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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 06 May 2012 15:03:30 -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/06/t1336331031lq8qlm75l5wts1c.htm/, Retrieved Sun, 28 Apr 2024 00:57:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166260, Retrieved Sun, 28 Apr 2024 00:57:59 +0000

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Estimated Impact

142

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

-       [Classical Decomposition] [] [2012-05-06 19:03:30] [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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166260&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166260&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166260&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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	98.19	NA	NA	-0.0112760416666641	NA
2	98.19	NA	NA	-0.151276041666665	NA
3	98.19	NA	NA	-0.255026041666666	NA
4	98.19	NA	NA	-0.0773177083333311	NA
5	98.19	NA	NA	-0.157109374999996	NA
6	98.19	NA	NA	-0.236901041666665	NA
7	98.19	99.3809114583333	100.102083333333	-0.721171875000005	-1.19091145833335
8	100.48	100.627578125	100.484583333333	0.142994791666664	-0.14757812500001
9	102.78	101.454244791667	100.867083333333	0.587161458333328	1.32575520833332
10	102.78	101.695182291667	101.249583333333	0.445598958333332	1.08481770833332
11	102.78	101.925390625	101.632083333333	0.293307291666666	0.854609374999995
12	102.78	102.155598958333	102.014583333333	0.141015625000003	0.624401041666658
13	102.78	102.385807291667	102.397083333333	-0.0112760416666641	0.394192708333335
14	102.78	102.486640625	102.637916666667	-0.151276041666665	0.293359375000009
15	102.78	102.386223958333	102.64125	-0.255026041666666	0.393776041666683
16	102.78	102.471432291667	102.54875	-0.0773177083333311	0.308567708333342
17	102.78	102.299140625	102.45625	-0.157109374999996	0.480859375000009
18	102.78	102.126848958333	102.36375	-0.236901041666665	0.653151041666689
19	102.78	101.550078125	102.27125	-0.721171875000005	1.22992187500003
20	101.67	102.321744791667	102.17875	0.142994791666664	-0.651744791666644
21	101.67	102.673411458333	102.08625	0.587161458333328	-1.0034114583333
22	101.67	102.439348958333	101.99375	0.445598958333332	-0.76934895833331
23	101.67	102.194557291667	101.90125	0.293307291666666	-0.524557291666639
24	101.67	101.949765625	101.80875	0.141015625000003	-0.279765624999982
25	101.67	101.704973958333	101.71625	-0.0112760416666641	-0.0349739583333104
26	101.67	101.690390625	101.841666666667	-0.151276041666665	-0.0203906249999761
27	101.67	101.929973958333	102.185	-0.255026041666666	-0.259973958333305
28	101.67	102.451015625	102.528333333333	-0.0773177083333311	-0.781015624999981
29	101.67	102.714557291667	102.871666666667	-0.157109374999996	-1.04455729166665
30	101.67	102.978098958333	103.215	-0.236901041666665	-1.3080989583333
31	101.67	102.837161458333	103.558333333333	-0.721171875000005	-1.1671614583333
32	105.79	104.044661458333	103.901666666667	0.142994791666664	1.7453385416667
33	105.79	104.832161458333	104.245	0.587161458333328	0.957838541666703
