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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Thu, 02 Apr 2015 18:09:42 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Apr/02/t1427994635sekx557a18ddfg1.htm/, Retrieved Thu, 09 May 2024 17:39:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278597, Retrieved Thu, 09 May 2024 17:39:51 +0000

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-       [Classical Decomposition] [] [2015-04-02 17:09:42] [7281bb56277fa48a38e7263e2ca5f521] [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	'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278597&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278597&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278597&T=0

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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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.3213	NA	NA	0.998207	NA
2	1.2999	NA	NA	0.994267	NA
3	1.3074	NA	NA	0.991	NA
4	1.3242	NA	NA	1.00094	NA
5	1.3516	NA	NA	1.00937	NA
6	1.3511	NA	NA	0.996817	NA
7	1.3419	1.35865	1.36498	0.995364	0.987671
8	1.3716	1.38426	1.3778	1.00469	0.990851
9	1.3622	1.39238	1.39193	1.00032	0.978321
10	1.3896	1.41018	1.40843	1.00124	0.985409
11	1.4227	1.43776	1.42726	1.00735	0.989525
12	1.4684	1.44571	1.4451	1.00043	1.01569
13	1.457	1.45989	1.46252	0.998207	0.998018
14	1.4718	1.47148	1.47997	0.994267	1.00022
15	1.4748	1.48072	1.49416	0.991	0.996005
16	1.5527	1.50318	1.50177	1.00094	1.03294
17	1.5751	1.51402	1.49997	1.00937	1.04034
18	1.5557	1.48333	1.48807	0.996817	1.04879
19	1.5553	1.46842	1.47526	0.995364	1.05916
20	1.577	1.4713	1.46443	1.00469	1.07184
21	1.4975	1.45056	1.45009	1.00032	1.03236
22	1.4369	1.43336	1.43159	1.00124	1.00247
23	1.3322	1.42097	1.4106	1.00735	0.937528
24	1.2732	1.39257	1.39198	1.00043	0.91428
25	1.3449	1.37516	1.37763	0.998207	0.977996
26	1.3239	1.3564	1.36422	0.994267	0.976043
27	1.2785	1.34207	1.35426	0.991	0.952629
28	1.305	1.35339	1.35212	1.00094	0.964244
29	1.319	1.37188	1.35915	1.00937	0.961455
30	1.365	1.37009	1.37447	0.996817	0.996284
31	1.4016	1.38198	1.38841	0.995364	1.0142
32	1.4088	1.40413	1.39757	1.00469	1.00332
33	1.4268	1.40609	1.40563	1.00032	1.01473
34	1.4562	1.4133	1.41155	1.00124	1.03036
35	1.4816	1.42501	1.41461	1.00735	1.03971
36	1.4914	1.41159	1.41099	1.00043	1.05654
37	1.4614	1.39643	1.39894	0.998207	1.04653
38	1.4272	1.37797	1.38592	0.994267	1.03573
39	1.3686	1.36233	1.3747	0.991	1.0046
40	1.3569	1.36403	1.36275	1.00094	0.994775
41	1.3406	1.36536	1.35269	1.00937	0.981865
42	1.2565	1.33937	1.34365	0.996817	0.938129
43	1.2209	1.32644	1.33262	0.995364	0.920435
44	1.277	1.32922	1.32301	1.00469	0.960714
