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R Software Module

rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 25 Apr 2016 15:50:55 +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/25/t1461595912ypvrmk88a32n20p.htm/, Retrieved Fri, 10 May 2024 17:26:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294727, Retrieved Fri, 10 May 2024 17:26:46 +0000

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-       [Classical Decomposition] [] [2016-04-25 14:50:55] [a1d1814f81d637d5e936c79e282724ec] [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=294727&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=294727&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294727&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	89.65	NA	NA	1.00605	NA
2	90.65	NA	NA	1.01172	NA
3	89.34	NA	NA	1.00966	NA
4	89.15	NA	NA	1.00392	NA
5	88.82	NA	NA	1.0018	NA
6	88.82	NA	NA	0.997231	NA
7	91.97	90.5687	91.2592	0.992434	1.01547
8	93.01	91.2285	91.5858	0.996099	1.01953
9	93.24	91.6207	91.9613	0.996297	1.01767
10	93.2	92.1911	92.3833	0.99792	1.01094
11	93.19	92.4985	92.8175	0.996564	1.00748
12	92.2	92.2956	93.1988	0.990309	0.998965
13	93.39	93.9565	93.3912	1.00605	0.993971
14	94.75	94.5213	93.4267	1.01172	1.00242
15	94.25	94.3155	93.4133	1.00966	0.999306
16	94.37	93.73	93.3642	1.00392	1.00683
17	94.02	93.4648	93.2967	1.0018	1.00594
18	92.77	92.9743	93.2325	0.997231	0.997803
19	92.64	92.5163	93.2217	0.992434	1.00134
20	93.19	92.9327	93.2967	0.996099	1.00277
21	92.74	93.0994	93.4454	0.996297	0.99614
22	92.52	93.3936	93.5883	0.99792	0.990646
23	92.25	93.3651	93.6871	0.996564	0.988056
24	91.6	92.9351	93.8446	0.990309	0.985634
25	93.73	94.6351	94.0658	1.00605	0.990436
26	96.21	95.4546	94.3492	1.01172	1.00791
27	96.36	95.6722	94.7571	1.00966	1.00719
28	95.69	95.6132	95.24	1.00392	1.0008
29	95.07	95.9218	95.7492	1.0018	0.99112
30	95.5	96.0088	96.2754	0.997231	0.994701
31	95.22	96.1321	96.865	0.992434	0.990512
32	97.41	97.0661	97.4462	0.996099	1.00354
33	98.31	97.5956	97.9583	0.996297	1.00732
34	98.54	98.2265	98.4312	0.99792	1.00319
35	98.45	98.546	98.8858	0.996564	0.999026
36	98.03	98.3567	99.3192	0.990309	0.996679
37	101.45	100.24	99.6367	1.00605	1.01207
38	102.44	100.922	99.7533	1.01172	1.01504
39	102.42	100.67	99.7075	1.00966	1.01738
40	100.98	100.07	99.6796	1.00392	1.00909
41	100.69	99.9419	99.7621	1.0018	1.00749
42	100.28	99.6375	99.9142	0.997231	1.00645
43	98.06	99.2161	99.9725	0.992434	0.988348
44	97.37	99.4438	99.8333	0.996099	0.979146
45	97.25	99.2366	99.6054	0.996297	0.979981
