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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Wed, 04 Dec 2013 03:56:24 -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/04/t1386147412reotnst5ie3xexx.htm/, Retrieved Fri, 19 Apr 2024 06:27:14 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230438, Retrieved Fri, 19 Apr 2024 06:27:14 +0000

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-       [Classical Decomposition] [] [2013-12-04 08:56:24] [17b6b1d507219cce54aa3edb43843a55] [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	6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230438&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]6 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=230438&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230438&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	6 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.2103	NA	NA	0.988253	NA
2	1.1938	NA	NA	0.984995	NA
3	1.202	NA	NA	1.00179	NA
4	1.2271	NA	NA	1.012	NA
5	1.277	NA	NA	0.998869	NA
6	1.265	NA	NA	0.994731	NA
7	1.2684	1.27547	1.25939	1.01276	0.994459
8	1.2811	1.2777	1.26786	1.00777	1.00266
9	1.2727	1.27812	1.27768	1.00034	0.995758
10	1.2611	1.29041	1.28796	1.0019	0.977285
11	1.2881	1.29536	1.29624	0.999326	0.994393
12	1.3213	1.29896	1.30253	0.997259	1.0172
13	1.2999	1.29464	1.31003	0.988253	1.00406
14	1.3074	1.29794	1.31771	0.984995	1.00729
15	1.3242	1.32834	1.32596	1.00179	0.996883
16	1.3516	1.35362	1.33757	1.012	0.99851
17	1.3511	1.35028	1.35181	0.998869	1.00061
18	1.3419	1.35779	1.36498	0.994731	0.988299
19	1.3716	1.39538	1.3778	1.01276	0.982956
20	1.3622	1.40274	1.39193	1.00777	0.971098
21	1.3896	1.40891	1.40843	1.00034	0.986293
22	1.4227	1.42998	1.42726	1.0019	0.994911
23	1.4684	1.44413	1.4451	0.999326	1.01681
24	1.457	1.45851	1.46252	0.997259	0.998966
25	1.4718	1.46258	1.47997	0.988253	1.0063
26	1.4748	1.47174	1.49416	0.984995	1.00208
27	1.5527	1.50446	1.50177	1.00179	1.03206
28	1.5751	1.51797	1.49997	1.012	1.03764
29	1.5557	1.48638	1.48807	0.998869	1.04663
30	1.5553	1.46749	1.47526	0.994731	1.05984
31	1.577	1.48312	1.46443	1.01276	1.0633
32	1.4975	1.46135	1.45009	1.00777	1.02474
33	1.4369	1.43208	1.43159	1.00034	1.00337
34	1.3322	1.41328	1.4106	1.0019	0.942631
35	1.2732	1.39104	1.39198	0.999326	0.915286
36	1.3449	1.37385	1.37763	0.997259	0.978926
37	1.3239	1.34819	1.36422	0.988253	0.981982
38	1.2785	1.33394	1.35426	0.984995	0.958438
39	1.305	1.35455	1.35212	1.00179	0.963423
40	1.319	1.37546	1.35915	1.012	0.958953
41	1.365	1.37291	1.37447	0.998869	0.994237
42	1.4016	1.3811	1.38841	0.994731	1.01485
43	1.4088	1.41541	1.39757	1.01276	0.995329
