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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Wed, 03 Dec 2014 18:23:56 +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/2014/Dec/03/t14176310524elorx8hepxciaf.htm/, Retrieved Thu, 16 May 2024 15:30:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263016, Retrieved Thu, 16 May 2024 15:30:09 +0000

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-       [Classical Decomposition] [] [2014-12-03 18:23:56] [bc3b0a9d08b571f2c6b79bb1a1231eac] [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 Ronald Aylmer Fisher' @ fisher.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 Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263016&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 Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263016&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263016&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	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	250.8	NA	NA	1.05137	NA
2	247.6	NA	NA	1.05577	NA
3	237.8	NA	NA	1.03557	NA
4	226.4	NA	NA	1.01441	NA
5	217.2	NA	NA	0.99433	NA
6	211.4	NA	NA	0.982146	NA
7	207.6	208.96	212.596	0.982898	0.993492
8	204.3	204.524	207.996	0.983307	0.998906
9	197.5	196.278	203.5	0.96451	1.00623
10	193.6	191.652	199.367	0.961306	1.01016
11	192.3	190.268	195.604	0.972722	1.01068
12	192	192.361	192.042	1.00166	0.998123
13	196.1	198.271	188.583	1.05137	0.98905
14	191.9	195.586	185.254	1.05577	0.981153
15	185.6	188.599	182.121	1.03557	0.984099
16	179.4	181.832	179.25	1.01441	0.986624
17	173.9	175.69	176.692	0.99433	0.989813
18	169.2	171.499	174.617	0.982146	0.986594
19	166.8	170.213	173.175	0.982898	0.979947
20	165.2	169.694	172.575	0.983307	0.973516
21	161.4	166.9	173.042	0.96451	0.967044
22	160.8	167.864	174.621	0.961306	0.957918
23	163.7	172.391	177.225	0.972722	0.949588
24	170.8	181.184	180.883	1.00166	0.942688
25	182.7	195.165	185.629	1.05137	0.93613
26	190.9	201.912	191.246	1.05577	0.945461
27	197.8	204.611	197.583	1.03557	0.96671
28	205.1	207.606	204.658	1.01441	0.987927
29	210.7	211.142	212.346	0.99433	0.997908
30	220.2	216.494	220.429	0.982146	1.01712
31	229.7	224.834	228.746	0.982898	1.02164
32	237.1	233.089	237.046	0.983307	1.01721
33	241.6	235.975	244.658	0.96451	1.02384
34	250.4	241.344	251.058	0.961306	1.03752
35	258.6	249.337	256.329	0.972722	1.03715
36	269.9	260.85	260.417	1.00166	1.0347
37	283.2	276.949	263.417	1.05137	1.02257
38	289.6	280.501	265.683	1.05577	1.03244
39	281.8	276.696	267.192	1.03557	1.01845
40	274.7	271.577	267.721	1.01441	1.0115
41	267.6	265.991	267.508	0.99433	1.00605
42	261.4	262.266	267.033	0.982146	0.996699
