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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 30 Apr 2017 16:37:44 +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/2017/Apr/30/t1493567879sc4hv5d2nyll9en.htm/, Retrieved Sun, 12 May 2024 16:09:32 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Sun, 12 May 2024 16:09:32 +0200

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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	4 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 & 4 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]4 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=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	4 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	78.46	NA	NA	-0.449361	NA
2	78.59	NA	NA	0.0623889	NA
3	81.37	NA	NA	1.29722	NA
4	83.61	NA	NA	0.339306	NA
5	84.65	NA	NA	-0.188694	NA
6	84.56	NA	NA	-0.305861	NA
7	83.85	83.8788	84.2946	-0.415778	-0.0288056
8	84.08	85.0468	85.3583	-0.311528	-0.966806
9	85.41	87.0159	86.525	0.490889	-1.60589
10	85.75	87.7159	87.6942	0.0217222	-1.96589
11	86.38	88.5688	88.8325	-0.263694	-2.18881
12	88.87	89.7471	90.0237	-0.276611	-0.877139
13	90.37	90.8302	91.2796	-0.449361	-0.460222
14	92.21	92.5924	92.53	0.0623889	-0.382389
15	95.75	95.0835	93.7863	1.29722	0.666528
16	97.29	95.3706	95.0312	0.339306	1.91944
17	98.29	96.0863	96.275	-0.188694	2.20369
18	99.51	97.1246	97.4304	-0.305861	2.38544
19	99.04	98.0642	98.48	-0.415778	0.975778
20	98.9	99.1985	99.51	-0.311528	-0.298472
21	100.74	100.925	100.435	0.490889	-0.185472
22	100.3	101.256	101.234	0.0217222	-0.955889
23	101.68	101.582	101.846	-0.263694	0.0978611
24	101.3	101.898	102.175	-0.276611	-0.597972
25	103.13	101.936	102.385	-0.449361	1.19394
26	104.17	102.798	102.735	0.0623889	1.37219
27	105.98	104.461	103.164	1.29722	1.51903
28	106.25	103.886	103.546	0.339306	2.36444
29	104.01	103.602	103.791	-0.188694	0.407861
30	101.68	103.602	103.908	-0.305861	-1.92247
31	101.93	103.53	103.946	-0.415778	-1.60047
32	104.41	103.521	103.833	-0.311528	0.889028
33	105.51	104.036	103.545	0.490889	1.47369
34	104.71	103.163	103.141	0.0217222	1.54703
35	103.14	102.471	102.735	-0.263694	0.669111
36	102.66	102.166	102.443	-0.276611	0.493694
37	102.68	101.811	102.26	-0.449361	0.868944
38	101.89	102.025	101.962	0.0623889	-0.134889
39	101.37	102.814	101.517	1.29722	-1.44389
40	101.16	101.359	101.02	0.339306	-0.199306
41	99.34	100.355	100.543	-0.188694	-1.01464
42	99.35	99.8591	100.165	-0.305861	-0.509139
43	99.88	99.3896	99.8054	-0.415778	0.490361
44	99.31	99.1547	99.4663	-0.311528	0.155278
45	99.91	99.6805	99.1896	0.490889	0.229528
