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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 28 Apr 2016 14:48:16 +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/2016/Apr/28/t14618513628fcgd243w1a84x5.htm/, Retrieved Tue, 21 Apr 2026 23:36:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295049, Retrieved Tue, 21 Apr 2026 23:36:15 +0000

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338

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-       [Classical Decomposition] [] [2016-04-28 13:48:16] [b94c13d84d922b33c8d74b1e5b1d38c1] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295049&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295049&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295049&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	83.8	NA	NA	0.558694	NA
2	86.62	NA	NA	0.467111	NA
3	83.98	NA	NA	0.0789444	NA
4	82.59	NA	NA	-0.562556	NA
5	82.3	NA	NA	-0.765389	NA
6	81.64	NA	NA	-1.08389	NA
7	81.66	83.5109	84.1288	-0.617806	-1.85094
8	81.63	84.3569	84.3308	0.0261111	-2.72694
9	85.54	85.2455	84.5454	0.700111	0.294472
10	85.62	85.5669	84.9271	0.639861	0.0530556
11	85.89	85.9	85.3908	0.509194	-0.0100278
12	86.38	85.9613	85.9117	0.0496111	0.418722
13	87.59	87.2674	86.7087	0.558694	0.322556
14	87.68	88.4313	87.9642	0.467111	-0.751278
15	88.07	89.3885	89.3096	0.0789444	-1.31853
16	87.66	90.0524	90.615	-0.562556	-2.39244
17	88.36	91.2446	92.01	-0.765389	-2.88461
18	88.08	92.329	93.4129	-1.08389	-4.24903
19	94.35	94.1226	94.7404	-0.617806	0.227389
20	99.07	96.0182	95.9921	0.0261111	3.05181
21	100.39	97.8747	97.1746	0.700111	2.51531
22	102.1	98.9249	98.285	0.639861	3.17514
23	102.89	99.8484	99.3392	0.509194	3.04164
24	103.05	100.401	100.351	0.0496111	2.64914
25	102.78	101.653	101.094	0.558694	1.12714
26	102.53	101.846	101.379	0.467111	0.684139
27	101.6	101.491	101.412	0.0789444	0.108972
28	100.78	100.735	101.298	-0.562556	0.0450556
29	100.54	100.307	101.072	-0.765389	0.233306
30	100.19	99.7169	100.801	-1.08389	0.473056
31	100.07	99.9934	100.611	-0.617806	0.0765556
32	100.18	100.594	100.567	0.0261111	-0.413611
33	100.08	101.279	100.579	0.700111	-1.19886
34	99.66	101.223	100.583	0.639861	-1.56278
35	99.92	101.07	100.561	0.509194	-1.15044
36	99.51	100.59	100.54	0.0496111	-1.07961
37	101.77	101.054	100.495	0.558694	0.715889
38	102.49	100.88	100.413	0.467111	1.60997
39	101.91	100.392	100.313	0.0789444	1.51814
40	100.57	99.682	100.245	-0.562556	0.887972
41	100.23	99.4254	100.191	-0.765389	0.804556
42	99.99	98.9919	100.076	-1.08389	0.998056
43	99.2	99.2626	99.8804	-0.617806	-0.0626111
44	99.07	99.6311	99.605	0.0261111	-0.561111
45	98.79	100.057	99.3571	0.700111	-1.26719
