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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 09 Dec 2013 04:05:01 -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/Dec/09/t1386579924v79bo9ia0rsl7e5.htm/, Retrieved Tue, 16 Apr 2024 15:20:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231576, Retrieved Tue, 16 Apr 2024 15:20:22 +0000

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Estimated Impact

102

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-       [Classical Decomposition] [] [2013-12-09 09:05:01] [8ac251e42bd40906c127555d6859e07b] [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	7 seconds
R Server	'Gwilym Jenkins' @ jenkins.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 & 7 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231576&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231576&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231576&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	7 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	28.53	NA	NA	0.983371	NA
2	28.48	NA	NA	0.988383	NA
3	28.68	NA	NA	0.994871	NA
4	28.89	NA	NA	1.00313	NA
5	29.2	NA	NA	1.00773	NA
6	29.21	NA	NA	1.00963	NA
7	29.15	29.1637	28.9617	1.00698	0.999531
8	29.22	29.2293	28.9879	1.00833	0.999682
9	29.34	29.3734	29.0108	1.0125	0.998863
10	29.13	29.1898	29.0262	1.00564	0.997951
11	28.84	28.9006	29.0362	0.995329	0.997902
12	28.76	28.5792	29.0404	0.984118	1.00633
13	28.75	28.5682	29.0512	0.983371	1.00637
14	28.89	28.7331	29.0708	0.988383	1.00546
15	28.82	28.9466	29.0958	0.994871	0.995626
16	29.12	29.2167	29.1254	1.00313	0.996691
17	29.21	29.3971	29.1717	1.00773	0.993635
18	29.3	29.5065	29.225	1.00963	0.993003
19	29.32	29.4779	29.2738	1.00698	0.994642
20	29.52	29.5696	29.3254	1.00833	0.998322
21	29.64	29.7666	29.3992	1.0125	0.995748
22	29.54	29.6558	29.4896	1.00564	0.996096
23	29.54	29.4377	29.5758	0.995329	1.00348
24	29.34	29.1906	29.6617	0.984118	1.00512
25	29.34	29.2528	29.7475	0.983371	1.00298
26	29.54	29.4785	29.825	0.988383	1.00208
27	29.94	29.7342	29.8875	0.994871	1.00692
28	30.17	30.0397	29.9458	1.00313	1.00434
29	30.23	30.223	29.9912	1.00773	1.00023
30	30.34	30.3049	30.0158	1.00963	1.00116
31	30.34	30.2495	30.04	1.00698	1.00299
32	30.36	30.3124	30.0621	1.00833	1.00157
33	30.3	30.4513	30.0754	1.0125	0.995032
34	30.28	30.2566	30.0871	1.00564	1.00077
35	29.89	29.9661	30.1067	0.995329	0.997462
36	29.58	29.6531	30.1317	0.984118	0.997534
37	29.68	29.6556	30.1571	0.983371	1.00082
38	29.73	29.8381	30.1888	0.988383	0.996378
39	30.07	30.0725	30.2275	0.994871	0.999918
40	30.32	30.3523	30.2575	1.00313	0.998936
