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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 09 Dec 2013 03:58:46 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/09/t1386579695t39ufbeg0ekp8tv.htm/, Retrieved Fri, 19 Apr 2024 13:26:25 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231574, Retrieved Fri, 19 Apr 2024 13:26:25 +0000

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Estimated Impact

115

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-       [Classical Decomposition] [] [2013-12-09 08:58:46] [79b59004c90874912279e9b1431bd052] [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	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231574&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231574&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231574&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	5 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	100.44	NA	NA	1.00223	NA
2	100.47	NA	NA	0.998605	NA
3	100.49	NA	NA	0.99868	NA
4	100.52	NA	NA	0.998493	NA
5	100.47	NA	NA	0.998698	NA
6	100.48	NA	NA	0.998319	NA
7	100.48	100.41	100.638	0.997736	1.00069
8	100.53	100.547	100.681	0.998671	0.999826
9	100.62	100.689	100.718	0.999704	0.999319
10	100.89	101.014	100.756	1.00257	0.998768
11	100.97	101.133	100.8	1.00331	0.998384
12	101.01	101.152	100.851	1.00298	0.998599
13	101.02	101.128	100.903	1.00223	0.998928
14	100.92	100.816	100.957	0.998605	1.00103
15	100.93	100.88	101.013	0.99868	1.0005
16	100.98	100.916	101.068	0.998493	1.00064
17	101.07	100.989	101.121	0.998698	1.0008
18	101.1	101.004	101.174	0.998319	1.00095
19	101.11	100.998	101.227	0.997736	1.00111
20	101.19	101.146	101.281	0.998671	1.00043
21	101.31	101.312	101.342	0.999704	0.999983
22	101.52	101.672	101.411	1.00257	0.99851
23	101.61	101.82	101.485	1.00331	0.997935
24	101.65	101.865	101.562	1.00298	0.997885
25	101.66	101.87	101.642	1.00223	0.997942
26	101.56	101.579	101.72	0.998605	0.999817
27	101.75	101.67	101.805	0.99868	1.00078
28	101.83	101.755	101.909	0.998493	1.00074
29	101.98	101.898	102.03	0.998698	1.00081
30	102.06	101.988	102.16	0.998319	1.0007
31	102.07	102.06	102.291	0.997736	1.0001
32	102.1	102.277	102.413	0.998671	0.998271
33	102.42	102.496	102.526	0.999704	0.999263
34	102.91	102.901	102.637	1.00257	1.00009
35	103.14	103.085	102.745	1.00331	1.00054
36	103.23	103.157	102.85	1.00298	1.00071
37	103.23	103.184	102.954	1.00223	1.00045
38	102.91	102.918	103.062	0.998605	0.999923
39	103.11	103.028	103.164	0.99868	1.0008
40	103.14	103.1	103.255	0.998493	1.00039
41	103.26	103.211	103.346	0.998698	1.00047
42	103.3	103.262	103.436	0.998319	1.00037
43	103.32	103.29	103.524	0.997736	1.00029
