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rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 10 Jan 2013 07:42:49 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Jan/10/t13578218232sxcp3x72i6id9h.htm/, Retrieved Mon, 29 Apr 2024 18:22:16 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=205130, Retrieved Mon, 29 Apr 2024 18:22:16 +0000

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Estimated Impact

130

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-       [Classical Decomposition] [] [2013-01-10 12:42:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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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	'Herman Ole Andreas Wold' @ wold.wessa.net

\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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205130&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205130&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205130&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	530.3	NA	NA	1.00160333338385	NA
2	527.76	NA	NA	0.99573322571617	NA
3	521.41	NA	NA	0.990467383918957	NA
4	1601.93	NA	NA	0.981735067903153	NA
5	1577.49	NA	NA	0.984973673826725	NA
6	1551.43	NA	NA	0.988134293444604	NA
7	1551.43	1339.20505654352	1284.74541666667	1.04238944087316	1.15847083493265
8	1516.88	1381.03973189035	1349.22833333333	1.0235774759328	1.09836086896915
9	1485.95	1426.55371371764	1410.45041666667	1.01141713091129	1.04163620739353
10	1438.22	1424.24256505491	1422.975	1.00089078518942	1.00981394271456
11	1385.06	1376.55033531588	1388.07416666667	0.991697971457491	1.00618187687424
12	1329.49	1336.26484614929	1353.34375	0.987380217442382	0.994930012438169
13	1329.49	1320.77049558745	1318.65625	1.00160333338385	1.00660183161396
14	1276.16	1277.84021433764	1283.31583333333	0.99573322571617	0.998685113898606
15	1242.34	1236.39465761963	1248.29416666667	0.990467383918957	1.0048086121561
16	1181.59	1193.35501574641	1215.55708333333	0.981735067903153	0.990141227387351
17	1160.21	1167.24305216836	1185.05	0.984973673826725	0.993974646364102
18	1135.18	1143.34178208382	1157.07125	0.988134293444604	0.99286146783778
19	1135.18	1178.63364975569	1130.70375	1.04238944087316	0.963132182960588
20	1084.96	1131.92144579783	1105.84833333333	1.0235774759328	0.958511744810414
21	1077.35	1095.40352376695	1083.03833333333	1.01141713091129	0.98351883723647
22	1061.13	1063.27547375462	1062.32916666667	1.00089078518942	0.997982203288257
23	1029.98	1035.10087280079	1043.76625	0.991697971457491	0.995052778975119
24	1013.08	1013.37588152552	1026.32791666667	0.987380217442382	0.99970802391204
25	1013.08	1011.05387816905	1009.43541666667	1.00160333338385	1.00200397018863
26	996.04	989.892420569657	994.134166666667	0.99573322571617	1.00621035104684
27	975.02	970.556100638983	979.897083333333	0.990467383918957	1.00459932131494
28	951.89	947.625092025136	965.255416666667	0.981735067903153	1.00450062794955
29	944.4	936.942253433959	951.235833333333	0.984973673826725	1.00795966511139
30	932.47	926.92637325029	938.057083333333	0.988134293444604	1.00598065489309
31	932.47	964.439124155733	925.219583333333	1.04238944087316	0.966852107763962
32	920.44	934.021697129133	912.507083333333	1.0235774759328	0.985458906178648
33	900.18	910.651327853818	900.371666666667	1.01141713091129	0.988501276467146
34	886.9	890.060897431912	889.26875	1.00089078518942	0.996448672848081
