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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Thu, 02 Apr 2015 22:34:44 +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/2015/Apr/02/t1428010565eal09hk0pwpwn3n.htm/, Retrieved Thu, 09 May 2024 12:23:01 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278677, Retrieved Thu, 09 May 2024 12:23:01 +0000

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-       [Classical Decomposition] [] [2015-04-02 21:34:44] [567f06ca3de45fa0ce67a0a89b883c29] [Current]
- R PD    [Classical Decomposition] [] [2015-05-27 06:42:55] [693750cd301bd4fecbcaa8326eb70b61] 

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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	1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278677&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]1 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=278677&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278677&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	1 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	94.67	NA	NA	1.00384	NA
2	94.6	NA	NA	1.01407	NA
3	93.9	NA	NA	1.00884	NA
4	93.41	NA	NA	1.00888	NA
5	93.37	NA	NA	1.00502	NA
6	93.35	NA	NA	1.00297	NA
7	93.08	91.9494	93.1317	0.987306	1.0123
8	93.05	92.3045	92.9675	0.992868	1.00808
9	92.61	92.0733	92.8287	0.991862	1.00583
10	92.37	92.248	92.7346	0.994753	1.00132
11	92.24	92.269	92.6658	0.995717	0.999686
12	91.95	92.0325	92.5988	0.993884	0.999104
13	92.63	92.7888	92.4342	1.00384	0.998288
14	92.7	93.4708	92.1738	1.01407	0.991754
15	92.47	92.7499	91.9375	1.00884	0.996983
16	92.58	92.5585	91.7442	1.00888	1.00023
17	92.55	92.0582	91.5983	1.00502	1.00534
18	92.56	91.7435	91.4721	1.00297	1.0089
19	89.92	90.1501	91.3092	0.987306	0.997448
20	89.96	90.6075	91.2583	0.992868	0.992854
21	90.03	90.6223	91.3658	0.991862	0.993464
22	90.31	91.0062	91.4863	0.994753	0.992349
23	90.8	91.2314	91.6238	0.995717	0.995272
24	90.36	91.2075	91.7688	0.993884	0.990708
25	90.31	92.2706	91.9179	1.00384	0.978752
26	93.8	93.3757	92.08	1.01407	1.00454
27	93.95	93.1034	92.2879	1.00884	1.00909
28	93.99	93.3698	92.5483	1.00888	1.00664
29	94.44	93.2613	92.7954	1.00502	1.01264
30	94.15	93.3625	93.0862	1.00297	1.00844
31	91.91	92.3057	93.4925	0.987306	0.995713
32	91.86	93.1716	93.8408	0.992868	0.985923
33	93.12	93.2656	94.0308	0.991862	0.998439
34	93.47	93.6676	94.1617	0.994753	0.99789
35	93.57	93.8455	94.2492	0.995717	0.997064
36	94.57	93.7399	94.3167	0.993884	1.00886
37	95.85	94.8132	94.4508	1.00384	1.01093
38	96.62	96.0267	94.6942	1.01407	1.00618
39	95.69	95.7629	94.9242	1.00884	0.999238
