Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_structuraltimeseries.wasp

Title produced by software

Structural Time Series Models

Date of computation

Mon, 27 Dec 2010 13:54:49 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/27/t12934580103m97289i8z4gg3k.htm/, Retrieved Mon, 06 May 2024 14:31:34 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115996, Retrieved Mon, 06 May 2024 14:31:34 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

STSM 2 - Handelsbalans België (1995-2009)

Estimated Impact

110

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD  [Structural Time Series Models] [HPC Retail Sales] [2008-03-06 16:52:55] [74be16979710d4c4e7c6647856088456]
- R  D    [Structural Time Series Models] [HPC Retail Sales] [2008-03-08 11:33:35] [74be16979710d4c4e7c6647856088456]
-  MPD      [Structural Time Series Models] [Paper Statistiek ] [2010-12-27 12:43:27] [82c18f3ebe9df70882495121eb816e07]
-   PD          [Structural Time Series Models] [Paper Statistiek ] [2010-12-27 13:54:49] [f6fdc0236f011c1845380977efc505f8] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115996&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115996&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115996&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Structural Time Series Model
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	2540.9	2540.9	0	0	0
2	2370.3	2403.24924220022	-33.0262994931002	-32.8106022456320	-0.0515760048945985
3	1807.5	1899.08565213502	-60.1141201628654	-82.2348547681139	-0.74644362976417
4	1834.8	1882.64971758962	-58.3161433188035	-48.7315746149965	0.0691987457464548
5	786.8	951.72914141744	29.4836641318971	-147.250014763606	-1.54486561578287
6	1561.4	1434.80877129596	69.3114047653	120.44137654359	0.596275212152444
7	1347.2	1332.38017698497	62.9511849408438	18.1019577113344	-0.268448903470677
8	1549.8	1432.84395008494	63.67029822502	116.223871151149	0.0586189578570718
9	1553.8	1761.99215161447	54.7134148070017	-213.408599611800	0.433626576690118
10	1822.5	1717.42247406297	49.3708619782162	106.679397072275	-0.141938122958428
11	3078.7	2902.70124212115	86.8374933633061	154.83576192816	1.76428976802993
12	1589.1	1679.05023825321	67.1945710549171	-64.958398785773	-2.03750832693580
13	1791.5	1949.63708045745	64.7650578145714	-162.043352650802	0.323219937913877
14	2558.1	2506.84682244767	84.263318888183	42.8163233388957	0.726993770255664
15	2111.8	1944.29561110069	64.329629166144	179.386023662537	-1.00026155177559
16	2083.1	2134.63018165642	66.1984410650525	-53.8972415275152	0.195339259616548
17	2052.1	2263.79552755699	66.174771687948	-212.885107513344	0.0987019302256869
18	2243.5	2159.90254881728	60.6533214443497	86.5909073839647	-0.255137574025964
19	2622	2424.04473580615	66.5839093529423	194.243876256577	0.313747641755618
20	1952.6	2076.86018284819	59.9630996849717	-116.564294830252	-0.640085582793468
21	808.9	1144.75520068021	53.1024230173618	-317.330581530955	-1.54300529308708
22	1709.8	1574.99310673692	63.9033070902898	128.077679713886	0.570837091286128
23	1582.1	1380.14961731873	56.7032657933839	206.653722283612	-0.398163486321655
24	865.6	941.39826291358	48.0198461424117	-66.6457330207683	-0.765112410724549
25	1116.1	1405.96021672508	52.9702601735526	-297.574231676639	0.644797905478254
26	1119.4	1029.35720633031	41.5657790094912	97.763903426313	-0.653569597301523
