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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 13 Dec 2012 09:25:01 -0500

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/13/t1355408718kbw3r5pst5ianfz.htm/, Retrieved Mon, 29 Apr 2024 01:19:00 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199250, Retrieved Mon, 29 Apr 2024 01:19:00 +0000

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Estimated Impact

147

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-       [Classical Decomposition] [Eigenreeks multip...] [2012-12-13 14:25:01] [56be9a844975c6d0d36e88eaea5fb75b] [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	'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199250&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199250&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199250&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	45.3	NA	NA	1.0144221989448	NA
2	49.9	NA	NA	1.03874577251358	NA
3	53.8	NA	NA	0.985353334328181	NA
4	55.1	NA	NA	0.990547560539078	NA
5	52.9	NA	NA	0.991061310368471	NA
6	53.5	NA	NA	1.05921569883422	NA
7	53.8	55.811997997833	50.975	1.09488961251266	0.963950439511034
8	52	53.275344152793	51.4708333333333	1.03505890040236	0.976061268621085
9	48.2	50.2139371066659	51.7125	0.971021263846572	0.959892865950985
10	45.5	47.5680162012548	51.7416666666667	0.919336760211077	0.956525069439405
11	45.7	48.627012291859	51.8166666666667	0.938443466552441	0.939806865486798
12	52.5	50.3516727977148	52.3458333333333	0.961904120946553	1.04266645143878
13	52.3	54.085610240407	53.3166666666667	1.0144221989448	0.966985484078481
14	54.8	56.6679099980014	54.5541666666667	1.03874577251358	0.96703760562076
15	54.7	55.282427694704	56.1041666666667	0.985353334328181	0.989464505829584
16	54.9	57.7159045274103	58.2666666666667	0.990547560539078	0.95121094349179
17	54.9	60.8718115672568	61.4208333333333	0.991061310368471	0.901895287596976
18	64.2	68.7828194430474	64.9375	1.05921569883422	0.933372614263916
19	66.4	74.9451939764917	68.45	1.09488961251266	0.885980761098943
20	69.1	76.0380144708082	73.4625	1.03505890040236	0.908755975296123
21	68.3	77.2852007583218	79.5916666666667	0.971021263846572	0.883739698284289
22	77.3	78.5994624282129	85.4958333333333	0.919336760211077	0.983467286059371
23	89.6	86.2742360250544	91.9333333333333	0.938443466552441	1.03854875021994
24	93	95.7335076372056	99.525	0.961904120946553	0.971446699231322
25	96.1	110.0436747897	108.479166666667	1.0144221989448	0.873289629627992
26	131.3	121.840551008458	117.295833333333	1.03874577251358	1.07763793673984
27	125.3	122.803764929543	124.629166666667	0.985353334328181	1.02032702394662
28	126	128.094308703712	129.316666666667	0.990547560539078	0.983650259524363
29	138.3	129.643207662576	130.8125	0.991061310368471	1.06677397523174
30	163	138.165861115434	130.441666666667	1.05921569883422	1.1797414982549
31	182.5	141.683277899191	129.404166666667	1.09488961251266	1.28808425882023
32	164.6	131.012580318428	126.575	1.03505890040236	1.25636789688392
33	148.8	118.104507137272	121.629166666667	0.971021263846572	1.25990111306295
34	109.3	107.041443447243	116.433333333333	0.919336760211077	1.02109983273787
35	93.5	103.971715731789	110.791666666667	0.938443466552441	0.899283034255176