45	1.2894	1.31948	1.31905	1.00032	0.977202
46	1.3067	1.32233	1.32069	1.00124	0.988181
47	1.3898	1.33656	1.3268	1.00735	1.03983
48	1.3661	1.33912	1.33855	1.00043	1.02015
49	1.322	1.35263	1.35506	0.998207	0.977353
50	1.336	1.36251	1.37037	0.994267	0.980543
51	1.3649	1.37019	1.38263	0.991	0.996142
52	1.3999	1.3929	1.3916	1.00094	1.00502
53	1.4442	1.40678	1.39372	1.00937	1.0266
54	1.4349	1.38805	1.39249	0.996817	1.03375
55	1.4388	1.38543	1.39188	0.995364	1.03853
56	1.4264	1.39634	1.38981	1.00469	1.02153
57	1.4343	1.3866	1.38615	1.00032	1.0344
58	1.377	1.38276	1.38105	1.00124	0.995833
59	1.3706	1.38249	1.37239	1.00735	0.991403
60	1.3556	1.36114	1.36056	1.00043	0.995932
61	1.3179	1.34389	1.3463	0.998207	0.980664
62	1.2905	1.32268	1.33031	0.994267	0.975669
63	1.3224	1.30215	1.31398	0.991	1.01555
64	1.3201	1.3033	1.30207	1.00094	1.01289
65	1.3162	1.30735	1.29522	1.00937	1.00677
66	1.2789	1.28503	1.28913	0.996817	0.99523
67	1.2526	1.27989	1.28585	0.995364	0.978679
68	1.2288	1.29324	1.2872	1.00469	0.950173
69	1.24	1.28977	1.28935	1.00032	0.96141
70	1.2856	1.29053	1.28893	1.00124	0.996182
71	1.2974	1.29684	1.28738	1.00735	1.00043
72	1.2828	1.28816	1.28761	1.00043	0.995839
73	1.3119	1.28886	1.29118	0.998207	1.01787
74	1.3288	1.2898	1.29724	0.994267	1.03023
75	1.3359	1.29259	1.30433	0.991	1.0335
76	1.2964	1.31141	1.31018	1.00094	0.988557
77	1.3026	1.32729	1.31498	1.00937	0.981395
78	1.2982	1.3163	1.3205	0.996817	0.986249
79	1.3189	1.31957	1.32571	0.995364	0.999495
80	1.308	NA	NA	1.00469	NA
81	1.331	NA	NA	1.00032	NA
82	1.3348	NA	NA	1.00124	NA
83	1.3635	NA	NA	1.00735	NA
84	1.3493	NA	NA	1.00043	NA
85	1.3704	NA	NA	0.998207	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.3213 & NA & NA & 0.998207 & NA \tabularnewline
2 & 1.2999 & NA & NA & 0.994267 & NA \tabularnewline
3 & 1.3074 & NA & NA & 0.991 & NA \tabularnewline
4 & 1.3242 & NA & NA & 1.00094 & NA \tabularnewline
5 & 1.3516 & NA & NA & 1.00937 & NA \tabularnewline
6 & 1.3511 & NA & NA & 0.996817 & NA \tabularnewline
7 & 1.3419 & 1.35865 & 1.36498 & 0.995364 & 0.987671 \tabularnewline
8 & 1.3716 & 1.38426 & 1.3778 & 1.00469 & 0.990851 \tabularnewline
9 & 1.3622 & 1.39238 & 1.39193 & 1.00032 & 0.978321 \tabularnewline
10 & 1.3896 & 1.41018 & 1.40843 & 1.00124 & 0.985409 \tabularnewline
11 & 1.4227 & 1.43776 & 1.42726 & 1.00735 & 0.989525 \tabularnewline
12 & 1.4684 & 1.44571 & 1.4451 & 1.00043 & 1.01569 \tabularnewline
13 & 1.457 & 1.45989 & 1.46252 & 0.998207 & 0.998018 \tabularnewline
14 & 1.4718 & 1.47148 & 1.47997 & 0.994267 & 1.00022 \tabularnewline
15 & 1.4748 & 1.48072 & 1.49416 & 0.991 & 0.996005 \tabularnewline
16 & 1.5527 & 1.50318 & 1.50177 & 1.00094 & 1.03294 \tabularnewline