44	103.44	103.475	103.613	0.998671	0.999659
45	103.54	103.663	103.694	0.999704	0.998813
46	103.98	104.028	103.761	1.00257	0.999543
47	104.24	104.161	103.818	1.00331	1.00076
48	104.29	104.176	103.867	1.00298	1.00109
49	104.29	104.146	103.914	1.00223	1.00138
50	103.98	103.829	103.974	0.998605	1.00146
51	103.98	103.909	104.046	0.99868	1.00068
52	103.89	103.96	104.117	0.998493	0.999329
53	103.86	104.042	104.178	0.998698	0.998248
54	103.88	104.055	104.23	0.998319	0.998316
55	103.88	104.045	104.281	0.997736	0.998413
56	104.31	104.191	104.33	0.998671	1.00114
57	104.41	104.351	104.382	0.999704	1.00056
58	104.8	104.72	104.452	1.00257	1.00077
59	104.89	104.887	104.542	1.00331	1.00002
60	104.9	104.953	104.641	1.00298	0.999491
61	104.9	104.977	104.742	1.00223	0.999271
62	104.54	104.695	104.841	0.998605	0.998519
63	104.67	104.81	104.948	0.99868	0.998666
64	104.87	104.91	105.069	0.998493	0.999615
65	105.04	105.058	105.195	0.998698	0.999824
66	105.09	105.151	105.328	0.998319	0.999417
67	105.1	105.225	105.464	0.997736	0.998812
68	105.46	105.451	105.591	0.998671	1.00009
69	105.83	105.674	105.705	0.999704	1.00147
70	106.27	106.086	105.814	1.00257	1.00174
71	106.46	106.271	105.921	1.00331	1.00178
72	106.52	106.345	106.029	1.00298	1.00164
73	106.53	106.376	106.139	1.00223	1.00145
74	105.96	106.101	106.25	0.998605	0.998667
75	106	106.214	106.354	0.99868	0.997987
76	106.15	106.287	106.447	0.998493	0.99871
77	106.32	106.398	106.537	0.998698	0.999263
78	106.41	106.446	106.625	0.998319	0.999664
79	106.41	NA	NA	0.997736	NA
80	106.81	NA	NA	0.998671	NA
81	106.99	NA	NA	0.999704	NA
82	107.35	NA	NA	1.00257	NA
83	107.53	NA	NA	1.00331	NA
84	107.56	NA	NA	1.00298	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 100.44 & NA & NA & 1.00223 & NA \tabularnewline
2 & 100.47 & NA & NA & 0.998605 & NA \tabularnewline
3 & 100.49 & NA & NA & 0.99868 & NA \tabularnewline
4 & 100.52 & NA & NA & 0.998493 & NA \tabularnewline
5 & 100.47 & NA & NA & 0.998698 & NA \tabularnewline
6 & 100.48 & NA & NA & 0.998319 & NA \tabularnewline
7 & 100.48 & 100.41 & 100.638 & 0.997736 & 1.00069 \tabularnewline
8 & 100.53 & 100.547 & 100.681 & 0.998671 & 0.999826 \tabularnewline
9 & 100.62 & 100.689 & 100.718 & 0.999704 & 0.999319 \tabularnewline
10 & 100.89 & 101.014 & 100.756 & 1.00257 & 0.998768 \tabularnewline
11 & 100.97 & 101.133 & 100.8 & 1.00331 & 0.998384 \tabularnewline
12 & 101.01 & 101.152 & 100.851 & 1.00298 & 0.998599 \tabularnewline
13 & 101.02 & 101.128 & 100.903 & 1.00223 & 0.998928 \tabularnewline
14 & 100.92 & 100.816 & 100.957 & 0.998605 & 1.00103 \tabularnewline
15 & 100.93 & 100.88 & 101.013 & 0.99868 & 1.0005 \tabularnewline