41	30.55	30.5081	30.2742	1.00773	1.00137
42	30.62	30.5662	30.2746	1.00963	1.00176
43	30.67	30.4677	30.2567	1.00698	1.00664
44	30.79	30.5086	30.2567	1.00833	1.00922
45	30.8	30.6487	30.2704	1.0125	1.00494
46	30.5	30.4477	30.2771	1.00564	1.00172
47	30.07	30.1489	30.2904	0.995329	0.997382
48	29.41	29.8294	30.3108	0.984118	0.985939
49	29.42	29.8277	30.3321	0.983371	0.986332
50	29.99	29.9958	30.3483	0.988383	0.999807
51	30.14	30.2325	30.3883	0.994871	0.996941
52	30.41	30.5588	30.4633	1.00313	0.995131
53	30.78	30.7915	30.5554	1.00773	0.999625
54	30.88	30.973	30.6775	1.00963	0.996999
55	30.92	31.0358	30.8208	1.00698	0.996268
56	30.93	31.2023	30.9446	1.00833	0.991274
57	31.62	31.4473	31.0592	1.0125	1.00549
58	31.48	31.3691	31.1933	1.00564	1.00353
59	31.3	31.1799	31.3262	0.995329	1.00385
60	31.11	30.9505	31.45	0.984118	1.00515
61	31.16	31.0491	31.5742	0.983371	1.00357
62	31.22	31.3346	31.7029	0.988383	0.996341
63	31.66	31.639	31.8021	0.994871	1.00066
64	32.11	31.9511	31.8512	1.00313	1.00497
65	32.27	32.1028	31.8567	1.00773	1.00521
66	32.36	32.1302	31.8237	1.00963	1.00715
67	32.42	NA	NA	1.00698	NA
68	32.52	NA	NA	1.00833	NA
69	32.41	NA	NA	1.0125	NA
70	31.87	NA	NA	1.00564	NA
71	31.04	NA	NA	0.995329	NA
72	30.58	NA	NA	0.984118	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 28.53 & NA & NA & 0.983371 & NA \tabularnewline
2 & 28.48 & NA & NA & 0.988383 & NA \tabularnewline
3 & 28.68 & NA & NA & 0.994871 & NA \tabularnewline
4 & 28.89 & NA & NA & 1.00313 & NA \tabularnewline
5 & 29.2 & NA & NA & 1.00773 & NA \tabularnewline
6 & 29.21 & NA & NA & 1.00963 & NA \tabularnewline
7 & 29.15 & 29.1637 & 28.9617 & 1.00698 & 0.999531 \tabularnewline
8 & 29.22 & 29.2293 & 28.9879 & 1.00833 & 0.999682 \tabularnewline
9 & 29.34 & 29.3734 & 29.0108 & 1.0125 & 0.998863 \tabularnewline
10 & 29.13 & 29.1898 & 29.0262 & 1.00564 & 0.997951 \tabularnewline
11 & 28.84 & 28.9006 & 29.0362 & 0.995329 & 0.997902 \tabularnewline
12 & 28.76 & 28.5792 & 29.0404 & 0.984118 & 1.00633 \tabularnewline
13 & 28.75 & 28.5682 & 29.0512 & 0.983371 & 1.00637 \tabularnewline
14 & 28.89 & 28.7331 & 29.0708 & 0.988383 & 1.00546 \tabularnewline
15 & 28.82 & 28.9466 & 29.0958 & 0.994871 & 0.995626 \tabularnewline
16 & 29.12 & 29.2167 & 29.1254 & 1.00313 & 0.996691 \tabularnewline
17 & 29.21 & 29.3971 & 29.1717 & 1.00773 & 0.993635 \tabularnewline
18 & 29.3 & 29.5065 & 29.225 & 1.00963 & 0.993003 \tabularnewline
19 & 29.32 & 29.4779 & 29.2738 & 1.00698 & 0.994642 \tabularnewline
20 & 29.52 & 29.5696 & 29.3254 & 1.00833 & 0.998322 \tabularnewline
21 & 29.64 & 29.7666 & 29.3992 & 1.0125 & 0.995748 \tabularnewline