36	80.2	99.9338222986723	103.891666666667	0.961904120946553	0.802531096632191
37	84	96.9026805542022	95.525	1.0144221989448	0.866849085284229
38	75.5	90.5353502893297	87.1583333333333	1.03874577251358	0.833928402096195
39	62.4	78.7913159962172	79.9625	0.985353334328181	0.791965449631478
40	64.2	74.3488489814623	75.0583333333333	0.990547560539078	0.863496891740816
41	64.7	72.2401106816085	72.8916666666667	0.991061310368471	0.89562431991777
42	71	76.6210156144206	72.3375	1.05921569883422	0.926638722165898
43	73.7	79.9086935532158	72.9833333333333	1.09488961251266	0.92230265222543
44	72.6	76.8962508090584	74.2916666666667	1.03505890040236	0.944129255147608
45	68.1	74.1374734946858	76.35	0.971021263846572	0.918563808421141
46	72.3	72.82296311822	79.2125	0.919336760211077	0.992818705861076
47	78.5	77.1987056672702	82.2625	0.938443466552441	1.01685642682066
48	81.9	81.733794743596	84.9708333333333	0.961904120946553	1.00203349492001
49	97.8	88.3984411197149	87.1416666666667	1.0144221989448	1.10635435151569
50	93.1	92.3574834986139	88.9125	1.03874577251358	1.00803959217227
51	94.2	89.4988222292501	90.8291666666667	0.985353334328181	1.05252781716734
52	101.1	92.1787050711657	93.0583333333333	0.990547560539078	1.09678260203316
53	101	94.5844138082909	95.4375	0.991061310368471	1.06782921131924
54	99.7	104.200344372817	98.375	1.05921569883422	0.956810657393655
55	97.1	111.071989149357	101.445833333333	1.09488961251266	0.874207806519343
56	91.7	107.982519784476	104.325	1.03505890040236	0.849211522226241
57	95	104.117755015949	107.225	0.971021263846572	0.912428432455617
58	98.9	100.855073164989	109.704166666667	0.919336760211077	0.980615024077261
59	109	104.804584308354	111.679166666667	0.938443466552441	1.04003084139241
60	121.9	109.244252602667	113.570833333333	0.961904120946553	1.11584817595268
61	131.5	117.301020271317	115.633333333333	1.0144221989448	1.12104736766859
62	128.5	122.628266552614	118.054166666667	1.03874577251358	1.04788238154591
63	128.4	118.86235159223	120.629166666667	0.985353334328181	1.08024112159997
64	126.4	121.610349463683	122.770833333333	0.990547560539078	1.03938522138486
65	123.1	122.804884621033	123.9125	0.991061310368471	1.00240312410925
66	123	131.135316914422	123.804166666667	1.05921569883422	0.937962426096618
67	123.3	NA	NA	1.09488961251266	NA
68	123.6	NA	NA	1.03505890040236	NA
69	124.9	NA	NA	0.971021263846572	NA
70	120.4	NA	NA	0.919336760211077	NA
71	114.9	NA	NA	0.938443466552441	NA
72	113.4	NA	NA	0.961904120946553	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 45.3 & NA & NA & 1.0144221989448 & NA \tabularnewline
2 & 49.9 & NA & NA & 1.03874577251358 & NA \tabularnewline
3 & 53.8 & NA & NA & 0.985353334328181 & NA \tabularnewline
4 & 55.1 & NA & NA & 0.990547560539078 & NA \tabularnewline
5 & 52.9 & NA & NA & 0.991061310368471 & NA \tabularnewline
6 & 53.5 & NA & NA & 1.05921569883422 & NA \tabularnewline
7 & 53.8 & 55.811997997833 & 50.975 & 1.09488961251266 & 0.963950439511034 \tabularnewline
8 & 52 & 53.275344152793 & 51.4708333333333 & 1.03505890040236 & 0.976061268621085 \tabularnewline
9 & 48.2 & 50.2139371066659 & 51.7125 & 0.971021263846572 & 0.959892865950985 \tabularnewline
10 & 45.5 & 47.5680162012548 & 51.7416666666667 & 0.919336760211077 & 0.956525069439405 \tabularnewline
