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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Thu, 26 Nov 2015 14:02:51 +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/26/t1448546587js2s02urexu2yz9.htm/, Retrieved Tue, 14 May 2024 01:17:35 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=284228, Retrieved Tue, 14 May 2024 01:17:35 +0000

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-       [Classical Decomposition] [] [2015-11-26 14:02:51] [88f551c1d3f4ff2d65b8ab6790c1e3d2] [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=284228&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=284228&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284228&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	94.94	NA	NA	-0.202562	NA
2	95.11	NA	NA	-0.111479	NA
3	95.53	NA	NA	-0.228063	NA
4	95.89	NA	NA	0.219354	NA
5	95.99	NA	NA	0.381771	NA
6	95.42	NA	NA	0.374271	NA
7	95.42	95.8455	95.6821	0.163438	-0.425521
8	95.45	95.6998	95.7713	-0.0714792	-0.249771
9	95.99	95.7415	95.8288	-0.0872292	0.248479
10	95.99	95.7263	95.8454	-0.119146	0.263729
11	95.97	95.7246	95.8529	-0.128312	0.245396
12	95.97	95.6949	95.8854	-0.190562	0.275146
13	95.97	95.7437	95.9462	-0.202562	0.226313
14	96.22	95.8877	95.9992	-0.111479	0.332312
15	95.8	95.7974	96.0254	-0.228063	0.00264583
16	96.02	96.261	96.0417	0.219354	-0.241021
17	96.04	96.4497	96.0679	0.381771	-0.409687
18	96.15	96.4755	96.1012	0.374271	-0.325521
19	96.15	96.3039	96.1404	0.163438	-0.153854
20	95.99	96.1139	96.1854	-0.0714792	-0.123937
21	96.08	96.1611	96.2483	-0.0872292	-0.0811042
22	96.29	96.21	96.3292	-0.119146	0.0799792
23	96.3	96.3109	96.4392	-0.128312	-0.0108542
24	96.44	96.3761	96.5667	-0.190562	0.0638958
25	96.44	96.4858	96.6883	-0.202562	-0.0457708
26	96.83	96.7052	96.8167	-0.111479	0.124813
27	96.7	96.7174	96.9454	-0.228063	-0.0173542
28	97.06	97.2798	97.0604	0.219354	-0.219771
29	97.64	97.558	97.1762	0.381771	0.0819792
30	97.61	97.6689	97.2946	0.374271	-0.0588542
31	97.61	97.5705	97.4071	0.163438	0.0394792
32	97.61	97.4319	97.5033	-0.0714792	0.178146
33	97.55	97.5103	97.5975	-0.0872292	0.0397292
34	97.58	97.5871	97.7062	-0.119146	-0.00710417
35	97.79	97.6759	97.8042	-0.128312	0.114146
36	97.79	97.7103	97.9008	-0.190562	0.0797292
37	97.79	97.8049	98.0075	-0.202562	-0.0149375
38	97.79	98.0027	98.1142	-0.111479	-0.212687
39	98	97.9949	98.2229	-0.228063	0.00514583
40	98.37	98.5556	98.3363	0.219354	-0.185604
41	98.68	98.8284	98.4467	0.381771	-0.148438
42	98.89	98.9259	98.5517	0.374271	-0.0359375
43	98.89	98.818	98.6546	0.163438	0.0719792
44	98.89	98.6852	98.7567	-0.0714792	0.204813
45	98.88	98.7711	98.8583	-0.0872292	0.108896
