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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 28 Nov 2015 11:10:59 +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/2015/Nov/28/t1448709094q0ve1oit96fzb91.htm/, Retrieved Tue, 10 Feb 2026 02:27:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284368, Retrieved Tue, 10 Feb 2026 02:27:12 +0000

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318

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-       [Classical Decomposition] [] [2015-11-28 11:10:59] [5a70237751c59f15349851dd3eb2a645] [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	'Sir Maurice George Kendall' @ kendall.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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284368&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284368&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284368&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	92.51	NA	NA	0.345292	NA
2	92.51	NA	NA	0.199625	NA
3	92.51	NA	NA	0.0539583	NA
4	92.51	NA	NA	-0.067875	NA
5	92.51	NA	NA	-0.165875	NA
6	92.51	NA	NA	-0.263875	NA
7	92.51	93.1946	93.7233	-0.528708	-0.684625
8	92.51	93.3956	94.07	-0.674375	-0.885625
9	92.51	93.5966	94.4167	-0.820042	-1.08662
10	96.67	95.5496	94.7633	0.786292	1.12038
11	96.67	95.7506	95.11	0.640625	0.919375
12	96.67	95.9516	95.4567	0.494958	0.718375
13	96.67	96.1486	95.8033	0.345292	0.521375
14	96.67	96.3496	96.15	0.199625	0.320375
15	96.67	96.5506	96.4967	0.0539583	0.119375
16	96.67	96.5821	96.65	-0.067875	0.087875
17	96.67	96.4441	96.61	-0.165875	0.225875
18	96.67	96.3061	96.57	-0.263875	0.363875
19	96.67	96.0013	96.53	-0.528708	0.668708
20	96.67	95.8156	96.49	-0.674375	0.854375
21	96.67	95.63	96.45	-0.820042	1.04004
22	96.19	97.1963	96.41	0.786292	-1.00629
23	96.19	97.0106	96.37	0.640625	-0.820625
24	96.19	96.825	96.33	0.494958	-0.634958
25	96.19	96.6353	96.29	0.345292	-0.445292
26	96.19	96.4496	96.25	0.199625	-0.259625
27	96.19	96.264	96.21	0.0539583	-0.0739583
28	96.19	96.2446	96.3125	-0.067875	-0.054625
29	96.19	96.3916	96.5575	-0.165875	-0.201625
30	96.19	96.5386	96.8025	-0.263875	-0.348625
31	96.19	96.5188	97.0475	-0.528708	-0.328792
32	96.19	96.6181	97.2925	-0.674375	-0.428125
33	96.19	96.7175	97.5375	-0.820042	-0.527458
34	99.13	98.5688	97.7825	0.786292	0.561208
35	99.13	98.6681	98.0275	0.640625	0.461875
36	99.13	98.7675	98.2725	0.494958	0.362542
37	99.13	98.8628	98.5175	0.345292	0.267208
38	99.13	98.9621	98.7625	0.199625	0.167875
39	99.13	99.0615	99.0075	0.0539583	0.0685417
40	99.13	99.0809	99.1487	-0.067875	0.049125
41	99.13	99.0204	99.1862	-0.165875	0.109625
42	99.13	98.9599	99.2238	-0.263875	0.170125