22 & 29.54 & 29.6558 & 29.4896 & 1.00564 & 0.996096 \tabularnewline
23 & 29.54 & 29.4377 & 29.5758 & 0.995329 & 1.00348 \tabularnewline
24 & 29.34 & 29.1906 & 29.6617 & 0.984118 & 1.00512 \tabularnewline
25 & 29.34 & 29.2528 & 29.7475 & 0.983371 & 1.00298 \tabularnewline
26 & 29.54 & 29.4785 & 29.825 & 0.988383 & 1.00208 \tabularnewline
27 & 29.94 & 29.7342 & 29.8875 & 0.994871 & 1.00692 \tabularnewline
28 & 30.17 & 30.0397 & 29.9458 & 1.00313 & 1.00434 \tabularnewline
29 & 30.23 & 30.223 & 29.9912 & 1.00773 & 1.00023 \tabularnewline
30 & 30.34 & 30.3049 & 30.0158 & 1.00963 & 1.00116 \tabularnewline
31 & 30.34 & 30.2495 & 30.04 & 1.00698 & 1.00299 \tabularnewline
32 & 30.36 & 30.3124 & 30.0621 & 1.00833 & 1.00157 \tabularnewline
33 & 30.3 & 30.4513 & 30.0754 & 1.0125 & 0.995032 \tabularnewline
34 & 30.28 & 30.2566 & 30.0871 & 1.00564 & 1.00077 \tabularnewline
35 & 29.89 & 29.9661 & 30.1067 & 0.995329 & 0.997462 \tabularnewline
36 & 29.58 & 29.6531 & 30.1317 & 0.984118 & 0.997534 \tabularnewline
37 & 29.68 & 29.6556 & 30.1571 & 0.983371 & 1.00082 \tabularnewline
38 & 29.73 & 29.8381 & 30.1888 & 0.988383 & 0.996378 \tabularnewline
39 & 30.07 & 30.0725 & 30.2275 & 0.994871 & 0.999918 \tabularnewline
40 & 30.32 & 30.3523 & 30.2575 & 1.00313 & 0.998936 \tabularnewline
41 & 30.55 & 30.5081 & 30.2742 & 1.00773 & 1.00137 \tabularnewline
42 & 30.62 & 30.5662 & 30.2746 & 1.00963 & 1.00176 \tabularnewline
43 & 30.67 & 30.4677 & 30.2567 & 1.00698 & 1.00664 \tabularnewline
44 & 30.79 & 30.5086 & 30.2567 & 1.00833 & 1.00922 \tabularnewline
45 & 30.8 & 30.6487 & 30.2704 & 1.0125 & 1.00494 \tabularnewline
46 & 30.5 & 30.4477 & 30.2771 & 1.00564 & 1.00172 \tabularnewline
47 & 30.07 & 30.1489 & 30.2904 & 0.995329 & 0.997382 \tabularnewline
48 & 29.41 & 29.8294 & 30.3108 & 0.984118 & 0.985939 \tabularnewline
49 & 29.42 & 29.8277 & 30.3321 & 0.983371 & 0.986332 \tabularnewline
50 & 29.99 & 29.9958 & 30.3483 & 0.988383 & 0.999807 \tabularnewline
51 & 30.14 & 30.2325 & 30.3883 & 0.994871 & 0.996941 \tabularnewline
52 & 30.41 & 30.5588 & 30.4633 & 1.00313 & 0.995131 \tabularnewline
53 & 30.78 & 30.7915 & 30.5554 & 1.00773 & 0.999625 \tabularnewline
54 & 30.88 & 30.973 & 30.6775 & 1.00963 & 0.996999 \tabularnewline
55 & 30.92 & 31.0358 & 30.8208 & 1.00698 & 0.996268 \tabularnewline
56 & 30.93 & 31.2023 & 30.9446 & 1.00833 & 0.991274 \tabularnewline
57 & 31.62 & 31.4473 & 31.0592 & 1.0125 & 1.00549 \tabularnewline
58 & 31.48 & 31.3691 & 31.1933 & 1.00564 & 1.00353 \tabularnewline
59 & 31.3 & 31.1799 & 31.3262 & 0.995329 & 1.00385 \tabularnewline