46	98.93	99.2107	99.4175	0.99792	0.997171
47	100.04	98.9629	99.3042	0.996564	1.01088
48	100.09	98.2547	99.2162	0.990309	1.01868
49	100.79	99.8008	99.2004	1.00605	1.00991
50	99.76	100.419	99.2558	1.01172	0.99344
51	99.63	100.275	99.3163	1.00966	0.993563
52	99.26	99.6983	99.3092	1.00392	0.995603
53	99.69	99.3254	99.1467	1.0018	1.00367
54	99.17	98.6157	98.8896	0.997231	1.00562
55	98.79	97.8676	98.6138	0.992434	1.00943
56	97.97	97.9592	98.3429	0.996099	1.00011
57	98.1	97.711	98.0742	0.996297	1.00398
58	97.91	97.6032	97.8067	0.99792	1.00314
59	97.16	97.1936	97.5288	0.996564	0.999654
60	96.8	96.3051	97.2475	0.990309	1.00514
61	97.46	97.5866	96.9996	1.00605	0.998702
62	96.59	97.9333	96.7992	1.01172	0.986283
63	96.35	97.554	96.6208	1.00966	0.987658
64	96.12	96.82	96.4421	1.00392	0.99277
65	96.16	96.4611	96.2875	1.0018	0.996879
66	95.95	95.8999	96.1662	0.997231	1.00052
67	96.06	NA	NA	0.992434	NA
68	95.89	NA	NA	0.996099	NA
69	95.9	NA	NA	0.996297	NA
70	95.82	NA	NA	0.99792	NA
71	95.54	NA	NA	0.996564	NA
72	95.51	NA	NA	0.990309	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 89.65 & NA & NA & 1.00605 & NA \tabularnewline
2 & 90.65 & NA & NA & 1.01172 & NA \tabularnewline
3 & 89.34 & NA & NA & 1.00966 & NA \tabularnewline
4 & 89.15 & NA & NA & 1.00392 & NA \tabularnewline
5 & 88.82 & NA & NA & 1.0018 & NA \tabularnewline
6 & 88.82 & NA & NA & 0.997231 & NA \tabularnewline
7 & 91.97 & 90.5687 & 91.2592 & 0.992434 & 1.01547 \tabularnewline
8 & 93.01 & 91.2285 & 91.5858 & 0.996099 & 1.01953 \tabularnewline
9 & 93.24 & 91.6207 & 91.9613 & 0.996297 & 1.01767 \tabularnewline
10 & 93.2 & 92.1911 & 92.3833 & 0.99792 & 1.01094 \tabularnewline
11 & 93.19 & 92.4985 & 92.8175 & 0.996564 & 1.00748 \tabularnewline
12 & 92.2 & 92.2956 & 93.1988 & 0.990309 & 0.998965 \tabularnewline
13 & 93.39 & 93.9565 & 93.3912 & 1.00605 & 0.993971 \tabularnewline
14 & 94.75 & 94.5213 & 93.4267 & 1.01172 & 1.00242 \tabularnewline
15 & 94.25 & 94.3155 & 93.4133 & 1.00966 & 0.999306 \tabularnewline
16 & 94.37 & 93.73 & 93.3642 & 1.00392 & 1.00683 \tabularnewline
17 & 94.02 & 93.4648 & 93.2967 & 1.0018 & 1.00594 \tabularnewline
18 & 92.77 & 92.9743 & 93.2325 & 0.997231 & 0.997803 \tabularnewline
19 & 92.64 & 92.5163 & 93.2217 & 0.992434 & 1.00134 \tabularnewline
20 & 93.19 & 92.9327 & 93.2967 & 0.996099 & 1.00277 \tabularnewline
21 & 92.74 & 93.0994 & 93.4454 & 0.996297 & 0.99614 \tabularnewline
22 & 92.52 & 93.3936 & 93.5883 & 0.99792 & 0.990646 \tabularnewline
23 & 92.25 & 93.3651 & 93.6871 & 0.996564 & 0.988056 \tabularnewline
