-21.0742002092838[/C][C]-0.517493978489517[/C][/ROW]
[ROW][C]14[/C][C]2266[/C][C]2254.63042018064[/C][C]-311.042583490159[/C][C]11.3695798193634[/C][C]0.221450641719808[/C][/ROW]
[ROW][C]15[/C][C]2088[/C][C]2062.4048966199[/C][C]-223.780385860205[/C][C]25.5951033800988[/C][C]0.548037194003999[/C][/ROW]
[ROW][C]16[/C][C]1932[/C][C]1885.12811360623[/C][C]-189.436273627021[/C][C]46.8718863937721[/C][C]0.218798237261057[/C][/ROW]
[ROW][C]17[/C][C]1784[/C][C]1768.46397035217[/C][C]-135.680422298517[/C][C]15.5360296478293[/C][C]0.337110549454524[/C][/ROW]
[ROW][C]18[/C][C]1851[/C][C]1949.36764264171[/C][C]96.8386750230845[/C][C]-98.3676426417081[/C][C]1.4611662625695[/C][/ROW]
[ROW][C]19[/C][C]2700[/C][C]2410.25787418582[/C][C]364.557413231091[/C][C]289.742125814179[/C][C]1.68429329247413[/C][/ROW]
[ROW][C]20[/C][C]2580[/C][C]2728.76396020645[/C][C]330.663129715337[/C][C]-148.763960206453[/C][C]-0.213119576721193[/C][/ROW]
[ROW][C]21[/C][C]2829[/C][C]2842.21808779584[/C][C]170.784291962522[/C][C]-13.2180877958423[/C][C]-1.00528997780698[/C][/ROW]
[ROW][C]22[/C][C]2298[/C][C]2422.9319125651[/C][C]-263.520639190831[/C][C]-124.931912565101[/C][C]-2.73097136959565[/C][/ROW]
[ROW][C]23[/C][C]2045[/C][C]2071.68499435855[/C][C]-328.076333395277[/C][C]-26.6849943585501[/C][C]-0.405921443073218[/C][/ROW]
[ROW][C]24[/C][C]1824[/C][C]1770.94605818772[/C][C]-307.975294787013[/C][C]53.0539418122791[/C][C]0.126419177550124[/C][/ROW]
[ROW][C]25[/C][C]1872[/C][C]1813.71522837652[/C][C]-50.0951096309418[/C][C]58.2847716234812[/C][C]1.62591288219237[/C][/ROW]
[ROW][C]26[/C][C]1801[/C][C]1812.27350932658[/C][C]-14.2792011961628[/C][C]-11.2735093265821[/C][C]0.225515918419823[/C][/ROW]
[ROW][C]27[/C][C]1735[/C][C]1715.18250347072[/C][C]-74.5217355450237[/C][C]19.8174965292804[/C][C]-0.378270078091017[/C][/ROW]
[ROW][C]28[/C][C]1639[/C][C]1588.69493438335[/C][C]-112.319134459529[/C][C]50.3050656166522[/C][C]-0.239052361931656[/C][/ROW]
[ROW][C]29[/C][C]1521[/C][C]1559.68504954285[/C][C]-51.5234587913615[/C][C]-38.685049542846[/C][C]0.382337989611295[/C][/ROW]
[ROW][C]30[/C][C]1758[/C][C]1890.44934070841[/C][C]226.430773552593[/C][C]-132.449340708406[/C][C]1.74536624628129[/C][/ROW]
[ROW][C]31[/C][C]2603[/C][C]2312.76244695178[/C][C]368.780125196721[/C][C]290.237553048224[/C][C]0.89534009133089[/C][/ROW]
[ROW][C]32[/C][C]2540[/C][C]2668.94970562274[/C][C]359.619627478365[/C][C]-128.949705622737[/C][C]-0.0576076578612994[/C][/ROW]
[ROW][C]33[/C][C]3103[/C][C]2972.93319801753[/C][C]319.135257613662[/C][C]130.066801982469[/C][C]-0.254552555312155[/C][/ROW]
[ROW][C]34[/C][C]2801[/C][C]2960.85093454054[/C][C]78.1318580864534[/C][C]-159.850934540542[/C][C]-1.51549629249334[/C][/ROW]
[ROW][C]35[/C][C]2590[/C][C]2685.13473316619[/C][C]-179.230373665122[/C][C]-95.1347331661929[/C][C]-1.61825202014122[/C][/ROW]
[ROW][C]36[/C][C]2324[/C][C]2385.92658635877[/C][C]-266.434699894323[/C][C]-61.9265863587737[/C][C]-0.548616955098713[/C][/ROW]
[ROW][C]37[/C][C]2424[/C][C]2327.87996012428[/C][C]-114.874431275599[/C][C]96.1200398757212[/C][C]0.954707986502277[/C][/ROW]
[ROW][C]38[/C][C]2288[/C][C]2257.33172597887[/C][C]-82.6487653773345[/C][C]30.6682740211252[/C][C]0.202594005573066[/C][/ROW]