17 & 1.5751 & 1.51402 & 1.49997 & 1.00937 & 1.04034 \tabularnewline
18 & 1.5557 & 1.48333 & 1.48807 & 0.996817 & 1.04879 \tabularnewline
19 & 1.5553 & 1.46842 & 1.47526 & 0.995364 & 1.05916 \tabularnewline
20 & 1.577 & 1.4713 & 1.46443 & 1.00469 & 1.07184 \tabularnewline
21 & 1.4975 & 1.45056 & 1.45009 & 1.00032 & 1.03236 \tabularnewline
22 & 1.4369 & 1.43336 & 1.43159 & 1.00124 & 1.00247 \tabularnewline
23 & 1.3322 & 1.42097 & 1.4106 & 1.00735 & 0.937528 \tabularnewline
24 & 1.2732 & 1.39257 & 1.39198 & 1.00043 & 0.91428 \tabularnewline
25 & 1.3449 & 1.37516 & 1.37763 & 0.998207 & 0.977996 \tabularnewline
26 & 1.3239 & 1.3564 & 1.36422 & 0.994267 & 0.976043 \tabularnewline
27 & 1.2785 & 1.34207 & 1.35426 & 0.991 & 0.952629 \tabularnewline
28 & 1.305 & 1.35339 & 1.35212 & 1.00094 & 0.964244 \tabularnewline
29 & 1.319 & 1.37188 & 1.35915 & 1.00937 & 0.961455 \tabularnewline
30 & 1.365 & 1.37009 & 1.37447 & 0.996817 & 0.996284 \tabularnewline
31 & 1.4016 & 1.38198 & 1.38841 & 0.995364 & 1.0142 \tabularnewline
32 & 1.4088 & 1.40413 & 1.39757 & 1.00469 & 1.00332 \tabularnewline
33 & 1.4268 & 1.40609 & 1.40563 & 1.00032 & 1.01473 \tabularnewline
34 & 1.4562 & 1.4133 & 1.41155 & 1.00124 & 1.03036 \tabularnewline
35 & 1.4816 & 1.42501 & 1.41461 & 1.00735 & 1.03971 \tabularnewline
36 & 1.4914 & 1.41159 & 1.41099 & 1.00043 & 1.05654 \tabularnewline
37 & 1.4614 & 1.39643 & 1.39894 & 0.998207 & 1.04653 \tabularnewline
38 & 1.4272 & 1.37797 & 1.38592 & 0.994267 & 1.03573 \tabularnewline
39 & 1.3686 & 1.36233 & 1.3747 & 0.991 & 1.0046 \tabularnewline
40 & 1.3569 & 1.36403 & 1.36275 & 1.00094 & 0.994775 \tabularnewline
41 & 1.3406 & 1.36536 & 1.35269 & 1.00937 & 0.981865 \tabularnewline
42 & 1.2565 & 1.33937 & 1.34365 & 0.996817 & 0.938129 \tabularnewline
43 & 1.2209 & 1.32644 & 1.33262 & 0.995364 & 0.920435 \tabularnewline
44 & 1.277 & 1.32922 & 1.32301 & 1.00469 & 0.960714 \tabularnewline
45 & 1.2894 & 1.31948 & 1.31905 & 1.00032 & 0.977202 \tabularnewline
46 & 1.3067 & 1.32233 & 1.32069 & 1.00124 & 0.988181 \tabularnewline
47 & 1.3898 & 1.33656 & 1.3268 & 1.00735 & 1.03983 \tabularnewline
48 & 1.3661 & 1.33912 & 1.33855 & 1.00043 & 1.02015 \tabularnewline
49 & 1.322 & 1.35263 & 1.35506 & 0.998207 & 0.977353 \tabularnewline
50 & 1.336 & 1.36251 & 1.37037 & 0.994267 & 0.980543 \tabularnewline
51 & 1.3649 & 1.37019 & 1.38263 & 0.991 & 0.996142 \tabularnewline
52 & 1.3999 & 1.3929 & 1.3916 & 1.00094 & 1.00502 \tabularnewline
53 & 1.4442 & 1.40678 & 1.39372 & 1.00937 & 1.0266 \tabularnewline
54 & 1.4349 & 1.38805 & 1.39249 & 0.996817 & 1.03375 \tabularnewline
55 & 1.4388 & 1.38543 & 1.39188 & 0.995364 & 1.03853 \tabularnewline
