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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 06 May 2013 16:44:48 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/06/t1367873197yaii6iv8idtpejq.htm/, Retrieved Mon, 29 Apr 2024 02:46:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208754, Retrieved Mon, 29 Apr 2024 02:46:08 +0000

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No (this computation is public)

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Estimated Impact

129

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [Gouden trouwring ...] [2013-05-06 20:44:48] [b63567b613f887a01bb6abfb1a1e8ea5] [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	3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208754&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]3 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=208754&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208754&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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	33.7	NA	NA	0.987006567728041	NA
2	34.59	NA	NA	0.989153728401334	NA
3	35.1	NA	NA	0.996709077324467	NA
4	35.87	NA	NA	1.00468927406617	NA
5	37.15	NA	NA	1.00718020737525	NA
6	37.61	NA	NA	1.00255741740333	NA
7	37.97	37.9208236277349	37.7275	1.00512420986641	1.00129681709311
8	38.94	38.3992004774195	38.2591666666667	1.00366013750307	1.01408361413406
9	39.18	38.8969285457525	38.7845833333333	1.00289664610945	1.00727747575016
10	39.49	39.443266551311	39.2920833333333	1.00384767630403	1.0011848270383
11	39.86	39.7959581717053	39.73375	1.00156562548728	1.00160925458858
12	40.02	39.9380427074489	40.1141666666667	0.99560943243116	1.00205211089465
13	40.2	39.9507358397386	40.4766666666667	0.987006567728041	1.00623928833905
14	40.85	40.3677758034453	40.8104166666667	0.989153728401334	1.01194577077773
15	41.45	40.9796937141955	41.115	0.996709077324467	1.0114765690804
16	41.7	41.6100435265122	41.4158333333333	1.00468927406617	1.00216189328018
17	41.92	42.0166206427574	41.7170833333333	1.00718020737525	0.997700418518211
18	41.97	42.1245385534872	42.0170833333333	1.00255741740333	0.996331388810562
19	42.31	42.5343437510217	42.3175	1.00512420986641	0.994725585697645
20	42.61	42.7776678272767	42.6216666666667	1.00366013750307	0.996080482275152
21	42.82	43.0869471584773	42.9625	1.00289664610945	0.99380445410775
22	43.07	43.5904122640421	43.4233333333333	1.00384767630403	0.988061313554693
23	43.51	44.078068539674	44.0091666666667	1.00156562548728	0.98711221796929
24	43.57	44.478021719335	44.6741666666667	0.99560943243116	0.979584934665826
25	43.86	44.7726741758267	45.3620833333333	0.987006567728041	0.979615374944044
26	44.49	45.5323947078607	46.0316666666667	0.989153728401334	0.977106525704418
27	45.99	46.5645869108036	46.7183333333333	0.996709077324467	0.987660431479738
28	48.22	47.6612033001066	47.43875	1.00468927406617	1.0117243514893
29	49.46	48.5242637576608	48.1783333333333	1.00718020737525	1.01928388335807
30	50.39	49.058476291603	48.9333333333333	1.00255741740333	1.02714156266253
31	50.4	49.9391775654583	49.6845833333333	1.00512420986641	1.0092276736824
32	50.59	50.6179262680715	50.4333333333333	1.00366013750307	0.999448292924456
33	51.32	51.2989991957035	51.1508333333333	1.00289664610945	1.00040938038998
34	51.86	51.9625018844177	51.7633333333333	1.00384767630403	0.998027387429387