27	2350	1951.68899559281	65.2044682151926	382.324558022941	1.35362415591016
28	1975.6	2087.12084008529	66.5397906997679	-112.811878217570	0.108288350326667
29	2536.5	2710.54450694367	75.1200372660775	-184.297455293075	0.859445697977624
30	2785	2794.43918763284	75.3431442489767	-9.59754576186648	0.0133910501349597
31	2819.7	2504.94149934109	65.8072491733637	321.376837369521	-0.560261724028455
32	1829.5	2077.35815975666	55.7813904742582	-238.819698975269	-0.759839684374817
33	758.3	1089.74874544031	37.0415259598888	-312.318146003386	-1.60708060136847
34	2921.6	2647.77453200980	74.8521220679837	246.312313123360	2.32546493039416
35	2482	2189.94070844713	61.180622788213	301.720827202298	-0.817586433318246
36	1892.7	2044.76059764758	56.7627624581198	-148.290042907563	-0.317475004096619
37	1855.1	2310.74201058281	60.9126764785346	-459.466679830692	0.321814560881375
38	2151.3	1912.34408154991	49.6082982037528	247.275398265569	-0.703030177765467
39	1642.2	1401.29836656822	35.3859631650194	251.070392891113	-0.860219024490696
40	1640.5	1756.82692524019	42.5217123000626	-122.165239699443	0.492111698744722
41	1366.1	1772.74907989586	41.9571434471202	-406.163857432573	-0.0408763740474573
42	1532.8	1299.40519986005	29.3090398873362	242.735406085996	-0.789256053377551
43	824.4	702.576761551008	13.5330939003320	133.180143958761	-0.9604665336808
44	-518.7	-259.91797349528	-8.90646526517968	-241.008012500901	-1.49932162240393
45	-978.5	-599.261100829277	-16.2626176017902	-373.220480693438	-0.507453521652441
46	1162.5	645.302571722459	14.7253768909594	494.33373259316	1.93189342701042
47	1243.4	958.480116986247	22.2199668951932	279.506350167183	0.457735295304846
48	1199.5	1356.02310821577	31.0565994374538	-163.350665869844	0.576251741741529
49	883.1	1408.60912704329	31.5526558117382	-525.900810237818	0.0330468449702881
50	1437.2	1041.37404078267	21.7185000690529	403.059029505694	-0.611178060320598
51	534.5	397.422796403572	5.01968152845378	149.151787224210	-1.02080702000920
52	-1901.9	-1461.04183172475	-39.6640626649202	-406.986280739806	-2.85994318013708
53	-2521.1	-1991.11924917610	-51.2521024069567	-521.066134070186	-0.75249704565682
54	-1721.1	-2197.50832982783	-55.0939319890017	479.222395490493	-0.237790496988483
55	-3094.5	-3305.76705295137	-81.5250695603381	230.370331104769	-1.61487216135076
56	-3694.8	-3359.74803760573	-80.8552193909207	-335.552321681858	0.0422595034494663
57	-2492.1	-2187.74927976893	-50.691880992268	-327.110697861798	1.92188280508946
58	-464.6	-1212.04089779946	-25.1622688718237	728.822442179367	1.57333724598374
59	-626.1	-888.620432616458	-16.4024760290047	256.197649187543	0.534457103630498
60	-1711.4	-1176.84040422838	-23.0854439324801	-529.624050185194	-0.416935505309733

\begin{tabular}{lllllllll}
\hline
Structural Time Series Model \tabularnewline
t & Observed & Level & Slope & Seasonal & Stand. Residuals \tabularnewline
1 & 2540.9 & 2540.9 & 0 & 0 & 0 \tabularnewline
2 & 2370.3 & 2403.24924220022 & -33.0262994931002 & -32.8106022456320 & -0.0515760048945985 \tabularnewline
3 & 1807.5 & 1899.08565213502 & -60.1141201628654 & -82.2348547681139 & -0.74644362976417 \tabularnewline
4 & 1834.8 & 1882.64971758962 & -58.3161433188035 & -48.7315746149965 & 0.0691987457464548 \tabularnewline
5 & 786.8 & 951.72914141744 & 29.4836641318971 & -147.250014763606 & -1.54486561578287 \tabularnewline