35	867.74	871.400875444817	878.695833333333	0.991697971457491	0.995798861869461
36	859.03	857.455791530226	868.415	0.987380217442382	1.00183590627683
37	859.03	859.853090965589	858.476666666667	1.00160333338385	0.999042753960837
38	844.99	845.326477305211	848.94875	0.99573322571617	0.999601955795489
39	834.82	832.378059382166	840.389166666667	0.990467383918957	1.00293369171653
40	825.62	817.091552115341	832.293333333333	0.981735067903153	1.01043756707872
41	816.92	812.101765144791	824.490833333333	0.984973673826725	1.00593304319976
42	813.21	807.210198095875	816.903333333333	0.988134293444604	1.00743276276523
43	813.21	843.44246681958	809.143333333333	1.04238944087316	0.964155863607889
44	811.03	820.36237472971	801.465833333333	1.0235774759328	0.988624082457725
45	804.16	802.873032688692	793.81	1.01141713091129	1.00160295247058
46	788.62	786.755623189895	786.055416666667	1.00089078518942	1.00236970255458
47	778.76	772.071580208658	778.535	0.991697971457491	1.00866295297326
48	765.91	761.758489447287	771.494583333333	0.987380217442382	1.00544990388716
49	765.91	765.888091578905	764.662083333333	1.00160333338385	1.000028605251
50	753.85	754.59899977755	757.8325	0.99573322571617	0.999007420129406
51	742.22	744.040749578894	751.201666666667	0.990467383918957	0.997552889972862
52	732.11	731.536613397808	745.146666666667	0.981735067903153	1.00078381121559
53	729.94	728.306771466772	739.4175	0.984973673826725	1.00224250082138
54	731.22	725.204933082908	733.913333333333	0.988134293444604	1.00829429950445
55	731.22	759.57702435413	728.688333333333	1.04238944087316	0.962667348478265
56	729.11	740.722502724144	723.660416666667	1.0235774759328	0.984322735327418
57	726.94	726.926141752368	718.720416666667	1.01141713091129	1.00001906417562
58	720.52	714.331165973588	713.695416666667	1.00089078518942	1.00866381633787
59	709.36	702.627516549859	708.509583333333	0.991697971457491	1.00958186705126
60	703.21	693.9427476628	702.812083333333	0.987380217442382	1.01335449122916
61	703.21	697.905099994921	696.787916666667	1.00160333338385	1.00760117672892
62	695.88	687.782396110086	690.729583333333	0.99573322571617	1.01177349687301
63	681.63	677.979876629446	684.505	0.990467383918957	1.00538382258291
64	672.1	665.831130584441	678.21875	0.981735067903153	1.00941510411214
65	665.49	662.06811271332	672.168333333333	0.984973673826725	1.00516848224672
66	658.93	658.463049122681	666.37	0.988134293444604	1.0007091527428
67	658.93	NA	NA	1.04238944087316	NA
68	656	NA	NA	1.0235774759328	NA
69	650.66	NA	NA	1.01141713091129	NA
70	645.93	NA	NA	1.00089078518942	NA
71	638.74	NA	NA	0.991697971457491	NA
72	634.67	NA	NA	0.987380217442382	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 530.3 & NA & NA & 1.00160333338385 & NA \tabularnewline
2 & 527.76 & NA & NA & 0.99573322571617 & NA \tabularnewline
3 & 521.41 & NA & NA & 0.990467383918957 & NA \tabularnewline
4 & 1601.93 & NA & NA & 0.981735067903153 & NA \tabularnewline
5 & 1577.49 & NA & NA & 0.984973673826725 & NA \tabularnewline
6 & 1551.43 & NA & NA & 0.988134293444604 & NA \tabularnewline
7 & 1551.43 & 1339.20505654352 & 1284.74541666667 & 1.04238944087316 & 1.15847083493265 \tabularnewline
8 & 1516.88 & 1381.03973189035 & 1349.22833333333 & 1.0235774759328 & 1.09836086896915 \tabularnewline
9 & 1485.95 & 1426.55371371764 & 1410.45041666667 & 1.01141713091129 & 1.04163620739353 \tabularnewline