35	52.47	52.3802129369423	52.2983333333333	1.00156562548728	1.00171414085631
36	52.73	52.5636148224666	52.7954166666667	0.99560943243116	1.00316540591996
37	52.73	52.6000475106466	53.2925	0.987006567728041	1.00247057741397
38	53.59	53.2387265468808	53.8225	0.989153728401334	1.00659808143251
39	54.11	54.1624171481582	54.34125	0.996709077324467	0.999032222878554
40	54.8	55.0992528924432	54.8420833333333	1.00468927406617	0.994568839381047
41	55.72	55.7344150672084	55.3370833333333	1.00718020737525	0.999741361469551
42	56.06	55.9731983458852	55.8304166666667	1.00255741740333	1.00155077173862
43	56.66	56.6307919926439	56.3420833333333	1.00512420986641	1.00051576194378
44	57.05	57.0601697756693	56.8520833333333	1.00366013750307	0.999821771023302
45	57.31	57.5737892115283	57.4075	1.00289664610945	0.995418241266714
46	57.89	58.2490979572717	58.0258333333333	1.00384767630403	0.993835132733985
47	58.32	58.7522569100945	58.6604166666667	1.00156562548728	0.992642718206451
48	58.72	59.0695076261407	59.33	0.99560943243116	0.994083112587415
49	59.02	59.2816707214289	60.0620833333333	0.987006567728041	0.995585975930765
50	59.54	60.19536228925	60.8554166666667	0.989153728401334	0.989112744498474
51	61.49	61.5401407976037	61.7433333333333	0.996709077324467	0.999185234272236
52	62.26	63.0760671079977	62.7816666666667	1.00468927406617	0.987062175157489
53	63.49	64.379378513846	63.9204166666667	1.00718020737525	0.986185351049098
54	64.36	65.2798553051889	65.1133333333333	1.00255741740333	0.985909048038043
55	65.93	66.6715640474552	66.3316666666666	1.00512420986641	0.988877356365491
56	66.82	67.8231701752179	67.5758333333333	1.00366013750307	0.985209034425459
57	68.85	69.0063931035735	68.8070833333333	1.00289664610945	0.997733643267823
58	71.27	70.318274915502	70.04875	1.00384767630403	1.01353453402606
59	72.27	71.4437626610609	71.3320833333333	1.00156562548728	1.0115648631618
60	73.4	72.2613326058536	72.58	0.99560943243116	1.01575763071458
61	73.58	72.7987256664644	73.7570833333333	0.987006567728041	1.01073197815461
62	74.84	74.1078094792148	74.9204166666667	0.989153728401334	1.0098800723693
63	75.74	75.9459093285333	76.1966666666667	0.996709077324467	0.997288737071505
64	77.81	77.8780704587084	77.5145833333333	1.00468927406617	0.999125935474422
65	78.74	79.396435405811	78.8304166666667	1.00718020737525	0.991732180387496
66	79.06	80.3691799016236	80.1641666666667	1.00255741740333	0.983710423532677
67	79.48	NA	NA	1.00512420986641	NA
68	81.19	NA	NA	1.00366013750307	NA
69	85.11	NA	NA	1.00289664610945	NA
70	86.64	NA	NA	1.00384767630403	NA
71	88.48	NA	NA	1.00156562548728	NA
72	89.2	NA	NA	0.99560943243116	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 33.7 & NA & NA & 0.987006567728041 & NA \tabularnewline
2 & 34.59 & NA & NA & 0.989153728401334 & NA \tabularnewline
3 & 35.1 & NA & NA & 0.996709077324467 & NA \tabularnewline
4 & 35.87 & NA & NA & 1.00468927406617 & NA \tabularnewline
5 & 37.15 & NA & NA & 1.00718020737525 & NA \tabularnewline
6 & 37.61 & NA & NA & 1.00255741740333 & NA \tabularnewline
7 & 37.97 & 37.9208236277349 & 37.7275 & 1.00512420986641 & 1.00129681709311 \tabularnewline
8 & 38.94 & 38.3992004774195 & 38.2591666666667 & 1.00366013750307 & 1.01408361413406 \tabularnewline
9 & 39.18 & 38.8969285457525 & 38.7845833333333 & 1.00289664610945 & 1.00727747575016 \tabularnewline