34	105.79	105.033932291667	104.588333333333	0.445598958333332	0.756067708333362
35	105.79	105.224973958333	104.931666666667	0.293307291666666	0.565026041666698
36	105.79	105.416015625	105.275	0.141015625000003	0.37398437500002
37	105.79	105.607057291667	105.618333333333	-0.0112760416666641	0.182942708333357
38	105.79	105.583723958333	105.735	-0.151276041666665	0.206276041666683
39	105.79	105.369973958333	105.625	-0.255026041666666	0.420026041666688
40	105.79	105.437682291667	105.515	-0.0773177083333311	0.352317708333345
41	105.79	105.247890625	105.405	-0.157109374999996	0.54210937500001
42	105.79	105.058098958333	105.295	-0.236901041666665	0.731901041666688
43	105.79	104.463828125	105.185	-0.721171875000005	1.32617187500003
44	104.47	105.217994791667	105.075	0.142994791666664	-0.747994791666656
45	104.47	105.552161458333	104.965	0.587161458333328	-1.08216145833332
46	104.47	105.343515625	104.897916666667	0.445598958333332	-0.873515624999982
47	104.47	105.167057291667	104.87375	0.293307291666666	-0.697057291666653
48	104.47	104.990598958333	104.849583333333	0.141015625000003	-0.520598958333323
49	104.47	104.814140625	104.825416666667	-0.0112760416666641	-0.344140624999994
50	104.47	104.751223958333	104.9025	-0.151276041666665	-0.281223958333328
51	104.47	104.825807291667	105.080833333333	-0.255026041666666	-0.355807291666665
52	105.5	105.181848958333	105.259166666667	-0.0773177083333311	0.318151041666667
53	105.5	105.280390625	105.4375	-0.157109374999996	0.219609375000005
54	105.5	105.378932291667	105.615833333333	-0.236901041666665	0.121067708333342
55	105.5	NA	NA	-0.721171875000005	NA
56	106.61	NA	NA	0.142994791666664	NA
57	106.61	NA	NA	0.587161458333328	NA
58	106.61	NA	NA	0.445598958333332	NA
59	106.61	NA	NA	0.293307291666666	NA
60	106.61	NA	NA	0.141015625000003	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 98.19 & NA & NA & -0.0112760416666641 & NA \tabularnewline
2 & 98.19 & NA & NA & -0.151276041666665 & NA \tabularnewline
3 & 98.19 & NA & NA & -0.255026041666666 & NA \tabularnewline
4 & 98.19 & NA & NA & -0.0773177083333311 & NA \tabularnewline
5 & 98.19 & NA & NA & -0.157109374999996 & NA \tabularnewline
6 & 98.19 & NA & NA & -0.236901041666665 & NA \tabularnewline
7 & 98.19 & 99.3809114583333 & 100.102083333333 & -0.721171875000005 & -1.19091145833335 \tabularnewline
8 & 100.48 & 100.627578125 & 100.484583333333 & 0.142994791666664 & -0.14757812500001 \tabularnewline
9 & 102.78 & 101.454244791667 & 100.867083333333 & 0.587161458333328 & 1.32575520833332 \tabularnewline
10 & 102.78 & 101.695182291667 & 101.249583333333 & 0.445598958333332 & 1.08481770833332 \tabularnewline
11 & 102.78 & 101.925390625 & 101.632083333333 & 0.293307291666666 & 0.854609374999995 \tabularnewline
12 & 102.78 & 102.155598958333 & 102.014583333333 & 0.141015625000003 & 0.624401041666658 \tabularnewline
13 & 102.78 & 102.385807291667 & 102.397083333333 & -0.0112760416666641 & 0.394192708333335 \tabularnewline
14 & 102.78 & 102.486640625 & 102.637916666667 & -0.151276041666665 & 0.293359375000009 \tabularnewline
15 & 102.78 & 102.386223958333 & 102.64125 & -0.255026041666666 & 0.393776041666683 \tabularnewline