24 & 91.6 & 92.9351 & 93.8446 & 0.990309 & 0.985634 \tabularnewline
25 & 93.73 & 94.6351 & 94.0658 & 1.00605 & 0.990436 \tabularnewline
26 & 96.21 & 95.4546 & 94.3492 & 1.01172 & 1.00791 \tabularnewline
27 & 96.36 & 95.6722 & 94.7571 & 1.00966 & 1.00719 \tabularnewline
28 & 95.69 & 95.6132 & 95.24 & 1.00392 & 1.0008 \tabularnewline
29 & 95.07 & 95.9218 & 95.7492 & 1.0018 & 0.99112 \tabularnewline
30 & 95.5 & 96.0088 & 96.2754 & 0.997231 & 0.994701 \tabularnewline
31 & 95.22 & 96.1321 & 96.865 & 0.992434 & 0.990512 \tabularnewline
32 & 97.41 & 97.0661 & 97.4462 & 0.996099 & 1.00354 \tabularnewline
33 & 98.31 & 97.5956 & 97.9583 & 0.996297 & 1.00732 \tabularnewline
34 & 98.54 & 98.2265 & 98.4312 & 0.99792 & 1.00319 \tabularnewline
35 & 98.45 & 98.546 & 98.8858 & 0.996564 & 0.999026 \tabularnewline
36 & 98.03 & 98.3567 & 99.3192 & 0.990309 & 0.996679 \tabularnewline
37 & 101.45 & 100.24 & 99.6367 & 1.00605 & 1.01207 \tabularnewline
38 & 102.44 & 100.922 & 99.7533 & 1.01172 & 1.01504 \tabularnewline
39 & 102.42 & 100.67 & 99.7075 & 1.00966 & 1.01738 \tabularnewline
40 & 100.98 & 100.07 & 99.6796 & 1.00392 & 1.00909 \tabularnewline
41 & 100.69 & 99.9419 & 99.7621 & 1.0018 & 1.00749 \tabularnewline
42 & 100.28 & 99.6375 & 99.9142 & 0.997231 & 1.00645 \tabularnewline
43 & 98.06 & 99.2161 & 99.9725 & 0.992434 & 0.988348 \tabularnewline
44 & 97.37 & 99.4438 & 99.8333 & 0.996099 & 0.979146 \tabularnewline
45 & 97.25 & 99.2366 & 99.6054 & 0.996297 & 0.979981 \tabularnewline
46 & 98.93 & 99.2107 & 99.4175 & 0.99792 & 0.997171 \tabularnewline
47 & 100.04 & 98.9629 & 99.3042 & 0.996564 & 1.01088 \tabularnewline
48 & 100.09 & 98.2547 & 99.2162 & 0.990309 & 1.01868 \tabularnewline
49 & 100.79 & 99.8008 & 99.2004 & 1.00605 & 1.00991 \tabularnewline
50 & 99.76 & 100.419 & 99.2558 & 1.01172 & 0.99344 \tabularnewline
51 & 99.63 & 100.275 & 99.3163 & 1.00966 & 0.993563 \tabularnewline
52 & 99.26 & 99.6983 & 99.3092 & 1.00392 & 0.995603 \tabularnewline
53 & 99.69 & 99.3254 & 99.1467 & 1.0018 & 1.00367 \tabularnewline
54 & 99.17 & 98.6157 & 98.8896 & 0.997231 & 1.00562 \tabularnewline
55 & 98.79 & 97.8676 & 98.6138 & 0.992434 & 1.00943 \tabularnewline
56 & 97.97 & 97.9592 & 98.3429 & 0.996099 & 1.00011 \tabularnewline
57 & 98.1 & 97.711 & 98.0742 & 0.996297 & 1.00398 \tabularnewline
58 & 97.91 & 97.6032 & 97.8067 & 0.99792 & 1.00314 \tabularnewline
59 & 97.16 & 97.1936 & 97.5288 & 0.996564 & 0.999654 \tabularnewline
60 & 96.8 & 96.3051 & 97.2475 & 0.990309 & 1.00514 \tabularnewline
61 & 97.46 & 97.5866 & 96.9996 & 1.00605 & 0.998702 \tabularnewline