10 & 1438.22 & 1424.24256505491 & 1422.975 & 1.00089078518942 & 1.00981394271456 \tabularnewline
11 & 1385.06 & 1376.55033531588 & 1388.07416666667 & 0.991697971457491 & 1.00618187687424 \tabularnewline
12 & 1329.49 & 1336.26484614929 & 1353.34375 & 0.987380217442382 & 0.994930012438169 \tabularnewline
13 & 1329.49 & 1320.77049558745 & 1318.65625 & 1.00160333338385 & 1.00660183161396 \tabularnewline
14 & 1276.16 & 1277.84021433764 & 1283.31583333333 & 0.99573322571617 & 0.998685113898606 \tabularnewline
15 & 1242.34 & 1236.39465761963 & 1248.29416666667 & 0.990467383918957 & 1.0048086121561 \tabularnewline
16 & 1181.59 & 1193.35501574641 & 1215.55708333333 & 0.981735067903153 & 0.990141227387351 \tabularnewline
17 & 1160.21 & 1167.24305216836 & 1185.05 & 0.984973673826725 & 0.993974646364102 \tabularnewline
18 & 1135.18 & 1143.34178208382 & 1157.07125 & 0.988134293444604 & 0.99286146783778 \tabularnewline
19 & 1135.18 & 1178.63364975569 & 1130.70375 & 1.04238944087316 & 0.963132182960588 \tabularnewline
20 & 1084.96 & 1131.92144579783 & 1105.84833333333 & 1.0235774759328 & 0.958511744810414 \tabularnewline
21 & 1077.35 & 1095.40352376695 & 1083.03833333333 & 1.01141713091129 & 0.98351883723647 \tabularnewline
22 & 1061.13 & 1063.27547375462 & 1062.32916666667 & 1.00089078518942 & 0.997982203288257 \tabularnewline
23 & 1029.98 & 1035.10087280079 & 1043.76625 & 0.991697971457491 & 0.995052778975119 \tabularnewline
24 & 1013.08 & 1013.37588152552 & 1026.32791666667 & 0.987380217442382 & 0.99970802391204 \tabularnewline
25 & 1013.08 & 1011.05387816905 & 1009.43541666667 & 1.00160333338385 & 1.00200397018863 \tabularnewline
26 & 996.04 & 989.892420569657 & 994.134166666667 & 0.99573322571617 & 1.00621035104684 \tabularnewline
27 & 975.02 & 970.556100638983 & 979.897083333333 & 0.990467383918957 & 1.00459932131494 \tabularnewline
28 & 951.89 & 947.625092025136 & 965.255416666667 & 0.981735067903153 & 1.00450062794955 \tabularnewline
29 & 944.4 & 936.942253433959 & 951.235833333333 & 0.984973673826725 & 1.00795966511139 \tabularnewline
30 & 932.47 & 926.92637325029 & 938.057083333333 & 0.988134293444604 & 1.00598065489309 \tabularnewline
31 & 932.47 & 964.439124155733 & 925.219583333333 & 1.04238944087316 & 0.966852107763962 \tabularnewline
32 & 920.44 & 934.021697129133 & 912.507083333333 & 1.0235774759328 & 0.985458906178648 \tabularnewline
33 & 900.18 & 910.651327853818 & 900.371666666667 & 1.01141713091129 & 0.988501276467146 \tabularnewline
34 & 886.9 & 890.060897431912 & 889.26875 & 1.00089078518942 & 0.996448672848081 \tabularnewline
35 & 867.74 & 871.400875444817 & 878.695833333333 & 0.991697971457491 & 0.995798861869461 \tabularnewline
36 & 859.03 & 857.455791530226 & 868.415 & 0.987380217442382 & 1.00183590627683 \tabularnewline
37 & 859.03 & 859.853090965589 & 858.476666666667 & 1.00160333338385 & 0.999042753960837 \tabularnewline
38 & 844.99 & 845.326477305211 & 848.94875 & 0.99573322571617 & 0.999601955795489 \tabularnewline
39 & 834.82 & 832.378059382166 & 840.389166666667 & 0.990467383918957 & 1.00293369171653 \tabularnewline
40 & 825.62 & 817.091552115341 & 832.293333333333 & 0.981735067903153 & 1.01043756707872 \tabularnewline
41 & 816.92 & 812.101765144791 & 824.490833333333 & 0.984973673826725 & 1.00593304319976 \tabularnewline
42 & 813.21 & 807.210198095875 & 816.903333333333 & 0.988134293444604 & 1.00743276276523 \tabularnewline