43	99.13	98.7325	99.2612	-0.528708	0.397458
44	99.13	98.6244	99.2988	-0.674375	0.505625
45	99.13	98.5162	99.3362	-0.820042	0.613792
46	99.58	100.16	99.3738	0.786292	-0.580042
47	99.58	100.052	99.4112	0.640625	-0.471875
48	99.58	99.9437	99.4488	0.494958	-0.363708
49	99.58	99.8315	99.4862	0.345292	-0.251542
50	99.58	99.7234	99.5237	0.199625	-0.143375
51	99.58	99.6152	99.5612	0.0539583	-0.0352083
52	99.58	99.5825	99.6504	-0.067875	-0.00254167
53	99.58	99.6254	99.7912	-0.165875	-0.045375
54	99.58	99.6682	99.9321	-0.263875	-0.0882083
55	99.58	99.5434	100.072	-0.528708	0.036625
56	99.58	99.5369	100.211	-0.674375	0.043125
57	99.58	99.5304	100.35	-0.820042	0.049625
58	101.27	101.276	100.49	0.786292	-0.005875
59	101.27	101.269	100.629	0.640625	0.000625
60	101.27	101.263	100.768	0.494958	0.007125
61	101.25	101.252	100.907	0.345292	-0.002375
62	101.25	101.246	101.046	0.199625	0.004125
63	101.25	101.239	101.185	0.0539583	0.010625
64	101.25	101.24	101.308	-0.067875	0.00954167
65	101.25	101.249	101.415	-0.165875	0.000875
66	101.25	101.258	101.522	-0.263875	-0.00779167
67	101.25	NA	NA	-0.528708	NA
68	101.25	NA	NA	-0.674375	NA
69	101.25	NA	NA	-0.820042	NA
70	102.55	NA	NA	0.786292	NA
71	102.55	NA	NA	0.640625	NA
72	102.55	NA	NA	0.494958	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 92.51 & NA & NA & 0.345292 & NA \tabularnewline
2 & 92.51 & NA & NA & 0.199625 & NA \tabularnewline
3 & 92.51 & NA & NA & 0.0539583 & NA \tabularnewline
4 & 92.51 & NA & NA & -0.067875 & NA \tabularnewline
5 & 92.51 & NA & NA & -0.165875 & NA \tabularnewline
6 & 92.51 & NA & NA & -0.263875 & NA \tabularnewline
7 & 92.51 & 93.1946 & 93.7233 & -0.528708 & -0.684625 \tabularnewline
8 & 92.51 & 93.3956 & 94.07 & -0.674375 & -0.885625 \tabularnewline
9 & 92.51 & 93.5966 & 94.4167 & -0.820042 & -1.08662 \tabularnewline
10 & 96.67 & 95.5496 & 94.7633 & 0.786292 & 1.12038 \tabularnewline
11 & 96.67 & 95.7506 & 95.11 & 0.640625 & 0.919375 \tabularnewline
12 & 96.67 & 95.9516 & 95.4567 & 0.494958 & 0.718375 \tabularnewline
13 & 96.67 & 96.1486 & 95.8033 & 0.345292 & 0.521375 \tabularnewline
14 & 96.67 & 96.3496 & 96.15 & 0.199625 & 0.320375 \tabularnewline
15 & 96.67 & 96.5506 & 96.4967 & 0.0539583 & 0.119375 \tabularnewline
16 & 96.67 & 96.5821 & 96.65 & -0.067875 & 0.087875 \tabularnewline
17 & 96.67 & 96.4441 & 96.61 & -0.165875 & 0.225875 \tabularnewline
18 & 96.67 & 96.3061 & 96.57 & -0.263875 & 0.363875 \tabularnewline
19 & 96.67 & 96.0013 & 96.53 & -0.528708 & 0.668708 \tabularnewline
20 & 96.67 & 95.8156 & 96.49 & -0.674375 & 0.854375 \tabularnewline
21 & 96.67 & 95.63 & 96.45 & -0.820042 & 1.04004 \tabularnewline