40	95.39	95.9096	95.0658	1.00888	0.994582
41	95.14	95.6805	95.2025	1.00502	0.994351
42	95.07	95.5757	95.2929	1.00297	0.994709
43	94.21	94.1034	95.3133	0.987306	1.00113
44	95.4	94.6307	95.3104	0.992868	1.00813
45	95.1	94.5389	95.3146	0.991862	1.00593
46	94.89	94.8427	95.3429	0.994753	1.0005
47	95.43	94.9732	95.3817	0.995717	1.00481
48	94.88	94.8526	95.4362	0.993884	1.00029
49	96.03	95.8091	95.4429	1.00384	1.00231
50	96.37	96.7581	95.4154	1.01407	0.995989
51	96.04	96.2215	95.3788	1.00884	0.998113
52	95.72	96.2253	95.3788	1.00888	0.994748
53	95.74	95.8803	95.4012	1.00502	0.998537
54	95.78	95.6634	95.3804	1.00297	1.00122
55	93.66	94.1659	95.3767	0.987306	0.994627
56	95.29	94.6998	95.38	0.992868	1.00623
57	94.33	94.5617	95.3375	0.991862	0.99755
58	95.66	94.7921	95.2921	0.994753	1.00916
59	95.2	94.7844	95.1921	0.995717	1.00438
60	94.61	94.3967	94.9775	0.993884	1.00226
61	96.21	95.1692	94.8054	1.00384	1.01094
62	96.27	96.006	94.6738	1.01407	1.00275
63	95.12	95.3308	94.4958	1.00884	0.997789
64	95.55	95.0735	94.2371	1.00888	1.00501
65	93.51	94.4213	93.9496	1.00502	0.990349
66	92.86	93.9922	93.7142	1.00297	0.987954
67	92.45	NA	NA	0.987306	NA
68	93.34	NA	NA	0.992868	NA
69	92.01	NA	NA	0.991862	NA
70	91.77	NA	NA	0.994753	NA
71	92.19	NA	NA	0.995717	NA
72	91.97	NA	NA	0.993884	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 94.67 & NA & NA & 1.00384 & NA \tabularnewline
2 & 94.6 & NA & NA & 1.01407 & NA \tabularnewline
3 & 93.9 & NA & NA & 1.00884 & NA \tabularnewline
4 & 93.41 & NA & NA & 1.00888 & NA \tabularnewline
5 & 93.37 & NA & NA & 1.00502 & NA \tabularnewline
6 & 93.35 & NA & NA & 1.00297 & NA \tabularnewline
7 & 93.08 & 91.9494 & 93.1317 & 0.987306 & 1.0123 \tabularnewline
8 & 93.05 & 92.3045 & 92.9675 & 0.992868 & 1.00808 \tabularnewline
9 & 92.61 & 92.0733 & 92.8287 & 0.991862 & 1.00583 \tabularnewline
10 & 92.37 & 92.248 & 92.7346 & 0.994753 & 1.00132 \tabularnewline
11 & 92.24 & 92.269 & 92.6658 & 0.995717 & 0.999686 \tabularnewline
12 & 91.95 & 92.0325 & 92.5988 & 0.993884 & 0.999104 \tabularnewline
13 & 92.63 & 92.7888 & 92.4342 & 1.00384 & 0.998288 \tabularnewline
14 & 92.7 & 93.4708 & 92.1738 & 1.01407 & 0.991754 \tabularnewline
15 & 92.47 & 92.7499 & 91.9375 & 1.00884 & 0.996983 \tabularnewline
16 & 92.58 & 92.5585 & 91.7442 & 1.00888 & 1.00023 \tabularnewline
17 & 92.55 & 92.0582 & 91.5983 & 1.00502 & 1.00534 \tabularnewline
18 & 92.56 & 91.7435 & 91.4721 & 1.00297 & 1.0089 \tabularnewline
19 & 89.92 & 90.1501 & 91.3092 & 0.987306 & 0.997448 \tabularnewline
20 & 89.96 & 90.6075 & 91.2583 & 0.992868 & 0.992854 \tabularnewline
21 & 90.03 & 90.6223 & 91.3658 & 0.991862 & 0.993464 \tabularnewline