10 & 39.49 & 39.443266551311 & 39.2920833333333 & 1.00384767630403 & 1.0011848270383 \tabularnewline
11 & 39.86 & 39.7959581717053 & 39.73375 & 1.00156562548728 & 1.00160925458858 \tabularnewline
12 & 40.02 & 39.9380427074489 & 40.1141666666667 & 0.99560943243116 & 1.00205211089465 \tabularnewline
13 & 40.2 & 39.9507358397386 & 40.4766666666667 & 0.987006567728041 & 1.00623928833905 \tabularnewline
14 & 40.85 & 40.3677758034453 & 40.8104166666667 & 0.989153728401334 & 1.01194577077773 \tabularnewline
15 & 41.45 & 40.9796937141955 & 41.115 & 0.996709077324467 & 1.0114765690804 \tabularnewline
16 & 41.7 & 41.6100435265122 & 41.4158333333333 & 1.00468927406617 & 1.00216189328018 \tabularnewline
17 & 41.92 & 42.0166206427574 & 41.7170833333333 & 1.00718020737525 & 0.997700418518211 \tabularnewline
18 & 41.97 & 42.1245385534872 & 42.0170833333333 & 1.00255741740333 & 0.996331388810562 \tabularnewline
19 & 42.31 & 42.5343437510217 & 42.3175 & 1.00512420986641 & 0.994725585697645 \tabularnewline
20 & 42.61 & 42.7776678272767 & 42.6216666666667 & 1.00366013750307 & 0.996080482275152 \tabularnewline
21 & 42.82 & 43.0869471584773 & 42.9625 & 1.00289664610945 & 0.99380445410775 \tabularnewline
22 & 43.07 & 43.5904122640421 & 43.4233333333333 & 1.00384767630403 & 0.988061313554693 \tabularnewline
23 & 43.51 & 44.078068539674 & 44.0091666666667 & 1.00156562548728 & 0.98711221796929 \tabularnewline
24 & 43.57 & 44.478021719335 & 44.6741666666667 & 0.99560943243116 & 0.979584934665826 \tabularnewline
25 & 43.86 & 44.7726741758267 & 45.3620833333333 & 0.987006567728041 & 0.979615374944044 \tabularnewline
26 & 44.49 & 45.5323947078607 & 46.0316666666667 & 0.989153728401334 & 0.977106525704418 \tabularnewline
27 & 45.99 & 46.5645869108036 & 46.7183333333333 & 0.996709077324467 & 0.987660431479738 \tabularnewline
28 & 48.22 & 47.6612033001066 & 47.43875 & 1.00468927406617 & 1.0117243514893 \tabularnewline
29 & 49.46 & 48.5242637576608 & 48.1783333333333 & 1.00718020737525 & 1.01928388335807 \tabularnewline
30 & 50.39 & 49.058476291603 & 48.9333333333333 & 1.00255741740333 & 1.02714156266253 \tabularnewline
31 & 50.4 & 49.9391775654583 & 49.6845833333333 & 1.00512420986641 & 1.0092276736824 \tabularnewline
32 & 50.59 & 50.6179262680715 & 50.4333333333333 & 1.00366013750307 & 0.999448292924456 \tabularnewline
33 & 51.32 & 51.2989991957035 & 51.1508333333333 & 1.00289664610945 & 1.00040938038998 \tabularnewline
34 & 51.86 & 51.9625018844177 & 51.7633333333333 & 1.00384767630403 & 0.998027387429387 \tabularnewline
35 & 52.47 & 52.3802129369423 & 52.2983333333333 & 1.00156562548728 & 1.00171414085631 \tabularnewline
36 & 52.73 & 52.5636148224666 & 52.7954166666667 & 0.99560943243116 & 1.00316540591996 \tabularnewline
37 & 52.73 & 52.6000475106466 & 53.2925 & 0.987006567728041 & 1.00247057741397 \tabularnewline
38 & 53.59 & 53.2387265468808 & 53.8225 & 0.989153728401334 & 1.00659808143251 \tabularnewline
39 & 54.11 & 54.1624171481582 & 54.34125 & 0.996709077324467 & 0.999032222878554 \tabularnewline
40 & 54.8 & 55.0992528924432 & 54.8420833333333 & 1.00468927406617 & 0.994568839381047 \tabularnewline
41 & 55.72 & 55.7344150672084 & 55.3370833333333 & 1.00718020737525 & 0.999741361469551 \tabularnewline
42 & 56.06 & 55.9731983458852 & 55.8304166666667 & 1.00255741740333 & 1.00155077173862 \tabularnewline