46	98.97	98.8696	98.9887	-0.119146	0.100396
47	99.05	99.0288	99.1571	-0.128312	0.0212292
48	99.05	99.1319	99.3225	-0.190562	-0.0819375
49	99	99.2749	99.4775	-0.202562	-0.274937
50	99.03	99.4969	99.6083	-0.111479	-0.466854
51	99.2	99.4794	99.7075	-0.228063	-0.279437
52	100.3	100.013	99.7933	0.219354	0.287313
53	100.79	100.256	99.8746	0.381771	0.533646
54	100.75	100.331	99.9571	0.374271	0.418646
55	100.75	100.224	100.06	0.163438	0.526146
56	100.17	100.121	100.192	-0.0714792	0.0489792
57	99.98	100.238	100.325	-0.0872292	-0.257771
58	99.93	100.309	100.428	-0.119146	-0.378771
59	100.04	100.352	100.48	-0.128312	-0.311687
60	100.04	100.319	100.509	-0.190562	-0.278604
61	100.49	100.322	100.525	-0.202562	0.167563
62	100.71	100.429	100.541	-0.111479	0.280646
63	100.7	100.353	100.581	-0.228063	0.347229
64	101.27	100.853	100.633	0.219354	0.417313
65	101.07	101.069	100.687	0.381771	0.000729167
66	101.17	101.11	100.736	0.374271	0.0598958
67	100.71	NA	NA	0.163438	NA
68	100.59	NA	NA	-0.0714792	NA
69	100.52	NA	NA	-0.0872292	NA
70	100.65	NA	NA	-0.119146	NA
71	100.62	NA	NA	-0.128312	NA
72	100.62	NA	NA	-0.190562	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 94.94 & NA & NA & -0.202562 & NA \tabularnewline
2 & 95.11 & NA & NA & -0.111479 & NA \tabularnewline
3 & 95.53 & NA & NA & -0.228063 & NA \tabularnewline
4 & 95.89 & NA & NA & 0.219354 & NA \tabularnewline
5 & 95.99 & NA & NA & 0.381771 & NA \tabularnewline
6 & 95.42 & NA & NA & 0.374271 & NA \tabularnewline
7 & 95.42 & 95.8455 & 95.6821 & 0.163438 & -0.425521 \tabularnewline
8 & 95.45 & 95.6998 & 95.7713 & -0.0714792 & -0.249771 \tabularnewline
9 & 95.99 & 95.7415 & 95.8288 & -0.0872292 & 0.248479 \tabularnewline
10 & 95.99 & 95.7263 & 95.8454 & -0.119146 & 0.263729 \tabularnewline
11 & 95.97 & 95.7246 & 95.8529 & -0.128312 & 0.245396 \tabularnewline
12 & 95.97 & 95.6949 & 95.8854 & -0.190562 & 0.275146 \tabularnewline
13 & 95.97 & 95.7437 & 95.9462 & -0.202562 & 0.226313 \tabularnewline
14 & 96.22 & 95.8877 & 95.9992 & -0.111479 & 0.332312 \tabularnewline
15 & 95.8 & 95.7974 & 96.0254 & -0.228063 & 0.00264583 \tabularnewline
16 & 96.02 & 96.261 & 96.0417 & 0.219354 & -0.241021 \tabularnewline
17 & 96.04 & 96.4497 & 96.0679 & 0.381771 & -0.409687 \tabularnewline
18 & 96.15 & 96.4755 & 96.1012 & 0.374271 & -0.325521 \tabularnewline
19 & 96.15 & 96.3039 & 96.1404 & 0.163438 & -0.153854 \tabularnewline
20 & 95.99 & 96.1139 & 96.1854 & -0.0714792 & -0.123937 \tabularnewline
21 & 96.08 & 96.1611 & 96.2483 & -0.0872292 & -0.0811042 \tabularnewline
22 & 96.29 & 96.21 & 96.3292 & -0.119146 & 0.0799792 \tabularnewline
23 & 96.3 & 96.3109 & 96.4392 & -0.128312 & -0.0108542 \tabularnewline