6 & 1561.4 & 1434.80877129596 & 69.3114047653 & 120.44137654359 & 0.596275212152444 \tabularnewline
7 & 1347.2 & 1332.38017698497 & 62.9511849408438 & 18.1019577113344 & -0.268448903470677 \tabularnewline
8 & 1549.8 & 1432.84395008494 & 63.67029822502 & 116.223871151149 & 0.0586189578570718 \tabularnewline
9 & 1553.8 & 1761.99215161447 & 54.7134148070017 & -213.408599611800 & 0.433626576690118 \tabularnewline
10 & 1822.5 & 1717.42247406297 & 49.3708619782162 & 106.679397072275 & -0.141938122958428 \tabularnewline
11 & 3078.7 & 2902.70124212115 & 86.8374933633061 & 154.83576192816 & 1.76428976802993 \tabularnewline
12 & 1589.1 & 1679.05023825321 & 67.1945710549171 & -64.958398785773 & -2.03750832693580 \tabularnewline
13 & 1791.5 & 1949.63708045745 & 64.7650578145714 & -162.043352650802 & 0.323219937913877 \tabularnewline
14 & 2558.1 & 2506.84682244767 & 84.263318888183 & 42.8163233388957 & 0.726993770255664 \tabularnewline
15 & 2111.8 & 1944.29561110069 & 64.329629166144 & 179.386023662537 & -1.00026155177559 \tabularnewline
16 & 2083.1 & 2134.63018165642 & 66.1984410650525 & -53.8972415275152 & 0.195339259616548 \tabularnewline
17 & 2052.1 & 2263.79552755699 & 66.174771687948 & -212.885107513344 & 0.0987019302256869 \tabularnewline
18 & 2243.5 & 2159.90254881728 & 60.6533214443497 & 86.5909073839647 & -0.255137574025964 \tabularnewline
19 & 2622 & 2424.04473580615 & 66.5839093529423 & 194.243876256577 & 0.313747641755618 \tabularnewline
20 & 1952.6 & 2076.86018284819 & 59.9630996849717 & -116.564294830252 & -0.640085582793468 \tabularnewline
21 & 808.9 & 1144.75520068021 & 53.1024230173618 & -317.330581530955 & -1.54300529308708 \tabularnewline
22 & 1709.8 & 1574.99310673692 & 63.9033070902898 & 128.077679713886 & 0.570837091286128 \tabularnewline
23 & 1582.1 & 1380.14961731873 & 56.7032657933839 & 206.653722283612 & -0.398163486321655 \tabularnewline
24 & 865.6 & 941.39826291358 & 48.0198461424117 & -66.6457330207683 & -0.765112410724549 \tabularnewline
25 & 1116.1 & 1405.96021672508 & 52.9702601735526 & -297.574231676639 & 0.644797905478254 \tabularnewline
26 & 1119.4 & 1029.35720633031 & 41.5657790094912 & 97.763903426313 & -0.653569597301523 \tabularnewline
27 & 2350 & 1951.68899559281 & 65.2044682151926 & 382.324558022941 & 1.35362415591016 \tabularnewline
28 & 1975.6 & 2087.12084008529 & 66.5397906997679 & -112.811878217570 & 0.108288350326667 \tabularnewline
29 & 2536.5 & 2710.54450694367 & 75.1200372660775 & -184.297455293075 & 0.859445697977624 \tabularnewline
30 & 2785 & 2794.43918763284 & 75.3431442489767 & -9.59754576186648 & 0.0133910501349597 \tabularnewline
31 & 2819.7 & 2504.94149934109 & 65.8072491733637 & 321.376837369521 & -0.560261724028455 \tabularnewline
32 & 1829.5 & 2077.35815975666 & 55.7813904742582 & -238.819698975269 & -0.759839684374817 \tabularnewline
33 & 758.3 & 1089.74874544031 & 37.0415259598888 & -312.318146003386 & -1.60708060136847 \tabularnewline
34 & 2921.6 & 2647.77453200980 & 74.8521220679837 & 246.312313123360 & 2.32546493039416 \tabularnewline
35 & 2482 & 2189.94070844713 & 61.180622788213 & 301.720827202298 & -0.817586433318246 \tabularnewline
36 & 1892.7 & 2044.76059764758 & 56.7627624581198 & -148.290042907563 & -0.317475004096619 \tabularnewline
37 & 1855.1 & 2310.74201058281 & 60.9126764785346 & -459.466679830692 & 0.321814560881375 \tabularnewline