22 & 96.19 & 97.1963 & 96.41 & 0.786292 & -1.00629 \tabularnewline
23 & 96.19 & 97.0106 & 96.37 & 0.640625 & -0.820625 \tabularnewline
24 & 96.19 & 96.825 & 96.33 & 0.494958 & -0.634958 \tabularnewline
25 & 96.19 & 96.6353 & 96.29 & 0.345292 & -0.445292 \tabularnewline
26 & 96.19 & 96.4496 & 96.25 & 0.199625 & -0.259625 \tabularnewline
27 & 96.19 & 96.264 & 96.21 & 0.0539583 & -0.0739583 \tabularnewline
28 & 96.19 & 96.2446 & 96.3125 & -0.067875 & -0.054625 \tabularnewline
29 & 96.19 & 96.3916 & 96.5575 & -0.165875 & -0.201625 \tabularnewline
30 & 96.19 & 96.5386 & 96.8025 & -0.263875 & -0.348625 \tabularnewline
31 & 96.19 & 96.5188 & 97.0475 & -0.528708 & -0.328792 \tabularnewline
32 & 96.19 & 96.6181 & 97.2925 & -0.674375 & -0.428125 \tabularnewline
33 & 96.19 & 96.7175 & 97.5375 & -0.820042 & -0.527458 \tabularnewline
34 & 99.13 & 98.5688 & 97.7825 & 0.786292 & 0.561208 \tabularnewline
35 & 99.13 & 98.6681 & 98.0275 & 0.640625 & 0.461875 \tabularnewline
36 & 99.13 & 98.7675 & 98.2725 & 0.494958 & 0.362542 \tabularnewline
37 & 99.13 & 98.8628 & 98.5175 & 0.345292 & 0.267208 \tabularnewline
38 & 99.13 & 98.9621 & 98.7625 & 0.199625 & 0.167875 \tabularnewline
39 & 99.13 & 99.0615 & 99.0075 & 0.0539583 & 0.0685417 \tabularnewline
40 & 99.13 & 99.0809 & 99.1487 & -0.067875 & 0.049125 \tabularnewline
41 & 99.13 & 99.0204 & 99.1862 & -0.165875 & 0.109625 \tabularnewline
42 & 99.13 & 98.9599 & 99.2238 & -0.263875 & 0.170125 \tabularnewline
43 & 99.13 & 98.7325 & 99.2612 & -0.528708 & 0.397458 \tabularnewline
44 & 99.13 & 98.6244 & 99.2988 & -0.674375 & 0.505625 \tabularnewline
45 & 99.13 & 98.5162 & 99.3362 & -0.820042 & 0.613792 \tabularnewline
46 & 99.58 & 100.16 & 99.3738 & 0.786292 & -0.580042 \tabularnewline
47 & 99.58 & 100.052 & 99.4112 & 0.640625 & -0.471875 \tabularnewline
48 & 99.58 & 99.9437 & 99.4488 & 0.494958 & -0.363708 \tabularnewline
49 & 99.58 & 99.8315 & 99.4862 & 0.345292 & -0.251542 \tabularnewline
50 & 99.58 & 99.7234 & 99.5237 & 0.199625 & -0.143375 \tabularnewline
51 & 99.58 & 99.6152 & 99.5612 & 0.0539583 & -0.0352083 \tabularnewline
52 & 99.58 & 99.5825 & 99.6504 & -0.067875 & -0.00254167 \tabularnewline
53 & 99.58 & 99.6254 & 99.7912 & -0.165875 & -0.045375 \tabularnewline
54 & 99.58 & 99.6682 & 99.9321 & -0.263875 & -0.0882083 \tabularnewline
55 & 99.58 & 99.5434 & 100.072 & -0.528708 & 0.036625 \tabularnewline
56 & 99.58 & 99.5369 & 100.211 & -0.674375 & 0.043125 \tabularnewline
57 & 99.58 & 99.5304 & 100.35 & -0.820042 & 0.049625 \tabularnewline
58 & 101.27 & 101.276 & 100.49 & 0.786292 & -0.005875 \tabularnewline
59 & 101.27 & 101.269 & 100.629 & 0.640625 & 0.000625 \tabularnewline