46	99.31	99.8886	99.2488	0.639861	-0.578611
47	98.98	99.7379	99.2287	0.509194	-0.757944
48	97.69	99.2804	99.2308	0.0496111	-1.59044
49	98.9	99.8224	99.2637	0.558694	-0.922444
50	98.75	99.7709	99.3038	0.467111	-1.02086
51	99.7	99.3989	99.32	0.0789444	0.301056
52	100.18	98.6974	99.26	-0.562556	1.48256
53	100.14	98.3621	99.1275	-0.765389	1.77789
54	100.13	97.9578	99.0417	-1.08389	2.17222
55	99.85	98.3168	98.9346	-0.617806	1.53322
56	99.38	98.8065	98.7804	0.0261111	0.573472
57	98.87	99.2901	98.59	0.700111	-0.420111
58	97.79	98.9532	98.3133	0.639861	-1.16319
59	97.32	98.5196	98.0104	0.509194	-1.19961
60	97.29	97.7642	97.7146	0.0496111	-0.474194
61	96.73	98.0495	97.4908	0.558694	-1.31953
62	97.22	97.8184	97.3512	0.467111	-0.598361
63	96.66	97.346	97.2671	0.0789444	-0.686028
64	96.58	96.6795	97.2421	-0.562556	-0.0995278
65	96.47	96.4775	97.2429	-0.765389	-0.00752778
66	96.7	96.1707	97.2546	-1.08389	0.529306
67	97.91	NA	NA	-0.617806	NA
68	97.97	NA	NA	0.0261111	NA
69	98.26	NA	NA	0.700111	NA
70	97.8	NA	NA	0.639861	NA
71	97.33	NA	NA	0.509194	NA
72	97.56	NA	NA	0.0496111	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 83.8 & NA & NA & 0.558694 & NA \tabularnewline
2 & 86.62 & NA & NA & 0.467111 & NA \tabularnewline
3 & 83.98 & NA & NA & 0.0789444 & NA \tabularnewline
4 & 82.59 & NA & NA & -0.562556 & NA \tabularnewline
5 & 82.3 & NA & NA & -0.765389 & NA \tabularnewline
6 & 81.64 & NA & NA & -1.08389 & NA \tabularnewline
7 & 81.66 & 83.5109 & 84.1288 & -0.617806 & -1.85094 \tabularnewline
8 & 81.63 & 84.3569 & 84.3308 & 0.0261111 & -2.72694 \tabularnewline
9 & 85.54 & 85.2455 & 84.5454 & 0.700111 & 0.294472 \tabularnewline
10 & 85.62 & 85.5669 & 84.9271 & 0.639861 & 0.0530556 \tabularnewline
11 & 85.89 & 85.9 & 85.3908 & 0.509194 & -0.0100278 \tabularnewline
12 & 86.38 & 85.9613 & 85.9117 & 0.0496111 & 0.418722 \tabularnewline
13 & 87.59 & 87.2674 & 86.7087 & 0.558694 & 0.322556 \tabularnewline
14 & 87.68 & 88.4313 & 87.9642 & 0.467111 & -0.751278 \tabularnewline
15 & 88.07 & 89.3885 & 89.3096 & 0.0789444 & -1.31853 \tabularnewline
16 & 87.66 & 90.0524 & 90.615 & -0.562556 & -2.39244 \tabularnewline
17 & 88.36 & 91.2446 & 92.01 & -0.765389 & -2.88461 \tabularnewline
18 & 88.08 & 92.329 & 93.4129 & -1.08389 & -4.24903 \tabularnewline
19 & 94.35 & 94.1226 & 94.7404 & -0.617806 & 0.227389 \tabularnewline
20 & 99.07 & 96.0182 & 95.9921 & 0.0261111 & 3.05181 \tabularnewline
21 & 100.39 & 97.8747 & 97.1746 & 0.700111 & 2.51531 \tabularnewline
22 & 102.1 & 98.9249 & 98.285 & 0.639861 & 3.17514 \tabularnewline
23 & 102.89 & 99.8484 & 99.3392 & 0.509194 & 3.04164 \tabularnewline