38 & 2151.3 & 1912.34408154991 & 49.6082982037528 & 247.275398265569 & -0.703030177765467 \tabularnewline
39 & 1642.2 & 1401.29836656822 & 35.3859631650194 & 251.070392891113 & -0.860219024490696 \tabularnewline
40 & 1640.5 & 1756.82692524019 & 42.5217123000626 & -122.165239699443 & 0.492111698744722 \tabularnewline
41 & 1366.1 & 1772.74907989586 & 41.9571434471202 & -406.163857432573 & -0.0408763740474573 \tabularnewline
42 & 1532.8 & 1299.40519986005 & 29.3090398873362 & 242.735406085996 & -0.789256053377551 \tabularnewline
43 & 824.4 & 702.576761551008 & 13.5330939003320 & 133.180143958761 & -0.9604665336808 \tabularnewline
44 & -518.7 & -259.91797349528 & -8.90646526517968 & -241.008012500901 & -1.49932162240393 \tabularnewline
45 & -978.5 & -599.261100829277 & -16.2626176017902 & -373.220480693438 & -0.507453521652441 \tabularnewline
46 & 1162.5 & 645.302571722459 & 14.7253768909594 & 494.33373259316 & 1.93189342701042 \tabularnewline
47 & 1243.4 & 958.480116986247 & 22.2199668951932 & 279.506350167183 & 0.457735295304846 \tabularnewline
48 & 1199.5 & 1356.02310821577 & 31.0565994374538 & -163.350665869844 & 0.576251741741529 \tabularnewline
49 & 883.1 & 1408.60912704329 & 31.5526558117382 & -525.900810237818 & 0.0330468449702881 \tabularnewline
50 & 1437.2 & 1041.37404078267 & 21.7185000690529 & 403.059029505694 & -0.611178060320598 \tabularnewline
51 & 534.5 & 397.422796403572 & 5.01968152845378 & 149.151787224210 & -1.02080702000920 \tabularnewline
52 & -1901.9 & -1461.04183172475 & -39.6640626649202 & -406.986280739806 & -2.85994318013708 \tabularnewline
53 & -2521.1 & -1991.11924917610 & -51.2521024069567 & -521.066134070186 & -0.75249704565682 \tabularnewline
54 & -1721.1 & -2197.50832982783 & -55.0939319890017 & 479.222395490493 & -0.237790496988483 \tabularnewline
55 & -3094.5 & -3305.76705295137 & -81.5250695603381 & 230.370331104769 & -1.61487216135076 \tabularnewline
56 & -3694.8 & -3359.74803760573 & -80.8552193909207 & -335.552321681858 & 0.0422595034494663 \tabularnewline
57 & -2492.1 & -2187.74927976893 & -50.691880992268 & -327.110697861798 & 1.92188280508946 \tabularnewline
58 & -464.6 & -1212.04089779946 & -25.1622688718237 & 728.822442179367 & 1.57333724598374 \tabularnewline
59 & -626.1 & -888.620432616458 & -16.4024760290047 & 256.197649187543 & 0.534457103630498 \tabularnewline
60 & -1711.4 & -1176.84040422838 & -23.0854439324801 & -529.624050185194 & -0.416935505309733 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115996&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]2540.9[/C][C]2540.9[/C][C]0[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]2[/C][C]2370.3[/C][C]2403.24924220022[/C][C]-33.0262994931002[/C][C]-32.8106022456320[/C][C]-0.0515760048945985[/C][/ROW]
[ROW][C]3[/C][C]1807.5[/C][C]1899.08565213502[/C][C]-60.1141201628654[/C][C]-82.2348547681139[/C][C]-0.74644362976417[/C][/ROW]
[ROW][C]4[/C][C]1834.8[/C][C]1882.64971758962[/C][C]-58.3161433188035[/C][C]-48.7315746149965[/C][C]0.0691987457464548[/C][/ROW]
[ROW][C]5[/C][C]786.8[/C][C]951.72914141744[/C][C]29.4836641318971[/C][C]-147.250014763606[/C][C]-1.54486561578287[/C][/ROW]
[ROW][C]6[/C][C]1561.4[/C][C]1434.80877129596[/C][C]69.3114047653[/C][C]120.44137654359[/C][C]0.596275212152444[/C][/ROW]
[ROW][C]7[/C][C]1347.2[/C][C]1332.38017698497[/C][C]62.9511849408438[/C][C]18.1019577113344[/C][C]-0.268448903470677[/C][/ROW]