43 & 56.66 & 56.6307919926439 & 56.3420833333333 & 1.00512420986641 & 1.00051576194378 \tabularnewline
44 & 57.05 & 57.0601697756693 & 56.8520833333333 & 1.00366013750307 & 0.999821771023302 \tabularnewline
45 & 57.31 & 57.5737892115283 & 57.4075 & 1.00289664610945 & 0.995418241266714 \tabularnewline
46 & 57.89 & 58.2490979572717 & 58.0258333333333 & 1.00384767630403 & 0.993835132733985 \tabularnewline
47 & 58.32 & 58.7522569100945 & 58.6604166666667 & 1.00156562548728 & 0.992642718206451 \tabularnewline
48 & 58.72 & 59.0695076261407 & 59.33 & 0.99560943243116 & 0.994083112587415 \tabularnewline
49 & 59.02 & 59.2816707214289 & 60.0620833333333 & 0.987006567728041 & 0.995585975930765 \tabularnewline
50 & 59.54 & 60.19536228925 & 60.8554166666667 & 0.989153728401334 & 0.989112744498474 \tabularnewline
51 & 61.49 & 61.5401407976037 & 61.7433333333333 & 0.996709077324467 & 0.999185234272236 \tabularnewline
52 & 62.26 & 63.0760671079977 & 62.7816666666667 & 1.00468927406617 & 0.987062175157489 \tabularnewline
53 & 63.49 & 64.379378513846 & 63.9204166666667 & 1.00718020737525 & 0.986185351049098 \tabularnewline
54 & 64.36 & 65.2798553051889 & 65.1133333333333 & 1.00255741740333 & 0.985909048038043 \tabularnewline
55 & 65.93 & 66.6715640474552 & 66.3316666666666 & 1.00512420986641 & 0.988877356365491 \tabularnewline
56 & 66.82 & 67.8231701752179 & 67.5758333333333 & 1.00366013750307 & 0.985209034425459 \tabularnewline
57 & 68.85 & 69.0063931035735 & 68.8070833333333 & 1.00289664610945 & 0.997733643267823 \tabularnewline
58 & 71.27 & 70.318274915502 & 70.04875 & 1.00384767630403 & 1.01353453402606 \tabularnewline
59 & 72.27 & 71.4437626610609 & 71.3320833333333 & 1.00156562548728 & 1.0115648631618 \tabularnewline
60 & 73.4 & 72.2613326058536 & 72.58 & 0.99560943243116 & 1.01575763071458 \tabularnewline
61 & 73.58 & 72.7987256664644 & 73.7570833333333 & 0.987006567728041 & 1.01073197815461 \tabularnewline
62 & 74.84 & 74.1078094792148 & 74.9204166666667 & 0.989153728401334 & 1.0098800723693 \tabularnewline
63 & 75.74 & 75.9459093285333 & 76.1966666666667 & 0.996709077324467 & 0.997288737071505 \tabularnewline
64 & 77.81 & 77.8780704587084 & 77.5145833333333 & 1.00468927406617 & 0.999125935474422 \tabularnewline
65 & 78.74 & 79.396435405811 & 78.8304166666667 & 1.00718020737525 & 0.991732180387496 \tabularnewline
66 & 79.06 & 80.3691799016236 & 80.1641666666667 & 1.00255741740333 & 0.983710423532677 \tabularnewline
67 & 79.48 & NA & NA & 1.00512420986641 & NA \tabularnewline
68 & 81.19 & NA & NA & 1.00366013750307 & NA \tabularnewline
69 & 85.11 & NA & NA & 1.00289664610945 & NA \tabularnewline
70 & 86.64 & NA & NA & 1.00384767630403 & NA \tabularnewline
71 & 88.48 & NA & NA & 1.00156562548728 & NA \tabularnewline
72 & 89.2 & NA & NA & 0.99560943243116 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208754&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]33.7[/C][C]NA[/C][C]NA[/C][C]0.987006567728041[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]34.59[/C][C]NA[/C][C]NA[/C][C]0.989153728401334[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]35.1[/C][C]NA[/C][C]NA[/C][C]0.996709077324467[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]35.87[/C][C]NA[/C][C]NA[/C][C]1.00468927406617[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]37.15[/C][C]NA[/C][C]NA[/C][C]1.00718020737525[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]37.61[/C][C]NA[/C][C]NA[/C][C]1.00255741740333[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]37.97[/C][C]37.9208236277349[/C][C]37.7275[/C][C]1.00512420986641[/C][C]1.00129681709311[/C][/ROW]