43 & 813.21 & 843.44246681958 & 809.143333333333 & 1.04238944087316 & 0.964155863607889 \tabularnewline
44 & 811.03 & 820.36237472971 & 801.465833333333 & 1.0235774759328 & 0.988624082457725 \tabularnewline
45 & 804.16 & 802.873032688692 & 793.81 & 1.01141713091129 & 1.00160295247058 \tabularnewline
46 & 788.62 & 786.755623189895 & 786.055416666667 & 1.00089078518942 & 1.00236970255458 \tabularnewline
47 & 778.76 & 772.071580208658 & 778.535 & 0.991697971457491 & 1.00866295297326 \tabularnewline
48 & 765.91 & 761.758489447287 & 771.494583333333 & 0.987380217442382 & 1.00544990388716 \tabularnewline
49 & 765.91 & 765.888091578905 & 764.662083333333 & 1.00160333338385 & 1.000028605251 \tabularnewline
50 & 753.85 & 754.59899977755 & 757.8325 & 0.99573322571617 & 0.999007420129406 \tabularnewline
51 & 742.22 & 744.040749578894 & 751.201666666667 & 0.990467383918957 & 0.997552889972862 \tabularnewline
52 & 732.11 & 731.536613397808 & 745.146666666667 & 0.981735067903153 & 1.00078381121559 \tabularnewline
53 & 729.94 & 728.306771466772 & 739.4175 & 0.984973673826725 & 1.00224250082138 \tabularnewline
54 & 731.22 & 725.204933082908 & 733.913333333333 & 0.988134293444604 & 1.00829429950445 \tabularnewline
55 & 731.22 & 759.57702435413 & 728.688333333333 & 1.04238944087316 & 0.962667348478265 \tabularnewline
56 & 729.11 & 740.722502724144 & 723.660416666667 & 1.0235774759328 & 0.984322735327418 \tabularnewline
57 & 726.94 & 726.926141752368 & 718.720416666667 & 1.01141713091129 & 1.00001906417562 \tabularnewline
58 & 720.52 & 714.331165973588 & 713.695416666667 & 1.00089078518942 & 1.00866381633787 \tabularnewline
59 & 709.36 & 702.627516549859 & 708.509583333333 & 0.991697971457491 & 1.00958186705126 \tabularnewline
60 & 703.21 & 693.9427476628 & 702.812083333333 & 0.987380217442382 & 1.01335449122916 \tabularnewline
61 & 703.21 & 697.905099994921 & 696.787916666667 & 1.00160333338385 & 1.00760117672892 \tabularnewline
62 & 695.88 & 687.782396110086 & 690.729583333333 & 0.99573322571617 & 1.01177349687301 \tabularnewline
63 & 681.63 & 677.979876629446 & 684.505 & 0.990467383918957 & 1.00538382258291 \tabularnewline
64 & 672.1 & 665.831130584441 & 678.21875 & 0.981735067903153 & 1.00941510411214 \tabularnewline
65 & 665.49 & 662.06811271332 & 672.168333333333 & 0.984973673826725 & 1.00516848224672 \tabularnewline
66 & 658.93 & 658.463049122681 & 666.37 & 0.988134293444604 & 1.0007091527428 \tabularnewline
67 & 658.93 & NA & NA & 1.04238944087316 & NA \tabularnewline
68 & 656 & NA & NA & 1.0235774759328 & NA \tabularnewline
69 & 650.66 & NA & NA & 1.01141713091129 & NA \tabularnewline
70 & 645.93 & NA & NA & 1.00089078518942 & NA \tabularnewline
71 & 638.74 & NA & NA & 0.991697971457491 & NA \tabularnewline
72 & 634.67 & NA & NA & 0.987380217442382 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=205130&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]530.3[/C][C]NA[/C][C]NA[/C][C]1.00160333338385[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]527.76[/C][C]NA[/C][C]NA[/C][C]0.99573322571617[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]521.41[/C][C]NA[/C][C]NA[/C][C]0.990467383918957[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1601.93[/C][C]NA[/C][C]NA[/C][C]0.981735067903153[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1577.49[/C][C]NA[/C][C]NA[/C][C]0.984973673826725[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1551.43[/C][C]NA[/C][C]NA[/C][C]0.988134293444604[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1551.43[/C][C]1339.20505654352[/C][C]1284.74541666667[/C][C]1.04238944087316[/C][C]1.15847083493265[/C][/ROW]
