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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 03 Dec 2012 13:34:12 -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/2012/Dec/03/t1354559677eg5rw71depjmymp.htm/, Retrieved Sun, 05 May 2024 04:01:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=195933, Retrieved Sun, 05 May 2024 04:01:14 +0000

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-       [Classical Decomposition] [Gemiddelde consum...] [2012-12-03 18:34:12] [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	5 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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195933&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195933&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195933&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	5 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	79.57	NA	NA	1.00478065840307	NA
2	77.45	NA	NA	0.999655069878869	NA
3	75.79	NA	NA	0.997184710808545	NA
4	74.88	NA	NA	0.997168202783886	NA
5	74.5	NA	NA	0.996117864481581	NA
6	74.59	NA	NA	1.00024002862165	NA
7	74.59	74.8066123342019	74.4291666666667	1.00507120641597	0.997104369153436
8	73.57	73.9476887160132	73.8679166666667	1.00107992824147	0.99489248788473
9	73.3	73.3555322252226	73.4020833333333	0.999365806718328	0.999242971545048
10	73.23	72.9693937304069	73.0191666666667	0.999318357925297	1.00357144627727
11	73	72.5824843922981	72.6533333333333	0.99902483564367	1.00575229149563
12	72.31	72.3384513202796	72.2666666666667	1.00099333007767	0.999606691603701
13	72.31	72.2169351882899	71.8733333333333	1.00478065840307	1.00128868403883
14	71.24	71.4565939637789	71.48125	0.999655069878869	0.996968873664918
15	70.82	70.8686709162748	71.06875	0.997184710808545	0.999313223803332
16	70.66	70.4495180399304	70.6495833333333	0.997168202783886	1.00298769907766
17	69.94	69.9158527115214	70.1883333333333	0.996117864481581	1.00034537644243
18	69.87	69.7329838953942	69.71625	1.00024002862165	1.00196486794271
19	69.87	69.6418026722318	69.2904166666667	1.00507120641597	1.00327672919155
20	68.88	68.9614764400972	68.8870833333333	1.00107992824147	0.998818522393905
21	68.09	68.4465641021383	68.49	0.999365806718328	0.994790620876072
22	68.38	68.0448361390808	68.09125	0.999318357925297	1.00492563256724
23	66.78	67.6818513131177	67.7479166666667	0.99902483564367	0.986675138229516
24	67.2	67.5186684359556	67.4516666666667	1.00099333007767	0.995280291461052
25	67.2	67.4827436527808	67.1616666666666	1.00478065840307	0.995810134006472
26	66.67	66.8619293488482	66.885	0.999655069878869	0.997129467385741
27	65.86	66.458621532724	66.64625	0.997184710808545	0.99099256772232
28	66.05	66.2073983105873	66.3954166666667	0.997168202783886	0.997622647700958
29	66.31	65.9317963027052	66.18875	0.996117864481581	1.0057362868677
30	66.39	66.0516838233879	66.0358333333333	1.00024002862165	1.00512199170451
31	66.39	66.1889642985236	65.855	1.00507120641597	1.00303729939888
32	65.72	65.7538495033568	65.6829166666667	1.00107992824147	0.999485208795949
33	65.52	65.5109270449032	65.5525	0.999365806718328	1.00013849529393
34	64.93	65.3903967508418	65.435	0.999318357925297	0.992959260476794
35	65.27	65.2396518503172	65.3033333333333	0.99902483564367	1.00046517951617