62 & 96.59 & 97.9333 & 96.7992 & 1.01172 & 0.986283 \tabularnewline
63 & 96.35 & 97.554 & 96.6208 & 1.00966 & 0.987658 \tabularnewline
64 & 96.12 & 96.82 & 96.4421 & 1.00392 & 0.99277 \tabularnewline
65 & 96.16 & 96.4611 & 96.2875 & 1.0018 & 0.996879 \tabularnewline
66 & 95.95 & 95.8999 & 96.1662 & 0.997231 & 1.00052 \tabularnewline
67 & 96.06 & NA & NA & 0.992434 & NA \tabularnewline
68 & 95.89 & NA & NA & 0.996099 & NA \tabularnewline
69 & 95.9 & NA & NA & 0.996297 & NA \tabularnewline
70 & 95.82 & NA & NA & 0.99792 & NA \tabularnewline
71 & 95.54 & NA & NA & 0.996564 & NA \tabularnewline
72 & 95.51 & NA & NA & 0.990309 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294727&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]89.65[/C][C]NA[/C][C]NA[/C][C]1.00605[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]90.65[/C][C]NA[/C][C]NA[/C][C]1.01172[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]89.34[/C][C]NA[/C][C]NA[/C][C]1.00966[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]89.15[/C][C]NA[/C][C]NA[/C][C]1.00392[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]88.82[/C][C]NA[/C][C]NA[/C][C]1.0018[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]88.82[/C][C]NA[/C][C]NA[/C][C]0.997231[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]91.97[/C][C]90.5687[/C][C]91.2592[/C][C]0.992434[/C][C]1.01547[/C][/ROW]
[ROW][C]8[/C][C]93.01[/C][C]91.2285[/C][C]91.5858[/C][C]0.996099[/C][C]1.01953[/C][/ROW]
[ROW][C]9[/C][C]93.24[/C][C]91.6207[/C][C]91.9613[/C][C]0.996297[/C][C]1.01767[/C][/ROW]
[ROW][C]10[/C][C]93.2[/C][C]92.1911[/C][C]92.3833[/C][C]0.99792[/C][C]1.01094[/C][/ROW]
[ROW][C]11[/C][C]93.19[/C][C]92.4985[/C][C]92.8175[/C][C]0.996564[/C][C]1.00748[/C][/ROW]
[ROW][C]12[/C][C]92.2[/C][C]92.2956[/C][C]93.1988[/C][C]0.990309[/C][C]0.998965[/C][/ROW]
[ROW][C]13[/C][C]93.39[/C][C]93.9565[/C][C]93.3912[/C][C]1.00605[/C][C]0.993971[/C][/ROW]
[ROW][C]14[/C][C]94.75[/C][C]94.5213[/C][C]93.4267[/C][C]1.01172[/C][C]1.00242[/C][/ROW]
[ROW][C]15[/C][C]94.25[/C][C]94.3155[/C][C]93.4133[/C][C]1.00966[/C][C]0.999306[/C][/ROW]
[ROW][C]16[/C][C]94.37[/C][C]93.73[/C][C]93.3642[/C][C]1.00392[/C][C]1.00683[/C][/ROW]
[ROW][C]17[/C][C]94.02[/C][C]93.4648[/C][C]93.2967[/C][C]1.0018[/C][C]1.00594[/C][/ROW]
[ROW][C]18[/C][C]92.77[/C][C]92.9743[/C][C]93.2325[/C][C]0.997231[/C][C]0.997803[/C][/ROW]
[ROW][C]19[/C][C]92.64[/C][C]92.5163[/C][C]93.2217[/C][C]0.992434[/C][C]1.00134[/C][/ROW]
[ROW][C]20[/C][C]93.19[/C][C]92.9327[/C][C]93.2967[/C][C]0.996099[/C][C]1.00277[/C][/ROW]
