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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 30 Nov 2014 21:19:46 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Nov/30/t14173824583h9x09jbq2hiyba.htm/, Retrieved Sun, 19 May 2024 16:31:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=261672, Retrieved Sun, 19 May 2024 16:31:43 +0000

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-       [Classical Decomposition] [] [2014-11-30 21:19:46] [a4941b106213b8203102126a01fbfecf] [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	2 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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261672&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261672&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261672&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	2 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	44.91	NA	NA	0.996645	NA
2	44.86	NA	NA	0.998066	NA
3	44.76	NA	NA	1.00143	NA
4	44.89	NA	NA	1.0039	NA
5	44.89	NA	NA	1.0017	NA
6	45	NA	NA	0.999905	NA
7	45.01	44.8965	44.8246	1.0016	1.00253
8	45.11	44.9043	44.795	1.00244	1.00458
9	45.05	44.8567	44.7846	1.00161	1.00431
10	44.67	44.7558	44.7817	0.999422	0.998084
11	44.48	44.6133	44.7575	0.996778	0.997012
12	44.48	44.5563	44.7129	0.996496	0.998288
13	44.48	44.5147	44.6646	0.996645	0.99922
14	44.58	44.5262	44.6125	0.998066	1.00121
15	44.79	44.6193	44.5554	1.00143	1.00383
16	44.79	44.6884	44.515	1.0039	1.00227
17	44.41	44.5754	44.4996	1.0017	0.996289
18	44.41	44.4887	44.4929	0.999905	0.998231
19	44.44	44.5547	44.4833	1.0016	0.997426
20	44.43	44.5789	44.4704	1.00244	0.99666
21	44.36	44.537	44.4654	1.00161	0.996025
22	44.39	44.4484	44.4742	0.999422	0.998685
23	44.39	44.3591	44.5025	0.996778	1.0007
24	44.41	44.3831	44.5392	0.996496	1.00061
25	44.32	44.4188	44.5683	0.996645	0.997776
26	44.43	44.5108	44.5971	0.998066	0.998184
27	44.82	44.6885	44.6246	1.00143	1.00294
28	44.97	44.8147	44.6408	1.0039	1.00346
29	44.91	44.7282	44.6521	1.0017	1.00406
30	44.79	44.6545	44.6588	0.999905	1.00303
31	44.76	44.7354	44.6638	1.0016	1.00055
32	44.8	44.7794	44.6704	1.00244	1.00046
33	44.65	44.7257	44.6538	1.00161	0.998308
34	44.49	44.5904	44.6162	0.999422	0.997747
35	44.56	44.4335	44.5771	0.996778	1.00285
36	44.4	44.3856	44.5417	0.996496	1.00032
37	44.45	44.3615	44.5108	0.996645	1.002
38	44.46	44.394	44.48	0.998066	1.00149
39	44.39	44.5212	44.4575	1.00143	0.997053
40	44.5	44.6227	44.4496	1.0039	0.997249
41	44.44	44.5212	44.4454	1.0017	0.998177
42	44.41	44.4425	44.4467	0.999905	0.99927
43	44.4	44.5242	44.4529	1.0016	0.99721
