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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 23 Nov 2015 21:22:56 +0000

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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/Nov/23/t1448313895mybus0kilw1nuxr.htm/, Retrieved Tue, 14 May 2024 00:45:37 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=283979, Retrieved Tue, 14 May 2024 00:45:37 +0000

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-       [Classical Decomposition] [] [2015-11-23 21:22:56] [4535d628e97572fda841f25b347e529f] [Current]

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283979&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283979&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283979&T=0

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

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

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	340.7	NA	NA	-0.0891447	NA
2	343.5	NA	NA	-0.0207237	NA
3	345.3	345.177	345.138	0.0398026	0.122697
4	346.9	347.233	347.162	0.0700658	-0.332566
5	349	349.023	349.112	-0.0891447	-0.0233553
6	351.4	351.067	351.088	-0.0207237	0.333224
7	353	353.527	353.487	0.0398026	-0.527303
8	355	356.608	356.538	0.0700658	-1.60757
9	360.1	359.798	359.888	-0.0891447	0.301645
10	364.7	363.304	363.325	-0.0207237	1.39572
11	366.5	366.34	366.3	0.0398026	0.160197
12	369	368.358	368.287	0.0700658	0.642434
13	369.9	369.961	370.05	-0.0891447	-0.0608553
14	370.8	372.204	372.225	-0.0207237	-1.40428
15	374.5	374.865	374.825	0.0398026	-0.364803
16	378.4	377.908	377.838	0.0700658	0.492434
17	381.3	380.973	381.062	-0.0891447	0.326645
18	383.5	384.342	384.362	-0.0207237	-0.841776
19	387.6	387.827	387.788	0.0398026	-0.227303
20	391.7	391.595	391.525	0.0700658	0.104934
21	395.4	395.373	395.462	-0.0891447	0.0266447
22	399.3	399.267	399.288	-0.0207237	0.0332237
23	403.3	403.077	403.038	0.0398026	0.222697
24	406.6	406.77	406.7	0.0700658	-0.170066
25	410.5	410.311	410.4	-0.0891447	0.189145
26	413.5	414.192	414.212	-0.0207237	-0.691776
27	418.7	417.677	417.638	0.0398026	1.0227
28	421.7	420.783	420.713	0.0700658	0.917434
29	422.8	423.273	423.362	-0.0891447	-0.473355
30	425.8	425.617	425.638	-0.0207237	0.183224
31	427.6	428.277	428.238	0.0398026	-0.677303
32	431	431.22	431.15	0.0700658	-0.220066
33	434.3	434.136	434.225	-0.0891447	0.164145
34	437.6	437.367	437.388	-0.0207237	0.233224
35	440.4	440.477	440.438	0.0398026	-0.0773026
36	443.5	443.07	443	0.0700658	0.429934
37	446.2	445.148	445.238	-0.0891447	1.05164
38	446.2	447.717	447.738	-0.0207237	-1.51678
39	449.7	450.64	450.6	0.0398026	-0.939803
40	454.2	454.058	453.988	0.0700658	0.142434
