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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 05 Dec 2011 15:13:36 -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/2011/Dec/05/t13231160676iykhzmusm6ijay.htm/, Retrieved Fri, 03 May 2024 08:41:38 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151249, Retrieved Fri, 03 May 2024 08:41:38 +0000

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No (this computation is public)

User-defined keywords

KDGP2W92

Estimated Impact

114

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

-       [Classical Decomposition] [] [2011-12-05 20:13:36] [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	1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151249&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]1 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=151249&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151249&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	1 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	99.96	NA	NA	-0.0274739583333368	NA
2	100.21	NA	NA	0.0600260416666547	NA
3	100.37	NA	NA	0.0631510416666661	NA
4	101.11	NA	NA	0.00388020833332625	NA
5	101.04	NA	NA	0.0316927083333329	NA
6	101.02	NA	NA	-0.0319531249999923	NA
7	101.02	100.821380208333	100.892083333333	-0.070703124999989	0.198619791666687
8	101.11	100.836067708333	100.974166666667	-0.138098958333329	0.273932291666682
9	100.96	100.853880208333	101.04625	-0.192369791666662	0.106119791666657
10	101.27	101.226380208333	101.09	0.13638020833333	0.0436197916666572
11	101.01	101.236276041667	101.12375	0.112526041666664	-0.226276041666651
12	101.07	101.229609375	101.176666666667	0.0529427083333349	-0.159609374999988
13	101.07	101.202526041667	101.23	-0.0274739583333368	-0.132526041666651
14	101.07	101.339609375	101.279583333333	0.0600260416666547	-0.269609375000002
15	101.24	101.400651041667	101.3375	0.0631510416666661	-0.160651041666668
16	101.29	101.420130208333	101.41625	0.00388020833332625	-0.130130208333313
17	101.67	101.548776041667	101.517083333333	0.0316927083333329	0.121223958333346
18	101.66	101.597630208333	101.629583333333	-0.0319531249999923	0.0623697916666686
19	101.66	101.669296875	101.74	-0.070703124999989	-0.00929687499998977
20	101.66	101.728151041667	101.86625	-0.138098958333329	-0.0681510416666526
21	101.8	101.810546875	102.002916666667	-0.192369791666662	-0.0105468749999886
22	102.32	102.268463541667	102.132083333333	0.13638020833333	0.0515364583333451
23	102.38	102.362109375	102.249583333333	0.112526041666664	0.0178906250000068
24	102.4	102.411276041667	102.358333333333	0.0529427083333349	-0.0112760416666475
25	102.39	102.440859375	102.468333333333	-0.0274739583333368	-0.0508593750000017
26	102.78	102.640442708333	102.580416666667	0.0600260416666547	0.139557291666677
27	102.81	102.761484375	102.698333333333	0.0631510416666661	0.0485156249999932
28	102.82	102.810963541667	102.807083333333	0.00388020833332625	0.0090364583333411
29	102.96	102.936692708333	102.905	0.0316927083333329	0.0233072916666686
30	102.98	102.969713541667	103.001666666667	-0.0319531249999923	0.01028645833334
31	102.98	103.024713541667	103.095416666667	-0.070703124999989	-0.0447135416666526
32	103.03	103.035234375	103.173333333333	-0.138098958333329	-0.00523437499998636