44	1.4268	1.41654	1.40563	1.00777	1.00724
45	1.4562	1.41203	1.41155	1.00034	1.03128
46	1.4816	1.4173	1.41461	1.0019	1.04537
47	1.4914	1.41004	1.41099	0.999326	1.0577
48	1.4614	1.3951	1.39894	0.997259	1.04752
49	1.4272	1.36964	1.38592	0.988253	1.04203
50	1.3686	1.35407	1.3747	0.984995	1.01073
51	1.3569	1.36519	1.36275	1.00179	0.993928
52	1.3406	1.36892	1.35269	1.012	0.97931
53	1.2565	1.34213	1.34365	0.998869	0.936202
54	1.2209	1.3256	1.33262	0.994731	0.92102
55	1.277	1.3399	1.32301	1.01276	0.953059
56	1.2894	1.3293	1.31905	1.00777	0.969987
57	1.3067	1.32115	1.32069	1.00034	0.989066
58	1.3898	1.32932	1.3268	1.0019	1.04549
59	1.3661	1.33765	1.33855	0.999326	1.02127
60	1.322	1.35135	1.35506	0.997259	0.978282
61	1.336	1.35427	1.37037	0.988253	0.98651
62	1.3649	1.36188	1.38263	0.984995	1.00222
63	1.3999	1.39409	1.3916	1.00179	1.00417
64	1.4442	1.41045	1.39372	1.012	1.02393
65	1.4349	1.39091	1.39249	0.998869	1.03163
66	1.4388	1.38455	1.39188	0.994731	1.03919
67	1.4264	1.40755	1.38981	1.01276	1.01339
68	1.4343	1.39691	1.38615	1.00777	1.02677
69	1.377	1.38152	1.38105	1.00034	0.996725
70	1.3706	1.375	1.37239	1.0019	0.996799
71	1.3556	1.35964	1.36056	0.999326	0.997028
72	1.3179	1.34261	1.3463	0.997259	0.981596
73	1.2905	1.31468	1.33031	0.988253	0.981607
74	1.3224	1.29426	1.31398	0.984995	1.02174
75	1.3201	1.30441	1.30207	1.00179	1.01203
76	1.3162	1.31076	1.29522	1.012	1.00415
77	1.2789	1.28767	1.28913	0.998869	0.993186
78	1.2526	1.27907	1.28585	0.994731	0.979302
79	1.2288	NA	NA	1.01276	NA
80	1.24	NA	NA	1.00777	NA
81	1.2856	NA	NA	1.00034	NA
82	1.2974	NA	NA	1.0019	NA
83	1.2828	NA	NA	0.999326	NA
84	1.3119	NA	NA	0.997259	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.2103 & NA & NA & 0.988253 & NA \tabularnewline
2 & 1.1938 & NA & NA & 0.984995 & NA \tabularnewline
3 & 1.202 & NA & NA & 1.00179 & NA \tabularnewline
4 & 1.2271 & NA & NA & 1.012 & NA \tabularnewline
5 & 1.277 & NA & NA & 0.998869 & NA \tabularnewline
6 & 1.265 & NA & NA & 0.994731 & NA \tabularnewline
7 & 1.2684 & 1.27547 & 1.25939 & 1.01276 & 0.994459 \tabularnewline
8 & 1.2811 & 1.2777 & 1.26786 & 1.00777 & 1.00266 \tabularnewline
9 & 1.2727 & 1.27812 & 1.27768 & 1.00034 & 0.995758 \tabularnewline
10 & 1.2611 & 1.29041 & 1.28796 & 1.0019 & 0.977285 \tabularnewline
11 & 1.2881 & 1.29536 & 1.29624 & 0.999326 & 0.994393 \tabularnewline
12 & 1.3213 & 1.29896 & 1.30253 & 0.997259 & 1.0172 \tabularnewline
13 & 1.2999 & 1.29464 & 1.31003 & 0.988253 & 1.00406 \tabularnewline
14 & 1.3074 & 1.29794 & 1.31771 & 0.984995 & 1.00729 \tabularnewline
15 & 1.3242 & 1.32834 & 1.32596 & 1.00179 & 0.996883 \tabularnewline