11 & 45.7 & 48.627012291859 & 51.8166666666667 & 0.938443466552441 & 0.939806865486798 \tabularnewline
12 & 52.5 & 50.3516727977148 & 52.3458333333333 & 0.961904120946553 & 1.04266645143878 \tabularnewline
13 & 52.3 & 54.085610240407 & 53.3166666666667 & 1.0144221989448 & 0.966985484078481 \tabularnewline
14 & 54.8 & 56.6679099980014 & 54.5541666666667 & 1.03874577251358 & 0.96703760562076 \tabularnewline
15 & 54.7 & 55.282427694704 & 56.1041666666667 & 0.985353334328181 & 0.989464505829584 \tabularnewline
16 & 54.9 & 57.7159045274103 & 58.2666666666667 & 0.990547560539078 & 0.95121094349179 \tabularnewline
17 & 54.9 & 60.8718115672568 & 61.4208333333333 & 0.991061310368471 & 0.901895287596976 \tabularnewline
18 & 64.2 & 68.7828194430474 & 64.9375 & 1.05921569883422 & 0.933372614263916 \tabularnewline
19 & 66.4 & 74.9451939764917 & 68.45 & 1.09488961251266 & 0.885980761098943 \tabularnewline
20 & 69.1 & 76.0380144708082 & 73.4625 & 1.03505890040236 & 0.908755975296123 \tabularnewline
21 & 68.3 & 77.2852007583218 & 79.5916666666667 & 0.971021263846572 & 0.883739698284289 \tabularnewline
22 & 77.3 & 78.5994624282129 & 85.4958333333333 & 0.919336760211077 & 0.983467286059371 \tabularnewline
23 & 89.6 & 86.2742360250544 & 91.9333333333333 & 0.938443466552441 & 1.03854875021994 \tabularnewline
24 & 93 & 95.7335076372056 & 99.525 & 0.961904120946553 & 0.971446699231322 \tabularnewline
25 & 96.1 & 110.0436747897 & 108.479166666667 & 1.0144221989448 & 0.873289629627992 \tabularnewline
26 & 131.3 & 121.840551008458 & 117.295833333333 & 1.03874577251358 & 1.07763793673984 \tabularnewline
27 & 125.3 & 122.803764929543 & 124.629166666667 & 0.985353334328181 & 1.02032702394662 \tabularnewline
28 & 126 & 128.094308703712 & 129.316666666667 & 0.990547560539078 & 0.983650259524363 \tabularnewline
29 & 138.3 & 129.643207662576 & 130.8125 & 0.991061310368471 & 1.06677397523174 \tabularnewline
30 & 163 & 138.165861115434 & 130.441666666667 & 1.05921569883422 & 1.1797414982549 \tabularnewline
31 & 182.5 & 141.683277899191 & 129.404166666667 & 1.09488961251266 & 1.28808425882023 \tabularnewline
32 & 164.6 & 131.012580318428 & 126.575 & 1.03505890040236 & 1.25636789688392 \tabularnewline
33 & 148.8 & 118.104507137272 & 121.629166666667 & 0.971021263846572 & 1.25990111306295 \tabularnewline
34 & 109.3 & 107.041443447243 & 116.433333333333 & 0.919336760211077 & 1.02109983273787 \tabularnewline
35 & 93.5 & 103.971715731789 & 110.791666666667 & 0.938443466552441 & 0.899283034255176 \tabularnewline
36 & 80.2 & 99.9338222986723 & 103.891666666667 & 0.961904120946553 & 0.802531096632191 \tabularnewline
37 & 84 & 96.9026805542022 & 95.525 & 1.0144221989448 & 0.866849085284229 \tabularnewline
38 & 75.5 & 90.5353502893297 & 87.1583333333333 & 1.03874577251358 & 0.833928402096195 \tabularnewline
39 & 62.4 & 78.7913159962172 & 79.9625 & 0.985353334328181 & 0.791965449631478 \tabularnewline
40 & 64.2 & 74.3488489814623 & 75.0583333333333 & 0.990547560539078 & 0.863496891740816 \tabularnewline
41 & 64.7 & 72.2401106816085 & 72.8916666666667 & 0.991061310368471 & 0.89562431991777 \tabularnewline
42 & 71 & 76.6210156144206 & 72.3375 & 1.05921569883422 & 0.926638722165898 \tabularnewline
43 & 73.7 & 79.9086935532158 & 72.9833333333333 & 1.09488961251266 & 0.92230265222543 \tabularnewline