33	103.26	103.042213541667	103.234583333333	-0.192369791666662	0.217786458333364
34	103.47	103.439713541667	103.303333333333	0.13638020833333	0.0302864583333502
35	103.58	103.495026041667	103.3825	0.112526041666664	0.084973958333336
36	103.52	103.514609375	103.461666666667	0.0529427083333349	0.00539062500000398
37	103.52	103.510859375	103.538333333333	-0.0274739583333368	0.00914062500000057
38	103.52	103.672942708333	103.612916666667	0.0600260416666547	-0.152942708333327
39	103.54	103.737734375	103.674583333333	0.0631510416666661	-0.197734374999982
40	103.74	103.747213541667	103.743333333333	0.00388020833332625	-0.00721354166665833
41	103.94	103.870026041667	103.838333333333	0.0316927083333329	0.0699739583333354
42	103.9	103.914296875	103.94625	-0.0319531249999923	-0.0142968749999852
43	103.9	103.988046875	104.05875	-0.070703124999989	-0.088046874999975
44	103.9	104.043984375	104.182083333333	-0.138098958333329	-0.143984374999988
45	103.87	104.126796875	104.319166666667	-0.192369791666662	-0.256796874999978
46	104.51	104.578880208333	104.4425	0.13638020833333	-0.0688802083333258
47	104.82	104.640026041667	104.5275	0.112526041666664	0.179973958333335
48	104.87	104.647942708333	104.595	0.0529427083333349	0.222057291666687
49	104.87	104.639192708333	104.666666666667	-0.0274739583333368	0.230807291666679
50	105.13	104.790442708333	104.730416666667	0.0600260416666547	0.339557291666679
51	105.22	104.853567708333	104.790416666667	0.0631510416666661	0.366432291666683
52	105.02	104.835130208333	104.83125	0.00388020833332625	0.184869791666671
53	104.7	104.857942708333	104.82625	0.0316927083333329	-0.157942708333323
54	104.76	104.761796875	104.79375	-0.0319531249999923	-0.00179687499999659
55	104.76	NA	NA	-0.070703124999989	NA
56	104.57	NA	NA	-0.138098958333329	NA
57	104.64	NA	NA	-0.192369791666662	NA
58	104.72	NA	NA	0.13638020833333	NA
59	104.49	NA	NA	0.112526041666664	NA
60	104.42	NA	NA	0.0529427083333349	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 99.96 & NA & NA & -0.0274739583333368 & NA \tabularnewline
2 & 100.21 & NA & NA & 0.0600260416666547 & NA \tabularnewline
3 & 100.37 & NA & NA & 0.0631510416666661 & NA \tabularnewline
4 & 101.11 & NA & NA & 0.00388020833332625 & NA \tabularnewline
5 & 101.04 & NA & NA & 0.0316927083333329 & NA \tabularnewline
6 & 101.02 & NA & NA & -0.0319531249999923 & NA \tabularnewline
7 & 101.02 & 100.821380208333 & 100.892083333333 & -0.070703124999989 & 0.198619791666687 \tabularnewline
8 & 101.11 & 100.836067708333 & 100.974166666667 & -0.138098958333329 & 0.273932291666682 \tabularnewline
9 & 100.96 & 100.853880208333 & 101.04625 & -0.192369791666662 & 0.106119791666657 \tabularnewline
10 & 101.27 & 101.226380208333 & 101.09 & 0.13638020833333 & 0.0436197916666572 \tabularnewline
11 & 101.01 & 101.236276041667 & 101.12375 & 0.112526041666664 & -0.226276041666651 \tabularnewline
12 & 101.07 & 101.229609375 & 101.176666666667 & 0.0529427083333349 & -0.159609374999988 \tabularnewline
13 & 101.07 & 101.202526041667 & 101.23 & -0.0274739583333368 & -0.132526041666651 \tabularnewline
14 & 101.07 & 101.339609375 & 101.279583333333 & 0.0600260416666547 & -0.269609375000002 \tabularnewline
15 & 101.24 & 101.400651041667 & 101.3375 & 0.0631510416666661 & -0.160651041666668 \tabularnewline