41	458.4	457.548	457.638	-0.0891447	0.851645
42	461.1	460.904	460.925	-0.0207237	0.195724
43	464	463.752	463.713	0.0398026	0.247697
44	466.2	466.408	466.338	0.0700658	-0.207566
45	468.7	468.948	469.038	-0.0891447	-0.248355
46	471.8	471.792	471.812	-0.0207237	0.00822368
47	474.9	474.677	474.638	0.0398026	0.222697
48	477.5	477.495	477.425	0.0700658	0.00493421
49	480	480.061	480.15	-0.0891447	-0.0608553
50	482.8	482.854	482.875	-0.0207237	-0.0542763
51	485.7	485.79	485.75	0.0398026	-0.0898026
52	488.5	488.858	488.788	0.0700658	-0.357566
53	492	491.836	491.925	-0.0891447	0.164145
54	495.1	495.217	495.238	-0.0207237	-0.116776
55	498.5	498.252	498.212	0.0398026	0.247697
56	502.2	501.408	501.338	0.0700658	0.792434
57	502.1	505.173	505.262	-0.0891447	-3.07336
58	510	509.579	509.6	-0.0207237	0.420724
59	515	514.802	514.763	0.0398026	0.197697
60	520.4	520.233	520.162	0.0700658	0.167434
61	525.2	525.023	525.113	-0.0891447	0.176645
62	530.1	529.792	529.812	-0.0207237	0.308224
63	534.5	534.515	534.475	0.0398026	-0.0148026
64	538.5	539.233	539.162	0.0700658	-0.732566
65	544.4	543.536	543.625	-0.0891447	0.864145
66	548.4	547.829	547.85	-0.0207237	0.570724
67	551.9	551.652	551.612	0.0398026	0.247697
68	554.9	555.008	554.938	0.0700658	-0.107566
69	558.1	558.023	558.112	-0.0891447	0.0766447
70	561.3	561.167	561.187	-0.0207237	0.133224
71	564.4	564.065	564.025	0.0398026	0.335197
72	567	566.62	566.55	0.0700658	0.379934
73	568.7	568.673	568.762	-0.0891447	0.0266447
74	570.9	570.704	570.725	-0.0207237	0.195724
75	572.5	572.765	572.725	0.0398026	-0.264803
76	574.6	575.095	575.025	0.0700658	-0.495066
77	577.1	577.536	577.625	-0.0891447	-0.435855
78	580.9	580.442	580.462	-0.0207237	0.458224
79	583.3	NA	NA	0.0398026	NA
80	586.5	NA	NA	0.0700658	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 340.7 & NA & NA & -0.0891447 & NA \tabularnewline
2 & 343.5 & NA & NA & -0.0207237 & NA \tabularnewline
3 & 345.3 & 345.177 & 345.138 & 0.0398026 & 0.122697 \tabularnewline
4 & 346.9 & 347.233 & 347.162 & 0.0700658 & -0.332566 \tabularnewline
5 & 349 & 349.023 & 349.112 & -0.0891447 & -0.0233553 \tabularnewline
6 & 351.4 & 351.067 & 351.088 & -0.0207237 & 0.333224 \tabularnewline
7 & 353 & 353.527 & 353.487 & 0.0398026 & -0.527303 \tabularnewline
8 & 355 & 356.608 & 356.538 & 0.0700658 & -1.60757 \tabularnewline
9 & 360.1 & 359.798 & 359.888 & -0.0891447 & 0.301645 \tabularnewline
10 & 364.7 & 363.304 & 363.325 & -0.0207237 & 1.39572 \tabularnewline
11 & 366.5 & 366.34 & 366.3 & 0.0398026 & 0.160197 \tabularnewline
12 & 369 & 368.358 & 368.287 & 0.0700658 & 0.642434 \tabularnewline
13 & 369.9 & 369.961 & 370.05 & -0.0891447 & -0.0608553 \tabularnewline