22 & 90.31 & 91.0062 & 91.4863 & 0.994753 & 0.992349 \tabularnewline
23 & 90.8 & 91.2314 & 91.6238 & 0.995717 & 0.995272 \tabularnewline
24 & 90.36 & 91.2075 & 91.7688 & 0.993884 & 0.990708 \tabularnewline
25 & 90.31 & 92.2706 & 91.9179 & 1.00384 & 0.978752 \tabularnewline
26 & 93.8 & 93.3757 & 92.08 & 1.01407 & 1.00454 \tabularnewline
27 & 93.95 & 93.1034 & 92.2879 & 1.00884 & 1.00909 \tabularnewline
28 & 93.99 & 93.3698 & 92.5483 & 1.00888 & 1.00664 \tabularnewline
29 & 94.44 & 93.2613 & 92.7954 & 1.00502 & 1.01264 \tabularnewline
30 & 94.15 & 93.3625 & 93.0862 & 1.00297 & 1.00844 \tabularnewline
31 & 91.91 & 92.3057 & 93.4925 & 0.987306 & 0.995713 \tabularnewline
32 & 91.86 & 93.1716 & 93.8408 & 0.992868 & 0.985923 \tabularnewline
33 & 93.12 & 93.2656 & 94.0308 & 0.991862 & 0.998439 \tabularnewline
34 & 93.47 & 93.6676 & 94.1617 & 0.994753 & 0.99789 \tabularnewline
35 & 93.57 & 93.8455 & 94.2492 & 0.995717 & 0.997064 \tabularnewline
36 & 94.57 & 93.7399 & 94.3167 & 0.993884 & 1.00886 \tabularnewline
37 & 95.85 & 94.8132 & 94.4508 & 1.00384 & 1.01093 \tabularnewline
38 & 96.62 & 96.0267 & 94.6942 & 1.01407 & 1.00618 \tabularnewline
39 & 95.69 & 95.7629 & 94.9242 & 1.00884 & 0.999238 \tabularnewline
40 & 95.39 & 95.9096 & 95.0658 & 1.00888 & 0.994582 \tabularnewline
41 & 95.14 & 95.6805 & 95.2025 & 1.00502 & 0.994351 \tabularnewline
42 & 95.07 & 95.5757 & 95.2929 & 1.00297 & 0.994709 \tabularnewline
43 & 94.21 & 94.1034 & 95.3133 & 0.987306 & 1.00113 \tabularnewline
44 & 95.4 & 94.6307 & 95.3104 & 0.992868 & 1.00813 \tabularnewline
45 & 95.1 & 94.5389 & 95.3146 & 0.991862 & 1.00593 \tabularnewline
46 & 94.89 & 94.8427 & 95.3429 & 0.994753 & 1.0005 \tabularnewline
47 & 95.43 & 94.9732 & 95.3817 & 0.995717 & 1.00481 \tabularnewline
48 & 94.88 & 94.8526 & 95.4362 & 0.993884 & 1.00029 \tabularnewline
49 & 96.03 & 95.8091 & 95.4429 & 1.00384 & 1.00231 \tabularnewline
50 & 96.37 & 96.7581 & 95.4154 & 1.01407 & 0.995989 \tabularnewline
51 & 96.04 & 96.2215 & 95.3788 & 1.00884 & 0.998113 \tabularnewline
52 & 95.72 & 96.2253 & 95.3788 & 1.00888 & 0.994748 \tabularnewline
53 & 95.74 & 95.8803 & 95.4012 & 1.00502 & 0.998537 \tabularnewline
54 & 95.78 & 95.6634 & 95.3804 & 1.00297 & 1.00122 \tabularnewline
55 & 93.66 & 94.1659 & 95.3767 & 0.987306 & 0.994627 \tabularnewline
56 & 95.29 & 94.6998 & 95.38 & 0.992868 & 1.00623 \tabularnewline
57 & 94.33 & 94.5617 & 95.3375 & 0.991862 & 0.99755 \tabularnewline
58 & 95.66 & 94.7921 & 95.2921 & 0.994753 & 1.00916 \tabularnewline
59 & 95.2 & 94.7844 & 95.1921 & 0.995717 & 1.00438 \tabularnewline