[ROW][C]8[/C][C]38.94[/C][C]38.3992004774195[/C][C]38.2591666666667[/C][C]1.00366013750307[/C][C]1.01408361413406[/C][/ROW]
[ROW][C]9[/C][C]39.18[/C][C]38.8969285457525[/C][C]38.7845833333333[/C][C]1.00289664610945[/C][C]1.00727747575016[/C][/ROW]
[ROW][C]10[/C][C]39.49[/C][C]39.443266551311[/C][C]39.2920833333333[/C][C]1.00384767630403[/C][C]1.0011848270383[/C][/ROW]
[ROW][C]11[/C][C]39.86[/C][C]39.7959581717053[/C][C]39.73375[/C][C]1.00156562548728[/C][C]1.00160925458858[/C][/ROW]
[ROW][C]12[/C][C]40.02[/C][C]39.9380427074489[/C][C]40.1141666666667[/C][C]0.99560943243116[/C][C]1.00205211089465[/C][/ROW]
[ROW][C]13[/C][C]40.2[/C][C]39.9507358397386[/C][C]40.4766666666667[/C][C]0.987006567728041[/C][C]1.00623928833905[/C][/ROW]
[ROW][C]14[/C][C]40.85[/C][C]40.3677758034453[/C][C]40.8104166666667[/C][C]0.989153728401334[/C][C]1.01194577077773[/C][/ROW]
[ROW][C]15[/C][C]41.45[/C][C]40.9796937141955[/C][C]41.115[/C][C]0.996709077324467[/C][C]1.0114765690804[/C][/ROW]
[ROW][C]16[/C][C]41.7[/C][C]41.6100435265122[/C][C]41.4158333333333[/C][C]1.00468927406617[/C][C]1.00216189328018[/C][/ROW]
[ROW][C]17[/C][C]41.92[/C][C]42.0166206427574[/C][C]41.7170833333333[/C][C]1.00718020737525[/C][C]0.997700418518211[/C][/ROW]
[ROW][C]18[/C][C]41.97[/C][C]42.1245385534872[/C][C]42.0170833333333[/C][C]1.00255741740333[/C][C]0.996331388810562[/C][/ROW]
[ROW][C]19[/C][C]42.31[/C][C]42.5343437510217[/C][C]42.3175[/C][C]1.00512420986641[/C][C]0.994725585697645[/C][/ROW]
[ROW][C]20[/C][C]42.61[/C][C]42.7776678272767[/C][C]42.6216666666667[/C][C]1.00366013750307[/C][C]0.996080482275152[/C][/ROW]
[ROW][C]21[/C][C]42.82[/C][C]43.0869471584773[/C][C]42.9625[/C][C]1.00289664610945[/C][C]0.99380445410775[/C][/ROW]
[ROW][C]22[/C][C]43.07[/C][C]43.5904122640421[/C][C]43.4233333333333[/C][C]1.00384767630403[/C][C]0.988061313554693[/C][/ROW]
[ROW][C]23[/C][C]43.51[/C][C]44.078068539674[/C][C]44.0091666666667[/C][C]1.00156562548728[/C][C]0.98711221796929[/C][/ROW]
[ROW][C]24[/C][C]43.57[/C][C]44.478021719335[/C][C]44.6741666666667[/C][C]0.99560943243116[/C][C]0.979584934665826[/C][/ROW]
[ROW][C]25[/C][C]43.86[/C][C]44.7726741758267[/C][C]45.3620833333333[/C][C]0.987006567728041[/C][C]0.979615374944044[/C][/ROW]
[ROW][C]26[/C][C]44.49[/C][C]45.5323947078607[/C][C]46.0316666666667[/C][C]0.989153728401334[/C][C]0.977106525704418[/C][/ROW]
[ROW][C]27[/C][C]45.99[/C][C]46.5645869108036[/C][C]46.7183333333333[/C][C]0.996709077324467[/C][C]0.987660431479738[/C][/ROW]
[ROW][C]28[/C][C]48.22[/C][C]47.6612033001066[/C][C]47.43875[/C][C]1.00468927406617[/C][C]1.0117243514893[/C][/ROW]
[ROW][C]29[/C][C]49.46[/C][C]48.5242637576608[/C][C]48.1783333333333[/C][C]1.00718020737525[/C][C]1.01928388335807[/C][/ROW]
[ROW][C]30[/C][C]50.39[/C][C]49.058476291603[/C][C]48.9333333333333[/C][C]1.00255741740333[/C][C]1.02714156266253[/C][/ROW]
[ROW][C]31[/C][C]50.4[/C][C]49.9391775654583[/C][C]49.6845833333333[/C][C]1.00512420986641[/C][C]1.0092276736824[/C][/ROW]
[ROW][C]32[/C][C]50.59[/C][C]50.6179262680715[/C][C]50.4333333333333[/C][C]1.00366013750307[/C][C]0.999448292924456[/C][/ROW]