14 & 370.8 & 372.204 & 372.225 & -0.0207237 & -1.40428 \tabularnewline
15 & 374.5 & 374.865 & 374.825 & 0.0398026 & -0.364803 \tabularnewline
16 & 378.4 & 377.908 & 377.838 & 0.0700658 & 0.492434 \tabularnewline
17 & 381.3 & 380.973 & 381.062 & -0.0891447 & 0.326645 \tabularnewline
18 & 383.5 & 384.342 & 384.362 & -0.0207237 & -0.841776 \tabularnewline
19 & 387.6 & 387.827 & 387.788 & 0.0398026 & -0.227303 \tabularnewline
20 & 391.7 & 391.595 & 391.525 & 0.0700658 & 0.104934 \tabularnewline
21 & 395.4 & 395.373 & 395.462 & -0.0891447 & 0.0266447 \tabularnewline
22 & 399.3 & 399.267 & 399.288 & -0.0207237 & 0.0332237 \tabularnewline
23 & 403.3 & 403.077 & 403.038 & 0.0398026 & 0.222697 \tabularnewline
24 & 406.6 & 406.77 & 406.7 & 0.0700658 & -0.170066 \tabularnewline
25 & 410.5 & 410.311 & 410.4 & -0.0891447 & 0.189145 \tabularnewline
26 & 413.5 & 414.192 & 414.212 & -0.0207237 & -0.691776 \tabularnewline
27 & 418.7 & 417.677 & 417.638 & 0.0398026 & 1.0227 \tabularnewline
28 & 421.7 & 420.783 & 420.713 & 0.0700658 & 0.917434 \tabularnewline
29 & 422.8 & 423.273 & 423.362 & -0.0891447 & -0.473355 \tabularnewline
30 & 425.8 & 425.617 & 425.638 & -0.0207237 & 0.183224 \tabularnewline
31 & 427.6 & 428.277 & 428.238 & 0.0398026 & -0.677303 \tabularnewline
32 & 431 & 431.22 & 431.15 & 0.0700658 & -0.220066 \tabularnewline
33 & 434.3 & 434.136 & 434.225 & -0.0891447 & 0.164145 \tabularnewline
34 & 437.6 & 437.367 & 437.388 & -0.0207237 & 0.233224 \tabularnewline
35 & 440.4 & 440.477 & 440.438 & 0.0398026 & -0.0773026 \tabularnewline
36 & 443.5 & 443.07 & 443 & 0.0700658 & 0.429934 \tabularnewline
37 & 446.2 & 445.148 & 445.238 & -0.0891447 & 1.05164 \tabularnewline
38 & 446.2 & 447.717 & 447.738 & -0.0207237 & -1.51678 \tabularnewline
39 & 449.7 & 450.64 & 450.6 & 0.0398026 & -0.939803 \tabularnewline
40 & 454.2 & 454.058 & 453.988 & 0.0700658 & 0.142434 \tabularnewline
41 & 458.4 & 457.548 & 457.638 & -0.0891447 & 0.851645 \tabularnewline
42 & 461.1 & 460.904 & 460.925 & -0.0207237 & 0.195724 \tabularnewline
43 & 464 & 463.752 & 463.713 & 0.0398026 & 0.247697 \tabularnewline
44 & 466.2 & 466.408 & 466.338 & 0.0700658 & -0.207566 \tabularnewline
45 & 468.7 & 468.948 & 469.038 & -0.0891447 & -0.248355 \tabularnewline
46 & 471.8 & 471.792 & 471.812 & -0.0207237 & 0.00822368 \tabularnewline
47 & 474.9 & 474.677 & 474.638 & 0.0398026 & 0.222697 \tabularnewline
48 & 477.5 & 477.495 & 477.425 & 0.0700658 & 0.00493421 \tabularnewline
49 & 480 & 480.061 & 480.15 & -0.0891447 & -0.0608553 \tabularnewline
50 & 482.8 & 482.854 & 482.875 & -0.0207237 & -0.0542763 \tabularnewline
51 & 485.7 & 485.79 & 485.75 & 0.0398026 & -0.0898026 \tabularnewline