[ROW][C]21[/C][C]92.74[/C][C]93.0994[/C][C]93.4454[/C][C]0.996297[/C][C]0.99614[/C][/ROW]
[ROW][C]22[/C][C]92.52[/C][C]93.3936[/C][C]93.5883[/C][C]0.99792[/C][C]0.990646[/C][/ROW]
[ROW][C]23[/C][C]92.25[/C][C]93.3651[/C][C]93.6871[/C][C]0.996564[/C][C]0.988056[/C][/ROW]
[ROW][C]24[/C][C]91.6[/C][C]92.9351[/C][C]93.8446[/C][C]0.990309[/C][C]0.985634[/C][/ROW]
[ROW][C]25[/C][C]93.73[/C][C]94.6351[/C][C]94.0658[/C][C]1.00605[/C][C]0.990436[/C][/ROW]
[ROW][C]26[/C][C]96.21[/C][C]95.4546[/C][C]94.3492[/C][C]1.01172[/C][C]1.00791[/C][/ROW]
[ROW][C]27[/C][C]96.36[/C][C]95.6722[/C][C]94.7571[/C][C]1.00966[/C][C]1.00719[/C][/ROW]
[ROW][C]28[/C][C]95.69[/C][C]95.6132[/C][C]95.24[/C][C]1.00392[/C][C]1.0008[/C][/ROW]
[ROW][C]29[/C][C]95.07[/C][C]95.9218[/C][C]95.7492[/C][C]1.0018[/C][C]0.99112[/C][/ROW]
[ROW][C]30[/C][C]95.5[/C][C]96.0088[/C][C]96.2754[/C][C]0.997231[/C][C]0.994701[/C][/ROW]
[ROW][C]31[/C][C]95.22[/C][C]96.1321[/C][C]96.865[/C][C]0.992434[/C][C]0.990512[/C][/ROW]
[ROW][C]32[/C][C]97.41[/C][C]97.0661[/C][C]97.4462[/C][C]0.996099[/C][C]1.00354[/C][/ROW]
[ROW][C]33[/C][C]98.31[/C][C]97.5956[/C][C]97.9583[/C][C]0.996297[/C][C]1.00732[/C][/ROW]
[ROW][C]34[/C][C]98.54[/C][C]98.2265[/C][C]98.4312[/C][C]0.99792[/C][C]1.00319[/C][/ROW]
[ROW][C]35[/C][C]98.45[/C][C]98.546[/C][C]98.8858[/C][C]0.996564[/C][C]0.999026[/C][/ROW]
[ROW][C]36[/C][C]98.03[/C][C]98.3567[/C][C]99.3192[/C][C]0.990309[/C][C]0.996679[/C][/ROW]
[ROW][C]37[/C][C]101.45[/C][C]100.24[/C][C]99.6367[/C][C]1.00605[/C][C]1.01207[/C][/ROW]
[ROW][C]38[/C][C]102.44[/C][C]100.922[/C][C]99.7533[/C][C]1.01172[/C][C]1.01504[/C][/ROW]
[ROW][C]39[/C][C]102.42[/C][C]100.67[/C][C]99.7075[/C][C]1.00966[/C][C]1.01738[/C][/ROW]
[ROW][C]40[/C][C]100.98[/C][C]100.07[/C][C]99.6796[/C][C]1.00392[/C][C]1.00909[/C][/ROW]
[ROW][C]41[/C][C]100.69[/C][C]99.9419[/C][C]99.7621[/C][C]1.0018[/C][C]1.00749[/C][/ROW]
[ROW][C]42[/C][C]100.28[/C][C]99.6375[/C][C]99.9142[/C][C]0.997231[/C][C]1.00645[/C][/ROW]
[ROW][C]43[/C][C]98.06[/C][C]99.2161[/C][C]99.9725[/C][C]0.992434[/C][C]0.988348[/C][/ROW]
[ROW][C]44[/C][C]97.37[/C][C]99.4438[/C][C]99.8333[/C][C]0.996099[/C][C]0.979146[/C][/ROW]
[ROW][C]45[/C][C]97.25[/C][C]99.2366[/C][C]99.6054[/C][C]0.996297[/C][C]0.979981[/C][/ROW]
[ROW][C]46[/C][C]98.93[/C][C]99.2107[/C][C]99.4175[/C][C]0.99792[/C][C]0.997171[/C][/ROW]
[ROW][C]47[/C][C]100.04[/C][C]98.9629[/C][C]99.3042[/C][C]0.996564[/C][C]1.01088[/C][/ROW]
[ROW][C]48[/C][C]100.09[/C][C]98.2547[/C][C]99.2162[/C][C]0.990309[/C][C]1.01868[/C][/ROW]
[ROW][C]49[/C][C]100.79[/C][C]99.8008[/C][C]99.2004[/C][C]1.00605[/C][C]1.00991[/C][/ROW]