16 & 1.3516 & 1.35362 & 1.33757 & 1.012 & 0.99851 \tabularnewline
17 & 1.3511 & 1.35028 & 1.35181 & 0.998869 & 1.00061 \tabularnewline
18 & 1.3419 & 1.35779 & 1.36498 & 0.994731 & 0.988299 \tabularnewline
19 & 1.3716 & 1.39538 & 1.3778 & 1.01276 & 0.982956 \tabularnewline
20 & 1.3622 & 1.40274 & 1.39193 & 1.00777 & 0.971098 \tabularnewline
21 & 1.3896 & 1.40891 & 1.40843 & 1.00034 & 0.986293 \tabularnewline
22 & 1.4227 & 1.42998 & 1.42726 & 1.0019 & 0.994911 \tabularnewline
23 & 1.4684 & 1.44413 & 1.4451 & 0.999326 & 1.01681 \tabularnewline
24 & 1.457 & 1.45851 & 1.46252 & 0.997259 & 0.998966 \tabularnewline
25 & 1.4718 & 1.46258 & 1.47997 & 0.988253 & 1.0063 \tabularnewline
26 & 1.4748 & 1.47174 & 1.49416 & 0.984995 & 1.00208 \tabularnewline
27 & 1.5527 & 1.50446 & 1.50177 & 1.00179 & 1.03206 \tabularnewline
28 & 1.5751 & 1.51797 & 1.49997 & 1.012 & 1.03764 \tabularnewline
29 & 1.5557 & 1.48638 & 1.48807 & 0.998869 & 1.04663 \tabularnewline
30 & 1.5553 & 1.46749 & 1.47526 & 0.994731 & 1.05984 \tabularnewline
31 & 1.577 & 1.48312 & 1.46443 & 1.01276 & 1.0633 \tabularnewline
32 & 1.4975 & 1.46135 & 1.45009 & 1.00777 & 1.02474 \tabularnewline
33 & 1.4369 & 1.43208 & 1.43159 & 1.00034 & 1.00337 \tabularnewline
34 & 1.3322 & 1.41328 & 1.4106 & 1.0019 & 0.942631 \tabularnewline
35 & 1.2732 & 1.39104 & 1.39198 & 0.999326 & 0.915286 \tabularnewline
36 & 1.3449 & 1.37385 & 1.37763 & 0.997259 & 0.978926 \tabularnewline
37 & 1.3239 & 1.34819 & 1.36422 & 0.988253 & 0.981982 \tabularnewline
38 & 1.2785 & 1.33394 & 1.35426 & 0.984995 & 0.958438 \tabularnewline
39 & 1.305 & 1.35455 & 1.35212 & 1.00179 & 0.963423 \tabularnewline
40 & 1.319 & 1.37546 & 1.35915 & 1.012 & 0.958953 \tabularnewline
41 & 1.365 & 1.37291 & 1.37447 & 0.998869 & 0.994237 \tabularnewline
42 & 1.4016 & 1.3811 & 1.38841 & 0.994731 & 1.01485 \tabularnewline
43 & 1.4088 & 1.41541 & 1.39757 & 1.01276 & 0.995329 \tabularnewline
44 & 1.4268 & 1.41654 & 1.40563 & 1.00777 & 1.00724 \tabularnewline
45 & 1.4562 & 1.41203 & 1.41155 & 1.00034 & 1.03128 \tabularnewline
46 & 1.4816 & 1.4173 & 1.41461 & 1.0019 & 1.04537 \tabularnewline
47 & 1.4914 & 1.41004 & 1.41099 & 0.999326 & 1.0577 \tabularnewline
48 & 1.4614 & 1.3951 & 1.39894 & 0.997259 & 1.04752 \tabularnewline
49 & 1.4272 & 1.36964 & 1.38592 & 0.988253 & 1.04203 \tabularnewline
50 & 1.3686 & 1.35407 & 1.3747 & 0.984995 & 1.01073 \tabularnewline
51 & 1.3569 & 1.36519 & 1.36275 & 1.00179 & 0.993928 \tabularnewline
52 & 1.3406 & 1.36892 & 1.35269 & 1.012 & 0.97931 \tabularnewline
53 & 1.2565 & 1.34213 & 1.34365 & 0.998869 & 0.936202 \tabularnewline
54 & 1.2209 & 1.3256 & 1.33262 & 0.994731 & 0.92102 \tabularnewline