43	260.5	261.926	266.483	0.982898	0.994556
44	260.7	261.101	265.533	0.983307	0.998465
45	254.2	254.835	264.213	0.96451	0.997506
46	250.5	252.699	262.871	0.961306	0.991296
47	253.4	254.468	261.604	0.972722	0.995803
48	263.7	261.004	260.571	1.00166	1.01033
49	276.2	273.151	259.804	1.05137	1.01116
50	273.8	273.718	259.258	1.05577	1.0003
51	265.9	268.118	258.908	1.03557	0.991728
52	258.4	262.596	258.867	1.01441	0.984022
53	253.5	257.664	259.133	0.99433	0.98384
54	250.7	254.941	259.575	0.982146	0.983366
55	252.8	256.02	260.475	0.982898	0.987422
56	255.3	257.786	262.162	0.983307	0.990355
57	251.2	255.061	264.446	0.96451	0.984864
58	252.5	256.753	267.088	0.961306	0.983436
59	257.8	262.683	270.05	0.972722	0.981409
60	269.9	273.725	273.271	1.00166	0.986025
61	291.6	291.037	276.817	1.05137	1.00193
62	298.9	296.386	280.729	1.05577	1.00848
63	295.6	295.107	284.971	1.03557	1.00167
64	292.1	293.742	289.571	1.01441	0.994409
65	290.9	292.975	294.646	0.99433	0.992917
66	290.6	294.902	300.263	0.982146	0.985413
67	298	301.189	306.429	0.982898	0.989413
68	304	307.685	312.908	0.983307	0.988023
69	304.3	308.309	319.654	0.96451	0.986995
70	309.8	314.155	326.8	0.961306	0.986138
71	322.3	324.95	334.062	0.972722	0.991845
72	340.2	342.043	341.475	1.00166	0.994612
73	369.3	367.235	349.292	1.05137	1.00562
74	376.7	377.214	357.288	1.05577	0.998637
75	379.7	378.255	365.262	1.03557	1.00382
76	379.5	378.745	373.367	1.01441	1.00199
77	377.8	379.337	381.5	0.99433	0.995949
78	381.6	382.64	389.596	0.982146	0.997282
79	394.6	NA	NA	0.982898	NA
80	399.3	NA	NA	0.983307	NA
81	400.4	NA	NA	0.96451	NA
82	408.2	NA	NA	0.961306	NA
83	419.1	NA	NA	0.972722	NA
84	437.7	NA	NA	1.00166	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 250.8 & NA & NA & 1.05137 & NA \tabularnewline
2 & 247.6 & NA & NA & 1.05577 & NA \tabularnewline
3 & 237.8 & NA & NA & 1.03557 & NA \tabularnewline
4 & 226.4 & NA & NA & 1.01441 & NA \tabularnewline
5 & 217.2 & NA & NA & 0.99433 & NA \tabularnewline
6 & 211.4 & NA & NA & 0.982146 & NA \tabularnewline
7 & 207.6 & 208.96 & 212.596 & 0.982898 & 0.993492 \tabularnewline
8 & 204.3 & 204.524 & 207.996 & 0.983307 & 0.998906 \tabularnewline
9 & 197.5 & 196.278 & 203.5 & 0.96451 & 1.00623 \tabularnewline
10 & 193.6 & 191.652 & 199.367 & 0.961306 & 1.01016 \tabularnewline
11 & 192.3 & 190.268 & 195.604 & 0.972722 & 1.01068 \tabularnewline
12 & 192 & 192.361 & 192.042 & 1.00166 & 0.998123 \tabularnewline
13 & 196.1 & 198.271 & 188.583 & 1.05137 & 0.98905 \tabularnewline
14 & 191.9 & 195.586 & 185.254 & 1.05577 & 0.981153 \tabularnewline
15 & 185.6 & 188.599 & 182.121 & 1.03557 & 0.984099 \tabularnewline