44	44.42	44.5651	44.4567	1.00244	0.996744
45	44.49	44.5366	44.465	1.00161	0.998953
46	44.46	44.4472	44.4729	0.999422	1.00029
47	44.49	44.333	44.4762	0.996778	1.00354
48	44.5	44.3258	44.4817	0.996496	1.00393
49	44.5	44.3449	44.4942	0.996645	1.0035
50	44.5	44.4243	44.5104	0.998066	1.0017
51	44.55	44.5842	44.5204	1.00143	0.999233
52	44.53	44.7014	44.5279	1.0039	0.996166
53	44.49	44.5896	44.5138	1.0017	0.997766
54	44.49	44.4725	44.4767	0.999905	1.00039
55	44.62	44.5117	44.4404	1.0016	1.00243
56	44.59	44.5142	44.4058	1.00244	1.0017
57	44.56	44.4465	44.375	1.00161	1.00255
58	44.57	44.3331	44.3588	0.999422	1.00534
59	44.04	44.2146	44.3575	0.996778	0.996051
60	44.06	44.1925	44.3479	0.996496	0.997001
61	44.07	44.1734	44.3221	0.996645	0.99766
62	44.1	44.2077	44.2933	0.998066	0.997565
63	44.21	44.3389	44.2754	1.00143	0.997094
64	44.48	44.4358	44.2633	1.0039	1.001
65	44.51	44.3392	44.2638	1.0017	1.00385
66	44.24	44.2746	44.2787	0.999905	0.999219
67	44.25	NA	NA	1.0016	NA
68	44.27	NA	NA	1.00244	NA
69	44.45	NA	NA	1.00161	NA
70	44.39	NA	NA	0.999422	NA
71	44.23	NA	NA	0.996778	NA
72	44.23	NA	NA	0.996496	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 44.91 & NA & NA & 0.996645 & NA \tabularnewline
2 & 44.86 & NA & NA & 0.998066 & NA \tabularnewline
3 & 44.76 & NA & NA & 1.00143 & NA \tabularnewline
4 & 44.89 & NA & NA & 1.0039 & NA \tabularnewline
5 & 44.89 & NA & NA & 1.0017 & NA \tabularnewline
6 & 45 & NA & NA & 0.999905 & NA \tabularnewline
7 & 45.01 & 44.8965 & 44.8246 & 1.0016 & 1.00253 \tabularnewline
8 & 45.11 & 44.9043 & 44.795 & 1.00244 & 1.00458 \tabularnewline
9 & 45.05 & 44.8567 & 44.7846 & 1.00161 & 1.00431 \tabularnewline
10 & 44.67 & 44.7558 & 44.7817 & 0.999422 & 0.998084 \tabularnewline
11 & 44.48 & 44.6133 & 44.7575 & 0.996778 & 0.997012 \tabularnewline
12 & 44.48 & 44.5563 & 44.7129 & 0.996496 & 0.998288 \tabularnewline
13 & 44.48 & 44.5147 & 44.6646 & 0.996645 & 0.99922 \tabularnewline
14 & 44.58 & 44.5262 & 44.6125 & 0.998066 & 1.00121 \tabularnewline
15 & 44.79 & 44.6193 & 44.5554 & 1.00143 & 1.00383 \tabularnewline
16 & 44.79 & 44.6884 & 44.515 & 1.0039 & 1.00227 \tabularnewline
17 & 44.41 & 44.5754 & 44.4996 & 1.0017 & 0.996289 \tabularnewline
18 & 44.41 & 44.4887 & 44.4929 & 0.999905 & 0.998231 \tabularnewline
19 & 44.44 & 44.5547 & 44.4833 & 1.0016 & 0.997426 \tabularnewline
20 & 44.43 & 44.5789 & 44.4704 & 1.00244 & 0.99666 \tabularnewline
21 & 44.36 & 44.537 & 44.4654 & 1.00161 & 0.996025 \tabularnewline
22 & 44.39 & 44.4484 & 44.4742 & 0.999422 & 0.998685 \tabularnewline