55 & 1.277 & 1.3399 & 1.32301 & 1.01276 & 0.953059 \tabularnewline
56 & 1.2894 & 1.3293 & 1.31905 & 1.00777 & 0.969987 \tabularnewline
57 & 1.3067 & 1.32115 & 1.32069 & 1.00034 & 0.989066 \tabularnewline
58 & 1.3898 & 1.32932 & 1.3268 & 1.0019 & 1.04549 \tabularnewline
59 & 1.3661 & 1.33765 & 1.33855 & 0.999326 & 1.02127 \tabularnewline
60 & 1.322 & 1.35135 & 1.35506 & 0.997259 & 0.978282 \tabularnewline
61 & 1.336 & 1.35427 & 1.37037 & 0.988253 & 0.98651 \tabularnewline
62 & 1.3649 & 1.36188 & 1.38263 & 0.984995 & 1.00222 \tabularnewline
63 & 1.3999 & 1.39409 & 1.3916 & 1.00179 & 1.00417 \tabularnewline
64 & 1.4442 & 1.41045 & 1.39372 & 1.012 & 1.02393 \tabularnewline
65 & 1.4349 & 1.39091 & 1.39249 & 0.998869 & 1.03163 \tabularnewline
66 & 1.4388 & 1.38455 & 1.39188 & 0.994731 & 1.03919 \tabularnewline
67 & 1.4264 & 1.40755 & 1.38981 & 1.01276 & 1.01339 \tabularnewline
68 & 1.4343 & 1.39691 & 1.38615 & 1.00777 & 1.02677 \tabularnewline
69 & 1.377 & 1.38152 & 1.38105 & 1.00034 & 0.996725 \tabularnewline
70 & 1.3706 & 1.375 & 1.37239 & 1.0019 & 0.996799 \tabularnewline
71 & 1.3556 & 1.35964 & 1.36056 & 0.999326 & 0.997028 \tabularnewline
72 & 1.3179 & 1.34261 & 1.3463 & 0.997259 & 0.981596 \tabularnewline
73 & 1.2905 & 1.31468 & 1.33031 & 0.988253 & 0.981607 \tabularnewline
74 & 1.3224 & 1.29426 & 1.31398 & 0.984995 & 1.02174 \tabularnewline
75 & 1.3201 & 1.30441 & 1.30207 & 1.00179 & 1.01203 \tabularnewline
76 & 1.3162 & 1.31076 & 1.29522 & 1.012 & 1.00415 \tabularnewline
77 & 1.2789 & 1.28767 & 1.28913 & 0.998869 & 0.993186 \tabularnewline
78 & 1.2526 & 1.27907 & 1.28585 & 0.994731 & 0.979302 \tabularnewline
79 & 1.2288 & NA & NA & 1.01276 & NA \tabularnewline
80 & 1.24 & NA & NA & 1.00777 & NA \tabularnewline
81 & 1.2856 & NA & NA & 1.00034 & NA \tabularnewline
82 & 1.2974 & NA & NA & 1.0019 & NA \tabularnewline
83 & 1.2828 & NA & NA & 0.999326 & NA \tabularnewline
84 & 1.3119 & NA & NA & 0.997259 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230438&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]1.2103[/C][C]NA[/C][C]NA[/C][C]0.988253[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.1938[/C][C]NA[/C][C]NA[/C][C]0.984995[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.202[/C][C]NA[/C][C]NA[/C][C]1.00179[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.2271[/C][C]NA[/C][C]NA[/C][C]1.012[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.277[/C][C]NA[/C][C]NA[/C][C]0.998869[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.265[/C][C]NA[/C][C]NA[/C][C]0.994731[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.2684[/C][C]1.27547[/C][C]1.25939[/C][C]1.01276[/C][C]0.994459[/C][/ROW]