60 & 101.27 & 101.263 & 100.768 & 0.494958 & 0.007125 \tabularnewline
61 & 101.25 & 101.252 & 100.907 & 0.345292 & -0.002375 \tabularnewline
62 & 101.25 & 101.246 & 101.046 & 0.199625 & 0.004125 \tabularnewline
63 & 101.25 & 101.239 & 101.185 & 0.0539583 & 0.010625 \tabularnewline
64 & 101.25 & 101.24 & 101.308 & -0.067875 & 0.00954167 \tabularnewline
65 & 101.25 & 101.249 & 101.415 & -0.165875 & 0.000875 \tabularnewline
66 & 101.25 & 101.258 & 101.522 & -0.263875 & -0.00779167 \tabularnewline
67 & 101.25 & NA & NA & -0.528708 & NA \tabularnewline
68 & 101.25 & NA & NA & -0.674375 & NA \tabularnewline
69 & 101.25 & NA & NA & -0.820042 & NA \tabularnewline
70 & 102.55 & NA & NA & 0.786292 & NA \tabularnewline
71 & 102.55 & NA & NA & 0.640625 & NA \tabularnewline
72 & 102.55 & NA & NA & 0.494958 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284368&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]92.51[/C][C]NA[/C][C]NA[/C][C]0.345292[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]92.51[/C][C]NA[/C][C]NA[/C][C]0.199625[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]92.51[/C][C]NA[/C][C]NA[/C][C]0.0539583[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]92.51[/C][C]NA[/C][C]NA[/C][C]-0.067875[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]92.51[/C][C]NA[/C][C]NA[/C][C]-0.165875[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]92.51[/C][C]NA[/C][C]NA[/C][C]-0.263875[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]92.51[/C][C]93.1946[/C][C]93.7233[/C][C]-0.528708[/C][C]-0.684625[/C][/ROW]
[ROW][C]8[/C][C]92.51[/C][C]93.3956[/C][C]94.07[/C][C]-0.674375[/C][C]-0.885625[/C][/ROW]
[ROW][C]9[/C][C]92.51[/C][C]93.5966[/C][C]94.4167[/C][C]-0.820042[/C][C]-1.08662[/C][/ROW]
[ROW][C]10[/C][C]96.67[/C][C]95.5496[/C][C]94.7633[/C][C]0.786292[/C][C]1.12038[/C][/ROW]
[ROW][C]11[/C][C]96.67[/C][C]95.7506[/C][C]95.11[/C][C]0.640625[/C][C]0.919375[/C][/ROW]
[ROW][C]12[/C][C]96.67[/C][C]95.9516[/C][C]95.4567[/C][C]0.494958[/C][C]0.718375[/C][/ROW]
[ROW][C]13[/C][C]96.67[/C][C]96.1486[/C][C]95.8033[/C][C]0.345292[/C][C]0.521375[/C][/ROW]
[ROW][C]14[/C][C]96.67[/C][C]96.3496[/C][C]96.15[/C][C]0.199625[/C][C]0.320375[/C][/ROW]
[ROW][C]15[/C][C]96.67[/C][C]96.5506[/C][C]96.4967[/C][C]0.0539583[/C][C]0.119375[/C][/ROW]
[ROW][C]16[/C][C]96.67[/C][C]96.5821[/C][C]96.65[/C][C]-0.067875[/C][C]0.087875[/C][/ROW]
[ROW][C]17[/C][C]96.67[/C][C]96.4441[/C][C]96.61[/C][C]-0.165875[/C][C]0.225875[/C][/ROW]
[ROW][C]18[/C][C]96.67[/C][C]96.3061[/C][C]96.57[/C][C]-0.263875[/C][C]0.363875[/C][/ROW]
[ROW][C]19[/C][C]96.67[/C][C]96.0013[/C][C]96.53[/C][C]-0.528708[/C][C]0.668708[/C][/ROW]