23 & 44.39 & 44.3591 & 44.5025 & 0.996778 & 1.0007 \tabularnewline
24 & 44.41 & 44.3831 & 44.5392 & 0.996496 & 1.00061 \tabularnewline
25 & 44.32 & 44.4188 & 44.5683 & 0.996645 & 0.997776 \tabularnewline
26 & 44.43 & 44.5108 & 44.5971 & 0.998066 & 0.998184 \tabularnewline
27 & 44.82 & 44.6885 & 44.6246 & 1.00143 & 1.00294 \tabularnewline
28 & 44.97 & 44.8147 & 44.6408 & 1.0039 & 1.00346 \tabularnewline
29 & 44.91 & 44.7282 & 44.6521 & 1.0017 & 1.00406 \tabularnewline
30 & 44.79 & 44.6545 & 44.6588 & 0.999905 & 1.00303 \tabularnewline
31 & 44.76 & 44.7354 & 44.6638 & 1.0016 & 1.00055 \tabularnewline
32 & 44.8 & 44.7794 & 44.6704 & 1.00244 & 1.00046 \tabularnewline
33 & 44.65 & 44.7257 & 44.6538 & 1.00161 & 0.998308 \tabularnewline
34 & 44.49 & 44.5904 & 44.6162 & 0.999422 & 0.997747 \tabularnewline
35 & 44.56 & 44.4335 & 44.5771 & 0.996778 & 1.00285 \tabularnewline
36 & 44.4 & 44.3856 & 44.5417 & 0.996496 & 1.00032 \tabularnewline
37 & 44.45 & 44.3615 & 44.5108 & 0.996645 & 1.002 \tabularnewline
38 & 44.46 & 44.394 & 44.48 & 0.998066 & 1.00149 \tabularnewline
39 & 44.39 & 44.5212 & 44.4575 & 1.00143 & 0.997053 \tabularnewline
40 & 44.5 & 44.6227 & 44.4496 & 1.0039 & 0.997249 \tabularnewline
41 & 44.44 & 44.5212 & 44.4454 & 1.0017 & 0.998177 \tabularnewline
42 & 44.41 & 44.4425 & 44.4467 & 0.999905 & 0.99927 \tabularnewline
43 & 44.4 & 44.5242 & 44.4529 & 1.0016 & 0.99721 \tabularnewline
44 & 44.42 & 44.5651 & 44.4567 & 1.00244 & 0.996744 \tabularnewline
45 & 44.49 & 44.5366 & 44.465 & 1.00161 & 0.998953 \tabularnewline
46 & 44.46 & 44.4472 & 44.4729 & 0.999422 & 1.00029 \tabularnewline
47 & 44.49 & 44.333 & 44.4762 & 0.996778 & 1.00354 \tabularnewline
48 & 44.5 & 44.3258 & 44.4817 & 0.996496 & 1.00393 \tabularnewline
49 & 44.5 & 44.3449 & 44.4942 & 0.996645 & 1.0035 \tabularnewline
50 & 44.5 & 44.4243 & 44.5104 & 0.998066 & 1.0017 \tabularnewline
51 & 44.55 & 44.5842 & 44.5204 & 1.00143 & 0.999233 \tabularnewline
52 & 44.53 & 44.7014 & 44.5279 & 1.0039 & 0.996166 \tabularnewline
53 & 44.49 & 44.5896 & 44.5138 & 1.0017 & 0.997766 \tabularnewline
54 & 44.49 & 44.4725 & 44.4767 & 0.999905 & 1.00039 \tabularnewline
55 & 44.62 & 44.5117 & 44.4404 & 1.0016 & 1.00243 \tabularnewline
56 & 44.59 & 44.5142 & 44.4058 & 1.00244 & 1.0017 \tabularnewline
57 & 44.56 & 44.4465 & 44.375 & 1.00161 & 1.00255 \tabularnewline
58 & 44.57 & 44.3331 & 44.3588 & 0.999422 & 1.00534 \tabularnewline
59 & 44.04 & 44.2146 & 44.3575 & 0.996778 & 0.996051 \tabularnewline
60 & 44.06 & 44.1925 & 44.3479 & 0.996496 & 0.997001 \tabularnewline