[ROW][C]8[/C][C]1516.88[/C][C]1381.03973189035[/C][C]1349.22833333333[/C][C]1.0235774759328[/C][C]1.09836086896915[/C][/ROW]
[ROW][C]9[/C][C]1485.95[/C][C]1426.55371371764[/C][C]1410.45041666667[/C][C]1.01141713091129[/C][C]1.04163620739353[/C][/ROW]
[ROW][C]10[/C][C]1438.22[/C][C]1424.24256505491[/C][C]1422.975[/C][C]1.00089078518942[/C][C]1.00981394271456[/C][/ROW]
[ROW][C]11[/C][C]1385.06[/C][C]1376.55033531588[/C][C]1388.07416666667[/C][C]0.991697971457491[/C][C]1.00618187687424[/C][/ROW]
[ROW][C]12[/C][C]1329.49[/C][C]1336.26484614929[/C][C]1353.34375[/C][C]0.987380217442382[/C][C]0.994930012438169[/C][/ROW]
[ROW][C]13[/C][C]1329.49[/C][C]1320.77049558745[/C][C]1318.65625[/C][C]1.00160333338385[/C][C]1.00660183161396[/C][/ROW]
[ROW][C]14[/C][C]1276.16[/C][C]1277.84021433764[/C][C]1283.31583333333[/C][C]0.99573322571617[/C][C]0.998685113898606[/C][/ROW]
[ROW][C]15[/C][C]1242.34[/C][C]1236.39465761963[/C][C]1248.29416666667[/C][C]0.990467383918957[/C][C]1.0048086121561[/C][/ROW]
[ROW][C]16[/C][C]1181.59[/C][C]1193.35501574641[/C][C]1215.55708333333[/C][C]0.981735067903153[/C][C]0.990141227387351[/C][/ROW]
[ROW][C]17[/C][C]1160.21[/C][C]1167.24305216836[/C][C]1185.05[/C][C]0.984973673826725[/C][C]0.993974646364102[/C][/ROW]
[ROW][C]18[/C][C]1135.18[/C][C]1143.34178208382[/C][C]1157.07125[/C][C]0.988134293444604[/C][C]0.99286146783778[/C][/ROW]
[ROW][C]19[/C][C]1135.18[/C][C]1178.63364975569[/C][C]1130.70375[/C][C]1.04238944087316[/C][C]0.963132182960588[/C][/ROW]
[ROW][C]20[/C][C]1084.96[/C][C]1131.92144579783[/C][C]1105.84833333333[/C][C]1.0235774759328[/C][C]0.958511744810414[/C][/ROW]
[ROW][C]21[/C][C]1077.35[/C][C]1095.40352376695[/C][C]1083.03833333333[/C][C]1.01141713091129[/C][C]0.98351883723647[/C][/ROW]
[ROW][C]22[/C][C]1061.13[/C][C]1063.27547375462[/C][C]1062.32916666667[/C][C]1.00089078518942[/C][C]0.997982203288257[/C][/ROW]
[ROW][C]23[/C][C]1029.98[/C][C]1035.10087280079[/C][C]1043.76625[/C][C]0.991697971457491[/C][C]0.995052778975119[/C][/ROW]
[ROW][C]24[/C][C]1013.08[/C][C]1013.37588152552[/C][C]1026.32791666667[/C][C]0.987380217442382[/C][C]0.99970802391204[/C][/ROW]
[ROW][C]25[/C][C]1013.08[/C][C]1011.05387816905[/C][C]1009.43541666667[/C][C]1.00160333338385[/C][C]1.00200397018863[/C][/ROW]
[ROW][C]26[/C][C]996.04[/C][C]989.892420569657[/C][C]994.134166666667[/C][C]0.99573322571617[/C][C]1.00621035104684[/C][/ROW]
[ROW][C]27[/C][C]975.02[/C][C]970.556100638983[/C][C]979.897083333333[/C][C]0.990467383918957[/C][C]1.00459932131494[/C][/ROW]
[ROW][C]28[/C][C]951.89[/C][C]947.625092025136[/C][C]965.255416666667[/C][C]0.981735067903153[/C][C]1.00450062794955[/C][/ROW]
[ROW][C]29[/C][C]944.4[/C][C]936.942253433959[/C][C]951.235833333333[/C][C]0.984973673826725[/C][C]1.00795966511139[/C][/ROW]
[ROW][C]30[/C][C]932.47[/C][C]926.92637325029[/C][C]938.057083333333[/C][C]0.988134293444604[/C][C]1.00598065489309[/C][/ROW]
[ROW][C]31[/C][C]932.47[/C][C]964.439124155733[/C][C]925.219583333333[/C][C]1.04238944087316[/C][C]0.966852107763962[/C][/ROW]
[ROW][C]32[/C][C]920.44[/C][C]934.021697129133[/C][C]912.507083333333[/C][C]1.0235774759328[/C][C]0.985458906178648[/C][/ROW]
[ROW][C]33[/C][C]900.18[/C][C]910.651327853818[/C][C]900.371666666667[/C][C]1.01141713091129[/C][C]0.988501276467146[/C][/ROW]
