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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 25 Apr 2016 15:13:57 +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/t1461593711jehw7mm72c1p0cx.htm/, Retrieved Sun, 05 May 2024 21:15:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294706, Retrieved Sun, 05 May 2024 21:15:29 +0000

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Estimated Impact

111

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-       [Classical Decomposition] [] [2016-04-25 14:13:57] [c0f67b4e93ea0adf92c2b9d3976edd70] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294706&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294706&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294706&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	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	87.5	NA	NA	0.72772	NA
2	87.3	NA	NA	0.479109	NA
3	87.8	NA	NA	-0.0764468	NA
4	88.1	NA	NA	-0.900752	NA
5	88	NA	NA	-1.032	NA
6	87.8	NA	NA	-0.675752	NA
7	87	87.1201	87.8458	-0.725752	-0.120081
8	87.2	87.9458	87.8875	0.0582755	-0.745775
9	87	87.9569	87.8625	0.0943866	-0.956887
10	89.4	88.0437	87.6417	0.402025	1.35631
11	89.1	88.0222	87.3208	0.701331	1.07784
12	87.8	87.9854	87.0375	0.947859	-0.185359
13	87.8	87.5819	86.8542	0.72772	0.218113
14	88	87.2458	86.7667	0.479109	0.754225
15	86.5	86.6152	86.6917	-0.0764468	-0.11522
16	84.1	85.6451	86.5458	-0.900752	-1.54508
17	84.3	85.4097	86.4417	-1.032	-1.10966
18	84.7	85.8867	86.5625	-0.675752	-1.18675
19	85.7	86.0409	86.7667	-0.725752	-0.340914
20	86.4	86.9666	86.9083	0.0582755	-0.566609
21	86	87.1486	87.0542	0.0943866	-1.14855
22	86.9	87.6562	87.2542	0.402025	-0.756192
23	89.1	88.1722	87.4708	0.701331	0.927836
24	90.7	88.7229	87.775	0.947859	1.97714
25	89.8	88.8194	88.0917	0.72772	0.980613
26	89.4	88.8874	88.4083	0.479109	0.512558
27	88.6	88.7944	88.8708	-0.0764468	-0.194387
28	86.8	88.4451	89.3458	-0.900752	-1.64508
29	86.8	88.6805	89.7125	-1.032	-1.8805
30	89.5	89.2826	89.9583	-0.675752	0.217419
31	88.5	89.4451	90.1708	-0.725752	-0.945081
32	91.2	90.5499	90.4917	0.0582755	0.650058
33	92.3	91.0111	90.9167	0.0943866	1.28895
34	92	91.8562	91.4542	0.402025	0.143808
35	92.8	92.8013	92.1	0.701331	-0.00133102
36	92.9	93.5979	92.65	0.947859	-0.697859
37	92.7	93.8694	93.1417	0.72772	-1.16939
38	94.2	94.1374	93.6583	0.479109	0.0625579
39	94	94.0569	94.1333	-0.0764468	-0.0568866
40	94.3	93.6867	94.5875	-0.900752	0.613252
41	94.8	93.9305	94.9625	-1.032	0.869502
42	94.7	94.6576	95.3333	-0.675752	0.042419
43	95.1	95.0992	95.825	-0.725752	0.000752315
44	97	96.3958	96.3375	0.0582755	0.604225
