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Author's title

multiplicatief model over de gegevens van de evolutie van de prijzen van da...

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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sat, 05 May 2012 05:35:30 -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/2012/May/05/t1336210694wlz2e32jd7bz7qr.htm/, Retrieved Wed, 01 May 2024 04:35:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166221, Retrieved Wed, 01 May 2024 04:35:24 +0000

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Estimated Impact

166

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

-       [Classical Decomposition] [multiplicatief mo...] [2012-05-05 09:35:30] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166221&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166221&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166221&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	369.82	NA	NA	0.990057655291765	NA
2	373.1	NA	NA	0.996967309830876	NA
3	374.55	NA	NA	1.00695770825806	NA
4	375.01	NA	NA	1.00569640930236	NA
5	374.81	NA	NA	1.0078952253204	NA
6	375.31	NA	NA	1.00571725488978	NA
7	375.31	376.119678173545	375.275833333333	1.00224859893779	0.997847285796167
8	375.39	376.167173768546	375.95125	1.00057433980748	0.997933967069055
9	375.59	376.469944509899	376.839166666667	0.999020212893384	0.997662643398946
10	376.26	376.746935434865	377.867083333333	0.997035603396341	0.998707526487765
11	377.18	377.110446545128	378.954583333333	0.995133620572723	1.00018443788951
12	377.26	377.337422546634	380.11375	0.992696061499049	0.999794818796101
13	377.26	377.477219612976	381.267916666667	0.990057655291765	0.999424549080873
14	381.87	381.269792895576	382.429583333333	0.996967309830876	1.00157423198902
15	387.09	386.262263836403	383.593333333333	1.00695770825806	1.00214293820829
16	387.14	386.89350385947	384.702083333333	1.00569640930236	1.00063711625569
17	388.78	388.76828600499	385.722916666667	1.0078952253204	1.00003013104574
18	389.16	388.917986296432	386.707083333333	1.00571725488978	1.00062227439228
19	389.16	388.564682547273	387.692916666667	1.00224859893779	1.00153209357275
20	389.42	388.821103919312	388.597916666667	1.00057433980748	1.0015402869717
21	389.49	388.789945026984	389.17125	0.999020212893384	1.00180059948044
22	388.97	388.37029341296	389.525	0.997035603396341	1.00154416184042
23	388.97	387.987671656996	389.885	0.995133620572723	1.00253185452726
24	389.09	387.364893637851	390.215	0.992696061499049	1.00445344012966
25	389.09	386.657116697646	390.54	0.990057655291765	1.00629209497845
26	391.76	389.677135138771	390.8625	0.996967309830876	1.00534510412187
27	390.96	393.926890259094	391.205	1.00695770825806	0.992468424135396
28	391.76	393.847475489626	391.616666666667	1.00569640930236	0.994699787050735
29	392.8	395.174720030933	392.079166666667	1.0078952253204	0.993990708639593
30	393.06	394.785089332146	392.540833333333	1.00571725488978	0.995630307783245
31	393.06	393.881193761055	392.9975	1.00224859893779	0.997915123204504
32	393.26	393.777282149158	393.55125	1.00057433980748	0.998686358577278
33	393.87	394.122215413303	394.50875	0.999020212893384	0.99936005786165