60 & 31.11 & 30.9505 & 31.45 & 0.984118 & 1.00515 \tabularnewline
61 & 31.16 & 31.0491 & 31.5742 & 0.983371 & 1.00357 \tabularnewline
62 & 31.22 & 31.3346 & 31.7029 & 0.988383 & 0.996341 \tabularnewline
63 & 31.66 & 31.639 & 31.8021 & 0.994871 & 1.00066 \tabularnewline
64 & 32.11 & 31.9511 & 31.8512 & 1.00313 & 1.00497 \tabularnewline
65 & 32.27 & 32.1028 & 31.8567 & 1.00773 & 1.00521 \tabularnewline
66 & 32.36 & 32.1302 & 31.8237 & 1.00963 & 1.00715 \tabularnewline
67 & 32.42 & NA & NA & 1.00698 & NA \tabularnewline
68 & 32.52 & NA & NA & 1.00833 & NA \tabularnewline
69 & 32.41 & NA & NA & 1.0125 & NA \tabularnewline
70 & 31.87 & NA & NA & 1.00564 & NA \tabularnewline
71 & 31.04 & NA & NA & 0.995329 & NA \tabularnewline
72 & 30.58 & NA & NA & 0.984118 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231576&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]28.53[/C][C]NA[/C][C]NA[/C][C]0.983371[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]28.48[/C][C]NA[/C][C]NA[/C][C]0.988383[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]28.68[/C][C]NA[/C][C]NA[/C][C]0.994871[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]28.89[/C][C]NA[/C][C]NA[/C][C]1.00313[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]29.2[/C][C]NA[/C][C]NA[/C][C]1.00773[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]29.21[/C][C]NA[/C][C]NA[/C][C]1.00963[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]29.15[/C][C]29.1637[/C][C]28.9617[/C][C]1.00698[/C][C]0.999531[/C][/ROW]
[ROW][C]8[/C][C]29.22[/C][C]29.2293[/C][C]28.9879[/C][C]1.00833[/C][C]0.999682[/C][/ROW]
[ROW][C]9[/C][C]29.34[/C][C]29.3734[/C][C]29.0108[/C][C]1.0125[/C][C]0.998863[/C][/ROW]
[ROW][C]10[/C][C]29.13[/C][C]29.1898[/C][C]29.0262[/C][C]1.00564[/C][C]0.997951[/C][/ROW]
[ROW][C]11[/C][C]28.84[/C][C]28.9006[/C][C]29.0362[/C][C]0.995329[/C][C]0.997902[/C][/ROW]
[ROW][C]12[/C][C]28.76[/C][C]28.5792[/C][C]29.0404[/C][C]0.984118[/C][C]1.00633[/C][/ROW]
[ROW][C]13[/C][C]28.75[/C][C]28.5682[/C][C]29.0512[/C][C]0.983371[/C][C]1.00637[/C][/ROW]
[ROW][C]14[/C][C]28.89[/C][C]28.7331[/C][C]29.0708[/C][C]0.988383[/C][C]1.00546[/C][/ROW]
[ROW][C]15[/C][C]28.82[/C][C]28.9466[/C][C]29.0958[/C][C]0.994871[/C][C]0.995626[/C][/ROW]
[ROW][C]16[/C][C]29.12[/C][C]29.2167[/C][C]29.1254[/C][C]1.00313[/C][C]0.996691[/C][/ROW]
[ROW][C]17[/C][C]29.21[/C][C]29.3971[/C][C]29.1717[/C][C]1.00773[/C][C]0.993635[/C][/ROW]
[ROW][C]18[/C][C]29.3[/C][C]29.5065[/C][C]29.225[/C][C]1.00963[/C][C]0.993003[/C][/ROW]
[ROW][C]19[/C][C]29.32[/C][C]29.4779[/C][C]29.2738[/C][C]1.00698[/C][C]0.994642[/C][/ROW]