45	97.9	96.9152	96.8208	0.0943866	0.98478
46	97.3	97.702	97.3	0.402025	-0.402025
47	96.5	98.443	97.7417	0.701331	-1.943
48	98.1	99.0979	98.15	0.947859	-0.997859
49	99.3	99.2777	98.55	0.72772	0.0222801
50	99.9	99.3583	98.8792	0.479109	0.541725
51	99.9	99.0236	99.1	-0.0764468	0.876447
52	99.9	98.4117	99.3125	-0.900752	1.48825
53	99.8	98.5722	99.6042	-1.032	1.22784
54	99.5	99.2117	99.8875	-0.675752	0.288252
55	99.9	99.3367	100.063	-0.725752	0.563252
56	100.1	100.208	100.15	0.0582755	-0.108275
57	100.1	100.315	100.221	0.0943866	-0.21522
58	100.2	100.694	100.292	0.402025	-0.493692
59	100.6	100.985	100.283	0.701331	-0.384664
60	100.8	101.131	100.183	0.947859	-0.331192
61	100.8	100.749	100.021	0.72772	0.0514468
62	100.5	100.283	99.8042	0.479109	0.216725
63	101	99.4569	99.5333	-0.0764468	1.54311
64	100.5	98.3201	99.2208	-0.900752	2.17992
65	99	97.8472	98.8792	-1.032	1.15284
66	97.9	97.8326	98.5083	-0.675752	0.067419
67	97.6	97.3742	98.1	-0.725752	0.225752
68	97.2	97.6499	97.5917	0.0582755	-0.449942
69	96.5	97.0694	96.975	0.0943866	-0.569387
70	96.3	96.7645	96.3625	0.402025	-0.464525
71	96.3	96.593	95.8917	0.701331	-0.292998
72	96.2	96.5812	95.6333	0.947859	-0.381192
73	95.6	96.3194	95.5917	0.72772	-0.719387
74	93.5	96.2041	95.725	0.479109	-2.70411
75	93.2	95.8694	95.9458	-0.0764468	-2.66939
76	93.6	95.3076	96.2083	-0.900752	-1.70758
77	94.6	95.4763	96.5083	-1.032	-0.876331
78	96.1	96.1451	96.8208	-0.675752	-0.045081
79	98.4	NA	NA	-0.725752	NA
80	99.6	NA	NA	0.0582755	NA
81	99.4	NA	NA	0.0943866	NA
82	99.7	NA	NA	0.402025	NA
83	100.1	NA	NA	0.701331	NA
84	99.9	NA	NA	0.947859	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 87.5 & NA & NA & 0.72772 & NA \tabularnewline
2 & 87.3 & NA & NA & 0.479109 & NA \tabularnewline
3 & 87.8 & NA & NA & -0.0764468 & NA \tabularnewline
4 & 88.1 & NA & NA & -0.900752 & NA \tabularnewline
5 & 88 & NA & NA & -1.032 & NA \tabularnewline
6 & 87.8 & NA & NA & -0.675752 & NA \tabularnewline
7 & 87 & 87.1201 & 87.8458 & -0.725752 & -0.120081 \tabularnewline
8 & 87.2 & 87.9458 & 87.8875 & 0.0582755 & -0.745775 \tabularnewline
9 & 87 & 87.9569 & 87.8625 & 0.0943866 & -0.956887 \tabularnewline
10 & 89.4 & 88.0437 & 87.6417 & 0.402025 & 1.35631 \tabularnewline
11 & 89.1 & 88.0222 & 87.3208 & 0.701331 & 1.07784 \tabularnewline
12 & 87.8 & 87.9854 & 87.0375 & 0.947859 & -0.185359 \tabularnewline
13 & 87.8 & 87.5819 & 86.8542 & 0.72772 & 0.218113 \tabularnewline
14 & 88 & 87.2458 & 86.7667 & 0.479109 & 0.754225 \tabularnewline
15 & 86.5 & 86.6152 & 86.6917 & -0.0764468 & -0.11522 \tabularnewline
16 & 84.1 & 85.6451 & 86.5458 & -0.900752 & -1.54508 \tabularnewline