[ROW][C]34[/C][C]886.9[/C][C]890.060897431912[/C][C]889.26875[/C][C]1.00089078518942[/C][C]0.996448672848081[/C][/ROW]
[ROW][C]35[/C][C]867.74[/C][C]871.400875444817[/C][C]878.695833333333[/C][C]0.991697971457491[/C][C]0.995798861869461[/C][/ROW]
[ROW][C]36[/C][C]859.03[/C][C]857.455791530226[/C][C]868.415[/C][C]0.987380217442382[/C][C]1.00183590627683[/C][/ROW]
[ROW][C]37[/C][C]859.03[/C][C]859.853090965589[/C][C]858.476666666667[/C][C]1.00160333338385[/C][C]0.999042753960837[/C][/ROW]
[ROW][C]38[/C][C]844.99[/C][C]845.326477305211[/C][C]848.94875[/C][C]0.99573322571617[/C][C]0.999601955795489[/C][/ROW]
[ROW][C]39[/C][C]834.82[/C][C]832.378059382166[/C][C]840.389166666667[/C][C]0.990467383918957[/C][C]1.00293369171653[/C][/ROW]
[ROW][C]40[/C][C]825.62[/C][C]817.091552115341[/C][C]832.293333333333[/C][C]0.981735067903153[/C][C]1.01043756707872[/C][/ROW]
[ROW][C]41[/C][C]816.92[/C][C]812.101765144791[/C][C]824.490833333333[/C][C]0.984973673826725[/C][C]1.00593304319976[/C][/ROW]
[ROW][C]42[/C][C]813.21[/C][C]807.210198095875[/C][C]816.903333333333[/C][C]0.988134293444604[/C][C]1.00743276276523[/C][/ROW]
[ROW][C]43[/C][C]813.21[/C][C]843.44246681958[/C][C]809.143333333333[/C][C]1.04238944087316[/C][C]0.964155863607889[/C][/ROW]
[ROW][C]44[/C][C]811.03[/C][C]820.36237472971[/C][C]801.465833333333[/C][C]1.0235774759328[/C][C]0.988624082457725[/C][/ROW]
[ROW][C]45[/C][C]804.16[/C][C]802.873032688692[/C][C]793.81[/C][C]1.01141713091129[/C][C]1.00160295247058[/C][/ROW]
[ROW][C]46[/C][C]788.62[/C][C]786.755623189895[/C][C]786.055416666667[/C][C]1.00089078518942[/C][C]1.00236970255458[/C][/ROW]
[ROW][C]47[/C][C]778.76[/C][C]772.071580208658[/C][C]778.535[/C][C]0.991697971457491[/C][C]1.00866295297326[/C][/ROW]
[ROW][C]48[/C][C]765.91[/C][C]761.758489447287[/C][C]771.494583333333[/C][C]0.987380217442382[/C][C]1.00544990388716[/C][/ROW]
[ROW][C]49[/C][C]765.91[/C][C]765.888091578905[/C][C]764.662083333333[/C][C]1.00160333338385[/C][C]1.000028605251[/C][/ROW]
[ROW][C]50[/C][C]753.85[/C][C]754.59899977755[/C][C]757.8325[/C][C]0.99573322571617[/C][C]0.999007420129406[/C][/ROW]
[ROW][C]51[/C][C]742.22[/C][C]744.040749578894[/C][C]751.201666666667[/C][C]0.990467383918957[/C][C]0.997552889972862[/C][/ROW]
[ROW][C]52[/C][C]732.11[/C][C]731.536613397808[/C][C]745.146666666667[/C][C]0.981735067903153[/C][C]1.00078381121559[/C][/ROW]
[ROW][C]53[/C][C]729.94[/C][C]728.306771466772[/C][C]739.4175[/C][C]0.984973673826725[/C][C]1.00224250082138[/C][/ROW]
[ROW][C]54[/C][C]731.22[/C][C]725.204933082908[/C][C]733.913333333333[/C][C]0.988134293444604[/C][C]1.00829429950445[/C][/ROW]
[ROW][C]55[/C][C]731.22[/C][C]759.57702435413[/C][C]728.688333333333[/C][C]1.04238944087316[/C][C]0.962667348478265[/C][/ROW]
[ROW][C]56[/C][C]729.11[/C][C]740.722502724144[/C][C]723.660416666667[/C][C]1.0235774759328[/C][C]0.984322735327418[/C][/ROW]
[ROW][C]57[/C][C]726.94[/C][C]726.926141752368[/C][C]718.720416666667[/C][C]1.01141713091129[/C][C]1.00001906417562[/C][/ROW]
[ROW][C]58[/C][C]720.52[/C][C]714.331165973588[/C][C]713.695416666667[/C][C]1.00089078518942[/C][C]1.00866381633787[/C][/ROW]
[ROW][C]59[/C][C]709.36[/C][C]702.627516549859[/C][C]708.509583333333[/C][C]0.991697971457491[/C][C]1.00958186705126[/C][/ROW]
[ROW][C]60[/C][C]703.21[/C][C]693.9427476628[/C][C]702.812083333333[/C][C]0.987380217442382[/C][C]1.01335449122916[/C][/ROW]