16 & 101.29 & 101.420130208333 & 101.41625 & 0.00388020833332625 & -0.130130208333313 \tabularnewline
17 & 101.67 & 101.548776041667 & 101.517083333333 & 0.0316927083333329 & 0.121223958333346 \tabularnewline
18 & 101.66 & 101.597630208333 & 101.629583333333 & -0.0319531249999923 & 0.0623697916666686 \tabularnewline
19 & 101.66 & 101.669296875 & 101.74 & -0.070703124999989 & -0.00929687499998977 \tabularnewline
20 & 101.66 & 101.728151041667 & 101.86625 & -0.138098958333329 & -0.0681510416666526 \tabularnewline
21 & 101.8 & 101.810546875 & 102.002916666667 & -0.192369791666662 & -0.0105468749999886 \tabularnewline
22 & 102.32 & 102.268463541667 & 102.132083333333 & 0.13638020833333 & 0.0515364583333451 \tabularnewline
23 & 102.38 & 102.362109375 & 102.249583333333 & 0.112526041666664 & 0.0178906250000068 \tabularnewline
24 & 102.4 & 102.411276041667 & 102.358333333333 & 0.0529427083333349 & -0.0112760416666475 \tabularnewline
25 & 102.39 & 102.440859375 & 102.468333333333 & -0.0274739583333368 & -0.0508593750000017 \tabularnewline
26 & 102.78 & 102.640442708333 & 102.580416666667 & 0.0600260416666547 & 0.139557291666677 \tabularnewline
27 & 102.81 & 102.761484375 & 102.698333333333 & 0.0631510416666661 & 0.0485156249999932 \tabularnewline
28 & 102.82 & 102.810963541667 & 102.807083333333 & 0.00388020833332625 & 0.0090364583333411 \tabularnewline
29 & 102.96 & 102.936692708333 & 102.905 & 0.0316927083333329 & 0.0233072916666686 \tabularnewline
30 & 102.98 & 102.969713541667 & 103.001666666667 & -0.0319531249999923 & 0.01028645833334 \tabularnewline
31 & 102.98 & 103.024713541667 & 103.095416666667 & -0.070703124999989 & -0.0447135416666526 \tabularnewline
32 & 103.03 & 103.035234375 & 103.173333333333 & -0.138098958333329 & -0.00523437499998636 \tabularnewline
33 & 103.26 & 103.042213541667 & 103.234583333333 & -0.192369791666662 & 0.217786458333364 \tabularnewline
34 & 103.47 & 103.439713541667 & 103.303333333333 & 0.13638020833333 & 0.0302864583333502 \tabularnewline
35 & 103.58 & 103.495026041667 & 103.3825 & 0.112526041666664 & 0.084973958333336 \tabularnewline
36 & 103.52 & 103.514609375 & 103.461666666667 & 0.0529427083333349 & 0.00539062500000398 \tabularnewline
37 & 103.52 & 103.510859375 & 103.538333333333 & -0.0274739583333368 & 0.00914062500000057 \tabularnewline
38 & 103.52 & 103.672942708333 & 103.612916666667 & 0.0600260416666547 & -0.152942708333327 \tabularnewline
39 & 103.54 & 103.737734375 & 103.674583333333 & 0.0631510416666661 & -0.197734374999982 \tabularnewline
40 & 103.74 & 103.747213541667 & 103.743333333333 & 0.00388020833332625 & -0.00721354166665833 \tabularnewline
41 & 103.94 & 103.870026041667 & 103.838333333333 & 0.0316927083333329 & 0.0699739583333354 \tabularnewline
42 & 103.9 & 103.914296875 & 103.94625 & -0.0319531249999923 & -0.0142968749999852 \tabularnewline
43 & 103.9 & 103.988046875 & 104.05875 & -0.070703124999989 & -0.088046874999975 \tabularnewline
44 & 103.9 & 104.043984375 & 104.182083333333 & -0.138098958333329 & -0.143984374999988 \tabularnewline
45 & 103.87 & 104.126796875 & 104.319166666667 & -0.192369791666662 & -0.256796874999978 \tabularnewline
46 & 104.51 & 104.578880208333 & 104.4425 & 0.13638020833333 & -0.0688802083333258 \tabularnewline