17 & 84.3 & 85.4097 & 86.4417 & -1.032 & -1.10966 \tabularnewline
18 & 84.7 & 85.8867 & 86.5625 & -0.675752 & -1.18675 \tabularnewline
19 & 85.7 & 86.0409 & 86.7667 & -0.725752 & -0.340914 \tabularnewline
20 & 86.4 & 86.9666 & 86.9083 & 0.0582755 & -0.566609 \tabularnewline
21 & 86 & 87.1486 & 87.0542 & 0.0943866 & -1.14855 \tabularnewline
22 & 86.9 & 87.6562 & 87.2542 & 0.402025 & -0.756192 \tabularnewline
23 & 89.1 & 88.1722 & 87.4708 & 0.701331 & 0.927836 \tabularnewline
24 & 90.7 & 88.7229 & 87.775 & 0.947859 & 1.97714 \tabularnewline
25 & 89.8 & 88.8194 & 88.0917 & 0.72772 & 0.980613 \tabularnewline
26 & 89.4 & 88.8874 & 88.4083 & 0.479109 & 0.512558 \tabularnewline
27 & 88.6 & 88.7944 & 88.8708 & -0.0764468 & -0.194387 \tabularnewline
28 & 86.8 & 88.4451 & 89.3458 & -0.900752 & -1.64508 \tabularnewline
29 & 86.8 & 88.6805 & 89.7125 & -1.032 & -1.8805 \tabularnewline
30 & 89.5 & 89.2826 & 89.9583 & -0.675752 & 0.217419 \tabularnewline
31 & 88.5 & 89.4451 & 90.1708 & -0.725752 & -0.945081 \tabularnewline
32 & 91.2 & 90.5499 & 90.4917 & 0.0582755 & 0.650058 \tabularnewline
33 & 92.3 & 91.0111 & 90.9167 & 0.0943866 & 1.28895 \tabularnewline
34 & 92 & 91.8562 & 91.4542 & 0.402025 & 0.143808 \tabularnewline
35 & 92.8 & 92.8013 & 92.1 & 0.701331 & -0.00133102 \tabularnewline
36 & 92.9 & 93.5979 & 92.65 & 0.947859 & -0.697859 \tabularnewline
37 & 92.7 & 93.8694 & 93.1417 & 0.72772 & -1.16939 \tabularnewline
38 & 94.2 & 94.1374 & 93.6583 & 0.479109 & 0.0625579 \tabularnewline
39 & 94 & 94.0569 & 94.1333 & -0.0764468 & -0.0568866 \tabularnewline
40 & 94.3 & 93.6867 & 94.5875 & -0.900752 & 0.613252 \tabularnewline
41 & 94.8 & 93.9305 & 94.9625 & -1.032 & 0.869502 \tabularnewline
42 & 94.7 & 94.6576 & 95.3333 & -0.675752 & 0.042419 \tabularnewline
43 & 95.1 & 95.0992 & 95.825 & -0.725752 & 0.000752315 \tabularnewline
44 & 97 & 96.3958 & 96.3375 & 0.0582755 & 0.604225 \tabularnewline
45 & 97.9 & 96.9152 & 96.8208 & 0.0943866 & 0.98478 \tabularnewline
46 & 97.3 & 97.702 & 97.3 & 0.402025 & -0.402025 \tabularnewline
47 & 96.5 & 98.443 & 97.7417 & 0.701331 & -1.943 \tabularnewline
48 & 98.1 & 99.0979 & 98.15 & 0.947859 & -0.997859 \tabularnewline
49 & 99.3 & 99.2777 & 98.55 & 0.72772 & 0.0222801 \tabularnewline
50 & 99.9 & 99.3583 & 98.8792 & 0.479109 & 0.541725 \tabularnewline
51 & 99.9 & 99.0236 & 99.1 & -0.0764468 & 0.876447 \tabularnewline
52 & 99.9 & 98.4117 & 99.3125 & -0.900752 & 1.48825 \tabularnewline
53 & 99.8 & 98.5722 & 99.6042 & -1.032 & 1.22784 \tabularnewline
54 & 99.5 & 99.2117 & 99.8875 & -0.675752 & 0.288252 \tabularnewline
55 & 99.9 & 99.3367 & 100.063 & -0.725752 & 0.563252 \tabularnewline