[ROW][C]20[/C][C]96.67[/C][C]95.8156[/C][C]96.49[/C][C]-0.674375[/C][C]0.854375[/C][/ROW]
[ROW][C]21[/C][C]96.67[/C][C]95.63[/C][C]96.45[/C][C]-0.820042[/C][C]1.04004[/C][/ROW]
[ROW][C]22[/C][C]96.19[/C][C]97.1963[/C][C]96.41[/C][C]0.786292[/C][C]-1.00629[/C][/ROW]
[ROW][C]23[/C][C]96.19[/C][C]97.0106[/C][C]96.37[/C][C]0.640625[/C][C]-0.820625[/C][/ROW]
[ROW][C]24[/C][C]96.19[/C][C]96.825[/C][C]96.33[/C][C]0.494958[/C][C]-0.634958[/C][/ROW]
[ROW][C]25[/C][C]96.19[/C][C]96.6353[/C][C]96.29[/C][C]0.345292[/C][C]-0.445292[/C][/ROW]
[ROW][C]26[/C][C]96.19[/C][C]96.4496[/C][C]96.25[/C][C]0.199625[/C][C]-0.259625[/C][/ROW]
[ROW][C]27[/C][C]96.19[/C][C]96.264[/C][C]96.21[/C][C]0.0539583[/C][C]-0.0739583[/C][/ROW]
[ROW][C]28[/C][C]96.19[/C][C]96.2446[/C][C]96.3125[/C][C]-0.067875[/C][C]-0.054625[/C][/ROW]
[ROW][C]29[/C][C]96.19[/C][C]96.3916[/C][C]96.5575[/C][C]-0.165875[/C][C]-0.201625[/C][/ROW]
[ROW][C]30[/C][C]96.19[/C][C]96.5386[/C][C]96.8025[/C][C]-0.263875[/C][C]-0.348625[/C][/ROW]
[ROW][C]31[/C][C]96.19[/C][C]96.5188[/C][C]97.0475[/C][C]-0.528708[/C][C]-0.328792[/C][/ROW]
[ROW][C]32[/C][C]96.19[/C][C]96.6181[/C][C]97.2925[/C][C]-0.674375[/C][C]-0.428125[/C][/ROW]
[ROW][C]33[/C][C]96.19[/C][C]96.7175[/C][C]97.5375[/C][C]-0.820042[/C][C]-0.527458[/C][/ROW]
[ROW][C]34[/C][C]99.13[/C][C]98.5688[/C][C]97.7825[/C][C]0.786292[/C][C]0.561208[/C][/ROW]
[ROW][C]35[/C][C]99.13[/C][C]98.6681[/C][C]98.0275[/C][C]0.640625[/C][C]0.461875[/C][/ROW]
[ROW][C]36[/C][C]99.13[/C][C]98.7675[/C][C]98.2725[/C][C]0.494958[/C][C]0.362542[/C][/ROW]
[ROW][C]37[/C][C]99.13[/C][C]98.8628[/C][C]98.5175[/C][C]0.345292[/C][C]0.267208[/C][/ROW]
[ROW][C]38[/C][C]99.13[/C][C]98.9621[/C][C]98.7625[/C][C]0.199625[/C][C]0.167875[/C][/ROW]
[ROW][C]39[/C][C]99.13[/C][C]99.0615[/C][C]99.0075[/C][C]0.0539583[/C][C]0.0685417[/C][/ROW]
[ROW][C]40[/C][C]99.13[/C][C]99.0809[/C][C]99.1487[/C][C]-0.067875[/C][C]0.049125[/C][/ROW]
[ROW][C]41[/C][C]99.13[/C][C]99.0204[/C][C]99.1862[/C][C]-0.165875[/C][C]0.109625[/C][/ROW]
[ROW][C]42[/C][C]99.13[/C][C]98.9599[/C][C]99.2238[/C][C]-0.263875[/C][C]0.170125[/C][/ROW]
[ROW][C]43[/C][C]99.13[/C][C]98.7325[/C][C]99.2612[/C][C]-0.528708[/C][C]0.397458[/C][/ROW]
[ROW][C]44[/C][C]99.13[/C][C]98.6244[/C][C]99.2988[/C][C]-0.674375[/C][C]0.505625[/C][/ROW]
[ROW][C]45[/C][C]99.13[/C][C]98.5162[/C][C]99.3362[/C][C]-0.820042[/C][C]0.613792[/C][/ROW]
[ROW][C]46[/C][C]99.58[/C][C]100.16[/C][C]99.3738[/C][C]0.786292[/C][C]-0.580042[/C][/ROW]
[ROW][C]47[/C][C]99.58[/C][C]100.052[/C][C]99.4112[/C][C]0.640625[/C][C]-0.471875[/C][/ROW]
[ROW][C]48[/C][C]99.58[/C][C]99.9437[/C][C]99.4488[/C][C]0.494958[/C][C]-0.363708[/C][/ROW]
[ROW][C]49[/C][C]99.58[/C][C]99.8315[/C][C]99.4862[/C][C]0.345292[/C][C]-0.251542[/C][/ROW]