16 & 179.4 & 181.832 & 179.25 & 1.01441 & 0.986624 \tabularnewline
17 & 173.9 & 175.69 & 176.692 & 0.99433 & 0.989813 \tabularnewline
18 & 169.2 & 171.499 & 174.617 & 0.982146 & 0.986594 \tabularnewline
19 & 166.8 & 170.213 & 173.175 & 0.982898 & 0.979947 \tabularnewline
20 & 165.2 & 169.694 & 172.575 & 0.983307 & 0.973516 \tabularnewline
21 & 161.4 & 166.9 & 173.042 & 0.96451 & 0.967044 \tabularnewline
22 & 160.8 & 167.864 & 174.621 & 0.961306 & 0.957918 \tabularnewline
23 & 163.7 & 172.391 & 177.225 & 0.972722 & 0.949588 \tabularnewline
24 & 170.8 & 181.184 & 180.883 & 1.00166 & 0.942688 \tabularnewline
25 & 182.7 & 195.165 & 185.629 & 1.05137 & 0.93613 \tabularnewline
26 & 190.9 & 201.912 & 191.246 & 1.05577 & 0.945461 \tabularnewline
27 & 197.8 & 204.611 & 197.583 & 1.03557 & 0.96671 \tabularnewline
28 & 205.1 & 207.606 & 204.658 & 1.01441 & 0.987927 \tabularnewline
29 & 210.7 & 211.142 & 212.346 & 0.99433 & 0.997908 \tabularnewline
30 & 220.2 & 216.494 & 220.429 & 0.982146 & 1.01712 \tabularnewline
31 & 229.7 & 224.834 & 228.746 & 0.982898 & 1.02164 \tabularnewline
32 & 237.1 & 233.089 & 237.046 & 0.983307 & 1.01721 \tabularnewline
33 & 241.6 & 235.975 & 244.658 & 0.96451 & 1.02384 \tabularnewline
34 & 250.4 & 241.344 & 251.058 & 0.961306 & 1.03752 \tabularnewline
35 & 258.6 & 249.337 & 256.329 & 0.972722 & 1.03715 \tabularnewline
36 & 269.9 & 260.85 & 260.417 & 1.00166 & 1.0347 \tabularnewline
37 & 283.2 & 276.949 & 263.417 & 1.05137 & 1.02257 \tabularnewline
38 & 289.6 & 280.501 & 265.683 & 1.05577 & 1.03244 \tabularnewline
39 & 281.8 & 276.696 & 267.192 & 1.03557 & 1.01845 \tabularnewline
40 & 274.7 & 271.577 & 267.721 & 1.01441 & 1.0115 \tabularnewline
41 & 267.6 & 265.991 & 267.508 & 0.99433 & 1.00605 \tabularnewline
42 & 261.4 & 262.266 & 267.033 & 0.982146 & 0.996699 \tabularnewline
43 & 260.5 & 261.926 & 266.483 & 0.982898 & 0.994556 \tabularnewline
44 & 260.7 & 261.101 & 265.533 & 0.983307 & 0.998465 \tabularnewline
45 & 254.2 & 254.835 & 264.213 & 0.96451 & 0.997506 \tabularnewline
46 & 250.5 & 252.699 & 262.871 & 0.961306 & 0.991296 \tabularnewline
47 & 253.4 & 254.468 & 261.604 & 0.972722 & 0.995803 \tabularnewline
48 & 263.7 & 261.004 & 260.571 & 1.00166 & 1.01033 \tabularnewline
49 & 276.2 & 273.151 & 259.804 & 1.05137 & 1.01116 \tabularnewline
50 & 273.8 & 273.718 & 259.258 & 1.05577 & 1.0003 \tabularnewline
51 & 265.9 & 268.118 & 258.908 & 1.03557 & 0.991728 \tabularnewline
52 & 258.4 & 262.596 & 258.867 & 1.01441 & 0.984022 \tabularnewline
53 & 253.5 & 257.664 & 259.133 & 0.99433 & 0.98384 \tabularnewline
54 & 250.7 & 254.941 & 259.575 & 0.982146 & 0.983366 \tabularnewline
