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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 04 Dec 2014 09:27:04 +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/2014/Dec/04/t1417685262j915omy1ci265hq.htm/, Retrieved Thu, 16 May 2024 22:04:39 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263058, Retrieved Thu, 16 May 2024 22:04:39 +0000

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115

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-       [Classical Decomposition] [] [2014-12-04 09:27:04] [fd8705890551d8de989fba3c4c1c4b9e] [Current]

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Dataseries X:

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1,4
1,5
1,8
1,8
1,8
1,7
1,5
1,1
1,3
1,6
1,9
1,9
2
2,2
2,2
2
2,3
2,6
3,2
3,2
3,1
2,8
2,3
1,9
1,9
2
2
1,8
1,6
1,4
0,2
0,3
0,4
0,7
1
1,1
0,8
0,8
1
1,1
1
0,8
1,6
1,5
1,6
1,6
1,6
1,9
2
1,9
2
2,1
2,3
2,3
2,6
2,6
2,7
2,6
2,6
2,4
2,5
2,5
2,5
2,4
2,1
2,1
2,3
2,3
2,3
2,9
2,8
2,9
3
3
2,9
2,6
2,8
2,9
3,1
2,8
2,4
1,6
1,5
1,7

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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263058&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263058&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263058&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 Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.4	NA	NA	1.02193	NA
2	1.5	NA	NA	1.01629	NA
3	1.8	NA	NA	1.04309	NA
4	1.8	NA	NA	1.00684	NA
5	1.8	NA	NA	1.00275	NA
6	1.7	NA	NA	0.982579	NA
7	1.5	1.55312	1.63333	0.950887	0.965801
8	1.1	1.50809	1.6875	0.893682	0.7294
9	1.3	1.61035	1.73333	0.929048	0.807278
10	1.6	1.79	1.75833	1.01801	0.893856
11	1.9	1.89724	1.7875	1.06139	1.00145
12	1.9	1.98151	1.84583	1.0735	0.958865
13	2	1.99702	1.95417	1.02193	1.00149
14	2.2	2.14691	2.1125	1.01629	1.02473
15	2.2	2.37302	2.275	1.04309	0.927088
16	2	2.41641	2.4	1.00684	0.827673
17	2.3	2.47345	2.46667	1.00275	0.929873
18	2.6	2.44007	2.48333	0.982579	1.06554
19	3.2	2.35741	2.47917	0.950887	1.35742
20	3.2	2.20442	2.46667	0.893682	1.45163
21	3.1	2.27617	2.45	0.929048	1.36194
22	2.8	2.47715	2.43333	1.01801	1.13033
23	2.3	2.54292	2.39583	1.06139	0.904472
24	1.9	2.48695	2.31667	1.0735	0.763988
25	1.9	2.18864	2.14167	1.02193	0.86812
26	2	1.92672	1.89583	1.01629	1.03804
27	2	1.73413	1.6625	1.04309	1.15331
28	1.8	1.4725	1.4625	1.00684	1.22241
29	1.6	1.32447	1.32083	1.00275	1.20803
30	1.4	1.21185	1.23333	0.982579	1.15526
31	0.2	1.09748	1.15417	0.950887	0.182235
32	0.3	0.945814	1.05833	0.893682	0.317187
33	0.4	0.89808	0.966667	0.929048	0.445395