61 & 44.07 & 44.1734 & 44.3221 & 0.996645 & 0.99766 \tabularnewline
62 & 44.1 & 44.2077 & 44.2933 & 0.998066 & 0.997565 \tabularnewline
63 & 44.21 & 44.3389 & 44.2754 & 1.00143 & 0.997094 \tabularnewline
64 & 44.48 & 44.4358 & 44.2633 & 1.0039 & 1.001 \tabularnewline
65 & 44.51 & 44.3392 & 44.2638 & 1.0017 & 1.00385 \tabularnewline
66 & 44.24 & 44.2746 & 44.2787 & 0.999905 & 0.999219 \tabularnewline
67 & 44.25 & NA & NA & 1.0016 & NA \tabularnewline
68 & 44.27 & NA & NA & 1.00244 & NA \tabularnewline
69 & 44.45 & NA & NA & 1.00161 & NA \tabularnewline
70 & 44.39 & NA & NA & 0.999422 & NA \tabularnewline
71 & 44.23 & NA & NA & 0.996778 & NA \tabularnewline
72 & 44.23 & NA & NA & 0.996496 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=261672&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]44.91[/C][C]NA[/C][C]NA[/C][C]0.996645[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]44.86[/C][C]NA[/C][C]NA[/C][C]0.998066[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]44.76[/C][C]NA[/C][C]NA[/C][C]1.00143[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]44.89[/C][C]NA[/C][C]NA[/C][C]1.0039[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]44.89[/C][C]NA[/C][C]NA[/C][C]1.0017[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]45[/C][C]NA[/C][C]NA[/C][C]0.999905[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]45.01[/C][C]44.8965[/C][C]44.8246[/C][C]1.0016[/C][C]1.00253[/C][/ROW]
[ROW][C]8[/C][C]45.11[/C][C]44.9043[/C][C]44.795[/C][C]1.00244[/C][C]1.00458[/C][/ROW]
[ROW][C]9[/C][C]45.05[/C][C]44.8567[/C][C]44.7846[/C][C]1.00161[/C][C]1.00431[/C][/ROW]
[ROW][C]10[/C][C]44.67[/C][C]44.7558[/C][C]44.7817[/C][C]0.999422[/C][C]0.998084[/C][/ROW]
[ROW][C]11[/C][C]44.48[/C][C]44.6133[/C][C]44.7575[/C][C]0.996778[/C][C]0.997012[/C][/ROW]
[ROW][C]12[/C][C]44.48[/C][C]44.5563[/C][C]44.7129[/C][C]0.996496[/C][C]0.998288[/C][/ROW]
[ROW][C]13[/C][C]44.48[/C][C]44.5147[/C][C]44.6646[/C][C]0.996645[/C][C]0.99922[/C][/ROW]
[ROW][C]14[/C][C]44.58[/C][C]44.5262[/C][C]44.6125[/C][C]0.998066[/C][C]1.00121[/C][/ROW]
[ROW][C]15[/C][C]44.79[/C][C]44.6193[/C][C]44.5554[/C][C]1.00143[/C][C]1.00383[/C][/ROW]
[ROW][C]16[/C][C]44.79[/C][C]44.6884[/C][C]44.515[/C][C]1.0039[/C][C]1.00227[/C][/ROW]
[ROW][C]17[/C][C]44.41[/C][C]44.5754[/C][C]44.4996[/C][C]1.0017[/C][C]0.996289[/C][/ROW]
[ROW][C]18[/C][C]44.41[/C][C]44.4887[/C][C]44.4929[/C][C]0.999905[/C][C]0.998231[/C][/ROW]
[ROW][C]19[/C][C]44.44[/C][C]44.5547[/C][C]44.4833[/C][C]1.0016[/C][C]0.997426[/C][/ROW]
[ROW][C]20[/C][C]44.43[/C][C]44.5789[/C][C]44.4704[/C][C]1.00244[/C][C]0.99666[/C][/ROW]