[ROW][C]39[/C][C]2163[/C][C]2112.02825671909[/C][C]-127.946941679866[/C][C]50.9717432809054[/C][C]-0.284613928451145[/C][/ROW]
[ROW][C]40[/C][C]2082[/C][C]2020.28549144245[/C][C]-101.782658861419[/C][C]61.7145085575511[/C][C]0.164995401597328[/C][/ROW]
[ROW][C]41[/C][C]1937[/C][C]2046.81273470064[/C][C]-8.81664598509114[/C][C]-109.812734700645[/C][C]0.585039709485024[/C][/ROW]
[ROW][C]42[/C][C]2155[/C][C]2295.95177730898[/C][C]177.766692944792[/C][C]-140.951777308984[/C][C]1.17196428997283[/C][/ROW]
[ROW][C]43[/C][C]2874[/C][C]2589.36348269849[/C][C]261.323175068105[/C][C]284.636517301509[/C][C]0.525344853228414[/C][/ROW]
[ROW][C]44[/C][C]2836[/C][C]2958.82413658518[/C][C]339.505870376773[/C][C]-122.824136585179[/C][C]0.491677046270253[/C][/ROW]
[ROW][C]45[/C][C]3439[/C][C]3246.73503793894[/C][C]302.186193739311[/C][C]192.264962061064[/C][C]-0.23465905208662[/C][/ROW]
[ROW][C]46[/C][C]3278[/C][C]3374.02365686944[/C][C]175.682184238808[/C][C]-96.0236568694404[/C][C]-0.795461686634786[/C][/ROW]
[ROW][C]47[/C][C]3129[/C][C]3252.48431823018[/C][C]-39.2108882243069[/C][C]-123.484318230177[/C][C]-1.35127280967065[/C][/ROW]
[ROW][C]48[/C][C]2959[/C][C]3100.15180750171[/C][C]-120.974293569908[/C][C]-141.151807501715[/C][C]-0.514423801137036[/C][/ROW]
[ROW][C]49[/C][C]3060[/C][C]2972.14054452987[/C][C]-126.063645289801[/C][C]87.8594554701331[/C][C]-0.0320345741624389[/C][/ROW]
[ROW][C]50[/C][C]2898[/C][C]2836.12378596156[/C][C]-133.256515505258[/C][C]61.8762140384404[/C][C]-0.0452095736285125[/C][/ROW]
[ROW][C]51[/C][C]2783[/C][C]2714.89932819909[/C][C]-124.589293626072[/C][C]68.1006718009058[/C][C]0.0544746343218403[/C][/ROW]
[ROW][C]52[/C][C]2632[/C][C]2588.12644875065[/C][C]-126.1617794179[/C][C]43.8735512493452[/C][C]-0.00990411744538079[/C][/ROW]
[ROW][C]53[/C][C]2465[/C][C]2604.05022701716[/C][C]-23.6573808605812[/C][C]-139.050227017159[/C][C]0.645074161407301[/C][/ROW]
[ROW][C]54[/C][C]2689[/C][C]2816.61139198726[/C][C]146.643517767402[/C][C]-127.611391987259[/C][C]1.07011712518994[/C][/ROW]
[ROW][C]55[/C][C]3321[/C][C]3066.03864354455[/C][C]220.667824554741[/C][C]254.961356455445[/C][C]0.465318489748285[/C][/ROW]
[ROW][C]56[/C][C]3359[/C][C]3453.71793609093[/C][C]340.978920306346[/C][C]-94.7179360909344[/C][C]0.756556254003159[/C][/ROW]
[ROW][C]57[/C][C]4108[/C][C]3868.98620739569[/C][C]394.518085458683[/C][C]239.013792604314[/C][C]0.336652662732684[/C][/ROW]
[ROW][C]58[/C][C]3407[/C][C]3582.58900433025[/C][C]-96.2147637535746[/C][C]-175.589004330245[/C][C]-3.08569895407298[/C][/ROW]
[ROW][C]59[/C][C]3241[/C][C]3349.92228909767[/C][C]-194.527004960755[/C][C]-108.922289097669[/C][C]-0.618238700894315[/C][/ROW]
[ROW][C]60[/C][C]3013[/C][C]3156.33281984418[/C][C]-193.851538820364[/C][C]-143.33281984418[/C][C]0.00424951123704307[/C][/ROW]
[ROW][C]61[/C][C]3067[/C][C]2970.52202683791[/C][C]-188.055922648614[/C][C]96.4779731620921[/C][C]0.0364631942862495[/C][/ROW]
[ROW][C]62[/C][C]2965[/C][C]2868.42829301131[/C][C]-126.144961359825[/C][C]96.5717069886926[/C][C]0.389131298758314[/C][/ROW]
[ROW][C]63[/C][C]2823[/C][C]2733.38062645764[/C][C]-132.543382696662[/C][C]89.619373542362[/C][C]-0.0402215478615863[/C][/ROW]