60 & 94.61 & 94.3967 & 94.9775 & 0.993884 & 1.00226 \tabularnewline
61 & 96.21 & 95.1692 & 94.8054 & 1.00384 & 1.01094 \tabularnewline
62 & 96.27 & 96.006 & 94.6738 & 1.01407 & 1.00275 \tabularnewline
63 & 95.12 & 95.3308 & 94.4958 & 1.00884 & 0.997789 \tabularnewline
64 & 95.55 & 95.0735 & 94.2371 & 1.00888 & 1.00501 \tabularnewline
65 & 93.51 & 94.4213 & 93.9496 & 1.00502 & 0.990349 \tabularnewline
66 & 92.86 & 93.9922 & 93.7142 & 1.00297 & 0.987954 \tabularnewline
67 & 92.45 & NA & NA & 0.987306 & NA \tabularnewline
68 & 93.34 & NA & NA & 0.992868 & NA \tabularnewline
69 & 92.01 & NA & NA & 0.991862 & NA \tabularnewline
70 & 91.77 & NA & NA & 0.994753 & NA \tabularnewline
71 & 92.19 & NA & NA & 0.995717 & NA \tabularnewline
72 & 91.97 & NA & NA & 0.993884 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278677&T=1

[TABLE]
[ROW][C]Classical Decomposition by Moving Averages[/C][/ROW]
[ROW][C]t[/C][C]Observations[/C][C]Fit[/C][C]Trend[/C][C]Seasonal[/C][C]Random[/C][/ROW]
[ROW][C]1[/C][C]94.67[/C][C]NA[/C][C]NA[/C][C]1.00384[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]94.6[/C][C]NA[/C][C]NA[/C][C]1.01407[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]93.9[/C][C]NA[/C][C]NA[/C][C]1.00884[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]93.41[/C][C]NA[/C][C]NA[/C][C]1.00888[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]93.37[/C][C]NA[/C][C]NA[/C][C]1.00502[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]93.35[/C][C]NA[/C][C]NA[/C][C]1.00297[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]93.08[/C][C]91.9494[/C][C]93.1317[/C][C]0.987306[/C][C]1.0123[/C][/ROW]
[ROW][C]8[/C][C]93.05[/C][C]92.3045[/C][C]92.9675[/C][C]0.992868[/C][C]1.00808[/C][/ROW]
[ROW][C]9[/C][C]92.61[/C][C]92.0733[/C][C]92.8287[/C][C]0.991862[/C][C]1.00583[/C][/ROW]
[ROW][C]10[/C][C]92.37[/C][C]92.248[/C][C]92.7346[/C][C]0.994753[/C][C]1.00132[/C][/ROW]
[ROW][C]11[/C][C]92.24[/C][C]92.269[/C][C]92.6658[/C][C]0.995717[/C][C]0.999686[/C][/ROW]
[ROW][C]12[/C][C]91.95[/C][C]92.0325[/C][C]92.5988[/C][C]0.993884[/C][C]0.999104[/C][/ROW]
[ROW][C]13[/C][C]92.63[/C][C]92.7888[/C][C]92.4342[/C][C]1.00384[/C][C]0.998288[/C][/ROW]
[ROW][C]14[/C][C]92.7[/C][C]93.4708[/C][C]92.1738[/C][C]1.01407[/C][C]0.991754[/C][/ROW]
[ROW][C]15[/C][C]92.47[/C][C]92.7499[/C][C]91.9375[/C][C]1.00884[/C][C]0.996983[/C][/ROW]
[ROW][C]16[/C][C]92.58[/C][C]92.5585[/C][C]91.7442[/C][C]1.00888[/C][C]1.00023[/C][/ROW]
[ROW][C]17[/C][C]92.55[/C][C]92.0582[/C][C]91.5983[/C][C]1.00502[/C][C]1.00534[/C][/ROW]
[ROW][C]18[/C][C]92.56[/C][C]91.7435[/C][C]91.4721[/C][C]1.00297[/C][C]1.0089[/C][/ROW]