34	0.7	0.911966	0.895833	1.01801	0.767573
35	1	0.893339	0.841667	1.06139	1.1194
36	1.1	0.849857	0.791667	1.0735	1.29433
37	0.8	0.843094	0.825	1.02193	0.948886
38	0.8	0.948537	0.933333	1.01629	0.843404
39	1	1.07786	1.03333	1.04309	0.927767
40	1.1	1.1285	1.12083	1.00684	0.974747
41	1	1.18659	1.18333	1.00275	0.842751
42	0.8	1.22004	1.24167	0.982579	0.655719
43	1.6	1.25993	1.325	0.950887	1.26992
44	1.5	1.26977	1.42083	0.893682	1.18131
45	1.6	1.40131	1.50833	0.929048	1.14179
46	1.6	1.62033	1.59167	1.01801	0.987453
47	1.6	1.7911	1.6875	1.06139	0.893306
48	1.9	1.93678	1.80417	1.0735	0.981009
49	2	1.95019	1.90833	1.02193	1.02554
50	1.9	2.02834	1.99583	1.01629	0.936724
51	2	2.17744	2.0875	1.04309	0.918508
52	2.1	2.18987	2.175	1.00684	0.95896
53	2.3	2.26455	2.25833	1.00275	1.01566
54	2.3	2.2804	2.32083	0.982579	1.00859
55	2.6	2.24647	2.3625	0.950887	1.15737
56	2.6	2.15229	2.40833	0.893682	1.20802
57	2.7	2.28004	2.45417	0.929048	1.18419
58	2.6	2.5323	2.4875	1.01801	1.02674
59	2.6	2.64464	2.49167	1.06139	0.983122
60	2.4	2.65692	2.475	1.0735	0.903301
61	2.5	2.50799	2.45417	1.02193	0.996814
62	2.5	2.46874	2.42917	1.01629	1.01266
63	2.5	2.50341	2.4	1.04309	0.998638
64	2.4	2.41222	2.39583	1.00684	0.994935
65	2.1	2.42332	2.41667	1.00275	0.866581
66	2.1	2.40322	2.44583	0.982579	0.873826
67	2.3	2.36533	2.4875	0.950887	0.972379
68	2.3	2.26027	2.52917	0.893682	1.01758
69	2.3	2.38456	2.56667	0.929048	0.96454
70	2.9	2.63834	2.59167	1.01801	1.09918
71	2.8	2.79058	2.62917	1.06139	1.00338
72	2.9	2.88952	2.69167	1.0735	1.00363
73	3	2.81883	2.75833	1.02193	1.06427
74	3	2.85831	2.8125	1.01629	1.04957
75	2.9	2.95976	2.8375	1.04309	0.979809
76	2.6	2.80656	2.7875	1.00684	0.9264
77	2.8	2.68654	2.67917	1.00275	1.04223
78	2.9	2.53014	2.575	0.982579	1.14618
79	3.1	NA	NA	0.950887	NA
80	2.8	NA	NA	0.893682	NA
81	2.4	NA	NA	0.929048	NA
82	1.6	NA	NA	1.01801	NA
83	1.5	NA	NA	1.06139	NA
84	1.7	NA	NA	1.0735	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.4 & NA & NA & 1.02193 & NA \tabularnewline
2 & 1.5 & NA & NA & 1.01629 & NA \tabularnewline
3 & 1.8 & NA & NA & 1.04309 & NA \tabularnewline
4 & 1.8 & NA & NA & 1.00684 & NA \tabularnewline
5 & 1.8 & NA & NA & 1.00275 & NA \tabularnewline
6 & 1.7 & NA & NA & 0.982579 & NA \tabularnewline
7 & 1.5 & 1.55312 & 1.63333 & 0.950887 & 0.965801 \tabularnewline
8 & 1.1 & 1.50809 & 1.6875 & 0.893682 & 0.7294 \tabularnewline
9 & 1.3 & 1.61035 & 1.73333 & 0.929048 & 0.807278 \tabularnewline
10 & 1.6 & 1.79 & 1.75833 & 1.01801 & 0.893856 \tabularnewline
11 & 1.9 & 1.89724 & 1.7875 & 1.06139 & 1.00145 \tabularnewline