[ROW][C]50[/C][C]99.76[/C][C]100.419[/C][C]99.2558[/C][C]1.01172[/C][C]0.99344[/C][/ROW]
[ROW][C]51[/C][C]99.63[/C][C]100.275[/C][C]99.3163[/C][C]1.00966[/C][C]0.993563[/C][/ROW]
[ROW][C]52[/C][C]99.26[/C][C]99.6983[/C][C]99.3092[/C][C]1.00392[/C][C]0.995603[/C][/ROW]
[ROW][C]53[/C][C]99.69[/C][C]99.3254[/C][C]99.1467[/C][C]1.0018[/C][C]1.00367[/C][/ROW]
[ROW][C]54[/C][C]99.17[/C][C]98.6157[/C][C]98.8896[/C][C]0.997231[/C][C]1.00562[/C][/ROW]
[ROW][C]55[/C][C]98.79[/C][C]97.8676[/C][C]98.6138[/C][C]0.992434[/C][C]1.00943[/C][/ROW]
[ROW][C]56[/C][C]97.97[/C][C]97.9592[/C][C]98.3429[/C][C]0.996099[/C][C]1.00011[/C][/ROW]
[ROW][C]57[/C][C]98.1[/C][C]97.711[/C][C]98.0742[/C][C]0.996297[/C][C]1.00398[/C][/ROW]
[ROW][C]58[/C][C]97.91[/C][C]97.6032[/C][C]97.8067[/C][C]0.99792[/C][C]1.00314[/C][/ROW]
[ROW][C]59[/C][C]97.16[/C][C]97.1936[/C][C]97.5288[/C][C]0.996564[/C][C]0.999654[/C][/ROW]
[ROW][C]60[/C][C]96.8[/C][C]96.3051[/C][C]97.2475[/C][C]0.990309[/C][C]1.00514[/C][/ROW]
[ROW][C]61[/C][C]97.46[/C][C]97.5866[/C][C]96.9996[/C][C]1.00605[/C][C]0.998702[/C][/ROW]
[ROW][C]62[/C][C]96.59[/C][C]97.9333[/C][C]96.7992[/C][C]1.01172[/C][C]0.986283[/C][/ROW]
[ROW][C]63[/C][C]96.35[/C][C]97.554[/C][C]96.6208[/C][C]1.00966[/C][C]0.987658[/C][/ROW]
[ROW][C]64[/C][C]96.12[/C][C]96.82[/C][C]96.4421[/C][C]1.00392[/C][C]0.99277[/C][/ROW]
[ROW][C]65[/C][C]96.16[/C][C]96.4611[/C][C]96.2875[/C][C]1.0018[/C][C]0.996879[/C][/ROW]
[ROW][C]66[/C][C]95.95[/C][C]95.8999[/C][C]96.1662[/C][C]0.997231[/C][C]1.00052[/C][/ROW]
[ROW][C]67[/C][C]96.06[/C][C]NA[/C][C]NA[/C][C]0.992434[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]95.89[/C][C]NA[/C][C]NA[/C][C]0.996099[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]95.9[/C][C]NA[/C][C]NA[/C][C]0.996297[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]95.82[/C][C]NA[/C][C]NA[/C][C]0.99792[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]95.54[/C][C]NA[/C][C]NA[/C][C]0.996564[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]95.51[/C][C]NA[/C][C]NA[/C][C]0.990309[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294727&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294727&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	89.65	NA	NA	1.00605	NA
2	90.65	NA	NA	1.01172	NA
3	89.34	NA	NA	1.00966	NA
4	89.15	NA	NA	1.00392	NA
5	88.82	NA	NA	1.0018	NA
6	88.82	NA	NA	0.997231	NA
7	91.97	90.5687	91.2592	0.992434	1.01547
8	93.01	91.2285	91.5858	0.996099	1.01953
9	93.24	91.6207	91.9613	0.996297	1.01767
10	93.2	92.1911	92.3833	0.99792	1.01094