36	65.04	65.2347353211617	65.17	1.00099333007767	0.997014852283787
37	65.02	65.3408862159516	65.03	1.00478065840307	0.995089044019222
38	64.72	64.9005227971566	64.9229166666667	0.999655069878869	0.997218469291521
39	64.68	64.6719989258587	64.8545833333333	0.997184710808545	1.00012371774917
40	64.41	64.6090207788749	64.7925	0.997168202783886	0.996919613136437
41	64.79	64.4687481892479	64.72	0.996117864481581	1.00498306264314
42	64.71	64.6600998835681	64.6445833333333	1.00024002862165	1.00077172965278
43	64.71	64.9054046119966	64.5779166666667	1.00507120641597	0.996989393823755
44	64.83	64.5442112567317	64.4745833333333	1.00107992824147	1.0044277982131
45	64.77	64.2871203340927	64.3279166666667	0.999365806718328	1.0075112971836
46	64.19	64.1137675485922	64.1575	0.999318357925297	1.00118901843274
47	64.27	63.8718203461817	63.9341666666667	0.99902483564367	1.00623404267579
48	64.23	63.7595214009597	63.69625	1.00099333007767	1.00737895436952
49	64.23	63.7822202196038	63.47875	1.00478065840307	1.00702044831388
50	63.03	63.2223518485975	63.2441666666667	0.999655069878869	0.996957534116128
51	62.85	62.7956296950206	62.9729166666667	0.997184710808545	1.00086582944137
52	62.15	62.5191224205403	62.6966666666667	0.997168202783886	0.994095847698286
53	61.69	62.1905436233565	62.4329166666667	0.996117864481581	0.991951451230465
54	62.1	62.1795046125864	62.1645833333333	1.00024002862165	0.998721369475654
55	62.1	62.2076259821084	61.89375	1.00507120641597	0.998269890862909
56	61.81	61.7449415073865	61.6783333333333	1.00107992824147	1.00105366514285
57	61.28	61.4647447349524	61.50375	0.999365806718328	0.996994297531877
58	61.05	61.2931914833481	61.335	0.999318357925297	0.996032324676483
59	61.08	61.107435373886	61.1670833333333	0.99902483564367	0.99955103051342
60	60.98	61.0167996765469	60.95625	1.00099333007767	0.999396892712466
61	60.98	61.0123748712727	60.7220833333333	1.00478065840307	0.999469372052129
62	61.11	60.4807978194547	60.5016666666667	0.999655069878869	1.01040333797222
63	60.58	60.1360549725683	60.3058333333333	0.997184710808545	1.00738234371434
64	60.37	59.9472594308602	60.1175	0.997168202783886	1.00705187481719
65	59.44	59.6990038148219	59.9316666666667	0.996117864481581	0.995661505246799
66	59.29	59.7622578767507	59.7479166666667	1.00024002862165	0.992097723654875
67	59.29	NA	NA	1.00507120641597	NA
68	59.33	NA	NA	1.00107992824147	NA
69	59.06	NA	NA	0.999365806718328	NA
70	58.75	NA	NA	0.999318357925297	NA
71	58.92	NA	NA	0.99902483564367	NA
72	58.73	NA	NA	1.00099333007767	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 79.57 & NA & NA & 1.00478065840307 & NA \tabularnewline
2 & 77.45 & NA & NA & 0.999655069878869 & NA \tabularnewline
3 & 75.79 & NA & NA & 0.997184710808545 & NA \tabularnewline
4 & 74.88 & NA & NA & 0.997168202783886 & NA \tabularnewline
5 & 74.5 & NA & NA & 0.996117864481581 & NA \tabularnewline
6 & 74.59 & NA & NA & 1.00024002862165 & NA \tabularnewline
7 & 74.59 & 74.8066123342019 & 74.4291666666667 & 1.00507120641597 & 0.997104369153436 \tabularnewline
8 & 73.57 & 73.9476887160132 & 73.8679166666667 & 1.00107992824147 & 0.99489248788473 \tabularnewline
9 & 73.3 & 73.3555322252226 & 73.4020833333333 & 0.999365806718328 & 0.999242971545048 \tabularnewline
10 & 73.23 & 72.9693937304069 & 73.0191666666667 & 0.999318357925297 & 1.00357144627727 \tabularnewline