[ROW][C]33[/C][C]51.32[/C][C]51.2989991957035[/C][C]51.1508333333333[/C][C]1.00289664610945[/C][C]1.00040938038998[/C][/ROW]
[ROW][C]34[/C][C]51.86[/C][C]51.9625018844177[/C][C]51.7633333333333[/C][C]1.00384767630403[/C][C]0.998027387429387[/C][/ROW]
[ROW][C]35[/C][C]52.47[/C][C]52.3802129369423[/C][C]52.2983333333333[/C][C]1.00156562548728[/C][C]1.00171414085631[/C][/ROW]
[ROW][C]36[/C][C]52.73[/C][C]52.5636148224666[/C][C]52.7954166666667[/C][C]0.99560943243116[/C][C]1.00316540591996[/C][/ROW]
[ROW][C]37[/C][C]52.73[/C][C]52.6000475106466[/C][C]53.2925[/C][C]0.987006567728041[/C][C]1.00247057741397[/C][/ROW]
[ROW][C]38[/C][C]53.59[/C][C]53.2387265468808[/C][C]53.8225[/C][C]0.989153728401334[/C][C]1.00659808143251[/C][/ROW]
[ROW][C]39[/C][C]54.11[/C][C]54.1624171481582[/C][C]54.34125[/C][C]0.996709077324467[/C][C]0.999032222878554[/C][/ROW]
[ROW][C]40[/C][C]54.8[/C][C]55.0992528924432[/C][C]54.8420833333333[/C][C]1.00468927406617[/C][C]0.994568839381047[/C][/ROW]
[ROW][C]41[/C][C]55.72[/C][C]55.7344150672084[/C][C]55.3370833333333[/C][C]1.00718020737525[/C][C]0.999741361469551[/C][/ROW]
[ROW][C]42[/C][C]56.06[/C][C]55.9731983458852[/C][C]55.8304166666667[/C][C]1.00255741740333[/C][C]1.00155077173862[/C][/ROW]
[ROW][C]43[/C][C]56.66[/C][C]56.6307919926439[/C][C]56.3420833333333[/C][C]1.00512420986641[/C][C]1.00051576194378[/C][/ROW]
[ROW][C]44[/C][C]57.05[/C][C]57.0601697756693[/C][C]56.8520833333333[/C][C]1.00366013750307[/C][C]0.999821771023302[/C][/ROW]
[ROW][C]45[/C][C]57.31[/C][C]57.5737892115283[/C][C]57.4075[/C][C]1.00289664610945[/C][C]0.995418241266714[/C][/ROW]
[ROW][C]46[/C][C]57.89[/C][C]58.2490979572717[/C][C]58.0258333333333[/C][C]1.00384767630403[/C][C]0.993835132733985[/C][/ROW]
[ROW][C]47[/C][C]58.32[/C][C]58.7522569100945[/C][C]58.6604166666667[/C][C]1.00156562548728[/C][C]0.992642718206451[/C][/ROW]
[ROW][C]48[/C][C]58.72[/C][C]59.0695076261407[/C][C]59.33[/C][C]0.99560943243116[/C][C]0.994083112587415[/C][/ROW]
[ROW][C]49[/C][C]59.02[/C][C]59.2816707214289[/C][C]60.0620833333333[/C][C]0.987006567728041[/C][C]0.995585975930765[/C][/ROW]
[ROW][C]50[/C][C]59.54[/C][C]60.19536228925[/C][C]60.8554166666667[/C][C]0.989153728401334[/C][C]0.989112744498474[/C][/ROW]
[ROW][C]51[/C][C]61.49[/C][C]61.5401407976037[/C][C]61.7433333333333[/C][C]0.996709077324467[/C][C]0.999185234272236[/C][/ROW]
[ROW][C]52[/C][C]62.26[/C][C]63.0760671079977[/C][C]62.7816666666667[/C][C]1.00468927406617[/C][C]0.987062175157489[/C][/ROW]
[ROW][C]53[/C][C]63.49[/C][C]64.379378513846[/C][C]63.9204166666667[/C][C]1.00718020737525[/C][C]0.986185351049098[/C][/ROW]
[ROW][C]54[/C][C]64.36[/C][C]65.2798553051889[/C][C]65.1133333333333[/C][C]1.00255741740333[/C][C]0.985909048038043[/C][/ROW]
[ROW][C]55[/C][C]65.93[/C][C]66.6715640474552[/C][C]66.3316666666666[/C][C]1.00512420986641[/C][C]0.988877356365491[/C][/ROW]
[ROW][C]56[/C][C]66.82[/C][C]67.8231701752179[/C][C]67.5758333333333[/C][C]1.00366013750307[/C][C]0.985209034425459[/C][/ROW]
[ROW][C]57[/C][C]68.85[/C][C]69.0063931035735[/C][C]68.8070833333333[/C][C]1.00289664610945[/C][C]0.997733643267823[/C][/ROW]
[ROW][C]58[/C][C]71.27[/C][C]70.318274915502[/C][C]70.04875[/C][C]1.00384767630403[/C][C]1.01353453402606[/C][/ROW]
[ROW][C]59[/C][C]72.27[/C][C]71.4437626610609[/C][C]71.3320833333333[/C][C]1.00156562548728[/C][C]1.0115648631618[/C][/ROW]