55 & 252.8 & 256.02 & 260.475 & 0.982898 & 0.987422 \tabularnewline
56 & 255.3 & 257.786 & 262.162 & 0.983307 & 0.990355 \tabularnewline
57 & 251.2 & 255.061 & 264.446 & 0.96451 & 0.984864 \tabularnewline
58 & 252.5 & 256.753 & 267.088 & 0.961306 & 0.983436 \tabularnewline
59 & 257.8 & 262.683 & 270.05 & 0.972722 & 0.981409 \tabularnewline
60 & 269.9 & 273.725 & 273.271 & 1.00166 & 0.986025 \tabularnewline
61 & 291.6 & 291.037 & 276.817 & 1.05137 & 1.00193 \tabularnewline
62 & 298.9 & 296.386 & 280.729 & 1.05577 & 1.00848 \tabularnewline
63 & 295.6 & 295.107 & 284.971 & 1.03557 & 1.00167 \tabularnewline
64 & 292.1 & 293.742 & 289.571 & 1.01441 & 0.994409 \tabularnewline
65 & 290.9 & 292.975 & 294.646 & 0.99433 & 0.992917 \tabularnewline
66 & 290.6 & 294.902 & 300.263 & 0.982146 & 0.985413 \tabularnewline
67 & 298 & 301.189 & 306.429 & 0.982898 & 0.989413 \tabularnewline
68 & 304 & 307.685 & 312.908 & 0.983307 & 0.988023 \tabularnewline
69 & 304.3 & 308.309 & 319.654 & 0.96451 & 0.986995 \tabularnewline
70 & 309.8 & 314.155 & 326.8 & 0.961306 & 0.986138 \tabularnewline
71 & 322.3 & 324.95 & 334.062 & 0.972722 & 0.991845 \tabularnewline
72 & 340.2 & 342.043 & 341.475 & 1.00166 & 0.994612 \tabularnewline
73 & 369.3 & 367.235 & 349.292 & 1.05137 & 1.00562 \tabularnewline
74 & 376.7 & 377.214 & 357.288 & 1.05577 & 0.998637 \tabularnewline
75 & 379.7 & 378.255 & 365.262 & 1.03557 & 1.00382 \tabularnewline
76 & 379.5 & 378.745 & 373.367 & 1.01441 & 1.00199 \tabularnewline
77 & 377.8 & 379.337 & 381.5 & 0.99433 & 0.995949 \tabularnewline
78 & 381.6 & 382.64 & 389.596 & 0.982146 & 0.997282 \tabularnewline
79 & 394.6 & NA & NA & 0.982898 & NA \tabularnewline
80 & 399.3 & NA & NA & 0.983307 & NA \tabularnewline
81 & 400.4 & NA & NA & 0.96451 & NA \tabularnewline
82 & 408.2 & NA & NA & 0.961306 & NA \tabularnewline
83 & 419.1 & NA & NA & 0.972722 & NA \tabularnewline
84 & 437.7 & NA & NA & 1.00166 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263016&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]250.8[/C][C]NA[/C][C]NA[/C][C]1.05137[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]247.6[/C][C]NA[/C][C]NA[/C][C]1.05577[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]237.8[/C][C]NA[/C][C]NA[/C][C]1.03557[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]226.4[/C][C]NA[/C][C]NA[/C][C]1.01441[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]217.2[/C][C]NA[/C][C]NA[/C][C]0.99433[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]211.4[/C][C]NA[/C][C]NA[/C][C]0.982146[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]207.6[/C][C]208.96[/C][C]212.596[/C][C]0.982898[/C][C]0.993492[/C][/ROW]