[ROW][C]8[/C][C]1549.8[/C][C]1432.84395008494[/C][C]63.67029822502[/C][C]116.223871151149[/C][C]0.0586189578570718[/C][/ROW]
[ROW][C]9[/C][C]1553.8[/C][C]1761.99215161447[/C][C]54.7134148070017[/C][C]-213.408599611800[/C][C]0.433626576690118[/C][/ROW]
[ROW][C]10[/C][C]1822.5[/C][C]1717.42247406297[/C][C]49.3708619782162[/C][C]106.679397072275[/C][C]-0.141938122958428[/C][/ROW]
[ROW][C]11[/C][C]3078.7[/C][C]2902.70124212115[/C][C]86.8374933633061[/C][C]154.83576192816[/C][C]1.76428976802993[/C][/ROW]
[ROW][C]12[/C][C]1589.1[/C][C]1679.05023825321[/C][C]67.1945710549171[/C][C]-64.958398785773[/C][C]-2.03750832693580[/C][/ROW]
[ROW][C]13[/C][C]1791.5[/C][C]1949.63708045745[/C][C]64.7650578145714[/C][C]-162.043352650802[/C][C]0.323219937913877[/C][/ROW]
[ROW][C]14[/C][C]2558.1[/C][C]2506.84682244767[/C][C]84.263318888183[/C][C]42.8163233388957[/C][C]0.726993770255664[/C][/ROW]
[ROW][C]15[/C][C]2111.8[/C][C]1944.29561110069[/C][C]64.329629166144[/C][C]179.386023662537[/C][C]-1.00026155177559[/C][/ROW]
[ROW][C]16[/C][C]2083.1[/C][C]2134.63018165642[/C][C]66.1984410650525[/C][C]-53.8972415275152[/C][C]0.195339259616548[/C][/ROW]
[ROW][C]17[/C][C]2052.1[/C][C]2263.79552755699[/C][C]66.174771687948[/C][C]-212.885107513344[/C][C]0.0987019302256869[/C][/ROW]
[ROW][C]18[/C][C]2243.5[/C][C]2159.90254881728[/C][C]60.6533214443497[/C][C]86.5909073839647[/C][C]-0.255137574025964[/C][/ROW]
[ROW][C]19[/C][C]2622[/C][C]2424.04473580615[/C][C]66.5839093529423[/C][C]194.243876256577[/C][C]0.313747641755618[/C][/ROW]
[ROW][C]20[/C][C]1952.6[/C][C]2076.86018284819[/C][C]59.9630996849717[/C][C]-116.564294830252[/C][C]-0.640085582793468[/C][/ROW]
[ROW][C]21[/C][C]808.9[/C][C]1144.75520068021[/C][C]53.1024230173618[/C][C]-317.330581530955[/C][C]-1.54300529308708[/C][/ROW]
[ROW][C]22[/C][C]1709.8[/C][C]1574.99310673692[/C][C]63.9033070902898[/C][C]128.077679713886[/C][C]0.570837091286128[/C][/ROW]
[ROW][C]23[/C][C]1582.1[/C][C]1380.14961731873[/C][C]56.7032657933839[/C][C]206.653722283612[/C][C]-0.398163486321655[/C][/ROW]
[ROW][C]24[/C][C]865.6[/C][C]941.39826291358[/C][C]48.0198461424117[/C][C]-66.6457330207683[/C][C]-0.765112410724549[/C][/ROW]
[ROW][C]25[/C][C]1116.1[/C][C]1405.96021672508[/C][C]52.9702601735526[/C][C]-297.574231676639[/C][C]0.644797905478254[/C][/ROW]
[ROW][C]26[/C][C]1119.4[/C][C]1029.35720633031[/C][C]41.5657790094912[/C][C]97.763903426313[/C][C]-0.653569597301523[/C][/ROW]
[ROW][C]27[/C][C]2350[/C][C]1951.68899559281[/C][C]65.2044682151926[/C][C]382.324558022941[/C][C]1.35362415591016[/C][/ROW]
[ROW][C]28[/C][C]1975.6[/C][C]2087.12084008529[/C][C]66.5397906997679[/C][C]-112.811878217570[/C][C]0.108288350326667[/C][/ROW]
[ROW][C]29[/C][C]2536.5[/C][C]2710.54450694367[/C][C]75.1200372660775[/C][C]-184.297455293075[/C][C]0.859445697977624[/C][/ROW]
[ROW][C]30[/C][C]2785[/C][C]2794.43918763284[/C][C]75.3431442489767[/C][C]-9.59754576186648[/C][C]0.0133910501349597[/C][/ROW]
[ROW][C]31[/C][C]2819.7[/C][C]2504.94149934109[/C][C]65.8072491733637[/C][C]321.376837369521[/C][C]-0.560261724028455[/C][/ROW]
[ROW][C]32[/C][C]1829.5[/C][C]2077.35815975666[/C][C]55.7813904742582[/C][C]-238.819698975269[/C][C]-0.759839684374817[/C][/ROW]
[ROW][C]33[/C][C]758.3[/C][C]1089.74874544031[/C][C]37.0415259598888[/C][C]-312.318146003386[/C][C]-1.60708060136847[/C][/ROW]
[ROW][C]34[/C][C]2921.6[/C][C]2647.77453200980[/C][C]74.8521220679837[/C][C]246.312313123360[/C][C]2.32546493039416[/C][/ROW]