47 & 104.82 & 104.640026041667 & 104.5275 & 0.112526041666664 & 0.179973958333335 \tabularnewline
48 & 104.87 & 104.647942708333 & 104.595 & 0.0529427083333349 & 0.222057291666687 \tabularnewline
49 & 104.87 & 104.639192708333 & 104.666666666667 & -0.0274739583333368 & 0.230807291666679 \tabularnewline
50 & 105.13 & 104.790442708333 & 104.730416666667 & 0.0600260416666547 & 0.339557291666679 \tabularnewline
51 & 105.22 & 104.853567708333 & 104.790416666667 & 0.0631510416666661 & 0.366432291666683 \tabularnewline
52 & 105.02 & 104.835130208333 & 104.83125 & 0.00388020833332625 & 0.184869791666671 \tabularnewline
53 & 104.7 & 104.857942708333 & 104.82625 & 0.0316927083333329 & -0.157942708333323 \tabularnewline
54 & 104.76 & 104.761796875 & 104.79375 & -0.0319531249999923 & -0.00179687499999659 \tabularnewline
55 & 104.76 & NA & NA & -0.070703124999989 & NA \tabularnewline
56 & 104.57 & NA & NA & -0.138098958333329 & NA \tabularnewline
57 & 104.64 & NA & NA & -0.192369791666662 & NA \tabularnewline
58 & 104.72 & NA & NA & 0.13638020833333 & NA \tabularnewline
59 & 104.49 & NA & NA & 0.112526041666664 & NA \tabularnewline
60 & 104.42 & NA & NA & 0.0529427083333349 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151249&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]99.96[/C][C]NA[/C][C]NA[/C][C]-0.0274739583333368[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]100.21[/C][C]NA[/C][C]NA[/C][C]0.0600260416666547[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100.37[/C][C]NA[/C][C]NA[/C][C]0.0631510416666661[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]101.11[/C][C]NA[/C][C]NA[/C][C]0.00388020833332625[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]101.04[/C][C]NA[/C][C]NA[/C][C]0.0316927083333329[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]101.02[/C][C]NA[/C][C]NA[/C][C]-0.0319531249999923[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]101.02[/C][C]100.821380208333[/C][C]100.892083333333[/C][C]-0.070703124999989[/C][C]0.198619791666687[/C][/ROW]
[ROW][C]8[/C][C]101.11[/C][C]100.836067708333[/C][C]100.974166666667[/C][C]-0.138098958333329[/C][C]0.273932291666682[/C][/ROW]
[ROW][C]9[/C][C]100.96[/C][C]100.853880208333[/C][C]101.04625[/C][C]-0.192369791666662[/C][C]0.106119791666657[/C][/ROW]
[ROW][C]10[/C][C]101.27[/C][C]101.226380208333[/C][C]101.09[/C][C]0.13638020833333[/C][C]0.0436197916666572[/C][/ROW]
[ROW][C]11[/C][C]101.01[/C][C]101.236276041667[/C][C]101.12375[/C][C]0.112526041666664[/C][C]-0.226276041666651[/C][/ROW]
[ROW][C]12[/C][C]101.07[/C][C]101.229609375[/C][C]101.176666666667[/C][C]0.0529427083333349[/C][C]-0.159609374999988[/C][/ROW]
[ROW][C]13[/C][C]101.07[/C][C]101.202526041667[/C][C]101.23[/C][C]-0.0274739583333368[/C][C]-0.132526041666651[/C][/ROW]
[ROW][C]14[/C][C]101.07[/C][C]101.339609375[/C][C]101.279583333333[/C][C]0.0600260416666547[/C][C]-0.269609375000002[/C][/ROW]
[ROW][C]15[/C][C]101.24[/C][C]101.400651041667[/C][C]101.3375[/C][C]0.0631510416666661[/C][C]-0.160651041666668[/C][/ROW]
[ROW][C]16[/C][C]101.29[/C][C]101.420130208333[/C][C]101.41625[/C][C]0.00388020833332625[/C][C]-0.130130208333313[/C][/ROW]
[ROW][C]17[/C][C]101.67[/C][C]101.548776041667[/C][C]101.517083333333[/C][C]0.0316927083333329[/C][C]0.121223958333346[/C][/ROW]
