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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 09 Dec 2013 06:12:36 -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/t1386587573dxwd9piqa7y0vo6.htm/, Retrieved Thu, 25 Apr 2024 08:07:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=231613, Retrieved Thu, 25 Apr 2024 08:07:11 +0000

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-       [Classical Decomposition] [] [2013-12-09 11:12:36] [7cfa17a50f4a533c9a90677dc09cc88d] [Current]

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Dataseries X:

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1,93
2,02
1,85
1,77
1,81
1,67
1,55
1,62
1,79
1,73
1,77
1,95
2,08
2,26
2,02
1,9
1,97
1,76
1,93
1,91
1,96
1,99
1,98
1,96
1,95
2,26
2,07
2,02
2,07
1,88
1,75
1,78
1,87
1,94
2,03
2,13
2,04
2,18
2,02
1,99
2,09
1,88
1,8
1,77
1,85
1,9
2,03
2,02
2,09
2,3
2,16
2,02
2,31
1,98
1,74
1,82
2,07
2,04
2,07
2,13
2,14
2,43
2,26
2,11
2,19
2,04
2,04
2,05
2,08
1,98
2,07
2,12
2,15
2,35
2,19
2,17
2,3
2,09
1,95
1,89
1,95
1,98
1,95
2,06

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	6 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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231613&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]6 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=231613&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231613&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	6 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.93	NA	NA	0.0563368	NA
2	2.02	NA	NA	0.273351	NA
3	1.85	NA	NA	0.0936979	NA
4	1.77	NA	NA	0.00585069	NA
5	1.81	NA	NA	0.122865	NA
6	1.67	NA	NA	-0.095816	NA
7	1.55	1.60939	1.79458	-0.185191	-0.0593924
8	1.62	1.64516	1.81083	-0.165677	-0.0251562
9	1.79	1.76925	1.82792	-0.0586632	0.0207465
10	1.73	1.76995	1.84042	-0.0704688	-0.0399479
11	1.77	1.83752	1.8525	-0.0149826	-0.0675174
12	1.95	1.90161	1.86292	0.0386979	0.0483854
13	2.08	1.93884	1.8825	0.0563368	0.141163
14	2.26	2.18377	1.91042	0.273351	0.0762326
15	2.02	2.02328	1.92958	0.0936979	-0.00328125
16	1.9	1.95335	1.9475	0.00585069	-0.0533507
17	1.97	2.08995	1.96708	0.122865	-0.119948
18	1.76	1.88043	1.97625	-0.095816	-0.120434
19	1.93	1.78606	1.97125	-0.185191	0.143941
20	1.91	1.80016	1.96583	-0.165677	0.109844
21	1.96	1.90925	1.96792	-0.0586632	0.0507465
22	1.99	1.90453	1.975	-0.0704688	0.0854688
23	1.98	1.96918	1.98417	-0.0149826	0.010816
24	1.96	2.03203	1.99333	0.0386979	-0.0720312
25	1.95	2.04717	1.99083	0.0563368	-0.0971701
26	2.26	2.25127	1.97792	0.273351	0.00873264
27	2.07	2.06245	1.96875	0.0936979	0.00755208
28	2.02	1.96877	1.96292	0.00585069	0.0512326
29	2.07	2.08578	1.96292	0.122865	-0.0157812
30	1.88	1.87627	1.97208	-0.095816	0.00373264
31	1.75	1.79773	1.98292	-0.185191	-0.0477257