24 & 103.05 & 100.401 & 100.351 & 0.0496111 & 2.64914 \tabularnewline
25 & 102.78 & 101.653 & 101.094 & 0.558694 & 1.12714 \tabularnewline
26 & 102.53 & 101.846 & 101.379 & 0.467111 & 0.684139 \tabularnewline
27 & 101.6 & 101.491 & 101.412 & 0.0789444 & 0.108972 \tabularnewline
28 & 100.78 & 100.735 & 101.298 & -0.562556 & 0.0450556 \tabularnewline
29 & 100.54 & 100.307 & 101.072 & -0.765389 & 0.233306 \tabularnewline
30 & 100.19 & 99.7169 & 100.801 & -1.08389 & 0.473056 \tabularnewline
31 & 100.07 & 99.9934 & 100.611 & -0.617806 & 0.0765556 \tabularnewline
32 & 100.18 & 100.594 & 100.567 & 0.0261111 & -0.413611 \tabularnewline
33 & 100.08 & 101.279 & 100.579 & 0.700111 & -1.19886 \tabularnewline
34 & 99.66 & 101.223 & 100.583 & 0.639861 & -1.56278 \tabularnewline
35 & 99.92 & 101.07 & 100.561 & 0.509194 & -1.15044 \tabularnewline
36 & 99.51 & 100.59 & 100.54 & 0.0496111 & -1.07961 \tabularnewline
37 & 101.77 & 101.054 & 100.495 & 0.558694 & 0.715889 \tabularnewline
38 & 102.49 & 100.88 & 100.413 & 0.467111 & 1.60997 \tabularnewline
39 & 101.91 & 100.392 & 100.313 & 0.0789444 & 1.51814 \tabularnewline
40 & 100.57 & 99.682 & 100.245 & -0.562556 & 0.887972 \tabularnewline
41 & 100.23 & 99.4254 & 100.191 & -0.765389 & 0.804556 \tabularnewline
42 & 99.99 & 98.9919 & 100.076 & -1.08389 & 0.998056 \tabularnewline
43 & 99.2 & 99.2626 & 99.8804 & -0.617806 & -0.0626111 \tabularnewline
44 & 99.07 & 99.6311 & 99.605 & 0.0261111 & -0.561111 \tabularnewline
45 & 98.79 & 100.057 & 99.3571 & 0.700111 & -1.26719 \tabularnewline
46 & 99.31 & 99.8886 & 99.2488 & 0.639861 & -0.578611 \tabularnewline
47 & 98.98 & 99.7379 & 99.2287 & 0.509194 & -0.757944 \tabularnewline
48 & 97.69 & 99.2804 & 99.2308 & 0.0496111 & -1.59044 \tabularnewline
49 & 98.9 & 99.8224 & 99.2637 & 0.558694 & -0.922444 \tabularnewline
50 & 98.75 & 99.7709 & 99.3038 & 0.467111 & -1.02086 \tabularnewline
51 & 99.7 & 99.3989 & 99.32 & 0.0789444 & 0.301056 \tabularnewline
52 & 100.18 & 98.6974 & 99.26 & -0.562556 & 1.48256 \tabularnewline
53 & 100.14 & 98.3621 & 99.1275 & -0.765389 & 1.77789 \tabularnewline
54 & 100.13 & 97.9578 & 99.0417 & -1.08389 & 2.17222 \tabularnewline
55 & 99.85 & 98.3168 & 98.9346 & -0.617806 & 1.53322 \tabularnewline
56 & 99.38 & 98.8065 & 98.7804 & 0.0261111 & 0.573472 \tabularnewline
57 & 98.87 & 99.2901 & 98.59 & 0.700111 & -0.420111 \tabularnewline
58 & 97.79 & 98.9532 & 98.3133 & 0.639861 & -1.16319 \tabularnewline
59 & 97.32 & 98.5196 & 98.0104 & 0.509194 & -1.19961 \tabularnewline
60 & 97.29 & 97.7642 & 97.7146 & 0.0496111 & -0.474194 \tabularnewline
61 & 96.73 & 98.0495 & 97.4908 & 0.558694 & -1.31953 \tabularnewline