[ROW][C]50[/C][C]99.58[/C][C]99.7234[/C][C]99.5237[/C][C]0.199625[/C][C]-0.143375[/C][/ROW]
[ROW][C]51[/C][C]99.58[/C][C]99.6152[/C][C]99.5612[/C][C]0.0539583[/C][C]-0.0352083[/C][/ROW]
[ROW][C]52[/C][C]99.58[/C][C]99.5825[/C][C]99.6504[/C][C]-0.067875[/C][C]-0.00254167[/C][/ROW]
[ROW][C]53[/C][C]99.58[/C][C]99.6254[/C][C]99.7912[/C][C]-0.165875[/C][C]-0.045375[/C][/ROW]
[ROW][C]54[/C][C]99.58[/C][C]99.6682[/C][C]99.9321[/C][C]-0.263875[/C][C]-0.0882083[/C][/ROW]
[ROW][C]55[/C][C]99.58[/C][C]99.5434[/C][C]100.072[/C][C]-0.528708[/C][C]0.036625[/C][/ROW]
[ROW][C]56[/C][C]99.58[/C][C]99.5369[/C][C]100.211[/C][C]-0.674375[/C][C]0.043125[/C][/ROW]
[ROW][C]57[/C][C]99.58[/C][C]99.5304[/C][C]100.35[/C][C]-0.820042[/C][C]0.049625[/C][/ROW]
[ROW][C]58[/C][C]101.27[/C][C]101.276[/C][C]100.49[/C][C]0.786292[/C][C]-0.005875[/C][/ROW]
[ROW][C]59[/C][C]101.27[/C][C]101.269[/C][C]100.629[/C][C]0.640625[/C][C]0.000625[/C][/ROW]
[ROW][C]60[/C][C]101.27[/C][C]101.263[/C][C]100.768[/C][C]0.494958[/C][C]0.007125[/C][/ROW]
[ROW][C]61[/C][C]101.25[/C][C]101.252[/C][C]100.907[/C][C]0.345292[/C][C]-0.002375[/C][/ROW]
[ROW][C]62[/C][C]101.25[/C][C]101.246[/C][C]101.046[/C][C]0.199625[/C][C]0.004125[/C][/ROW]
[ROW][C]63[/C][C]101.25[/C][C]101.239[/C][C]101.185[/C][C]0.0539583[/C][C]0.010625[/C][/ROW]
[ROW][C]64[/C][C]101.25[/C][C]101.24[/C][C]101.308[/C][C]-0.067875[/C][C]0.00954167[/C][/ROW]
[ROW][C]65[/C][C]101.25[/C][C]101.249[/C][C]101.415[/C][C]-0.165875[/C][C]0.000875[/C][/ROW]
[ROW][C]66[/C][C]101.25[/C][C]101.258[/C][C]101.522[/C][C]-0.263875[/C][C]-0.00779167[/C][/ROW]
[ROW][C]67[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]-0.528708[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]-0.674375[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]101.25[/C][C]NA[/C][C]NA[/C][C]-0.820042[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]102.55[/C][C]NA[/C][C]NA[/C][C]0.786292[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]102.55[/C][C]NA[/C][C]NA[/C][C]0.640625[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]102.55[/C][C]NA[/C][C]NA[/C][C]0.494958[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284368&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284368&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	92.51	NA	NA	0.345292	NA
2	92.51	NA	NA	0.199625	NA
3	92.51	NA	NA	0.0539583	NA
4	92.51	NA	NA	-0.067875	NA
5	92.51	NA	NA	-0.165875	NA
6	92.51	NA	NA	-0.263875	NA
7	92.51	93.1946	93.7233	-0.528708	-0.684625
8	92.51	93.3956	94.07	-0.674375	-0.885625
9	92.51	93.5966	94.4167	-0.820042	-1.08662
10	96.67	95.5496	94.7633	0.786292	1.12038
