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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 25 May 2008 07:21:36 -0600

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/25/t12117217529npgrkg73tkeo8z.htm/, Retrieved Wed, 15 May 2024 23:11:29 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13143, Retrieved Wed, 15 May 2024 23:11:29 +0000

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Estimated Impact

218

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

-       [Classical Decomposition] [multiplicatief mo...] [2008-05-25 13:21:36] [16094f22cd17e7ed684f81a8d68c07fe] [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	6 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 6 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13143&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13143&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13143&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	6 seconds
R Server	'Herman Ole Andreas Wold' @ 193.190.124.10:1001

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	430	NA	NA	0.999243518318136	NA
2	433.87	NA	NA	1.00697616543581	NA
3	434.55	NA	NA	1.00634489447381	NA
4	434.55	NA	NA	1.00481138613321	NA
5	434.55	NA	NA	1.00329589799725	NA
6	434.55	NA	NA	1.00109680421736	NA
7	434.71	434.862675966241	434.64625	1.00049793588750	0.99964890993254
8	434.71	434.918671830980	435.19875	0.999356436182275	0.999520204938312
9	434.71	434.124297626871	435.649166666667	0.99649977744371	1.00134915823954
10	434.71	434.179950234911	436.07875	0.995645741130268	1.00122080663744
11	434.73	433.95230093831	436.512916666667	0.99413392907612	1.00179213028715
12	436.34	433.494114995458	436.947083333333	0.992097513704557	1.00656499109468
13	437.55	437.056208016908	437.387083333333	0.999243518318136	1.00112981345199
14	439.58	440.890248540393	437.835833333333	1.00697616543581	0.997028175277792
15	439.65	441.112415525822	438.33125	1.00634489447381	0.996684710122977
16	439.76	440.980317018047	438.86875	1.00481138613321	0.997232717717882
17	439.76	440.851979939609	439.40375	1.00329589799725	0.997523023624033
18	439.76	440.355371136771	439.872916666667	1.00109680421736	0.998647975758229
19	440.06	440.773951270776	440.554583333333	1.00049793588750	0.998380232614206
20	440.13	441.453213728067	441.7375	0.999356436182275	0.997002595774775
21	441.18	441.603858873068	443.155	0.99649977744371	0.999040183040634
22	441.14	442.646257853655	444.582083333333	0.995645741130268	0.996597152179804
23	441.14	443.407343048765	446.02375	0.99413392907612	0.994886546007166
24	441.19	443.890470191154	447.42625	0.992097513704557	0.993916359164028
25	449.06	448.424684795106	448.764166666667	0.999243518318136	1.00141677125822
26	456.46	453.238713342452	450.09875	1.00697616543581	1.00710726282358
27	456.79	454.25989226175	451.395833333333	1.00634489447381	1.00556973613861
28	456.87	454.843783446809	452.665833333333	1.00481138613321	1.00445475265779
29	457.25	455.491739251219	453.995416666667	1.00329589799725	1.00386013751132
30	455.93	455.865280499777	455.365833333333	1.00109680421736	1.00014197067202
31	456	456.751069558619	456.52375	1.00049793588750	0.998355626053936
32	456.22	456.868703154694	457.162916666667	0.999356436182275	0.998580110324444
33	456.22	455.951379627054	457.552916666667	0.99649977744371	1.00058914258175
34	456.58	456.012387075937	458.006666666667	0.995645741130268	1.00124473137167