16 & 102.78 & 102.471432291667 & 102.54875 & -0.0773177083333311 & 0.308567708333342 \tabularnewline
17 & 102.78 & 102.299140625 & 102.45625 & -0.157109374999996 & 0.480859375000009 \tabularnewline
18 & 102.78 & 102.126848958333 & 102.36375 & -0.236901041666665 & 0.653151041666689 \tabularnewline
19 & 102.78 & 101.550078125 & 102.27125 & -0.721171875000005 & 1.22992187500003 \tabularnewline
20 & 101.67 & 102.321744791667 & 102.17875 & 0.142994791666664 & -0.651744791666644 \tabularnewline
21 & 101.67 & 102.673411458333 & 102.08625 & 0.587161458333328 & -1.0034114583333 \tabularnewline
22 & 101.67 & 102.439348958333 & 101.99375 & 0.445598958333332 & -0.76934895833331 \tabularnewline
23 & 101.67 & 102.194557291667 & 101.90125 & 0.293307291666666 & -0.524557291666639 \tabularnewline
24 & 101.67 & 101.949765625 & 101.80875 & 0.141015625000003 & -0.279765624999982 \tabularnewline
25 & 101.67 & 101.704973958333 & 101.71625 & -0.0112760416666641 & -0.0349739583333104 \tabularnewline
26 & 101.67 & 101.690390625 & 101.841666666667 & -0.151276041666665 & -0.0203906249999761 \tabularnewline
27 & 101.67 & 101.929973958333 & 102.185 & -0.255026041666666 & -0.259973958333305 \tabularnewline
28 & 101.67 & 102.451015625 & 102.528333333333 & -0.0773177083333311 & -0.781015624999981 \tabularnewline
29 & 101.67 & 102.714557291667 & 102.871666666667 & -0.157109374999996 & -1.04455729166665 \tabularnewline
30 & 101.67 & 102.978098958333 & 103.215 & -0.236901041666665 & -1.3080989583333 \tabularnewline
31 & 101.67 & 102.837161458333 & 103.558333333333 & -0.721171875000005 & -1.1671614583333 \tabularnewline
32 & 105.79 & 104.044661458333 & 103.901666666667 & 0.142994791666664 & 1.7453385416667 \tabularnewline
33 & 105.79 & 104.832161458333 & 104.245 & 0.587161458333328 & 0.957838541666703 \tabularnewline
34 & 105.79 & 105.033932291667 & 104.588333333333 & 0.445598958333332 & 0.756067708333362 \tabularnewline
35 & 105.79 & 105.224973958333 & 104.931666666667 & 0.293307291666666 & 0.565026041666698 \tabularnewline
36 & 105.79 & 105.416015625 & 105.275 & 0.141015625000003 & 0.37398437500002 \tabularnewline
37 & 105.79 & 105.607057291667 & 105.618333333333 & -0.0112760416666641 & 0.182942708333357 \tabularnewline
38 & 105.79 & 105.583723958333 & 105.735 & -0.151276041666665 & 0.206276041666683 \tabularnewline
39 & 105.79 & 105.369973958333 & 105.625 & -0.255026041666666 & 0.420026041666688 \tabularnewline
40 & 105.79 & 105.437682291667 & 105.515 & -0.0773177083333311 & 0.352317708333345 \tabularnewline
41 & 105.79 & 105.247890625 & 105.405 & -0.157109374999996 & 0.54210937500001 \tabularnewline
42 & 105.79 & 105.058098958333 & 105.295 & -0.236901041666665 & 0.731901041666688 \tabularnewline
43 & 105.79 & 104.463828125 & 105.185 & -0.721171875000005 & 1.32617187500003 \tabularnewline
44 & 104.47 & 105.217994791667 & 105.075 & 0.142994791666664 & -0.747994791666656 \tabularnewline
45 & 104.47 & 105.552161458333 & 104.965 & 0.587161458333328 & -1.08216145833332 \tabularnewline
46 & 104.47 & 105.343515625 & 104.897916666667 & 0.445598958333332 & -0.873515624999982 \tabularnewline
47 & 104.47 & 105.167057291667 & 104.87375 & 0.293307291666666 & -0.697057291666653 \tabularnewline