52 & 488.5 & 488.858 & 488.788 & 0.0700658 & -0.357566 \tabularnewline
53 & 492 & 491.836 & 491.925 & -0.0891447 & 0.164145 \tabularnewline
54 & 495.1 & 495.217 & 495.238 & -0.0207237 & -0.116776 \tabularnewline
55 & 498.5 & 498.252 & 498.212 & 0.0398026 & 0.247697 \tabularnewline
56 & 502.2 & 501.408 & 501.338 & 0.0700658 & 0.792434 \tabularnewline
57 & 502.1 & 505.173 & 505.262 & -0.0891447 & -3.07336 \tabularnewline
58 & 510 & 509.579 & 509.6 & -0.0207237 & 0.420724 \tabularnewline
59 & 515 & 514.802 & 514.763 & 0.0398026 & 0.197697 \tabularnewline
60 & 520.4 & 520.233 & 520.162 & 0.0700658 & 0.167434 \tabularnewline
61 & 525.2 & 525.023 & 525.113 & -0.0891447 & 0.176645 \tabularnewline
62 & 530.1 & 529.792 & 529.812 & -0.0207237 & 0.308224 \tabularnewline
63 & 534.5 & 534.515 & 534.475 & 0.0398026 & -0.0148026 \tabularnewline
64 & 538.5 & 539.233 & 539.162 & 0.0700658 & -0.732566 \tabularnewline
65 & 544.4 & 543.536 & 543.625 & -0.0891447 & 0.864145 \tabularnewline
66 & 548.4 & 547.829 & 547.85 & -0.0207237 & 0.570724 \tabularnewline
67 & 551.9 & 551.652 & 551.612 & 0.0398026 & 0.247697 \tabularnewline
68 & 554.9 & 555.008 & 554.938 & 0.0700658 & -0.107566 \tabularnewline
69 & 558.1 & 558.023 & 558.112 & -0.0891447 & 0.0766447 \tabularnewline
70 & 561.3 & 561.167 & 561.187 & -0.0207237 & 0.133224 \tabularnewline
71 & 564.4 & 564.065 & 564.025 & 0.0398026 & 0.335197 \tabularnewline
72 & 567 & 566.62 & 566.55 & 0.0700658 & 0.379934 \tabularnewline
73 & 568.7 & 568.673 & 568.762 & -0.0891447 & 0.0266447 \tabularnewline
74 & 570.9 & 570.704 & 570.725 & -0.0207237 & 0.195724 \tabularnewline
75 & 572.5 & 572.765 & 572.725 & 0.0398026 & -0.264803 \tabularnewline
76 & 574.6 & 575.095 & 575.025 & 0.0700658 & -0.495066 \tabularnewline
77 & 577.1 & 577.536 & 577.625 & -0.0891447 & -0.435855 \tabularnewline
78 & 580.9 & 580.442 & 580.462 & -0.0207237 & 0.458224 \tabularnewline
79 & 583.3 & NA & NA & 0.0398026 & NA \tabularnewline
80 & 586.5 & NA & NA & 0.0700658 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=283979&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]340.7[/C][C]NA[/C][C]NA[/C][C]-0.0891447[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]343.5[/C][C]NA[/C][C]NA[/C][C]-0.0207237[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]345.3[/C][C]345.177[/C][C]345.138[/C][C]0.0398026[/C][C]0.122697[/C][/ROW]
[ROW][C]4[/C][C]346.9[/C][C]347.233[/C][C]347.162[/C][C]0.0700658[/C][C]-0.332566[/C][/ROW]
[ROW][C]5[/C][C]349[/C][C]349.023[/C][C]349.112[/C][C]-0.0891447[/C][C]-0.0233553[/C][/ROW]
[ROW][C]6[/C][C]351.4[/C][C]351.067[/C][C]351.088[/C][C]-0.0207237[/C][C]0.333224[/C][/ROW]