16 & 100.98 & 100.916 & 101.068 & 0.998493 & 1.00064 \tabularnewline
17 & 101.07 & 100.989 & 101.121 & 0.998698 & 1.0008 \tabularnewline
18 & 101.1 & 101.004 & 101.174 & 0.998319 & 1.00095 \tabularnewline
19 & 101.11 & 100.998 & 101.227 & 0.997736 & 1.00111 \tabularnewline
20 & 101.19 & 101.146 & 101.281 & 0.998671 & 1.00043 \tabularnewline
21 & 101.31 & 101.312 & 101.342 & 0.999704 & 0.999983 \tabularnewline
22 & 101.52 & 101.672 & 101.411 & 1.00257 & 0.99851 \tabularnewline
23 & 101.61 & 101.82 & 101.485 & 1.00331 & 0.997935 \tabularnewline
24 & 101.65 & 101.865 & 101.562 & 1.00298 & 0.997885 \tabularnewline
25 & 101.66 & 101.87 & 101.642 & 1.00223 & 0.997942 \tabularnewline
26 & 101.56 & 101.579 & 101.72 & 0.998605 & 0.999817 \tabularnewline
27 & 101.75 & 101.67 & 101.805 & 0.99868 & 1.00078 \tabularnewline
28 & 101.83 & 101.755 & 101.909 & 0.998493 & 1.00074 \tabularnewline
29 & 101.98 & 101.898 & 102.03 & 0.998698 & 1.00081 \tabularnewline
30 & 102.06 & 101.988 & 102.16 & 0.998319 & 1.0007 \tabularnewline
31 & 102.07 & 102.06 & 102.291 & 0.997736 & 1.0001 \tabularnewline
32 & 102.1 & 102.277 & 102.413 & 0.998671 & 0.998271 \tabularnewline
33 & 102.42 & 102.496 & 102.526 & 0.999704 & 0.999263 \tabularnewline
34 & 102.91 & 102.901 & 102.637 & 1.00257 & 1.00009 \tabularnewline
35 & 103.14 & 103.085 & 102.745 & 1.00331 & 1.00054 \tabularnewline
36 & 103.23 & 103.157 & 102.85 & 1.00298 & 1.00071 \tabularnewline
37 & 103.23 & 103.184 & 102.954 & 1.00223 & 1.00045 \tabularnewline
38 & 102.91 & 102.918 & 103.062 & 0.998605 & 0.999923 \tabularnewline
39 & 103.11 & 103.028 & 103.164 & 0.99868 & 1.0008 \tabularnewline
40 & 103.14 & 103.1 & 103.255 & 0.998493 & 1.00039 \tabularnewline
41 & 103.26 & 103.211 & 103.346 & 0.998698 & 1.00047 \tabularnewline
42 & 103.3 & 103.262 & 103.436 & 0.998319 & 1.00037 \tabularnewline
43 & 103.32 & 103.29 & 103.524 & 0.997736 & 1.00029 \tabularnewline
44 & 103.44 & 103.475 & 103.613 & 0.998671 & 0.999659 \tabularnewline
45 & 103.54 & 103.663 & 103.694 & 0.999704 & 0.998813 \tabularnewline
46 & 103.98 & 104.028 & 103.761 & 1.00257 & 0.999543 \tabularnewline
47 & 104.24 & 104.161 & 103.818 & 1.00331 & 1.00076 \tabularnewline
48 & 104.29 & 104.176 & 103.867 & 1.00298 & 1.00109 \tabularnewline
49 & 104.29 & 104.146 & 103.914 & 1.00223 & 1.00138 \tabularnewline
50 & 103.98 & 103.829 & 103.974 & 0.998605 & 1.00146 \tabularnewline
51 & 103.98 & 103.909 & 104.046 & 0.99868 & 1.00068 \tabularnewline
52 & 103.89 & 103.96 & 104.117 & 0.998493 & 0.999329 \tabularnewline
53 & 103.86 & 104.042 & 104.178 & 0.998698 & 0.998248 \tabularnewline
54 & 103.88 & 104.055 & 104.23 & 0.998319 & 0.998316 \tabularnewline