46	98.39	98.7601	98.7383	0.0217222	-0.370056
47	98.02	97.8984	98.1621	-0.263694	0.121611
48	98.7	97.3813	97.6579	-0.276611	1.31869
49	98.01	96.6802	97.1296	-0.449361	1.32978
50	98.42	96.6191	96.5567	0.0623889	1.80094
51	98.2	97.2364	95.9392	1.29722	0.963611
52	93.5	95.7122	95.3729	0.339306	-2.21222
53	93.17	94.6692	94.8579	-0.188694	-1.49922
54	93.42	93.8891	94.195	-0.305861	-0.469139
55	93.13	92.8992	93.315	-0.415778	0.230778
56	92.31	92.0214	92.3329	-0.311528	0.288611
57	92.09	91.9342	91.4433	0.490889	0.155778
58	92.62	90.8076	90.7858	0.0217222	1.81244
59	91.43	90.0621	90.3258	-0.263694	1.36786
60	89.38	89.6496	89.9262	-0.276611	-0.269639
61	86.21	89.0748	89.5242	-0.449361	-2.86481
62	86.65	89.2382	89.1758	0.0623889	-2.58822
63	88.62	90.2576	88.9604	1.29722	-1.63764
64	87.3	89.1047	88.7654	0.339306	-1.80472
65	88.33	88.3601	88.5488	-0.188694	-0.0300556
66	88.67	88.0871	88.3929	-0.305861	0.582944
67	88.23	NA	NA	-0.415778	NA
68	88.85	NA	NA	-0.311528	NA
69	90.38	NA	NA	0.490889	NA
70	89.65	NA	NA	0.0217222	NA
71	89.2	NA	NA	-0.263694	NA
72	87.87	NA	NA	-0.276611	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 78.46 & NA & NA & -0.449361 & NA \tabularnewline
2 & 78.59 & NA & NA & 0.0623889 & NA \tabularnewline
3 & 81.37 & NA & NA & 1.29722 & NA \tabularnewline
4 & 83.61 & NA & NA & 0.339306 & NA \tabularnewline
5 & 84.65 & NA & NA & -0.188694 & NA \tabularnewline
6 & 84.56 & NA & NA & -0.305861 & NA \tabularnewline
7 & 83.85 & 83.8788 & 84.2946 & -0.415778 & -0.0288056 \tabularnewline
8 & 84.08 & 85.0468 & 85.3583 & -0.311528 & -0.966806 \tabularnewline
9 & 85.41 & 87.0159 & 86.525 & 0.490889 & -1.60589 \tabularnewline
10 & 85.75 & 87.7159 & 87.6942 & 0.0217222 & -1.96589 \tabularnewline
11 & 86.38 & 88.5688 & 88.8325 & -0.263694 & -2.18881 \tabularnewline
12 & 88.87 & 89.7471 & 90.0237 & -0.276611 & -0.877139 \tabularnewline
13 & 90.37 & 90.8302 & 91.2796 & -0.449361 & -0.460222 \tabularnewline
14 & 92.21 & 92.5924 & 92.53 & 0.0623889 & -0.382389 \tabularnewline
15 & 95.75 & 95.0835 & 93.7863 & 1.29722 & 0.666528 \tabularnewline
16 & 97.29 & 95.3706 & 95.0312 & 0.339306 & 1.91944 \tabularnewline
17 & 98.29 & 96.0863 & 96.275 & -0.188694 & 2.20369 \tabularnewline
18 & 99.51 & 97.1246 & 97.4304 & -0.305861 & 2.38544 \tabularnewline
19 & 99.04 & 98.0642 & 98.48 & -0.415778 & 0.975778 \tabularnewline
20 & 98.9 & 99.1985 & 99.51 & -0.311528 & -0.298472 \tabularnewline
21 & 100.74 & 100.925 & 100.435 & 0.490889 & -0.185472 \tabularnewline
22 & 100.3 & 101.256 & 101.234 & 0.0217222 & -0.955889 \tabularnewline
23 & 101.68 & 101.582 & 101.846 & -0.263694 & 0.0978611 \tabularnewline