12 & 1.9 & 1.98151 & 1.84583 & 1.0735 & 0.958865 \tabularnewline
13 & 2 & 1.99702 & 1.95417 & 1.02193 & 1.00149 \tabularnewline
14 & 2.2 & 2.14691 & 2.1125 & 1.01629 & 1.02473 \tabularnewline
15 & 2.2 & 2.37302 & 2.275 & 1.04309 & 0.927088 \tabularnewline
16 & 2 & 2.41641 & 2.4 & 1.00684 & 0.827673 \tabularnewline
17 & 2.3 & 2.47345 & 2.46667 & 1.00275 & 0.929873 \tabularnewline
18 & 2.6 & 2.44007 & 2.48333 & 0.982579 & 1.06554 \tabularnewline
19 & 3.2 & 2.35741 & 2.47917 & 0.950887 & 1.35742 \tabularnewline
20 & 3.2 & 2.20442 & 2.46667 & 0.893682 & 1.45163 \tabularnewline
21 & 3.1 & 2.27617 & 2.45 & 0.929048 & 1.36194 \tabularnewline
22 & 2.8 & 2.47715 & 2.43333 & 1.01801 & 1.13033 \tabularnewline
23 & 2.3 & 2.54292 & 2.39583 & 1.06139 & 0.904472 \tabularnewline
24 & 1.9 & 2.48695 & 2.31667 & 1.0735 & 0.763988 \tabularnewline
25 & 1.9 & 2.18864 & 2.14167 & 1.02193 & 0.86812 \tabularnewline
26 & 2 & 1.92672 & 1.89583 & 1.01629 & 1.03804 \tabularnewline
27 & 2 & 1.73413 & 1.6625 & 1.04309 & 1.15331 \tabularnewline
28 & 1.8 & 1.4725 & 1.4625 & 1.00684 & 1.22241 \tabularnewline
29 & 1.6 & 1.32447 & 1.32083 & 1.00275 & 1.20803 \tabularnewline
30 & 1.4 & 1.21185 & 1.23333 & 0.982579 & 1.15526 \tabularnewline
31 & 0.2 & 1.09748 & 1.15417 & 0.950887 & 0.182235 \tabularnewline
32 & 0.3 & 0.945814 & 1.05833 & 0.893682 & 0.317187 \tabularnewline
33 & 0.4 & 0.89808 & 0.966667 & 0.929048 & 0.445395 \tabularnewline
34 & 0.7 & 0.911966 & 0.895833 & 1.01801 & 0.767573 \tabularnewline
35 & 1 & 0.893339 & 0.841667 & 1.06139 & 1.1194 \tabularnewline
36 & 1.1 & 0.849857 & 0.791667 & 1.0735 & 1.29433 \tabularnewline
37 & 0.8 & 0.843094 & 0.825 & 1.02193 & 0.948886 \tabularnewline
38 & 0.8 & 0.948537 & 0.933333 & 1.01629 & 0.843404 \tabularnewline
39 & 1 & 1.07786 & 1.03333 & 1.04309 & 0.927767 \tabularnewline
40 & 1.1 & 1.1285 & 1.12083 & 1.00684 & 0.974747 \tabularnewline
41 & 1 & 1.18659 & 1.18333 & 1.00275 & 0.842751 \tabularnewline
42 & 0.8 & 1.22004 & 1.24167 & 0.982579 & 0.655719 \tabularnewline
43 & 1.6 & 1.25993 & 1.325 & 0.950887 & 1.26992 \tabularnewline
44 & 1.5 & 1.26977 & 1.42083 & 0.893682 & 1.18131 \tabularnewline
45 & 1.6 & 1.40131 & 1.50833 & 0.929048 & 1.14179 \tabularnewline
46 & 1.6 & 1.62033 & 1.59167 & 1.01801 & 0.987453 \tabularnewline
47 & 1.6 & 1.7911 & 1.6875 & 1.06139 & 0.893306 \tabularnewline
48 & 1.9 & 1.93678 & 1.80417 & 1.0735 & 0.981009 \tabularnewline
49 & 2 & 1.95019 & 1.90833 & 1.02193 & 1.02554 \tabularnewline
50 & 1.9 & 2.02834 & 1.99583 & 1.01629 & 0.936724 \tabularnewline