[ROW][C]8[/C][C]1.2811[/C][C]1.2777[/C][C]1.26786[/C][C]1.00777[/C][C]1.00266[/C][/ROW]
[ROW][C]9[/C][C]1.2727[/C][C]1.27812[/C][C]1.27768[/C][C]1.00034[/C][C]0.995758[/C][/ROW]
[ROW][C]10[/C][C]1.2611[/C][C]1.29041[/C][C]1.28796[/C][C]1.0019[/C][C]0.977285[/C][/ROW]
[ROW][C]11[/C][C]1.2881[/C][C]1.29536[/C][C]1.29624[/C][C]0.999326[/C][C]0.994393[/C][/ROW]
[ROW][C]12[/C][C]1.3213[/C][C]1.29896[/C][C]1.30253[/C][C]0.997259[/C][C]1.0172[/C][/ROW]
[ROW][C]13[/C][C]1.2999[/C][C]1.29464[/C][C]1.31003[/C][C]0.988253[/C][C]1.00406[/C][/ROW]
[ROW][C]14[/C][C]1.3074[/C][C]1.29794[/C][C]1.31771[/C][C]0.984995[/C][C]1.00729[/C][/ROW]
[ROW][C]15[/C][C]1.3242[/C][C]1.32834[/C][C]1.32596[/C][C]1.00179[/C][C]0.996883[/C][/ROW]
[ROW][C]16[/C][C]1.3516[/C][C]1.35362[/C][C]1.33757[/C][C]1.012[/C][C]0.99851[/C][/ROW]
[ROW][C]17[/C][C]1.3511[/C][C]1.35028[/C][C]1.35181[/C][C]0.998869[/C][C]1.00061[/C][/ROW]
[ROW][C]18[/C][C]1.3419[/C][C]1.35779[/C][C]1.36498[/C][C]0.994731[/C][C]0.988299[/C][/ROW]
[ROW][C]19[/C][C]1.3716[/C][C]1.39538[/C][C]1.3778[/C][C]1.01276[/C][C]0.982956[/C][/ROW]
[ROW][C]20[/C][C]1.3622[/C][C]1.40274[/C][C]1.39193[/C][C]1.00777[/C][C]0.971098[/C][/ROW]
[ROW][C]21[/C][C]1.3896[/C][C]1.40891[/C][C]1.40843[/C][C]1.00034[/C][C]0.986293[/C][/ROW]
[ROW][C]22[/C][C]1.4227[/C][C]1.42998[/C][C]1.42726[/C][C]1.0019[/C][C]0.994911[/C][/ROW]
[ROW][C]23[/C][C]1.4684[/C][C]1.44413[/C][C]1.4451[/C][C]0.999326[/C][C]1.01681[/C][/ROW]
[ROW][C]24[/C][C]1.457[/C][C]1.45851[/C][C]1.46252[/C][C]0.997259[/C][C]0.998966[/C][/ROW]
[ROW][C]25[/C][C]1.4718[/C][C]1.46258[/C][C]1.47997[/C][C]0.988253[/C][C]1.0063[/C][/ROW]
[ROW][C]26[/C][C]1.4748[/C][C]1.47174[/C][C]1.49416[/C][C]0.984995[/C][C]1.00208[/C][/ROW]
[ROW][C]27[/C][C]1.5527[/C][C]1.50446[/C][C]1.50177[/C][C]1.00179[/C][C]1.03206[/C][/ROW]
[ROW][C]28[/C][C]1.5751[/C][C]1.51797[/C][C]1.49997[/C][C]1.012[/C][C]1.03764[/C][/ROW]
[ROW][C]29[/C][C]1.5557[/C][C]1.48638[/C][C]1.48807[/C][C]0.998869[/C][C]1.04663[/C][/ROW]
[ROW][C]30[/C][C]1.5553[/C][C]1.46749[/C][C]1.47526[/C][C]0.994731[/C][C]1.05984[/C][/ROW]
[ROW][C]31[/C][C]1.577[/C][C]1.48312[/C][C]1.46443[/C][C]1.01276[/C][C]1.0633[/C][/ROW]
[ROW][C]32[/C][C]1.4975[/C][C]1.46135[/C][C]1.45009[/C][C]1.00777[/C][C]1.02474[/C][/ROW]
[ROW][C]33[/C][C]1.4369[/C][C]1.43208[/C][C]1.43159[/C][C]1.00034[/C][C]1.00337[/C][/ROW]
[ROW][C]34[/C][C]1.3322[/C][C]1.41328[/C][C]1.4106[/C][C]1.0019[/C][C]0.942631[/C][/ROW]
[ROW][C]35[/C][C]1.2732[/C][C]1.39104[/C][C]1.39198[/C][C]0.999326[/C][C]0.915286[/C][/ROW]
[ROW][C]36[/C][C]1.3449[/C][C]1.37385[/C][C]1.37763[/C][C]0.997259[/C][C]0.978926[/C][/ROW]