56 & 100.1 & 100.208 & 100.15 & 0.0582755 & -0.108275 \tabularnewline
57 & 100.1 & 100.315 & 100.221 & 0.0943866 & -0.21522 \tabularnewline
58 & 100.2 & 100.694 & 100.292 & 0.402025 & -0.493692 \tabularnewline
59 & 100.6 & 100.985 & 100.283 & 0.701331 & -0.384664 \tabularnewline
60 & 100.8 & 101.131 & 100.183 & 0.947859 & -0.331192 \tabularnewline
61 & 100.8 & 100.749 & 100.021 & 0.72772 & 0.0514468 \tabularnewline
62 & 100.5 & 100.283 & 99.8042 & 0.479109 & 0.216725 \tabularnewline
63 & 101 & 99.4569 & 99.5333 & -0.0764468 & 1.54311 \tabularnewline
64 & 100.5 & 98.3201 & 99.2208 & -0.900752 & 2.17992 \tabularnewline
65 & 99 & 97.8472 & 98.8792 & -1.032 & 1.15284 \tabularnewline
66 & 97.9 & 97.8326 & 98.5083 & -0.675752 & 0.067419 \tabularnewline
67 & 97.6 & 97.3742 & 98.1 & -0.725752 & 0.225752 \tabularnewline
68 & 97.2 & 97.6499 & 97.5917 & 0.0582755 & -0.449942 \tabularnewline
69 & 96.5 & 97.0694 & 96.975 & 0.0943866 & -0.569387 \tabularnewline
70 & 96.3 & 96.7645 & 96.3625 & 0.402025 & -0.464525 \tabularnewline
71 & 96.3 & 96.593 & 95.8917 & 0.701331 & -0.292998 \tabularnewline
72 & 96.2 & 96.5812 & 95.6333 & 0.947859 & -0.381192 \tabularnewline
73 & 95.6 & 96.3194 & 95.5917 & 0.72772 & -0.719387 \tabularnewline
74 & 93.5 & 96.2041 & 95.725 & 0.479109 & -2.70411 \tabularnewline
75 & 93.2 & 95.8694 & 95.9458 & -0.0764468 & -2.66939 \tabularnewline
76 & 93.6 & 95.3076 & 96.2083 & -0.900752 & -1.70758 \tabularnewline
77 & 94.6 & 95.4763 & 96.5083 & -1.032 & -0.876331 \tabularnewline
78 & 96.1 & 96.1451 & 96.8208 & -0.675752 & -0.045081 \tabularnewline
79 & 98.4 & NA & NA & -0.725752 & NA \tabularnewline
80 & 99.6 & NA & NA & 0.0582755 & NA \tabularnewline
81 & 99.4 & NA & NA & 0.0943866 & NA \tabularnewline
82 & 99.7 & NA & NA & 0.402025 & NA \tabularnewline
83 & 100.1 & NA & NA & 0.701331 & NA \tabularnewline
84 & 99.9 & NA & NA & 0.947859 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294706&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]87.5[/C][C]NA[/C][C]NA[/C][C]0.72772[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]87.3[/C][C]NA[/C][C]NA[/C][C]0.479109[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]87.8[/C][C]NA[/C][C]NA[/C][C]-0.0764468[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]88.1[/C][C]NA[/C][C]NA[/C][C]-0.900752[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]88[/C][C]NA[/C][C]NA[/C][C]-1.032[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]87.8[/C][C]NA[/C][C]NA[/C][C]-0.675752[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]87[/C][C]87.1201[/C][C]87.8458[/C][C]-0.725752[/C][C]-0.120081[/C][/ROW]