56 & 1.4264 & 1.39634 & 1.38981 & 1.00469 & 1.02153 \tabularnewline
57 & 1.4343 & 1.3866 & 1.38615 & 1.00032 & 1.0344 \tabularnewline
58 & 1.377 & 1.38276 & 1.38105 & 1.00124 & 0.995833 \tabularnewline
59 & 1.3706 & 1.38249 & 1.37239 & 1.00735 & 0.991403 \tabularnewline
60 & 1.3556 & 1.36114 & 1.36056 & 1.00043 & 0.995932 \tabularnewline
61 & 1.3179 & 1.34389 & 1.3463 & 0.998207 & 0.980664 \tabularnewline
62 & 1.2905 & 1.32268 & 1.33031 & 0.994267 & 0.975669 \tabularnewline
63 & 1.3224 & 1.30215 & 1.31398 & 0.991 & 1.01555 \tabularnewline
64 & 1.3201 & 1.3033 & 1.30207 & 1.00094 & 1.01289 \tabularnewline
65 & 1.3162 & 1.30735 & 1.29522 & 1.00937 & 1.00677 \tabularnewline
66 & 1.2789 & 1.28503 & 1.28913 & 0.996817 & 0.99523 \tabularnewline
67 & 1.2526 & 1.27989 & 1.28585 & 0.995364 & 0.978679 \tabularnewline
68 & 1.2288 & 1.29324 & 1.2872 & 1.00469 & 0.950173 \tabularnewline
69 & 1.24 & 1.28977 & 1.28935 & 1.00032 & 0.96141 \tabularnewline
70 & 1.2856 & 1.29053 & 1.28893 & 1.00124 & 0.996182 \tabularnewline
71 & 1.2974 & 1.29684 & 1.28738 & 1.00735 & 1.00043 \tabularnewline
72 & 1.2828 & 1.28816 & 1.28761 & 1.00043 & 0.995839 \tabularnewline
73 & 1.3119 & 1.28886 & 1.29118 & 0.998207 & 1.01787 \tabularnewline
74 & 1.3288 & 1.2898 & 1.29724 & 0.994267 & 1.03023 \tabularnewline
75 & 1.3359 & 1.29259 & 1.30433 & 0.991 & 1.0335 \tabularnewline
76 & 1.2964 & 1.31141 & 1.31018 & 1.00094 & 0.988557 \tabularnewline
77 & 1.3026 & 1.32729 & 1.31498 & 1.00937 & 0.981395 \tabularnewline
78 & 1.2982 & 1.3163 & 1.3205 & 0.996817 & 0.986249 \tabularnewline
79 & 1.3189 & 1.31957 & 1.32571 & 0.995364 & 0.999495 \tabularnewline
80 & 1.308 & NA & NA & 1.00469 & NA \tabularnewline
81 & 1.331 & NA & NA & 1.00032 & NA \tabularnewline
82 & 1.3348 & NA & NA & 1.00124 & NA \tabularnewline
83 & 1.3635 & NA & NA & 1.00735 & NA \tabularnewline
84 & 1.3493 & NA & NA & 1.00043 & NA \tabularnewline
85 & 1.3704 & NA & NA & 0.998207 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278597&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]1.3213[/C][C]NA[/C][C]NA[/C][C]0.998207[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.2999[/C][C]NA[/C][C]NA[/C][C]0.994267[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.3074[/C][C]NA[/C][C]NA[/C][C]0.991[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.3242[/C][C]NA[/C][C]NA[/C][C]1.00094[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.3516[/C][C]NA[/C][C]NA[/C][C]1.00937[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.3511[/C][C]NA[/C][C]NA[/C][C]0.996817[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.3419[/C][C]1.35865[/C][C]1.36498[/C][C]0.995364[/C][C]0.987671[/C][/ROW]