32	1.78	1.81766	1.98333	-0.165677	-0.0376562
33	1.87	1.91925	1.97792	-0.0586632	-0.0492535
34	1.94	1.90411	1.97458	-0.0704688	0.0358854
35	2.03	1.95918	1.97417	-0.0149826	0.070816
36	2.13	2.0137	1.975	0.0386979	0.116302
37	2.04	2.03342	1.97708	0.0563368	0.00657986
38	2.18	2.2521	1.97875	0.273351	-0.0721007
39	2.02	2.0712	1.9775	0.0936979	-0.0511979
40	1.99	1.98085	1.975	0.00585069	0.00914931
41	2.09	2.0962	1.97333	0.122865	-0.00619792
42	1.88	1.87293	1.96875	-0.095816	0.00706597
43	1.8	1.78106	1.96625	-0.185191	0.018941
44	1.77	1.80766	1.97333	-0.165677	-0.0376562
45	1.85	1.9255	1.98417	-0.0586632	-0.0755035
46	1.9	1.92078	1.99125	-0.0704688	-0.0207812
47	2.03	1.98668	2.00167	-0.0149826	0.043316
48	2.02	2.0537	2.015	0.0386979	-0.0336979
49	2.09	2.073	2.01667	0.0563368	0.0169965
50	2.3	2.2896	2.01625	0.273351	0.0103993
51	2.16	2.1212	2.0275	0.0936979	0.0388021
52	2.02	2.04835	2.0425	0.00585069	-0.0283507
53	2.31	2.17286	2.05	0.122865	0.137135
54	1.98	1.96043	2.05625	-0.095816	0.019566
55	1.74	1.87773	2.06292	-0.185191	-0.137726
56	1.82	1.90474	2.07042	-0.165677	-0.0847396
57	2.07	2.02134	2.08	-0.0586632	0.0486632
58	2.04	2.01745	2.08792	-0.0704688	0.0225521
59	2.07	2.07168	2.08667	-0.0149826	-0.00168403
60	2.13	2.12286	2.08417	0.0386979	0.00713542
61	2.14	2.1555	2.09917	0.0563368	-0.0155035
62	2.43	2.3946	2.12125	0.273351	0.0353993
63	2.26	2.22495	2.13125	0.0936979	0.0350521
64	2.11	2.13502	2.12917	0.00585069	-0.0250174
65	2.19	2.24953	2.12667	0.122865	-0.0595313
66	2.04	2.03043	2.12625	-0.095816	0.00956597
67	2.04	1.94106	2.12625	-0.185191	0.098941
68	2.05	1.95766	2.12333	-0.165677	0.0923438
69	2.08	2.05842	2.11708	-0.0586632	0.0215799
70	1.98	2.0462	2.11667	-0.0704688	-0.0661979
71	2.07	2.10877	2.12375	-0.0149826	-0.0387674
72	2.12	2.16911	2.13042	0.0386979	-0.0491146
73	2.15	2.18509	2.12875	0.0563368	-0.0350868
74	2.35	2.39168	2.11833	0.273351	-0.041684
75	2.19	2.19995	2.10625	0.0936979	-0.00994792
76	2.17	2.10668	2.10083	0.00585069	0.063316
77	2.3	2.2187	2.09583	0.122865	0.0813021
78	2.09	1.99252	2.08833	-0.095816	0.0974826
79	1.95	NA	NA	-0.185191	NA
80	1.89	NA	NA	-0.165677	NA
81	1.95	NA	NA	-0.0586632	NA
82	1.98	NA	NA	-0.0704688	NA
83	1.95	NA	NA	-0.0149826	NA
84	2.06	NA	NA	0.0386979	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.93 & NA & NA & 0.0563368 & NA \tabularnewline
2 & 2.02 & NA & NA & 0.273351 & NA \tabularnewline
3 & 1.85 & NA & NA & 0.0936979 & NA \tabularnewline
4 & 1.77 & NA & NA & 0.00585069 & NA \tabularnewline
5 & 1.81 & NA & NA & 0.122865 & NA \tabularnewline
6 & 1.67 & NA & NA & -0.095816 & NA \tabularnewline
7 & 1.55 & 1.60939 & 1.79458 & -0.185191 & -0.0593924 \tabularnewline
8 & 1.62 & 1.64516 & 1.81083 & -0.165677 & -0.0251562 \tabularnewline
9 & 1.79 & 1.76925 & 1.82792 & -0.0586632 & 0.0207465 \tabularnewline
