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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Wed, 09 May 2012 12:21:56 -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/09/t1336580531zekyosiihyi4kmh.htm/, Retrieved Fri, 03 May 2024 20:28:46 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166353, Retrieved Fri, 03 May 2024 20:28:46 +0000

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Estimated Impact

165

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

-       [Classical Decomposition] [] [2012-05-09 16:21:56] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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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	'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166353&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166353&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166353&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	'Herman Ole Andreas Wold' @ wold.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	163.93	NA	NA	0.99970585038172	NA
2	164.28	NA	NA	1.00039430505393	NA
3	164.58	NA	NA	0.999926677414323	NA
4	165.97	NA	NA	0.999935590190184	NA
5	166.3	NA	NA	1.0004449067646	NA
6	166.27	NA	NA	0.999806951859801	NA
7	166.27	165.769052488007	165.860833333333	0.999446639429685	1.00302196039897
8	166.44	165.826387721891	166.034583333333	0.998746070804874	1.00370032952257
9	166.26	165.897258548643	166.187916666667	0.998251027367973	1.00218654277069
10	166.64	166.572595765211	166.284583333333	1.00173204530513	1.00040465380562
11	166.07	166.52347338974	166.34375	1.00108043367869	0.997276820015166
12	166.19	166.505201470036	166.417083333333	1.00052950174909	0.998106957216631
13	166.19	166.442276662365	166.49125	0.99970585038172	0.998484299377392
14	166.19	166.624008125941	166.558333333333	1.00039430505393	0.997395284564195
15	166.35	166.623198527051	166.635416666667	0.999926677414323	0.998360381210621
16	166.52	166.747592460798	166.758333333333	0.999935590190184	0.998635107965043
17	167.17	167.011771623015	166.9375	1.0004449067646	1.00094740852963
18	167.16	167.108150520077	167.140416666667	0.999806951859801	1.00031027499115
19	167.16	167.246984206064	167.339583333333	0.999446639429685	0.999479905682745
20	167.16	167.354885354419	167.565	0.998746070804874	0.998835496472027
21	167.39	167.519832406044	167.813333333333	0.998251027367973	0.99922497292303
22	168.46	168.340235436823	168.049166666667	1.00173204530513	1.00071144348151
23	168.55	168.442628004472	168.260833333333	1.00108043367869	1.00063743956503
24	168.58	168.548782977359	168.459583333333	1.00052950174909	1.00018521060841
25	168.58	168.610805269485	168.660416666667	0.99970585038172	0.999817299553039
26	169.21	168.932001153893	168.865416666667	1.00039430505393	1.00164562572046
27	169.29	169.068019253329	169.080416666667	0.999926677414323	1.0013129670984
28	169.24	169.26034727098	169.27125	0.999935590190184	0.99987978713675
29	169.53	169.511216481749	169.435833333333	1.0004449067646	1.0001108098841
30	169.57	169.566425862962	169.599166666667	0.999806951859801	1.00002107809385
31	169.57	169.663562892985	169.7575	0.999446639429685	0.999448538676253
32	169.67	169.676553824844	169.889583333333	0.998746070804874	0.999961374599518