34	394.47	394.603843091694	395.777083333333	0.997035603396341	0.999660816553014
35	394.57	395.175024231583	397.1075	0.995133620572723	0.998468971482297
36	394.57	395.592689494243	398.503333333333	0.992696061499049	0.997414791725423
37	394.57	395.930656735545	399.906666666667	0.990057655291765	0.996563396361464
38	399.57	400.094612720412	401.311666666667	0.996967309830876	0.99868877834459
39	406.13	405.511519126891	402.709583333333	1.00695770825806	1.00152518694029
40	407.03	406.381805070897	404.08	1.00569640930236	1.00159503924884
41	409.46	408.632641027024	405.431666666667	1.0078952253204	1.00202470113718
42	409.9	409.116560214325	406.790833333333	1.00571725488978	1.00191495495871
43	409.9	409.075282520952	408.1575	1.00224859893779	1.00201605306966
44	410.14	409.66890410115	409.43375	1.00057433980748	1.00114994302505
45	410.54	410.340059794361	410.7425	0.999020212893384	1.00048725490204
46	410.69	410.937363432833	412.159166666667	0.997035603396341	0.999398050761881
47	410.79	411.561557850347	413.574166666667	0.995133620572723	0.998125291744018
48	410.97	411.93908464026	414.97	0.992696061499049	0.997647504991893
49	410.97	412.194003819805	416.333333333333	0.990057655291765	0.997030515222294
50	413.8	416.422444837167	417.689166666667	0.996967309830876	0.993702441187596
51	423.31	421.970662434081	419.055	1.00695770825806	1.0031740063591
52	423.85	422.844217210836	420.449166666667	1.00569640930236	1.00237861308781
53	426.6	425.211677570856	421.880833333333	1.0078952253204	1.00326501482056
54	426.26	425.773333199581	423.352916666667	1.00571725488978	1.00114301850884
55	426.26	NA	NA	1.00224859893779	NA
56	426.32	NA	NA	1.00057433980748	NA
57	427.14	NA	NA	0.999020212893384	NA
58	427.55	NA	NA	0.997035603396341	NA
59	428.29	NA	NA	0.995133620572723	NA
60	428.8	NA	NA	0.992696061499049	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 369.82 & NA & NA & 0.990057655291765 & NA \tabularnewline
2 & 373.1 & NA & NA & 0.996967309830876 & NA \tabularnewline
3 & 374.55 & NA & NA & 1.00695770825806 & NA \tabularnewline
4 & 375.01 & NA & NA & 1.00569640930236 & NA \tabularnewline
5 & 374.81 & NA & NA & 1.0078952253204 & NA \tabularnewline
6 & 375.31 & NA & NA & 1.00571725488978 & NA \tabularnewline
7 & 375.31 & 376.119678173545 & 375.275833333333 & 1.00224859893779 & 0.997847285796167 \tabularnewline
8 & 375.39 & 376.167173768546 & 375.95125 & 1.00057433980748 & 0.997933967069055 \tabularnewline
9 & 375.59 & 376.469944509899 & 376.839166666667 & 0.999020212893384 & 0.997662643398946 \tabularnewline
10 & 376.26 & 376.746935434865 & 377.867083333333 & 0.997035603396341 & 0.998707526487765 \tabularnewline
11 & 377.18 & 377.110446545128 & 378.954583333333 & 0.995133620572723 & 1.00018443788951 \tabularnewline
12 & 377.26 & 377.337422546634 & 380.11375 & 0.992696061499049 & 0.999794818796101 \tabularnewline
13 & 377.26 & 377.477219612976 & 381.267916666667 & 0.990057655291765 & 0.999424549080873 \tabularnewline
14 & 381.87 & 381.269792895576 & 382.429583333333 & 0.996967309830876 & 1.00157423198902 \tabularnewline
15 & 387.09 & 386.262263836403 & 383.593333333333 & 1.00695770825806 & 1.00214293820829 \tabularnewline