[ROW][C]7[/C][C]353[/C][C]353.527[/C][C]353.487[/C][C]0.0398026[/C][C]-0.527303[/C][/ROW]
[ROW][C]8[/C][C]355[/C][C]356.608[/C][C]356.538[/C][C]0.0700658[/C][C]-1.60757[/C][/ROW]
[ROW][C]9[/C][C]360.1[/C][C]359.798[/C][C]359.888[/C][C]-0.0891447[/C][C]0.301645[/C][/ROW]
[ROW][C]10[/C][C]364.7[/C][C]363.304[/C][C]363.325[/C][C]-0.0207237[/C][C]1.39572[/C][/ROW]
[ROW][C]11[/C][C]366.5[/C][C]366.34[/C][C]366.3[/C][C]0.0398026[/C][C]0.160197[/C][/ROW]
[ROW][C]12[/C][C]369[/C][C]368.358[/C][C]368.287[/C][C]0.0700658[/C][C]0.642434[/C][/ROW]
[ROW][C]13[/C][C]369.9[/C][C]369.961[/C][C]370.05[/C][C]-0.0891447[/C][C]-0.0608553[/C][/ROW]
[ROW][C]14[/C][C]370.8[/C][C]372.204[/C][C]372.225[/C][C]-0.0207237[/C][C]-1.40428[/C][/ROW]
[ROW][C]15[/C][C]374.5[/C][C]374.865[/C][C]374.825[/C][C]0.0398026[/C][C]-0.364803[/C][/ROW]
[ROW][C]16[/C][C]378.4[/C][C]377.908[/C][C]377.838[/C][C]0.0700658[/C][C]0.492434[/C][/ROW]
[ROW][C]17[/C][C]381.3[/C][C]380.973[/C][C]381.062[/C][C]-0.0891447[/C][C]0.326645[/C][/ROW]
[ROW][C]18[/C][C]383.5[/C][C]384.342[/C][C]384.362[/C][C]-0.0207237[/C][C]-0.841776[/C][/ROW]
[ROW][C]19[/C][C]387.6[/C][C]387.827[/C][C]387.788[/C][C]0.0398026[/C][C]-0.227303[/C][/ROW]
[ROW][C]20[/C][C]391.7[/C][C]391.595[/C][C]391.525[/C][C]0.0700658[/C][C]0.104934[/C][/ROW]
[ROW][C]21[/C][C]395.4[/C][C]395.373[/C][C]395.462[/C][C]-0.0891447[/C][C]0.0266447[/C][/ROW]
[ROW][C]22[/C][C]399.3[/C][C]399.267[/C][C]399.288[/C][C]-0.0207237[/C][C]0.0332237[/C][/ROW]
[ROW][C]23[/C][C]403.3[/C][C]403.077[/C][C]403.038[/C][C]0.0398026[/C][C]0.222697[/C][/ROW]
[ROW][C]24[/C][C]406.6[/C][C]406.77[/C][C]406.7[/C][C]0.0700658[/C][C]-0.170066[/C][/ROW]
[ROW][C]25[/C][C]410.5[/C][C]410.311[/C][C]410.4[/C][C]-0.0891447[/C][C]0.189145[/C][/ROW]
[ROW][C]26[/C][C]413.5[/C][C]414.192[/C][C]414.212[/C][C]-0.0207237[/C][C]-0.691776[/C][/ROW]
[ROW][C]27[/C][C]418.7[/C][C]417.677[/C][C]417.638[/C][C]0.0398026[/C][C]1.0227[/C][/ROW]
[ROW][C]28[/C][C]421.7[/C][C]420.783[/C][C]420.713[/C][C]0.0700658[/C][C]0.917434[/C][/ROW]
[ROW][C]29[/C][C]422.8[/C][C]423.273[/C][C]423.362[/C][C]-0.0891447[/C][C]-0.473355[/C][/ROW]
[ROW][C]30[/C][C]425.8[/C][C]425.617[/C][C]425.638[/C][C]-0.0207237[/C][C]0.183224[/C][/ROW]
[ROW][C]31[/C][C]427.6[/C][C]428.277[/C][C]428.238[/C][C]0.0398026[/C][C]-0.677303[/C][/ROW]
[ROW][C]32[/C][C]431[/C][C]431.22[/C][C]431.15[/C][C]0.0700658[/C][C]-0.220066[/C][/ROW]
[ROW][C]33[/C][C]434.3[/C][C]434.136[/C][C]434.225[/C][C]-0.0891447[/C][C]0.164145[/C][/ROW]
[ROW][C]34[/C][C]437.6[/C][C]437.367[/C][C]437.388[/C][C]-0.0207237[/C][C]0.233224[/C][/ROW]
[ROW][C]35[/C][C]440.4[/C][C]440.477[/C][C]440.438[/C][C]0.0398026[/C][C]-0.0773026[/C][/ROW]