35	457.61	455.768984234356	458.458333333333	0.99413392907612	1.00403936167078
36	457.61	455.35622383183	458.983333333333	0.992097513704557	1.00494947922135
37	460.43	459.24982291022	459.5975	0.999243518318136	1.00256979323868
38	460.43	463.45658440781	460.245833333333	1.00697616543581	0.993469540600708
39	462.18	463.722469442412	460.79875	1.00634489447381	0.996673722875092
40	462.37	463.516561723371	461.297083333333	1.00481138613321	0.99752638456087
41	462.59	463.34043945326	461.818333333333	1.00329589799725	0.998380371343919
42	463.19	462.80371560034	462.296666666667	1.00109680421736	1.00083466140534
43	463.48	462.926226193745	462.695833333333	1.00049793588750	1.00119624634536
44	464.3	463.051388306542	463.349583333333	0.999356436182275	1.00269648623239
45	461.41	462.642460424348	464.2675	0.99649977744371	0.997336041263447
46	463.35	463.091013442981	465.11625	0.995645741130268	1.00055925627901
47	463.35	463.222917590074	465.95625	0.99413392907612	1.00027434396076
48	463.35	463.073502366559	466.762083333333	0.992097513704557	1.00059709232342
49	464.27	467.243354705299	467.597083333333	0.999243518318136	0.993636389527307
50	472.28	471.738543795117	468.470416666667	1.00697616543581	1.00114778877411
51	472.36	472.442867263401	469.464166666667	1.00634489447381	0.999824598339519
52	472.56	472.777992003643	470.514166666667	1.00481138613321	0.999538912539648
53	472.56	473.038130387318	471.484166666667	1.00329589799725	0.99898923499692
54	472.56	472.972356389178	472.454166666667	1.00109680421736	0.999128159640605
55	474.15	473.761201965267	473.525416666667	1.00049793588750	1.00082066246269
56	474.59	474.36535235967	474.670833333333	0.999356436182275	1.00047357514458
57	474.97	474.12255306874	475.787916666667	0.99649977744371	1.00178740059036
58	474.99	474.823039092632	476.899583333333	0.995645741130268	1.00035162764572
59	474.99	475.202645657912	478.006666666667	0.99413392907612	0.999552515837496
60	474.99	475.327560156667	479.11375	0.992097513704557	0.999289836767396
61	478.34	479.791355186579	480.154583333333	0.999243518318136	0.996975028476671
62	485.7	484.473435700662	481.117083333333	1.00697616543581	1.00253174727230
63	485.75	485.227640526945	482.168333333333	1.00634489447381	1.00107652456173
64	485.85	485.683119572881	483.3575	1.00481138613321	1.00034359939721
65	485.84	486.181306651082	484.584166666667	1.00329589799725	0.999297984833203
66	485.85	486.343672704175	485.810833333333	1.00109680421736	0.99898493034477
67	485.84	NA	NA	1.00049793588750	NA
68	486	NA	NA	0.999356436182275	NA
69	488.79	NA	NA	0.99649977744371	NA
70	489.71	NA	NA	0.995645741130268	NA
71	489.71	NA	NA	0.99413392907612	NA
72	489.71	NA	NA	0.992097513704557	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 430 & NA & NA & 0.999243518318136 & NA \tabularnewline
2 & 433.87 & NA & NA & 1.00697616543581 & NA \tabularnewline
3 & 434.55 & NA & NA & 1.00634489447381 & NA \tabularnewline
4 & 434.55 & NA & NA & 1.00481138613321 & NA \tabularnewline
5 & 434.55 & NA & NA & 1.00329589799725 & NA \tabularnewline
6 & 434.55 & NA & NA & 1.00109680421736 & NA \tabularnewline
7 & 434.71 & 434.862675966241 & 434.64625 & 1.00049793588750 & 0.99964890993254 \tabularnewline
8 & 434.71 & 434.918671830980 & 435.19875 & 0.999356436182275 & 0.999520204938312 \tabularnewline
9 & 434.71 & 434.124297626871 & 435.649166666667 & 0.99649977744371 & 1.00134915823954 \tabularnewline