16 & 387.14 & 386.89350385947 & 384.702083333333 & 1.00569640930236 & 1.00063711625569 \tabularnewline
17 & 388.78 & 388.76828600499 & 385.722916666667 & 1.0078952253204 & 1.00003013104574 \tabularnewline
18 & 389.16 & 388.917986296432 & 386.707083333333 & 1.00571725488978 & 1.00062227439228 \tabularnewline
19 & 389.16 & 388.564682547273 & 387.692916666667 & 1.00224859893779 & 1.00153209357275 \tabularnewline
20 & 389.42 & 388.821103919312 & 388.597916666667 & 1.00057433980748 & 1.0015402869717 \tabularnewline
21 & 389.49 & 388.789945026984 & 389.17125 & 0.999020212893384 & 1.00180059948044 \tabularnewline
22 & 388.97 & 388.37029341296 & 389.525 & 0.997035603396341 & 1.00154416184042 \tabularnewline
23 & 388.97 & 387.987671656996 & 389.885 & 0.995133620572723 & 1.00253185452726 \tabularnewline
24 & 389.09 & 387.364893637851 & 390.215 & 0.992696061499049 & 1.00445344012966 \tabularnewline
25 & 389.09 & 386.657116697646 & 390.54 & 0.990057655291765 & 1.00629209497845 \tabularnewline
26 & 391.76 & 389.677135138771 & 390.8625 & 0.996967309830876 & 1.00534510412187 \tabularnewline
27 & 390.96 & 393.926890259094 & 391.205 & 1.00695770825806 & 0.992468424135396 \tabularnewline
28 & 391.76 & 393.847475489626 & 391.616666666667 & 1.00569640930236 & 0.994699787050735 \tabularnewline
29 & 392.8 & 395.174720030933 & 392.079166666667 & 1.0078952253204 & 0.993990708639593 \tabularnewline
30 & 393.06 & 394.785089332146 & 392.540833333333 & 1.00571725488978 & 0.995630307783245 \tabularnewline
31 & 393.06 & 393.881193761055 & 392.9975 & 1.00224859893779 & 0.997915123204504 \tabularnewline
32 & 393.26 & 393.777282149158 & 393.55125 & 1.00057433980748 & 0.998686358577278 \tabularnewline
33 & 393.87 & 394.122215413303 & 394.50875 & 0.999020212893384 & 0.99936005786165 \tabularnewline
34 & 394.47 & 394.603843091694 & 395.777083333333 & 0.997035603396341 & 0.999660816553014 \tabularnewline
35 & 394.57 & 395.175024231583 & 397.1075 & 0.995133620572723 & 0.998468971482297 \tabularnewline
36 & 394.57 & 395.592689494243 & 398.503333333333 & 0.992696061499049 & 0.997414791725423 \tabularnewline
37 & 394.57 & 395.930656735545 & 399.906666666667 & 0.990057655291765 & 0.996563396361464 \tabularnewline
38 & 399.57 & 400.094612720412 & 401.311666666667 & 0.996967309830876 & 0.99868877834459 \tabularnewline
39 & 406.13 & 405.511519126891 & 402.709583333333 & 1.00695770825806 & 1.00152518694029 \tabularnewline
40 & 407.03 & 406.381805070897 & 404.08 & 1.00569640930236 & 1.00159503924884 \tabularnewline
41 & 409.46 & 408.632641027024 & 405.431666666667 & 1.0078952253204 & 1.00202470113718 \tabularnewline
42 & 409.9 & 409.116560214325 & 406.790833333333 & 1.00571725488978 & 1.00191495495871 \tabularnewline
43 & 409.9 & 409.075282520952 & 408.1575 & 1.00224859893779 & 1.00201605306966 \tabularnewline
44 & 410.14 & 409.66890410115 & 409.43375 & 1.00057433980748 & 1.00114994302505 \tabularnewline
45 & 410.54 & 410.340059794361 & 410.7425 & 0.999020212893384 & 1.00048725490204 \tabularnewline
46 & 410.69 & 410.937363432833 & 412.159166666667 & 0.997035603396341 & 0.999398050761881 \tabularnewline
47 & 410.79 & 411.561557850347 & 413.574166666667 & 0.995133620572723 & 0.998125291744018 \tabularnewline