55 & 103.88 & 104.045 & 104.281 & 0.997736 & 0.998413 \tabularnewline
56 & 104.31 & 104.191 & 104.33 & 0.998671 & 1.00114 \tabularnewline
57 & 104.41 & 104.351 & 104.382 & 0.999704 & 1.00056 \tabularnewline
58 & 104.8 & 104.72 & 104.452 & 1.00257 & 1.00077 \tabularnewline
59 & 104.89 & 104.887 & 104.542 & 1.00331 & 1.00002 \tabularnewline
60 & 104.9 & 104.953 & 104.641 & 1.00298 & 0.999491 \tabularnewline
61 & 104.9 & 104.977 & 104.742 & 1.00223 & 0.999271 \tabularnewline
62 & 104.54 & 104.695 & 104.841 & 0.998605 & 0.998519 \tabularnewline
63 & 104.67 & 104.81 & 104.948 & 0.99868 & 0.998666 \tabularnewline
64 & 104.87 & 104.91 & 105.069 & 0.998493 & 0.999615 \tabularnewline
65 & 105.04 & 105.058 & 105.195 & 0.998698 & 0.999824 \tabularnewline
66 & 105.09 & 105.151 & 105.328 & 0.998319 & 0.999417 \tabularnewline
67 & 105.1 & 105.225 & 105.464 & 0.997736 & 0.998812 \tabularnewline
68 & 105.46 & 105.451 & 105.591 & 0.998671 & 1.00009 \tabularnewline
69 & 105.83 & 105.674 & 105.705 & 0.999704 & 1.00147 \tabularnewline
70 & 106.27 & 106.086 & 105.814 & 1.00257 & 1.00174 \tabularnewline
71 & 106.46 & 106.271 & 105.921 & 1.00331 & 1.00178 \tabularnewline
72 & 106.52 & 106.345 & 106.029 & 1.00298 & 1.00164 \tabularnewline
73 & 106.53 & 106.376 & 106.139 & 1.00223 & 1.00145 \tabularnewline
74 & 105.96 & 106.101 & 106.25 & 0.998605 & 0.998667 \tabularnewline
75 & 106 & 106.214 & 106.354 & 0.99868 & 0.997987 \tabularnewline
76 & 106.15 & 106.287 & 106.447 & 0.998493 & 0.99871 \tabularnewline
77 & 106.32 & 106.398 & 106.537 & 0.998698 & 0.999263 \tabularnewline
78 & 106.41 & 106.446 & 106.625 & 0.998319 & 0.999664 \tabularnewline
79 & 106.41 & NA & NA & 0.997736 & NA \tabularnewline
80 & 106.81 & NA & NA & 0.998671 & NA \tabularnewline
81 & 106.99 & NA & NA & 0.999704 & NA \tabularnewline
82 & 107.35 & NA & NA & 1.00257 & NA \tabularnewline
83 & 107.53 & NA & NA & 1.00331 & NA \tabularnewline
84 & 107.56 & NA & NA & 1.00298 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231574&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]100.44[/C][C]NA[/C][C]NA[/C][C]1.00223[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]100.47[/C][C]NA[/C][C]NA[/C][C]0.998605[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100.49[/C][C]NA[/C][C]NA[/C][C]0.99868[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]100.52[/C][C]NA[/C][C]NA[/C][C]0.998493[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]100.47[/C][C]NA[/C][C]NA[/C][C]0.998698[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.48[/C][C]NA[/C][C]NA[/C][C]0.998319[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]100.48[/C][C]100.41[/C][C]100.638[/C][C]0.997736[/C][C]1.00069[/C][/ROW]