[ROW][C]8[/C][C]1.3716[/C][C]1.38426[/C][C]1.3778[/C][C]1.00469[/C][C]0.990851[/C][/ROW]
[ROW][C]9[/C][C]1.3622[/C][C]1.39238[/C][C]1.39193[/C][C]1.00032[/C][C]0.978321[/C][/ROW]
[ROW][C]10[/C][C]1.3896[/C][C]1.41018[/C][C]1.40843[/C][C]1.00124[/C][C]0.985409[/C][/ROW]
[ROW][C]11[/C][C]1.4227[/C][C]1.43776[/C][C]1.42726[/C][C]1.00735[/C][C]0.989525[/C][/ROW]
[ROW][C]12[/C][C]1.4684[/C][C]1.44571[/C][C]1.4451[/C][C]1.00043[/C][C]1.01569[/C][/ROW]
[ROW][C]13[/C][C]1.457[/C][C]1.45989[/C][C]1.46252[/C][C]0.998207[/C][C]0.998018[/C][/ROW]
[ROW][C]14[/C][C]1.4718[/C][C]1.47148[/C][C]1.47997[/C][C]0.994267[/C][C]1.00022[/C][/ROW]
[ROW][C]15[/C][C]1.4748[/C][C]1.48072[/C][C]1.49416[/C][C]0.991[/C][C]0.996005[/C][/ROW]
[ROW][C]16[/C][C]1.5527[/C][C]1.50318[/C][C]1.50177[/C][C]1.00094[/C][C]1.03294[/C][/ROW]
[ROW][C]17[/C][C]1.5751[/C][C]1.51402[/C][C]1.49997[/C][C]1.00937[/C][C]1.04034[/C][/ROW]
[ROW][C]18[/C][C]1.5557[/C][C]1.48333[/C][C]1.48807[/C][C]0.996817[/C][C]1.04879[/C][/ROW]
[ROW][C]19[/C][C]1.5553[/C][C]1.46842[/C][C]1.47526[/C][C]0.995364[/C][C]1.05916[/C][/ROW]
[ROW][C]20[/C][C]1.577[/C][C]1.4713[/C][C]1.46443[/C][C]1.00469[/C][C]1.07184[/C][/ROW]
[ROW][C]21[/C][C]1.4975[/C][C]1.45056[/C][C]1.45009[/C][C]1.00032[/C][C]1.03236[/C][/ROW]
[ROW][C]22[/C][C]1.4369[/C][C]1.43336[/C][C]1.43159[/C][C]1.00124[/C][C]1.00247[/C][/ROW]
[ROW][C]23[/C][C]1.3322[/C][C]1.42097[/C][C]1.4106[/C][C]1.00735[/C][C]0.937528[/C][/ROW]
[ROW][C]24[/C][C]1.2732[/C][C]1.39257[/C][C]1.39198[/C][C]1.00043[/C][C]0.91428[/C][/ROW]
[ROW][C]25[/C][C]1.3449[/C][C]1.37516[/C][C]1.37763[/C][C]0.998207[/C][C]0.977996[/C][/ROW]
[ROW][C]26[/C][C]1.3239[/C][C]1.3564[/C][C]1.36422[/C][C]0.994267[/C][C]0.976043[/C][/ROW]
[ROW][C]27[/C][C]1.2785[/C][C]1.34207[/C][C]1.35426[/C][C]0.991[/C][C]0.952629[/C][/ROW]
[ROW][C]28[/C][C]1.305[/C][C]1.35339[/C][C]1.35212[/C][C]1.00094[/C][C]0.964244[/C][/ROW]
[ROW][C]29[/C][C]1.319[/C][C]1.37188[/C][C]1.35915[/C][C]1.00937[/C][C]0.961455[/C][/ROW]
[ROW][C]30[/C][C]1.365[/C][C]1.37009[/C][C]1.37447[/C][C]0.996817[/C][C]0.996284[/C][/ROW]
[ROW][C]31[/C][C]1.4016[/C][C]1.38198[/C][C]1.38841[/C][C]0.995364[/C][C]1.0142[/C][/ROW]
[ROW][C]32[/C][C]1.4088[/C][C]1.40413[/C][C]1.39757[/C][C]1.00469[/C][C]1.00332[/C][/ROW]
[ROW][C]33[/C][C]1.4268[/C][C]1.40609[/C][C]1.40563[/C][C]1.00032[/C][C]1.01473[/C][/ROW]
[ROW][C]34[/C][C]1.4562[/C][C]1.4133[/C][C]1.41155[/C][C]1.00124[/C][C]1.03036[/C][/ROW]
[ROW][C]35[/C][C]1.4816[/C][C]1.42501[/C][C]1.41461[/C][C]1.00735[/C][C]1.03971[/C][/ROW]
[ROW][C]36[/C][C]1.4914[/C][C]1.41159[/C][C]1.41099[/C][C]1.00043[/C][C]1.05654[/C][/ROW]