48 & 410.97 & 411.93908464026 & 414.97 & 0.992696061499049 & 0.997647504991893 \tabularnewline
49 & 410.97 & 412.194003819805 & 416.333333333333 & 0.990057655291765 & 0.997030515222294 \tabularnewline
50 & 413.8 & 416.422444837167 & 417.689166666667 & 0.996967309830876 & 0.993702441187596 \tabularnewline
51 & 423.31 & 421.970662434081 & 419.055 & 1.00695770825806 & 1.0031740063591 \tabularnewline
52 & 423.85 & 422.844217210836 & 420.449166666667 & 1.00569640930236 & 1.00237861308781 \tabularnewline
53 & 426.6 & 425.211677570856 & 421.880833333333 & 1.0078952253204 & 1.00326501482056 \tabularnewline
54 & 426.26 & 425.773333199581 & 423.352916666667 & 1.00571725488978 & 1.00114301850884 \tabularnewline
55 & 426.26 & NA & NA & 1.00224859893779 & NA \tabularnewline
56 & 426.32 & NA & NA & 1.00057433980748 & NA \tabularnewline
57 & 427.14 & NA & NA & 0.999020212893384 & NA \tabularnewline
58 & 427.55 & NA & NA & 0.997035603396341 & NA \tabularnewline
59 & 428.29 & NA & NA & 0.995133620572723 & NA \tabularnewline
60 & 428.8 & NA & NA & 0.992696061499049 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166221&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]369.82[/C][C]NA[/C][C]NA[/C][C]0.990057655291765[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]373.1[/C][C]NA[/C][C]NA[/C][C]0.996967309830876[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]374.55[/C][C]NA[/C][C]NA[/C][C]1.00695770825806[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]375.01[/C][C]NA[/C][C]NA[/C][C]1.00569640930236[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]374.81[/C][C]NA[/C][C]NA[/C][C]1.0078952253204[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]375.31[/C][C]NA[/C][C]NA[/C][C]1.00571725488978[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]375.31[/C][C]376.119678173545[/C][C]375.275833333333[/C][C]1.00224859893779[/C][C]0.997847285796167[/C][/ROW]
[ROW][C]8[/C][C]375.39[/C][C]376.167173768546[/C][C]375.95125[/C][C]1.00057433980748[/C][C]0.997933967069055[/C][/ROW]
[ROW][C]9[/C][C]375.59[/C][C]376.469944509899[/C][C]376.839166666667[/C][C]0.999020212893384[/C][C]0.997662643398946[/C][/ROW]
[ROW][C]10[/C][C]376.26[/C][C]376.746935434865[/C][C]377.867083333333[/C][C]0.997035603396341[/C][C]0.998707526487765[/C][/ROW]
[ROW][C]11[/C][C]377.18[/C][C]377.110446545128[/C][C]378.954583333333[/C][C]0.995133620572723[/C][C]1.00018443788951[/C][/ROW]
[ROW][C]12[/C][C]377.26[/C][C]377.337422546634[/C][C]380.11375[/C][C]0.992696061499049[/C][C]0.999794818796101[/C][/ROW]
[ROW][C]13[/C][C]377.26[/C][C]377.477219612976[/C][C]381.267916666667[/C][C]0.990057655291765[/C][C]0.999424549080873[/C][/ROW]
[ROW][C]14[/C][C]381.87[/C][C]381.269792895576[/C][C]382.429583333333[/C][C]0.996967309830876[/C][C]1.00157423198902[/C][/ROW]
[ROW][C]15[/C][C]387.09[/C][C]386.262263836403[/C][C]383.593333333333[/C][C]1.00695770825806[/C][C]1.00214293820829[/C][/ROW]
[ROW][C]16[/C][C]387.14[/C][C]386.89350385947[/C][C]384.702083333333[/C][C]1.00569640930236[/C][C]1.00063711625569[/C][/ROW]
[ROW][C]17[/C][C]388.78[/C][C]388.76828600499[/C][C]385.722916666667[/C][C]1.0078952253204[/C][C]1.00003013104574[/C][/ROW]