10 & 1.73 & 1.76995 & 1.84042 & -0.0704688 & -0.0399479 \tabularnewline
11 & 1.77 & 1.83752 & 1.8525 & -0.0149826 & -0.0675174 \tabularnewline
12 & 1.95 & 1.90161 & 1.86292 & 0.0386979 & 0.0483854 \tabularnewline
13 & 2.08 & 1.93884 & 1.8825 & 0.0563368 & 0.141163 \tabularnewline
14 & 2.26 & 2.18377 & 1.91042 & 0.273351 & 0.0762326 \tabularnewline
15 & 2.02 & 2.02328 & 1.92958 & 0.0936979 & -0.00328125 \tabularnewline
16 & 1.9 & 1.95335 & 1.9475 & 0.00585069 & -0.0533507 \tabularnewline
17 & 1.97 & 2.08995 & 1.96708 & 0.122865 & -0.119948 \tabularnewline
18 & 1.76 & 1.88043 & 1.97625 & -0.095816 & -0.120434 \tabularnewline
19 & 1.93 & 1.78606 & 1.97125 & -0.185191 & 0.143941 \tabularnewline
20 & 1.91 & 1.80016 & 1.96583 & -0.165677 & 0.109844 \tabularnewline
21 & 1.96 & 1.90925 & 1.96792 & -0.0586632 & 0.0507465 \tabularnewline
22 & 1.99 & 1.90453 & 1.975 & -0.0704688 & 0.0854688 \tabularnewline
23 & 1.98 & 1.96918 & 1.98417 & -0.0149826 & 0.010816 \tabularnewline
24 & 1.96 & 2.03203 & 1.99333 & 0.0386979 & -0.0720312 \tabularnewline
25 & 1.95 & 2.04717 & 1.99083 & 0.0563368 & -0.0971701 \tabularnewline
26 & 2.26 & 2.25127 & 1.97792 & 0.273351 & 0.00873264 \tabularnewline
27 & 2.07 & 2.06245 & 1.96875 & 0.0936979 & 0.00755208 \tabularnewline
28 & 2.02 & 1.96877 & 1.96292 & 0.00585069 & 0.0512326 \tabularnewline
29 & 2.07 & 2.08578 & 1.96292 & 0.122865 & -0.0157812 \tabularnewline
30 & 1.88 & 1.87627 & 1.97208 & -0.095816 & 0.00373264 \tabularnewline
31 & 1.75 & 1.79773 & 1.98292 & -0.185191 & -0.0477257 \tabularnewline
32 & 1.78 & 1.81766 & 1.98333 & -0.165677 & -0.0376562 \tabularnewline
33 & 1.87 & 1.91925 & 1.97792 & -0.0586632 & -0.0492535 \tabularnewline
34 & 1.94 & 1.90411 & 1.97458 & -0.0704688 & 0.0358854 \tabularnewline
35 & 2.03 & 1.95918 & 1.97417 & -0.0149826 & 0.070816 \tabularnewline
36 & 2.13 & 2.0137 & 1.975 & 0.0386979 & 0.116302 \tabularnewline
37 & 2.04 & 2.03342 & 1.97708 & 0.0563368 & 0.00657986 \tabularnewline
38 & 2.18 & 2.2521 & 1.97875 & 0.273351 & -0.0721007 \tabularnewline
39 & 2.02 & 2.0712 & 1.9775 & 0.0936979 & -0.0511979 \tabularnewline
40 & 1.99 & 1.98085 & 1.975 & 0.00585069 & 0.00914931 \tabularnewline
41 & 2.09 & 2.0962 & 1.97333 & 0.122865 & -0.00619792 \tabularnewline
42 & 1.88 & 1.87293 & 1.96875 & -0.095816 & 0.00706597 \tabularnewline
43 & 1.8 & 1.78106 & 1.96625 & -0.185191 & 0.018941 \tabularnewline
44 & 1.77 & 1.80766 & 1.97333 & -0.165677 & -0.0376562 \tabularnewline
45 & 1.85 & 1.9255 & 1.98417 & -0.0586632 & -0.0755035 \tabularnewline
46 & 1.9 & 1.92078 & 1.99125 & -0.0704688 & -0.0207812 \tabularnewline
47 & 2.03 & 1.98668 & 2.00167 & -0.0149826 & 0.043316 \tabularnewline
48 & 2.02 & 2.0537 & 2.015 & 0.0386979 & -0.0336979 \tabularnewline