33	170.04	169.69518776985	169.9925	0.998251027367973	1.00203195055017
34	170.39	170.398794789925	170.104166666667	1.00173204530513	0.999948387018021
35	170.57	170.415590692513	170.231666666667	1.00108043367869	1.00090607500675
36	170.48	170.450205917974	170.36	1.00052950174909	1.00017479639796
37	170.48	170.434851902327	170.485	0.99970585038172	1.00026489944497
38	170.48	170.673104075647	170.605833333333	1.00039430505393	0.998868573483251
39	170.49	170.693733376359	170.70625	0.999926677414323	0.998806439039507
40	170.72	170.816080393384	170.827083333333	0.999935590190184	0.999437521378765
41	171.11	171.072327388346	170.99625	1.0004449067646	1.00022021452697
42	171.07	171.15278622658	171.185833333333	0.999806951859801	0.999516302197557
43	171.07	171.289329426457	171.384166666667	0.999446639429685	0.998719538297036
44	171.07	171.383161173332	171.598333333333	0.998746070804874	0.998172742460883
45	171.05	171.525730591286	171.82625	0.998251027367973	0.997226476811111
46	172.28	172.347998394748	172.05	1.00173204530513	0.999605458749849
47	172.74	172.42108849465	172.235	1.00108043367869	1.00184960846805
48	172.86	172.480030144648	172.38875	1.00052950174909	1.002202978832
49	172.86	172.497161762844	172.547916666667	0.99970585038172	1.0021034446796
50	173.24	172.763094511289	172.695	1.00039430505393	1.0027604592871
51	173.2	172.821494018673	172.834166666667	0.999926677414323	1.00219015570648
52	173.38	172.910112175174	172.92125	0.999935590190184	1.00271752657444
53	172.89	172.995265869556	172.918333333333	1.0004449067646	0.999391510114296
54	172.98	172.837877526694	172.87125	0.999806951859801	1.00082228777245
55	172.98	NA	NA	0.999446639429685	NA
56	172.69	NA	NA	0.998746070804874	NA
57	172.77	NA	NA	0.998251027367973	NA
58	172.65	NA	NA	1.00173204530513	NA
59	172.3	NA	NA	1.00108043367869	NA
60	172.17	NA	NA	1.00052950174909	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 163.93 & NA & NA & 0.99970585038172 & NA \tabularnewline
2 & 164.28 & NA & NA & 1.00039430505393 & NA \tabularnewline
3 & 164.58 & NA & NA & 0.999926677414323 & NA \tabularnewline
4 & 165.97 & NA & NA & 0.999935590190184 & NA \tabularnewline
5 & 166.3 & NA & NA & 1.0004449067646 & NA \tabularnewline
6 & 166.27 & NA & NA & 0.999806951859801 & NA \tabularnewline
7 & 166.27 & 165.769052488007 & 165.860833333333 & 0.999446639429685 & 1.00302196039897 \tabularnewline
8 & 166.44 & 165.826387721891 & 166.034583333333 & 0.998746070804874 & 1.00370032952257 \tabularnewline
9 & 166.26 & 165.897258548643 & 166.187916666667 & 0.998251027367973 & 1.00218654277069 \tabularnewline
10 & 166.64 & 166.572595765211 & 166.284583333333 & 1.00173204530513 & 1.00040465380562 \tabularnewline
11 & 166.07 & 166.52347338974 & 166.34375 & 1.00108043367869 & 0.997276820015166 \tabularnewline
12 & 166.19 & 166.505201470036 & 166.417083333333 & 1.00052950174909 & 0.998106957216631 \tabularnewline
13 & 166.19 & 166.442276662365 & 166.49125 & 0.99970585038172 & 0.998484299377392 \tabularnewline
14 & 166.19 & 166.624008125941 & 166.558333333333 & 1.00039430505393 & 0.997395284564195 \tabularnewline
15 & 166.35 & 166.623198527051 & 166.635416666667 & 0.999926677414323 & 0.998360381210621 \tabularnewline
16 & 166.52 & 166.747592460798 & 166.758333333333 & 0.999935590190184 & 0.998635107965043 \tabularnewline