10 & 434.71 & 434.179950234911 & 436.07875 & 0.995645741130268 & 1.00122080663744 \tabularnewline
11 & 434.73 & 433.95230093831 & 436.512916666667 & 0.99413392907612 & 1.00179213028715 \tabularnewline
12 & 436.34 & 433.494114995458 & 436.947083333333 & 0.992097513704557 & 1.00656499109468 \tabularnewline
13 & 437.55 & 437.056208016908 & 437.387083333333 & 0.999243518318136 & 1.00112981345199 \tabularnewline
14 & 439.58 & 440.890248540393 & 437.835833333333 & 1.00697616543581 & 0.997028175277792 \tabularnewline
15 & 439.65 & 441.112415525822 & 438.33125 & 1.00634489447381 & 0.996684710122977 \tabularnewline
16 & 439.76 & 440.980317018047 & 438.86875 & 1.00481138613321 & 0.997232717717882 \tabularnewline
17 & 439.76 & 440.851979939609 & 439.40375 & 1.00329589799725 & 0.997523023624033 \tabularnewline
18 & 439.76 & 440.355371136771 & 439.872916666667 & 1.00109680421736 & 0.998647975758229 \tabularnewline
19 & 440.06 & 440.773951270776 & 440.554583333333 & 1.00049793588750 & 0.998380232614206 \tabularnewline
20 & 440.13 & 441.453213728067 & 441.7375 & 0.999356436182275 & 0.997002595774775 \tabularnewline
21 & 441.18 & 441.603858873068 & 443.155 & 0.99649977744371 & 0.999040183040634 \tabularnewline
22 & 441.14 & 442.646257853655 & 444.582083333333 & 0.995645741130268 & 0.996597152179804 \tabularnewline
23 & 441.14 & 443.407343048765 & 446.02375 & 0.99413392907612 & 0.994886546007166 \tabularnewline
24 & 441.19 & 443.890470191154 & 447.42625 & 0.992097513704557 & 0.993916359164028 \tabularnewline
25 & 449.06 & 448.424684795106 & 448.764166666667 & 0.999243518318136 & 1.00141677125822 \tabularnewline
26 & 456.46 & 453.238713342452 & 450.09875 & 1.00697616543581 & 1.00710726282358 \tabularnewline
27 & 456.79 & 454.25989226175 & 451.395833333333 & 1.00634489447381 & 1.00556973613861 \tabularnewline
28 & 456.87 & 454.843783446809 & 452.665833333333 & 1.00481138613321 & 1.00445475265779 \tabularnewline
29 & 457.25 & 455.491739251219 & 453.995416666667 & 1.00329589799725 & 1.00386013751132 \tabularnewline
30 & 455.93 & 455.865280499777 & 455.365833333333 & 1.00109680421736 & 1.00014197067202 \tabularnewline
31 & 456 & 456.751069558619 & 456.52375 & 1.00049793588750 & 0.998355626053936 \tabularnewline
32 & 456.22 & 456.868703154694 & 457.162916666667 & 0.999356436182275 & 0.998580110324444 \tabularnewline
33 & 456.22 & 455.951379627054 & 457.552916666667 & 0.99649977744371 & 1.00058914258175 \tabularnewline
34 & 456.58 & 456.012387075937 & 458.006666666667 & 0.995645741130268 & 1.00124473137167 \tabularnewline
35 & 457.61 & 455.768984234356 & 458.458333333333 & 0.99413392907612 & 1.00403936167078 \tabularnewline
36 & 457.61 & 455.35622383183 & 458.983333333333 & 0.992097513704557 & 1.00494947922135 \tabularnewline
37 & 460.43 & 459.24982291022 & 459.5975 & 0.999243518318136 & 1.00256979323868 \tabularnewline
38 & 460.43 & 463.45658440781 & 460.245833333333 & 1.00697616543581 & 0.993469540600708 \tabularnewline
39 & 462.18 & 463.722469442412 & 460.79875 & 1.00634489447381 & 0.996673722875092 \tabularnewline
40 & 462.37 & 463.516561723371 & 461.297083333333 & 1.00481138613321 & 0.99752638456087 \tabularnewline
41 & 462.59 & 463.34043945326 & 461.818333333333 & 1.00329589799725 & 0.998380371343919 \tabularnewline
42 & 463.19 & 462.80371560034 & 462.296666666667 & 1.00109680421736 & 1.00083466140534 \tabularnewline