[ROW][C]8[/C][C]204.3[/C][C]204.524[/C][C]207.996[/C][C]0.983307[/C][C]0.998906[/C][/ROW]
[ROW][C]9[/C][C]197.5[/C][C]196.278[/C][C]203.5[/C][C]0.96451[/C][C]1.00623[/C][/ROW]
[ROW][C]10[/C][C]193.6[/C][C]191.652[/C][C]199.367[/C][C]0.961306[/C][C]1.01016[/C][/ROW]
[ROW][C]11[/C][C]192.3[/C][C]190.268[/C][C]195.604[/C][C]0.972722[/C][C]1.01068[/C][/ROW]
[ROW][C]12[/C][C]192[/C][C]192.361[/C][C]192.042[/C][C]1.00166[/C][C]0.998123[/C][/ROW]
[ROW][C]13[/C][C]196.1[/C][C]198.271[/C][C]188.583[/C][C]1.05137[/C][C]0.98905[/C][/ROW]
[ROW][C]14[/C][C]191.9[/C][C]195.586[/C][C]185.254[/C][C]1.05577[/C][C]0.981153[/C][/ROW]
[ROW][C]15[/C][C]185.6[/C][C]188.599[/C][C]182.121[/C][C]1.03557[/C][C]0.984099[/C][/ROW]
[ROW][C]16[/C][C]179.4[/C][C]181.832[/C][C]179.25[/C][C]1.01441[/C][C]0.986624[/C][/ROW]
[ROW][C]17[/C][C]173.9[/C][C]175.69[/C][C]176.692[/C][C]0.99433[/C][C]0.989813[/C][/ROW]
[ROW][C]18[/C][C]169.2[/C][C]171.499[/C][C]174.617[/C][C]0.982146[/C][C]0.986594[/C][/ROW]
[ROW][C]19[/C][C]166.8[/C][C]170.213[/C][C]173.175[/C][C]0.982898[/C][C]0.979947[/C][/ROW]
[ROW][C]20[/C][C]165.2[/C][C]169.694[/C][C]172.575[/C][C]0.983307[/C][C]0.973516[/C][/ROW]
[ROW][C]21[/C][C]161.4[/C][C]166.9[/C][C]173.042[/C][C]0.96451[/C][C]0.967044[/C][/ROW]
[ROW][C]22[/C][C]160.8[/C][C]167.864[/C][C]174.621[/C][C]0.961306[/C][C]0.957918[/C][/ROW]
[ROW][C]23[/C][C]163.7[/C][C]172.391[/C][C]177.225[/C][C]0.972722[/C][C]0.949588[/C][/ROW]
[ROW][C]24[/C][C]170.8[/C][C]181.184[/C][C]180.883[/C][C]1.00166[/C][C]0.942688[/C][/ROW]
[ROW][C]25[/C][C]182.7[/C][C]195.165[/C][C]185.629[/C][C]1.05137[/C][C]0.93613[/C][/ROW]
[ROW][C]26[/C][C]190.9[/C][C]201.912[/C][C]191.246[/C][C]1.05577[/C][C]0.945461[/C][/ROW]
[ROW][C]27[/C][C]197.8[/C][C]204.611[/C][C]197.583[/C][C]1.03557[/C][C]0.96671[/C][/ROW]
[ROW][C]28[/C][C]205.1[/C][C]207.606[/C][C]204.658[/C][C]1.01441[/C][C]0.987927[/C][/ROW]
[ROW][C]29[/C][C]210.7[/C][C]211.142[/C][C]212.346[/C][C]0.99433[/C][C]0.997908[/C][/ROW]
[ROW][C]30[/C][C]220.2[/C][C]216.494[/C][C]220.429[/C][C]0.982146[/C][C]1.01712[/C][/ROW]
[ROW][C]31[/C][C]229.7[/C][C]224.834[/C][C]228.746[/C][C]0.982898[/C][C]1.02164[/C][/ROW]
[ROW][C]32[/C][C]237.1[/C][C]233.089[/C][C]237.046[/C][C]0.983307[/C][C]1.01721[/C][/ROW]
[ROW][C]33[/C][C]241.6[/C][C]235.975[/C][C]244.658[/C][C]0.96451[/C][C]1.02384[/C][/ROW]
[ROW][C]34[/C][C]250.4[/C][C]241.344[/C][C]251.058[/C][C]0.961306[/C][C]1.03752[/C][/ROW]
[ROW][C]35[/C][C]258.6[/C][C]249.337[/C][C]256.329[/C][C]0.972722[/C][C]1.03715[/C][/ROW]
[ROW][C]36[/C][C]269.9[/C][C]260.85[/C][C]260.417[/C][C]1.00166[/C][C]1.0347[/C][/ROW]