[ROW][C]37[/C][C]1.4614[/C][C]1.39643[/C][C]1.39894[/C][C]0.998207[/C][C]1.04653[/C][/ROW]
[ROW][C]38[/C][C]1.4272[/C][C]1.37797[/C][C]1.38592[/C][C]0.994267[/C][C]1.03573[/C][/ROW]
[ROW][C]39[/C][C]1.3686[/C][C]1.36233[/C][C]1.3747[/C][C]0.991[/C][C]1.0046[/C][/ROW]
[ROW][C]40[/C][C]1.3569[/C][C]1.36403[/C][C]1.36275[/C][C]1.00094[/C][C]0.994775[/C][/ROW]
[ROW][C]41[/C][C]1.3406[/C][C]1.36536[/C][C]1.35269[/C][C]1.00937[/C][C]0.981865[/C][/ROW]
[ROW][C]42[/C][C]1.2565[/C][C]1.33937[/C][C]1.34365[/C][C]0.996817[/C][C]0.938129[/C][/ROW]
[ROW][C]43[/C][C]1.2209[/C][C]1.32644[/C][C]1.33262[/C][C]0.995364[/C][C]0.920435[/C][/ROW]
[ROW][C]44[/C][C]1.277[/C][C]1.32922[/C][C]1.32301[/C][C]1.00469[/C][C]0.960714[/C][/ROW]
[ROW][C]45[/C][C]1.2894[/C][C]1.31948[/C][C]1.31905[/C][C]1.00032[/C][C]0.977202[/C][/ROW]
[ROW][C]46[/C][C]1.3067[/C][C]1.32233[/C][C]1.32069[/C][C]1.00124[/C][C]0.988181[/C][/ROW]
[ROW][C]47[/C][C]1.3898[/C][C]1.33656[/C][C]1.3268[/C][C]1.00735[/C][C]1.03983[/C][/ROW]
[ROW][C]48[/C][C]1.3661[/C][C]1.33912[/C][C]1.33855[/C][C]1.00043[/C][C]1.02015[/C][/ROW]
[ROW][C]49[/C][C]1.322[/C][C]1.35263[/C][C]1.35506[/C][C]0.998207[/C][C]0.977353[/C][/ROW]
[ROW][C]50[/C][C]1.336[/C][C]1.36251[/C][C]1.37037[/C][C]0.994267[/C][C]0.980543[/C][/ROW]
[ROW][C]51[/C][C]1.3649[/C][C]1.37019[/C][C]1.38263[/C][C]0.991[/C][C]0.996142[/C][/ROW]
[ROW][C]52[/C][C]1.3999[/C][C]1.3929[/C][C]1.3916[/C][C]1.00094[/C][C]1.00502[/C][/ROW]
[ROW][C]53[/C][C]1.4442[/C][C]1.40678[/C][C]1.39372[/C][C]1.00937[/C][C]1.0266[/C][/ROW]
[ROW][C]54[/C][C]1.4349[/C][C]1.38805[/C][C]1.39249[/C][C]0.996817[/C][C]1.03375[/C][/ROW]
[ROW][C]55[/C][C]1.4388[/C][C]1.38543[/C][C]1.39188[/C][C]0.995364[/C][C]1.03853[/C][/ROW]
[ROW][C]56[/C][C]1.4264[/C][C]1.39634[/C][C]1.38981[/C][C]1.00469[/C][C]1.02153[/C][/ROW]
[ROW][C]57[/C][C]1.4343[/C][C]1.3866[/C][C]1.38615[/C][C]1.00032[/C][C]1.0344[/C][/ROW]
[ROW][C]58[/C][C]1.377[/C][C]1.38276[/C][C]1.38105[/C][C]1.00124[/C][C]0.995833[/C][/ROW]
[ROW][C]59[/C][C]1.3706[/C][C]1.38249[/C][C]1.37239[/C][C]1.00735[/C][C]0.991403[/C][/ROW]
[ROW][C]60[/C][C]1.3556[/C][C]1.36114[/C][C]1.36056[/C][C]1.00043[/C][C]0.995932[/C][/ROW]
[ROW][C]61[/C][C]1.3179[/C][C]1.34389[/C][C]1.3463[/C][C]0.998207[/C][C]0.980664[/C][/ROW]
[ROW][C]62[/C][C]1.2905[/C][C]1.32268[/C][C]1.33031[/C][C]0.994267[/C][C]0.975669[/C][/ROW]
[ROW][C]63[/C][C]1.3224[/C][C]1.30215[/C][C]1.31398[/C][C]0.991[/C][C]1.01555[/C][/ROW]
[ROW][C]64[/C][C]1.3201[/C][C]1.3033[/C][C]1.30207[/C][C]1.00094[/C][C]1.01289[/C][/ROW]
[ROW][C]65[/C][C]1.3162[/C][C]1.30735[/C][C]1.29522[/C][C]1.00937[/C][C]1.00677[/C][/ROW]
[ROW][C]66[/C][C]1.2789[/C][C]1.28503[/C][C]1.28913[/C][C]0.996817[/C][C]0.99523[/C][/ROW]