24 & 101.3 & 101.898 & 102.175 & -0.276611 & -0.597972 \tabularnewline
25 & 103.13 & 101.936 & 102.385 & -0.449361 & 1.19394 \tabularnewline
26 & 104.17 & 102.798 & 102.735 & 0.0623889 & 1.37219 \tabularnewline
27 & 105.98 & 104.461 & 103.164 & 1.29722 & 1.51903 \tabularnewline
28 & 106.25 & 103.886 & 103.546 & 0.339306 & 2.36444 \tabularnewline
29 & 104.01 & 103.602 & 103.791 & -0.188694 & 0.407861 \tabularnewline
30 & 101.68 & 103.602 & 103.908 & -0.305861 & -1.92247 \tabularnewline
31 & 101.93 & 103.53 & 103.946 & -0.415778 & -1.60047 \tabularnewline
32 & 104.41 & 103.521 & 103.833 & -0.311528 & 0.889028 \tabularnewline
33 & 105.51 & 104.036 & 103.545 & 0.490889 & 1.47369 \tabularnewline
34 & 104.71 & 103.163 & 103.141 & 0.0217222 & 1.54703 \tabularnewline
35 & 103.14 & 102.471 & 102.735 & -0.263694 & 0.669111 \tabularnewline
36 & 102.66 & 102.166 & 102.443 & -0.276611 & 0.493694 \tabularnewline
37 & 102.68 & 101.811 & 102.26 & -0.449361 & 0.868944 \tabularnewline
38 & 101.89 & 102.025 & 101.962 & 0.0623889 & -0.134889 \tabularnewline
39 & 101.37 & 102.814 & 101.517 & 1.29722 & -1.44389 \tabularnewline
40 & 101.16 & 101.359 & 101.02 & 0.339306 & -0.199306 \tabularnewline
41 & 99.34 & 100.355 & 100.543 & -0.188694 & -1.01464 \tabularnewline
42 & 99.35 & 99.8591 & 100.165 & -0.305861 & -0.509139 \tabularnewline
43 & 99.88 & 99.3896 & 99.8054 & -0.415778 & 0.490361 \tabularnewline
44 & 99.31 & 99.1547 & 99.4663 & -0.311528 & 0.155278 \tabularnewline
45 & 99.91 & 99.6805 & 99.1896 & 0.490889 & 0.229528 \tabularnewline
46 & 98.39 & 98.7601 & 98.7383 & 0.0217222 & -0.370056 \tabularnewline
47 & 98.02 & 97.8984 & 98.1621 & -0.263694 & 0.121611 \tabularnewline
48 & 98.7 & 97.3813 & 97.6579 & -0.276611 & 1.31869 \tabularnewline
49 & 98.01 & 96.6802 & 97.1296 & -0.449361 & 1.32978 \tabularnewline
50 & 98.42 & 96.6191 & 96.5567 & 0.0623889 & 1.80094 \tabularnewline
51 & 98.2 & 97.2364 & 95.9392 & 1.29722 & 0.963611 \tabularnewline
52 & 93.5 & 95.7122 & 95.3729 & 0.339306 & -2.21222 \tabularnewline
53 & 93.17 & 94.6692 & 94.8579 & -0.188694 & -1.49922 \tabularnewline
54 & 93.42 & 93.8891 & 94.195 & -0.305861 & -0.469139 \tabularnewline
55 & 93.13 & 92.8992 & 93.315 & -0.415778 & 0.230778 \tabularnewline
56 & 92.31 & 92.0214 & 92.3329 & -0.311528 & 0.288611 \tabularnewline
57 & 92.09 & 91.9342 & 91.4433 & 0.490889 & 0.155778 \tabularnewline
58 & 92.62 & 90.8076 & 90.7858 & 0.0217222 & 1.81244 \tabularnewline
59 & 91.43 & 90.0621 & 90.3258 & -0.263694 & 1.36786 \tabularnewline
60 & 89.38 & 89.6496 & 89.9262 & -0.276611 & -0.269639 \tabularnewline