51 & 2 & 2.17744 & 2.0875 & 1.04309 & 0.918508 \tabularnewline
52 & 2.1 & 2.18987 & 2.175 & 1.00684 & 0.95896 \tabularnewline
53 & 2.3 & 2.26455 & 2.25833 & 1.00275 & 1.01566 \tabularnewline
54 & 2.3 & 2.2804 & 2.32083 & 0.982579 & 1.00859 \tabularnewline
55 & 2.6 & 2.24647 & 2.3625 & 0.950887 & 1.15737 \tabularnewline
56 & 2.6 & 2.15229 & 2.40833 & 0.893682 & 1.20802 \tabularnewline
57 & 2.7 & 2.28004 & 2.45417 & 0.929048 & 1.18419 \tabularnewline
58 & 2.6 & 2.5323 & 2.4875 & 1.01801 & 1.02674 \tabularnewline
59 & 2.6 & 2.64464 & 2.49167 & 1.06139 & 0.983122 \tabularnewline
60 & 2.4 & 2.65692 & 2.475 & 1.0735 & 0.903301 \tabularnewline
61 & 2.5 & 2.50799 & 2.45417 & 1.02193 & 0.996814 \tabularnewline
62 & 2.5 & 2.46874 & 2.42917 & 1.01629 & 1.01266 \tabularnewline
63 & 2.5 & 2.50341 & 2.4 & 1.04309 & 0.998638 \tabularnewline
64 & 2.4 & 2.41222 & 2.39583 & 1.00684 & 0.994935 \tabularnewline
65 & 2.1 & 2.42332 & 2.41667 & 1.00275 & 0.866581 \tabularnewline
66 & 2.1 & 2.40322 & 2.44583 & 0.982579 & 0.873826 \tabularnewline
67 & 2.3 & 2.36533 & 2.4875 & 0.950887 & 0.972379 \tabularnewline
68 & 2.3 & 2.26027 & 2.52917 & 0.893682 & 1.01758 \tabularnewline
69 & 2.3 & 2.38456 & 2.56667 & 0.929048 & 0.96454 \tabularnewline
70 & 2.9 & 2.63834 & 2.59167 & 1.01801 & 1.09918 \tabularnewline
71 & 2.8 & 2.79058 & 2.62917 & 1.06139 & 1.00338 \tabularnewline
72 & 2.9 & 2.88952 & 2.69167 & 1.0735 & 1.00363 \tabularnewline
73 & 3 & 2.81883 & 2.75833 & 1.02193 & 1.06427 \tabularnewline
74 & 3 & 2.85831 & 2.8125 & 1.01629 & 1.04957 \tabularnewline
75 & 2.9 & 2.95976 & 2.8375 & 1.04309 & 0.979809 \tabularnewline
76 & 2.6 & 2.80656 & 2.7875 & 1.00684 & 0.9264 \tabularnewline
77 & 2.8 & 2.68654 & 2.67917 & 1.00275 & 1.04223 \tabularnewline
78 & 2.9 & 2.53014 & 2.575 & 0.982579 & 1.14618 \tabularnewline
79 & 3.1 & NA & NA & 0.950887 & NA \tabularnewline
80 & 2.8 & NA & NA & 0.893682 & NA \tabularnewline
81 & 2.4 & NA & NA & 0.929048 & NA \tabularnewline
82 & 1.6 & NA & NA & 1.01801 & NA \tabularnewline
83 & 1.5 & NA & NA & 1.06139 & NA \tabularnewline
84 & 1.7 & NA & NA & 1.0735 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263058&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]1.4[/C][C]NA[/C][C]NA[/C][C]1.02193[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.5[/C][C]NA[/C][C]NA[/C][C]1.01629[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]1.04309[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]1.00684[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.8[/C][C]NA[/C][C]NA[/C][C]1.00275[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.7[/C][C]NA[/C][C]NA[/C][C]0.982579[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.5[/C][C]1.55312[/C][C]1.63333[/C][C]0.950887[/C][C]0.965801[/C][/ROW]