[ROW][C]67[/C][C]1.2526[/C][C]1.27989[/C][C]1.28585[/C][C]0.995364[/C][C]0.978679[/C][/ROW]
[ROW][C]68[/C][C]1.2288[/C][C]1.29324[/C][C]1.2872[/C][C]1.00469[/C][C]0.950173[/C][/ROW]
[ROW][C]69[/C][C]1.24[/C][C]1.28977[/C][C]1.28935[/C][C]1.00032[/C][C]0.96141[/C][/ROW]
[ROW][C]70[/C][C]1.2856[/C][C]1.29053[/C][C]1.28893[/C][C]1.00124[/C][C]0.996182[/C][/ROW]
[ROW][C]71[/C][C]1.2974[/C][C]1.29684[/C][C]1.28738[/C][C]1.00735[/C][C]1.00043[/C][/ROW]
[ROW][C]72[/C][C]1.2828[/C][C]1.28816[/C][C]1.28761[/C][C]1.00043[/C][C]0.995839[/C][/ROW]
[ROW][C]73[/C][C]1.3119[/C][C]1.28886[/C][C]1.29118[/C][C]0.998207[/C][C]1.01787[/C][/ROW]
[ROW][C]74[/C][C]1.3288[/C][C]1.2898[/C][C]1.29724[/C][C]0.994267[/C][C]1.03023[/C][/ROW]
[ROW][C]75[/C][C]1.3359[/C][C]1.29259[/C][C]1.30433[/C][C]0.991[/C][C]1.0335[/C][/ROW]
[ROW][C]76[/C][C]1.2964[/C][C]1.31141[/C][C]1.31018[/C][C]1.00094[/C][C]0.988557[/C][/ROW]
[ROW][C]77[/C][C]1.3026[/C][C]1.32729[/C][C]1.31498[/C][C]1.00937[/C][C]0.981395[/C][/ROW]
[ROW][C]78[/C][C]1.2982[/C][C]1.3163[/C][C]1.3205[/C][C]0.996817[/C][C]0.986249[/C][/ROW]
[ROW][C]79[/C][C]1.3189[/C][C]1.31957[/C][C]1.32571[/C][C]0.995364[/C][C]0.999495[/C][/ROW]
[ROW][C]80[/C][C]1.308[/C][C]NA[/C][C]NA[/C][C]1.00469[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]1.331[/C][C]NA[/C][C]NA[/C][C]1.00032[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]1.3348[/C][C]NA[/C][C]NA[/C][C]1.00124[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]1.3635[/C][C]NA[/C][C]NA[/C][C]1.00735[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]1.3493[/C][C]NA[/C][C]NA[/C][C]1.00043[/C][C]NA[/C][/ROW]
[ROW][C]85[/C][C]1.3704[/C][C]NA[/C][C]NA[/C][C]0.998207[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278597&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278597&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	1.3213	NA	NA	0.998207	NA
2	1.2999	NA	NA	0.994267	NA
3	1.3074	NA	NA	0.991	NA
4	1.3242	NA	NA	1.00094	NA
5	1.3516	NA	NA	1.00937	NA
6	1.3511	NA	NA	0.996817	NA
7	1.3419	1.35865	1.36498	0.995364	0.987671
8	1.3716	1.38426	1.3778	1.00469	0.990851
9	1.3622	1.39238	1.39193	1.00032	0.978321
10	1.3896	1.41018	1.40843	1.00124	0.985409
11	1.4227	1.43776	1.42726	1.00735	0.989525
12	1.4684	1.44571	1.4451	1.00043	1.01569
13	1.457	1.45989	1.46252	0.998207	0.998018
14	1.4718	1.47148	1.47997	0.994267	1.00022
15	1.4748	1.48072	1.49416	0.991	0.996005
16	1.5527	1.50318	1.50177	1.00094	1.03294
17	1.5751	1.51402	1.49997	1.00937	1.04034
18	1.5557	1.48333	1.48807	0.996817	1.04879
19	1.5553	1.46842	1.47526	0.995364	1.05916
20	1.577	1.4713	1.46443	1.00469	1.07184
21	1.4975	1.45056	1.45009	1.00032	1.03236