61 & 86.21 & 89.0748 & 89.5242 & -0.449361 & -2.86481 \tabularnewline
62 & 86.65 & 89.2382 & 89.1758 & 0.0623889 & -2.58822 \tabularnewline
63 & 88.62 & 90.2576 & 88.9604 & 1.29722 & -1.63764 \tabularnewline
64 & 87.3 & 89.1047 & 88.7654 & 0.339306 & -1.80472 \tabularnewline
65 & 88.33 & 88.3601 & 88.5488 & -0.188694 & -0.0300556 \tabularnewline
66 & 88.67 & 88.0871 & 88.3929 & -0.305861 & 0.582944 \tabularnewline
67 & 88.23 & NA & NA & -0.415778 & NA \tabularnewline
68 & 88.85 & NA & NA & -0.311528 & NA \tabularnewline
69 & 90.38 & NA & NA & 0.490889 & NA \tabularnewline
70 & 89.65 & NA & NA & 0.0217222 & NA \tabularnewline
71 & 89.2 & NA & NA & -0.263694 & NA \tabularnewline
72 & 87.87 & NA & NA & -0.276611 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]78.46[/C][C]NA[/C][C]NA[/C][C]-0.449361[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]78.59[/C][C]NA[/C][C]NA[/C][C]0.0623889[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]81.37[/C][C]NA[/C][C]NA[/C][C]1.29722[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]83.61[/C][C]NA[/C][C]NA[/C][C]0.339306[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]84.65[/C][C]NA[/C][C]NA[/C][C]-0.188694[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]84.56[/C][C]NA[/C][C]NA[/C][C]-0.305861[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]83.85[/C][C]83.8788[/C][C]84.2946[/C][C]-0.415778[/C][C]-0.0288056[/C][/ROW]
[ROW][C]8[/C][C]84.08[/C][C]85.0468[/C][C]85.3583[/C][C]-0.311528[/C][C]-0.966806[/C][/ROW]
[ROW][C]9[/C][C]85.41[/C][C]87.0159[/C][C]86.525[/C][C]0.490889[/C][C]-1.60589[/C][/ROW]
[ROW][C]10[/C][C]85.75[/C][C]87.7159[/C][C]87.6942[/C][C]0.0217222[/C][C]-1.96589[/C][/ROW]
[ROW][C]11[/C][C]86.38[/C][C]88.5688[/C][C]88.8325[/C][C]-0.263694[/C][C]-2.18881[/C][/ROW]
[ROW][C]12[/C][C]88.87[/C][C]89.7471[/C][C]90.0237[/C][C]-0.276611[/C][C]-0.877139[/C][/ROW]
[ROW][C]13[/C][C]90.37[/C][C]90.8302[/C][C]91.2796[/C][C]-0.449361[/C][C]-0.460222[/C][/ROW]
[ROW][C]14[/C][C]92.21[/C][C]92.5924[/C][C]92.53[/C][C]0.0623889[/C][C]-0.382389[/C][/ROW]
[ROW][C]15[/C][C]95.75[/C][C]95.0835[/C][C]93.7863[/C][C]1.29722[/C][C]0.666528[/C][/ROW]
[ROW][C]16[/C][C]97.29[/C][C]95.3706[/C][C]95.0312[/C][C]0.339306[/C][C]1.91944[/C][/ROW]
[ROW][C]17[/C][C]98.29[/C][C]96.0863[/C][C]96.275[/C][C]-0.188694[/C][C]2.20369[/C][/ROW]
[ROW][C]18[/C][C]99.51[/C][C]97.1246[/C][C]97.4304[/C][C]-0.305861[/C][C]2.38544[/C][/ROW]
[ROW][C]19[/C][C]99.04[/C][C]98.0642[/C][C]98.48[/C][C]-0.415778[/C][C]0.975778[/C][/ROW]
[ROW][C]20[/C][C]98.9[/C][C]99.1985[/C][C]99.51[/C][C]-0.311528[/C][C]-0.298472[/C][/ROW]