[ROW][C]8[/C][C]1.1[/C][C]1.50809[/C][C]1.6875[/C][C]0.893682[/C][C]0.7294[/C][/ROW]
[ROW][C]9[/C][C]1.3[/C][C]1.61035[/C][C]1.73333[/C][C]0.929048[/C][C]0.807278[/C][/ROW]
[ROW][C]10[/C][C]1.6[/C][C]1.79[/C][C]1.75833[/C][C]1.01801[/C][C]0.893856[/C][/ROW]
[ROW][C]11[/C][C]1.9[/C][C]1.89724[/C][C]1.7875[/C][C]1.06139[/C][C]1.00145[/C][/ROW]
[ROW][C]12[/C][C]1.9[/C][C]1.98151[/C][C]1.84583[/C][C]1.0735[/C][C]0.958865[/C][/ROW]
[ROW][C]13[/C][C]2[/C][C]1.99702[/C][C]1.95417[/C][C]1.02193[/C][C]1.00149[/C][/ROW]
[ROW][C]14[/C][C]2.2[/C][C]2.14691[/C][C]2.1125[/C][C]1.01629[/C][C]1.02473[/C][/ROW]
[ROW][C]15[/C][C]2.2[/C][C]2.37302[/C][C]2.275[/C][C]1.04309[/C][C]0.927088[/C][/ROW]
[ROW][C]16[/C][C]2[/C][C]2.41641[/C][C]2.4[/C][C]1.00684[/C][C]0.827673[/C][/ROW]
[ROW][C]17[/C][C]2.3[/C][C]2.47345[/C][C]2.46667[/C][C]1.00275[/C][C]0.929873[/C][/ROW]
[ROW][C]18[/C][C]2.6[/C][C]2.44007[/C][C]2.48333[/C][C]0.982579[/C][C]1.06554[/C][/ROW]
[ROW][C]19[/C][C]3.2[/C][C]2.35741[/C][C]2.47917[/C][C]0.950887[/C][C]1.35742[/C][/ROW]
[ROW][C]20[/C][C]3.2[/C][C]2.20442[/C][C]2.46667[/C][C]0.893682[/C][C]1.45163[/C][/ROW]
[ROW][C]21[/C][C]3.1[/C][C]2.27617[/C][C]2.45[/C][C]0.929048[/C][C]1.36194[/C][/ROW]
[ROW][C]22[/C][C]2.8[/C][C]2.47715[/C][C]2.43333[/C][C]1.01801[/C][C]1.13033[/C][/ROW]
[ROW][C]23[/C][C]2.3[/C][C]2.54292[/C][C]2.39583[/C][C]1.06139[/C][C]0.904472[/C][/ROW]
[ROW][C]24[/C][C]1.9[/C][C]2.48695[/C][C]2.31667[/C][C]1.0735[/C][C]0.763988[/C][/ROW]
[ROW][C]25[/C][C]1.9[/C][C]2.18864[/C][C]2.14167[/C][C]1.02193[/C][C]0.86812[/C][/ROW]
[ROW][C]26[/C][C]2[/C][C]1.92672[/C][C]1.89583[/C][C]1.01629[/C][C]1.03804[/C][/ROW]
[ROW][C]27[/C][C]2[/C][C]1.73413[/C][C]1.6625[/C][C]1.04309[/C][C]1.15331[/C][/ROW]
[ROW][C]28[/C][C]1.8[/C][C]1.4725[/C][C]1.4625[/C][C]1.00684[/C][C]1.22241[/C][/ROW]
[ROW][C]29[/C][C]1.6[/C][C]1.32447[/C][C]1.32083[/C][C]1.00275[/C][C]1.20803[/C][/ROW]
[ROW][C]30[/C][C]1.4[/C][C]1.21185[/C][C]1.23333[/C][C]0.982579[/C][C]1.15526[/C][/ROW]
[ROW][C]31[/C][C]0.2[/C][C]1.09748[/C][C]1.15417[/C][C]0.950887[/C][C]0.182235[/C][/ROW]
[ROW][C]32[/C][C]0.3[/C][C]0.945814[/C][C]1.05833[/C][C]0.893682[/C][C]0.317187[/C][/ROW]
[ROW][C]33[/C][C]0.4[/C][C]0.89808[/C][C]0.966667[/C][C]0.929048[/C][C]0.445395[/C][/ROW]
[ROW][C]34[/C][C]0.7[/C][C]0.911966[/C][C]0.895833[/C][C]1.01801[/C][C]0.767573[/C][/ROW]