[ROW][C]35[/C][C]2482[/C][C]2189.94070844713[/C][C]61.180622788213[/C][C]301.720827202298[/C][C]-0.817586433318246[/C][/ROW]
[ROW][C]36[/C][C]1892.7[/C][C]2044.76059764758[/C][C]56.7627624581198[/C][C]-148.290042907563[/C][C]-0.317475004096619[/C][/ROW]
[ROW][C]37[/C][C]1855.1[/C][C]2310.74201058281[/C][C]60.9126764785346[/C][C]-459.466679830692[/C][C]0.321814560881375[/C][/ROW]
[ROW][C]38[/C][C]2151.3[/C][C]1912.34408154991[/C][C]49.6082982037528[/C][C]247.275398265569[/C][C]-0.703030177765467[/C][/ROW]
[ROW][C]39[/C][C]1642.2[/C][C]1401.29836656822[/C][C]35.3859631650194[/C][C]251.070392891113[/C][C]-0.860219024490696[/C][/ROW]
[ROW][C]40[/C][C]1640.5[/C][C]1756.82692524019[/C][C]42.5217123000626[/C][C]-122.165239699443[/C][C]0.492111698744722[/C][/ROW]
[ROW][C]41[/C][C]1366.1[/C][C]1772.74907989586[/C][C]41.9571434471202[/C][C]-406.163857432573[/C][C]-0.0408763740474573[/C][/ROW]
[ROW][C]42[/C][C]1532.8[/C][C]1299.40519986005[/C][C]29.3090398873362[/C][C]242.735406085996[/C][C]-0.789256053377551[/C][/ROW]
[ROW][C]43[/C][C]824.4[/C][C]702.576761551008[/C][C]13.5330939003320[/C][C]133.180143958761[/C][C]-0.9604665336808[/C][/ROW]
[ROW][C]44[/C][C]-518.7[/C][C]-259.91797349528[/C][C]-8.90646526517968[/C][C]-241.008012500901[/C][C]-1.49932162240393[/C][/ROW]
[ROW][C]45[/C][C]-978.5[/C][C]-599.261100829277[/C][C]-16.2626176017902[/C][C]-373.220480693438[/C][C]-0.507453521652441[/C][/ROW]
[ROW][C]46[/C][C]1162.5[/C][C]645.302571722459[/C][C]14.7253768909594[/C][C]494.33373259316[/C][C]1.93189342701042[/C][/ROW]
[ROW][C]47[/C][C]1243.4[/C][C]958.480116986247[/C][C]22.2199668951932[/C][C]279.506350167183[/C][C]0.457735295304846[/C][/ROW]
[ROW][C]48[/C][C]1199.5[/C][C]1356.02310821577[/C][C]31.0565994374538[/C][C]-163.350665869844[/C][C]0.576251741741529[/C][/ROW]
[ROW][C]49[/C][C]883.1[/C][C]1408.60912704329[/C][C]31.5526558117382[/C][C]-525.900810237818[/C][C]0.0330468449702881[/C][/ROW]
[ROW][C]50[/C][C]1437.2[/C][C]1041.37404078267[/C][C]21.7185000690529[/C][C]403.059029505694[/C][C]-0.611178060320598[/C][/ROW]
[ROW][C]51[/C][C]534.5[/C][C]397.422796403572[/C][C]5.01968152845378[/C][C]149.151787224210[/C][C]-1.02080702000920[/C][/ROW]
[ROW][C]52[/C][C]-1901.9[/C][C]-1461.04183172475[/C][C]-39.6640626649202[/C][C]-406.986280739806[/C][C]-2.85994318013708[/C][/ROW]
[ROW][C]53[/C][C]-2521.1[/C][C]-1991.11924917610[/C][C]-51.2521024069567[/C][C]-521.066134070186[/C][C]-0.75249704565682[/C][/ROW]
[ROW][C]54[/C][C]-1721.1[/C][C]-2197.50832982783[/C][C]-55.0939319890017[/C][C]479.222395490493[/C][C]-0.237790496988483[/C][/ROW]
[ROW][C]55[/C][C]-3094.5[/C][C]-3305.76705295137[/C][C]-81.5250695603381[/C][C]230.370331104769[/C][C]-1.61487216135076[/C][/ROW]
[ROW][C]56[/C][C]-3694.8[/C][C]-3359.74803760573[/C][C]-80.8552193909207[/C][C]-335.552321681858[/C][C]0.0422595034494663[/C][/ROW]
[ROW][C]57[/C][C]-2492.1[/C][C]-2187.74927976893[/C][C]-50.691880992268[/C][C]-327.110697861798[/C][C]1.92188280508946[/C][/ROW]
[ROW][C]58[/C][C]-464.6[/C][C]-1212.04089779946[/C][C]-25.1622688718237[/C][C]728.822442179367[/C][C]1.57333724598374[/C][/ROW]
[ROW][C]59[/C][C]-626.1[/C][C]-888.620432616458[/C][C]-16.4024760290047[/C][C]256.197649187543[/C][C]0.534457103630498[/C][/ROW]