[ROW][C]8[/C][C]87.2[/C][C]87.9458[/C][C]87.8875[/C][C]0.0582755[/C][C]-0.745775[/C][/ROW]
[ROW][C]9[/C][C]87[/C][C]87.9569[/C][C]87.8625[/C][C]0.0943866[/C][C]-0.956887[/C][/ROW]
[ROW][C]10[/C][C]89.4[/C][C]88.0437[/C][C]87.6417[/C][C]0.402025[/C][C]1.35631[/C][/ROW]
[ROW][C]11[/C][C]89.1[/C][C]88.0222[/C][C]87.3208[/C][C]0.701331[/C][C]1.07784[/C][/ROW]
[ROW][C]12[/C][C]87.8[/C][C]87.9854[/C][C]87.0375[/C][C]0.947859[/C][C]-0.185359[/C][/ROW]
[ROW][C]13[/C][C]87.8[/C][C]87.5819[/C][C]86.8542[/C][C]0.72772[/C][C]0.218113[/C][/ROW]
[ROW][C]14[/C][C]88[/C][C]87.2458[/C][C]86.7667[/C][C]0.479109[/C][C]0.754225[/C][/ROW]
[ROW][C]15[/C][C]86.5[/C][C]86.6152[/C][C]86.6917[/C][C]-0.0764468[/C][C]-0.11522[/C][/ROW]
[ROW][C]16[/C][C]84.1[/C][C]85.6451[/C][C]86.5458[/C][C]-0.900752[/C][C]-1.54508[/C][/ROW]
[ROW][C]17[/C][C]84.3[/C][C]85.4097[/C][C]86.4417[/C][C]-1.032[/C][C]-1.10966[/C][/ROW]
[ROW][C]18[/C][C]84.7[/C][C]85.8867[/C][C]86.5625[/C][C]-0.675752[/C][C]-1.18675[/C][/ROW]
[ROW][C]19[/C][C]85.7[/C][C]86.0409[/C][C]86.7667[/C][C]-0.725752[/C][C]-0.340914[/C][/ROW]
[ROW][C]20[/C][C]86.4[/C][C]86.9666[/C][C]86.9083[/C][C]0.0582755[/C][C]-0.566609[/C][/ROW]
[ROW][C]21[/C][C]86[/C][C]87.1486[/C][C]87.0542[/C][C]0.0943866[/C][C]-1.14855[/C][/ROW]
[ROW][C]22[/C][C]86.9[/C][C]87.6562[/C][C]87.2542[/C][C]0.402025[/C][C]-0.756192[/C][/ROW]
[ROW][C]23[/C][C]89.1[/C][C]88.1722[/C][C]87.4708[/C][C]0.701331[/C][C]0.927836[/C][/ROW]
[ROW][C]24[/C][C]90.7[/C][C]88.7229[/C][C]87.775[/C][C]0.947859[/C][C]1.97714[/C][/ROW]
[ROW][C]25[/C][C]89.8[/C][C]88.8194[/C][C]88.0917[/C][C]0.72772[/C][C]0.980613[/C][/ROW]
[ROW][C]26[/C][C]89.4[/C][C]88.8874[/C][C]88.4083[/C][C]0.479109[/C][C]0.512558[/C][/ROW]
[ROW][C]27[/C][C]88.6[/C][C]88.7944[/C][C]88.8708[/C][C]-0.0764468[/C][C]-0.194387[/C][/ROW]
[ROW][C]28[/C][C]86.8[/C][C]88.4451[/C][C]89.3458[/C][C]-0.900752[/C][C]-1.64508[/C][/ROW]
[ROW][C]29[/C][C]86.8[/C][C]88.6805[/C][C]89.7125[/C][C]-1.032[/C][C]-1.8805[/C][/ROW]
[ROW][C]30[/C][C]89.5[/C][C]89.2826[/C][C]89.9583[/C][C]-0.675752[/C][C]0.217419[/C][/ROW]
[ROW][C]31[/C][C]88.5[/C][C]89.4451[/C][C]90.1708[/C][C]-0.725752[/C][C]-0.945081[/C][/ROW]
[ROW][C]32[/C][C]91.2[/C][C]90.5499[/C][C]90.4917[/C][C]0.0582755[/C][C]0.650058[/C][/ROW]
[ROW][C]33[/C][C]92.3[/C][C]91.0111[/C][C]90.9167[/C][C]0.0943866[/C][C]1.28895[/C][/ROW]
[ROW][C]34[/C][C]92[/C][C]91.8562[/C][C]91.4542[/C][C]0.402025[/C][C]0.143808[/C][/ROW]
[ROW][C]35[/C][C]92.8[/C][C]92.8013[/C][C]92.1[/C][C]0.701331[/C][C]-0.00133102[/C][/ROW]
[ROW][C]36[/C][C]92.9[/C][C]93.5979[/C][C]92.65[/C][C]0.947859[/C][C]-0.697859[/C][/ROW]