[ROW][C]36[/C][C]443.5[/C][C]443.07[/C][C]443[/C][C]0.0700658[/C][C]0.429934[/C][/ROW]
[ROW][C]37[/C][C]446.2[/C][C]445.148[/C][C]445.238[/C][C]-0.0891447[/C][C]1.05164[/C][/ROW]
[ROW][C]38[/C][C]446.2[/C][C]447.717[/C][C]447.738[/C][C]-0.0207237[/C][C]-1.51678[/C][/ROW]
[ROW][C]39[/C][C]449.7[/C][C]450.64[/C][C]450.6[/C][C]0.0398026[/C][C]-0.939803[/C][/ROW]
[ROW][C]40[/C][C]454.2[/C][C]454.058[/C][C]453.988[/C][C]0.0700658[/C][C]0.142434[/C][/ROW]
[ROW][C]41[/C][C]458.4[/C][C]457.548[/C][C]457.638[/C][C]-0.0891447[/C][C]0.851645[/C][/ROW]
[ROW][C]42[/C][C]461.1[/C][C]460.904[/C][C]460.925[/C][C]-0.0207237[/C][C]0.195724[/C][/ROW]
[ROW][C]43[/C][C]464[/C][C]463.752[/C][C]463.713[/C][C]0.0398026[/C][C]0.247697[/C][/ROW]
[ROW][C]44[/C][C]466.2[/C][C]466.408[/C][C]466.338[/C][C]0.0700658[/C][C]-0.207566[/C][/ROW]
[ROW][C]45[/C][C]468.7[/C][C]468.948[/C][C]469.038[/C][C]-0.0891447[/C][C]-0.248355[/C][/ROW]
[ROW][C]46[/C][C]471.8[/C][C]471.792[/C][C]471.812[/C][C]-0.0207237[/C][C]0.00822368[/C][/ROW]
[ROW][C]47[/C][C]474.9[/C][C]474.677[/C][C]474.638[/C][C]0.0398026[/C][C]0.222697[/C][/ROW]
[ROW][C]48[/C][C]477.5[/C][C]477.495[/C][C]477.425[/C][C]0.0700658[/C][C]0.00493421[/C][/ROW]
[ROW][C]49[/C][C]480[/C][C]480.061[/C][C]480.15[/C][C]-0.0891447[/C][C]-0.0608553[/C][/ROW]
[ROW][C]50[/C][C]482.8[/C][C]482.854[/C][C]482.875[/C][C]-0.0207237[/C][C]-0.0542763[/C][/ROW]
[ROW][C]51[/C][C]485.7[/C][C]485.79[/C][C]485.75[/C][C]0.0398026[/C][C]-0.0898026[/C][/ROW]
[ROW][C]52[/C][C]488.5[/C][C]488.858[/C][C]488.788[/C][C]0.0700658[/C][C]-0.357566[/C][/ROW]
[ROW][C]53[/C][C]492[/C][C]491.836[/C][C]491.925[/C][C]-0.0891447[/C][C]0.164145[/C][/ROW]
[ROW][C]54[/C][C]495.1[/C][C]495.217[/C][C]495.238[/C][C]-0.0207237[/C][C]-0.116776[/C][/ROW]
[ROW][C]55[/C][C]498.5[/C][C]498.252[/C][C]498.212[/C][C]0.0398026[/C][C]0.247697[/C][/ROW]
[ROW][C]56[/C][C]502.2[/C][C]501.408[/C][C]501.338[/C][C]0.0700658[/C][C]0.792434[/C][/ROW]
[ROW][C]57[/C][C]502.1[/C][C]505.173[/C][C]505.262[/C][C]-0.0891447[/C][C]-3.07336[/C][/ROW]
[ROW][C]58[/C][C]510[/C][C]509.579[/C][C]509.6[/C][C]-0.0207237[/C][C]0.420724[/C][/ROW]
[ROW][C]59[/C][C]515[/C][C]514.802[/C][C]514.763[/C][C]0.0398026[/C][C]0.197697[/C][/ROW]
[ROW][C]60[/C][C]520.4[/C][C]520.233[/C][C]520.162[/C][C]0.0700658[/C][C]0.167434[/C][/ROW]
[ROW][C]61[/C][C]525.2[/C][C]525.023[/C][C]525.113[/C][C]-0.0891447[/C][C]0.176645[/C][/ROW]
[ROW][C]62[/C][C]530.1[/C][C]529.792[/C][C]529.812[/C][C]-0.0207237[/C][C]0.308224[/C][/ROW]
[ROW][C]63[/C][C]534.5[/C][C]534.515[/C][C]534.475[/C][C]0.0398026[/C][C]-0.0148026[/C][/ROW]
[ROW][C]64[/C][C]538.5[/C][C]539.233[/C][C]539.162[/C][C]0.0700658[/C][C]-0.732566[/C][/ROW]