11	96.67	95.7506	95.11	0.640625	0.919375
12	96.67	95.9516	95.4567	0.494958	0.718375
13	96.67	96.1486	95.8033	0.345292	0.521375
14	96.67	96.3496	96.15	0.199625	0.320375
15	96.67	96.5506	96.4967	0.0539583	0.119375
16	96.67	96.5821	96.65	-0.067875	0.087875
17	96.67	96.4441	96.61	-0.165875	0.225875
18	96.67	96.3061	96.57	-0.263875	0.363875
19	96.67	96.0013	96.53	-0.528708	0.668708
20	96.67	95.8156	96.49	-0.674375	0.854375
21	96.67	95.63	96.45	-0.820042	1.04004
22	96.19	97.1963	96.41	0.786292	-1.00629
23	96.19	97.0106	96.37	0.640625	-0.820625
24	96.19	96.825	96.33	0.494958	-0.634958
25	96.19	96.6353	96.29	0.345292	-0.445292
26	96.19	96.4496	96.25	0.199625	-0.259625
27	96.19	96.264	96.21	0.0539583	-0.0739583
28	96.19	96.2446	96.3125	-0.067875	-0.054625
29	96.19	96.3916	96.5575	-0.165875	-0.201625
30	96.19	96.5386	96.8025	-0.263875	-0.348625
31	96.19	96.5188	97.0475	-0.528708	-0.328792
32	96.19	96.6181	97.2925	-0.674375	-0.428125
33	96.19	96.7175	97.5375	-0.820042	-0.527458
34	99.13	98.5688	97.7825	0.786292	0.561208
35	99.13	98.6681	98.0275	0.640625	0.461875
36	99.13	98.7675	98.2725	0.494958	0.362542
37	99.13	98.8628	98.5175	0.345292	0.267208
38	99.13	98.9621	98.7625	0.199625	0.167875
39	99.13	99.0615	99.0075	0.0539583	0.0685417
40	99.13	99.0809	99.1487	-0.067875	0.049125
41	99.13	99.0204	99.1862	-0.165875	0.109625
42	99.13	98.9599	99.2238	-0.263875	0.170125
43	99.13	98.7325	99.2612	-0.528708	0.397458
44	99.13	98.6244	99.2988	-0.674375	0.505625
45	99.13	98.5162	99.3362	-0.820042	0.613792
46	99.58	100.16	99.3738	0.786292	-0.580042
47	99.58	100.052	99.4112	0.640625	-0.471875
48	99.58	99.9437	99.4488	0.494958	-0.363708
49	99.58	99.8315	99.4862	0.345292	-0.251542
50	99.58	99.7234	99.5237	0.199625	-0.143375
51	99.58	99.6152	99.5612	0.0539583	-0.0352083
52	99.58	99.5825	99.6504	-0.067875	-0.00254167
53	99.58	99.6254	99.7912	-0.165875	-0.045375
54	99.58	99.6682	99.9321	-0.263875	-0.0882083
55	99.58	99.5434	100.072	-0.528708	0.036625
56	99.58	99.5369	100.211	-0.674375	0.043125
57	99.58	99.5304	100.35	-0.820042	0.049625
58	101.27	101.276	100.49	0.786292	-0.005875
59	101.27	101.269	100.629	0.640625	0.000625
60	101.27	101.263	100.768	0.494958	0.007125
61	101.25	101.252	100.907	0.345292	-0.002375
62	101.25	101.246	101.046	0.199625	0.004125
63	101.25	101.239	101.185	0.0539583	0.010625
64	101.25	101.24	101.308	-0.067875	0.00954167
65	101.25	101.249	101.415	-0.165875	0.000875
66	101.25	101.258	101.522	-0.263875	-0.00779167
67	101.25	NA	NA	-0.528708	NA
68	101.25	NA	NA	-0.674375	NA
69	101.25	NA	NA	-0.820042	NA
70	102.55	NA	NA	0.786292	NA
71	102.55	NA	NA	0.640625	NA
72	102.55	NA	NA	0.494958	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