[ROW][C]21[/C][C]44.36[/C][C]44.537[/C][C]44.4654[/C][C]1.00161[/C][C]0.996025[/C][/ROW]
[ROW][C]22[/C][C]44.39[/C][C]44.4484[/C][C]44.4742[/C][C]0.999422[/C][C]0.998685[/C][/ROW]
[ROW][C]23[/C][C]44.39[/C][C]44.3591[/C][C]44.5025[/C][C]0.996778[/C][C]1.0007[/C][/ROW]
[ROW][C]24[/C][C]44.41[/C][C]44.3831[/C][C]44.5392[/C][C]0.996496[/C][C]1.00061[/C][/ROW]
[ROW][C]25[/C][C]44.32[/C][C]44.4188[/C][C]44.5683[/C][C]0.996645[/C][C]0.997776[/C][/ROW]
[ROW][C]26[/C][C]44.43[/C][C]44.5108[/C][C]44.5971[/C][C]0.998066[/C][C]0.998184[/C][/ROW]
[ROW][C]27[/C][C]44.82[/C][C]44.6885[/C][C]44.6246[/C][C]1.00143[/C][C]1.00294[/C][/ROW]
[ROW][C]28[/C][C]44.97[/C][C]44.8147[/C][C]44.6408[/C][C]1.0039[/C][C]1.00346[/C][/ROW]
[ROW][C]29[/C][C]44.91[/C][C]44.7282[/C][C]44.6521[/C][C]1.0017[/C][C]1.00406[/C][/ROW]
[ROW][C]30[/C][C]44.79[/C][C]44.6545[/C][C]44.6588[/C][C]0.999905[/C][C]1.00303[/C][/ROW]
[ROW][C]31[/C][C]44.76[/C][C]44.7354[/C][C]44.6638[/C][C]1.0016[/C][C]1.00055[/C][/ROW]
[ROW][C]32[/C][C]44.8[/C][C]44.7794[/C][C]44.6704[/C][C]1.00244[/C][C]1.00046[/C][/ROW]
[ROW][C]33[/C][C]44.65[/C][C]44.7257[/C][C]44.6538[/C][C]1.00161[/C][C]0.998308[/C][/ROW]
[ROW][C]34[/C][C]44.49[/C][C]44.5904[/C][C]44.6162[/C][C]0.999422[/C][C]0.997747[/C][/ROW]
[ROW][C]35[/C][C]44.56[/C][C]44.4335[/C][C]44.5771[/C][C]0.996778[/C][C]1.00285[/C][/ROW]
[ROW][C]36[/C][C]44.4[/C][C]44.3856[/C][C]44.5417[/C][C]0.996496[/C][C]1.00032[/C][/ROW]
[ROW][C]37[/C][C]44.45[/C][C]44.3615[/C][C]44.5108[/C][C]0.996645[/C][C]1.002[/C][/ROW]
[ROW][C]38[/C][C]44.46[/C][C]44.394[/C][C]44.48[/C][C]0.998066[/C][C]1.00149[/C][/ROW]
[ROW][C]39[/C][C]44.39[/C][C]44.5212[/C][C]44.4575[/C][C]1.00143[/C][C]0.997053[/C][/ROW]
[ROW][C]40[/C][C]44.5[/C][C]44.6227[/C][C]44.4496[/C][C]1.0039[/C][C]0.997249[/C][/ROW]
[ROW][C]41[/C][C]44.44[/C][C]44.5212[/C][C]44.4454[/C][C]1.0017[/C][C]0.998177[/C][/ROW]
[ROW][C]42[/C][C]44.41[/C][C]44.4425[/C][C]44.4467[/C][C]0.999905[/C][C]0.99927[/C][/ROW]
[ROW][C]43[/C][C]44.4[/C][C]44.5242[/C][C]44.4529[/C][C]1.0016[/C][C]0.99721[/C][/ROW]
[ROW][C]44[/C][C]44.42[/C][C]44.5651[/C][C]44.4567[/C][C]1.00244[/C][C]0.996744[/C][/ROW]
[ROW][C]45[/C][C]44.49[/C][C]44.5366[/C][C]44.465[/C][C]1.00161[/C][C]0.998953[/C][/ROW]
[ROW][C]46[/C][C]44.46[/C][C]44.4472[/C][C]44.4729[/C][C]0.999422[/C][C]1.00029[/C][/ROW]
[ROW][C]47[/C][C]44.49[/C][C]44.333[/C][C]44.4762[/C][C]0.996778[/C][C]1.00354[/C][/ROW]
[ROW][C]48[/C][C]44.5[/C][C]44.3258[/C][C]44.4817[/C][C]0.996496[/C][C]1.00393[/C][/ROW]
[ROW][C]49[/C][C]44.5[/C][C]44.3449[/C][C]44.4942[/C][C]0.996645[/C][C]1.0035[/C][/ROW]