[ROW][C]37[/C][C]92.7[/C][C]93.8694[/C][C]93.1417[/C][C]0.72772[/C][C]-1.16939[/C][/ROW]
[ROW][C]38[/C][C]94.2[/C][C]94.1374[/C][C]93.6583[/C][C]0.479109[/C][C]0.0625579[/C][/ROW]
[ROW][C]39[/C][C]94[/C][C]94.0569[/C][C]94.1333[/C][C]-0.0764468[/C][C]-0.0568866[/C][/ROW]
[ROW][C]40[/C][C]94.3[/C][C]93.6867[/C][C]94.5875[/C][C]-0.900752[/C][C]0.613252[/C][/ROW]
[ROW][C]41[/C][C]94.8[/C][C]93.9305[/C][C]94.9625[/C][C]-1.032[/C][C]0.869502[/C][/ROW]
[ROW][C]42[/C][C]94.7[/C][C]94.6576[/C][C]95.3333[/C][C]-0.675752[/C][C]0.042419[/C][/ROW]
[ROW][C]43[/C][C]95.1[/C][C]95.0992[/C][C]95.825[/C][C]-0.725752[/C][C]0.000752315[/C][/ROW]
[ROW][C]44[/C][C]97[/C][C]96.3958[/C][C]96.3375[/C][C]0.0582755[/C][C]0.604225[/C][/ROW]
[ROW][C]45[/C][C]97.9[/C][C]96.9152[/C][C]96.8208[/C][C]0.0943866[/C][C]0.98478[/C][/ROW]
[ROW][C]46[/C][C]97.3[/C][C]97.702[/C][C]97.3[/C][C]0.402025[/C][C]-0.402025[/C][/ROW]
[ROW][C]47[/C][C]96.5[/C][C]98.443[/C][C]97.7417[/C][C]0.701331[/C][C]-1.943[/C][/ROW]
[ROW][C]48[/C][C]98.1[/C][C]99.0979[/C][C]98.15[/C][C]0.947859[/C][C]-0.997859[/C][/ROW]
[ROW][C]49[/C][C]99.3[/C][C]99.2777[/C][C]98.55[/C][C]0.72772[/C][C]0.0222801[/C][/ROW]
[ROW][C]50[/C][C]99.9[/C][C]99.3583[/C][C]98.8792[/C][C]0.479109[/C][C]0.541725[/C][/ROW]
[ROW][C]51[/C][C]99.9[/C][C]99.0236[/C][C]99.1[/C][C]-0.0764468[/C][C]0.876447[/C][/ROW]
[ROW][C]52[/C][C]99.9[/C][C]98.4117[/C][C]99.3125[/C][C]-0.900752[/C][C]1.48825[/C][/ROW]
[ROW][C]53[/C][C]99.8[/C][C]98.5722[/C][C]99.6042[/C][C]-1.032[/C][C]1.22784[/C][/ROW]
[ROW][C]54[/C][C]99.5[/C][C]99.2117[/C][C]99.8875[/C][C]-0.675752[/C][C]0.288252[/C][/ROW]
[ROW][C]55[/C][C]99.9[/C][C]99.3367[/C][C]100.063[/C][C]-0.725752[/C][C]0.563252[/C][/ROW]
[ROW][C]56[/C][C]100.1[/C][C]100.208[/C][C]100.15[/C][C]0.0582755[/C][C]-0.108275[/C][/ROW]
[ROW][C]57[/C][C]100.1[/C][C]100.315[/C][C]100.221[/C][C]0.0943866[/C][C]-0.21522[/C][/ROW]
[ROW][C]58[/C][C]100.2[/C][C]100.694[/C][C]100.292[/C][C]0.402025[/C][C]-0.493692[/C][/ROW]
[ROW][C]59[/C][C]100.6[/C][C]100.985[/C][C]100.283[/C][C]0.701331[/C][C]-0.384664[/C][/ROW]
[ROW][C]60[/C][C]100.8[/C][C]101.131[/C][C]100.183[/C][C]0.947859[/C][C]-0.331192[/C][/ROW]
[ROW][C]61[/C][C]100.8[/C][C]100.749[/C][C]100.021[/C][C]0.72772[/C][C]0.0514468[/C][/ROW]
[ROW][C]62[/C][C]100.5[/C][C]100.283[/C][C]99.8042[/C][C]0.479109[/C][C]0.216725[/C][/ROW]
[ROW][C]63[/C][C]101[/C][C]99.4569[/C][C]99.5333[/C][C]-0.0764468[/C][C]1.54311[/C][/ROW]
[ROW][C]64[/C][C]100.5[/C][C]98.3201[/C][C]99.2208[/C][C]-0.900752[/C][C]2.17992[/C][/ROW]
[ROW][C]65[/C][C]99[/C][C]97.8472[/C][C]98.8792[/C][C]-1.032[/C][C]1.15284[/C][/ROW]