[ROW][C]8[/C][C]100.53[/C][C]100.547[/C][C]100.681[/C][C]0.998671[/C][C]0.999826[/C][/ROW]
[ROW][C]9[/C][C]100.62[/C][C]100.689[/C][C]100.718[/C][C]0.999704[/C][C]0.999319[/C][/ROW]
[ROW][C]10[/C][C]100.89[/C][C]101.014[/C][C]100.756[/C][C]1.00257[/C][C]0.998768[/C][/ROW]
[ROW][C]11[/C][C]100.97[/C][C]101.133[/C][C]100.8[/C][C]1.00331[/C][C]0.998384[/C][/ROW]
[ROW][C]12[/C][C]101.01[/C][C]101.152[/C][C]100.851[/C][C]1.00298[/C][C]0.998599[/C][/ROW]
[ROW][C]13[/C][C]101.02[/C][C]101.128[/C][C]100.903[/C][C]1.00223[/C][C]0.998928[/C][/ROW]
[ROW][C]14[/C][C]100.92[/C][C]100.816[/C][C]100.957[/C][C]0.998605[/C][C]1.00103[/C][/ROW]
[ROW][C]15[/C][C]100.93[/C][C]100.88[/C][C]101.013[/C][C]0.99868[/C][C]1.0005[/C][/ROW]
[ROW][C]16[/C][C]100.98[/C][C]100.916[/C][C]101.068[/C][C]0.998493[/C][C]1.00064[/C][/ROW]
[ROW][C]17[/C][C]101.07[/C][C]100.989[/C][C]101.121[/C][C]0.998698[/C][C]1.0008[/C][/ROW]
[ROW][C]18[/C][C]101.1[/C][C]101.004[/C][C]101.174[/C][C]0.998319[/C][C]1.00095[/C][/ROW]
[ROW][C]19[/C][C]101.11[/C][C]100.998[/C][C]101.227[/C][C]0.997736[/C][C]1.00111[/C][/ROW]
[ROW][C]20[/C][C]101.19[/C][C]101.146[/C][C]101.281[/C][C]0.998671[/C][C]1.00043[/C][/ROW]
[ROW][C]21[/C][C]101.31[/C][C]101.312[/C][C]101.342[/C][C]0.999704[/C][C]0.999983[/C][/ROW]
[ROW][C]22[/C][C]101.52[/C][C]101.672[/C][C]101.411[/C][C]1.00257[/C][C]0.99851[/C][/ROW]
[ROW][C]23[/C][C]101.61[/C][C]101.82[/C][C]101.485[/C][C]1.00331[/C][C]0.997935[/C][/ROW]
[ROW][C]24[/C][C]101.65[/C][C]101.865[/C][C]101.562[/C][C]1.00298[/C][C]0.997885[/C][/ROW]
[ROW][C]25[/C][C]101.66[/C][C]101.87[/C][C]101.642[/C][C]1.00223[/C][C]0.997942[/C][/ROW]
[ROW][C]26[/C][C]101.56[/C][C]101.579[/C][C]101.72[/C][C]0.998605[/C][C]0.999817[/C][/ROW]
[ROW][C]27[/C][C]101.75[/C][C]101.67[/C][C]101.805[/C][C]0.99868[/C][C]1.00078[/C][/ROW]
[ROW][C]28[/C][C]101.83[/C][C]101.755[/C][C]101.909[/C][C]0.998493[/C][C]1.00074[/C][/ROW]
[ROW][C]29[/C][C]101.98[/C][C]101.898[/C][C]102.03[/C][C]0.998698[/C][C]1.00081[/C][/ROW]
[ROW][C]30[/C][C]102.06[/C][C]101.988[/C][C]102.16[/C][C]0.998319[/C][C]1.0007[/C][/ROW]
[ROW][C]31[/C][C]102.07[/C][C]102.06[/C][C]102.291[/C][C]0.997736[/C][C]1.0001[/C][/ROW]
[ROW][C]32[/C][C]102.1[/C][C]102.277[/C][C]102.413[/C][C]0.998671[/C][C]0.998271[/C][/ROW]
[ROW][C]33[/C][C]102.42[/C][C]102.496[/C][C]102.526[/C][C]0.999704[/C][C]0.999263[/C][/ROW]
[ROW][C]34[/C][C]102.91[/C][C]102.901[/C][C]102.637[/C][C]1.00257[/C][C]1.00009[/C][/ROW]
[ROW][C]35[/C][C]103.14[/C][C]103.085[/C][C]102.745[/C][C]1.00331[/C][C]1.00054[/C][/ROW]
[ROW][C]36[/C][C]103.23[/C][C]103.157[/C][C]102.85[/C][C]1.00298[/C][C]1.00071[/C][/ROW]