[ROW][C]19[/C][C]89.92[/C][C]90.1501[/C][C]91.3092[/C][C]0.987306[/C][C]0.997448[/C][/ROW]
[ROW][C]20[/C][C]89.96[/C][C]90.6075[/C][C]91.2583[/C][C]0.992868[/C][C]0.992854[/C][/ROW]
[ROW][C]21[/C][C]90.03[/C][C]90.6223[/C][C]91.3658[/C][C]0.991862[/C][C]0.993464[/C][/ROW]
[ROW][C]22[/C][C]90.31[/C][C]91.0062[/C][C]91.4863[/C][C]0.994753[/C][C]0.992349[/C][/ROW]
[ROW][C]23[/C][C]90.8[/C][C]91.2314[/C][C]91.6238[/C][C]0.995717[/C][C]0.995272[/C][/ROW]
[ROW][C]24[/C][C]90.36[/C][C]91.2075[/C][C]91.7688[/C][C]0.993884[/C][C]0.990708[/C][/ROW]
[ROW][C]25[/C][C]90.31[/C][C]92.2706[/C][C]91.9179[/C][C]1.00384[/C][C]0.978752[/C][/ROW]
[ROW][C]26[/C][C]93.8[/C][C]93.3757[/C][C]92.08[/C][C]1.01407[/C][C]1.00454[/C][/ROW]
[ROW][C]27[/C][C]93.95[/C][C]93.1034[/C][C]92.2879[/C][C]1.00884[/C][C]1.00909[/C][/ROW]
[ROW][C]28[/C][C]93.99[/C][C]93.3698[/C][C]92.5483[/C][C]1.00888[/C][C]1.00664[/C][/ROW]
[ROW][C]29[/C][C]94.44[/C][C]93.2613[/C][C]92.7954[/C][C]1.00502[/C][C]1.01264[/C][/ROW]
[ROW][C]30[/C][C]94.15[/C][C]93.3625[/C][C]93.0862[/C][C]1.00297[/C][C]1.00844[/C][/ROW]
[ROW][C]31[/C][C]91.91[/C][C]92.3057[/C][C]93.4925[/C][C]0.987306[/C][C]0.995713[/C][/ROW]
[ROW][C]32[/C][C]91.86[/C][C]93.1716[/C][C]93.8408[/C][C]0.992868[/C][C]0.985923[/C][/ROW]
[ROW][C]33[/C][C]93.12[/C][C]93.2656[/C][C]94.0308[/C][C]0.991862[/C][C]0.998439[/C][/ROW]
[ROW][C]34[/C][C]93.47[/C][C]93.6676[/C][C]94.1617[/C][C]0.994753[/C][C]0.99789[/C][/ROW]
[ROW][C]35[/C][C]93.57[/C][C]93.8455[/C][C]94.2492[/C][C]0.995717[/C][C]0.997064[/C][/ROW]
[ROW][C]36[/C][C]94.57[/C][C]93.7399[/C][C]94.3167[/C][C]0.993884[/C][C]1.00886[/C][/ROW]
[ROW][C]37[/C][C]95.85[/C][C]94.8132[/C][C]94.4508[/C][C]1.00384[/C][C]1.01093[/C][/ROW]
[ROW][C]38[/C][C]96.62[/C][C]96.0267[/C][C]94.6942[/C][C]1.01407[/C][C]1.00618[/C][/ROW]
[ROW][C]39[/C][C]95.69[/C][C]95.7629[/C][C]94.9242[/C][C]1.00884[/C][C]0.999238[/C][/ROW]
[ROW][C]40[/C][C]95.39[/C][C]95.9096[/C][C]95.0658[/C][C]1.00888[/C][C]0.994582[/C][/ROW]
[ROW][C]41[/C][C]95.14[/C][C]95.6805[/C][C]95.2025[/C][C]1.00502[/C][C]0.994351[/C][/ROW]
[ROW][C]42[/C][C]95.07[/C][C]95.5757[/C][C]95.2929[/C][C]1.00297[/C][C]0.994709[/C][/ROW]
[ROW][C]43[/C][C]94.21[/C][C]94.1034[/C][C]95.3133[/C][C]0.987306[/C][C]1.00113[/C][/ROW]
[ROW][C]44[/C][C]95.4[/C][C]94.6307[/C][C]95.3104[/C][C]0.992868[/C][C]1.00813[/C][/ROW]
[ROW][C]45[/C][C]95.1[/C][C]94.5389[/C][C]95.3146[/C][C]0.991862[/C][C]1.00593[/C][/ROW]
[ROW][C]46[/C][C]94.89[/C][C]94.8427[/C][C]95.3429[/C][C]0.994753[/C][C]1.0005[/C][/ROW]
[ROW][C]47[/C][C]95.43[/C][C]94.9732[/C][C]95.3817[/C][C]0.995717[/C][C]1.00481[/C][/ROW]