[ROW][C]35[/C][C]1[/C][C]0.893339[/C][C]0.841667[/C][C]1.06139[/C][C]1.1194[/C][/ROW]
[ROW][C]36[/C][C]1.1[/C][C]0.849857[/C][C]0.791667[/C][C]1.0735[/C][C]1.29433[/C][/ROW]
[ROW][C]37[/C][C]0.8[/C][C]0.843094[/C][C]0.825[/C][C]1.02193[/C][C]0.948886[/C][/ROW]
[ROW][C]38[/C][C]0.8[/C][C]0.948537[/C][C]0.933333[/C][C]1.01629[/C][C]0.843404[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]1.07786[/C][C]1.03333[/C][C]1.04309[/C][C]0.927767[/C][/ROW]
[ROW][C]40[/C][C]1.1[/C][C]1.1285[/C][C]1.12083[/C][C]1.00684[/C][C]0.974747[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]1.18659[/C][C]1.18333[/C][C]1.00275[/C][C]0.842751[/C][/ROW]
[ROW][C]42[/C][C]0.8[/C][C]1.22004[/C][C]1.24167[/C][C]0.982579[/C][C]0.655719[/C][/ROW]
[ROW][C]43[/C][C]1.6[/C][C]1.25993[/C][C]1.325[/C][C]0.950887[/C][C]1.26992[/C][/ROW]
[ROW][C]44[/C][C]1.5[/C][C]1.26977[/C][C]1.42083[/C][C]0.893682[/C][C]1.18131[/C][/ROW]
[ROW][C]45[/C][C]1.6[/C][C]1.40131[/C][C]1.50833[/C][C]0.929048[/C][C]1.14179[/C][/ROW]
[ROW][C]46[/C][C]1.6[/C][C]1.62033[/C][C]1.59167[/C][C]1.01801[/C][C]0.987453[/C][/ROW]
[ROW][C]47[/C][C]1.6[/C][C]1.7911[/C][C]1.6875[/C][C]1.06139[/C][C]0.893306[/C][/ROW]
[ROW][C]48[/C][C]1.9[/C][C]1.93678[/C][C]1.80417[/C][C]1.0735[/C][C]0.981009[/C][/ROW]
[ROW][C]49[/C][C]2[/C][C]1.95019[/C][C]1.90833[/C][C]1.02193[/C][C]1.02554[/C][/ROW]
[ROW][C]50[/C][C]1.9[/C][C]2.02834[/C][C]1.99583[/C][C]1.01629[/C][C]0.936724[/C][/ROW]
[ROW][C]51[/C][C]2[/C][C]2.17744[/C][C]2.0875[/C][C]1.04309[/C][C]0.918508[/C][/ROW]
[ROW][C]52[/C][C]2.1[/C][C]2.18987[/C][C]2.175[/C][C]1.00684[/C][C]0.95896[/C][/ROW]
[ROW][C]53[/C][C]2.3[/C][C]2.26455[/C][C]2.25833[/C][C]1.00275[/C][C]1.01566[/C][/ROW]
[ROW][C]54[/C][C]2.3[/C][C]2.2804[/C][C]2.32083[/C][C]0.982579[/C][C]1.00859[/C][/ROW]
[ROW][C]55[/C][C]2.6[/C][C]2.24647[/C][C]2.3625[/C][C]0.950887[/C][C]1.15737[/C][/ROW]
[ROW][C]56[/C][C]2.6[/C][C]2.15229[/C][C]2.40833[/C][C]0.893682[/C][C]1.20802[/C][/ROW]
[ROW][C]57[/C][C]2.7[/C][C]2.28004[/C][C]2.45417[/C][C]0.929048[/C][C]1.18419[/C][/ROW]
[ROW][C]58[/C][C]2.6[/C][C]2.5323[/C][C]2.4875[/C][C]1.01801[/C][C]1.02674[/C][/ROW]
[ROW][C]59[/C][C]2.6[/C][C]2.64464[/C][C]2.49167[/C][C]1.06139[/C][C]0.983122[/C][/ROW]
[ROW][C]60[/C][C]2.4[/C][C]2.65692[/C][C]2.475[/C][C]1.0735[/C][C]0.903301[/C][/ROW]
[ROW][C]61[/C][C]2.5[/C][C]2.50799[/C][C]2.45417[/C][C]1.02193[/C][C]0.996814[/C][/ROW]
[ROW][C]62[/C][C]2.5[/C][C]2.46874[/C][C]2.42917[/C][C]1.01629[/C][C]1.01266[/C][/ROW]
[ROW][C]63[/C][C]2.5[/C][C]2.50341[/C][C]2.4[/C][C]1.04309[/C][C]0.998638[/C][/ROW]