11 & 73 & 72.5824843922981 & 72.6533333333333 & 0.99902483564367 & 1.00575229149563 \tabularnewline
12 & 72.31 & 72.3384513202796 & 72.2666666666667 & 1.00099333007767 & 0.999606691603701 \tabularnewline
13 & 72.31 & 72.2169351882899 & 71.8733333333333 & 1.00478065840307 & 1.00128868403883 \tabularnewline
14 & 71.24 & 71.4565939637789 & 71.48125 & 0.999655069878869 & 0.996968873664918 \tabularnewline
15 & 70.82 & 70.8686709162748 & 71.06875 & 0.997184710808545 & 0.999313223803332 \tabularnewline
16 & 70.66 & 70.4495180399304 & 70.6495833333333 & 0.997168202783886 & 1.00298769907766 \tabularnewline
17 & 69.94 & 69.9158527115214 & 70.1883333333333 & 0.996117864481581 & 1.00034537644243 \tabularnewline
18 & 69.87 & 69.7329838953942 & 69.71625 & 1.00024002862165 & 1.00196486794271 \tabularnewline
19 & 69.87 & 69.6418026722318 & 69.2904166666667 & 1.00507120641597 & 1.00327672919155 \tabularnewline
20 & 68.88 & 68.9614764400972 & 68.8870833333333 & 1.00107992824147 & 0.998818522393905 \tabularnewline
21 & 68.09 & 68.4465641021383 & 68.49 & 0.999365806718328 & 0.994790620876072 \tabularnewline
22 & 68.38 & 68.0448361390808 & 68.09125 & 0.999318357925297 & 1.00492563256724 \tabularnewline
23 & 66.78 & 67.6818513131177 & 67.7479166666667 & 0.99902483564367 & 0.986675138229516 \tabularnewline
24 & 67.2 & 67.5186684359556 & 67.4516666666667 & 1.00099333007767 & 0.995280291461052 \tabularnewline
25 & 67.2 & 67.4827436527808 & 67.1616666666666 & 1.00478065840307 & 0.995810134006472 \tabularnewline
26 & 66.67 & 66.8619293488482 & 66.885 & 0.999655069878869 & 0.997129467385741 \tabularnewline
27 & 65.86 & 66.458621532724 & 66.64625 & 0.997184710808545 & 0.99099256772232 \tabularnewline
28 & 66.05 & 66.2073983105873 & 66.3954166666667 & 0.997168202783886 & 0.997622647700958 \tabularnewline
29 & 66.31 & 65.9317963027052 & 66.18875 & 0.996117864481581 & 1.0057362868677 \tabularnewline
30 & 66.39 & 66.0516838233879 & 66.0358333333333 & 1.00024002862165 & 1.00512199170451 \tabularnewline
31 & 66.39 & 66.1889642985236 & 65.855 & 1.00507120641597 & 1.00303729939888 \tabularnewline
32 & 65.72 & 65.7538495033568 & 65.6829166666667 & 1.00107992824147 & 0.999485208795949 \tabularnewline
33 & 65.52 & 65.5109270449032 & 65.5525 & 0.999365806718328 & 1.00013849529393 \tabularnewline
34 & 64.93 & 65.3903967508418 & 65.435 & 0.999318357925297 & 0.992959260476794 \tabularnewline
35 & 65.27 & 65.2396518503172 & 65.3033333333333 & 0.99902483564367 & 1.00046517951617 \tabularnewline
36 & 65.04 & 65.2347353211617 & 65.17 & 1.00099333007767 & 0.997014852283787 \tabularnewline
37 & 65.02 & 65.3408862159516 & 65.03 & 1.00478065840307 & 0.995089044019222 \tabularnewline
38 & 64.72 & 64.9005227971566 & 64.9229166666667 & 0.999655069878869 & 0.997218469291521 \tabularnewline
39 & 64.68 & 64.6719989258587 & 64.8545833333333 & 0.997184710808545 & 1.00012371774917 \tabularnewline
40 & 64.41 & 64.6090207788749 & 64.7925 & 0.997168202783886 & 0.996919613136437 \tabularnewline
41 & 64.79 & 64.4687481892479 & 64.72 & 0.996117864481581 & 1.00498306264314 \tabularnewline
42 & 64.71 & 64.6600998835681 & 64.6445833333333 & 1.00024002862165 & 1.00077172965278 \tabularnewline
43 & 64.71 & 64.9054046119966 & 64.5779166666667 & 1.00507120641597 & 0.996989393823755 \tabularnewline