[ROW][C]20[/C][C]29.52[/C][C]29.5696[/C][C]29.3254[/C][C]1.00833[/C][C]0.998322[/C][/ROW]
[ROW][C]21[/C][C]29.64[/C][C]29.7666[/C][C]29.3992[/C][C]1.0125[/C][C]0.995748[/C][/ROW]
[ROW][C]22[/C][C]29.54[/C][C]29.6558[/C][C]29.4896[/C][C]1.00564[/C][C]0.996096[/C][/ROW]
[ROW][C]23[/C][C]29.54[/C][C]29.4377[/C][C]29.5758[/C][C]0.995329[/C][C]1.00348[/C][/ROW]
[ROW][C]24[/C][C]29.34[/C][C]29.1906[/C][C]29.6617[/C][C]0.984118[/C][C]1.00512[/C][/ROW]
[ROW][C]25[/C][C]29.34[/C][C]29.2528[/C][C]29.7475[/C][C]0.983371[/C][C]1.00298[/C][/ROW]
[ROW][C]26[/C][C]29.54[/C][C]29.4785[/C][C]29.825[/C][C]0.988383[/C][C]1.00208[/C][/ROW]
[ROW][C]27[/C][C]29.94[/C][C]29.7342[/C][C]29.8875[/C][C]0.994871[/C][C]1.00692[/C][/ROW]
[ROW][C]28[/C][C]30.17[/C][C]30.0397[/C][C]29.9458[/C][C]1.00313[/C][C]1.00434[/C][/ROW]
[ROW][C]29[/C][C]30.23[/C][C]30.223[/C][C]29.9912[/C][C]1.00773[/C][C]1.00023[/C][/ROW]
[ROW][C]30[/C][C]30.34[/C][C]30.3049[/C][C]30.0158[/C][C]1.00963[/C][C]1.00116[/C][/ROW]
[ROW][C]31[/C][C]30.34[/C][C]30.2495[/C][C]30.04[/C][C]1.00698[/C][C]1.00299[/C][/ROW]
[ROW][C]32[/C][C]30.36[/C][C]30.3124[/C][C]30.0621[/C][C]1.00833[/C][C]1.00157[/C][/ROW]
[ROW][C]33[/C][C]30.3[/C][C]30.4513[/C][C]30.0754[/C][C]1.0125[/C][C]0.995032[/C][/ROW]
[ROW][C]34[/C][C]30.28[/C][C]30.2566[/C][C]30.0871[/C][C]1.00564[/C][C]1.00077[/C][/ROW]
[ROW][C]35[/C][C]29.89[/C][C]29.9661[/C][C]30.1067[/C][C]0.995329[/C][C]0.997462[/C][/ROW]
[ROW][C]36[/C][C]29.58[/C][C]29.6531[/C][C]30.1317[/C][C]0.984118[/C][C]0.997534[/C][/ROW]
[ROW][C]37[/C][C]29.68[/C][C]29.6556[/C][C]30.1571[/C][C]0.983371[/C][C]1.00082[/C][/ROW]
[ROW][C]38[/C][C]29.73[/C][C]29.8381[/C][C]30.1888[/C][C]0.988383[/C][C]0.996378[/C][/ROW]
[ROW][C]39[/C][C]30.07[/C][C]30.0725[/C][C]30.2275[/C][C]0.994871[/C][C]0.999918[/C][/ROW]
[ROW][C]40[/C][C]30.32[/C][C]30.3523[/C][C]30.2575[/C][C]1.00313[/C][C]0.998936[/C][/ROW]
[ROW][C]41[/C][C]30.55[/C][C]30.5081[/C][C]30.2742[/C][C]1.00773[/C][C]1.00137[/C][/ROW]
[ROW][C]42[/C][C]30.62[/C][C]30.5662[/C][C]30.2746[/C][C]1.00963[/C][C]1.00176[/C][/ROW]
[ROW][C]43[/C][C]30.67[/C][C]30.4677[/C][C]30.2567[/C][C]1.00698[/C][C]1.00664[/C][/ROW]
[ROW][C]44[/C][C]30.79[/C][C]30.5086[/C][C]30.2567[/C][C]1.00833[/C][C]1.00922[/C][/ROW]
[ROW][C]45[/C][C]30.8[/C][C]30.6487[/C][C]30.2704[/C][C]1.0125[/C][C]1.00494[/C][/ROW]
[ROW][C]46[/C][C]30.5[/C][C]30.4477[/C][C]30.2771[/C][C]1.00564[/C][C]1.00172[/C][/ROW]
[ROW][C]47[/C][C]30.07[/C][C]30.1489[/C][C]30.2904[/C][C]0.995329[/C][C]0.997382[/C][/ROW]
[ROW][C]48[/C][C]29.41[/C][C]29.8294[/C][C]30.3108[/C][C]0.984118[/C][C]0.985939[/C][/ROW]