43 & 463.48 & 462.926226193745 & 462.695833333333 & 1.00049793588750 & 1.00119624634536 \tabularnewline
44 & 464.3 & 463.051388306542 & 463.349583333333 & 0.999356436182275 & 1.00269648623239 \tabularnewline
45 & 461.41 & 462.642460424348 & 464.2675 & 0.99649977744371 & 0.997336041263447 \tabularnewline
46 & 463.35 & 463.091013442981 & 465.11625 & 0.995645741130268 & 1.00055925627901 \tabularnewline
47 & 463.35 & 463.222917590074 & 465.95625 & 0.99413392907612 & 1.00027434396076 \tabularnewline
48 & 463.35 & 463.073502366559 & 466.762083333333 & 0.992097513704557 & 1.00059709232342 \tabularnewline
49 & 464.27 & 467.243354705299 & 467.597083333333 & 0.999243518318136 & 0.993636389527307 \tabularnewline
50 & 472.28 & 471.738543795117 & 468.470416666667 & 1.00697616543581 & 1.00114778877411 \tabularnewline
51 & 472.36 & 472.442867263401 & 469.464166666667 & 1.00634489447381 & 0.999824598339519 \tabularnewline
52 & 472.56 & 472.777992003643 & 470.514166666667 & 1.00481138613321 & 0.999538912539648 \tabularnewline
53 & 472.56 & 473.038130387318 & 471.484166666667 & 1.00329589799725 & 0.99898923499692 \tabularnewline
54 & 472.56 & 472.972356389178 & 472.454166666667 & 1.00109680421736 & 0.999128159640605 \tabularnewline
55 & 474.15 & 473.761201965267 & 473.525416666667 & 1.00049793588750 & 1.00082066246269 \tabularnewline
56 & 474.59 & 474.36535235967 & 474.670833333333 & 0.999356436182275 & 1.00047357514458 \tabularnewline
57 & 474.97 & 474.12255306874 & 475.787916666667 & 0.99649977744371 & 1.00178740059036 \tabularnewline
58 & 474.99 & 474.823039092632 & 476.899583333333 & 0.995645741130268 & 1.00035162764572 \tabularnewline
59 & 474.99 & 475.202645657912 & 478.006666666667 & 0.99413392907612 & 0.999552515837496 \tabularnewline
60 & 474.99 & 475.327560156667 & 479.11375 & 0.992097513704557 & 0.999289836767396 \tabularnewline
61 & 478.34 & 479.791355186579 & 480.154583333333 & 0.999243518318136 & 0.996975028476671 \tabularnewline
62 & 485.7 & 484.473435700662 & 481.117083333333 & 1.00697616543581 & 1.00253174727230 \tabularnewline
63 & 485.75 & 485.227640526945 & 482.168333333333 & 1.00634489447381 & 1.00107652456173 \tabularnewline
64 & 485.85 & 485.683119572881 & 483.3575 & 1.00481138613321 & 1.00034359939721 \tabularnewline
65 & 485.84 & 486.181306651082 & 484.584166666667 & 1.00329589799725 & 0.999297984833203 \tabularnewline
66 & 485.85 & 486.343672704175 & 485.810833333333 & 1.00109680421736 & 0.99898493034477 \tabularnewline
67 & 485.84 & NA & NA & 1.00049793588750 & NA \tabularnewline
68 & 486 & NA & NA & 0.999356436182275 & NA \tabularnewline
69 & 488.79 & NA & NA & 0.99649977744371 & NA \tabularnewline
70 & 489.71 & NA & NA & 0.995645741130268 & NA \tabularnewline
71 & 489.71 & NA & NA & 0.99413392907612 & NA \tabularnewline
72 & 489.71 & NA & NA & 0.992097513704557 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13143&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]430[/C][C]NA[/C][C]NA[/C][C]0.999243518318136[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]433.87[/C][C]NA[/C][C]NA[/C][C]1.00697616543581[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]434.55[/C][C]NA[/C][C]NA[/C][C]1.00634489447381[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]434.55[/C][C]NA[/C][C]NA[/C][C]1.00481138613321[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]434.55[/C][C]NA[/C][C]NA[/C][C]1.00329589799725[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]434.55[/C][C]NA[/C][C]NA[/C][C]1.00109680421736[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]434.71[/C][C]434.862675966241[/C][C]434.64625[/C][C]1.00049793588750[/C][C]0.99964890993254[/C][/ROW]