48 & 104.47 & 104.990598958333 & 104.849583333333 & 0.141015625000003 & -0.520598958333323 \tabularnewline
49 & 104.47 & 104.814140625 & 104.825416666667 & -0.0112760416666641 & -0.344140624999994 \tabularnewline
50 & 104.47 & 104.751223958333 & 104.9025 & -0.151276041666665 & -0.281223958333328 \tabularnewline
51 & 104.47 & 104.825807291667 & 105.080833333333 & -0.255026041666666 & -0.355807291666665 \tabularnewline
52 & 105.5 & 105.181848958333 & 105.259166666667 & -0.0773177083333311 & 0.318151041666667 \tabularnewline
53 & 105.5 & 105.280390625 & 105.4375 & -0.157109374999996 & 0.219609375000005 \tabularnewline
54 & 105.5 & 105.378932291667 & 105.615833333333 & -0.236901041666665 & 0.121067708333342 \tabularnewline
55 & 105.5 & NA & NA & -0.721171875000005 & NA \tabularnewline
56 & 106.61 & NA & NA & 0.142994791666664 & NA \tabularnewline
57 & 106.61 & NA & NA & 0.587161458333328 & NA \tabularnewline
58 & 106.61 & NA & NA & 0.445598958333332 & NA \tabularnewline
59 & 106.61 & NA & NA & 0.293307291666666 & NA \tabularnewline
60 & 106.61 & NA & NA & 0.141015625000003 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166260&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]98.19[/C][C]NA[/C][C]NA[/C][C]-0.0112760416666641[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]98.19[/C][C]NA[/C][C]NA[/C][C]-0.151276041666665[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]98.19[/C][C]NA[/C][C]NA[/C][C]-0.255026041666666[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]98.19[/C][C]NA[/C][C]NA[/C][C]-0.0773177083333311[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]98.19[/C][C]NA[/C][C]NA[/C][C]-0.157109374999996[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]98.19[/C][C]NA[/C][C]NA[/C][C]-0.236901041666665[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]98.19[/C][C]99.3809114583333[/C][C]100.102083333333[/C][C]-0.721171875000005[/C][C]-1.19091145833335[/C][/ROW]
[ROW][C]8[/C][C]100.48[/C][C]100.627578125[/C][C]100.484583333333[/C][C]0.142994791666664[/C][C]-0.14757812500001[/C][/ROW]
[ROW][C]9[/C][C]102.78[/C][C]101.454244791667[/C][C]100.867083333333[/C][C]0.587161458333328[/C][C]1.32575520833332[/C][/ROW]
[ROW][C]10[/C][C]102.78[/C][C]101.695182291667[/C][C]101.249583333333[/C][C]0.445598958333332[/C][C]1.08481770833332[/C][/ROW]
[ROW][C]11[/C][C]102.78[/C][C]101.925390625[/C][C]101.632083333333[/C][C]0.293307291666666[/C][C]0.854609374999995[/C][/ROW]
[ROW][C]12[/C][C]102.78[/C][C]102.155598958333[/C][C]102.014583333333[/C][C]0.141015625000003[/C][C]0.624401041666658[/C][/ROW]
[ROW][C]13[/C][C]102.78[/C][C]102.385807291667[/C][C]102.397083333333[/C][C]-0.0112760416666641[/C][C]0.394192708333335[/C][/ROW]
[ROW][C]14[/C][C]102.78[/C][C]102.486640625[/C][C]102.637916666667[/C][C]-0.151276041666665[/C][C]0.293359375000009[/C][/ROW]
[ROW][C]15[/C][C]102.78[/C][C]102.386223958333[/C][C]102.64125[/C][C]-0.255026041666666[/C][C]0.393776041666683[/C][/ROW]
[ROW][C]16[/C][C]102.78[/C][C]102.471432291667[/C][C]102.54875[/C][C]-0.0773177083333311[/C][C]0.308567708333342[/C][/ROW]
[ROW][C]17[/C][C]102.78[/C][C]102.299140625[/C][C]102.45625[/C][C]-0.157109374999996[/C][C]0.480859375000009[/C][/ROW]