[ROW][C]18[/C][C]101.66[/C][C]101.597630208333[/C][C]101.629583333333[/C][C]-0.0319531249999923[/C][C]0.0623697916666686[/C][/ROW]
[ROW][C]19[/C][C]101.66[/C][C]101.669296875[/C][C]101.74[/C][C]-0.070703124999989[/C][C]-0.00929687499998977[/C][/ROW]
[ROW][C]20[/C][C]101.66[/C][C]101.728151041667[/C][C]101.86625[/C][C]-0.138098958333329[/C][C]-0.0681510416666526[/C][/ROW]
[ROW][C]21[/C][C]101.8[/C][C]101.810546875[/C][C]102.002916666667[/C][C]-0.192369791666662[/C][C]-0.0105468749999886[/C][/ROW]
[ROW][C]22[/C][C]102.32[/C][C]102.268463541667[/C][C]102.132083333333[/C][C]0.13638020833333[/C][C]0.0515364583333451[/C][/ROW]
[ROW][C]23[/C][C]102.38[/C][C]102.362109375[/C][C]102.249583333333[/C][C]0.112526041666664[/C][C]0.0178906250000068[/C][/ROW]
[ROW][C]24[/C][C]102.4[/C][C]102.411276041667[/C][C]102.358333333333[/C][C]0.0529427083333349[/C][C]-0.0112760416666475[/C][/ROW]
[ROW][C]25[/C][C]102.39[/C][C]102.440859375[/C][C]102.468333333333[/C][C]-0.0274739583333368[/C][C]-0.0508593750000017[/C][/ROW]
[ROW][C]26[/C][C]102.78[/C][C]102.640442708333[/C][C]102.580416666667[/C][C]0.0600260416666547[/C][C]0.139557291666677[/C][/ROW]
[ROW][C]27[/C][C]102.81[/C][C]102.761484375[/C][C]102.698333333333[/C][C]0.0631510416666661[/C][C]0.0485156249999932[/C][/ROW]
[ROW][C]28[/C][C]102.82[/C][C]102.810963541667[/C][C]102.807083333333[/C][C]0.00388020833332625[/C][C]0.0090364583333411[/C][/ROW]
[ROW][C]29[/C][C]102.96[/C][C]102.936692708333[/C][C]102.905[/C][C]0.0316927083333329[/C][C]0.0233072916666686[/C][/ROW]
[ROW][C]30[/C][C]102.98[/C][C]102.969713541667[/C][C]103.001666666667[/C][C]-0.0319531249999923[/C][C]0.01028645833334[/C][/ROW]
[ROW][C]31[/C][C]102.98[/C][C]103.024713541667[/C][C]103.095416666667[/C][C]-0.070703124999989[/C][C]-0.0447135416666526[/C][/ROW]
[ROW][C]32[/C][C]103.03[/C][C]103.035234375[/C][C]103.173333333333[/C][C]-0.138098958333329[/C][C]-0.00523437499998636[/C][/ROW]
[ROW][C]33[/C][C]103.26[/C][C]103.042213541667[/C][C]103.234583333333[/C][C]-0.192369791666662[/C][C]0.217786458333364[/C][/ROW]
[ROW][C]34[/C][C]103.47[/C][C]103.439713541667[/C][C]103.303333333333[/C][C]0.13638020833333[/C][C]0.0302864583333502[/C][/ROW]
[ROW][C]35[/C][C]103.58[/C][C]103.495026041667[/C][C]103.3825[/C][C]0.112526041666664[/C][C]0.084973958333336[/C][/ROW]
[ROW][C]36[/C][C]103.52[/C][C]103.514609375[/C][C]103.461666666667[/C][C]0.0529427083333349[/C][C]0.00539062500000398[/C][/ROW]
[ROW][C]37[/C][C]103.52[/C][C]103.510859375[/C][C]103.538333333333[/C][C]-0.0274739583333368[/C][C]0.00914062500000057[/C][/ROW]
[ROW][C]38[/C][C]103.52[/C][C]103.672942708333[/C][C]103.612916666667[/C][C]0.0600260416666547[/C][C]-0.152942708333327[/C][/ROW]
[ROW][C]39[/C][C]103.54[/C][C]103.737734375[/C][C]103.674583333333[/C][C]0.0631510416666661[/C][C]-0.197734374999982[/C][/ROW]
[ROW][C]40[/C][C]103.74[/C][C]103.747213541667[/C][C]103.743333333333[/C][C]0.00388020833332625[/C][C]-0.00721354166665833[/C][/ROW]
[ROW][C]41[/C][C]103.94[/C][C]103.870026041667[/C][C]103.838333333333[/C][C]0.0316927083333329[/C][C]0.0699739583333354[/C][/ROW]
[ROW][C]42[/C][C]103.9[/C][C]103.914296875[/C][C]103.94625[/C][C]-0.0319531249999923[/C][C]-0.0142968749999852[/C][/ROW]
[ROW][C]43[/C][C]103.9[/C][C]103.988046875[/C][C]104.05875[/C][C]-0.070703124999989[/C][C]-0.088046874999975[/C][/ROW]