[ROW][C]50[/C][C]44.5[/C][C]44.4243[/C][C]44.5104[/C][C]0.998066[/C][C]1.0017[/C][/ROW]
[ROW][C]51[/C][C]44.55[/C][C]44.5842[/C][C]44.5204[/C][C]1.00143[/C][C]0.999233[/C][/ROW]
[ROW][C]52[/C][C]44.53[/C][C]44.7014[/C][C]44.5279[/C][C]1.0039[/C][C]0.996166[/C][/ROW]
[ROW][C]53[/C][C]44.49[/C][C]44.5896[/C][C]44.5138[/C][C]1.0017[/C][C]0.997766[/C][/ROW]
[ROW][C]54[/C][C]44.49[/C][C]44.4725[/C][C]44.4767[/C][C]0.999905[/C][C]1.00039[/C][/ROW]
[ROW][C]55[/C][C]44.62[/C][C]44.5117[/C][C]44.4404[/C][C]1.0016[/C][C]1.00243[/C][/ROW]
[ROW][C]56[/C][C]44.59[/C][C]44.5142[/C][C]44.4058[/C][C]1.00244[/C][C]1.0017[/C][/ROW]
[ROW][C]57[/C][C]44.56[/C][C]44.4465[/C][C]44.375[/C][C]1.00161[/C][C]1.00255[/C][/ROW]
[ROW][C]58[/C][C]44.57[/C][C]44.3331[/C][C]44.3588[/C][C]0.999422[/C][C]1.00534[/C][/ROW]
[ROW][C]59[/C][C]44.04[/C][C]44.2146[/C][C]44.3575[/C][C]0.996778[/C][C]0.996051[/C][/ROW]
[ROW][C]60[/C][C]44.06[/C][C]44.1925[/C][C]44.3479[/C][C]0.996496[/C][C]0.997001[/C][/ROW]
[ROW][C]61[/C][C]44.07[/C][C]44.1734[/C][C]44.3221[/C][C]0.996645[/C][C]0.99766[/C][/ROW]
[ROW][C]62[/C][C]44.1[/C][C]44.2077[/C][C]44.2933[/C][C]0.998066[/C][C]0.997565[/C][/ROW]
[ROW][C]63[/C][C]44.21[/C][C]44.3389[/C][C]44.2754[/C][C]1.00143[/C][C]0.997094[/C][/ROW]
[ROW][C]64[/C][C]44.48[/C][C]44.4358[/C][C]44.2633[/C][C]1.0039[/C][C]1.001[/C][/ROW]
[ROW][C]65[/C][C]44.51[/C][C]44.3392[/C][C]44.2638[/C][C]1.0017[/C][C]1.00385[/C][/ROW]
[ROW][C]66[/C][C]44.24[/C][C]44.2746[/C][C]44.2787[/C][C]0.999905[/C][C]0.999219[/C][/ROW]
[ROW][C]67[/C][C]44.25[/C][C]NA[/C][C]NA[/C][C]1.0016[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]44.27[/C][C]NA[/C][C]NA[/C][C]1.00244[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]44.45[/C][C]NA[/C][C]NA[/C][C]1.00161[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]44.39[/C][C]NA[/C][C]NA[/C][C]0.999422[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]44.23[/C][C]NA[/C][C]NA[/C][C]0.996778[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]44.23[/C][C]NA[/C][C]NA[/C][C]0.996496[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=261672&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=261672&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	44.91	NA	NA	0.996645	NA
2	44.86	NA	NA	0.998066	NA
3	44.76	NA	NA	1.00143	NA
4	44.89	NA	NA	1.0039	NA
5	44.89	NA	NA	1.0017	NA
6	45	NA	NA	0.999905	NA
7	45.01	44.8965	44.8246	1.0016	1.00253
8	45.11	44.9043	44.795	1.00244	1.00458
9	45.05	44.8567	44.7846	1.00161	1.00431
10	44.67	44.7558	44.7817	0.999422	0.998084