17 & 167.17 & 167.011771623015 & 166.9375 & 1.0004449067646 & 1.00094740852963 \tabularnewline
18 & 167.16 & 167.108150520077 & 167.140416666667 & 0.999806951859801 & 1.00031027499115 \tabularnewline
19 & 167.16 & 167.246984206064 & 167.339583333333 & 0.999446639429685 & 0.999479905682745 \tabularnewline
20 & 167.16 & 167.354885354419 & 167.565 & 0.998746070804874 & 0.998835496472027 \tabularnewline
21 & 167.39 & 167.519832406044 & 167.813333333333 & 0.998251027367973 & 0.99922497292303 \tabularnewline
22 & 168.46 & 168.340235436823 & 168.049166666667 & 1.00173204530513 & 1.00071144348151 \tabularnewline
23 & 168.55 & 168.442628004472 & 168.260833333333 & 1.00108043367869 & 1.00063743956503 \tabularnewline
24 & 168.58 & 168.548782977359 & 168.459583333333 & 1.00052950174909 & 1.00018521060841 \tabularnewline
25 & 168.58 & 168.610805269485 & 168.660416666667 & 0.99970585038172 & 0.999817299553039 \tabularnewline
26 & 169.21 & 168.932001153893 & 168.865416666667 & 1.00039430505393 & 1.00164562572046 \tabularnewline
27 & 169.29 & 169.068019253329 & 169.080416666667 & 0.999926677414323 & 1.0013129670984 \tabularnewline
28 & 169.24 & 169.26034727098 & 169.27125 & 0.999935590190184 & 0.99987978713675 \tabularnewline
29 & 169.53 & 169.511216481749 & 169.435833333333 & 1.0004449067646 & 1.0001108098841 \tabularnewline
30 & 169.57 & 169.566425862962 & 169.599166666667 & 0.999806951859801 & 1.00002107809385 \tabularnewline
31 & 169.57 & 169.663562892985 & 169.7575 & 0.999446639429685 & 0.999448538676253 \tabularnewline
32 & 169.67 & 169.676553824844 & 169.889583333333 & 0.998746070804874 & 0.999961374599518 \tabularnewline
33 & 170.04 & 169.69518776985 & 169.9925 & 0.998251027367973 & 1.00203195055017 \tabularnewline
34 & 170.39 & 170.398794789925 & 170.104166666667 & 1.00173204530513 & 0.999948387018021 \tabularnewline
35 & 170.57 & 170.415590692513 & 170.231666666667 & 1.00108043367869 & 1.00090607500675 \tabularnewline
36 & 170.48 & 170.450205917974 & 170.36 & 1.00052950174909 & 1.00017479639796 \tabularnewline
37 & 170.48 & 170.434851902327 & 170.485 & 0.99970585038172 & 1.00026489944497 \tabularnewline
38 & 170.48 & 170.673104075647 & 170.605833333333 & 1.00039430505393 & 0.998868573483251 \tabularnewline
39 & 170.49 & 170.693733376359 & 170.70625 & 0.999926677414323 & 0.998806439039507 \tabularnewline
40 & 170.72 & 170.816080393384 & 170.827083333333 & 0.999935590190184 & 0.999437521378765 \tabularnewline
41 & 171.11 & 171.072327388346 & 170.99625 & 1.0004449067646 & 1.00022021452697 \tabularnewline
42 & 171.07 & 171.15278622658 & 171.185833333333 & 0.999806951859801 & 0.999516302197557 \tabularnewline
43 & 171.07 & 171.289329426457 & 171.384166666667 & 0.999446639429685 & 0.998719538297036 \tabularnewline
44 & 171.07 & 171.383161173332 & 171.598333333333 & 0.998746070804874 & 0.998172742460883 \tabularnewline
45 & 171.05 & 171.525730591286 & 171.82625 & 0.998251027367973 & 0.997226476811111 \tabularnewline
46 & 172.28 & 172.347998394748 & 172.05 & 1.00173204530513 & 0.999605458749849 \tabularnewline
47 & 172.74 & 172.42108849465 & 172.235 & 1.00108043367869 & 1.00184960846805 \tabularnewline
48 & 172.86 & 172.480030144648 & 172.38875 & 1.00052950174909 & 1.002202978832 \tabularnewline