[ROW][C]44[/C][C]103.9[/C][C]104.043984375[/C][C]104.182083333333[/C][C]-0.138098958333329[/C][C]-0.143984374999988[/C][/ROW]
[ROW][C]45[/C][C]103.87[/C][C]104.126796875[/C][C]104.319166666667[/C][C]-0.192369791666662[/C][C]-0.256796874999978[/C][/ROW]
[ROW][C]46[/C][C]104.51[/C][C]104.578880208333[/C][C]104.4425[/C][C]0.13638020833333[/C][C]-0.0688802083333258[/C][/ROW]
[ROW][C]47[/C][C]104.82[/C][C]104.640026041667[/C][C]104.5275[/C][C]0.112526041666664[/C][C]0.179973958333335[/C][/ROW]
[ROW][C]48[/C][C]104.87[/C][C]104.647942708333[/C][C]104.595[/C][C]0.0529427083333349[/C][C]0.222057291666687[/C][/ROW]
[ROW][C]49[/C][C]104.87[/C][C]104.639192708333[/C][C]104.666666666667[/C][C]-0.0274739583333368[/C][C]0.230807291666679[/C][/ROW]
[ROW][C]50[/C][C]105.13[/C][C]104.790442708333[/C][C]104.730416666667[/C][C]0.0600260416666547[/C][C]0.339557291666679[/C][/ROW]
[ROW][C]51[/C][C]105.22[/C][C]104.853567708333[/C][C]104.790416666667[/C][C]0.0631510416666661[/C][C]0.366432291666683[/C][/ROW]
[ROW][C]52[/C][C]105.02[/C][C]104.835130208333[/C][C]104.83125[/C][C]0.00388020833332625[/C][C]0.184869791666671[/C][/ROW]
[ROW][C]53[/C][C]104.7[/C][C]104.857942708333[/C][C]104.82625[/C][C]0.0316927083333329[/C][C]-0.157942708333323[/C][/ROW]
[ROW][C]54[/C][C]104.76[/C][C]104.761796875[/C][C]104.79375[/C][C]-0.0319531249999923[/C][C]-0.00179687499999659[/C][/ROW]
[ROW][C]55[/C][C]104.76[/C][C]NA[/C][C]NA[/C][C]-0.070703124999989[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]104.57[/C][C]NA[/C][C]NA[/C][C]-0.138098958333329[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]104.64[/C][C]NA[/C][C]NA[/C][C]-0.192369791666662[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]104.72[/C][C]NA[/C][C]NA[/C][C]0.13638020833333[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]104.49[/C][C]NA[/C][C]NA[/C][C]0.112526041666664[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]104.42[/C][C]NA[/C][C]NA[/C][C]0.0529427083333349[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151249&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151249&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	99.96	NA	NA	-0.0274739583333368	NA
2	100.21	NA	NA	0.0600260416666547	NA
3	100.37	NA	NA	0.0631510416666661	NA
4	101.11	NA	NA	0.00388020833332625	NA
5	101.04	NA	NA	0.0316927083333329	NA
6	101.02	NA	NA	-0.0319531249999923	NA
7	101.02	100.821380208333	100.892083333333	-0.070703124999989	0.198619791666687
8	101.11	100.836067708333	100.974166666667	-0.138098958333329	0.273932291666682
9	100.96	100.853880208333	101.04625	-0.192369791666662	0.106119791666657
10	101.27	101.226380208333	101.09	0.13638020833333	0.0436197916666572
11	101.01	101.236276041667	101.12375	0.112526041666664	-0.226276041666651
12	101.07	101.229609375	101.176666666667	0.0529427083333349	-0.159609374999988
13	101.07	101.202526041667	101.23	-0.0274739583333368	-0.132526041666651
14	101.07	101.339609375	101.279583333333	0.0600260416666547	-0.269609375000002
15	101.24	101.400651041667	101.3375	0.0631510416666661	-0.160651041666668
16	101.29	101.420130208333	101.41625	0.00388020833332625	-0.130130208333313
17	101.67	101.548776041667	101.517083333333	0.0316927083333329	0.121223958333346