62 & 97.22 & 97.8184 & 97.3512 & 0.467111 & -0.598361 \tabularnewline
63 & 96.66 & 97.346 & 97.2671 & 0.0789444 & -0.686028 \tabularnewline
64 & 96.58 & 96.6795 & 97.2421 & -0.562556 & -0.0995278 \tabularnewline
65 & 96.47 & 96.4775 & 97.2429 & -0.765389 & -0.00752778 \tabularnewline
66 & 96.7 & 96.1707 & 97.2546 & -1.08389 & 0.529306 \tabularnewline
67 & 97.91 & NA & NA & -0.617806 & NA \tabularnewline
68 & 97.97 & NA & NA & 0.0261111 & NA \tabularnewline
69 & 98.26 & NA & NA & 0.700111 & NA \tabularnewline
70 & 97.8 & NA & NA & 0.639861 & NA \tabularnewline
71 & 97.33 & NA & NA & 0.509194 & NA \tabularnewline
72 & 97.56 & NA & NA & 0.0496111 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295049&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]83.8[/C][C]NA[/C][C]NA[/C][C]0.558694[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]86.62[/C][C]NA[/C][C]NA[/C][C]0.467111[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]83.98[/C][C]NA[/C][C]NA[/C][C]0.0789444[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]82.59[/C][C]NA[/C][C]NA[/C][C]-0.562556[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]82.3[/C][C]NA[/C][C]NA[/C][C]-0.765389[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]81.64[/C][C]NA[/C][C]NA[/C][C]-1.08389[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]81.66[/C][C]83.5109[/C][C]84.1288[/C][C]-0.617806[/C][C]-1.85094[/C][/ROW]
[ROW][C]8[/C][C]81.63[/C][C]84.3569[/C][C]84.3308[/C][C]0.0261111[/C][C]-2.72694[/C][/ROW]
[ROW][C]9[/C][C]85.54[/C][C]85.2455[/C][C]84.5454[/C][C]0.700111[/C][C]0.294472[/C][/ROW]
[ROW][C]10[/C][C]85.62[/C][C]85.5669[/C][C]84.9271[/C][C]0.639861[/C][C]0.0530556[/C][/ROW]
[ROW][C]11[/C][C]85.89[/C][C]85.9[/C][C]85.3908[/C][C]0.509194[/C][C]-0.0100278[/C][/ROW]
[ROW][C]12[/C][C]86.38[/C][C]85.9613[/C][C]85.9117[/C][C]0.0496111[/C][C]0.418722[/C][/ROW]
[ROW][C]13[/C][C]87.59[/C][C]87.2674[/C][C]86.7087[/C][C]0.558694[/C][C]0.322556[/C][/ROW]
[ROW][C]14[/C][C]87.68[/C][C]88.4313[/C][C]87.9642[/C][C]0.467111[/C][C]-0.751278[/C][/ROW]
[ROW][C]15[/C][C]88.07[/C][C]89.3885[/C][C]89.3096[/C][C]0.0789444[/C][C]-1.31853[/C][/ROW]
[ROW][C]16[/C][C]87.66[/C][C]90.0524[/C][C]90.615[/C][C]-0.562556[/C][C]-2.39244[/C][/ROW]
[ROW][C]17[/C][C]88.36[/C][C]91.2446[/C][C]92.01[/C][C]-0.765389[/C][C]-2.88461[/C][/ROW]
[ROW][C]18[/C][C]88.08[/C][C]92.329[/C][C]93.4129[/C][C]-1.08389[/C][C]-4.24903[/C][/ROW]
[ROW][C]19[/C][C]94.35[/C][C]94.1226[/C][C]94.7404[/C][C]-0.617806[/C][C]0.227389[/C][/ROW]
[ROW][C]20[/C][C]99.07[/C][C]96.0182[/C][C]95.9921[/C][C]0.0261111[/C][C]3.05181[/C][/ROW]
[ROW][C]21[/C][C]100.39[/C][C]97.8747[/C][C]97.1746[/C][C]0.700111[/C][C]2.51531[/C][/ROW]