[ROW][C]49[/C][C]29.42[/C][C]29.8277[/C][C]30.3321[/C][C]0.983371[/C][C]0.986332[/C][/ROW]
[ROW][C]50[/C][C]29.99[/C][C]29.9958[/C][C]30.3483[/C][C]0.988383[/C][C]0.999807[/C][/ROW]
[ROW][C]51[/C][C]30.14[/C][C]30.2325[/C][C]30.3883[/C][C]0.994871[/C][C]0.996941[/C][/ROW]
[ROW][C]52[/C][C]30.41[/C][C]30.5588[/C][C]30.4633[/C][C]1.00313[/C][C]0.995131[/C][/ROW]
[ROW][C]53[/C][C]30.78[/C][C]30.7915[/C][C]30.5554[/C][C]1.00773[/C][C]0.999625[/C][/ROW]
[ROW][C]54[/C][C]30.88[/C][C]30.973[/C][C]30.6775[/C][C]1.00963[/C][C]0.996999[/C][/ROW]
[ROW][C]55[/C][C]30.92[/C][C]31.0358[/C][C]30.8208[/C][C]1.00698[/C][C]0.996268[/C][/ROW]
[ROW][C]56[/C][C]30.93[/C][C]31.2023[/C][C]30.9446[/C][C]1.00833[/C][C]0.991274[/C][/ROW]
[ROW][C]57[/C][C]31.62[/C][C]31.4473[/C][C]31.0592[/C][C]1.0125[/C][C]1.00549[/C][/ROW]
[ROW][C]58[/C][C]31.48[/C][C]31.3691[/C][C]31.1933[/C][C]1.00564[/C][C]1.00353[/C][/ROW]
[ROW][C]59[/C][C]31.3[/C][C]31.1799[/C][C]31.3262[/C][C]0.995329[/C][C]1.00385[/C][/ROW]
[ROW][C]60[/C][C]31.11[/C][C]30.9505[/C][C]31.45[/C][C]0.984118[/C][C]1.00515[/C][/ROW]
[ROW][C]61[/C][C]31.16[/C][C]31.0491[/C][C]31.5742[/C][C]0.983371[/C][C]1.00357[/C][/ROW]
[ROW][C]62[/C][C]31.22[/C][C]31.3346[/C][C]31.7029[/C][C]0.988383[/C][C]0.996341[/C][/ROW]
[ROW][C]63[/C][C]31.66[/C][C]31.639[/C][C]31.8021[/C][C]0.994871[/C][C]1.00066[/C][/ROW]
[ROW][C]64[/C][C]32.11[/C][C]31.9511[/C][C]31.8512[/C][C]1.00313[/C][C]1.00497[/C][/ROW]
[ROW][C]65[/C][C]32.27[/C][C]32.1028[/C][C]31.8567[/C][C]1.00773[/C][C]1.00521[/C][/ROW]
[ROW][C]66[/C][C]32.36[/C][C]32.1302[/C][C]31.8237[/C][C]1.00963[/C][C]1.00715[/C][/ROW]
[ROW][C]67[/C][C]32.42[/C][C]NA[/C][C]NA[/C][C]1.00698[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]32.52[/C][C]NA[/C][C]NA[/C][C]1.00833[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]32.41[/C][C]NA[/C][C]NA[/C][C]1.0125[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]31.87[/C][C]NA[/C][C]NA[/C][C]1.00564[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]31.04[/C][C]NA[/C][C]NA[/C][C]0.995329[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]30.58[/C][C]NA[/C][C]NA[/C][C]0.984118[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231576&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231576&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	28.53	NA	NA	0.983371	NA
2	28.48	NA	NA	0.988383	NA
3	28.68	NA	NA	0.994871	NA
4	28.89	NA	NA	1.00313	NA
5	29.2	NA	NA	1.00773	NA
6	29.21	NA	NA	1.00963	NA
7	29.15	29.1637	28.9617	1.00698	0.999531
8	29.22	29.2293	28.9879	1.00833	0.999682
9	29.34	29.3734	29.0108	1.0125	0.998863
10	29.13	29.1898	29.0262	1.00564	0.997951
11	28.84	28.9006	29.0362	0.995329	0.997902