[ROW][C]18[/C][C]102.78[/C][C]102.126848958333[/C][C]102.36375[/C][C]-0.236901041666665[/C][C]0.653151041666689[/C][/ROW]
[ROW][C]19[/C][C]102.78[/C][C]101.550078125[/C][C]102.27125[/C][C]-0.721171875000005[/C][C]1.22992187500003[/C][/ROW]
[ROW][C]20[/C][C]101.67[/C][C]102.321744791667[/C][C]102.17875[/C][C]0.142994791666664[/C][C]-0.651744791666644[/C][/ROW]
[ROW][C]21[/C][C]101.67[/C][C]102.673411458333[/C][C]102.08625[/C][C]0.587161458333328[/C][C]-1.0034114583333[/C][/ROW]
[ROW][C]22[/C][C]101.67[/C][C]102.439348958333[/C][C]101.99375[/C][C]0.445598958333332[/C][C]-0.76934895833331[/C][/ROW]
[ROW][C]23[/C][C]101.67[/C][C]102.194557291667[/C][C]101.90125[/C][C]0.293307291666666[/C][C]-0.524557291666639[/C][/ROW]
[ROW][C]24[/C][C]101.67[/C][C]101.949765625[/C][C]101.80875[/C][C]0.141015625000003[/C][C]-0.279765624999982[/C][/ROW]
[ROW][C]25[/C][C]101.67[/C][C]101.704973958333[/C][C]101.71625[/C][C]-0.0112760416666641[/C][C]-0.0349739583333104[/C][/ROW]
[ROW][C]26[/C][C]101.67[/C][C]101.690390625[/C][C]101.841666666667[/C][C]-0.151276041666665[/C][C]-0.0203906249999761[/C][/ROW]
[ROW][C]27[/C][C]101.67[/C][C]101.929973958333[/C][C]102.185[/C][C]-0.255026041666666[/C][C]-0.259973958333305[/C][/ROW]
[ROW][C]28[/C][C]101.67[/C][C]102.451015625[/C][C]102.528333333333[/C][C]-0.0773177083333311[/C][C]-0.781015624999981[/C][/ROW]
[ROW][C]29[/C][C]101.67[/C][C]102.714557291667[/C][C]102.871666666667[/C][C]-0.157109374999996[/C][C]-1.04455729166665[/C][/ROW]
[ROW][C]30[/C][C]101.67[/C][C]102.978098958333[/C][C]103.215[/C][C]-0.236901041666665[/C][C]-1.3080989583333[/C][/ROW]
[ROW][C]31[/C][C]101.67[/C][C]102.837161458333[/C][C]103.558333333333[/C][C]-0.721171875000005[/C][C]-1.1671614583333[/C][/ROW]
[ROW][C]32[/C][C]105.79[/C][C]104.044661458333[/C][C]103.901666666667[/C][C]0.142994791666664[/C][C]1.7453385416667[/C][/ROW]
[ROW][C]33[/C][C]105.79[/C][C]104.832161458333[/C][C]104.245[/C][C]0.587161458333328[/C][C]0.957838541666703[/C][/ROW]
[ROW][C]34[/C][C]105.79[/C][C]105.033932291667[/C][C]104.588333333333[/C][C]0.445598958333332[/C][C]0.756067708333362[/C][/ROW]
[ROW][C]35[/C][C]105.79[/C][C]105.224973958333[/C][C]104.931666666667[/C][C]0.293307291666666[/C][C]0.565026041666698[/C][/ROW]
[ROW][C]36[/C][C]105.79[/C][C]105.416015625[/C][C]105.275[/C][C]0.141015625000003[/C][C]0.37398437500002[/C][/ROW]
[ROW][C]37[/C][C]105.79[/C][C]105.607057291667[/C][C]105.618333333333[/C][C]-0.0112760416666641[/C][C]0.182942708333357[/C][/ROW]
[ROW][C]38[/C][C]105.79[/C][C]105.583723958333[/C][C]105.735[/C][C]-0.151276041666665[/C][C]0.206276041666683[/C][/ROW]
[ROW][C]39[/C][C]105.79[/C][C]105.369973958333[/C][C]105.625[/C][C]-0.255026041666666[/C][C]0.420026041666688[/C][/ROW]
[ROW][C]40[/C][C]105.79[/C][C]105.437682291667[/C][C]105.515[/C][C]-0.0773177083333311[/C][C]0.352317708333345[/C][/ROW]
[ROW][C]41[/C][C]105.79[/C][C]105.247890625[/C][C]105.405[/C][C]-0.157109374999996[/C][C]0.54210937500001[/C][/ROW]
[ROW][C]42[/C][C]105.79[/C][C]105.058098958333[/C][C]105.295[/C][C]-0.236901041666665[/C][C]0.731901041666688[/C][/ROW]