11	93.19	92.4985	92.8175	0.996564	1.00748
12	92.2	92.2956	93.1988	0.990309	0.998965
13	93.39	93.9565	93.3912	1.00605	0.993971
14	94.75	94.5213	93.4267	1.01172	1.00242
15	94.25	94.3155	93.4133	1.00966	0.999306
16	94.37	93.73	93.3642	1.00392	1.00683
17	94.02	93.4648	93.2967	1.0018	1.00594
18	92.77	92.9743	93.2325	0.997231	0.997803
19	92.64	92.5163	93.2217	0.992434	1.00134
20	93.19	92.9327	93.2967	0.996099	1.00277
21	92.74	93.0994	93.4454	0.996297	0.99614
22	92.52	93.3936	93.5883	0.99792	0.990646
23	92.25	93.3651	93.6871	0.996564	0.988056
24	91.6	92.9351	93.8446	0.990309	0.985634
25	93.73	94.6351	94.0658	1.00605	0.990436
26	96.21	95.4546	94.3492	1.01172	1.00791
27	96.36	95.6722	94.7571	1.00966	1.00719
28	95.69	95.6132	95.24	1.00392	1.0008
29	95.07	95.9218	95.7492	1.0018	0.99112
30	95.5	96.0088	96.2754	0.997231	0.994701
31	95.22	96.1321	96.865	0.992434	0.990512
32	97.41	97.0661	97.4462	0.996099	1.00354
33	98.31	97.5956	97.9583	0.996297	1.00732
34	98.54	98.2265	98.4312	0.99792	1.00319
35	98.45	98.546	98.8858	0.996564	0.999026
36	98.03	98.3567	99.3192	0.990309	0.996679
37	101.45	100.24	99.6367	1.00605	1.01207
38	102.44	100.922	99.7533	1.01172	1.01504
39	102.42	100.67	99.7075	1.00966	1.01738
40	100.98	100.07	99.6796	1.00392	1.00909
41	100.69	99.9419	99.7621	1.0018	1.00749
42	100.28	99.6375	99.9142	0.997231	1.00645
43	98.06	99.2161	99.9725	0.992434	0.988348
44	97.37	99.4438	99.8333	0.996099	0.979146
45	97.25	99.2366	99.6054	0.996297	0.979981
46	98.93	99.2107	99.4175	0.99792	0.997171
47	100.04	98.9629	99.3042	0.996564	1.01088
48	100.09	98.2547	99.2162	0.990309	1.01868
49	100.79	99.8008	99.2004	1.00605	1.00991
50	99.76	100.419	99.2558	1.01172	0.99344
51	99.63	100.275	99.3163	1.00966	0.993563
52	99.26	99.6983	99.3092	1.00392	0.995603
53	99.69	99.3254	99.1467	1.0018	1.00367
54	99.17	98.6157	98.8896	0.997231	1.00562
55	98.79	97.8676	98.6138	0.992434	1.00943
56	97.97	97.9592	98.3429	0.996099	1.00011
57	98.1	97.711	98.0742	0.996297	1.00398
58	97.91	97.6032	97.8067	0.99792	1.00314
59	97.16	97.1936	97.5288	0.996564	0.999654
60	96.8	96.3051	97.2475	0.990309	1.00514
61	97.46	97.5866	96.9996	1.00605	0.998702
62	96.59	97.9333	96.7992	1.01172	0.986283
63	96.35	97.554	96.6208	1.00966	0.987658
64	96.12	96.82	96.4421	1.00392	0.99277
65	96.16	96.4611	96.2875	1.0018	0.996879
66	95.95	95.8999	96.1662	0.997231	1.00052
67	96.06	NA	NA	0.992434	NA
68	95.89	NA	NA	0.996099	NA
69	95.9	NA	NA	0.996297	NA
70	95.82	NA	NA	0.99792	NA
71	95.54	NA	NA	0.996564	NA
72	95.51	NA	NA	0.990309	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