12	28.76	28.5792	29.0404	0.984118	1.00633
13	28.75	28.5682	29.0512	0.983371	1.00637
14	28.89	28.7331	29.0708	0.988383	1.00546
15	28.82	28.9466	29.0958	0.994871	0.995626
16	29.12	29.2167	29.1254	1.00313	0.996691
17	29.21	29.3971	29.1717	1.00773	0.993635
18	29.3	29.5065	29.225	1.00963	0.993003
19	29.32	29.4779	29.2738	1.00698	0.994642
20	29.52	29.5696	29.3254	1.00833	0.998322
21	29.64	29.7666	29.3992	1.0125	0.995748
22	29.54	29.6558	29.4896	1.00564	0.996096
23	29.54	29.4377	29.5758	0.995329	1.00348
24	29.34	29.1906	29.6617	0.984118	1.00512
25	29.34	29.2528	29.7475	0.983371	1.00298
26	29.54	29.4785	29.825	0.988383	1.00208
27	29.94	29.7342	29.8875	0.994871	1.00692
28	30.17	30.0397	29.9458	1.00313	1.00434
29	30.23	30.223	29.9912	1.00773	1.00023
30	30.34	30.3049	30.0158	1.00963	1.00116
31	30.34	30.2495	30.04	1.00698	1.00299
32	30.36	30.3124	30.0621	1.00833	1.00157
33	30.3	30.4513	30.0754	1.0125	0.995032
34	30.28	30.2566	30.0871	1.00564	1.00077
35	29.89	29.9661	30.1067	0.995329	0.997462
36	29.58	29.6531	30.1317	0.984118	0.997534
37	29.68	29.6556	30.1571	0.983371	1.00082
38	29.73	29.8381	30.1888	0.988383	0.996378
39	30.07	30.0725	30.2275	0.994871	0.999918
40	30.32	30.3523	30.2575	1.00313	0.998936
41	30.55	30.5081	30.2742	1.00773	1.00137
42	30.62	30.5662	30.2746	1.00963	1.00176
43	30.67	30.4677	30.2567	1.00698	1.00664
44	30.79	30.5086	30.2567	1.00833	1.00922
45	30.8	30.6487	30.2704	1.0125	1.00494
46	30.5	30.4477	30.2771	1.00564	1.00172
47	30.07	30.1489	30.2904	0.995329	0.997382
48	29.41	29.8294	30.3108	0.984118	0.985939
49	29.42	29.8277	30.3321	0.983371	0.986332
50	29.99	29.9958	30.3483	0.988383	0.999807
51	30.14	30.2325	30.3883	0.994871	0.996941
52	30.41	30.5588	30.4633	1.00313	0.995131
53	30.78	30.7915	30.5554	1.00773	0.999625
54	30.88	30.973	30.6775	1.00963	0.996999
55	30.92	31.0358	30.8208	1.00698	0.996268
56	30.93	31.2023	30.9446	1.00833	0.991274
57	31.62	31.4473	31.0592	1.0125	1.00549
58	31.48	31.3691	31.1933	1.00564	1.00353
59	31.3	31.1799	31.3262	0.995329	1.00385
60	31.11	30.9505	31.45	0.984118	1.00515
61	31.16	31.0491	31.5742	0.983371	1.00357
62	31.22	31.3346	31.7029	0.988383	0.996341
63	31.66	31.639	31.8021	0.994871	1.00066
64	32.11	31.9511	31.8512	1.00313	1.00497
65	32.27	32.1028	31.8567	1.00773	1.00521
66	32.36	32.1302	31.8237	1.00963	1.00715
67	32.42	NA	NA	1.00698	NA
68	32.52	NA	NA	1.00833	NA
69	32.41	NA	NA	1.0125	NA
70	31.87	NA	NA	1.00564	NA
71	31.04	NA	NA	0.995329	NA
72	30.58	NA	NA	0.984118	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 <- '12'
par1 <- 'multiplicative'
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