[ROW][C]37[/C][C]1.3239[/C][C]1.34819[/C][C]1.36422[/C][C]0.988253[/C][C]0.981982[/C][/ROW]
[ROW][C]38[/C][C]1.2785[/C][C]1.33394[/C][C]1.35426[/C][C]0.984995[/C][C]0.958438[/C][/ROW]
[ROW][C]39[/C][C]1.305[/C][C]1.35455[/C][C]1.35212[/C][C]1.00179[/C][C]0.963423[/C][/ROW]
[ROW][C]40[/C][C]1.319[/C][C]1.37546[/C][C]1.35915[/C][C]1.012[/C][C]0.958953[/C][/ROW]
[ROW][C]41[/C][C]1.365[/C][C]1.37291[/C][C]1.37447[/C][C]0.998869[/C][C]0.994237[/C][/ROW]
[ROW][C]42[/C][C]1.4016[/C][C]1.3811[/C][C]1.38841[/C][C]0.994731[/C][C]1.01485[/C][/ROW]
[ROW][C]43[/C][C]1.4088[/C][C]1.41541[/C][C]1.39757[/C][C]1.01276[/C][C]0.995329[/C][/ROW]
[ROW][C]44[/C][C]1.4268[/C][C]1.41654[/C][C]1.40563[/C][C]1.00777[/C][C]1.00724[/C][/ROW]
[ROW][C]45[/C][C]1.4562[/C][C]1.41203[/C][C]1.41155[/C][C]1.00034[/C][C]1.03128[/C][/ROW]
[ROW][C]46[/C][C]1.4816[/C][C]1.4173[/C][C]1.41461[/C][C]1.0019[/C][C]1.04537[/C][/ROW]
[ROW][C]47[/C][C]1.4914[/C][C]1.41004[/C][C]1.41099[/C][C]0.999326[/C][C]1.0577[/C][/ROW]
[ROW][C]48[/C][C]1.4614[/C][C]1.3951[/C][C]1.39894[/C][C]0.997259[/C][C]1.04752[/C][/ROW]
[ROW][C]49[/C][C]1.4272[/C][C]1.36964[/C][C]1.38592[/C][C]0.988253[/C][C]1.04203[/C][/ROW]
[ROW][C]50[/C][C]1.3686[/C][C]1.35407[/C][C]1.3747[/C][C]0.984995[/C][C]1.01073[/C][/ROW]
[ROW][C]51[/C][C]1.3569[/C][C]1.36519[/C][C]1.36275[/C][C]1.00179[/C][C]0.993928[/C][/ROW]
[ROW][C]52[/C][C]1.3406[/C][C]1.36892[/C][C]1.35269[/C][C]1.012[/C][C]0.97931[/C][/ROW]
[ROW][C]53[/C][C]1.2565[/C][C]1.34213[/C][C]1.34365[/C][C]0.998869[/C][C]0.936202[/C][/ROW]
[ROW][C]54[/C][C]1.2209[/C][C]1.3256[/C][C]1.33262[/C][C]0.994731[/C][C]0.92102[/C][/ROW]
[ROW][C]55[/C][C]1.277[/C][C]1.3399[/C][C]1.32301[/C][C]1.01276[/C][C]0.953059[/C][/ROW]
[ROW][C]56[/C][C]1.2894[/C][C]1.3293[/C][C]1.31905[/C][C]1.00777[/C][C]0.969987[/C][/ROW]
[ROW][C]57[/C][C]1.3067[/C][C]1.32115[/C][C]1.32069[/C][C]1.00034[/C][C]0.989066[/C][/ROW]
[ROW][C]58[/C][C]1.3898[/C][C]1.32932[/C][C]1.3268[/C][C]1.0019[/C][C]1.04549[/C][/ROW]
[ROW][C]59[/C][C]1.3661[/C][C]1.33765[/C][C]1.33855[/C][C]0.999326[/C][C]1.02127[/C][/ROW]
[ROW][C]60[/C][C]1.322[/C][C]1.35135[/C][C]1.35506[/C][C]0.997259[/C][C]0.978282[/C][/ROW]
[ROW][C]61[/C][C]1.336[/C][C]1.35427[/C][C]1.37037[/C][C]0.988253[/C][C]0.98651[/C][/ROW]
[ROW][C]62[/C][C]1.3649[/C][C]1.36188[/C][C]1.38263[/C][C]0.984995[/C][C]1.00222[/C][/ROW]
[ROW][C]63[/C][C]1.3999[/C][C]1.39409[/C][C]1.3916[/C][C]1.00179[/C][C]1.00417[/C][/ROW]
[ROW][C]64[/C][C]1.4442[/C][C]1.41045[/C][C]1.39372[/C][C]1.012[/C][C]1.02393[/C][/ROW]
[ROW][C]65[/C][C]1.4349[/C][C]1.39091[/C][C]1.39249[/C][C]0.998869[/C][C]1.03163[/C][/ROW]