49 & 2.09 & 2.073 & 2.01667 & 0.0563368 & 0.0169965 \tabularnewline
50 & 2.3 & 2.2896 & 2.01625 & 0.273351 & 0.0103993 \tabularnewline
51 & 2.16 & 2.1212 & 2.0275 & 0.0936979 & 0.0388021 \tabularnewline
52 & 2.02 & 2.04835 & 2.0425 & 0.00585069 & -0.0283507 \tabularnewline
53 & 2.31 & 2.17286 & 2.05 & 0.122865 & 0.137135 \tabularnewline
54 & 1.98 & 1.96043 & 2.05625 & -0.095816 & 0.019566 \tabularnewline
55 & 1.74 & 1.87773 & 2.06292 & -0.185191 & -0.137726 \tabularnewline
56 & 1.82 & 1.90474 & 2.07042 & -0.165677 & -0.0847396 \tabularnewline
57 & 2.07 & 2.02134 & 2.08 & -0.0586632 & 0.0486632 \tabularnewline
58 & 2.04 & 2.01745 & 2.08792 & -0.0704688 & 0.0225521 \tabularnewline
59 & 2.07 & 2.07168 & 2.08667 & -0.0149826 & -0.00168403 \tabularnewline
60 & 2.13 & 2.12286 & 2.08417 & 0.0386979 & 0.00713542 \tabularnewline
61 & 2.14 & 2.1555 & 2.09917 & 0.0563368 & -0.0155035 \tabularnewline
62 & 2.43 & 2.3946 & 2.12125 & 0.273351 & 0.0353993 \tabularnewline
63 & 2.26 & 2.22495 & 2.13125 & 0.0936979 & 0.0350521 \tabularnewline
64 & 2.11 & 2.13502 & 2.12917 & 0.00585069 & -0.0250174 \tabularnewline
65 & 2.19 & 2.24953 & 2.12667 & 0.122865 & -0.0595313 \tabularnewline
66 & 2.04 & 2.03043 & 2.12625 & -0.095816 & 0.00956597 \tabularnewline
67 & 2.04 & 1.94106 & 2.12625 & -0.185191 & 0.098941 \tabularnewline
68 & 2.05 & 1.95766 & 2.12333 & -0.165677 & 0.0923438 \tabularnewline
69 & 2.08 & 2.05842 & 2.11708 & -0.0586632 & 0.0215799 \tabularnewline
70 & 1.98 & 2.0462 & 2.11667 & -0.0704688 & -0.0661979 \tabularnewline
71 & 2.07 & 2.10877 & 2.12375 & -0.0149826 & -0.0387674 \tabularnewline
72 & 2.12 & 2.16911 & 2.13042 & 0.0386979 & -0.0491146 \tabularnewline
73 & 2.15 & 2.18509 & 2.12875 & 0.0563368 & -0.0350868 \tabularnewline
74 & 2.35 & 2.39168 & 2.11833 & 0.273351 & -0.041684 \tabularnewline
75 & 2.19 & 2.19995 & 2.10625 & 0.0936979 & -0.00994792 \tabularnewline
76 & 2.17 & 2.10668 & 2.10083 & 0.00585069 & 0.063316 \tabularnewline
77 & 2.3 & 2.2187 & 2.09583 & 0.122865 & 0.0813021 \tabularnewline
78 & 2.09 & 1.99252 & 2.08833 & -0.095816 & 0.0974826 \tabularnewline
79 & 1.95 & NA & NA & -0.185191 & NA \tabularnewline
80 & 1.89 & NA & NA & -0.165677 & NA \tabularnewline
81 & 1.95 & NA & NA & -0.0586632 & NA \tabularnewline
82 & 1.98 & NA & NA & -0.0704688 & NA \tabularnewline
83 & 1.95 & NA & NA & -0.0149826 & NA \tabularnewline
84 & 2.06 & NA & NA & 0.0386979 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=231613&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]1.93[/C][C]NA[/C][C]NA[/C][C]0.0563368[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.02[/C][C]NA[/C][C]NA[/C][C]0.273351[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.85[/C][C]NA[/C][C]NA[/C][C]0.0936979[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.77[/C][C]NA[/C][C]NA[/C][C]0.00585069[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.81[/C][C]NA[/C][C]NA[/C][C]0.122865[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.67[/C][C]NA[/C][C]NA[/C][C]-0.095816[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.55[/C][C]1.60939[/C][C]1.79458[/C][C]-0.185191[/C][C]-0.0593924[/C][/ROW]