[ROW][C]65[/C][C]544.4[/C][C]543.536[/C][C]543.625[/C][C]-0.0891447[/C][C]0.864145[/C][/ROW]
[ROW][C]66[/C][C]548.4[/C][C]547.829[/C][C]547.85[/C][C]-0.0207237[/C][C]0.570724[/C][/ROW]
[ROW][C]67[/C][C]551.9[/C][C]551.652[/C][C]551.612[/C][C]0.0398026[/C][C]0.247697[/C][/ROW]
[ROW][C]68[/C][C]554.9[/C][C]555.008[/C][C]554.938[/C][C]0.0700658[/C][C]-0.107566[/C][/ROW]
[ROW][C]69[/C][C]558.1[/C][C]558.023[/C][C]558.112[/C][C]-0.0891447[/C][C]0.0766447[/C][/ROW]
[ROW][C]70[/C][C]561.3[/C][C]561.167[/C][C]561.187[/C][C]-0.0207237[/C][C]0.133224[/C][/ROW]
[ROW][C]71[/C][C]564.4[/C][C]564.065[/C][C]564.025[/C][C]0.0398026[/C][C]0.335197[/C][/ROW]
[ROW][C]72[/C][C]567[/C][C]566.62[/C][C]566.55[/C][C]0.0700658[/C][C]0.379934[/C][/ROW]
[ROW][C]73[/C][C]568.7[/C][C]568.673[/C][C]568.762[/C][C]-0.0891447[/C][C]0.0266447[/C][/ROW]
[ROW][C]74[/C][C]570.9[/C][C]570.704[/C][C]570.725[/C][C]-0.0207237[/C][C]0.195724[/C][/ROW]
[ROW][C]75[/C][C]572.5[/C][C]572.765[/C][C]572.725[/C][C]0.0398026[/C][C]-0.264803[/C][/ROW]
[ROW][C]76[/C][C]574.6[/C][C]575.095[/C][C]575.025[/C][C]0.0700658[/C][C]-0.495066[/C][/ROW]
[ROW][C]77[/C][C]577.1[/C][C]577.536[/C][C]577.625[/C][C]-0.0891447[/C][C]-0.435855[/C][/ROW]
[ROW][C]78[/C][C]580.9[/C][C]580.442[/C][C]580.462[/C][C]-0.0207237[/C][C]0.458224[/C][/ROW]
[ROW][C]79[/C][C]583.3[/C][C]NA[/C][C]NA[/C][C]0.0398026[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]586.5[/C][C]NA[/C][C]NA[/C][C]0.0700658[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=283979&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=283979&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	340.7	NA	NA	-0.0891447	NA
2	343.5	NA	NA	-0.0207237	NA
3	345.3	345.177	345.138	0.0398026	0.122697
4	346.9	347.233	347.162	0.0700658	-0.332566
5	349	349.023	349.112	-0.0891447	-0.0233553
6	351.4	351.067	351.088	-0.0207237	0.333224
7	353	353.527	353.487	0.0398026	-0.527303
8	355	356.608	356.538	0.0700658	-1.60757
9	360.1	359.798	359.888	-0.0891447	0.301645
10	364.7	363.304	363.325	-0.0207237	1.39572
11	366.5	366.34	366.3	0.0398026	0.160197
12	369	368.358	368.287	0.0700658	0.642434
13	369.9	369.961	370.05	-0.0891447	-0.0608553
14	370.8	372.204	372.225	-0.0207237	-1.40428
15	374.5	374.865	374.825	0.0398026	-0.364803
16	378.4	377.908	377.838	0.0700658	0.492434
17	381.3	380.973	381.062	-0.0891447	0.326645
18	383.5	384.342	384.362	-0.0207237	-0.841776
19	387.6	387.827	387.788	0.0398026	-0.227303
20	391.7	391.595	391.525	0.0700658	0.104934
21	395.4	395.373	395.462	-0.0891447	0.0266447
22	399.3	399.267	399.288	-0.0207237	0.0332237
23	403.3	403.077	403.038	0.0398026	0.222697
24	406.6	406.77	406.7	0.0700658	-0.170066
25	410.5	410.311	410.4	-0.0891447	0.189145