24 & 96.44 & 96.3761 & 96.5667 & -0.190562 & 0.0638958 \tabularnewline
25 & 96.44 & 96.4858 & 96.6883 & -0.202562 & -0.0457708 \tabularnewline
26 & 96.83 & 96.7052 & 96.8167 & -0.111479 & 0.124813 \tabularnewline
27 & 96.7 & 96.7174 & 96.9454 & -0.228063 & -0.0173542 \tabularnewline
28 & 97.06 & 97.2798 & 97.0604 & 0.219354 & -0.219771 \tabularnewline
29 & 97.64 & 97.558 & 97.1762 & 0.381771 & 0.0819792 \tabularnewline
30 & 97.61 & 97.6689 & 97.2946 & 0.374271 & -0.0588542 \tabularnewline
31 & 97.61 & 97.5705 & 97.4071 & 0.163438 & 0.0394792 \tabularnewline
32 & 97.61 & 97.4319 & 97.5033 & -0.0714792 & 0.178146 \tabularnewline
33 & 97.55 & 97.5103 & 97.5975 & -0.0872292 & 0.0397292 \tabularnewline
34 & 97.58 & 97.5871 & 97.7062 & -0.119146 & -0.00710417 \tabularnewline
35 & 97.79 & 97.6759 & 97.8042 & -0.128312 & 0.114146 \tabularnewline
36 & 97.79 & 97.7103 & 97.9008 & -0.190562 & 0.0797292 \tabularnewline
37 & 97.79 & 97.8049 & 98.0075 & -0.202562 & -0.0149375 \tabularnewline
38 & 97.79 & 98.0027 & 98.1142 & -0.111479 & -0.212687 \tabularnewline
39 & 98 & 97.9949 & 98.2229 & -0.228063 & 0.00514583 \tabularnewline
40 & 98.37 & 98.5556 & 98.3363 & 0.219354 & -0.185604 \tabularnewline
41 & 98.68 & 98.8284 & 98.4467 & 0.381771 & -0.148438 \tabularnewline
42 & 98.89 & 98.9259 & 98.5517 & 0.374271 & -0.0359375 \tabularnewline
43 & 98.89 & 98.818 & 98.6546 & 0.163438 & 0.0719792 \tabularnewline
44 & 98.89 & 98.6852 & 98.7567 & -0.0714792 & 0.204813 \tabularnewline
45 & 98.88 & 98.7711 & 98.8583 & -0.0872292 & 0.108896 \tabularnewline
46 & 98.97 & 98.8696 & 98.9887 & -0.119146 & 0.100396 \tabularnewline
47 & 99.05 & 99.0288 & 99.1571 & -0.128312 & 0.0212292 \tabularnewline
48 & 99.05 & 99.1319 & 99.3225 & -0.190562 & -0.0819375 \tabularnewline
49 & 99 & 99.2749 & 99.4775 & -0.202562 & -0.274937 \tabularnewline
50 & 99.03 & 99.4969 & 99.6083 & -0.111479 & -0.466854 \tabularnewline
51 & 99.2 & 99.4794 & 99.7075 & -0.228063 & -0.279437 \tabularnewline
52 & 100.3 & 100.013 & 99.7933 & 0.219354 & 0.287313 \tabularnewline
53 & 100.79 & 100.256 & 99.8746 & 0.381771 & 0.533646 \tabularnewline
54 & 100.75 & 100.331 & 99.9571 & 0.374271 & 0.418646 \tabularnewline
55 & 100.75 & 100.224 & 100.06 & 0.163438 & 0.526146 \tabularnewline
56 & 100.17 & 100.121 & 100.192 & -0.0714792 & 0.0489792 \tabularnewline
57 & 99.98 & 100.238 & 100.325 & -0.0872292 & -0.257771 \tabularnewline
58 & 99.93 & 100.309 & 100.428 & -0.119146 & -0.378771 \tabularnewline
59 & 100.04 & 100.352 & 100.48 & -0.128312 & -0.311687 \tabularnewline
60 & 100.04 & 100.319 & 100.509 & -0.190562 & -0.278604 \tabularnewline
61 & 100.49 & 100.322 & 100.525 & -0.202562 & 0.167563 \tabularnewline