[ROW][C]8[/C][C]1.62[/C][C]1.64516[/C][C]1.81083[/C][C]-0.165677[/C][C]-0.0251562[/C][/ROW]
[ROW][C]9[/C][C]1.79[/C][C]1.76925[/C][C]1.82792[/C][C]-0.0586632[/C][C]0.0207465[/C][/ROW]
[ROW][C]10[/C][C]1.73[/C][C]1.76995[/C][C]1.84042[/C][C]-0.0704688[/C][C]-0.0399479[/C][/ROW]
[ROW][C]11[/C][C]1.77[/C][C]1.83752[/C][C]1.8525[/C][C]-0.0149826[/C][C]-0.0675174[/C][/ROW]
[ROW][C]12[/C][C]1.95[/C][C]1.90161[/C][C]1.86292[/C][C]0.0386979[/C][C]0.0483854[/C][/ROW]
[ROW][C]13[/C][C]2.08[/C][C]1.93884[/C][C]1.8825[/C][C]0.0563368[/C][C]0.141163[/C][/ROW]
[ROW][C]14[/C][C]2.26[/C][C]2.18377[/C][C]1.91042[/C][C]0.273351[/C][C]0.0762326[/C][/ROW]
[ROW][C]15[/C][C]2.02[/C][C]2.02328[/C][C]1.92958[/C][C]0.0936979[/C][C]-0.00328125[/C][/ROW]
[ROW][C]16[/C][C]1.9[/C][C]1.95335[/C][C]1.9475[/C][C]0.00585069[/C][C]-0.0533507[/C][/ROW]
[ROW][C]17[/C][C]1.97[/C][C]2.08995[/C][C]1.96708[/C][C]0.122865[/C][C]-0.119948[/C][/ROW]
[ROW][C]18[/C][C]1.76[/C][C]1.88043[/C][C]1.97625[/C][C]-0.095816[/C][C]-0.120434[/C][/ROW]
[ROW][C]19[/C][C]1.93[/C][C]1.78606[/C][C]1.97125[/C][C]-0.185191[/C][C]0.143941[/C][/ROW]
[ROW][C]20[/C][C]1.91[/C][C]1.80016[/C][C]1.96583[/C][C]-0.165677[/C][C]0.109844[/C][/ROW]
[ROW][C]21[/C][C]1.96[/C][C]1.90925[/C][C]1.96792[/C][C]-0.0586632[/C][C]0.0507465[/C][/ROW]
[ROW][C]22[/C][C]1.99[/C][C]1.90453[/C][C]1.975[/C][C]-0.0704688[/C][C]0.0854688[/C][/ROW]
[ROW][C]23[/C][C]1.98[/C][C]1.96918[/C][C]1.98417[/C][C]-0.0149826[/C][C]0.010816[/C][/ROW]
[ROW][C]24[/C][C]1.96[/C][C]2.03203[/C][C]1.99333[/C][C]0.0386979[/C][C]-0.0720312[/C][/ROW]
[ROW][C]25[/C][C]1.95[/C][C]2.04717[/C][C]1.99083[/C][C]0.0563368[/C][C]-0.0971701[/C][/ROW]
[ROW][C]26[/C][C]2.26[/C][C]2.25127[/C][C]1.97792[/C][C]0.273351[/C][C]0.00873264[/C][/ROW]
[ROW][C]27[/C][C]2.07[/C][C]2.06245[/C][C]1.96875[/C][C]0.0936979[/C][C]0.00755208[/C][/ROW]
[ROW][C]28[/C][C]2.02[/C][C]1.96877[/C][C]1.96292[/C][C]0.00585069[/C][C]0.0512326[/C][/ROW]
[ROW][C]29[/C][C]2.07[/C][C]2.08578[/C][C]1.96292[/C][C]0.122865[/C][C]-0.0157812[/C][/ROW]
[ROW][C]30[/C][C]1.88[/C][C]1.87627[/C][C]1.97208[/C][C]-0.095816[/C][C]0.00373264[/C][/ROW]
[ROW][C]31[/C][C]1.75[/C][C]1.79773[/C][C]1.98292[/C][C]-0.185191[/C][C]-0.0477257[/C][/ROW]
[ROW][C]32[/C][C]1.78[/C][C]1.81766[/C][C]1.98333[/C][C]-0.165677[/C][C]-0.0376562[/C][/ROW]
[ROW][C]33[/C][C]1.87[/C][C]1.91925[/C][C]1.97792[/C][C]-0.0586632[/C][C]-0.0492535[/C][/ROW]
[ROW][C]34[/C][C]1.94[/C][C]1.90411[/C][C]1.97458[/C][C]-0.0704688[/C][C]0.0358854[/C][/ROW]