22	1.4369	1.43336	1.43159	1.00124	1.00247
23	1.3322	1.42097	1.4106	1.00735	0.937528
24	1.2732	1.39257	1.39198	1.00043	0.91428
25	1.3449	1.37516	1.37763	0.998207	0.977996
26	1.3239	1.3564	1.36422	0.994267	0.976043
27	1.2785	1.34207	1.35426	0.991	0.952629
28	1.305	1.35339	1.35212	1.00094	0.964244
29	1.319	1.37188	1.35915	1.00937	0.961455
30	1.365	1.37009	1.37447	0.996817	0.996284
31	1.4016	1.38198	1.38841	0.995364	1.0142
32	1.4088	1.40413	1.39757	1.00469	1.00332
33	1.4268	1.40609	1.40563	1.00032	1.01473
34	1.4562	1.4133	1.41155	1.00124	1.03036
35	1.4816	1.42501	1.41461	1.00735	1.03971
36	1.4914	1.41159	1.41099	1.00043	1.05654
37	1.4614	1.39643	1.39894	0.998207	1.04653
38	1.4272	1.37797	1.38592	0.994267	1.03573
39	1.3686	1.36233	1.3747	0.991	1.0046
40	1.3569	1.36403	1.36275	1.00094	0.994775
41	1.3406	1.36536	1.35269	1.00937	0.981865
42	1.2565	1.33937	1.34365	0.996817	0.938129
43	1.2209	1.32644	1.33262	0.995364	0.920435
44	1.277	1.32922	1.32301	1.00469	0.960714
45	1.2894	1.31948	1.31905	1.00032	0.977202
46	1.3067	1.32233	1.32069	1.00124	0.988181
47	1.3898	1.33656	1.3268	1.00735	1.03983
48	1.3661	1.33912	1.33855	1.00043	1.02015
49	1.322	1.35263	1.35506	0.998207	0.977353
50	1.336	1.36251	1.37037	0.994267	0.980543
51	1.3649	1.37019	1.38263	0.991	0.996142
52	1.3999	1.3929	1.3916	1.00094	1.00502
53	1.4442	1.40678	1.39372	1.00937	1.0266
54	1.4349	1.38805	1.39249	0.996817	1.03375
55	1.4388	1.38543	1.39188	0.995364	1.03853
56	1.4264	1.39634	1.38981	1.00469	1.02153
57	1.4343	1.3866	1.38615	1.00032	1.0344
58	1.377	1.38276	1.38105	1.00124	0.995833
59	1.3706	1.38249	1.37239	1.00735	0.991403
60	1.3556	1.36114	1.36056	1.00043	0.995932
61	1.3179	1.34389	1.3463	0.998207	0.980664
62	1.2905	1.32268	1.33031	0.994267	0.975669
63	1.3224	1.30215	1.31398	0.991	1.01555
64	1.3201	1.3033	1.30207	1.00094	1.01289
65	1.3162	1.30735	1.29522	1.00937	1.00677
66	1.2789	1.28503	1.28913	0.996817	0.99523
67	1.2526	1.27989	1.28585	0.995364	0.978679
68	1.2288	1.29324	1.2872	1.00469	0.950173
69	1.24	1.28977	1.28935	1.00032	0.96141
70	1.2856	1.29053	1.28893	1.00124	0.996182
71	1.2974	1.29684	1.28738	1.00735	1.00043
72	1.2828	1.28816	1.28761	1.00043	0.995839
73	1.3119	1.28886	1.29118	0.998207	1.01787
74	1.3288	1.2898	1.29724	0.994267	1.03023
75	1.3359	1.29259	1.30433	0.991	1.0335
76	1.2964	1.31141	1.31018	1.00094	0.988557
77	1.3026	1.32729	1.31498	1.00937	0.981395
78	1.2982	1.3163	1.3205	0.996817	0.986249
79	1.3189	1.31957	1.32571	0.995364	0.999495
80	1.308	NA	NA	1.00469	NA
81	1.331	NA	NA	1.00032	NA
82	1.3348	NA	NA	1.00124	NA
83	1.3635	NA	NA	1.00735	NA
84	1.3493	NA	NA	1.00043	NA
85	1.3704	NA	NA	0.998207	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