[ROW][C]22[/C][C]102.1[/C][C]98.9249[/C][C]98.285[/C][C]0.639861[/C][C]3.17514[/C][/ROW]
[ROW][C]23[/C][C]102.89[/C][C]99.8484[/C][C]99.3392[/C][C]0.509194[/C][C]3.04164[/C][/ROW]
[ROW][C]24[/C][C]103.05[/C][C]100.401[/C][C]100.351[/C][C]0.0496111[/C][C]2.64914[/C][/ROW]
[ROW][C]25[/C][C]102.78[/C][C]101.653[/C][C]101.094[/C][C]0.558694[/C][C]1.12714[/C][/ROW]
[ROW][C]26[/C][C]102.53[/C][C]101.846[/C][C]101.379[/C][C]0.467111[/C][C]0.684139[/C][/ROW]
[ROW][C]27[/C][C]101.6[/C][C]101.491[/C][C]101.412[/C][C]0.0789444[/C][C]0.108972[/C][/ROW]
[ROW][C]28[/C][C]100.78[/C][C]100.735[/C][C]101.298[/C][C]-0.562556[/C][C]0.0450556[/C][/ROW]
[ROW][C]29[/C][C]100.54[/C][C]100.307[/C][C]101.072[/C][C]-0.765389[/C][C]0.233306[/C][/ROW]
[ROW][C]30[/C][C]100.19[/C][C]99.7169[/C][C]100.801[/C][C]-1.08389[/C][C]0.473056[/C][/ROW]
[ROW][C]31[/C][C]100.07[/C][C]99.9934[/C][C]100.611[/C][C]-0.617806[/C][C]0.0765556[/C][/ROW]
[ROW][C]32[/C][C]100.18[/C][C]100.594[/C][C]100.567[/C][C]0.0261111[/C][C]-0.413611[/C][/ROW]
[ROW][C]33[/C][C]100.08[/C][C]101.279[/C][C]100.579[/C][C]0.700111[/C][C]-1.19886[/C][/ROW]
[ROW][C]34[/C][C]99.66[/C][C]101.223[/C][C]100.583[/C][C]0.639861[/C][C]-1.56278[/C][/ROW]
[ROW][C]35[/C][C]99.92[/C][C]101.07[/C][C]100.561[/C][C]0.509194[/C][C]-1.15044[/C][/ROW]
[ROW][C]36[/C][C]99.51[/C][C]100.59[/C][C]100.54[/C][C]0.0496111[/C][C]-1.07961[/C][/ROW]
[ROW][C]37[/C][C]101.77[/C][C]101.054[/C][C]100.495[/C][C]0.558694[/C][C]0.715889[/C][/ROW]
[ROW][C]38[/C][C]102.49[/C][C]100.88[/C][C]100.413[/C][C]0.467111[/C][C]1.60997[/C][/ROW]
[ROW][C]39[/C][C]101.91[/C][C]100.392[/C][C]100.313[/C][C]0.0789444[/C][C]1.51814[/C][/ROW]
[ROW][C]40[/C][C]100.57[/C][C]99.682[/C][C]100.245[/C][C]-0.562556[/C][C]0.887972[/C][/ROW]
[ROW][C]41[/C][C]100.23[/C][C]99.4254[/C][C]100.191[/C][C]-0.765389[/C][C]0.804556[/C][/ROW]
[ROW][C]42[/C][C]99.99[/C][C]98.9919[/C][C]100.076[/C][C]-1.08389[/C][C]0.998056[/C][/ROW]
[ROW][C]43[/C][C]99.2[/C][C]99.2626[/C][C]99.8804[/C][C]-0.617806[/C][C]-0.0626111[/C][/ROW]
[ROW][C]44[/C][C]99.07[/C][C]99.6311[/C][C]99.605[/C][C]0.0261111[/C][C]-0.561111[/C][/ROW]
[ROW][C]45[/C][C]98.79[/C][C]100.057[/C][C]99.3571[/C][C]0.700111[/C][C]-1.26719[/C][/ROW]
[ROW][C]46[/C][C]99.31[/C][C]99.8886[/C][C]99.2488[/C][C]0.639861[/C][C]-0.578611[/C][/ROW]
[ROW][C]47[/C][C]98.98[/C][C]99.7379[/C][C]99.2287[/C][C]0.509194[/C][C]-0.757944[/C][/ROW]
[ROW][C]48[/C][C]97.69[/C][C]99.2804[/C][C]99.2308[/C][C]0.0496111[/C][C]-1.59044[/C][/ROW]
[ROW][C]49[/C][C]98.9[/C][C]99.8224[/C][C]99.2637[/C][C]0.558694[/C][C]-0.922444[/C][/ROW]
[ROW][C]50[/C][C]98.75[/C][C]99.7709[/C][C]99.3038[/C][C]0.467111[/C][C]-1.02086[/C][/ROW]