44 & 64.83 & 64.5442112567317 & 64.4745833333333 & 1.00107992824147 & 1.0044277982131 \tabularnewline
45 & 64.77 & 64.2871203340927 & 64.3279166666667 & 0.999365806718328 & 1.0075112971836 \tabularnewline
46 & 64.19 & 64.1137675485922 & 64.1575 & 0.999318357925297 & 1.00118901843274 \tabularnewline
47 & 64.27 & 63.8718203461817 & 63.9341666666667 & 0.99902483564367 & 1.00623404267579 \tabularnewline
48 & 64.23 & 63.7595214009597 & 63.69625 & 1.00099333007767 & 1.00737895436952 \tabularnewline
49 & 64.23 & 63.7822202196038 & 63.47875 & 1.00478065840307 & 1.00702044831388 \tabularnewline
50 & 63.03 & 63.2223518485975 & 63.2441666666667 & 0.999655069878869 & 0.996957534116128 \tabularnewline
51 & 62.85 & 62.7956296950206 & 62.9729166666667 & 0.997184710808545 & 1.00086582944137 \tabularnewline
52 & 62.15 & 62.5191224205403 & 62.6966666666667 & 0.997168202783886 & 0.994095847698286 \tabularnewline
53 & 61.69 & 62.1905436233565 & 62.4329166666667 & 0.996117864481581 & 0.991951451230465 \tabularnewline
54 & 62.1 & 62.1795046125864 & 62.1645833333333 & 1.00024002862165 & 0.998721369475654 \tabularnewline
55 & 62.1 & 62.2076259821084 & 61.89375 & 1.00507120641597 & 0.998269890862909 \tabularnewline
56 & 61.81 & 61.7449415073865 & 61.6783333333333 & 1.00107992824147 & 1.00105366514285 \tabularnewline
57 & 61.28 & 61.4647447349524 & 61.50375 & 0.999365806718328 & 0.996994297531877 \tabularnewline
58 & 61.05 & 61.2931914833481 & 61.335 & 0.999318357925297 & 0.996032324676483 \tabularnewline
59 & 61.08 & 61.107435373886 & 61.1670833333333 & 0.99902483564367 & 0.99955103051342 \tabularnewline
60 & 60.98 & 61.0167996765469 & 60.95625 & 1.00099333007767 & 0.999396892712466 \tabularnewline
61 & 60.98 & 61.0123748712727 & 60.7220833333333 & 1.00478065840307 & 0.999469372052129 \tabularnewline
62 & 61.11 & 60.4807978194547 & 60.5016666666667 & 0.999655069878869 & 1.01040333797222 \tabularnewline
63 & 60.58 & 60.1360549725683 & 60.3058333333333 & 0.997184710808545 & 1.00738234371434 \tabularnewline
64 & 60.37 & 59.9472594308602 & 60.1175 & 0.997168202783886 & 1.00705187481719 \tabularnewline
65 & 59.44 & 59.6990038148219 & 59.9316666666667 & 0.996117864481581 & 0.995661505246799 \tabularnewline
66 & 59.29 & 59.7622578767507 & 59.7479166666667 & 1.00024002862165 & 0.992097723654875 \tabularnewline
67 & 59.29 & NA & NA & 1.00507120641597 & NA \tabularnewline
68 & 59.33 & NA & NA & 1.00107992824147 & NA \tabularnewline
69 & 59.06 & NA & NA & 0.999365806718328 & NA \tabularnewline
70 & 58.75 & NA & NA & 0.999318357925297 & NA \tabularnewline
71 & 58.92 & NA & NA & 0.99902483564367 & NA \tabularnewline
72 & 58.73 & NA & NA & 1.00099333007767 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=195933&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]79.57[/C][C]NA[/C][C]NA[/C][C]1.00478065840307[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]77.45[/C][C]NA[/C][C]NA[/C][C]0.999655069878869[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]75.79[/C][C]NA[/C][C]NA[/C][C]0.997184710808545[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]74.88[/C][C]NA[/C][C]NA[/C][C]0.997168202783886[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]74.5[/C][C]NA[/C][C]NA[/C][C]0.996117864481581[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]74.59[/C][C]NA[/C][C]NA[/C][C]1.00024002862165[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]74.59[/C][C]74.8066123342019[/C][C]74.4291666666667[/C][C]1.00507120641597[/C][C]0.997104369153436[/C][/ROW]