[ROW][C]35[/C][C]2.03[/C][C]1.95918[/C][C]1.97417[/C][C]-0.0149826[/C][C]0.070816[/C][/ROW]
[ROW][C]36[/C][C]2.13[/C][C]2.0137[/C][C]1.975[/C][C]0.0386979[/C][C]0.116302[/C][/ROW]
[ROW][C]37[/C][C]2.04[/C][C]2.03342[/C][C]1.97708[/C][C]0.0563368[/C][C]0.00657986[/C][/ROW]
[ROW][C]38[/C][C]2.18[/C][C]2.2521[/C][C]1.97875[/C][C]0.273351[/C][C]-0.0721007[/C][/ROW]
[ROW][C]39[/C][C]2.02[/C][C]2.0712[/C][C]1.9775[/C][C]0.0936979[/C][C]-0.0511979[/C][/ROW]
[ROW][C]40[/C][C]1.99[/C][C]1.98085[/C][C]1.975[/C][C]0.00585069[/C][C]0.00914931[/C][/ROW]
[ROW][C]41[/C][C]2.09[/C][C]2.0962[/C][C]1.97333[/C][C]0.122865[/C][C]-0.00619792[/C][/ROW]
[ROW][C]42[/C][C]1.88[/C][C]1.87293[/C][C]1.96875[/C][C]-0.095816[/C][C]0.00706597[/C][/ROW]
[ROW][C]43[/C][C]1.8[/C][C]1.78106[/C][C]1.96625[/C][C]-0.185191[/C][C]0.018941[/C][/ROW]
[ROW][C]44[/C][C]1.77[/C][C]1.80766[/C][C]1.97333[/C][C]-0.165677[/C][C]-0.0376562[/C][/ROW]
[ROW][C]45[/C][C]1.85[/C][C]1.9255[/C][C]1.98417[/C][C]-0.0586632[/C][C]-0.0755035[/C][/ROW]
[ROW][C]46[/C][C]1.9[/C][C]1.92078[/C][C]1.99125[/C][C]-0.0704688[/C][C]-0.0207812[/C][/ROW]
[ROW][C]47[/C][C]2.03[/C][C]1.98668[/C][C]2.00167[/C][C]-0.0149826[/C][C]0.043316[/C][/ROW]
[ROW][C]48[/C][C]2.02[/C][C]2.0537[/C][C]2.015[/C][C]0.0386979[/C][C]-0.0336979[/C][/ROW]
[ROW][C]49[/C][C]2.09[/C][C]2.073[/C][C]2.01667[/C][C]0.0563368[/C][C]0.0169965[/C][/ROW]
[ROW][C]50[/C][C]2.3[/C][C]2.2896[/C][C]2.01625[/C][C]0.273351[/C][C]0.0103993[/C][/ROW]
[ROW][C]51[/C][C]2.16[/C][C]2.1212[/C][C]2.0275[/C][C]0.0936979[/C][C]0.0388021[/C][/ROW]
[ROW][C]52[/C][C]2.02[/C][C]2.04835[/C][C]2.0425[/C][C]0.00585069[/C][C]-0.0283507[/C][/ROW]
[ROW][C]53[/C][C]2.31[/C][C]2.17286[/C][C]2.05[/C][C]0.122865[/C][C]0.137135[/C][/ROW]
[ROW][C]54[/C][C]1.98[/C][C]1.96043[/C][C]2.05625[/C][C]-0.095816[/C][C]0.019566[/C][/ROW]
[ROW][C]55[/C][C]1.74[/C][C]1.87773[/C][C]2.06292[/C][C]-0.185191[/C][C]-0.137726[/C][/ROW]
[ROW][C]56[/C][C]1.82[/C][C]1.90474[/C][C]2.07042[/C][C]-0.165677[/C][C]-0.0847396[/C][/ROW]
[ROW][C]57[/C][C]2.07[/C][C]2.02134[/C][C]2.08[/C][C]-0.0586632[/C][C]0.0486632[/C][/ROW]
[ROW][C]58[/C][C]2.04[/C][C]2.01745[/C][C]2.08792[/C][C]-0.0704688[/C][C]0.0225521[/C][/ROW]
[ROW][C]59[/C][C]2.07[/C][C]2.07168[/C][C]2.08667[/C][C]-0.0149826[/C][C]-0.00168403[/C][/ROW]
[ROW][C]60[/C][C]2.13[/C][C]2.12286[/C][C]2.08417[/C][C]0.0386979[/C][C]0.00713542[/C][/ROW]
[ROW][C]61[/C][C]2.14[/C][C]2.1555[/C][C]2.09917[/C][C]0.0563368[/C][C]-0.0155035[/C][/ROW]
[ROW][C]62[/C][C]2.43[/C][C]2.3946[/C][C]2.12125[/C][C]0.273351[/C][C]0.0353993[/C][/ROW]
[ROW][C]63[/C][C]2.26[/C][C]2.22495[/C][C]2.13125[/C][C]0.0936979[/C][C]0.0350521[/C][/ROW]
[ROW][C]64[/C][C]2.11[/C][C]2.13502[/C][C]2.12917[/C][C]0.00585069[/C][C]-0.0250174[/C][/ROW]