[ROW][C]21[/C][C]100.74[/C][C]100.925[/C][C]100.435[/C][C]0.490889[/C][C]-0.185472[/C][/ROW]
[ROW][C]22[/C][C]100.3[/C][C]101.256[/C][C]101.234[/C][C]0.0217222[/C][C]-0.955889[/C][/ROW]
[ROW][C]23[/C][C]101.68[/C][C]101.582[/C][C]101.846[/C][C]-0.263694[/C][C]0.0978611[/C][/ROW]
[ROW][C]24[/C][C]101.3[/C][C]101.898[/C][C]102.175[/C][C]-0.276611[/C][C]-0.597972[/C][/ROW]
[ROW][C]25[/C][C]103.13[/C][C]101.936[/C][C]102.385[/C][C]-0.449361[/C][C]1.19394[/C][/ROW]
[ROW][C]26[/C][C]104.17[/C][C]102.798[/C][C]102.735[/C][C]0.0623889[/C][C]1.37219[/C][/ROW]
[ROW][C]27[/C][C]105.98[/C][C]104.461[/C][C]103.164[/C][C]1.29722[/C][C]1.51903[/C][/ROW]
[ROW][C]28[/C][C]106.25[/C][C]103.886[/C][C]103.546[/C][C]0.339306[/C][C]2.36444[/C][/ROW]
[ROW][C]29[/C][C]104.01[/C][C]103.602[/C][C]103.791[/C][C]-0.188694[/C][C]0.407861[/C][/ROW]
[ROW][C]30[/C][C]101.68[/C][C]103.602[/C][C]103.908[/C][C]-0.305861[/C][C]-1.92247[/C][/ROW]
[ROW][C]31[/C][C]101.93[/C][C]103.53[/C][C]103.946[/C][C]-0.415778[/C][C]-1.60047[/C][/ROW]
[ROW][C]32[/C][C]104.41[/C][C]103.521[/C][C]103.833[/C][C]-0.311528[/C][C]0.889028[/C][/ROW]
[ROW][C]33[/C][C]105.51[/C][C]104.036[/C][C]103.545[/C][C]0.490889[/C][C]1.47369[/C][/ROW]
[ROW][C]34[/C][C]104.71[/C][C]103.163[/C][C]103.141[/C][C]0.0217222[/C][C]1.54703[/C][/ROW]
[ROW][C]35[/C][C]103.14[/C][C]102.471[/C][C]102.735[/C][C]-0.263694[/C][C]0.669111[/C][/ROW]
[ROW][C]36[/C][C]102.66[/C][C]102.166[/C][C]102.443[/C][C]-0.276611[/C][C]0.493694[/C][/ROW]
[ROW][C]37[/C][C]102.68[/C][C]101.811[/C][C]102.26[/C][C]-0.449361[/C][C]0.868944[/C][/ROW]
[ROW][C]38[/C][C]101.89[/C][C]102.025[/C][C]101.962[/C][C]0.0623889[/C][C]-0.134889[/C][/ROW]
[ROW][C]39[/C][C]101.37[/C][C]102.814[/C][C]101.517[/C][C]1.29722[/C][C]-1.44389[/C][/ROW]
[ROW][C]40[/C][C]101.16[/C][C]101.359[/C][C]101.02[/C][C]0.339306[/C][C]-0.199306[/C][/ROW]
[ROW][C]41[/C][C]99.34[/C][C]100.355[/C][C]100.543[/C][C]-0.188694[/C][C]-1.01464[/C][/ROW]
[ROW][C]42[/C][C]99.35[/C][C]99.8591[/C][C]100.165[/C][C]-0.305861[/C][C]-0.509139[/C][/ROW]
[ROW][C]43[/C][C]99.88[/C][C]99.3896[/C][C]99.8054[/C][C]-0.415778[/C][C]0.490361[/C][/ROW]
[ROW][C]44[/C][C]99.31[/C][C]99.1547[/C][C]99.4663[/C][C]-0.311528[/C][C]0.155278[/C][/ROW]
[ROW][C]45[/C][C]99.91[/C][C]99.6805[/C][C]99.1896[/C][C]0.490889[/C][C]0.229528[/C][/ROW]
[ROW][C]46[/C][C]98.39[/C][C]98.7601[/C][C]98.7383[/C][C]0.0217222[/C][C]-0.370056[/C][/ROW]
[ROW][C]47[/C][C]98.02[/C][C]97.8984[/C][C]98.1621[/C][C]-0.263694[/C][C]0.121611[/C][/ROW]
[ROW][C]48[/C][C]98.7[/C][C]97.3813[/C][C]97.6579[/C][C]-0.276611[/C][C]1.31869[/C][/ROW]