49 & 172.86 & 172.497161762844 & 172.547916666667 & 0.99970585038172 & 1.0021034446796 \tabularnewline
50 & 173.24 & 172.763094511289 & 172.695 & 1.00039430505393 & 1.0027604592871 \tabularnewline
51 & 173.2 & 172.821494018673 & 172.834166666667 & 0.999926677414323 & 1.00219015570648 \tabularnewline
52 & 173.38 & 172.910112175174 & 172.92125 & 0.999935590190184 & 1.00271752657444 \tabularnewline
53 & 172.89 & 172.995265869556 & 172.918333333333 & 1.0004449067646 & 0.999391510114296 \tabularnewline
54 & 172.98 & 172.837877526694 & 172.87125 & 0.999806951859801 & 1.00082228777245 \tabularnewline
55 & 172.98 & NA & NA & 0.999446639429685 & NA \tabularnewline
56 & 172.69 & NA & NA & 0.998746070804874 & NA \tabularnewline
57 & 172.77 & NA & NA & 0.998251027367973 & NA \tabularnewline
58 & 172.65 & NA & NA & 1.00173204530513 & NA \tabularnewline
59 & 172.3 & NA & NA & 1.00108043367869 & NA \tabularnewline
60 & 172.17 & NA & NA & 1.00052950174909 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166353&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]163.93[/C][C]NA[/C][C]NA[/C][C]0.99970585038172[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]164.28[/C][C]NA[/C][C]NA[/C][C]1.00039430505393[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]164.58[/C][C]NA[/C][C]NA[/C][C]0.999926677414323[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]165.97[/C][C]NA[/C][C]NA[/C][C]0.999935590190184[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]166.3[/C][C]NA[/C][C]NA[/C][C]1.0004449067646[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]166.27[/C][C]NA[/C][C]NA[/C][C]0.999806951859801[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]166.27[/C][C]165.769052488007[/C][C]165.860833333333[/C][C]0.999446639429685[/C][C]1.00302196039897[/C][/ROW]
[ROW][C]8[/C][C]166.44[/C][C]165.826387721891[/C][C]166.034583333333[/C][C]0.998746070804874[/C][C]1.00370032952257[/C][/ROW]
[ROW][C]9[/C][C]166.26[/C][C]165.897258548643[/C][C]166.187916666667[/C][C]0.998251027367973[/C][C]1.00218654277069[/C][/ROW]
[ROW][C]10[/C][C]166.64[/C][C]166.572595765211[/C][C]166.284583333333[/C][C]1.00173204530513[/C][C]1.00040465380562[/C][/ROW]
[ROW][C]11[/C][C]166.07[/C][C]166.52347338974[/C][C]166.34375[/C][C]1.00108043367869[/C][C]0.997276820015166[/C][/ROW]
[ROW][C]12[/C][C]166.19[/C][C]166.505201470036[/C][C]166.417083333333[/C][C]1.00052950174909[/C][C]0.998106957216631[/C][/ROW]
[ROW][C]13[/C][C]166.19[/C][C]166.442276662365[/C][C]166.49125[/C][C]0.99970585038172[/C][C]0.998484299377392[/C][/ROW]
[ROW][C]14[/C][C]166.19[/C][C]166.624008125941[/C][C]166.558333333333[/C][C]1.00039430505393[/C][C]0.997395284564195[/C][/ROW]
[ROW][C]15[/C][C]166.35[/C][C]166.623198527051[/C][C]166.635416666667[/C][C]0.999926677414323[/C][C]0.998360381210621[/C][/ROW]
[ROW][C]16[/C][C]166.52[/C][C]166.747592460798[/C][C]166.758333333333[/C][C]0.999935590190184[/C][C]0.998635107965043[/C][/ROW]
[ROW][C]17[/C][C]167.17[/C][C]167.011771623015[/C][C]166.9375[/C][C]1.0004449067646[/C][C]1.00094740852963[/C][/ROW]
[ROW][C]18[/C][C]167.16[/C][C]167.108150520077[/C][C]167.140416666667[/C][C]0.999806951859801[/C][C]1.00031027499115[/C][/ROW]
[ROW][C]19[/C][C]167.16[/C][C]167.246984206064[/C][C]167.339583333333[/C][C]0.999446639429685[/C][C]0.999479905682745[/C][/ROW]