[ROW][C]37[/C][C]103.23[/C][C]103.184[/C][C]102.954[/C][C]1.00223[/C][C]1.00045[/C][/ROW]
[ROW][C]38[/C][C]102.91[/C][C]102.918[/C][C]103.062[/C][C]0.998605[/C][C]0.999923[/C][/ROW]
[ROW][C]39[/C][C]103.11[/C][C]103.028[/C][C]103.164[/C][C]0.99868[/C][C]1.0008[/C][/ROW]
[ROW][C]40[/C][C]103.14[/C][C]103.1[/C][C]103.255[/C][C]0.998493[/C][C]1.00039[/C][/ROW]
[ROW][C]41[/C][C]103.26[/C][C]103.211[/C][C]103.346[/C][C]0.998698[/C][C]1.00047[/C][/ROW]
[ROW][C]42[/C][C]103.3[/C][C]103.262[/C][C]103.436[/C][C]0.998319[/C][C]1.00037[/C][/ROW]
[ROW][C]43[/C][C]103.32[/C][C]103.29[/C][C]103.524[/C][C]0.997736[/C][C]1.00029[/C][/ROW]
[ROW][C]44[/C][C]103.44[/C][C]103.475[/C][C]103.613[/C][C]0.998671[/C][C]0.999659[/C][/ROW]
[ROW][C]45[/C][C]103.54[/C][C]103.663[/C][C]103.694[/C][C]0.999704[/C][C]0.998813[/C][/ROW]
[ROW][C]46[/C][C]103.98[/C][C]104.028[/C][C]103.761[/C][C]1.00257[/C][C]0.999543[/C][/ROW]
[ROW][C]47[/C][C]104.24[/C][C]104.161[/C][C]103.818[/C][C]1.00331[/C][C]1.00076[/C][/ROW]
[ROW][C]48[/C][C]104.29[/C][C]104.176[/C][C]103.867[/C][C]1.00298[/C][C]1.00109[/C][/ROW]
[ROW][C]49[/C][C]104.29[/C][C]104.146[/C][C]103.914[/C][C]1.00223[/C][C]1.00138[/C][/ROW]
[ROW][C]50[/C][C]103.98[/C][C]103.829[/C][C]103.974[/C][C]0.998605[/C][C]1.00146[/C][/ROW]
[ROW][C]51[/C][C]103.98[/C][C]103.909[/C][C]104.046[/C][C]0.99868[/C][C]1.00068[/C][/ROW]
[ROW][C]52[/C][C]103.89[/C][C]103.96[/C][C]104.117[/C][C]0.998493[/C][C]0.999329[/C][/ROW]
[ROW][C]53[/C][C]103.86[/C][C]104.042[/C][C]104.178[/C][C]0.998698[/C][C]0.998248[/C][/ROW]
[ROW][C]54[/C][C]103.88[/C][C]104.055[/C][C]104.23[/C][C]0.998319[/C][C]0.998316[/C][/ROW]
[ROW][C]55[/C][C]103.88[/C][C]104.045[/C][C]104.281[/C][C]0.997736[/C][C]0.998413[/C][/ROW]
[ROW][C]56[/C][C]104.31[/C][C]104.191[/C][C]104.33[/C][C]0.998671[/C][C]1.00114[/C][/ROW]
[ROW][C]57[/C][C]104.41[/C][C]104.351[/C][C]104.382[/C][C]0.999704[/C][C]1.00056[/C][/ROW]
[ROW][C]58[/C][C]104.8[/C][C]104.72[/C][C]104.452[/C][C]1.00257[/C][C]1.00077[/C][/ROW]
[ROW][C]59[/C][C]104.89[/C][C]104.887[/C][C]104.542[/C][C]1.00331[/C][C]1.00002[/C][/ROW]
[ROW][C]60[/C][C]104.9[/C][C]104.953[/C][C]104.641[/C][C]1.00298[/C][C]0.999491[/C][/ROW]
[ROW][C]61[/C][C]104.9[/C][C]104.977[/C][C]104.742[/C][C]1.00223[/C][C]0.999271[/C][/ROW]
[ROW][C]62[/C][C]104.54[/C][C]104.695[/C][C]104.841[/C][C]0.998605[/C][C]0.998519[/C][/ROW]
[ROW][C]63[/C][C]104.67[/C][C]104.81[/C][C]104.948[/C][C]0.99868[/C][C]0.998666[/C][/ROW]
[ROW][C]64[/C][C]104.87[/C][C]104.91[/C][C]105.069[/C][C]0.998493[/C][C]0.999615[/C][/ROW]
[ROW][C]65[/C][C]105.04[/C][C]105.058[/C][C]105.195[/C][C]0.998698[/C][C]0.999824[/C][/ROW]