[ROW][C]8[/C][C]73.57[/C][C]73.9476887160132[/C][C]73.8679166666667[/C][C]1.00107992824147[/C][C]0.99489248788473[/C][/ROW]
[ROW][C]9[/C][C]73.3[/C][C]73.3555322252226[/C][C]73.4020833333333[/C][C]0.999365806718328[/C][C]0.999242971545048[/C][/ROW]
[ROW][C]10[/C][C]73.23[/C][C]72.9693937304069[/C][C]73.0191666666667[/C][C]0.999318357925297[/C][C]1.00357144627727[/C][/ROW]
[ROW][C]11[/C][C]73[/C][C]72.5824843922981[/C][C]72.6533333333333[/C][C]0.99902483564367[/C][C]1.00575229149563[/C][/ROW]
[ROW][C]12[/C][C]72.31[/C][C]72.3384513202796[/C][C]72.2666666666667[/C][C]1.00099333007767[/C][C]0.999606691603701[/C][/ROW]
[ROW][C]13[/C][C]72.31[/C][C]72.2169351882899[/C][C]71.8733333333333[/C][C]1.00478065840307[/C][C]1.00128868403883[/C][/ROW]
[ROW][C]14[/C][C]71.24[/C][C]71.4565939637789[/C][C]71.48125[/C][C]0.999655069878869[/C][C]0.996968873664918[/C][/ROW]
[ROW][C]15[/C][C]70.82[/C][C]70.8686709162748[/C][C]71.06875[/C][C]0.997184710808545[/C][C]0.999313223803332[/C][/ROW]
[ROW][C]16[/C][C]70.66[/C][C]70.4495180399304[/C][C]70.6495833333333[/C][C]0.997168202783886[/C][C]1.00298769907766[/C][/ROW]
[ROW][C]17[/C][C]69.94[/C][C]69.9158527115214[/C][C]70.1883333333333[/C][C]0.996117864481581[/C][C]1.00034537644243[/C][/ROW]
[ROW][C]18[/C][C]69.87[/C][C]69.7329838953942[/C][C]69.71625[/C][C]1.00024002862165[/C][C]1.00196486794271[/C][/ROW]
[ROW][C]19[/C][C]69.87[/C][C]69.6418026722318[/C][C]69.2904166666667[/C][C]1.00507120641597[/C][C]1.00327672919155[/C][/ROW]
[ROW][C]20[/C][C]68.88[/C][C]68.9614764400972[/C][C]68.8870833333333[/C][C]1.00107992824147[/C][C]0.998818522393905[/C][/ROW]
[ROW][C]21[/C][C]68.09[/C][C]68.4465641021383[/C][C]68.49[/C][C]0.999365806718328[/C][C]0.994790620876072[/C][/ROW]
[ROW][C]22[/C][C]68.38[/C][C]68.0448361390808[/C][C]68.09125[/C][C]0.999318357925297[/C][C]1.00492563256724[/C][/ROW]
[ROW][C]23[/C][C]66.78[/C][C]67.6818513131177[/C][C]67.7479166666667[/C][C]0.99902483564367[/C][C]0.986675138229516[/C][/ROW]
[ROW][C]24[/C][C]67.2[/C][C]67.5186684359556[/C][C]67.4516666666667[/C][C]1.00099333007767[/C][C]0.995280291461052[/C][/ROW]
[ROW][C]25[/C][C]67.2[/C][C]67.4827436527808[/C][C]67.1616666666666[/C][C]1.00478065840307[/C][C]0.995810134006472[/C][/ROW]
[ROW][C]26[/C][C]66.67[/C][C]66.8619293488482[/C][C]66.885[/C][C]0.999655069878869[/C][C]0.997129467385741[/C][/ROW]
[ROW][C]27[/C][C]65.86[/C][C]66.458621532724[/C][C]66.64625[/C][C]0.997184710808545[/C][C]0.99099256772232[/C][/ROW]
[ROW][C]28[/C][C]66.05[/C][C]66.2073983105873[/C][C]66.3954166666667[/C][C]0.997168202783886[/C][C]0.997622647700958[/C][/ROW]
[ROW][C]29[/C][C]66.31[/C][C]65.9317963027052[/C][C]66.18875[/C][C]0.996117864481581[/C][C]1.0057362868677[/C][/ROW]
[ROW][C]30[/C][C]66.39[/C][C]66.0516838233879[/C][C]66.0358333333333[/C][C]1.00024002862165[/C][C]1.00512199170451[/C][/ROW]
[ROW][C]31[/C][C]66.39[/C][C]66.1889642985236[/C][C]65.855[/C][C]1.00507120641597[/C][C]1.00303729939888[/C][/ROW]
[ROW][C]32[/C][C]65.72[/C][C]65.7538495033568[/C][C]65.6829166666667[/C][C]1.00107992824147[/C][C]0.999485208795949[/C][/ROW]