44 & 72.6 & 76.8962508090584 & 74.2916666666667 & 1.03505890040236 & 0.944129255147608 \tabularnewline
45 & 68.1 & 74.1374734946858 & 76.35 & 0.971021263846572 & 0.918563808421141 \tabularnewline
46 & 72.3 & 72.82296311822 & 79.2125 & 0.919336760211077 & 0.992818705861076 \tabularnewline
47 & 78.5 & 77.1987056672702 & 82.2625 & 0.938443466552441 & 1.01685642682066 \tabularnewline
48 & 81.9 & 81.733794743596 & 84.9708333333333 & 0.961904120946553 & 1.00203349492001 \tabularnewline
49 & 97.8 & 88.3984411197149 & 87.1416666666667 & 1.0144221989448 & 1.10635435151569 \tabularnewline
50 & 93.1 & 92.3574834986139 & 88.9125 & 1.03874577251358 & 1.00803959217227 \tabularnewline
51 & 94.2 & 89.4988222292501 & 90.8291666666667 & 0.985353334328181 & 1.05252781716734 \tabularnewline
52 & 101.1 & 92.1787050711657 & 93.0583333333333 & 0.990547560539078 & 1.09678260203316 \tabularnewline
53 & 101 & 94.5844138082909 & 95.4375 & 0.991061310368471 & 1.06782921131924 \tabularnewline
54 & 99.7 & 104.200344372817 & 98.375 & 1.05921569883422 & 0.956810657393655 \tabularnewline
55 & 97.1 & 111.071989149357 & 101.445833333333 & 1.09488961251266 & 0.874207806519343 \tabularnewline
56 & 91.7 & 107.982519784476 & 104.325 & 1.03505890040236 & 0.849211522226241 \tabularnewline
57 & 95 & 104.117755015949 & 107.225 & 0.971021263846572 & 0.912428432455617 \tabularnewline
58 & 98.9 & 100.855073164989 & 109.704166666667 & 0.919336760211077 & 0.980615024077261 \tabularnewline
59 & 109 & 104.804584308354 & 111.679166666667 & 0.938443466552441 & 1.04003084139241 \tabularnewline
60 & 121.9 & 109.244252602667 & 113.570833333333 & 0.961904120946553 & 1.11584817595268 \tabularnewline
61 & 131.5 & 117.301020271317 & 115.633333333333 & 1.0144221989448 & 1.12104736766859 \tabularnewline
62 & 128.5 & 122.628266552614 & 118.054166666667 & 1.03874577251358 & 1.04788238154591 \tabularnewline
63 & 128.4 & 118.86235159223 & 120.629166666667 & 0.985353334328181 & 1.08024112159997 \tabularnewline
64 & 126.4 & 121.610349463683 & 122.770833333333 & 0.990547560539078 & 1.03938522138486 \tabularnewline
65 & 123.1 & 122.804884621033 & 123.9125 & 0.991061310368471 & 1.00240312410925 \tabularnewline
66 & 123 & 131.135316914422 & 123.804166666667 & 1.05921569883422 & 0.937962426096618 \tabularnewline
67 & 123.3 & NA & NA & 1.09488961251266 & NA \tabularnewline
68 & 123.6 & NA & NA & 1.03505890040236 & NA \tabularnewline
69 & 124.9 & NA & NA & 0.971021263846572 & NA \tabularnewline
70 & 120.4 & NA & NA & 0.919336760211077 & NA \tabularnewline
71 & 114.9 & NA & NA & 0.938443466552441 & NA \tabularnewline
72 & 113.4 & NA & NA & 0.961904120946553 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199250&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]45.3[/C][C]NA[/C][C]NA[/C][C]1.0144221989448[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]49.9[/C][C]NA[/C][C]NA[/C][C]1.03874577251358[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]53.8[/C][C]NA[/C][C]NA[/C][C]0.985353334328181[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]55.1[/C][C]NA[/C][C]NA[/C][C]0.990547560539078[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]52.9[/C][C]NA[/C][C]NA[/C][C]0.991061310368471[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]53.5[/C][C]NA[/C][C]NA[/C][C]1.05921569883422[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]53.8[/C][C]55.811997997833[/C][C]50.975[/C][C]1.09488961251266[/C][C]0.963950439511034[/C][/ROW]