[ROW][C]37[/C][C]283.2[/C][C]276.949[/C][C]263.417[/C][C]1.05137[/C][C]1.02257[/C][/ROW]
[ROW][C]38[/C][C]289.6[/C][C]280.501[/C][C]265.683[/C][C]1.05577[/C][C]1.03244[/C][/ROW]
[ROW][C]39[/C][C]281.8[/C][C]276.696[/C][C]267.192[/C][C]1.03557[/C][C]1.01845[/C][/ROW]
[ROW][C]40[/C][C]274.7[/C][C]271.577[/C][C]267.721[/C][C]1.01441[/C][C]1.0115[/C][/ROW]
[ROW][C]41[/C][C]267.6[/C][C]265.991[/C][C]267.508[/C][C]0.99433[/C][C]1.00605[/C][/ROW]
[ROW][C]42[/C][C]261.4[/C][C]262.266[/C][C]267.033[/C][C]0.982146[/C][C]0.996699[/C][/ROW]
[ROW][C]43[/C][C]260.5[/C][C]261.926[/C][C]266.483[/C][C]0.982898[/C][C]0.994556[/C][/ROW]
[ROW][C]44[/C][C]260.7[/C][C]261.101[/C][C]265.533[/C][C]0.983307[/C][C]0.998465[/C][/ROW]
[ROW][C]45[/C][C]254.2[/C][C]254.835[/C][C]264.213[/C][C]0.96451[/C][C]0.997506[/C][/ROW]
[ROW][C]46[/C][C]250.5[/C][C]252.699[/C][C]262.871[/C][C]0.961306[/C][C]0.991296[/C][/ROW]
[ROW][C]47[/C][C]253.4[/C][C]254.468[/C][C]261.604[/C][C]0.972722[/C][C]0.995803[/C][/ROW]
[ROW][C]48[/C][C]263.7[/C][C]261.004[/C][C]260.571[/C][C]1.00166[/C][C]1.01033[/C][/ROW]
[ROW][C]49[/C][C]276.2[/C][C]273.151[/C][C]259.804[/C][C]1.05137[/C][C]1.01116[/C][/ROW]
[ROW][C]50[/C][C]273.8[/C][C]273.718[/C][C]259.258[/C][C]1.05577[/C][C]1.0003[/C][/ROW]
[ROW][C]51[/C][C]265.9[/C][C]268.118[/C][C]258.908[/C][C]1.03557[/C][C]0.991728[/C][/ROW]
[ROW][C]52[/C][C]258.4[/C][C]262.596[/C][C]258.867[/C][C]1.01441[/C][C]0.984022[/C][/ROW]
[ROW][C]53[/C][C]253.5[/C][C]257.664[/C][C]259.133[/C][C]0.99433[/C][C]0.98384[/C][/ROW]
[ROW][C]54[/C][C]250.7[/C][C]254.941[/C][C]259.575[/C][C]0.982146[/C][C]0.983366[/C][/ROW]
[ROW][C]55[/C][C]252.8[/C][C]256.02[/C][C]260.475[/C][C]0.982898[/C][C]0.987422[/C][/ROW]
[ROW][C]56[/C][C]255.3[/C][C]257.786[/C][C]262.162[/C][C]0.983307[/C][C]0.990355[/C][/ROW]
[ROW][C]57[/C][C]251.2[/C][C]255.061[/C][C]264.446[/C][C]0.96451[/C][C]0.984864[/C][/ROW]
[ROW][C]58[/C][C]252.5[/C][C]256.753[/C][C]267.088[/C][C]0.961306[/C][C]0.983436[/C][/ROW]
[ROW][C]59[/C][C]257.8[/C][C]262.683[/C][C]270.05[/C][C]0.972722[/C][C]0.981409[/C][/ROW]
[ROW][C]60[/C][C]269.9[/C][C]273.725[/C][C]273.271[/C][C]1.00166[/C][C]0.986025[/C][/ROW]
[ROW][C]61[/C][C]291.6[/C][C]291.037[/C][C]276.817[/C][C]1.05137[/C][C]1.00193[/C][/ROW]
[ROW][C]62[/C][C]298.9[/C][C]296.386[/C][C]280.729[/C][C]1.05577[/C][C]1.00848[/C][/ROW]
[ROW][C]63[/C][C]295.6[/C][C]295.107[/C][C]284.971[/C][C]1.03557[/C][C]1.00167[/C][/ROW]
[ROW][C]64[/C][C]292.1[/C][C]293.742[/C][C]289.571[/C][C]1.01441[/C][C]0.994409[/C][/ROW]
[ROW][C]65[/C][C]290.9[/C][C]292.975[/C][C]294.646[/C][C]0.99433[/C][C]0.992917[/C][/ROW]