[ROW][C]49[/C][C]98.01[/C][C]96.6802[/C][C]97.1296[/C][C]-0.449361[/C][C]1.32978[/C][/ROW]
[ROW][C]50[/C][C]98.42[/C][C]96.6191[/C][C]96.5567[/C][C]0.0623889[/C][C]1.80094[/C][/ROW]
[ROW][C]51[/C][C]98.2[/C][C]97.2364[/C][C]95.9392[/C][C]1.29722[/C][C]0.963611[/C][/ROW]
[ROW][C]52[/C][C]93.5[/C][C]95.7122[/C][C]95.3729[/C][C]0.339306[/C][C]-2.21222[/C][/ROW]
[ROW][C]53[/C][C]93.17[/C][C]94.6692[/C][C]94.8579[/C][C]-0.188694[/C][C]-1.49922[/C][/ROW]
[ROW][C]54[/C][C]93.42[/C][C]93.8891[/C][C]94.195[/C][C]-0.305861[/C][C]-0.469139[/C][/ROW]
[ROW][C]55[/C][C]93.13[/C][C]92.8992[/C][C]93.315[/C][C]-0.415778[/C][C]0.230778[/C][/ROW]
[ROW][C]56[/C][C]92.31[/C][C]92.0214[/C][C]92.3329[/C][C]-0.311528[/C][C]0.288611[/C][/ROW]
[ROW][C]57[/C][C]92.09[/C][C]91.9342[/C][C]91.4433[/C][C]0.490889[/C][C]0.155778[/C][/ROW]
[ROW][C]58[/C][C]92.62[/C][C]90.8076[/C][C]90.7858[/C][C]0.0217222[/C][C]1.81244[/C][/ROW]
[ROW][C]59[/C][C]91.43[/C][C]90.0621[/C][C]90.3258[/C][C]-0.263694[/C][C]1.36786[/C][/ROW]
[ROW][C]60[/C][C]89.38[/C][C]89.6496[/C][C]89.9262[/C][C]-0.276611[/C][C]-0.269639[/C][/ROW]
[ROW][C]61[/C][C]86.21[/C][C]89.0748[/C][C]89.5242[/C][C]-0.449361[/C][C]-2.86481[/C][/ROW]
[ROW][C]62[/C][C]86.65[/C][C]89.2382[/C][C]89.1758[/C][C]0.0623889[/C][C]-2.58822[/C][/ROW]
[ROW][C]63[/C][C]88.62[/C][C]90.2576[/C][C]88.9604[/C][C]1.29722[/C][C]-1.63764[/C][/ROW]
[ROW][C]64[/C][C]87.3[/C][C]89.1047[/C][C]88.7654[/C][C]0.339306[/C][C]-1.80472[/C][/ROW]
[ROW][C]65[/C][C]88.33[/C][C]88.3601[/C][C]88.5488[/C][C]-0.188694[/C][C]-0.0300556[/C][/ROW]
[ROW][C]66[/C][C]88.67[/C][C]88.0871[/C][C]88.3929[/C][C]-0.305861[/C][C]0.582944[/C][/ROW]
[ROW][C]67[/C][C]88.23[/C][C]NA[/C][C]NA[/C][C]-0.415778[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]88.85[/C][C]NA[/C][C]NA[/C][C]-0.311528[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]90.38[/C][C]NA[/C][C]NA[/C][C]0.490889[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]89.65[/C][C]NA[/C][C]NA[/C][C]0.0217222[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]89.2[/C][C]NA[/C][C]NA[/C][C]-0.263694[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]87.87[/C][C]NA[/C][C]NA[/C][C]-0.276611[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	78.46	NA	NA	-0.449361	NA
2	78.59	NA	NA	0.0623889	NA
3	81.37	NA	NA	1.29722	NA
4	83.61	NA	NA	0.339306	NA
5	84.65	NA	NA	-0.188694	NA
6	84.56	NA	NA	-0.305861	NA
7	83.85	83.8788	84.2946	-0.415778	-0.0288056
8	84.08	85.0468	85.3583	-0.311528	-0.966806
9	85.41	87.0159	86.525	0.490889	-1.60589
10	85.75	87.7159	87.6942	0.0217222	-1.96589
11	86.38	88.5688	88.8325	-0.263694	-2.18881