[ROW][C]18[/C][C]389.16[/C][C]388.917986296432[/C][C]386.707083333333[/C][C]1.00571725488978[/C][C]1.00062227439228[/C][/ROW]
[ROW][C]19[/C][C]389.16[/C][C]388.564682547273[/C][C]387.692916666667[/C][C]1.00224859893779[/C][C]1.00153209357275[/C][/ROW]
[ROW][C]20[/C][C]389.42[/C][C]388.821103919312[/C][C]388.597916666667[/C][C]1.00057433980748[/C][C]1.0015402869717[/C][/ROW]
[ROW][C]21[/C][C]389.49[/C][C]388.789945026984[/C][C]389.17125[/C][C]0.999020212893384[/C][C]1.00180059948044[/C][/ROW]
[ROW][C]22[/C][C]388.97[/C][C]388.37029341296[/C][C]389.525[/C][C]0.997035603396341[/C][C]1.00154416184042[/C][/ROW]
[ROW][C]23[/C][C]388.97[/C][C]387.987671656996[/C][C]389.885[/C][C]0.995133620572723[/C][C]1.00253185452726[/C][/ROW]
[ROW][C]24[/C][C]389.09[/C][C]387.364893637851[/C][C]390.215[/C][C]0.992696061499049[/C][C]1.00445344012966[/C][/ROW]
[ROW][C]25[/C][C]389.09[/C][C]386.657116697646[/C][C]390.54[/C][C]0.990057655291765[/C][C]1.00629209497845[/C][/ROW]
[ROW][C]26[/C][C]391.76[/C][C]389.677135138771[/C][C]390.8625[/C][C]0.996967309830876[/C][C]1.00534510412187[/C][/ROW]
[ROW][C]27[/C][C]390.96[/C][C]393.926890259094[/C][C]391.205[/C][C]1.00695770825806[/C][C]0.992468424135396[/C][/ROW]
[ROW][C]28[/C][C]391.76[/C][C]393.847475489626[/C][C]391.616666666667[/C][C]1.00569640930236[/C][C]0.994699787050735[/C][/ROW]
[ROW][C]29[/C][C]392.8[/C][C]395.174720030933[/C][C]392.079166666667[/C][C]1.0078952253204[/C][C]0.993990708639593[/C][/ROW]
[ROW][C]30[/C][C]393.06[/C][C]394.785089332146[/C][C]392.540833333333[/C][C]1.00571725488978[/C][C]0.995630307783245[/C][/ROW]
[ROW][C]31[/C][C]393.06[/C][C]393.881193761055[/C][C]392.9975[/C][C]1.00224859893779[/C][C]0.997915123204504[/C][/ROW]
[ROW][C]32[/C][C]393.26[/C][C]393.777282149158[/C][C]393.55125[/C][C]1.00057433980748[/C][C]0.998686358577278[/C][/ROW]
[ROW][C]33[/C][C]393.87[/C][C]394.122215413303[/C][C]394.50875[/C][C]0.999020212893384[/C][C]0.99936005786165[/C][/ROW]
[ROW][C]34[/C][C]394.47[/C][C]394.603843091694[/C][C]395.777083333333[/C][C]0.997035603396341[/C][C]0.999660816553014[/C][/ROW]
[ROW][C]35[/C][C]394.57[/C][C]395.175024231583[/C][C]397.1075[/C][C]0.995133620572723[/C][C]0.998468971482297[/C][/ROW]
[ROW][C]36[/C][C]394.57[/C][C]395.592689494243[/C][C]398.503333333333[/C][C]0.992696061499049[/C][C]0.997414791725423[/C][/ROW]
[ROW][C]37[/C][C]394.57[/C][C]395.930656735545[/C][C]399.906666666667[/C][C]0.990057655291765[/C][C]0.996563396361464[/C][/ROW]
[ROW][C]38[/C][C]399.57[/C][C]400.094612720412[/C][C]401.311666666667[/C][C]0.996967309830876[/C][C]0.99868877834459[/C][/ROW]
[ROW][C]39[/C][C]406.13[/C][C]405.511519126891[/C][C]402.709583333333[/C][C]1.00695770825806[/C][C]1.00152518694029[/C][/ROW]
[ROW][C]40[/C][C]407.03[/C][C]406.381805070897[/C][C]404.08[/C][C]1.00569640930236[/C][C]1.00159503924884[/C][/ROW]
[ROW][C]41[/C][C]409.46[/C][C]408.632641027024[/C][C]405.431666666667[/C][C]1.0078952253204[/C][C]1.00202470113718[/C][/ROW]
[ROW][C]42[/C][C]409.9[/C][C]409.116560214325[/C][C]406.790833333333[/C][C]1.00571725488978[/C][C]1.00191495495871[/C][/ROW]
[ROW][C]43[/C][C]409.9[/C][C]409.075282520952[/C][C]408.1575[/C][C]1.00224859893779[/C][C]1.00201605306966[/C][/ROW]