[ROW][C]66[/C][C]290.6[/C][C]294.902[/C][C]300.263[/C][C]0.982146[/C][C]0.985413[/C][/ROW]
[ROW][C]67[/C][C]298[/C][C]301.189[/C][C]306.429[/C][C]0.982898[/C][C]0.989413[/C][/ROW]
[ROW][C]68[/C][C]304[/C][C]307.685[/C][C]312.908[/C][C]0.983307[/C][C]0.988023[/C][/ROW]
[ROW][C]69[/C][C]304.3[/C][C]308.309[/C][C]319.654[/C][C]0.96451[/C][C]0.986995[/C][/ROW]
[ROW][C]70[/C][C]309.8[/C][C]314.155[/C][C]326.8[/C][C]0.961306[/C][C]0.986138[/C][/ROW]
[ROW][C]71[/C][C]322.3[/C][C]324.95[/C][C]334.062[/C][C]0.972722[/C][C]0.991845[/C][/ROW]
[ROW][C]72[/C][C]340.2[/C][C]342.043[/C][C]341.475[/C][C]1.00166[/C][C]0.994612[/C][/ROW]
[ROW][C]73[/C][C]369.3[/C][C]367.235[/C][C]349.292[/C][C]1.05137[/C][C]1.00562[/C][/ROW]
[ROW][C]74[/C][C]376.7[/C][C]377.214[/C][C]357.288[/C][C]1.05577[/C][C]0.998637[/C][/ROW]
[ROW][C]75[/C][C]379.7[/C][C]378.255[/C][C]365.262[/C][C]1.03557[/C][C]1.00382[/C][/ROW]
[ROW][C]76[/C][C]379.5[/C][C]378.745[/C][C]373.367[/C][C]1.01441[/C][C]1.00199[/C][/ROW]
[ROW][C]77[/C][C]377.8[/C][C]379.337[/C][C]381.5[/C][C]0.99433[/C][C]0.995949[/C][/ROW]
[ROW][C]78[/C][C]381.6[/C][C]382.64[/C][C]389.596[/C][C]0.982146[/C][C]0.997282[/C][/ROW]
[ROW][C]79[/C][C]394.6[/C][C]NA[/C][C]NA[/C][C]0.982898[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]399.3[/C][C]NA[/C][C]NA[/C][C]0.983307[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]400.4[/C][C]NA[/C][C]NA[/C][C]0.96451[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]408.2[/C][C]NA[/C][C]NA[/C][C]0.961306[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]419.1[/C][C]NA[/C][C]NA[/C][C]0.972722[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]437.7[/C][C]NA[/C][C]NA[/C][C]1.00166[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263016&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263016&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	250.8	NA	NA	1.05137	NA
2	247.6	NA	NA	1.05577	NA
3	237.8	NA	NA	1.03557	NA
4	226.4	NA	NA	1.01441	NA
5	217.2	NA	NA	0.99433	NA
6	211.4	NA	NA	0.982146	NA
7	207.6	208.96	212.596	0.982898	0.993492
8	204.3	204.524	207.996	0.983307	0.998906
9	197.5	196.278	203.5	0.96451	1.00623
10	193.6	191.652	199.367	0.961306	1.01016
11	192.3	190.268	195.604	0.972722	1.01068
12	192	192.361	192.042	1.00166	0.998123
13	196.1	198.271	188.583	1.05137	0.98905
14	191.9	195.586	185.254	1.05577	0.981153
15	185.6	188.599	182.121	1.03557	0.984099
16	179.4	181.832	179.25	1.01441	0.986624
17	173.9	175.69	176.692	0.99433	0.989813
18	169.2	171.499	174.617	0.982146	0.986594
19	166.8	170.213	173.175	0.982898	0.979947
20	165.2	169.694	172.575	0.983307	0.973516
21	161.4	166.9	173.042	0.96451	0.967044