[ROW][C]33[/C][C]65.52[/C][C]65.5109270449032[/C][C]65.5525[/C][C]0.999365806718328[/C][C]1.00013849529393[/C][/ROW]
[ROW][C]34[/C][C]64.93[/C][C]65.3903967508418[/C][C]65.435[/C][C]0.999318357925297[/C][C]0.992959260476794[/C][/ROW]
[ROW][C]35[/C][C]65.27[/C][C]65.2396518503172[/C][C]65.3033333333333[/C][C]0.99902483564367[/C][C]1.00046517951617[/C][/ROW]
[ROW][C]36[/C][C]65.04[/C][C]65.2347353211617[/C][C]65.17[/C][C]1.00099333007767[/C][C]0.997014852283787[/C][/ROW]
[ROW][C]37[/C][C]65.02[/C][C]65.3408862159516[/C][C]65.03[/C][C]1.00478065840307[/C][C]0.995089044019222[/C][/ROW]
[ROW][C]38[/C][C]64.72[/C][C]64.9005227971566[/C][C]64.9229166666667[/C][C]0.999655069878869[/C][C]0.997218469291521[/C][/ROW]
[ROW][C]39[/C][C]64.68[/C][C]64.6719989258587[/C][C]64.8545833333333[/C][C]0.997184710808545[/C][C]1.00012371774917[/C][/ROW]
[ROW][C]40[/C][C]64.41[/C][C]64.6090207788749[/C][C]64.7925[/C][C]0.997168202783886[/C][C]0.996919613136437[/C][/ROW]
[ROW][C]41[/C][C]64.79[/C][C]64.4687481892479[/C][C]64.72[/C][C]0.996117864481581[/C][C]1.00498306264314[/C][/ROW]
[ROW][C]42[/C][C]64.71[/C][C]64.6600998835681[/C][C]64.6445833333333[/C][C]1.00024002862165[/C][C]1.00077172965278[/C][/ROW]
[ROW][C]43[/C][C]64.71[/C][C]64.9054046119966[/C][C]64.5779166666667[/C][C]1.00507120641597[/C][C]0.996989393823755[/C][/ROW]
[ROW][C]44[/C][C]64.83[/C][C]64.5442112567317[/C][C]64.4745833333333[/C][C]1.00107992824147[/C][C]1.0044277982131[/C][/ROW]
[ROW][C]45[/C][C]64.77[/C][C]64.2871203340927[/C][C]64.3279166666667[/C][C]0.999365806718328[/C][C]1.0075112971836[/C][/ROW]
[ROW][C]46[/C][C]64.19[/C][C]64.1137675485922[/C][C]64.1575[/C][C]0.999318357925297[/C][C]1.00118901843274[/C][/ROW]
[ROW][C]47[/C][C]64.27[/C][C]63.8718203461817[/C][C]63.9341666666667[/C][C]0.99902483564367[/C][C]1.00623404267579[/C][/ROW]
[ROW][C]48[/C][C]64.23[/C][C]63.7595214009597[/C][C]63.69625[/C][C]1.00099333007767[/C][C]1.00737895436952[/C][/ROW]
[ROW][C]49[/C][C]64.23[/C][C]63.7822202196038[/C][C]63.47875[/C][C]1.00478065840307[/C][C]1.00702044831388[/C][/ROW]
[ROW][C]50[/C][C]63.03[/C][C]63.2223518485975[/C][C]63.2441666666667[/C][C]0.999655069878869[/C][C]0.996957534116128[/C][/ROW]
[ROW][C]51[/C][C]62.85[/C][C]62.7956296950206[/C][C]62.9729166666667[/C][C]0.997184710808545[/C][C]1.00086582944137[/C][/ROW]
[ROW][C]52[/C][C]62.15[/C][C]62.5191224205403[/C][C]62.6966666666667[/C][C]0.997168202783886[/C][C]0.994095847698286[/C][/ROW]
[ROW][C]53[/C][C]61.69[/C][C]62.1905436233565[/C][C]62.4329166666667[/C][C]0.996117864481581[/C][C]0.991951451230465[/C][/ROW]
[ROW][C]54[/C][C]62.1[/C][C]62.1795046125864[/C][C]62.1645833333333[/C][C]1.00024002862165[/C][C]0.998721369475654[/C][/ROW]
[ROW][C]55[/C][C]62.1[/C][C]62.2076259821084[/C][C]61.89375[/C][C]1.00507120641597[/C][C]0.998269890862909[/C][/ROW]
[ROW][C]56[/C][C]61.81[/C][C]61.7449415073865[/C][C]61.6783333333333[/C][C]1.00107992824147[/C][C]1.00105366514285[/C][/ROW]
[ROW][C]57[/C][C]61.28[/C][C]61.4647447349524[/C][C]61.50375[/C][C]0.999365806718328[/C][C]0.996994297531877[/C][/ROW]
[ROW][C]58[/C][C]61.05[/C][C]61.2931914833481[/C][C]61.335[/C][C]0.999318357925297[/C][C]0.996032324676483[/C][/ROW]
[ROW][C]59[/C][C]61.08[/C][C]61.107435373886[/C][C]61.1670833333333[/C][C]0.99902483564367[/C][C]0.99955103051342[/C][/ROW]