[ROW][C]60[/C][C]73.4[/C][C]72.2613326058536[/C][C]72.58[/C][C]0.99560943243116[/C][C]1.01575763071458[/C][/ROW]
[ROW][C]61[/C][C]73.58[/C][C]72.7987256664644[/C][C]73.7570833333333[/C][C]0.987006567728041[/C][C]1.01073197815461[/C][/ROW]
[ROW][C]62[/C][C]74.84[/C][C]74.1078094792148[/C][C]74.9204166666667[/C][C]0.989153728401334[/C][C]1.0098800723693[/C][/ROW]
[ROW][C]63[/C][C]75.74[/C][C]75.9459093285333[/C][C]76.1966666666667[/C][C]0.996709077324467[/C][C]0.997288737071505[/C][/ROW]
[ROW][C]64[/C][C]77.81[/C][C]77.8780704587084[/C][C]77.5145833333333[/C][C]1.00468927406617[/C][C]0.999125935474422[/C][/ROW]
[ROW][C]65[/C][C]78.74[/C][C]79.396435405811[/C][C]78.8304166666667[/C][C]1.00718020737525[/C][C]0.991732180387496[/C][/ROW]
[ROW][C]66[/C][C]79.06[/C][C]80.3691799016236[/C][C]80.1641666666667[/C][C]1.00255741740333[/C][C]0.983710423532677[/C][/ROW]
[ROW][C]67[/C][C]79.48[/C][C]NA[/C][C]NA[/C][C]1.00512420986641[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]81.19[/C][C]NA[/C][C]NA[/C][C]1.00366013750307[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]85.11[/C][C]NA[/C][C]NA[/C][C]1.00289664610945[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]86.64[/C][C]NA[/C][C]NA[/C][C]1.00384767630403[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]88.48[/C][C]NA[/C][C]NA[/C][C]1.00156562548728[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]89.2[/C][C]NA[/C][C]NA[/C][C]0.99560943243116[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208754&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208754&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	33.7	NA	NA	0.987006567728041	NA
2	34.59	NA	NA	0.989153728401334	NA
3	35.1	NA	NA	0.996709077324467	NA
4	35.87	NA	NA	1.00468927406617	NA
5	37.15	NA	NA	1.00718020737525	NA
6	37.61	NA	NA	1.00255741740333	NA
7	37.97	37.9208236277349	37.7275	1.00512420986641	1.00129681709311
8	38.94	38.3992004774195	38.2591666666667	1.00366013750307	1.01408361413406
9	39.18	38.8969285457525	38.7845833333333	1.00289664610945	1.00727747575016
10	39.49	39.443266551311	39.2920833333333	1.00384767630403	1.0011848270383
11	39.86	39.7959581717053	39.73375	1.00156562548728	1.00160925458858
12	40.02	39.9380427074489	40.1141666666667	0.99560943243116	1.00205211089465
13	40.2	39.9507358397386	40.4766666666667	0.987006567728041	1.00623928833905
14	40.85	40.3677758034453	40.8104166666667	0.989153728401334	1.01194577077773
15	41.45	40.9796937141955	41.115	0.996709077324467	1.0114765690804
16	41.7	41.6100435265122	41.4158333333333	1.00468927406617	1.00216189328018
17	41.92	42.0166206427574	41.7170833333333	1.00718020737525	0.997700418518211
18	41.97	42.1245385534872	42.0170833333333	1.00255741740333	0.996331388810562
19	42.31	42.5343437510217	42.3175	1.00512420986641	0.994725585697645
20	42.61	42.7776678272767	42.6216666666667	1.00366013750307	0.996080482275152
21	42.82	43.0869471584773	42.9625	1.00289664610945	0.99380445410775
22	43.07	43.5904122640421	43.4233333333333	1.00384767630403	0.988061313554693
23	43.51	44.078068539674	44.0091666666667	1.00156562548728	0.98711221796929
24	43.57	44.478021719335	44.6741666666667	0.99560943243116	0.979584934665826
25	43.86	44.7726741758267	45.3620833333333	0.987006567728041	0.979615374944044
26	44.49	45.5323947078607	46.0316666666667	0.989153728401334	0.977106525704418