[ROW][C]8[/C][C]434.71[/C][C]434.918671830980[/C][C]435.19875[/C][C]0.999356436182275[/C][C]0.999520204938312[/C][/ROW]
[ROW][C]9[/C][C]434.71[/C][C]434.124297626871[/C][C]435.649166666667[/C][C]0.99649977744371[/C][C]1.00134915823954[/C][/ROW]
[ROW][C]10[/C][C]434.71[/C][C]434.179950234911[/C][C]436.07875[/C][C]0.995645741130268[/C][C]1.00122080663744[/C][/ROW]
[ROW][C]11[/C][C]434.73[/C][C]433.95230093831[/C][C]436.512916666667[/C][C]0.99413392907612[/C][C]1.00179213028715[/C][/ROW]
[ROW][C]12[/C][C]436.34[/C][C]433.494114995458[/C][C]436.947083333333[/C][C]0.992097513704557[/C][C]1.00656499109468[/C][/ROW]
[ROW][C]13[/C][C]437.55[/C][C]437.056208016908[/C][C]437.387083333333[/C][C]0.999243518318136[/C][C]1.00112981345199[/C][/ROW]
[ROW][C]14[/C][C]439.58[/C][C]440.890248540393[/C][C]437.835833333333[/C][C]1.00697616543581[/C][C]0.997028175277792[/C][/ROW]
[ROW][C]15[/C][C]439.65[/C][C]441.112415525822[/C][C]438.33125[/C][C]1.00634489447381[/C][C]0.996684710122977[/C][/ROW]
[ROW][C]16[/C][C]439.76[/C][C]440.980317018047[/C][C]438.86875[/C][C]1.00481138613321[/C][C]0.997232717717882[/C][/ROW]
[ROW][C]17[/C][C]439.76[/C][C]440.851979939609[/C][C]439.40375[/C][C]1.00329589799725[/C][C]0.997523023624033[/C][/ROW]
[ROW][C]18[/C][C]439.76[/C][C]440.355371136771[/C][C]439.872916666667[/C][C]1.00109680421736[/C][C]0.998647975758229[/C][/ROW]
[ROW][C]19[/C][C]440.06[/C][C]440.773951270776[/C][C]440.554583333333[/C][C]1.00049793588750[/C][C]0.998380232614206[/C][/ROW]
[ROW][C]20[/C][C]440.13[/C][C]441.453213728067[/C][C]441.7375[/C][C]0.999356436182275[/C][C]0.997002595774775[/C][/ROW]
[ROW][C]21[/C][C]441.18[/C][C]441.603858873068[/C][C]443.155[/C][C]0.99649977744371[/C][C]0.999040183040634[/C][/ROW]
[ROW][C]22[/C][C]441.14[/C][C]442.646257853655[/C][C]444.582083333333[/C][C]0.995645741130268[/C][C]0.996597152179804[/C][/ROW]
[ROW][C]23[/C][C]441.14[/C][C]443.407343048765[/C][C]446.02375[/C][C]0.99413392907612[/C][C]0.994886546007166[/C][/ROW]
[ROW][C]24[/C][C]441.19[/C][C]443.890470191154[/C][C]447.42625[/C][C]0.992097513704557[/C][C]0.993916359164028[/C][/ROW]
[ROW][C]25[/C][C]449.06[/C][C]448.424684795106[/C][C]448.764166666667[/C][C]0.999243518318136[/C][C]1.00141677125822[/C][/ROW]
[ROW][C]26[/C][C]456.46[/C][C]453.238713342452[/C][C]450.09875[/C][C]1.00697616543581[/C][C]1.00710726282358[/C][/ROW]
[ROW][C]27[/C][C]456.79[/C][C]454.25989226175[/C][C]451.395833333333[/C][C]1.00634489447381[/C][C]1.00556973613861[/C][/ROW]
[ROW][C]28[/C][C]456.87[/C][C]454.843783446809[/C][C]452.665833333333[/C][C]1.00481138613321[/C][C]1.00445475265779[/C][/ROW]
[ROW][C]29[/C][C]457.25[/C][C]455.491739251219[/C][C]453.995416666667[/C][C]1.00329589799725[/C][C]1.00386013751132[/C][/ROW]
[ROW][C]30[/C][C]455.93[/C][C]455.865280499777[/C][C]455.365833333333[/C][C]1.00109680421736[/C][C]1.00014197067202[/C][/ROW]
[ROW][C]31[/C][C]456[/C][C]456.751069558619[/C][C]456.52375[/C][C]1.00049793588750[/C][C]0.998355626053936[/C][/ROW]
[ROW][C]32[/C][C]456.22[/C][C]456.868703154694[/C][C]457.162916666667[/C][C]0.999356436182275[/C][C]0.998580110324444[/C][/ROW]