[ROW][C]64[/C][C]2.4[/C][C]2.41222[/C][C]2.39583[/C][C]1.00684[/C][C]0.994935[/C][/ROW]
[ROW][C]65[/C][C]2.1[/C][C]2.42332[/C][C]2.41667[/C][C]1.00275[/C][C]0.866581[/C][/ROW]
[ROW][C]66[/C][C]2.1[/C][C]2.40322[/C][C]2.44583[/C][C]0.982579[/C][C]0.873826[/C][/ROW]
[ROW][C]67[/C][C]2.3[/C][C]2.36533[/C][C]2.4875[/C][C]0.950887[/C][C]0.972379[/C][/ROW]
[ROW][C]68[/C][C]2.3[/C][C]2.26027[/C][C]2.52917[/C][C]0.893682[/C][C]1.01758[/C][/ROW]
[ROW][C]69[/C][C]2.3[/C][C]2.38456[/C][C]2.56667[/C][C]0.929048[/C][C]0.96454[/C][/ROW]
[ROW][C]70[/C][C]2.9[/C][C]2.63834[/C][C]2.59167[/C][C]1.01801[/C][C]1.09918[/C][/ROW]
[ROW][C]71[/C][C]2.8[/C][C]2.79058[/C][C]2.62917[/C][C]1.06139[/C][C]1.00338[/C][/ROW]
[ROW][C]72[/C][C]2.9[/C][C]2.88952[/C][C]2.69167[/C][C]1.0735[/C][C]1.00363[/C][/ROW]
[ROW][C]73[/C][C]3[/C][C]2.81883[/C][C]2.75833[/C][C]1.02193[/C][C]1.06427[/C][/ROW]
[ROW][C]74[/C][C]3[/C][C]2.85831[/C][C]2.8125[/C][C]1.01629[/C][C]1.04957[/C][/ROW]
[ROW][C]75[/C][C]2.9[/C][C]2.95976[/C][C]2.8375[/C][C]1.04309[/C][C]0.979809[/C][/ROW]
[ROW][C]76[/C][C]2.6[/C][C]2.80656[/C][C]2.7875[/C][C]1.00684[/C][C]0.9264[/C][/ROW]
[ROW][C]77[/C][C]2.8[/C][C]2.68654[/C][C]2.67917[/C][C]1.00275[/C][C]1.04223[/C][/ROW]
[ROW][C]78[/C][C]2.9[/C][C]2.53014[/C][C]2.575[/C][C]0.982579[/C][C]1.14618[/C][/ROW]
[ROW][C]79[/C][C]3.1[/C][C]NA[/C][C]NA[/C][C]0.950887[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]2.8[/C][C]NA[/C][C]NA[/C][C]0.893682[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]2.4[/C][C]NA[/C][C]NA[/C][C]0.929048[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]1.6[/C][C]NA[/C][C]NA[/C][C]1.01801[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]1.5[/C][C]NA[/C][C]NA[/C][C]1.06139[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]1.7[/C][C]NA[/C][C]NA[/C][C]1.0735[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263058&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263058&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	1.4	NA	NA	1.02193	NA
2	1.5	NA	NA	1.01629	NA
3	1.8	NA	NA	1.04309	NA
4	1.8	NA	NA	1.00684	NA
5	1.8	NA	NA	1.00275	NA
6	1.7	NA	NA	0.982579	NA
7	1.5	1.55312	1.63333	0.950887	0.965801
8	1.1	1.50809	1.6875	0.893682	0.7294
9	1.3	1.61035	1.73333	0.929048	0.807278
10	1.6	1.79	1.75833	1.01801	0.893856
11	1.9	1.89724	1.7875	1.06139	1.00145
12	1.9	1.98151	1.84583	1.0735	0.958865
13	2	1.99702	1.95417	1.02193	1.00149
14	2.2	2.14691	2.1125	1.01629	1.02473
15	2.2	2.37302	2.275	1.04309	0.927088
16	2	2.41641	2.4	1.00684	0.827673
17	2.3	2.47345	2.46667	1.00275	0.929873
18	2.6	2.44007	2.48333	0.982579	1.06554