[ROW][C]60[/C][C]-1711.4[/C][C]-1176.84040422838[/C][C]-23.0854439324801[/C][C]-529.624050185194[/C][C]-0.416935505309733[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115996&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115996&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
t	Observed	Level	Slope	Seasonal	Stand. Residuals
1	2540.9	2540.9	0	0	0
2	2370.3	2403.24924220022	-33.0262994931002	-32.8106022456320	-0.0515760048945985
3	1807.5	1899.08565213502	-60.1141201628654	-82.2348547681139	-0.74644362976417
4	1834.8	1882.64971758962	-58.3161433188035	-48.7315746149965	0.0691987457464548
5	786.8	951.72914141744	29.4836641318971	-147.250014763606	-1.54486561578287
6	1561.4	1434.80877129596	69.3114047653	120.44137654359	0.596275212152444
7	1347.2	1332.38017698497	62.9511849408438	18.1019577113344	-0.268448903470677
8	1549.8	1432.84395008494	63.67029822502	116.223871151149	0.0586189578570718
9	1553.8	1761.99215161447	54.7134148070017	-213.408599611800	0.433626576690118
10	1822.5	1717.42247406297	49.3708619782162	106.679397072275	-0.141938122958428
11	3078.7	2902.70124212115	86.8374933633061	154.83576192816	1.76428976802993
12	1589.1	1679.05023825321	67.1945710549171	-64.958398785773	-2.03750832693580
13	1791.5	1949.63708045745	64.7650578145714	-162.043352650802	0.323219937913877
14	2558.1	2506.84682244767	84.263318888183	42.8163233388957	0.726993770255664
15	2111.8	1944.29561110069	64.329629166144	179.386023662537	-1.00026155177559
16	2083.1	2134.63018165642	66.1984410650525	-53.8972415275152	0.195339259616548
17	2052.1	2263.79552755699	66.174771687948	-212.885107513344	0.0987019302256869
18	2243.5	2159.90254881728	60.6533214443497	86.5909073839647	-0.255137574025964
19	2622	2424.04473580615	66.5839093529423	194.243876256577	0.313747641755618
20	1952.6	2076.86018284819	59.9630996849717	-116.564294830252	-0.640085582793468
21	808.9	1144.75520068021	53.1024230173618	-317.330581530955	-1.54300529308708
22	1709.8	1574.99310673692	63.9033070902898	128.077679713886	0.570837091286128
23	1582.1	1380.14961731873	56.7032657933839	206.653722283612	-0.398163486321655
24	865.6	941.39826291358	48.0198461424117	-66.6457330207683	-0.765112410724549
25	1116.1	1405.96021672508	52.9702601735526	-297.574231676639	0.644797905478254
26	1119.4	1029.35720633031	41.5657790094912	97.763903426313	-0.653569597301523
27	2350	1951.68899559281	65.2044682151926	382.324558022941	1.35362415591016
28	1975.6	2087.12084008529	66.5397906997679	-112.811878217570	0.108288350326667
29	2536.5	2710.54450694367	75.1200372660775	-184.297455293075	0.859445697977624
30	2785	2794.43918763284	75.3431442489767	-9.59754576186648	0.0133910501349597
31	2819.7	2504.94149934109	65.8072491733637	321.376837369521	-0.560261724028455
32	1829.5	2077.35815975666	55.7813904742582	-238.819698975269	-0.759839684374817
33	758.3	1089.74874544031	37.0415259598888	-312.318146003386	-1.60708060136847
34	2921.6	2647.77453200980	74.8521220679837	246.312313123360	2.32546493039416
35	2482	2189.94070844713	61.180622788213	301.720827202298	-0.817586433318246
36	1892.7	2044.76059764758	56.7627624581198	-148.290042907563	-0.317475004096619
37	1855.1	2310.74201058281	60.9126764785346	-459.466679830692	0.321814560881375
38	2151.3	1912.34408154991	49.6082982037528	247.275398265569	-0.703030177765467
39	1642.2	1401.29836656822	35.3859631650194	251.070392891113	-0.860219024490696
40	1640.5	1756.82692524019	42.5217123000626	-122.165239699443	0.492111698744722