[ROW][C]44[/C][C]410.14[/C][C]409.66890410115[/C][C]409.43375[/C][C]1.00057433980748[/C][C]1.00114994302505[/C][/ROW]
[ROW][C]45[/C][C]410.54[/C][C]410.340059794361[/C][C]410.7425[/C][C]0.999020212893384[/C][C]1.00048725490204[/C][/ROW]
[ROW][C]46[/C][C]410.69[/C][C]410.937363432833[/C][C]412.159166666667[/C][C]0.997035603396341[/C][C]0.999398050761881[/C][/ROW]
[ROW][C]47[/C][C]410.79[/C][C]411.561557850347[/C][C]413.574166666667[/C][C]0.995133620572723[/C][C]0.998125291744018[/C][/ROW]
[ROW][C]48[/C][C]410.97[/C][C]411.93908464026[/C][C]414.97[/C][C]0.992696061499049[/C][C]0.997647504991893[/C][/ROW]
[ROW][C]49[/C][C]410.97[/C][C]412.194003819805[/C][C]416.333333333333[/C][C]0.990057655291765[/C][C]0.997030515222294[/C][/ROW]
[ROW][C]50[/C][C]413.8[/C][C]416.422444837167[/C][C]417.689166666667[/C][C]0.996967309830876[/C][C]0.993702441187596[/C][/ROW]
[ROW][C]51[/C][C]423.31[/C][C]421.970662434081[/C][C]419.055[/C][C]1.00695770825806[/C][C]1.0031740063591[/C][/ROW]
[ROW][C]52[/C][C]423.85[/C][C]422.844217210836[/C][C]420.449166666667[/C][C]1.00569640930236[/C][C]1.00237861308781[/C][/ROW]
[ROW][C]53[/C][C]426.6[/C][C]425.211677570856[/C][C]421.880833333333[/C][C]1.0078952253204[/C][C]1.00326501482056[/C][/ROW]
[ROW][C]54[/C][C]426.26[/C][C]425.773333199581[/C][C]423.352916666667[/C][C]1.00571725488978[/C][C]1.00114301850884[/C][/ROW]
[ROW][C]55[/C][C]426.26[/C][C]NA[/C][C]NA[/C][C]1.00224859893779[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]426.32[/C][C]NA[/C][C]NA[/C][C]1.00057433980748[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]427.14[/C][C]NA[/C][C]NA[/C][C]0.999020212893384[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]427.55[/C][C]NA[/C][C]NA[/C][C]0.997035603396341[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]428.29[/C][C]NA[/C][C]NA[/C][C]0.995133620572723[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]428.8[/C][C]NA[/C][C]NA[/C][C]0.992696061499049[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166221&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166221&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	369.82	NA	NA	0.990057655291765	NA
2	373.1	NA	NA	0.996967309830876	NA
3	374.55	NA	NA	1.00695770825806	NA
4	375.01	NA	NA	1.00569640930236	NA
5	374.81	NA	NA	1.0078952253204	NA
6	375.31	NA	NA	1.00571725488978	NA
7	375.31	376.119678173545	375.275833333333	1.00224859893779	0.997847285796167
8	375.39	376.167173768546	375.95125	1.00057433980748	0.997933967069055
9	375.59	376.469944509899	376.839166666667	0.999020212893384	0.997662643398946
10	376.26	376.746935434865	377.867083333333	0.997035603396341	0.998707526487765
11	377.18	377.110446545128	378.954583333333	0.995133620572723	1.00018443788951
12	377.26	377.337422546634	380.11375	0.992696061499049	0.999794818796101
13	377.26	377.477219612976	381.267916666667	0.990057655291765	0.999424549080873
14	381.87	381.269792895576	382.429583333333	0.996967309830876	1.00157423198902
15	387.09	386.262263836403	383.593333333333	1.00695770825806	1.00214293820829
16	387.14	386.89350385947	384.702083333333	1.00569640930236	1.00063711625569
17	388.78	388.76828600499	385.722916666667	1.0078952253204	1.00003013104574