[ROW][C]64[/C][C]2718[/C][C]2676.60491289207[/C][C]-78.0989277341145[/C][C]41.3950871079259[/C][C]0.342707534470107[/C][/ROW]
[ROW][C]65[/C][C]2567[/C][C]2733.29299074601[/C][C]18.878087622085[/C][C]-166.29299074601[/C][C]0.610223872428589[/C][/ROW]
[ROW][C]66[/C][C]2658[/C][C]2814.47117922924[/C][C]63.6936816447249[/C][C]-156.471179229237[/C][C]0.281689107048199[/C][/ROW]
[ROW][C]67[/C][C]3436[/C][C]3195.8435886772[/C][C]292.023865959307[/C][C]240.156411322798[/C][C]1.43521013520164[/C][/ROW]
[ROW][C]68[/C][C]3375[/C][C]3513.49534691749[/C][C]310.443191405403[/C][C]-138.495346917489[/C][C]0.115816452023226[/C][/ROW]
[ROW][C]69[/C][C]3931[/C][C]3562.46723760569[/C][C]122.461057320644[/C][C]368.532762394312[/C][C]-1.1820397174037[/C][/ROW]
[ROW][C]70[/C][C]3371[/C][C]3535.72795516838[/C][C]15.1900677394097[/C][C]-164.727955168382[/C][C]-0.674528766231616[/C][/ROW]
[ROW][C]71[/C][C]3038[/C][C]3219.50169645456[/C][C]-223.055421458684[/C][C]-181.501696454564[/C][C]-1.49829686584636[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116511&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116511&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
130653065000
229973008.52132984141-57.4308461652338-11.5213298414105-0.394571923099675
329012904.48245445651-92.0410946133205-3.482454456509-0.233214850986717
428152811.98042638843-92.40062911815433.01957361156934-0.00228395106446355
527092710.84711376416-99.0688472962668-1.84711376416367-0.0417410036872391
627112692.90041666764-37.112717630337718.0995833323590.390063775627983
735093360.9252125022502.450445333022148.0747874978043.39282560013221
833693494.63203290656220.254613650929-125.63203290656-1.77441480569011
935963598.04039785579130.84742838385-2.04039785578978-0.562189657734893
1034483492.23032542799-50.2163857782155-44.2303254279921-1.13851232294309
1131603198.12608032255-236.811707873242-38.1260803225456-1.17329512656562
1229342926.23880999051-263.6481050742927.76119000949463-0.168744903466494
1325342555.07420020928-345.745313209625-21.0742002092838-0.517493978489517
1422662254.63042018064-311.04258349015911.36957981936340.221450641719808
1520882062.4048966199-223.78038586020525.59510338009880.548037194003999
1619321885.12811360623-189.43627362702146.87188639377210.218798237261057
1717841768.46397035217-135.68042229851715.53602964782930.337110549454524
1818511949.3676426417196.8386750230845-98.36764264170811.4611662625695
1927002410.25787418582364.557413231091289.7421258141791.68429329247413
2025802728.76396020645330.663129715337-148.763960206453-0.213119576721193
2128292842.21808779584170.784291962522-13.2180877958423-1.00528997780698
2222982422.9319125651-263.520639190831-124.931912565101-2.73097136959565
2320452071.68499435855-328.076333395277-26.6849943585501-0.405921443073218
2418241770.94605818772-307.97529478701353.05394181227910.126419177550124
2518721813.71522837652-50.095109630941858.28477162348121.62591288219237
2618011812.27350932658-14.2792011961628-11.27350932658210.225515918419823
2717351715.18250347072-74.521735545023719.8174965292804-0.378270078091017
2816391588.69493438335-112.31913445952950.3050656166522-0.239052361931656