26	413.5	414.192	414.212	-0.0207237	-0.691776
27	418.7	417.677	417.638	0.0398026	1.0227
28	421.7	420.783	420.713	0.0700658	0.917434
29	422.8	423.273	423.362	-0.0891447	-0.473355
30	425.8	425.617	425.638	-0.0207237	0.183224
31	427.6	428.277	428.238	0.0398026	-0.677303
32	431	431.22	431.15	0.0700658	-0.220066
33	434.3	434.136	434.225	-0.0891447	0.164145
34	437.6	437.367	437.388	-0.0207237	0.233224
35	440.4	440.477	440.438	0.0398026	-0.0773026
36	443.5	443.07	443	0.0700658	0.429934
37	446.2	445.148	445.238	-0.0891447	1.05164
38	446.2	447.717	447.738	-0.0207237	-1.51678
39	449.7	450.64	450.6	0.0398026	-0.939803
40	454.2	454.058	453.988	0.0700658	0.142434
41	458.4	457.548	457.638	-0.0891447	0.851645
42	461.1	460.904	460.925	-0.0207237	0.195724
43	464	463.752	463.713	0.0398026	0.247697
44	466.2	466.408	466.338	0.0700658	-0.207566
45	468.7	468.948	469.038	-0.0891447	-0.248355
46	471.8	471.792	471.812	-0.0207237	0.00822368
47	474.9	474.677	474.638	0.0398026	0.222697
48	477.5	477.495	477.425	0.0700658	0.00493421
49	480	480.061	480.15	-0.0891447	-0.0608553
50	482.8	482.854	482.875	-0.0207237	-0.0542763
51	485.7	485.79	485.75	0.0398026	-0.0898026
52	488.5	488.858	488.788	0.0700658	-0.357566
53	492	491.836	491.925	-0.0891447	0.164145
54	495.1	495.217	495.238	-0.0207237	-0.116776
55	498.5	498.252	498.212	0.0398026	0.247697
56	502.2	501.408	501.338	0.0700658	0.792434
57	502.1	505.173	505.262	-0.0891447	-3.07336
58	510	509.579	509.6	-0.0207237	0.420724
59	515	514.802	514.763	0.0398026	0.197697
60	520.4	520.233	520.162	0.0700658	0.167434
61	525.2	525.023	525.113	-0.0891447	0.176645
62	530.1	529.792	529.812	-0.0207237	0.308224
63	534.5	534.515	534.475	0.0398026	-0.0148026
64	538.5	539.233	539.162	0.0700658	-0.732566
65	544.4	543.536	543.625	-0.0891447	0.864145
66	548.4	547.829	547.85	-0.0207237	0.570724
67	551.9	551.652	551.612	0.0398026	0.247697
68	554.9	555.008	554.938	0.0700658	-0.107566
69	558.1	558.023	558.112	-0.0891447	0.0766447
70	561.3	561.167	561.187	-0.0207237	0.133224
71	564.4	564.065	564.025	0.0398026	0.335197
72	567	566.62	566.55	0.0700658	0.379934
73	568.7	568.673	568.762	-0.0891447	0.0266447
74	570.9	570.704	570.725	-0.0207237	0.195724
75	572.5	572.765	572.725	0.0398026	-0.264803
76	574.6	575.095	575.025	0.0700658	-0.495066
77	577.1	577.536	577.625	-0.0891447	-0.435855
78	580.9	580.442	580.462	-0.0207237	0.458224
79	583.3	NA	NA	0.0398026	NA
80	586.5	NA	NA	0.0700658	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 = 4 ;

Parameters (R input):

par1 = additive ; par2 = 4 ;

R code (references can be found in the software module):

par2 <- '12'
par1 <- 'multiplicative'
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