[ROW][C]66[/C][C]105.09[/C][C]105.151[/C][C]105.328[/C][C]0.998319[/C][C]0.999417[/C][/ROW]
[ROW][C]67[/C][C]105.1[/C][C]105.225[/C][C]105.464[/C][C]0.997736[/C][C]0.998812[/C][/ROW]
[ROW][C]68[/C][C]105.46[/C][C]105.451[/C][C]105.591[/C][C]0.998671[/C][C]1.00009[/C][/ROW]
[ROW][C]69[/C][C]105.83[/C][C]105.674[/C][C]105.705[/C][C]0.999704[/C][C]1.00147[/C][/ROW]
[ROW][C]70[/C][C]106.27[/C][C]106.086[/C][C]105.814[/C][C]1.00257[/C][C]1.00174[/C][/ROW]
[ROW][C]71[/C][C]106.46[/C][C]106.271[/C][C]105.921[/C][C]1.00331[/C][C]1.00178[/C][/ROW]
[ROW][C]72[/C][C]106.52[/C][C]106.345[/C][C]106.029[/C][C]1.00298[/C][C]1.00164[/C][/ROW]
[ROW][C]73[/C][C]106.53[/C][C]106.376[/C][C]106.139[/C][C]1.00223[/C][C]1.00145[/C][/ROW]
[ROW][C]74[/C][C]105.96[/C][C]106.101[/C][C]106.25[/C][C]0.998605[/C][C]0.998667[/C][/ROW]
[ROW][C]75[/C][C]106[/C][C]106.214[/C][C]106.354[/C][C]0.99868[/C][C]0.997987[/C][/ROW]
[ROW][C]76[/C][C]106.15[/C][C]106.287[/C][C]106.447[/C][C]0.998493[/C][C]0.99871[/C][/ROW]
[ROW][C]77[/C][C]106.32[/C][C]106.398[/C][C]106.537[/C][C]0.998698[/C][C]0.999263[/C][/ROW]
[ROW][C]78[/C][C]106.41[/C][C]106.446[/C][C]106.625[/C][C]0.998319[/C][C]0.999664[/C][/ROW]
[ROW][C]79[/C][C]106.41[/C][C]NA[/C][C]NA[/C][C]0.997736[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]106.81[/C][C]NA[/C][C]NA[/C][C]0.998671[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]106.99[/C][C]NA[/C][C]NA[/C][C]0.999704[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]107.35[/C][C]NA[/C][C]NA[/C][C]1.00257[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]107.53[/C][C]NA[/C][C]NA[/C][C]1.00331[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]107.56[/C][C]NA[/C][C]NA[/C][C]1.00298[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231574&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231574&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	100.44	NA	NA	1.00223	NA
2	100.47	NA	NA	0.998605	NA
3	100.49	NA	NA	0.99868	NA
4	100.52	NA	NA	0.998493	NA
5	100.47	NA	NA	0.998698	NA
6	100.48	NA	NA	0.998319	NA
7	100.48	100.41	100.638	0.997736	1.00069
8	100.53	100.547	100.681	0.998671	0.999826
9	100.62	100.689	100.718	0.999704	0.999319
10	100.89	101.014	100.756	1.00257	0.998768
11	100.97	101.133	100.8	1.00331	0.998384
12	101.01	101.152	100.851	1.00298	0.998599
13	101.02	101.128	100.903	1.00223	0.998928
14	100.92	100.816	100.957	0.998605	1.00103
15	100.93	100.88	101.013	0.99868	1.0005
16	100.98	100.916	101.068	0.998493	1.00064
17	101.07	100.989	101.121	0.998698	1.0008
18	101.1	101.004	101.174	0.998319	1.00095
19	101.11	100.998	101.227	0.997736	1.00111
20	101.19	101.146	101.281	0.998671	1.00043
21	101.31	101.312	101.342	0.999704	0.999983