[ROW][C]33[/C][C]456.22[/C][C]455.951379627054[/C][C]457.552916666667[/C][C]0.99649977744371[/C][C]1.00058914258175[/C][/ROW]
[ROW][C]34[/C][C]456.58[/C][C]456.012387075937[/C][C]458.006666666667[/C][C]0.995645741130268[/C][C]1.00124473137167[/C][/ROW]
[ROW][C]35[/C][C]457.61[/C][C]455.768984234356[/C][C]458.458333333333[/C][C]0.99413392907612[/C][C]1.00403936167078[/C][/ROW]
[ROW][C]36[/C][C]457.61[/C][C]455.35622383183[/C][C]458.983333333333[/C][C]0.992097513704557[/C][C]1.00494947922135[/C][/ROW]
[ROW][C]37[/C][C]460.43[/C][C]459.24982291022[/C][C]459.5975[/C][C]0.999243518318136[/C][C]1.00256979323868[/C][/ROW]
[ROW][C]38[/C][C]460.43[/C][C]463.45658440781[/C][C]460.245833333333[/C][C]1.00697616543581[/C][C]0.993469540600708[/C][/ROW]
[ROW][C]39[/C][C]462.18[/C][C]463.722469442412[/C][C]460.79875[/C][C]1.00634489447381[/C][C]0.996673722875092[/C][/ROW]
[ROW][C]40[/C][C]462.37[/C][C]463.516561723371[/C][C]461.297083333333[/C][C]1.00481138613321[/C][C]0.99752638456087[/C][/ROW]
[ROW][C]41[/C][C]462.59[/C][C]463.34043945326[/C][C]461.818333333333[/C][C]1.00329589799725[/C][C]0.998380371343919[/C][/ROW]
[ROW][C]42[/C][C]463.19[/C][C]462.80371560034[/C][C]462.296666666667[/C][C]1.00109680421736[/C][C]1.00083466140534[/C][/ROW]
[ROW][C]43[/C][C]463.48[/C][C]462.926226193745[/C][C]462.695833333333[/C][C]1.00049793588750[/C][C]1.00119624634536[/C][/ROW]
[ROW][C]44[/C][C]464.3[/C][C]463.051388306542[/C][C]463.349583333333[/C][C]0.999356436182275[/C][C]1.00269648623239[/C][/ROW]
[ROW][C]45[/C][C]461.41[/C][C]462.642460424348[/C][C]464.2675[/C][C]0.99649977744371[/C][C]0.997336041263447[/C][/ROW]
[ROW][C]46[/C][C]463.35[/C][C]463.091013442981[/C][C]465.11625[/C][C]0.995645741130268[/C][C]1.00055925627901[/C][/ROW]
[ROW][C]47[/C][C]463.35[/C][C]463.222917590074[/C][C]465.95625[/C][C]0.99413392907612[/C][C]1.00027434396076[/C][/ROW]
[ROW][C]48[/C][C]463.35[/C][C]463.073502366559[/C][C]466.762083333333[/C][C]0.992097513704557[/C][C]1.00059709232342[/C][/ROW]
[ROW][C]49[/C][C]464.27[/C][C]467.243354705299[/C][C]467.597083333333[/C][C]0.999243518318136[/C][C]0.993636389527307[/C][/ROW]
[ROW][C]50[/C][C]472.28[/C][C]471.738543795117[/C][C]468.470416666667[/C][C]1.00697616543581[/C][C]1.00114778877411[/C][/ROW]
[ROW][C]51[/C][C]472.36[/C][C]472.442867263401[/C][C]469.464166666667[/C][C]1.00634489447381[/C][C]0.999824598339519[/C][/ROW]
[ROW][C]52[/C][C]472.56[/C][C]472.777992003643[/C][C]470.514166666667[/C][C]1.00481138613321[/C][C]0.999538912539648[/C][/ROW]
[ROW][C]53[/C][C]472.56[/C][C]473.038130387318[/C][C]471.484166666667[/C][C]1.00329589799725[/C][C]0.99898923499692[/C][/ROW]
[ROW][C]54[/C][C]472.56[/C][C]472.972356389178[/C][C]472.454166666667[/C][C]1.00109680421736[/C][C]0.999128159640605[/C][/ROW]
[ROW][C]55[/C][C]474.15[/C][C]473.761201965267[/C][C]473.525416666667[/C][C]1.00049793588750[/C][C]1.00082066246269[/C][/ROW]
[ROW][C]56[/C][C]474.59[/C][C]474.36535235967[/C][C]474.670833333333[/C][C]0.999356436182275[/C][C]1.00047357514458[/C][/ROW]
[ROW][C]57[/C][C]474.97[/C][C]474.12255306874[/C][C]475.787916666667[/C][C]0.99649977744371[/C][C]1.00178740059036[/C][/ROW]
[ROW][C]58[/C][C]474.99[/C][C]474.823039092632[/C][C]476.899583333333[/C][C]0.995645741130268[/C][C]1.00035162764572[/C][/ROW]