[ROW][C]8[/C][C]52[/C][C]53.275344152793[/C][C]51.4708333333333[/C][C]1.03505890040236[/C][C]0.976061268621085[/C][/ROW]
[ROW][C]9[/C][C]48.2[/C][C]50.2139371066659[/C][C]51.7125[/C][C]0.971021263846572[/C][C]0.959892865950985[/C][/ROW]
[ROW][C]10[/C][C]45.5[/C][C]47.5680162012548[/C][C]51.7416666666667[/C][C]0.919336760211077[/C][C]0.956525069439405[/C][/ROW]
[ROW][C]11[/C][C]45.7[/C][C]48.627012291859[/C][C]51.8166666666667[/C][C]0.938443466552441[/C][C]0.939806865486798[/C][/ROW]
[ROW][C]12[/C][C]52.5[/C][C]50.3516727977148[/C][C]52.3458333333333[/C][C]0.961904120946553[/C][C]1.04266645143878[/C][/ROW]
[ROW][C]13[/C][C]52.3[/C][C]54.085610240407[/C][C]53.3166666666667[/C][C]1.0144221989448[/C][C]0.966985484078481[/C][/ROW]
[ROW][C]14[/C][C]54.8[/C][C]56.6679099980014[/C][C]54.5541666666667[/C][C]1.03874577251358[/C][C]0.96703760562076[/C][/ROW]
[ROW][C]15[/C][C]54.7[/C][C]55.282427694704[/C][C]56.1041666666667[/C][C]0.985353334328181[/C][C]0.989464505829584[/C][/ROW]
[ROW][C]16[/C][C]54.9[/C][C]57.7159045274103[/C][C]58.2666666666667[/C][C]0.990547560539078[/C][C]0.95121094349179[/C][/ROW]
[ROW][C]17[/C][C]54.9[/C][C]60.8718115672568[/C][C]61.4208333333333[/C][C]0.991061310368471[/C][C]0.901895287596976[/C][/ROW]
[ROW][C]18[/C][C]64.2[/C][C]68.7828194430474[/C][C]64.9375[/C][C]1.05921569883422[/C][C]0.933372614263916[/C][/ROW]
[ROW][C]19[/C][C]66.4[/C][C]74.9451939764917[/C][C]68.45[/C][C]1.09488961251266[/C][C]0.885980761098943[/C][/ROW]
[ROW][C]20[/C][C]69.1[/C][C]76.0380144708082[/C][C]73.4625[/C][C]1.03505890040236[/C][C]0.908755975296123[/C][/ROW]
[ROW][C]21[/C][C]68.3[/C][C]77.2852007583218[/C][C]79.5916666666667[/C][C]0.971021263846572[/C][C]0.883739698284289[/C][/ROW]
[ROW][C]22[/C][C]77.3[/C][C]78.5994624282129[/C][C]85.4958333333333[/C][C]0.919336760211077[/C][C]0.983467286059371[/C][/ROW]
[ROW][C]23[/C][C]89.6[/C][C]86.2742360250544[/C][C]91.9333333333333[/C][C]0.938443466552441[/C][C]1.03854875021994[/C][/ROW]
[ROW][C]24[/C][C]93[/C][C]95.7335076372056[/C][C]99.525[/C][C]0.961904120946553[/C][C]0.971446699231322[/C][/ROW]
[ROW][C]25[/C][C]96.1[/C][C]110.0436747897[/C][C]108.479166666667[/C][C]1.0144221989448[/C][C]0.873289629627992[/C][/ROW]
[ROW][C]26[/C][C]131.3[/C][C]121.840551008458[/C][C]117.295833333333[/C][C]1.03874577251358[/C][C]1.07763793673984[/C][/ROW]
[ROW][C]27[/C][C]125.3[/C][C]122.803764929543[/C][C]124.629166666667[/C][C]0.985353334328181[/C][C]1.02032702394662[/C][/ROW]
[ROW][C]28[/C][C]126[/C][C]128.094308703712[/C][C]129.316666666667[/C][C]0.990547560539078[/C][C]0.983650259524363[/C][/ROW]
[ROW][C]29[/C][C]138.3[/C][C]129.643207662576[/C][C]130.8125[/C][C]0.991061310368471[/C][C]1.06677397523174[/C][/ROW]
[ROW][C]30[/C][C]163[/C][C]138.165861115434[/C][C]130.441666666667[/C][C]1.05921569883422[/C][C]1.1797414982549[/C][/ROW]
[ROW][C]31[/C][C]182.5[/C][C]141.683277899191[/C][C]129.404166666667[/C][C]1.09488961251266[/C][C]1.28808425882023[/C][/ROW]
[ROW][C]32[/C][C]164.6[/C][C]131.012580318428[/C][C]126.575[/C][C]1.03505890040236[/C][C]1.25636789688392[/C][/ROW]