22	101.52	101.672	101.411	1.00257	0.99851
23	101.61	101.82	101.485	1.00331	0.997935
24	101.65	101.865	101.562	1.00298	0.997885
25	101.66	101.87	101.642	1.00223	0.997942
26	101.56	101.579	101.72	0.998605	0.999817
27	101.75	101.67	101.805	0.99868	1.00078
28	101.83	101.755	101.909	0.998493	1.00074
29	101.98	101.898	102.03	0.998698	1.00081
30	102.06	101.988	102.16	0.998319	1.0007
31	102.07	102.06	102.291	0.997736	1.0001
32	102.1	102.277	102.413	0.998671	0.998271
33	102.42	102.496	102.526	0.999704	0.999263
34	102.91	102.901	102.637	1.00257	1.00009
35	103.14	103.085	102.745	1.00331	1.00054
36	103.23	103.157	102.85	1.00298	1.00071
37	103.23	103.184	102.954	1.00223	1.00045
38	102.91	102.918	103.062	0.998605	0.999923
39	103.11	103.028	103.164	0.99868	1.0008
40	103.14	103.1	103.255	0.998493	1.00039
41	103.26	103.211	103.346	0.998698	1.00047
42	103.3	103.262	103.436	0.998319	1.00037
43	103.32	103.29	103.524	0.997736	1.00029
44	103.44	103.475	103.613	0.998671	0.999659
45	103.54	103.663	103.694	0.999704	0.998813
46	103.98	104.028	103.761	1.00257	0.999543
47	104.24	104.161	103.818	1.00331	1.00076
48	104.29	104.176	103.867	1.00298	1.00109
49	104.29	104.146	103.914	1.00223	1.00138
50	103.98	103.829	103.974	0.998605	1.00146
51	103.98	103.909	104.046	0.99868	1.00068
52	103.89	103.96	104.117	0.998493	0.999329
53	103.86	104.042	104.178	0.998698	0.998248
54	103.88	104.055	104.23	0.998319	0.998316
55	103.88	104.045	104.281	0.997736	0.998413
56	104.31	104.191	104.33	0.998671	1.00114
57	104.41	104.351	104.382	0.999704	1.00056
58	104.8	104.72	104.452	1.00257	1.00077
59	104.89	104.887	104.542	1.00331	1.00002
60	104.9	104.953	104.641	1.00298	0.999491
61	104.9	104.977	104.742	1.00223	0.999271
62	104.54	104.695	104.841	0.998605	0.998519
63	104.67	104.81	104.948	0.99868	0.998666
64	104.87	104.91	105.069	0.998493	0.999615
65	105.04	105.058	105.195	0.998698	0.999824
66	105.09	105.151	105.328	0.998319	0.999417
67	105.1	105.225	105.464	0.997736	0.998812
68	105.46	105.451	105.591	0.998671	1.00009
69	105.83	105.674	105.705	0.999704	1.00147
70	106.27	106.086	105.814	1.00257	1.00174
71	106.46	106.271	105.921	1.00331	1.00178
72	106.52	106.345	106.029	1.00298	1.00164
73	106.53	106.376	106.139	1.00223	1.00145
74	105.96	106.101	106.25	0.998605	0.998667
75	106	106.214	106.354	0.99868	0.997987
76	106.15	106.287	106.447	0.998493	0.99871
77	106.32	106.398	106.537	0.998698	0.999263
78	106.41	106.446	106.625	0.998319	0.999664
79	106.41	NA	NA	0.997736	NA
80	106.81	NA	NA	0.998671	NA
81	106.99	NA	NA	0.999704	NA
82	107.35	NA	NA	1.00257	NA
83	107.53	NA	NA	1.00331	NA
84	107.56	NA	NA	1.00298	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