2915211559.68504954285-51.5234587913615-38.6850495428460.382337989611295
3017581890.44934070841226.430773552593-132.4493407084061.74536624628129
3126032312.76244695178368.780125196721290.2375530482240.89534009133089
3225402668.94970562274359.619627478365-128.949705622737-0.0576076578612994
3331032972.93319801753319.135257613662130.066801982469-0.254552555312155
3428012960.8509345405478.1318580864534-159.850934540542-1.51549629249334
3525902685.13473316619-179.230373665122-95.1347331661929-1.61825202014122
3623242385.92658635877-266.434699894323-61.9265863587737-0.548616955098713
3724242327.87996012428-114.87443127559996.12003987572120.954707986502277
3822882257.33172597887-82.648765377334530.66827402112520.202594005573066
3921632112.02825671909-127.94694167986650.9717432809054-0.284613928451145
4020822020.28549144245-101.78265886141961.71450855755110.164995401597328
4119372046.81273470064-8.81664598509114-109.8127347006450.585039709485024
4221552295.95177730898177.766692944792-140.9517773089841.17196428997283
4328742589.36348269849261.323175068105284.6365173015090.525344853228414
4428362958.82413658518339.505870376773-122.8241365851790.491677046270253
4534393246.73503793894302.186193739311192.264962061064-0.23465905208662
4632783374.02365686944175.682184238808-96.0236568694404-0.795461686634786
4731293252.48431823018-39.2108882243069-123.484318230177-1.35127280967065
4829593100.15180750171-120.974293569908-141.151807501715-0.514423801137036
4930602972.14054452987-126.06364528980187.8594554701331-0.0320345741624389
5028982836.12378596156-133.25651550525861.8762140384404-0.0452095736285125
5127832714.89932819909-124.58929362607268.10067180090580.0544746343218403
5226322588.12644875065-126.161779417943.8735512493452-0.00990411744538079
5324652604.05022701716-23.6573808605812-139.0502270171590.645074161407301
5426892816.61139198726146.643517767402-127.6113919872591.07011712518994
5533213066.03864354455220.667824554741254.9613564554450.465318489748285
5633593453.71793609093340.978920306346-94.71793609093440.756556254003159
5741083868.98620739569394.518085458683239.0137926043140.336652662732684
5834073582.58900433025-96.2147637535746-175.589004330245-3.08569895407298
5932413349.92228909767-194.527004960755-108.922289097669-0.618238700894315
6030133156.33281984418-193.851538820364-143.332819844180.00424951123704307
6130672970.52202683791-188.05592264861496.47797316209210.0364631942862495
6229652868.42829301131-126.14496135982596.57170698869260.389131298758314
6328232733.38062645764-132.54338269666289.619373542362-0.0402215478615863
6427182676.60491289207-78.098927734114541.39508710792590.342707534470107
6525672733.2929907460118.878087622085-166.292990746010.610223872428589
6626582814.4711792292463.6936816447249-156.4711792292370.281689107048199
6734363195.8435886772292.023865959307240.1564113227981.43521013520164
6833753513.49534691749310.443191405403-138.4953469174890.115816452023226
6939313562.46723760569122.461057320644368.532762394312-1.1820397174037
7033713535.7279551683815.1900677394097-164.727955168382-0.674528766231616
7130383219.50169645456-223.055421458684-181.501696454564-1.49829686584636



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')