18	389.16	388.917986296432	386.707083333333	1.00571725488978	1.00062227439228
19	389.16	388.564682547273	387.692916666667	1.00224859893779	1.00153209357275
20	389.42	388.821103919312	388.597916666667	1.00057433980748	1.0015402869717
21	389.49	388.789945026984	389.17125	0.999020212893384	1.00180059948044
22	388.97	388.37029341296	389.525	0.997035603396341	1.00154416184042
23	388.97	387.987671656996	389.885	0.995133620572723	1.00253185452726
24	389.09	387.364893637851	390.215	0.992696061499049	1.00445344012966
25	389.09	386.657116697646	390.54	0.990057655291765	1.00629209497845
26	391.76	389.677135138771	390.8625	0.996967309830876	1.00534510412187
27	390.96	393.926890259094	391.205	1.00695770825806	0.992468424135396
28	391.76	393.847475489626	391.616666666667	1.00569640930236	0.994699787050735
29	392.8	395.174720030933	392.079166666667	1.0078952253204	0.993990708639593
30	393.06	394.785089332146	392.540833333333	1.00571725488978	0.995630307783245
31	393.06	393.881193761055	392.9975	1.00224859893779	0.997915123204504
32	393.26	393.777282149158	393.55125	1.00057433980748	0.998686358577278
33	393.87	394.122215413303	394.50875	0.999020212893384	0.99936005786165
34	394.47	394.603843091694	395.777083333333	0.997035603396341	0.999660816553014
35	394.57	395.175024231583	397.1075	0.995133620572723	0.998468971482297
36	394.57	395.592689494243	398.503333333333	0.992696061499049	0.997414791725423
37	394.57	395.930656735545	399.906666666667	0.990057655291765	0.996563396361464
38	399.57	400.094612720412	401.311666666667	0.996967309830876	0.99868877834459
39	406.13	405.511519126891	402.709583333333	1.00695770825806	1.00152518694029
40	407.03	406.381805070897	404.08	1.00569640930236	1.00159503924884
41	409.46	408.632641027024	405.431666666667	1.0078952253204	1.00202470113718
42	409.9	409.116560214325	406.790833333333	1.00571725488978	1.00191495495871
43	409.9	409.075282520952	408.1575	1.00224859893779	1.00201605306966
44	410.14	409.66890410115	409.43375	1.00057433980748	1.00114994302505
45	410.54	410.340059794361	410.7425	0.999020212893384	1.00048725490204
46	410.69	410.937363432833	412.159166666667	0.997035603396341	0.999398050761881
47	410.79	411.561557850347	413.574166666667	0.995133620572723	0.998125291744018
48	410.97	411.93908464026	414.97	0.992696061499049	0.997647504991893
49	410.97	412.194003819805	416.333333333333	0.990057655291765	0.997030515222294
50	413.8	416.422444837167	417.689166666667	0.996967309830876	0.993702441187596
51	423.31	421.970662434081	419.055	1.00695770825806	1.0031740063591
52	423.85	422.844217210836	420.449166666667	1.00569640930236	1.00237861308781
53	426.6	425.211677570856	421.880833333333	1.0078952253204	1.00326501482056
54	426.26	425.773333199581	423.352916666667	1.00571725488978	1.00114301850884
55	426.26	NA	NA	1.00224859893779	NA
56	426.32	NA	NA	1.00057433980748	NA
57	427.14	NA	NA	0.999020212893384	NA
58	427.55	NA	NA	0.997035603396341	NA
59	428.29	NA	NA	0.995133620572723	NA
60	428.8	NA	NA	0.992696061499049	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

multiplicatief model over de gegevens van de evolutie van de prijzen van da...

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code