11	44.48	44.6133	44.7575	0.996778	0.997012
12	44.48	44.5563	44.7129	0.996496	0.998288
13	44.48	44.5147	44.6646	0.996645	0.99922
14	44.58	44.5262	44.6125	0.998066	1.00121
15	44.79	44.6193	44.5554	1.00143	1.00383
16	44.79	44.6884	44.515	1.0039	1.00227
17	44.41	44.5754	44.4996	1.0017	0.996289
18	44.41	44.4887	44.4929	0.999905	0.998231
19	44.44	44.5547	44.4833	1.0016	0.997426
20	44.43	44.5789	44.4704	1.00244	0.99666
21	44.36	44.537	44.4654	1.00161	0.996025
22	44.39	44.4484	44.4742	0.999422	0.998685
23	44.39	44.3591	44.5025	0.996778	1.0007
24	44.41	44.3831	44.5392	0.996496	1.00061
25	44.32	44.4188	44.5683	0.996645	0.997776
26	44.43	44.5108	44.5971	0.998066	0.998184
27	44.82	44.6885	44.6246	1.00143	1.00294
28	44.97	44.8147	44.6408	1.0039	1.00346
29	44.91	44.7282	44.6521	1.0017	1.00406
30	44.79	44.6545	44.6588	0.999905	1.00303
31	44.76	44.7354	44.6638	1.0016	1.00055
32	44.8	44.7794	44.6704	1.00244	1.00046
33	44.65	44.7257	44.6538	1.00161	0.998308
34	44.49	44.5904	44.6162	0.999422	0.997747
35	44.56	44.4335	44.5771	0.996778	1.00285
36	44.4	44.3856	44.5417	0.996496	1.00032
37	44.45	44.3615	44.5108	0.996645	1.002
38	44.46	44.394	44.48	0.998066	1.00149
39	44.39	44.5212	44.4575	1.00143	0.997053
40	44.5	44.6227	44.4496	1.0039	0.997249
41	44.44	44.5212	44.4454	1.0017	0.998177
42	44.41	44.4425	44.4467	0.999905	0.99927
43	44.4	44.5242	44.4529	1.0016	0.99721
44	44.42	44.5651	44.4567	1.00244	0.996744
45	44.49	44.5366	44.465	1.00161	0.998953
46	44.46	44.4472	44.4729	0.999422	1.00029
47	44.49	44.333	44.4762	0.996778	1.00354
48	44.5	44.3258	44.4817	0.996496	1.00393
49	44.5	44.3449	44.4942	0.996645	1.0035
50	44.5	44.4243	44.5104	0.998066	1.0017
51	44.55	44.5842	44.5204	1.00143	0.999233
52	44.53	44.7014	44.5279	1.0039	0.996166
53	44.49	44.5896	44.5138	1.0017	0.997766
54	44.49	44.4725	44.4767	0.999905	1.00039
55	44.62	44.5117	44.4404	1.0016	1.00243
56	44.59	44.5142	44.4058	1.00244	1.0017
57	44.56	44.4465	44.375	1.00161	1.00255
58	44.57	44.3331	44.3588	0.999422	1.00534
59	44.04	44.2146	44.3575	0.996778	0.996051
60	44.06	44.1925	44.3479	0.996496	0.997001
61	44.07	44.1734	44.3221	0.996645	0.99766
62	44.1	44.2077	44.2933	0.998066	0.997565
63	44.21	44.3389	44.2754	1.00143	0.997094
64	44.48	44.4358	44.2633	1.0039	1.001
65	44.51	44.3392	44.2638	1.0017	1.00385
66	44.24	44.2746	44.2787	0.999905	0.999219
67	44.25	NA	NA	1.0016	NA
68	44.27	NA	NA	1.00244	NA
69	44.45	NA	NA	1.00161	NA
70	44.39	NA	NA	0.999422	NA
71	44.23	NA	NA	0.996778	NA
72	44.23	NA	NA	0.996496	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
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