[ROW][C]33[/C][C]148.8[/C][C]118.104507137272[/C][C]121.629166666667[/C][C]0.971021263846572[/C][C]1.25990111306295[/C][/ROW]
[ROW][C]34[/C][C]109.3[/C][C]107.041443447243[/C][C]116.433333333333[/C][C]0.919336760211077[/C][C]1.02109983273787[/C][/ROW]
[ROW][C]35[/C][C]93.5[/C][C]103.971715731789[/C][C]110.791666666667[/C][C]0.938443466552441[/C][C]0.899283034255176[/C][/ROW]
[ROW][C]36[/C][C]80.2[/C][C]99.9338222986723[/C][C]103.891666666667[/C][C]0.961904120946553[/C][C]0.802531096632191[/C][/ROW]
[ROW][C]37[/C][C]84[/C][C]96.9026805542022[/C][C]95.525[/C][C]1.0144221989448[/C][C]0.866849085284229[/C][/ROW]
[ROW][C]38[/C][C]75.5[/C][C]90.5353502893297[/C][C]87.1583333333333[/C][C]1.03874577251358[/C][C]0.833928402096195[/C][/ROW]
[ROW][C]39[/C][C]62.4[/C][C]78.7913159962172[/C][C]79.9625[/C][C]0.985353334328181[/C][C]0.791965449631478[/C][/ROW]
[ROW][C]40[/C][C]64.2[/C][C]74.3488489814623[/C][C]75.0583333333333[/C][C]0.990547560539078[/C][C]0.863496891740816[/C][/ROW]
[ROW][C]41[/C][C]64.7[/C][C]72.2401106816085[/C][C]72.8916666666667[/C][C]0.991061310368471[/C][C]0.89562431991777[/C][/ROW]
[ROW][C]42[/C][C]71[/C][C]76.6210156144206[/C][C]72.3375[/C][C]1.05921569883422[/C][C]0.926638722165898[/C][/ROW]
[ROW][C]43[/C][C]73.7[/C][C]79.9086935532158[/C][C]72.9833333333333[/C][C]1.09488961251266[/C][C]0.92230265222543[/C][/ROW]
[ROW][C]44[/C][C]72.6[/C][C]76.8962508090584[/C][C]74.2916666666667[/C][C]1.03505890040236[/C][C]0.944129255147608[/C][/ROW]
[ROW][C]45[/C][C]68.1[/C][C]74.1374734946858[/C][C]76.35[/C][C]0.971021263846572[/C][C]0.918563808421141[/C][/ROW]
[ROW][C]46[/C][C]72.3[/C][C]72.82296311822[/C][C]79.2125[/C][C]0.919336760211077[/C][C]0.992818705861076[/C][/ROW]
[ROW][C]47[/C][C]78.5[/C][C]77.1987056672702[/C][C]82.2625[/C][C]0.938443466552441[/C][C]1.01685642682066[/C][/ROW]
[ROW][C]48[/C][C]81.9[/C][C]81.733794743596[/C][C]84.9708333333333[/C][C]0.961904120946553[/C][C]1.00203349492001[/C][/ROW]
[ROW][C]49[/C][C]97.8[/C][C]88.3984411197149[/C][C]87.1416666666667[/C][C]1.0144221989448[/C][C]1.10635435151569[/C][/ROW]
[ROW][C]50[/C][C]93.1[/C][C]92.3574834986139[/C][C]88.9125[/C][C]1.03874577251358[/C][C]1.00803959217227[/C][/ROW]
[ROW][C]51[/C][C]94.2[/C][C]89.4988222292501[/C][C]90.8291666666667[/C][C]0.985353334328181[/C][C]1.05252781716734[/C][/ROW]
[ROW][C]52[/C][C]101.1[/C][C]92.1787050711657[/C][C]93.0583333333333[/C][C]0.990547560539078[/C][C]1.09678260203316[/C][/ROW]
[ROW][C]53[/C][C]101[/C][C]94.5844138082909[/C][C]95.4375[/C][C]0.991061310368471[/C][C]1.06782921131924[/C][/ROW]
[ROW][C]54[/C][C]99.7[/C][C]104.200344372817[/C][C]98.375[/C][C]1.05921569883422[/C][C]0.956810657393655[/C][/ROW]
[ROW][C]55[/C][C]97.1[/C][C]111.071989149357[/C][C]101.445833333333[/C][C]1.09488961251266[/C][C]0.874207806519343[/C][/ROW]
[ROW][C]56[/C][C]91.7[/C][C]107.982519784476[/C][C]104.325[/C][C]1.03505890040236[/C][C]0.849211522226241[/C][/ROW]
[ROW][C]57[/C][C]95[/C][C]104.117755015949[/C][C]107.225[/C][C]0.971021263846572[/C][C]0.912428432455617[/C][/ROW]
[ROW][C]58[/C][C]98.9[/C][C]100.855073164989[/C][C]109.704166666667[/C][C]0.919336760211077[/C][C]0.980615024077261[/C][/ROW]
[ROW][C]59[/C][C]109[/C][C]104.804584308354[/C][C]111.679166666667[/C][C]0.938443466552441[/C][C]1.04003084139241[/C][/ROW]