[ROW][C]48[/C][C]94.88[/C][C]94.8526[/C][C]95.4362[/C][C]0.993884[/C][C]1.00029[/C][/ROW]
[ROW][C]49[/C][C]96.03[/C][C]95.8091[/C][C]95.4429[/C][C]1.00384[/C][C]1.00231[/C][/ROW]
[ROW][C]50[/C][C]96.37[/C][C]96.7581[/C][C]95.4154[/C][C]1.01407[/C][C]0.995989[/C][/ROW]
[ROW][C]51[/C][C]96.04[/C][C]96.2215[/C][C]95.3788[/C][C]1.00884[/C][C]0.998113[/C][/ROW]
[ROW][C]52[/C][C]95.72[/C][C]96.2253[/C][C]95.3788[/C][C]1.00888[/C][C]0.994748[/C][/ROW]
[ROW][C]53[/C][C]95.74[/C][C]95.8803[/C][C]95.4012[/C][C]1.00502[/C][C]0.998537[/C][/ROW]
[ROW][C]54[/C][C]95.78[/C][C]95.6634[/C][C]95.3804[/C][C]1.00297[/C][C]1.00122[/C][/ROW]
[ROW][C]55[/C][C]93.66[/C][C]94.1659[/C][C]95.3767[/C][C]0.987306[/C][C]0.994627[/C][/ROW]
[ROW][C]56[/C][C]95.29[/C][C]94.6998[/C][C]95.38[/C][C]0.992868[/C][C]1.00623[/C][/ROW]
[ROW][C]57[/C][C]94.33[/C][C]94.5617[/C][C]95.3375[/C][C]0.991862[/C][C]0.99755[/C][/ROW]
[ROW][C]58[/C][C]95.66[/C][C]94.7921[/C][C]95.2921[/C][C]0.994753[/C][C]1.00916[/C][/ROW]
[ROW][C]59[/C][C]95.2[/C][C]94.7844[/C][C]95.1921[/C][C]0.995717[/C][C]1.00438[/C][/ROW]
[ROW][C]60[/C][C]94.61[/C][C]94.3967[/C][C]94.9775[/C][C]0.993884[/C][C]1.00226[/C][/ROW]
[ROW][C]61[/C][C]96.21[/C][C]95.1692[/C][C]94.8054[/C][C]1.00384[/C][C]1.01094[/C][/ROW]
[ROW][C]62[/C][C]96.27[/C][C]96.006[/C][C]94.6738[/C][C]1.01407[/C][C]1.00275[/C][/ROW]
[ROW][C]63[/C][C]95.12[/C][C]95.3308[/C][C]94.4958[/C][C]1.00884[/C][C]0.997789[/C][/ROW]
[ROW][C]64[/C][C]95.55[/C][C]95.0735[/C][C]94.2371[/C][C]1.00888[/C][C]1.00501[/C][/ROW]
[ROW][C]65[/C][C]93.51[/C][C]94.4213[/C][C]93.9496[/C][C]1.00502[/C][C]0.990349[/C][/ROW]
[ROW][C]66[/C][C]92.86[/C][C]93.9922[/C][C]93.7142[/C][C]1.00297[/C][C]0.987954[/C][/ROW]
[ROW][C]67[/C][C]92.45[/C][C]NA[/C][C]NA[/C][C]0.987306[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]93.34[/C][C]NA[/C][C]NA[/C][C]0.992868[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]92.01[/C][C]NA[/C][C]NA[/C][C]0.991862[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]91.77[/C][C]NA[/C][C]NA[/C][C]0.994753[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]92.19[/C][C]NA[/C][C]NA[/C][C]0.995717[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]91.97[/C][C]NA[/C][C]NA[/C][C]0.993884[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278677&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278677&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	94.67	NA	NA	1.00384	NA
2	94.6	NA	NA	1.01407	NA
3	93.9	NA	NA	1.00884	NA
4	93.41	NA	NA	1.00888	NA
5	93.37	NA	NA	1.00502	NA
6	93.35	NA	NA	1.00297	NA
7	93.08	91.9494	93.1317	0.987306	1.0123
8	93.05	92.3045	92.9675	0.992868	1.00808