41	1366.1	1772.74907989586	41.9571434471202	-406.163857432573	-0.0408763740474573
42	1532.8	1299.40519986005	29.3090398873362	242.735406085996	-0.789256053377551
43	824.4	702.576761551008	13.5330939003320	133.180143958761	-0.9604665336808
44	-518.7	-259.91797349528	-8.90646526517968	-241.008012500901	-1.49932162240393
45	-978.5	-599.261100829277	-16.2626176017902	-373.220480693438	-0.507453521652441
46	1162.5	645.302571722459	14.7253768909594	494.33373259316	1.93189342701042
47	1243.4	958.480116986247	22.2199668951932	279.506350167183	0.457735295304846
48	1199.5	1356.02310821577	31.0565994374538	-163.350665869844	0.576251741741529
49	883.1	1408.60912704329	31.5526558117382	-525.900810237818	0.0330468449702881
50	1437.2	1041.37404078267	21.7185000690529	403.059029505694	-0.611178060320598
51	534.5	397.422796403572	5.01968152845378	149.151787224210	-1.02080702000920
52	-1901.9	-1461.04183172475	-39.6640626649202	-406.986280739806	-2.85994318013708
53	-2521.1	-1991.11924917610	-51.2521024069567	-521.066134070186	-0.75249704565682
54	-1721.1	-2197.50832982783	-55.0939319890017	479.222395490493	-0.237790496988483
55	-3094.5	-3305.76705295137	-81.5250695603381	230.370331104769	-1.61487216135076
56	-3694.8	-3359.74803760573	-80.8552193909207	-335.552321681858	0.0422595034494663
57	-2492.1	-2187.74927976893	-50.691880992268	-327.110697861798	1.92188280508946
58	-464.6	-1212.04089779946	-25.1622688718237	728.822442179367	1.57333724598374
59	-626.1	-888.620432616458	-16.4024760290047	256.197649187543	0.534457103630498
60	-1711.4	-1176.84040422838	-23.0854439324801	-529.624050185194	-0.416935505309733

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 4 ; par2 = periodic ; par3 = 0 ; par5 = 1 ; par7 = 1 ; par8 = FALSE ;

Parameters (R input):

par1 = 4 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1)
nx <- length(x)
x <- ts(x,frequency=par1)
m <- StructTS(x,type='BSM')
m$coef
m$fitted
m$resid
mylevel <- as.numeric(m$fitted[,'level'])
myslope <- as.numeric(m$fitted[,'slope'])
myseas <- as.numeric(m$fitted[,'sea'])
myresid <- as.numeric(m$resid)
myfit <- mylevel+myseas
bitmap(file='test1.png')
plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time')
grid()
dev.off()
mylagmax <- nx/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level')
acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(mylevel,main='Level')
spectrum(myseas,main='Seasonal')
spectrum(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(mylevel,main='Level')
cpgram(myseas,main='Seasonal')
cpgram(myresid,main='Standardized Residals')
par(op)
dev.off()
bitmap(file='test5.png')
op <- par(mfrow = c(2,2))
hist(m$resid,main='Residual Histogram')
plot(density(m$resid),main='Residual Kernel Density')
qqnorm(m$resid,main='Residual Normal QQ Plot')
qqline(m$resid)
plot(m$resid^2, myfit^2,main='Sq.Resid vs. Sq.Fit',xlab='Squared residuals',ylab='Squared Fit')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Structural Time Series Model',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Level',header=TRUE)
a<-table.element(a,'Slope',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Stand. Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:nx) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,mylevel[i])
a<-table.element(a,myslope[i])
a<-table.element(a,myseas[i])
a<-table.element(a,myresid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code