62 & 100.71 & 100.429 & 100.541 & -0.111479 & 0.280646 \tabularnewline
63 & 100.7 & 100.353 & 100.581 & -0.228063 & 0.347229 \tabularnewline
64 & 101.27 & 100.853 & 100.633 & 0.219354 & 0.417313 \tabularnewline
65 & 101.07 & 101.069 & 100.687 & 0.381771 & 0.000729167 \tabularnewline
66 & 101.17 & 101.11 & 100.736 & 0.374271 & 0.0598958 \tabularnewline
67 & 100.71 & NA & NA & 0.163438 & NA \tabularnewline
68 & 100.59 & NA & NA & -0.0714792 & NA \tabularnewline
69 & 100.52 & NA & NA & -0.0872292 & NA \tabularnewline
70 & 100.65 & NA & NA & -0.119146 & NA \tabularnewline
71 & 100.62 & NA & NA & -0.128312 & NA \tabularnewline
72 & 100.62 & NA & NA & -0.190562 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=284228&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]94.94[/C][C]NA[/C][C]NA[/C][C]-0.202562[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]95.11[/C][C]NA[/C][C]NA[/C][C]-0.111479[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]95.53[/C][C]NA[/C][C]NA[/C][C]-0.228063[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]95.89[/C][C]NA[/C][C]NA[/C][C]0.219354[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]95.99[/C][C]NA[/C][C]NA[/C][C]0.381771[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]95.42[/C][C]NA[/C][C]NA[/C][C]0.374271[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]95.42[/C][C]95.8455[/C][C]95.6821[/C][C]0.163438[/C][C]-0.425521[/C][/ROW]
[ROW][C]8[/C][C]95.45[/C][C]95.6998[/C][C]95.7713[/C][C]-0.0714792[/C][C]-0.249771[/C][/ROW]
[ROW][C]9[/C][C]95.99[/C][C]95.7415[/C][C]95.8288[/C][C]-0.0872292[/C][C]0.248479[/C][/ROW]
[ROW][C]10[/C][C]95.99[/C][C]95.7263[/C][C]95.8454[/C][C]-0.119146[/C][C]0.263729[/C][/ROW]
[ROW][C]11[/C][C]95.97[/C][C]95.7246[/C][C]95.8529[/C][C]-0.128312[/C][C]0.245396[/C][/ROW]
[ROW][C]12[/C][C]95.97[/C][C]95.6949[/C][C]95.8854[/C][C]-0.190562[/C][C]0.275146[/C][/ROW]
[ROW][C]13[/C][C]95.97[/C][C]95.7437[/C][C]95.9462[/C][C]-0.202562[/C][C]0.226313[/C][/ROW]
[ROW][C]14[/C][C]96.22[/C][C]95.8877[/C][C]95.9992[/C][C]-0.111479[/C][C]0.332312[/C][/ROW]
[ROW][C]15[/C][C]95.8[/C][C]95.7974[/C][C]96.0254[/C][C]-0.228063[/C][C]0.00264583[/C][/ROW]
[ROW][C]16[/C][C]96.02[/C][C]96.261[/C][C]96.0417[/C][C]0.219354[/C][C]-0.241021[/C][/ROW]
[ROW][C]17[/C][C]96.04[/C][C]96.4497[/C][C]96.0679[/C][C]0.381771[/C][C]-0.409687[/C][/ROW]
[ROW][C]18[/C][C]96.15[/C][C]96.4755[/C][C]96.1012[/C][C]0.374271[/C][C]-0.325521[/C][/ROW]
[ROW][C]19[/C][C]96.15[/C][C]96.3039[/C][C]96.1404[/C][C]0.163438[/C][C]-0.153854[/C][/ROW]
[ROW][C]20[/C][C]95.99[/C][C]96.1139[/C][C]96.1854[/C][C]-0.0714792[/C][C]-0.123937[/C][/ROW]