[ROW][C]43[/C][C]105.79[/C][C]104.463828125[/C][C]105.185[/C][C]-0.721171875000005[/C][C]1.32617187500003[/C][/ROW]
[ROW][C]44[/C][C]104.47[/C][C]105.217994791667[/C][C]105.075[/C][C]0.142994791666664[/C][C]-0.747994791666656[/C][/ROW]
[ROW][C]45[/C][C]104.47[/C][C]105.552161458333[/C][C]104.965[/C][C]0.587161458333328[/C][C]-1.08216145833332[/C][/ROW]
[ROW][C]46[/C][C]104.47[/C][C]105.343515625[/C][C]104.897916666667[/C][C]0.445598958333332[/C][C]-0.873515624999982[/C][/ROW]
[ROW][C]47[/C][C]104.47[/C][C]105.167057291667[/C][C]104.87375[/C][C]0.293307291666666[/C][C]-0.697057291666653[/C][/ROW]
[ROW][C]48[/C][C]104.47[/C][C]104.990598958333[/C][C]104.849583333333[/C][C]0.141015625000003[/C][C]-0.520598958333323[/C][/ROW]
[ROW][C]49[/C][C]104.47[/C][C]104.814140625[/C][C]104.825416666667[/C][C]-0.0112760416666641[/C][C]-0.344140624999994[/C][/ROW]
[ROW][C]50[/C][C]104.47[/C][C]104.751223958333[/C][C]104.9025[/C][C]-0.151276041666665[/C][C]-0.281223958333328[/C][/ROW]
[ROW][C]51[/C][C]104.47[/C][C]104.825807291667[/C][C]105.080833333333[/C][C]-0.255026041666666[/C][C]-0.355807291666665[/C][/ROW]
[ROW][C]52[/C][C]105.5[/C][C]105.181848958333[/C][C]105.259166666667[/C][C]-0.0773177083333311[/C][C]0.318151041666667[/C][/ROW]
[ROW][C]53[/C][C]105.5[/C][C]105.280390625[/C][C]105.4375[/C][C]-0.157109374999996[/C][C]0.219609375000005[/C][/ROW]
[ROW][C]54[/C][C]105.5[/C][C]105.378932291667[/C][C]105.615833333333[/C][C]-0.236901041666665[/C][C]0.121067708333342[/C][/ROW]
[ROW][C]55[/C][C]105.5[/C][C]NA[/C][C]NA[/C][C]-0.721171875000005[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]106.61[/C][C]NA[/C][C]NA[/C][C]0.142994791666664[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]106.61[/C][C]NA[/C][C]NA[/C][C]0.587161458333328[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]106.61[/C][C]NA[/C][C]NA[/C][C]0.445598958333332[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]106.61[/C][C]NA[/C][C]NA[/C][C]0.293307291666666[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]106.61[/C][C]NA[/C][C]NA[/C][C]0.141015625000003[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166260&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166260&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	98.19	NA	NA	-0.0112760416666641	NA
2	98.19	NA	NA	-0.151276041666665	NA
3	98.19	NA	NA	-0.255026041666666	NA
4	98.19	NA	NA	-0.0773177083333311	NA
5	98.19	NA	NA	-0.157109374999996	NA
6	98.19	NA	NA	-0.236901041666665	NA
7	98.19	99.3809114583333	100.102083333333	-0.721171875000005	-1.19091145833335
8	100.48	100.627578125	100.484583333333	0.142994791666664	-0.14757812500001
9	102.78	101.454244791667	100.867083333333	0.587161458333328	1.32575520833332
10	102.78	101.695182291667	101.249583333333	0.445598958333332	1.08481770833332
11	102.78	101.925390625	101.632083333333	0.293307291666666	0.854609374999995
12	102.78	102.155598958333	102.014583333333	0.141015625000003	0.624401041666658
13	102.78	102.385807291667	102.397083333333	-0.0112760416666641	0.394192708333335
14	102.78	102.486640625	102.637916666667	-0.151276041666665	0.293359375000009
15	102.78	102.386223958333	102.64125	-0.255026041666666	0.393776041666683