[ROW][C]66[/C][C]1.4388[/C][C]1.38455[/C][C]1.39188[/C][C]0.994731[/C][C]1.03919[/C][/ROW]
[ROW][C]67[/C][C]1.4264[/C][C]1.40755[/C][C]1.38981[/C][C]1.01276[/C][C]1.01339[/C][/ROW]
[ROW][C]68[/C][C]1.4343[/C][C]1.39691[/C][C]1.38615[/C][C]1.00777[/C][C]1.02677[/C][/ROW]
[ROW][C]69[/C][C]1.377[/C][C]1.38152[/C][C]1.38105[/C][C]1.00034[/C][C]0.996725[/C][/ROW]
[ROW][C]70[/C][C]1.3706[/C][C]1.375[/C][C]1.37239[/C][C]1.0019[/C][C]0.996799[/C][/ROW]
[ROW][C]71[/C][C]1.3556[/C][C]1.35964[/C][C]1.36056[/C][C]0.999326[/C][C]0.997028[/C][/ROW]
[ROW][C]72[/C][C]1.3179[/C][C]1.34261[/C][C]1.3463[/C][C]0.997259[/C][C]0.981596[/C][/ROW]
[ROW][C]73[/C][C]1.2905[/C][C]1.31468[/C][C]1.33031[/C][C]0.988253[/C][C]0.981607[/C][/ROW]
[ROW][C]74[/C][C]1.3224[/C][C]1.29426[/C][C]1.31398[/C][C]0.984995[/C][C]1.02174[/C][/ROW]
[ROW][C]75[/C][C]1.3201[/C][C]1.30441[/C][C]1.30207[/C][C]1.00179[/C][C]1.01203[/C][/ROW]
[ROW][C]76[/C][C]1.3162[/C][C]1.31076[/C][C]1.29522[/C][C]1.012[/C][C]1.00415[/C][/ROW]
[ROW][C]77[/C][C]1.2789[/C][C]1.28767[/C][C]1.28913[/C][C]0.998869[/C][C]0.993186[/C][/ROW]
[ROW][C]78[/C][C]1.2526[/C][C]1.27907[/C][C]1.28585[/C][C]0.994731[/C][C]0.979302[/C][/ROW]
[ROW][C]79[/C][C]1.2288[/C][C]NA[/C][C]NA[/C][C]1.01276[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]1.24[/C][C]NA[/C][C]NA[/C][C]1.00777[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]1.2856[/C][C]NA[/C][C]NA[/C][C]1.00034[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]1.2974[/C][C]NA[/C][C]NA[/C][C]1.0019[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]1.2828[/C][C]NA[/C][C]NA[/C][C]0.999326[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]1.3119[/C][C]NA[/C][C]NA[/C][C]0.997259[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230438&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230438&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	1.2103	NA	NA	0.988253	NA
2	1.1938	NA	NA	0.984995	NA
3	1.202	NA	NA	1.00179	NA
4	1.2271	NA	NA	1.012	NA
5	1.277	NA	NA	0.998869	NA
6	1.265	NA	NA	0.994731	NA
7	1.2684	1.27547	1.25939	1.01276	0.994459
8	1.2811	1.2777	1.26786	1.00777	1.00266
9	1.2727	1.27812	1.27768	1.00034	0.995758
10	1.2611	1.29041	1.28796	1.0019	0.977285
11	1.2881	1.29536	1.29624	0.999326	0.994393
12	1.3213	1.29896	1.30253	0.997259	1.0172
13	1.2999	1.29464	1.31003	0.988253	1.00406
14	1.3074	1.29794	1.31771	0.984995	1.00729
15	1.3242	1.32834	1.32596	1.00179	0.996883
16	1.3516	1.35362	1.33757	1.012	0.99851
17	1.3511	1.35028	1.35181	0.998869	1.00061
18	1.3419	1.35779	1.36498	0.994731	0.988299
19	1.3716	1.39538	1.3778	1.01276	0.982956
20	1.3622	1.40274	1.39193	1.00777	0.971098
21	1.3896	1.40891	1.40843	1.00034	0.986293