[ROW][C]59[/C][C]474.99[/C][C]475.202645657912[/C][C]478.006666666667[/C][C]0.99413392907612[/C][C]0.999552515837496[/C][/ROW]
[ROW][C]60[/C][C]474.99[/C][C]475.327560156667[/C][C]479.11375[/C][C]0.992097513704557[/C][C]0.999289836767396[/C][/ROW]
[ROW][C]61[/C][C]478.34[/C][C]479.791355186579[/C][C]480.154583333333[/C][C]0.999243518318136[/C][C]0.996975028476671[/C][/ROW]
[ROW][C]62[/C][C]485.7[/C][C]484.473435700662[/C][C]481.117083333333[/C][C]1.00697616543581[/C][C]1.00253174727230[/C][/ROW]
[ROW][C]63[/C][C]485.75[/C][C]485.227640526945[/C][C]482.168333333333[/C][C]1.00634489447381[/C][C]1.00107652456173[/C][/ROW]
[ROW][C]64[/C][C]485.85[/C][C]485.683119572881[/C][C]483.3575[/C][C]1.00481138613321[/C][C]1.00034359939721[/C][/ROW]
[ROW][C]65[/C][C]485.84[/C][C]486.181306651082[/C][C]484.584166666667[/C][C]1.00329589799725[/C][C]0.999297984833203[/C][/ROW]
[ROW][C]66[/C][C]485.85[/C][C]486.343672704175[/C][C]485.810833333333[/C][C]1.00109680421736[/C][C]0.99898493034477[/C][/ROW]
[ROW][C]67[/C][C]485.84[/C][C]NA[/C][C]NA[/C][C]1.00049793588750[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]486[/C][C]NA[/C][C]NA[/C][C]0.999356436182275[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]488.79[/C][C]NA[/C][C]NA[/C][C]0.99649977744371[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]489.71[/C][C]NA[/C][C]NA[/C][C]0.995645741130268[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]489.71[/C][C]NA[/C][C]NA[/C][C]0.99413392907612[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]489.71[/C][C]NA[/C][C]NA[/C][C]0.992097513704557[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13143&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13143&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	430	NA	NA	0.999243518318136	NA
2	433.87	NA	NA	1.00697616543581	NA
3	434.55	NA	NA	1.00634489447381	NA
4	434.55	NA	NA	1.00481138613321	NA
5	434.55	NA	NA	1.00329589799725	NA
6	434.55	NA	NA	1.00109680421736	NA
7	434.71	434.862675966241	434.64625	1.00049793588750	0.99964890993254
8	434.71	434.918671830980	435.19875	0.999356436182275	0.999520204938312
9	434.71	434.124297626871	435.649166666667	0.99649977744371	1.00134915823954
10	434.71	434.179950234911	436.07875	0.995645741130268	1.00122080663744
11	434.73	433.95230093831	436.512916666667	0.99413392907612	1.00179213028715
12	436.34	433.494114995458	436.947083333333	0.992097513704557	1.00656499109468
13	437.55	437.056208016908	437.387083333333	0.999243518318136	1.00112981345199
14	439.58	440.890248540393	437.835833333333	1.00697616543581	0.997028175277792
15	439.65	441.112415525822	438.33125	1.00634489447381	0.996684710122977
16	439.76	440.980317018047	438.86875	1.00481138613321	0.997232717717882
17	439.76	440.851979939609	439.40375	1.00329589799725	0.997523023624033
18	439.76	440.355371136771	439.872916666667	1.00109680421736	0.998647975758229
19	440.06	440.773951270776	440.554583333333	1.00049793588750	0.998380232614206
20	440.13	441.453213728067	441.7375	0.999356436182275	0.997002595774775
21	441.18	441.603858873068	443.155	0.99649977744371	0.999040183040634
22	441.14	442.646257853655	444.582083333333	0.995645741130268	0.996597152179804
23	441.14	443.407343048765	446.02375	0.99413392907612	0.994886546007166
24	441.19	443.890470191154	447.42625	0.992097513704557	0.993916359164028
25	449.06	448.424684795106	448.764166666667	0.999243518318136	1.00141677125822
26	456.46	453.238713342452	450.09875	1.00697616543581	1.00710726282358