[ROW][C]51[/C][C]99.7[/C][C]99.3989[/C][C]99.32[/C][C]0.0789444[/C][C]0.301056[/C][/ROW]
[ROW][C]52[/C][C]100.18[/C][C]98.6974[/C][C]99.26[/C][C]-0.562556[/C][C]1.48256[/C][/ROW]
[ROW][C]53[/C][C]100.14[/C][C]98.3621[/C][C]99.1275[/C][C]-0.765389[/C][C]1.77789[/C][/ROW]
[ROW][C]54[/C][C]100.13[/C][C]97.9578[/C][C]99.0417[/C][C]-1.08389[/C][C]2.17222[/C][/ROW]
[ROW][C]55[/C][C]99.85[/C][C]98.3168[/C][C]98.9346[/C][C]-0.617806[/C][C]1.53322[/C][/ROW]
[ROW][C]56[/C][C]99.38[/C][C]98.8065[/C][C]98.7804[/C][C]0.0261111[/C][C]0.573472[/C][/ROW]
[ROW][C]57[/C][C]98.87[/C][C]99.2901[/C][C]98.59[/C][C]0.700111[/C][C]-0.420111[/C][/ROW]
[ROW][C]58[/C][C]97.79[/C][C]98.9532[/C][C]98.3133[/C][C]0.639861[/C][C]-1.16319[/C][/ROW]
[ROW][C]59[/C][C]97.32[/C][C]98.5196[/C][C]98.0104[/C][C]0.509194[/C][C]-1.19961[/C][/ROW]
[ROW][C]60[/C][C]97.29[/C][C]97.7642[/C][C]97.7146[/C][C]0.0496111[/C][C]-0.474194[/C][/ROW]
[ROW][C]61[/C][C]96.73[/C][C]98.0495[/C][C]97.4908[/C][C]0.558694[/C][C]-1.31953[/C][/ROW]
[ROW][C]62[/C][C]97.22[/C][C]97.8184[/C][C]97.3512[/C][C]0.467111[/C][C]-0.598361[/C][/ROW]
[ROW][C]63[/C][C]96.66[/C][C]97.346[/C][C]97.2671[/C][C]0.0789444[/C][C]-0.686028[/C][/ROW]
[ROW][C]64[/C][C]96.58[/C][C]96.6795[/C][C]97.2421[/C][C]-0.562556[/C][C]-0.0995278[/C][/ROW]
[ROW][C]65[/C][C]96.47[/C][C]96.4775[/C][C]97.2429[/C][C]-0.765389[/C][C]-0.00752778[/C][/ROW]
[ROW][C]66[/C][C]96.7[/C][C]96.1707[/C][C]97.2546[/C][C]-1.08389[/C][C]0.529306[/C][/ROW]
[ROW][C]67[/C][C]97.91[/C][C]NA[/C][C]NA[/C][C]-0.617806[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]97.97[/C][C]NA[/C][C]NA[/C][C]0.0261111[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]98.26[/C][C]NA[/C][C]NA[/C][C]0.700111[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]97.8[/C][C]NA[/C][C]NA[/C][C]0.639861[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]97.33[/C][C]NA[/C][C]NA[/C][C]0.509194[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]97.56[/C][C]NA[/C][C]NA[/C][C]0.0496111[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295049&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295049&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	83.8	NA	NA	0.558694	NA
2	86.62	NA	NA	0.467111	NA
3	83.98	NA	NA	0.0789444	NA
4	82.59	NA	NA	-0.562556	NA
5	82.3	NA	NA	-0.765389	NA
6	81.64	NA	NA	-1.08389	NA
7	81.66	83.5109	84.1288	-0.617806	-1.85094
8	81.63	84.3569	84.3308	0.0261111	-2.72694
9	85.54	85.2455	84.5454	0.700111	0.294472
10	85.62	85.5669	84.9271	0.639861	0.0530556
11	85.89	85.9	85.3908	0.509194	-0.0100278
12	86.38	85.9613	85.9117	0.0496111	0.418722
13	87.59	87.2674	86.7087	0.558694	0.322556