12	88.87	89.7471	90.0237	-0.276611	-0.877139
13	90.37	90.8302	91.2796	-0.449361	-0.460222
14	92.21	92.5924	92.53	0.0623889	-0.382389
15	95.75	95.0835	93.7863	1.29722	0.666528
16	97.29	95.3706	95.0312	0.339306	1.91944
17	98.29	96.0863	96.275	-0.188694	2.20369
18	99.51	97.1246	97.4304	-0.305861	2.38544
19	99.04	98.0642	98.48	-0.415778	0.975778
20	98.9	99.1985	99.51	-0.311528	-0.298472
21	100.74	100.925	100.435	0.490889	-0.185472
22	100.3	101.256	101.234	0.0217222	-0.955889
23	101.68	101.582	101.846	-0.263694	0.0978611
24	101.3	101.898	102.175	-0.276611	-0.597972
25	103.13	101.936	102.385	-0.449361	1.19394
26	104.17	102.798	102.735	0.0623889	1.37219
27	105.98	104.461	103.164	1.29722	1.51903
28	106.25	103.886	103.546	0.339306	2.36444
29	104.01	103.602	103.791	-0.188694	0.407861
30	101.68	103.602	103.908	-0.305861	-1.92247
31	101.93	103.53	103.946	-0.415778	-1.60047
32	104.41	103.521	103.833	-0.311528	0.889028
33	105.51	104.036	103.545	0.490889	1.47369
34	104.71	103.163	103.141	0.0217222	1.54703
35	103.14	102.471	102.735	-0.263694	0.669111
36	102.66	102.166	102.443	-0.276611	0.493694
37	102.68	101.811	102.26	-0.449361	0.868944
38	101.89	102.025	101.962	0.0623889	-0.134889
39	101.37	102.814	101.517	1.29722	-1.44389
40	101.16	101.359	101.02	0.339306	-0.199306
41	99.34	100.355	100.543	-0.188694	-1.01464
42	99.35	99.8591	100.165	-0.305861	-0.509139
43	99.88	99.3896	99.8054	-0.415778	0.490361
44	99.31	99.1547	99.4663	-0.311528	0.155278
45	99.91	99.6805	99.1896	0.490889	0.229528
46	98.39	98.7601	98.7383	0.0217222	-0.370056
47	98.02	97.8984	98.1621	-0.263694	0.121611
48	98.7	97.3813	97.6579	-0.276611	1.31869
49	98.01	96.6802	97.1296	-0.449361	1.32978
50	98.42	96.6191	96.5567	0.0623889	1.80094
51	98.2	97.2364	95.9392	1.29722	0.963611
52	93.5	95.7122	95.3729	0.339306	-2.21222
53	93.17	94.6692	94.8579	-0.188694	-1.49922
54	93.42	93.8891	94.195	-0.305861	-0.469139
55	93.13	92.8992	93.315	-0.415778	0.230778
56	92.31	92.0214	92.3329	-0.311528	0.288611
57	92.09	91.9342	91.4433	0.490889	0.155778
58	92.62	90.8076	90.7858	0.0217222	1.81244
59	91.43	90.0621	90.3258	-0.263694	1.36786
60	89.38	89.6496	89.9262	-0.276611	-0.269639
61	86.21	89.0748	89.5242	-0.449361	-2.86481
62	86.65	89.2382	89.1758	0.0623889	-2.58822
63	88.62	90.2576	88.9604	1.29722	-1.63764
64	87.3	89.1047	88.7654	0.339306	-1.80472
65	88.33	88.3601	88.5488	-0.188694	-0.0300556
66	88.67	88.0871	88.3929	-0.305861	0.582944
67	88.23	NA	NA	-0.415778	NA
68	88.85	NA	NA	-0.311528	NA
69	90.38	NA	NA	0.490889	NA
70	89.65	NA	NA	0.0217222	NA
71	89.2	NA	NA	-0.263694	NA
72	87.87	NA	NA	-0.276611	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