[ROW][C]60[/C][C]60.98[/C][C]61.0167996765469[/C][C]60.95625[/C][C]1.00099333007767[/C][C]0.999396892712466[/C][/ROW]
[ROW][C]61[/C][C]60.98[/C][C]61.0123748712727[/C][C]60.7220833333333[/C][C]1.00478065840307[/C][C]0.999469372052129[/C][/ROW]
[ROW][C]62[/C][C]61.11[/C][C]60.4807978194547[/C][C]60.5016666666667[/C][C]0.999655069878869[/C][C]1.01040333797222[/C][/ROW]
[ROW][C]63[/C][C]60.58[/C][C]60.1360549725683[/C][C]60.3058333333333[/C][C]0.997184710808545[/C][C]1.00738234371434[/C][/ROW]
[ROW][C]64[/C][C]60.37[/C][C]59.9472594308602[/C][C]60.1175[/C][C]0.997168202783886[/C][C]1.00705187481719[/C][/ROW]
[ROW][C]65[/C][C]59.44[/C][C]59.6990038148219[/C][C]59.9316666666667[/C][C]0.996117864481581[/C][C]0.995661505246799[/C][/ROW]
[ROW][C]66[/C][C]59.29[/C][C]59.7622578767507[/C][C]59.7479166666667[/C][C]1.00024002862165[/C][C]0.992097723654875[/C][/ROW]
[ROW][C]67[/C][C]59.29[/C][C]NA[/C][C]NA[/C][C]1.00507120641597[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]59.33[/C][C]NA[/C][C]NA[/C][C]1.00107992824147[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]59.06[/C][C]NA[/C][C]NA[/C][C]0.999365806718328[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]58.75[/C][C]NA[/C][C]NA[/C][C]0.999318357925297[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]58.92[/C][C]NA[/C][C]NA[/C][C]0.99902483564367[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]58.73[/C][C]NA[/C][C]NA[/C][C]1.00099333007767[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=195933&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=195933&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	79.57	NA	NA	1.00478065840307	NA
2	77.45	NA	NA	0.999655069878869	NA
3	75.79	NA	NA	0.997184710808545	NA
4	74.88	NA	NA	0.997168202783886	NA
5	74.5	NA	NA	0.996117864481581	NA
6	74.59	NA	NA	1.00024002862165	NA
7	74.59	74.8066123342019	74.4291666666667	1.00507120641597	0.997104369153436
8	73.57	73.9476887160132	73.8679166666667	1.00107992824147	0.99489248788473
9	73.3	73.3555322252226	73.4020833333333	0.999365806718328	0.999242971545048
10	73.23	72.9693937304069	73.0191666666667	0.999318357925297	1.00357144627727
11	73	72.5824843922981	72.6533333333333	0.99902483564367	1.00575229149563
12	72.31	72.3384513202796	72.2666666666667	1.00099333007767	0.999606691603701
13	72.31	72.2169351882899	71.8733333333333	1.00478065840307	1.00128868403883
14	71.24	71.4565939637789	71.48125	0.999655069878869	0.996968873664918
15	70.82	70.8686709162748	71.06875	0.997184710808545	0.999313223803332
16	70.66	70.4495180399304	70.6495833333333	0.997168202783886	1.00298769907766
17	69.94	69.9158527115214	70.1883333333333	0.996117864481581	1.00034537644243
18	69.87	69.7329838953942	69.71625	1.00024002862165	1.00196486794271
19	69.87	69.6418026722318	69.2904166666667	1.00507120641597	1.00327672919155
20	68.88	68.9614764400972	68.8870833333333	1.00107992824147	0.998818522393905
21	68.09	68.4465641021383	68.49	0.999365806718328	0.994790620876072
22	68.38	68.0448361390808	68.09125	0.999318357925297	1.00492563256724
23	66.78	67.6818513131177	67.7479166666667	0.99902483564367	0.986675138229516
24	67.2	67.5186684359556	67.4516666666667	1.00099333007767	0.995280291461052
25	67.2	67.4827436527808	67.1616666666666	1.00478065840307	0.995810134006472