27	45.99	46.5645869108036	46.7183333333333	0.996709077324467	0.987660431479738
28	48.22	47.6612033001066	47.43875	1.00468927406617	1.0117243514893
29	49.46	48.5242637576608	48.1783333333333	1.00718020737525	1.01928388335807
30	50.39	49.058476291603	48.9333333333333	1.00255741740333	1.02714156266253
31	50.4	49.9391775654583	49.6845833333333	1.00512420986641	1.0092276736824
32	50.59	50.6179262680715	50.4333333333333	1.00366013750307	0.999448292924456
33	51.32	51.2989991957035	51.1508333333333	1.00289664610945	1.00040938038998
34	51.86	51.9625018844177	51.7633333333333	1.00384767630403	0.998027387429387
35	52.47	52.3802129369423	52.2983333333333	1.00156562548728	1.00171414085631
36	52.73	52.5636148224666	52.7954166666667	0.99560943243116	1.00316540591996
37	52.73	52.6000475106466	53.2925	0.987006567728041	1.00247057741397
38	53.59	53.2387265468808	53.8225	0.989153728401334	1.00659808143251
39	54.11	54.1624171481582	54.34125	0.996709077324467	0.999032222878554
40	54.8	55.0992528924432	54.8420833333333	1.00468927406617	0.994568839381047
41	55.72	55.7344150672084	55.3370833333333	1.00718020737525	0.999741361469551
42	56.06	55.9731983458852	55.8304166666667	1.00255741740333	1.00155077173862
43	56.66	56.6307919926439	56.3420833333333	1.00512420986641	1.00051576194378
44	57.05	57.0601697756693	56.8520833333333	1.00366013750307	0.999821771023302
45	57.31	57.5737892115283	57.4075	1.00289664610945	0.995418241266714
46	57.89	58.2490979572717	58.0258333333333	1.00384767630403	0.993835132733985
47	58.32	58.7522569100945	58.6604166666667	1.00156562548728	0.992642718206451
48	58.72	59.0695076261407	59.33	0.99560943243116	0.994083112587415
49	59.02	59.2816707214289	60.0620833333333	0.987006567728041	0.995585975930765
50	59.54	60.19536228925	60.8554166666667	0.989153728401334	0.989112744498474
51	61.49	61.5401407976037	61.7433333333333	0.996709077324467	0.999185234272236
52	62.26	63.0760671079977	62.7816666666667	1.00468927406617	0.987062175157489
53	63.49	64.379378513846	63.9204166666667	1.00718020737525	0.986185351049098
54	64.36	65.2798553051889	65.1133333333333	1.00255741740333	0.985909048038043
55	65.93	66.6715640474552	66.3316666666666	1.00512420986641	0.988877356365491
56	66.82	67.8231701752179	67.5758333333333	1.00366013750307	0.985209034425459
57	68.85	69.0063931035735	68.8070833333333	1.00289664610945	0.997733643267823
58	71.27	70.318274915502	70.04875	1.00384767630403	1.01353453402606
59	72.27	71.4437626610609	71.3320833333333	1.00156562548728	1.0115648631618
60	73.4	72.2613326058536	72.58	0.99560943243116	1.01575763071458
61	73.58	72.7987256664644	73.7570833333333	0.987006567728041	1.01073197815461
62	74.84	74.1078094792148	74.9204166666667	0.989153728401334	1.0098800723693
63	75.74	75.9459093285333	76.1966666666667	0.996709077324467	0.997288737071505
64	77.81	77.8780704587084	77.5145833333333	1.00468927406617	0.999125935474422
65	78.74	79.396435405811	78.8304166666667	1.00718020737525	0.991732180387496
66	79.06	80.3691799016236	80.1641666666667	1.00255741740333	0.983710423532677
67	79.48	NA	NA	1.00512420986641	NA
68	81.19	NA	NA	1.00366013750307	NA
69	85.11	NA	NA	1.00289664610945	NA
70	86.64	NA	NA	1.00384767630403	NA
71	88.48	NA	NA	1.00156562548728	NA
72	89.2	NA	NA	0.99560943243116	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
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