16	102.78	102.471432291667	102.54875	-0.0773177083333311	0.308567708333342
17	102.78	102.299140625	102.45625	-0.157109374999996	0.480859375000009
18	102.78	102.126848958333	102.36375	-0.236901041666665	0.653151041666689
19	102.78	101.550078125	102.27125	-0.721171875000005	1.22992187500003
20	101.67	102.321744791667	102.17875	0.142994791666664	-0.651744791666644
21	101.67	102.673411458333	102.08625	0.587161458333328	-1.0034114583333
22	101.67	102.439348958333	101.99375	0.445598958333332	-0.76934895833331
23	101.67	102.194557291667	101.90125	0.293307291666666	-0.524557291666639
24	101.67	101.949765625	101.80875	0.141015625000003	-0.279765624999982
25	101.67	101.704973958333	101.71625	-0.0112760416666641	-0.0349739583333104
26	101.67	101.690390625	101.841666666667	-0.151276041666665	-0.0203906249999761
27	101.67	101.929973958333	102.185	-0.255026041666666	-0.259973958333305
28	101.67	102.451015625	102.528333333333	-0.0773177083333311	-0.781015624999981
29	101.67	102.714557291667	102.871666666667	-0.157109374999996	-1.04455729166665
30	101.67	102.978098958333	103.215	-0.236901041666665	-1.3080989583333
31	101.67	102.837161458333	103.558333333333	-0.721171875000005	-1.1671614583333
32	105.79	104.044661458333	103.901666666667	0.142994791666664	1.7453385416667
33	105.79	104.832161458333	104.245	0.587161458333328	0.957838541666703
34	105.79	105.033932291667	104.588333333333	0.445598958333332	0.756067708333362
35	105.79	105.224973958333	104.931666666667	0.293307291666666	0.565026041666698
36	105.79	105.416015625	105.275	0.141015625000003	0.37398437500002
37	105.79	105.607057291667	105.618333333333	-0.0112760416666641	0.182942708333357
38	105.79	105.583723958333	105.735	-0.151276041666665	0.206276041666683
39	105.79	105.369973958333	105.625	-0.255026041666666	0.420026041666688
40	105.79	105.437682291667	105.515	-0.0773177083333311	0.352317708333345
41	105.79	105.247890625	105.405	-0.157109374999996	0.54210937500001
42	105.79	105.058098958333	105.295	-0.236901041666665	0.731901041666688
43	105.79	104.463828125	105.185	-0.721171875000005	1.32617187500003
44	104.47	105.217994791667	105.075	0.142994791666664	-0.747994791666656
45	104.47	105.552161458333	104.965	0.587161458333328	-1.08216145833332
46	104.47	105.343515625	104.897916666667	0.445598958333332	-0.873515624999982
47	104.47	105.167057291667	104.87375	0.293307291666666	-0.697057291666653
48	104.47	104.990598958333	104.849583333333	0.141015625000003	-0.520598958333323
49	104.47	104.814140625	104.825416666667	-0.0112760416666641	-0.344140624999994
50	104.47	104.751223958333	104.9025	-0.151276041666665	-0.281223958333328
51	104.47	104.825807291667	105.080833333333	-0.255026041666666	-0.355807291666665
52	105.5	105.181848958333	105.259166666667	-0.0773177083333311	0.318151041666667
53	105.5	105.280390625	105.4375	-0.157109374999996	0.219609375000005
54	105.5	105.378932291667	105.615833333333	-0.236901041666665	0.121067708333342
55	105.5	NA	NA	-0.721171875000005	NA
56	106.61	NA	NA	0.142994791666664	NA
57	106.61	NA	NA	0.587161458333328	NA
58	106.61	NA	NA	0.445598958333332	NA
59	106.61	NA	NA	0.293307291666666	NA
60	106.61	NA	NA	0.141015625000003	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