[ROW][C]21[/C][C]96.08[/C][C]96.1611[/C][C]96.2483[/C][C]-0.0872292[/C][C]-0.0811042[/C][/ROW]
[ROW][C]22[/C][C]96.29[/C][C]96.21[/C][C]96.3292[/C][C]-0.119146[/C][C]0.0799792[/C][/ROW]
[ROW][C]23[/C][C]96.3[/C][C]96.3109[/C][C]96.4392[/C][C]-0.128312[/C][C]-0.0108542[/C][/ROW]
[ROW][C]24[/C][C]96.44[/C][C]96.3761[/C][C]96.5667[/C][C]-0.190562[/C][C]0.0638958[/C][/ROW]
[ROW][C]25[/C][C]96.44[/C][C]96.4858[/C][C]96.6883[/C][C]-0.202562[/C][C]-0.0457708[/C][/ROW]
[ROW][C]26[/C][C]96.83[/C][C]96.7052[/C][C]96.8167[/C][C]-0.111479[/C][C]0.124813[/C][/ROW]
[ROW][C]27[/C][C]96.7[/C][C]96.7174[/C][C]96.9454[/C][C]-0.228063[/C][C]-0.0173542[/C][/ROW]
[ROW][C]28[/C][C]97.06[/C][C]97.2798[/C][C]97.0604[/C][C]0.219354[/C][C]-0.219771[/C][/ROW]
[ROW][C]29[/C][C]97.64[/C][C]97.558[/C][C]97.1762[/C][C]0.381771[/C][C]0.0819792[/C][/ROW]
[ROW][C]30[/C][C]97.61[/C][C]97.6689[/C][C]97.2946[/C][C]0.374271[/C][C]-0.0588542[/C][/ROW]
[ROW][C]31[/C][C]97.61[/C][C]97.5705[/C][C]97.4071[/C][C]0.163438[/C][C]0.0394792[/C][/ROW]
[ROW][C]32[/C][C]97.61[/C][C]97.4319[/C][C]97.5033[/C][C]-0.0714792[/C][C]0.178146[/C][/ROW]
[ROW][C]33[/C][C]97.55[/C][C]97.5103[/C][C]97.5975[/C][C]-0.0872292[/C][C]0.0397292[/C][/ROW]
[ROW][C]34[/C][C]97.58[/C][C]97.5871[/C][C]97.7062[/C][C]-0.119146[/C][C]-0.00710417[/C][/ROW]
[ROW][C]35[/C][C]97.79[/C][C]97.6759[/C][C]97.8042[/C][C]-0.128312[/C][C]0.114146[/C][/ROW]
[ROW][C]36[/C][C]97.79[/C][C]97.7103[/C][C]97.9008[/C][C]-0.190562[/C][C]0.0797292[/C][/ROW]
[ROW][C]37[/C][C]97.79[/C][C]97.8049[/C][C]98.0075[/C][C]-0.202562[/C][C]-0.0149375[/C][/ROW]
[ROW][C]38[/C][C]97.79[/C][C]98.0027[/C][C]98.1142[/C][C]-0.111479[/C][C]-0.212687[/C][/ROW]
[ROW][C]39[/C][C]98[/C][C]97.9949[/C][C]98.2229[/C][C]-0.228063[/C][C]0.00514583[/C][/ROW]
[ROW][C]40[/C][C]98.37[/C][C]98.5556[/C][C]98.3363[/C][C]0.219354[/C][C]-0.185604[/C][/ROW]
[ROW][C]41[/C][C]98.68[/C][C]98.8284[/C][C]98.4467[/C][C]0.381771[/C][C]-0.148438[/C][/ROW]
[ROW][C]42[/C][C]98.89[/C][C]98.9259[/C][C]98.5517[/C][C]0.374271[/C][C]-0.0359375[/C][/ROW]
[ROW][C]43[/C][C]98.89[/C][C]98.818[/C][C]98.6546[/C][C]0.163438[/C][C]0.0719792[/C][/ROW]
[ROW][C]44[/C][C]98.89[/C][C]98.6852[/C][C]98.7567[/C][C]-0.0714792[/C][C]0.204813[/C][/ROW]
[ROW][C]45[/C][C]98.88[/C][C]98.7711[/C][C]98.8583[/C][C]-0.0872292[/C][C]0.108896[/C][/ROW]
[ROW][C]46[/C][C]98.97[/C][C]98.8696[/C][C]98.9887[/C][C]-0.119146[/C][C]0.100396[/C][/ROW]
[ROW][C]47[/C][C]99.05[/C][C]99.0288[/C][C]99.1571[/C][C]-0.128312[/C][C]0.0212292[/C][/ROW]
[ROW][C]48[/C][C]99.05[/C][C]99.1319[/C][C]99.3225[/C][C]-0.190562[/C][C]-0.0819375[/C][/ROW]
[ROW][C]49[/C][C]99[/C][C]99.2749[/C][C]99.4775[/C][C]-0.202562[/C][C]-0.274937[/C][/ROW]