14	87.68	88.4313	87.9642	0.467111	-0.751278
15	88.07	89.3885	89.3096	0.0789444	-1.31853
16	87.66	90.0524	90.615	-0.562556	-2.39244
17	88.36	91.2446	92.01	-0.765389	-2.88461
18	88.08	92.329	93.4129	-1.08389	-4.24903
19	94.35	94.1226	94.7404	-0.617806	0.227389
20	99.07	96.0182	95.9921	0.0261111	3.05181
21	100.39	97.8747	97.1746	0.700111	2.51531
22	102.1	98.9249	98.285	0.639861	3.17514
23	102.89	99.8484	99.3392	0.509194	3.04164
24	103.05	100.401	100.351	0.0496111	2.64914
25	102.78	101.653	101.094	0.558694	1.12714
26	102.53	101.846	101.379	0.467111	0.684139
27	101.6	101.491	101.412	0.0789444	0.108972
28	100.78	100.735	101.298	-0.562556	0.0450556
29	100.54	100.307	101.072	-0.765389	0.233306
30	100.19	99.7169	100.801	-1.08389	0.473056
31	100.07	99.9934	100.611	-0.617806	0.0765556
32	100.18	100.594	100.567	0.0261111	-0.413611
33	100.08	101.279	100.579	0.700111	-1.19886
34	99.66	101.223	100.583	0.639861	-1.56278
35	99.92	101.07	100.561	0.509194	-1.15044
36	99.51	100.59	100.54	0.0496111	-1.07961
37	101.77	101.054	100.495	0.558694	0.715889
38	102.49	100.88	100.413	0.467111	1.60997
39	101.91	100.392	100.313	0.0789444	1.51814
40	100.57	99.682	100.245	-0.562556	0.887972
41	100.23	99.4254	100.191	-0.765389	0.804556
42	99.99	98.9919	100.076	-1.08389	0.998056
43	99.2	99.2626	99.8804	-0.617806	-0.0626111
44	99.07	99.6311	99.605	0.0261111	-0.561111
45	98.79	100.057	99.3571	0.700111	-1.26719
46	99.31	99.8886	99.2488	0.639861	-0.578611
47	98.98	99.7379	99.2287	0.509194	-0.757944
48	97.69	99.2804	99.2308	0.0496111	-1.59044
49	98.9	99.8224	99.2637	0.558694	-0.922444
50	98.75	99.7709	99.3038	0.467111	-1.02086
51	99.7	99.3989	99.32	0.0789444	0.301056
52	100.18	98.6974	99.26	-0.562556	1.48256
53	100.14	98.3621	99.1275	-0.765389	1.77789
54	100.13	97.9578	99.0417	-1.08389	2.17222
55	99.85	98.3168	98.9346	-0.617806	1.53322
56	99.38	98.8065	98.7804	0.0261111	0.573472
57	98.87	99.2901	98.59	0.700111	-0.420111
58	97.79	98.9532	98.3133	0.639861	-1.16319
59	97.32	98.5196	98.0104	0.509194	-1.19961
60	97.29	97.7642	97.7146	0.0496111	-0.474194
61	96.73	98.0495	97.4908	0.558694	-1.31953
62	97.22	97.8184	97.3512	0.467111	-0.598361
63	96.66	97.346	97.2671	0.0789444	-0.686028
64	96.58	96.6795	97.2421	-0.562556	-0.0995278
65	96.47	96.4775	97.2429	-0.765389	-0.00752778
66	96.7	96.1707	97.2546	-1.08389	0.529306
67	97.91	NA	NA	-0.617806	NA
68	97.97	NA	NA	0.0261111	NA
69	98.26	NA	NA	0.700111	NA
70	97.8	NA	NA	0.639861	NA
71	97.33	NA	NA	0.509194	NA
72	97.56	NA	NA	0.0496111	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 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; 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