22	160.8	167.864	174.621	0.961306	0.957918
23	163.7	172.391	177.225	0.972722	0.949588
24	170.8	181.184	180.883	1.00166	0.942688
25	182.7	195.165	185.629	1.05137	0.93613
26	190.9	201.912	191.246	1.05577	0.945461
27	197.8	204.611	197.583	1.03557	0.96671
28	205.1	207.606	204.658	1.01441	0.987927
29	210.7	211.142	212.346	0.99433	0.997908
30	220.2	216.494	220.429	0.982146	1.01712
31	229.7	224.834	228.746	0.982898	1.02164
32	237.1	233.089	237.046	0.983307	1.01721
33	241.6	235.975	244.658	0.96451	1.02384
34	250.4	241.344	251.058	0.961306	1.03752
35	258.6	249.337	256.329	0.972722	1.03715
36	269.9	260.85	260.417	1.00166	1.0347
37	283.2	276.949	263.417	1.05137	1.02257
38	289.6	280.501	265.683	1.05577	1.03244
39	281.8	276.696	267.192	1.03557	1.01845
40	274.7	271.577	267.721	1.01441	1.0115
41	267.6	265.991	267.508	0.99433	1.00605
42	261.4	262.266	267.033	0.982146	0.996699
43	260.5	261.926	266.483	0.982898	0.994556
44	260.7	261.101	265.533	0.983307	0.998465
45	254.2	254.835	264.213	0.96451	0.997506
46	250.5	252.699	262.871	0.961306	0.991296
47	253.4	254.468	261.604	0.972722	0.995803
48	263.7	261.004	260.571	1.00166	1.01033
49	276.2	273.151	259.804	1.05137	1.01116
50	273.8	273.718	259.258	1.05577	1.0003
51	265.9	268.118	258.908	1.03557	0.991728
52	258.4	262.596	258.867	1.01441	0.984022
53	253.5	257.664	259.133	0.99433	0.98384
54	250.7	254.941	259.575	0.982146	0.983366
55	252.8	256.02	260.475	0.982898	0.987422
56	255.3	257.786	262.162	0.983307	0.990355
57	251.2	255.061	264.446	0.96451	0.984864
58	252.5	256.753	267.088	0.961306	0.983436
59	257.8	262.683	270.05	0.972722	0.981409
60	269.9	273.725	273.271	1.00166	0.986025
61	291.6	291.037	276.817	1.05137	1.00193
62	298.9	296.386	280.729	1.05577	1.00848
63	295.6	295.107	284.971	1.03557	1.00167
64	292.1	293.742	289.571	1.01441	0.994409
65	290.9	292.975	294.646	0.99433	0.992917
66	290.6	294.902	300.263	0.982146	0.985413
67	298	301.189	306.429	0.982898	0.989413
68	304	307.685	312.908	0.983307	0.988023
69	304.3	308.309	319.654	0.96451	0.986995
70	309.8	314.155	326.8	0.961306	0.986138
71	322.3	324.95	334.062	0.972722	0.991845
72	340.2	342.043	341.475	1.00166	0.994612
73	369.3	367.235	349.292	1.05137	1.00562
74	376.7	377.214	357.288	1.05577	0.998637
75	379.7	378.255	365.262	1.03557	1.00382
76	379.5	378.745	373.367	1.01441	1.00199
77	377.8	379.337	381.5	0.99433	0.995949
78	381.6	382.64	389.596	0.982146	0.997282
79	394.6	NA	NA	0.982898	NA
80	399.3	NA	NA	0.983307	NA
81	400.4	NA	NA	0.96451	NA
82	408.2	NA	NA	0.961306	NA
83	419.1	NA	NA	0.972722	NA
84	437.7	NA	NA	1.00166	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 <- '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