[ROW][C]50[/C][C]99.03[/C][C]99.4969[/C][C]99.6083[/C][C]-0.111479[/C][C]-0.466854[/C][/ROW]
[ROW][C]51[/C][C]99.2[/C][C]99.4794[/C][C]99.7075[/C][C]-0.228063[/C][C]-0.279437[/C][/ROW]
[ROW][C]52[/C][C]100.3[/C][C]100.013[/C][C]99.7933[/C][C]0.219354[/C][C]0.287313[/C][/ROW]
[ROW][C]53[/C][C]100.79[/C][C]100.256[/C][C]99.8746[/C][C]0.381771[/C][C]0.533646[/C][/ROW]
[ROW][C]54[/C][C]100.75[/C][C]100.331[/C][C]99.9571[/C][C]0.374271[/C][C]0.418646[/C][/ROW]
[ROW][C]55[/C][C]100.75[/C][C]100.224[/C][C]100.06[/C][C]0.163438[/C][C]0.526146[/C][/ROW]
[ROW][C]56[/C][C]100.17[/C][C]100.121[/C][C]100.192[/C][C]-0.0714792[/C][C]0.0489792[/C][/ROW]
[ROW][C]57[/C][C]99.98[/C][C]100.238[/C][C]100.325[/C][C]-0.0872292[/C][C]-0.257771[/C][/ROW]
[ROW][C]58[/C][C]99.93[/C][C]100.309[/C][C]100.428[/C][C]-0.119146[/C][C]-0.378771[/C][/ROW]
[ROW][C]59[/C][C]100.04[/C][C]100.352[/C][C]100.48[/C][C]-0.128312[/C][C]-0.311687[/C][/ROW]
[ROW][C]60[/C][C]100.04[/C][C]100.319[/C][C]100.509[/C][C]-0.190562[/C][C]-0.278604[/C][/ROW]
[ROW][C]61[/C][C]100.49[/C][C]100.322[/C][C]100.525[/C][C]-0.202562[/C][C]0.167563[/C][/ROW]
[ROW][C]62[/C][C]100.71[/C][C]100.429[/C][C]100.541[/C][C]-0.111479[/C][C]0.280646[/C][/ROW]
[ROW][C]63[/C][C]100.7[/C][C]100.353[/C][C]100.581[/C][C]-0.228063[/C][C]0.347229[/C][/ROW]
[ROW][C]64[/C][C]101.27[/C][C]100.853[/C][C]100.633[/C][C]0.219354[/C][C]0.417313[/C][/ROW]
[ROW][C]65[/C][C]101.07[/C][C]101.069[/C][C]100.687[/C][C]0.381771[/C][C]0.000729167[/C][/ROW]
[ROW][C]66[/C][C]101.17[/C][C]101.11[/C][C]100.736[/C][C]0.374271[/C][C]0.0598958[/C][/ROW]
[ROW][C]67[/C][C]100.71[/C][C]NA[/C][C]NA[/C][C]0.163438[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]100.59[/C][C]NA[/C][C]NA[/C][C]-0.0714792[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]100.52[/C][C]NA[/C][C]NA[/C][C]-0.0872292[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]100.65[/C][C]NA[/C][C]NA[/C][C]-0.119146[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]100.62[/C][C]NA[/C][C]NA[/C][C]-0.128312[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]100.62[/C][C]NA[/C][C]NA[/C][C]-0.190562[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=284228&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=284228&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	94.94	NA	NA	-0.202562	NA
2	95.11	NA	NA	-0.111479	NA
3	95.53	NA	NA	-0.228063	NA
4	95.89	NA	NA	0.219354	NA
5	95.99	NA	NA	0.381771	NA
6	95.42	NA	NA	0.374271	NA
7	95.42	95.8455	95.6821	0.163438	-0.425521
8	95.45	95.6998	95.7713	-0.0714792	-0.249771
9	95.99	95.7415	95.8288	-0.0872292	0.248479
10	95.99	95.7263	95.8454	-0.119146	0.263729
11	95.97	95.7246	95.8529	-0.128312	0.245396