27	456.79	454.25989226175	451.395833333333	1.00634489447381	1.00556973613861
28	456.87	454.843783446809	452.665833333333	1.00481138613321	1.00445475265779
29	457.25	455.491739251219	453.995416666667	1.00329589799725	1.00386013751132
30	455.93	455.865280499777	455.365833333333	1.00109680421736	1.00014197067202
31	456	456.751069558619	456.52375	1.00049793588750	0.998355626053936
32	456.22	456.868703154694	457.162916666667	0.999356436182275	0.998580110324444
33	456.22	455.951379627054	457.552916666667	0.99649977744371	1.00058914258175
34	456.58	456.012387075937	458.006666666667	0.995645741130268	1.00124473137167
35	457.61	455.768984234356	458.458333333333	0.99413392907612	1.00403936167078
36	457.61	455.35622383183	458.983333333333	0.992097513704557	1.00494947922135
37	460.43	459.24982291022	459.5975	0.999243518318136	1.00256979323868
38	460.43	463.45658440781	460.245833333333	1.00697616543581	0.993469540600708
39	462.18	463.722469442412	460.79875	1.00634489447381	0.996673722875092
40	462.37	463.516561723371	461.297083333333	1.00481138613321	0.99752638456087
41	462.59	463.34043945326	461.818333333333	1.00329589799725	0.998380371343919
42	463.19	462.80371560034	462.296666666667	1.00109680421736	1.00083466140534
43	463.48	462.926226193745	462.695833333333	1.00049793588750	1.00119624634536
44	464.3	463.051388306542	463.349583333333	0.999356436182275	1.00269648623239
45	461.41	462.642460424348	464.2675	0.99649977744371	0.997336041263447
46	463.35	463.091013442981	465.11625	0.995645741130268	1.00055925627901
47	463.35	463.222917590074	465.95625	0.99413392907612	1.00027434396076
48	463.35	463.073502366559	466.762083333333	0.992097513704557	1.00059709232342
49	464.27	467.243354705299	467.597083333333	0.999243518318136	0.993636389527307
50	472.28	471.738543795117	468.470416666667	1.00697616543581	1.00114778877411
51	472.36	472.442867263401	469.464166666667	1.00634489447381	0.999824598339519
52	472.56	472.777992003643	470.514166666667	1.00481138613321	0.999538912539648
53	472.56	473.038130387318	471.484166666667	1.00329589799725	0.99898923499692
54	472.56	472.972356389178	472.454166666667	1.00109680421736	0.999128159640605
55	474.15	473.761201965267	473.525416666667	1.00049793588750	1.00082066246269
56	474.59	474.36535235967	474.670833333333	0.999356436182275	1.00047357514458
57	474.97	474.12255306874	475.787916666667	0.99649977744371	1.00178740059036
58	474.99	474.823039092632	476.899583333333	0.995645741130268	1.00035162764572
59	474.99	475.202645657912	478.006666666667	0.99413392907612	0.999552515837496
60	474.99	475.327560156667	479.11375	0.992097513704557	0.999289836767396
61	478.34	479.791355186579	480.154583333333	0.999243518318136	0.996975028476671
62	485.7	484.473435700662	481.117083333333	1.00697616543581	1.00253174727230
63	485.75	485.227640526945	482.168333333333	1.00634489447381	1.00107652456173
64	485.85	485.683119572881	483.3575	1.00481138613321	1.00034359939721
65	485.84	486.181306651082	484.584166666667	1.00329589799725	0.999297984833203
66	485.85	486.343672704175	485.810833333333	1.00109680421736	0.99898493034477
67	485.84	NA	NA	1.00049793588750	NA
68	486	NA	NA	0.999356436182275	NA
69	488.79	NA	NA	0.99649977744371	NA
70	489.71	NA	NA	0.995645741130268	NA
71	489.71	NA	NA	0.99413392907612	NA
72	489.71	NA	NA	0.992097513704557	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