18	101.66	101.597630208333	101.629583333333	-0.0319531249999923	0.0623697916666686
19	101.66	101.669296875	101.74	-0.070703124999989	-0.00929687499998977
20	101.66	101.728151041667	101.86625	-0.138098958333329	-0.0681510416666526
21	101.8	101.810546875	102.002916666667	-0.192369791666662	-0.0105468749999886
22	102.32	102.268463541667	102.132083333333	0.13638020833333	0.0515364583333451
23	102.38	102.362109375	102.249583333333	0.112526041666664	0.0178906250000068
24	102.4	102.411276041667	102.358333333333	0.0529427083333349	-0.0112760416666475
25	102.39	102.440859375	102.468333333333	-0.0274739583333368	-0.0508593750000017
26	102.78	102.640442708333	102.580416666667	0.0600260416666547	0.139557291666677
27	102.81	102.761484375	102.698333333333	0.0631510416666661	0.0485156249999932
28	102.82	102.810963541667	102.807083333333	0.00388020833332625	0.0090364583333411
29	102.96	102.936692708333	102.905	0.0316927083333329	0.0233072916666686
30	102.98	102.969713541667	103.001666666667	-0.0319531249999923	0.01028645833334
31	102.98	103.024713541667	103.095416666667	-0.070703124999989	-0.0447135416666526
32	103.03	103.035234375	103.173333333333	-0.138098958333329	-0.00523437499998636
33	103.26	103.042213541667	103.234583333333	-0.192369791666662	0.217786458333364
34	103.47	103.439713541667	103.303333333333	0.13638020833333	0.0302864583333502
35	103.58	103.495026041667	103.3825	0.112526041666664	0.084973958333336
36	103.52	103.514609375	103.461666666667	0.0529427083333349	0.00539062500000398
37	103.52	103.510859375	103.538333333333	-0.0274739583333368	0.00914062500000057
38	103.52	103.672942708333	103.612916666667	0.0600260416666547	-0.152942708333327
39	103.54	103.737734375	103.674583333333	0.0631510416666661	-0.197734374999982
40	103.74	103.747213541667	103.743333333333	0.00388020833332625	-0.00721354166665833
41	103.94	103.870026041667	103.838333333333	0.0316927083333329	0.0699739583333354
42	103.9	103.914296875	103.94625	-0.0319531249999923	-0.0142968749999852
43	103.9	103.988046875	104.05875	-0.070703124999989	-0.088046874999975
44	103.9	104.043984375	104.182083333333	-0.138098958333329	-0.143984374999988
45	103.87	104.126796875	104.319166666667	-0.192369791666662	-0.256796874999978
46	104.51	104.578880208333	104.4425	0.13638020833333	-0.0688802083333258
47	104.82	104.640026041667	104.5275	0.112526041666664	0.179973958333335
48	104.87	104.647942708333	104.595	0.0529427083333349	0.222057291666687
49	104.87	104.639192708333	104.666666666667	-0.0274739583333368	0.230807291666679
50	105.13	104.790442708333	104.730416666667	0.0600260416666547	0.339557291666679
51	105.22	104.853567708333	104.790416666667	0.0631510416666661	0.366432291666683
52	105.02	104.835130208333	104.83125	0.00388020833332625	0.184869791666671
53	104.7	104.857942708333	104.82625	0.0316927083333329	-0.157942708333323
54	104.76	104.761796875	104.79375	-0.0319531249999923	-0.00179687499999659
55	104.76	NA	NA	-0.070703124999989	NA
56	104.57	NA	NA	-0.138098958333329	NA
57	104.64	NA	NA	-0.192369791666662	NA
58	104.72	NA	NA	0.13638020833333	NA
59	104.49	NA	NA	0.112526041666664	NA
60	104.42	NA	NA	0.0529427083333349	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 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; 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