[ROW][C]61[/C][C]703.21[/C][C]697.905099994921[/C][C]696.787916666667[/C][C]1.00160333338385[/C][C]1.00760117672892[/C][/ROW]
[ROW][C]62[/C][C]695.88[/C][C]687.782396110086[/C][C]690.729583333333[/C][C]0.99573322571617[/C][C]1.01177349687301[/C][/ROW]
[ROW][C]63[/C][C]681.63[/C][C]677.979876629446[/C][C]684.505[/C][C]0.990467383918957[/C][C]1.00538382258291[/C][/ROW]
[ROW][C]64[/C][C]672.1[/C][C]665.831130584441[/C][C]678.21875[/C][C]0.981735067903153[/C][C]1.00941510411214[/C][/ROW]
[ROW][C]65[/C][C]665.49[/C][C]662.06811271332[/C][C]672.168333333333[/C][C]0.984973673826725[/C][C]1.00516848224672[/C][/ROW]
[ROW][C]66[/C][C]658.93[/C][C]658.463049122681[/C][C]666.37[/C][C]0.988134293444604[/C][C]1.0007091527428[/C][/ROW]
[ROW][C]67[/C][C]658.93[/C][C]NA[/C][C]NA[/C][C]1.04238944087316[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]656[/C][C]NA[/C][C]NA[/C][C]1.0235774759328[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]650.66[/C][C]NA[/C][C]NA[/C][C]1.01141713091129[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]645.93[/C][C]NA[/C][C]NA[/C][C]1.00089078518942[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]638.74[/C][C]NA[/C][C]NA[/C][C]0.991697971457491[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]634.67[/C][C]NA[/C][C]NA[/C][C]0.987380217442382[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=205130&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=205130&T=1

As an alternative you can also use a QR Code:

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

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	530.3	NA	NA	1.00160333338385	NA
2	527.76	NA	NA	0.99573322571617	NA
3	521.41	NA	NA	0.990467383918957	NA
4	1601.93	NA	NA	0.981735067903153	NA
5	1577.49	NA	NA	0.984973673826725	NA
6	1551.43	NA	NA	0.988134293444604	NA
7	1551.43	1339.20505654352	1284.74541666667	1.04238944087316	1.15847083493265
8	1516.88	1381.03973189035	1349.22833333333	1.0235774759328	1.09836086896915
9	1485.95	1426.55371371764	1410.45041666667	1.01141713091129	1.04163620739353
10	1438.22	1424.24256505491	1422.975	1.00089078518942	1.00981394271456
11	1385.06	1376.55033531588	1388.07416666667	0.991697971457491	1.00618187687424
12	1329.49	1336.26484614929	1353.34375	0.987380217442382	0.994930012438169
13	1329.49	1320.77049558745	1318.65625	1.00160333338385	1.00660183161396
14	1276.16	1277.84021433764	1283.31583333333	0.99573322571617	0.998685113898606
15	1242.34	1236.39465761963	1248.29416666667	0.990467383918957	1.0048086121561
16	1181.59	1193.35501574641	1215.55708333333	0.981735067903153	0.990141227387351
17	1160.21	1167.24305216836	1185.05	0.984973673826725	0.993974646364102
18	1135.18	1143.34178208382	1157.07125	0.988134293444604	0.99286146783778
19	1135.18	1178.63364975569	1130.70375	1.04238944087316	0.963132182960588
20	1084.96	1131.92144579783	1105.84833333333	1.0235774759328	0.958511744810414
21	1077.35	1095.40352376695	1083.03833333333	1.01141713091129	0.98351883723647
22	1061.13	1063.27547375462	1062.32916666667	1.00089078518942	0.997982203288257
23	1029.98	1035.10087280079	1043.76625	0.991697971457491	0.995052778975119
24	1013.08	1013.37588152552	1026.32791666667	0.987380217442382	0.99970802391204
25	1013.08	1011.05387816905	1009.43541666667	1.00160333338385	1.00200397018863
26	996.04	989.892420569657	994.134166666667	0.99573322571617	1.00621035104684
27	975.02	970.556100638983	979.897083333333	0.990467383918957	1.00459932131494
28	951.89	947.625092025136	965.255416666667	0.981735067903153	1.00450062794955