26	66.67	66.8619293488482	66.885	0.999655069878869	0.997129467385741
27	65.86	66.458621532724	66.64625	0.997184710808545	0.99099256772232
28	66.05	66.2073983105873	66.3954166666667	0.997168202783886	0.997622647700958
29	66.31	65.9317963027052	66.18875	0.996117864481581	1.0057362868677
30	66.39	66.0516838233879	66.0358333333333	1.00024002862165	1.00512199170451
31	66.39	66.1889642985236	65.855	1.00507120641597	1.00303729939888
32	65.72	65.7538495033568	65.6829166666667	1.00107992824147	0.999485208795949
33	65.52	65.5109270449032	65.5525	0.999365806718328	1.00013849529393
34	64.93	65.3903967508418	65.435	0.999318357925297	0.992959260476794
35	65.27	65.2396518503172	65.3033333333333	0.99902483564367	1.00046517951617
36	65.04	65.2347353211617	65.17	1.00099333007767	0.997014852283787
37	65.02	65.3408862159516	65.03	1.00478065840307	0.995089044019222
38	64.72	64.9005227971566	64.9229166666667	0.999655069878869	0.997218469291521
39	64.68	64.6719989258587	64.8545833333333	0.997184710808545	1.00012371774917
40	64.41	64.6090207788749	64.7925	0.997168202783886	0.996919613136437
41	64.79	64.4687481892479	64.72	0.996117864481581	1.00498306264314
42	64.71	64.6600998835681	64.6445833333333	1.00024002862165	1.00077172965278
43	64.71	64.9054046119966	64.5779166666667	1.00507120641597	0.996989393823755
44	64.83	64.5442112567317	64.4745833333333	1.00107992824147	1.0044277982131
45	64.77	64.2871203340927	64.3279166666667	0.999365806718328	1.0075112971836
46	64.19	64.1137675485922	64.1575	0.999318357925297	1.00118901843274
47	64.27	63.8718203461817	63.9341666666667	0.99902483564367	1.00623404267579
48	64.23	63.7595214009597	63.69625	1.00099333007767	1.00737895436952
49	64.23	63.7822202196038	63.47875	1.00478065840307	1.00702044831388
50	63.03	63.2223518485975	63.2441666666667	0.999655069878869	0.996957534116128
51	62.85	62.7956296950206	62.9729166666667	0.997184710808545	1.00086582944137
52	62.15	62.5191224205403	62.6966666666667	0.997168202783886	0.994095847698286
53	61.69	62.1905436233565	62.4329166666667	0.996117864481581	0.991951451230465
54	62.1	62.1795046125864	62.1645833333333	1.00024002862165	0.998721369475654
55	62.1	62.2076259821084	61.89375	1.00507120641597	0.998269890862909
56	61.81	61.7449415073865	61.6783333333333	1.00107992824147	1.00105366514285
57	61.28	61.4647447349524	61.50375	0.999365806718328	0.996994297531877
58	61.05	61.2931914833481	61.335	0.999318357925297	0.996032324676483
59	61.08	61.107435373886	61.1670833333333	0.99902483564367	0.99955103051342
60	60.98	61.0167996765469	60.95625	1.00099333007767	0.999396892712466
61	60.98	61.0123748712727	60.7220833333333	1.00478065840307	0.999469372052129
62	61.11	60.4807978194547	60.5016666666667	0.999655069878869	1.01040333797222
63	60.58	60.1360549725683	60.3058333333333	0.997184710808545	1.00738234371434
64	60.37	59.9472594308602	60.1175	0.997168202783886	1.00705187481719
65	59.44	59.6990038148219	59.9316666666667	0.996117864481581	0.995661505246799
66	59.29	59.7622578767507	59.7479166666667	1.00024002862165	0.992097723654875
67	59.29	NA	NA	1.00507120641597	NA
68	59.33	NA	NA	1.00107992824147	NA
69	59.06	NA	NA	0.999365806718328	NA
70	58.75	NA	NA	0.999318357925297	NA
71	58.92	NA	NA	0.99902483564367	NA
72	58.73	NA	NA	1.00099333007767	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