[ROW][C]60[/C][C]121.9[/C][C]109.244252602667[/C][C]113.570833333333[/C][C]0.961904120946553[/C][C]1.11584817595268[/C][/ROW]
[ROW][C]61[/C][C]131.5[/C][C]117.301020271317[/C][C]115.633333333333[/C][C]1.0144221989448[/C][C]1.12104736766859[/C][/ROW]
[ROW][C]62[/C][C]128.5[/C][C]122.628266552614[/C][C]118.054166666667[/C][C]1.03874577251358[/C][C]1.04788238154591[/C][/ROW]
[ROW][C]63[/C][C]128.4[/C][C]118.86235159223[/C][C]120.629166666667[/C][C]0.985353334328181[/C][C]1.08024112159997[/C][/ROW]
[ROW][C]64[/C][C]126.4[/C][C]121.610349463683[/C][C]122.770833333333[/C][C]0.990547560539078[/C][C]1.03938522138486[/C][/ROW]
[ROW][C]65[/C][C]123.1[/C][C]122.804884621033[/C][C]123.9125[/C][C]0.991061310368471[/C][C]1.00240312410925[/C][/ROW]
[ROW][C]66[/C][C]123[/C][C]131.135316914422[/C][C]123.804166666667[/C][C]1.05921569883422[/C][C]0.937962426096618[/C][/ROW]
[ROW][C]67[/C][C]123.3[/C][C]NA[/C][C]NA[/C][C]1.09488961251266[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]123.6[/C][C]NA[/C][C]NA[/C][C]1.03505890040236[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]124.9[/C][C]NA[/C][C]NA[/C][C]0.971021263846572[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]120.4[/C][C]NA[/C][C]NA[/C][C]0.919336760211077[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]114.9[/C][C]NA[/C][C]NA[/C][C]0.938443466552441[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]113.4[/C][C]NA[/C][C]NA[/C][C]0.961904120946553[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199250&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199250&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	45.3	NA	NA	1.0144221989448	NA
2	49.9	NA	NA	1.03874577251358	NA
3	53.8	NA	NA	0.985353334328181	NA
4	55.1	NA	NA	0.990547560539078	NA
5	52.9	NA	NA	0.991061310368471	NA
6	53.5	NA	NA	1.05921569883422	NA
7	53.8	55.811997997833	50.975	1.09488961251266	0.963950439511034
8	52	53.275344152793	51.4708333333333	1.03505890040236	0.976061268621085
9	48.2	50.2139371066659	51.7125	0.971021263846572	0.959892865950985
10	45.5	47.5680162012548	51.7416666666667	0.919336760211077	0.956525069439405
11	45.7	48.627012291859	51.8166666666667	0.938443466552441	0.939806865486798
12	52.5	50.3516727977148	52.3458333333333	0.961904120946553	1.04266645143878
13	52.3	54.085610240407	53.3166666666667	1.0144221989448	0.966985484078481
14	54.8	56.6679099980014	54.5541666666667	1.03874577251358	0.96703760562076
15	54.7	55.282427694704	56.1041666666667	0.985353334328181	0.989464505829584
16	54.9	57.7159045274103	58.2666666666667	0.990547560539078	0.95121094349179
17	54.9	60.8718115672568	61.4208333333333	0.991061310368471	0.901895287596976
18	64.2	68.7828194430474	64.9375	1.05921569883422	0.933372614263916
19	66.4	74.9451939764917	68.45	1.09488961251266	0.885980761098943
20	69.1	76.0380144708082	73.4625	1.03505890040236	0.908755975296123
21	68.3	77.2852007583218	79.5916666666667	0.971021263846572	0.883739698284289
22	77.3	78.5994624282129	85.4958333333333	0.919336760211077	0.983467286059371
23	89.6	86.2742360250544	91.9333333333333	0.938443466552441	1.03854875021994
24	93	95.7335076372056	99.525	0.961904120946553	0.971446699231322
25	96.1	110.0436747897	108.479166666667	1.0144221989448	0.873289629627992