[ROW][C]65[/C][C]2.19[/C][C]2.24953[/C][C]2.12667[/C][C]0.122865[/C][C]-0.0595313[/C][/ROW]
[ROW][C]66[/C][C]2.04[/C][C]2.03043[/C][C]2.12625[/C][C]-0.095816[/C][C]0.00956597[/C][/ROW]
[ROW][C]67[/C][C]2.04[/C][C]1.94106[/C][C]2.12625[/C][C]-0.185191[/C][C]0.098941[/C][/ROW]
[ROW][C]68[/C][C]2.05[/C][C]1.95766[/C][C]2.12333[/C][C]-0.165677[/C][C]0.0923438[/C][/ROW]
[ROW][C]69[/C][C]2.08[/C][C]2.05842[/C][C]2.11708[/C][C]-0.0586632[/C][C]0.0215799[/C][/ROW]
[ROW][C]70[/C][C]1.98[/C][C]2.0462[/C][C]2.11667[/C][C]-0.0704688[/C][C]-0.0661979[/C][/ROW]
[ROW][C]71[/C][C]2.07[/C][C]2.10877[/C][C]2.12375[/C][C]-0.0149826[/C][C]-0.0387674[/C][/ROW]
[ROW][C]72[/C][C]2.12[/C][C]2.16911[/C][C]2.13042[/C][C]0.0386979[/C][C]-0.0491146[/C][/ROW]
[ROW][C]73[/C][C]2.15[/C][C]2.18509[/C][C]2.12875[/C][C]0.0563368[/C][C]-0.0350868[/C][/ROW]
[ROW][C]74[/C][C]2.35[/C][C]2.39168[/C][C]2.11833[/C][C]0.273351[/C][C]-0.041684[/C][/ROW]
[ROW][C]75[/C][C]2.19[/C][C]2.19995[/C][C]2.10625[/C][C]0.0936979[/C][C]-0.00994792[/C][/ROW]
[ROW][C]76[/C][C]2.17[/C][C]2.10668[/C][C]2.10083[/C][C]0.00585069[/C][C]0.063316[/C][/ROW]
[ROW][C]77[/C][C]2.3[/C][C]2.2187[/C][C]2.09583[/C][C]0.122865[/C][C]0.0813021[/C][/ROW]
[ROW][C]78[/C][C]2.09[/C][C]1.99252[/C][C]2.08833[/C][C]-0.095816[/C][C]0.0974826[/C][/ROW]
[ROW][C]79[/C][C]1.95[/C][C]NA[/C][C]NA[/C][C]-0.185191[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]1.89[/C][C]NA[/C][C]NA[/C][C]-0.165677[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]1.95[/C][C]NA[/C][C]NA[/C][C]-0.0586632[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]1.98[/C][C]NA[/C][C]NA[/C][C]-0.0704688[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]1.95[/C][C]NA[/C][C]NA[/C][C]-0.0149826[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]2.06[/C][C]NA[/C][C]NA[/C][C]0.0386979[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=231613&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=231613&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	1.93	NA	NA	0.0563368	NA
2	2.02	NA	NA	0.273351	NA
3	1.85	NA	NA	0.0936979	NA
4	1.77	NA	NA	0.00585069	NA
5	1.81	NA	NA	0.122865	NA
6	1.67	NA	NA	-0.095816	NA
7	1.55	1.60939	1.79458	-0.185191	-0.0593924
8	1.62	1.64516	1.81083	-0.165677	-0.0251562
9	1.79	1.76925	1.82792	-0.0586632	0.0207465
10	1.73	1.76995	1.84042	-0.0704688	-0.0399479
11	1.77	1.83752	1.8525	-0.0149826	-0.0675174
12	1.95	1.90161	1.86292	0.0386979	0.0483854
13	2.08	1.93884	1.8825	0.0563368	0.141163
14	2.26	2.18377	1.91042	0.273351	0.0762326
15	2.02	2.02328	1.92958	0.0936979	-0.00328125
16	1.9	1.95335	1.9475	0.00585069	-0.0533507
17	1.97	2.08995	1.96708	0.122865	-0.119948
18	1.76	1.88043	1.97625	-0.095816	-0.120434
19	1.93	1.78606	1.97125	-0.185191	0.143941
20	1.91	1.80016	1.96583	-0.165677	0.109844