9	92.61	92.0733	92.8287	0.991862	1.00583
10	92.37	92.248	92.7346	0.994753	1.00132
11	92.24	92.269	92.6658	0.995717	0.999686
12	91.95	92.0325	92.5988	0.993884	0.999104
13	92.63	92.7888	92.4342	1.00384	0.998288
14	92.7	93.4708	92.1738	1.01407	0.991754
15	92.47	92.7499	91.9375	1.00884	0.996983
16	92.58	92.5585	91.7442	1.00888	1.00023
17	92.55	92.0582	91.5983	1.00502	1.00534
18	92.56	91.7435	91.4721	1.00297	1.0089
19	89.92	90.1501	91.3092	0.987306	0.997448
20	89.96	90.6075	91.2583	0.992868	0.992854
21	90.03	90.6223	91.3658	0.991862	0.993464
22	90.31	91.0062	91.4863	0.994753	0.992349
23	90.8	91.2314	91.6238	0.995717	0.995272
24	90.36	91.2075	91.7688	0.993884	0.990708
25	90.31	92.2706	91.9179	1.00384	0.978752
26	93.8	93.3757	92.08	1.01407	1.00454
27	93.95	93.1034	92.2879	1.00884	1.00909
28	93.99	93.3698	92.5483	1.00888	1.00664
29	94.44	93.2613	92.7954	1.00502	1.01264
30	94.15	93.3625	93.0862	1.00297	1.00844
31	91.91	92.3057	93.4925	0.987306	0.995713
32	91.86	93.1716	93.8408	0.992868	0.985923
33	93.12	93.2656	94.0308	0.991862	0.998439
34	93.47	93.6676	94.1617	0.994753	0.99789
35	93.57	93.8455	94.2492	0.995717	0.997064
36	94.57	93.7399	94.3167	0.993884	1.00886
37	95.85	94.8132	94.4508	1.00384	1.01093
38	96.62	96.0267	94.6942	1.01407	1.00618
39	95.69	95.7629	94.9242	1.00884	0.999238
40	95.39	95.9096	95.0658	1.00888	0.994582
41	95.14	95.6805	95.2025	1.00502	0.994351
42	95.07	95.5757	95.2929	1.00297	0.994709
43	94.21	94.1034	95.3133	0.987306	1.00113
44	95.4	94.6307	95.3104	0.992868	1.00813
45	95.1	94.5389	95.3146	0.991862	1.00593
46	94.89	94.8427	95.3429	0.994753	1.0005
47	95.43	94.9732	95.3817	0.995717	1.00481
48	94.88	94.8526	95.4362	0.993884	1.00029
49	96.03	95.8091	95.4429	1.00384	1.00231
50	96.37	96.7581	95.4154	1.01407	0.995989
51	96.04	96.2215	95.3788	1.00884	0.998113
52	95.72	96.2253	95.3788	1.00888	0.994748
53	95.74	95.8803	95.4012	1.00502	0.998537
54	95.78	95.6634	95.3804	1.00297	1.00122
55	93.66	94.1659	95.3767	0.987306	0.994627
56	95.29	94.6998	95.38	0.992868	1.00623
57	94.33	94.5617	95.3375	0.991862	0.99755
58	95.66	94.7921	95.2921	0.994753	1.00916
59	95.2	94.7844	95.1921	0.995717	1.00438
60	94.61	94.3967	94.9775	0.993884	1.00226
61	96.21	95.1692	94.8054	1.00384	1.01094
62	96.27	96.006	94.6738	1.01407	1.00275
63	95.12	95.3308	94.4958	1.00884	0.997789
64	95.55	95.0735	94.2371	1.00888	1.00501
65	93.51	94.4213	93.9496	1.00502	0.990349
66	92.86	93.9922	93.7142	1.00297	0.987954
67	92.45	NA	NA	0.987306	NA
68	93.34	NA	NA	0.992868	NA
69	92.01	NA	NA	0.991862	NA
70	91.77	NA	NA	0.994753	NA
71	92.19	NA	NA	0.995717	NA
72	91.97	NA	NA	0.993884	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