22	1.4227	1.42998	1.42726	1.0019	0.994911
23	1.4684	1.44413	1.4451	0.999326	1.01681
24	1.457	1.45851	1.46252	0.997259	0.998966
25	1.4718	1.46258	1.47997	0.988253	1.0063
26	1.4748	1.47174	1.49416	0.984995	1.00208
27	1.5527	1.50446	1.50177	1.00179	1.03206
28	1.5751	1.51797	1.49997	1.012	1.03764
29	1.5557	1.48638	1.48807	0.998869	1.04663
30	1.5553	1.46749	1.47526	0.994731	1.05984
31	1.577	1.48312	1.46443	1.01276	1.0633
32	1.4975	1.46135	1.45009	1.00777	1.02474
33	1.4369	1.43208	1.43159	1.00034	1.00337
34	1.3322	1.41328	1.4106	1.0019	0.942631
35	1.2732	1.39104	1.39198	0.999326	0.915286
36	1.3449	1.37385	1.37763	0.997259	0.978926
37	1.3239	1.34819	1.36422	0.988253	0.981982
38	1.2785	1.33394	1.35426	0.984995	0.958438
39	1.305	1.35455	1.35212	1.00179	0.963423
40	1.319	1.37546	1.35915	1.012	0.958953
41	1.365	1.37291	1.37447	0.998869	0.994237
42	1.4016	1.3811	1.38841	0.994731	1.01485
43	1.4088	1.41541	1.39757	1.01276	0.995329
44	1.4268	1.41654	1.40563	1.00777	1.00724
45	1.4562	1.41203	1.41155	1.00034	1.03128
46	1.4816	1.4173	1.41461	1.0019	1.04537
47	1.4914	1.41004	1.41099	0.999326	1.0577
48	1.4614	1.3951	1.39894	0.997259	1.04752
49	1.4272	1.36964	1.38592	0.988253	1.04203
50	1.3686	1.35407	1.3747	0.984995	1.01073
51	1.3569	1.36519	1.36275	1.00179	0.993928
52	1.3406	1.36892	1.35269	1.012	0.97931
53	1.2565	1.34213	1.34365	0.998869	0.936202
54	1.2209	1.3256	1.33262	0.994731	0.92102
55	1.277	1.3399	1.32301	1.01276	0.953059
56	1.2894	1.3293	1.31905	1.00777	0.969987
57	1.3067	1.32115	1.32069	1.00034	0.989066
58	1.3898	1.32932	1.3268	1.0019	1.04549
59	1.3661	1.33765	1.33855	0.999326	1.02127
60	1.322	1.35135	1.35506	0.997259	0.978282
61	1.336	1.35427	1.37037	0.988253	0.98651
62	1.3649	1.36188	1.38263	0.984995	1.00222
63	1.3999	1.39409	1.3916	1.00179	1.00417
64	1.4442	1.41045	1.39372	1.012	1.02393
65	1.4349	1.39091	1.39249	0.998869	1.03163
66	1.4388	1.38455	1.39188	0.994731	1.03919
67	1.4264	1.40755	1.38981	1.01276	1.01339
68	1.4343	1.39691	1.38615	1.00777	1.02677
69	1.377	1.38152	1.38105	1.00034	0.996725
70	1.3706	1.375	1.37239	1.0019	0.996799
71	1.3556	1.35964	1.36056	0.999326	0.997028
72	1.3179	1.34261	1.3463	0.997259	0.981596
73	1.2905	1.31468	1.33031	0.988253	0.981607
74	1.3224	1.29426	1.31398	0.984995	1.02174
75	1.3201	1.30441	1.30207	1.00179	1.01203
76	1.3162	1.31076	1.29522	1.012	1.00415
77	1.2789	1.28767	1.28913	0.998869	0.993186
78	1.2526	1.27907	1.28585	0.994731	0.979302
79	1.2288	NA	NA	1.01276	NA
80	1.24	NA	NA	1.00777	NA
81	1.2856	NA	NA	1.00034	NA
82	1.2974	NA	NA	1.0019	NA
83	1.2828	NA	NA	0.999326	NA
84	1.3119	NA	NA	0.997259	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