[ROW][C]66[/C][C]97.9[/C][C]97.8326[/C][C]98.5083[/C][C]-0.675752[/C][C]0.067419[/C][/ROW]
[ROW][C]67[/C][C]97.6[/C][C]97.3742[/C][C]98.1[/C][C]-0.725752[/C][C]0.225752[/C][/ROW]
[ROW][C]68[/C][C]97.2[/C][C]97.6499[/C][C]97.5917[/C][C]0.0582755[/C][C]-0.449942[/C][/ROW]
[ROW][C]69[/C][C]96.5[/C][C]97.0694[/C][C]96.975[/C][C]0.0943866[/C][C]-0.569387[/C][/ROW]
[ROW][C]70[/C][C]96.3[/C][C]96.7645[/C][C]96.3625[/C][C]0.402025[/C][C]-0.464525[/C][/ROW]
[ROW][C]71[/C][C]96.3[/C][C]96.593[/C][C]95.8917[/C][C]0.701331[/C][C]-0.292998[/C][/ROW]
[ROW][C]72[/C][C]96.2[/C][C]96.5812[/C][C]95.6333[/C][C]0.947859[/C][C]-0.381192[/C][/ROW]
[ROW][C]73[/C][C]95.6[/C][C]96.3194[/C][C]95.5917[/C][C]0.72772[/C][C]-0.719387[/C][/ROW]
[ROW][C]74[/C][C]93.5[/C][C]96.2041[/C][C]95.725[/C][C]0.479109[/C][C]-2.70411[/C][/ROW]
[ROW][C]75[/C][C]93.2[/C][C]95.8694[/C][C]95.9458[/C][C]-0.0764468[/C][C]-2.66939[/C][/ROW]
[ROW][C]76[/C][C]93.6[/C][C]95.3076[/C][C]96.2083[/C][C]-0.900752[/C][C]-1.70758[/C][/ROW]
[ROW][C]77[/C][C]94.6[/C][C]95.4763[/C][C]96.5083[/C][C]-1.032[/C][C]-0.876331[/C][/ROW]
[ROW][C]78[/C][C]96.1[/C][C]96.1451[/C][C]96.8208[/C][C]-0.675752[/C][C]-0.045081[/C][/ROW]
[ROW][C]79[/C][C]98.4[/C][C]NA[/C][C]NA[/C][C]-0.725752[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]99.6[/C][C]NA[/C][C]NA[/C][C]0.0582755[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]99.4[/C][C]NA[/C][C]NA[/C][C]0.0943866[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]99.7[/C][C]NA[/C][C]NA[/C][C]0.402025[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]100.1[/C][C]NA[/C][C]NA[/C][C]0.701331[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]99.9[/C][C]NA[/C][C]NA[/C][C]0.947859[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294706&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294706&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	87.5	NA	NA	0.72772	NA
2	87.3	NA	NA	0.479109	NA
3	87.8	NA	NA	-0.0764468	NA
4	88.1	NA	NA	-0.900752	NA
5	88	NA	NA	-1.032	NA
6	87.8	NA	NA	-0.675752	NA
7	87	87.1201	87.8458	-0.725752	-0.120081
8	87.2	87.9458	87.8875	0.0582755	-0.745775
9	87	87.9569	87.8625	0.0943866	-0.956887
10	89.4	88.0437	87.6417	0.402025	1.35631
11	89.1	88.0222	87.3208	0.701331	1.07784
12	87.8	87.9854	87.0375	0.947859	-0.185359
13	87.8	87.5819	86.8542	0.72772	0.218113
14	88	87.2458	86.7667	0.479109	0.754225
15	86.5	86.6152	86.6917	-0.0764468	-0.11522
16	84.1	85.6451	86.5458	-0.900752	-1.54508
17	84.3	85.4097	86.4417	-1.032	-1.10966
18	84.7	85.8867	86.5625	-0.675752	-1.18675
19	85.7	86.0409	86.7667	-0.725752	-0.340914
20	86.4	86.9666	86.9083	0.0582755	-0.566609
21	86	87.1486	87.0542	0.0943866	-1.14855