21	1.96	1.90925	1.96792	-0.0586632	0.0507465
22	1.99	1.90453	1.975	-0.0704688	0.0854688
23	1.98	1.96918	1.98417	-0.0149826	0.010816
24	1.96	2.03203	1.99333	0.0386979	-0.0720312
25	1.95	2.04717	1.99083	0.0563368	-0.0971701
26	2.26	2.25127	1.97792	0.273351	0.00873264
27	2.07	2.06245	1.96875	0.0936979	0.00755208
28	2.02	1.96877	1.96292	0.00585069	0.0512326
29	2.07	2.08578	1.96292	0.122865	-0.0157812
30	1.88	1.87627	1.97208	-0.095816	0.00373264
31	1.75	1.79773	1.98292	-0.185191	-0.0477257
32	1.78	1.81766	1.98333	-0.165677	-0.0376562
33	1.87	1.91925	1.97792	-0.0586632	-0.0492535
34	1.94	1.90411	1.97458	-0.0704688	0.0358854
35	2.03	1.95918	1.97417	-0.0149826	0.070816
36	2.13	2.0137	1.975	0.0386979	0.116302
37	2.04	2.03342	1.97708	0.0563368	0.00657986
38	2.18	2.2521	1.97875	0.273351	-0.0721007
39	2.02	2.0712	1.9775	0.0936979	-0.0511979
40	1.99	1.98085	1.975	0.00585069	0.00914931
41	2.09	2.0962	1.97333	0.122865	-0.00619792
42	1.88	1.87293	1.96875	-0.095816	0.00706597
43	1.8	1.78106	1.96625	-0.185191	0.018941
44	1.77	1.80766	1.97333	-0.165677	-0.0376562
45	1.85	1.9255	1.98417	-0.0586632	-0.0755035
46	1.9	1.92078	1.99125	-0.0704688	-0.0207812
47	2.03	1.98668	2.00167	-0.0149826	0.043316
48	2.02	2.0537	2.015	0.0386979	-0.0336979
49	2.09	2.073	2.01667	0.0563368	0.0169965
50	2.3	2.2896	2.01625	0.273351	0.0103993
51	2.16	2.1212	2.0275	0.0936979	0.0388021
52	2.02	2.04835	2.0425	0.00585069	-0.0283507
53	2.31	2.17286	2.05	0.122865	0.137135
54	1.98	1.96043	2.05625	-0.095816	0.019566
55	1.74	1.87773	2.06292	-0.185191	-0.137726
56	1.82	1.90474	2.07042	-0.165677	-0.0847396
57	2.07	2.02134	2.08	-0.0586632	0.0486632
58	2.04	2.01745	2.08792	-0.0704688	0.0225521
59	2.07	2.07168	2.08667	-0.0149826	-0.00168403
60	2.13	2.12286	2.08417	0.0386979	0.00713542
61	2.14	2.1555	2.09917	0.0563368	-0.0155035
62	2.43	2.3946	2.12125	0.273351	0.0353993
63	2.26	2.22495	2.13125	0.0936979	0.0350521
64	2.11	2.13502	2.12917	0.00585069	-0.0250174
65	2.19	2.24953	2.12667	0.122865	-0.0595313
66	2.04	2.03043	2.12625	-0.095816	0.00956597
67	2.04	1.94106	2.12625	-0.185191	0.098941
68	2.05	1.95766	2.12333	-0.165677	0.0923438
69	2.08	2.05842	2.11708	-0.0586632	0.0215799
70	1.98	2.0462	2.11667	-0.0704688	-0.0661979
71	2.07	2.10877	2.12375	-0.0149826	-0.0387674
72	2.12	2.16911	2.13042	0.0386979	-0.0491146
73	2.15	2.18509	2.12875	0.0563368	-0.0350868
74	2.35	2.39168	2.11833	0.273351	-0.041684
75	2.19	2.19995	2.10625	0.0936979	-0.00994792
76	2.17	2.10668	2.10083	0.00585069	0.063316
77	2.3	2.2187	2.09583	0.122865	0.0813021
78	2.09	1.99252	2.08833	-0.095816	0.0974826
79	1.95	NA	NA	-0.185191	NA
80	1.89	NA	NA	-0.165677	NA
81	1.95	NA	NA	-0.0586632	NA
82	1.98	NA	NA	-0.0704688	NA
83	1.95	NA	NA	-0.0149826	NA
84	2.06	NA	NA	0.0386979	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