26	131.3	121.840551008458	117.295833333333	1.03874577251358	1.07763793673984
27	125.3	122.803764929543	124.629166666667	0.985353334328181	1.02032702394662
28	126	128.094308703712	129.316666666667	0.990547560539078	0.983650259524363
29	138.3	129.643207662576	130.8125	0.991061310368471	1.06677397523174
30	163	138.165861115434	130.441666666667	1.05921569883422	1.1797414982549
31	182.5	141.683277899191	129.404166666667	1.09488961251266	1.28808425882023
32	164.6	131.012580318428	126.575	1.03505890040236	1.25636789688392
33	148.8	118.104507137272	121.629166666667	0.971021263846572	1.25990111306295
34	109.3	107.041443447243	116.433333333333	0.919336760211077	1.02109983273787
35	93.5	103.971715731789	110.791666666667	0.938443466552441	0.899283034255176
36	80.2	99.9338222986723	103.891666666667	0.961904120946553	0.802531096632191
37	84	96.9026805542022	95.525	1.0144221989448	0.866849085284229
38	75.5	90.5353502893297	87.1583333333333	1.03874577251358	0.833928402096195
39	62.4	78.7913159962172	79.9625	0.985353334328181	0.791965449631478
40	64.2	74.3488489814623	75.0583333333333	0.990547560539078	0.863496891740816
41	64.7	72.2401106816085	72.8916666666667	0.991061310368471	0.89562431991777
42	71	76.6210156144206	72.3375	1.05921569883422	0.926638722165898
43	73.7	79.9086935532158	72.9833333333333	1.09488961251266	0.92230265222543
44	72.6	76.8962508090584	74.2916666666667	1.03505890040236	0.944129255147608
45	68.1	74.1374734946858	76.35	0.971021263846572	0.918563808421141
46	72.3	72.82296311822	79.2125	0.919336760211077	0.992818705861076
47	78.5	77.1987056672702	82.2625	0.938443466552441	1.01685642682066
48	81.9	81.733794743596	84.9708333333333	0.961904120946553	1.00203349492001
49	97.8	88.3984411197149	87.1416666666667	1.0144221989448	1.10635435151569
50	93.1	92.3574834986139	88.9125	1.03874577251358	1.00803959217227
51	94.2	89.4988222292501	90.8291666666667	0.985353334328181	1.05252781716734
52	101.1	92.1787050711657	93.0583333333333	0.990547560539078	1.09678260203316
53	101	94.5844138082909	95.4375	0.991061310368471	1.06782921131924
54	99.7	104.200344372817	98.375	1.05921569883422	0.956810657393655
55	97.1	111.071989149357	101.445833333333	1.09488961251266	0.874207806519343
56	91.7	107.982519784476	104.325	1.03505890040236	0.849211522226241
57	95	104.117755015949	107.225	0.971021263846572	0.912428432455617
58	98.9	100.855073164989	109.704166666667	0.919336760211077	0.980615024077261
59	109	104.804584308354	111.679166666667	0.938443466552441	1.04003084139241
60	121.9	109.244252602667	113.570833333333	0.961904120946553	1.11584817595268
61	131.5	117.301020271317	115.633333333333	1.0144221989448	1.12104736766859
62	128.5	122.628266552614	118.054166666667	1.03874577251358	1.04788238154591
63	128.4	118.86235159223	120.629166666667	0.985353334328181	1.08024112159997
64	126.4	121.610349463683	122.770833333333	0.990547560539078	1.03938522138486
65	123.1	122.804884621033	123.9125	0.991061310368471	1.00240312410925
66	123	131.135316914422	123.804166666667	1.05921569883422	0.937962426096618
67	123.3	NA	NA	1.09488961251266	NA
68	123.6	NA	NA	1.03505890040236	NA
69	124.9	NA	NA	0.971021263846572	NA
70	120.4	NA	NA	0.919336760211077	NA
71	114.9	NA	NA	0.938443466552441	NA
72	113.4	NA	NA	0.961904120946553	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