12	95.97	95.6949	95.8854	-0.190562	0.275146
13	95.97	95.7437	95.9462	-0.202562	0.226313
14	96.22	95.8877	95.9992	-0.111479	0.332312
15	95.8	95.7974	96.0254	-0.228063	0.00264583
16	96.02	96.261	96.0417	0.219354	-0.241021
17	96.04	96.4497	96.0679	0.381771	-0.409687
18	96.15	96.4755	96.1012	0.374271	-0.325521
19	96.15	96.3039	96.1404	0.163438	-0.153854
20	95.99	96.1139	96.1854	-0.0714792	-0.123937
21	96.08	96.1611	96.2483	-0.0872292	-0.0811042
22	96.29	96.21	96.3292	-0.119146	0.0799792
23	96.3	96.3109	96.4392	-0.128312	-0.0108542
24	96.44	96.3761	96.5667	-0.190562	0.0638958
25	96.44	96.4858	96.6883	-0.202562	-0.0457708
26	96.83	96.7052	96.8167	-0.111479	0.124813
27	96.7	96.7174	96.9454	-0.228063	-0.0173542
28	97.06	97.2798	97.0604	0.219354	-0.219771
29	97.64	97.558	97.1762	0.381771	0.0819792
30	97.61	97.6689	97.2946	0.374271	-0.0588542
31	97.61	97.5705	97.4071	0.163438	0.0394792
32	97.61	97.4319	97.5033	-0.0714792	0.178146
33	97.55	97.5103	97.5975	-0.0872292	0.0397292
34	97.58	97.5871	97.7062	-0.119146	-0.00710417
35	97.79	97.6759	97.8042	-0.128312	0.114146
36	97.79	97.7103	97.9008	-0.190562	0.0797292
37	97.79	97.8049	98.0075	-0.202562	-0.0149375
38	97.79	98.0027	98.1142	-0.111479	-0.212687
39	98	97.9949	98.2229	-0.228063	0.00514583
40	98.37	98.5556	98.3363	0.219354	-0.185604
41	98.68	98.8284	98.4467	0.381771	-0.148438
42	98.89	98.9259	98.5517	0.374271	-0.0359375
43	98.89	98.818	98.6546	0.163438	0.0719792
44	98.89	98.6852	98.7567	-0.0714792	0.204813
45	98.88	98.7711	98.8583	-0.0872292	0.108896
46	98.97	98.8696	98.9887	-0.119146	0.100396
47	99.05	99.0288	99.1571	-0.128312	0.0212292
48	99.05	99.1319	99.3225	-0.190562	-0.0819375
49	99	99.2749	99.4775	-0.202562	-0.274937
50	99.03	99.4969	99.6083	-0.111479	-0.466854
51	99.2	99.4794	99.7075	-0.228063	-0.279437
52	100.3	100.013	99.7933	0.219354	0.287313
53	100.79	100.256	99.8746	0.381771	0.533646
54	100.75	100.331	99.9571	0.374271	0.418646
55	100.75	100.224	100.06	0.163438	0.526146
56	100.17	100.121	100.192	-0.0714792	0.0489792
57	99.98	100.238	100.325	-0.0872292	-0.257771
58	99.93	100.309	100.428	-0.119146	-0.378771
59	100.04	100.352	100.48	-0.128312	-0.311687
60	100.04	100.319	100.509	-0.190562	-0.278604
61	100.49	100.322	100.525	-0.202562	0.167563
62	100.71	100.429	100.541	-0.111479	0.280646
63	100.7	100.353	100.581	-0.228063	0.347229
64	101.27	100.853	100.633	0.219354	0.417313
65	101.07	101.069	100.687	0.381771	0.000729167
66	101.17	101.11	100.736	0.374271	0.0598958
67	100.71	NA	NA	0.163438	NA
68	100.59	NA	NA	-0.0714792	NA
69	100.52	NA	NA	-0.0872292	NA
70	100.65	NA	NA	-0.119146	NA
71	100.62	NA	NA	-0.128312	NA
72	100.62	NA	NA	-0.190562	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