29	944.4	936.942253433959	951.235833333333	0.984973673826725	1.00795966511139
30	932.47	926.92637325029	938.057083333333	0.988134293444604	1.00598065489309
31	932.47	964.439124155733	925.219583333333	1.04238944087316	0.966852107763962
32	920.44	934.021697129133	912.507083333333	1.0235774759328	0.985458906178648
33	900.18	910.651327853818	900.371666666667	1.01141713091129	0.988501276467146
34	886.9	890.060897431912	889.26875	1.00089078518942	0.996448672848081
35	867.74	871.400875444817	878.695833333333	0.991697971457491	0.995798861869461
36	859.03	857.455791530226	868.415	0.987380217442382	1.00183590627683
37	859.03	859.853090965589	858.476666666667	1.00160333338385	0.999042753960837
38	844.99	845.326477305211	848.94875	0.99573322571617	0.999601955795489
39	834.82	832.378059382166	840.389166666667	0.990467383918957	1.00293369171653
40	825.62	817.091552115341	832.293333333333	0.981735067903153	1.01043756707872
41	816.92	812.101765144791	824.490833333333	0.984973673826725	1.00593304319976
42	813.21	807.210198095875	816.903333333333	0.988134293444604	1.00743276276523
43	813.21	843.44246681958	809.143333333333	1.04238944087316	0.964155863607889
44	811.03	820.36237472971	801.465833333333	1.0235774759328	0.988624082457725
45	804.16	802.873032688692	793.81	1.01141713091129	1.00160295247058
46	788.62	786.755623189895	786.055416666667	1.00089078518942	1.00236970255458
47	778.76	772.071580208658	778.535	0.991697971457491	1.00866295297326
48	765.91	761.758489447287	771.494583333333	0.987380217442382	1.00544990388716
49	765.91	765.888091578905	764.662083333333	1.00160333338385	1.000028605251
50	753.85	754.59899977755	757.8325	0.99573322571617	0.999007420129406
51	742.22	744.040749578894	751.201666666667	0.990467383918957	0.997552889972862
52	732.11	731.536613397808	745.146666666667	0.981735067903153	1.00078381121559
53	729.94	728.306771466772	739.4175	0.984973673826725	1.00224250082138
54	731.22	725.204933082908	733.913333333333	0.988134293444604	1.00829429950445
55	731.22	759.57702435413	728.688333333333	1.04238944087316	0.962667348478265
56	729.11	740.722502724144	723.660416666667	1.0235774759328	0.984322735327418
57	726.94	726.926141752368	718.720416666667	1.01141713091129	1.00001906417562
58	720.52	714.331165973588	713.695416666667	1.00089078518942	1.00866381633787
59	709.36	702.627516549859	708.509583333333	0.991697971457491	1.00958186705126
60	703.21	693.9427476628	702.812083333333	0.987380217442382	1.01335449122916
61	703.21	697.905099994921	696.787916666667	1.00160333338385	1.00760117672892
62	695.88	687.782396110086	690.729583333333	0.99573322571617	1.01177349687301
63	681.63	677.979876629446	684.505	0.990467383918957	1.00538382258291
64	672.1	665.831130584441	678.21875	0.981735067903153	1.00941510411214
65	665.49	662.06811271332	672.168333333333	0.984973673826725	1.00516848224672
66	658.93	658.463049122681	666.37	0.988134293444604	1.0007091527428
67	658.93	NA	NA	1.04238944087316	NA
68	656	NA	NA	1.0235774759328	NA
69	650.66	NA	NA	1.01141713091129	NA
70	645.93	NA	NA	1.00089078518942	NA
71	638.74	NA	NA	0.991697971457491	NA
72	634.67	NA	NA	0.987380217442382	NA

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

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

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

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[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