22	86.9	87.6562	87.2542	0.402025	-0.756192
23	89.1	88.1722	87.4708	0.701331	0.927836
24	90.7	88.7229	87.775	0.947859	1.97714
25	89.8	88.8194	88.0917	0.72772	0.980613
26	89.4	88.8874	88.4083	0.479109	0.512558
27	88.6	88.7944	88.8708	-0.0764468	-0.194387
28	86.8	88.4451	89.3458	-0.900752	-1.64508
29	86.8	88.6805	89.7125	-1.032	-1.8805
30	89.5	89.2826	89.9583	-0.675752	0.217419
31	88.5	89.4451	90.1708	-0.725752	-0.945081
32	91.2	90.5499	90.4917	0.0582755	0.650058
33	92.3	91.0111	90.9167	0.0943866	1.28895
34	92	91.8562	91.4542	0.402025	0.143808
35	92.8	92.8013	92.1	0.701331	-0.00133102
36	92.9	93.5979	92.65	0.947859	-0.697859
37	92.7	93.8694	93.1417	0.72772	-1.16939
38	94.2	94.1374	93.6583	0.479109	0.0625579
39	94	94.0569	94.1333	-0.0764468	-0.0568866
40	94.3	93.6867	94.5875	-0.900752	0.613252
41	94.8	93.9305	94.9625	-1.032	0.869502
42	94.7	94.6576	95.3333	-0.675752	0.042419
43	95.1	95.0992	95.825	-0.725752	0.000752315
44	97	96.3958	96.3375	0.0582755	0.604225
45	97.9	96.9152	96.8208	0.0943866	0.98478
46	97.3	97.702	97.3	0.402025	-0.402025
47	96.5	98.443	97.7417	0.701331	-1.943
48	98.1	99.0979	98.15	0.947859	-0.997859
49	99.3	99.2777	98.55	0.72772	0.0222801
50	99.9	99.3583	98.8792	0.479109	0.541725
51	99.9	99.0236	99.1	-0.0764468	0.876447
52	99.9	98.4117	99.3125	-0.900752	1.48825
53	99.8	98.5722	99.6042	-1.032	1.22784
54	99.5	99.2117	99.8875	-0.675752	0.288252
55	99.9	99.3367	100.063	-0.725752	0.563252
56	100.1	100.208	100.15	0.0582755	-0.108275
57	100.1	100.315	100.221	0.0943866	-0.21522
58	100.2	100.694	100.292	0.402025	-0.493692
59	100.6	100.985	100.283	0.701331	-0.384664
60	100.8	101.131	100.183	0.947859	-0.331192
61	100.8	100.749	100.021	0.72772	0.0514468
62	100.5	100.283	99.8042	0.479109	0.216725
63	101	99.4569	99.5333	-0.0764468	1.54311
64	100.5	98.3201	99.2208	-0.900752	2.17992
65	99	97.8472	98.8792	-1.032	1.15284
66	97.9	97.8326	98.5083	-0.675752	0.067419
67	97.6	97.3742	98.1	-0.725752	0.225752
68	97.2	97.6499	97.5917	0.0582755	-0.449942
69	96.5	97.0694	96.975	0.0943866	-0.569387
70	96.3	96.7645	96.3625	0.402025	-0.464525
71	96.3	96.593	95.8917	0.701331	-0.292998
72	96.2	96.5812	95.6333	0.947859	-0.381192
73	95.6	96.3194	95.5917	0.72772	-0.719387
74	93.5	96.2041	95.725	0.479109	-2.70411
75	93.2	95.8694	95.9458	-0.0764468	-2.66939
76	93.6	95.3076	96.2083	-0.900752	-1.70758
77	94.6	95.4763	96.5083	-1.032	-0.876331
78	96.1	96.1451	96.8208	-0.675752	-0.045081
79	98.4	NA	NA	-0.725752	NA
80	99.6	NA	NA	0.0582755	NA
81	99.4	NA	NA	0.0943866	NA
82	99.7	NA	NA	0.402025	NA
83	100.1	NA	NA	0.701331	NA
84	99.9	NA	NA	0.947859	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