19	3.2	2.35741	2.47917	0.950887	1.35742
20	3.2	2.20442	2.46667	0.893682	1.45163
21	3.1	2.27617	2.45	0.929048	1.36194
22	2.8	2.47715	2.43333	1.01801	1.13033
23	2.3	2.54292	2.39583	1.06139	0.904472
24	1.9	2.48695	2.31667	1.0735	0.763988
25	1.9	2.18864	2.14167	1.02193	0.86812
26	2	1.92672	1.89583	1.01629	1.03804
27	2	1.73413	1.6625	1.04309	1.15331
28	1.8	1.4725	1.4625	1.00684	1.22241
29	1.6	1.32447	1.32083	1.00275	1.20803
30	1.4	1.21185	1.23333	0.982579	1.15526
31	0.2	1.09748	1.15417	0.950887	0.182235
32	0.3	0.945814	1.05833	0.893682	0.317187
33	0.4	0.89808	0.966667	0.929048	0.445395
34	0.7	0.911966	0.895833	1.01801	0.767573
35	1	0.893339	0.841667	1.06139	1.1194
36	1.1	0.849857	0.791667	1.0735	1.29433
37	0.8	0.843094	0.825	1.02193	0.948886
38	0.8	0.948537	0.933333	1.01629	0.843404
39	1	1.07786	1.03333	1.04309	0.927767
40	1.1	1.1285	1.12083	1.00684	0.974747
41	1	1.18659	1.18333	1.00275	0.842751
42	0.8	1.22004	1.24167	0.982579	0.655719
43	1.6	1.25993	1.325	0.950887	1.26992
44	1.5	1.26977	1.42083	0.893682	1.18131
45	1.6	1.40131	1.50833	0.929048	1.14179
46	1.6	1.62033	1.59167	1.01801	0.987453
47	1.6	1.7911	1.6875	1.06139	0.893306
48	1.9	1.93678	1.80417	1.0735	0.981009
49	2	1.95019	1.90833	1.02193	1.02554
50	1.9	2.02834	1.99583	1.01629	0.936724
51	2	2.17744	2.0875	1.04309	0.918508
52	2.1	2.18987	2.175	1.00684	0.95896
53	2.3	2.26455	2.25833	1.00275	1.01566
54	2.3	2.2804	2.32083	0.982579	1.00859
55	2.6	2.24647	2.3625	0.950887	1.15737
56	2.6	2.15229	2.40833	0.893682	1.20802
57	2.7	2.28004	2.45417	0.929048	1.18419
58	2.6	2.5323	2.4875	1.01801	1.02674
59	2.6	2.64464	2.49167	1.06139	0.983122
60	2.4	2.65692	2.475	1.0735	0.903301
61	2.5	2.50799	2.45417	1.02193	0.996814
62	2.5	2.46874	2.42917	1.01629	1.01266
63	2.5	2.50341	2.4	1.04309	0.998638
64	2.4	2.41222	2.39583	1.00684	0.994935
65	2.1	2.42332	2.41667	1.00275	0.866581
66	2.1	2.40322	2.44583	0.982579	0.873826
67	2.3	2.36533	2.4875	0.950887	0.972379
68	2.3	2.26027	2.52917	0.893682	1.01758
69	2.3	2.38456	2.56667	0.929048	0.96454
70	2.9	2.63834	2.59167	1.01801	1.09918
71	2.8	2.79058	2.62917	1.06139	1.00338
72	2.9	2.88952	2.69167	1.0735	1.00363
73	3	2.81883	2.75833	1.02193	1.06427
74	3	2.85831	2.8125	1.01629	1.04957
75	2.9	2.95976	2.8375	1.04309	0.979809
76	2.6	2.80656	2.7875	1.00684	0.9264
77	2.8	2.68654	2.67917	1.00275	1.04223
78	2.9	2.53014	2.575	0.982579	1.14618
79	3.1	NA	NA	0.950887	NA
80	2.8	NA	NA	0.893682	NA
81	2.4	NA	NA	0.929048	NA
82	1.6	NA	NA	1.01801	NA
83	1.5	NA	NA	1.06139	NA
84	1.7	NA	NA	1.0735	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