[ROW][C]20[/C][C]167.16[/C][C]167.354885354419[/C][C]167.565[/C][C]0.998746070804874[/C][C]0.998835496472027[/C][/ROW]
[ROW][C]21[/C][C]167.39[/C][C]167.519832406044[/C][C]167.813333333333[/C][C]0.998251027367973[/C][C]0.99922497292303[/C][/ROW]
[ROW][C]22[/C][C]168.46[/C][C]168.340235436823[/C][C]168.049166666667[/C][C]1.00173204530513[/C][C]1.00071144348151[/C][/ROW]
[ROW][C]23[/C][C]168.55[/C][C]168.442628004472[/C][C]168.260833333333[/C][C]1.00108043367869[/C][C]1.00063743956503[/C][/ROW]
[ROW][C]24[/C][C]168.58[/C][C]168.548782977359[/C][C]168.459583333333[/C][C]1.00052950174909[/C][C]1.00018521060841[/C][/ROW]
[ROW][C]25[/C][C]168.58[/C][C]168.610805269485[/C][C]168.660416666667[/C][C]0.99970585038172[/C][C]0.999817299553039[/C][/ROW]
[ROW][C]26[/C][C]169.21[/C][C]168.932001153893[/C][C]168.865416666667[/C][C]1.00039430505393[/C][C]1.00164562572046[/C][/ROW]
[ROW][C]27[/C][C]169.29[/C][C]169.068019253329[/C][C]169.080416666667[/C][C]0.999926677414323[/C][C]1.0013129670984[/C][/ROW]
[ROW][C]28[/C][C]169.24[/C][C]169.26034727098[/C][C]169.27125[/C][C]0.999935590190184[/C][C]0.99987978713675[/C][/ROW]
[ROW][C]29[/C][C]169.53[/C][C]169.511216481749[/C][C]169.435833333333[/C][C]1.0004449067646[/C][C]1.0001108098841[/C][/ROW]
[ROW][C]30[/C][C]169.57[/C][C]169.566425862962[/C][C]169.599166666667[/C][C]0.999806951859801[/C][C]1.00002107809385[/C][/ROW]
[ROW][C]31[/C][C]169.57[/C][C]169.663562892985[/C][C]169.7575[/C][C]0.999446639429685[/C][C]0.999448538676253[/C][/ROW]
[ROW][C]32[/C][C]169.67[/C][C]169.676553824844[/C][C]169.889583333333[/C][C]0.998746070804874[/C][C]0.999961374599518[/C][/ROW]
[ROW][C]33[/C][C]170.04[/C][C]169.69518776985[/C][C]169.9925[/C][C]0.998251027367973[/C][C]1.00203195055017[/C][/ROW]
[ROW][C]34[/C][C]170.39[/C][C]170.398794789925[/C][C]170.104166666667[/C][C]1.00173204530513[/C][C]0.999948387018021[/C][/ROW]
[ROW][C]35[/C][C]170.57[/C][C]170.415590692513[/C][C]170.231666666667[/C][C]1.00108043367869[/C][C]1.00090607500675[/C][/ROW]
[ROW][C]36[/C][C]170.48[/C][C]170.450205917974[/C][C]170.36[/C][C]1.00052950174909[/C][C]1.00017479639796[/C][/ROW]
[ROW][C]37[/C][C]170.48[/C][C]170.434851902327[/C][C]170.485[/C][C]0.99970585038172[/C][C]1.00026489944497[/C][/ROW]
[ROW][C]38[/C][C]170.48[/C][C]170.673104075647[/C][C]170.605833333333[/C][C]1.00039430505393[/C][C]0.998868573483251[/C][/ROW]
[ROW][C]39[/C][C]170.49[/C][C]170.693733376359[/C][C]170.70625[/C][C]0.999926677414323[/C][C]0.998806439039507[/C][/ROW]
[ROW][C]40[/C][C]170.72[/C][C]170.816080393384[/C][C]170.827083333333[/C][C]0.999935590190184[/C][C]0.999437521378765[/C][/ROW]
[ROW][C]41[/C][C]171.11[/C][C]171.072327388346[/C][C]170.99625[/C][C]1.0004449067646[/C][C]1.00022021452697[/C][/ROW]
[ROW][C]42[/C][C]171.07[/C][C]171.15278622658[/C][C]171.185833333333[/C][C]0.999806951859801[/C][C]0.999516302197557[/C][/ROW]
[ROW][C]43[/C][C]171.07[/C][C]171.289329426457[/C][C]171.384166666667[/C][C]0.999446639429685[/C][C]0.998719538297036[/C][/ROW]
[ROW][C]44[/C][C]171.07[/C][C]171.383161173332[/C][C]171.598333333333[/C][C]0.998746070804874[/C][C]0.998172742460883[/C][/ROW]
[ROW][C]45[/C][C]171.05[/C][C]171.525730591286[/C][C]171.82625[/C][C]0.998251027367973[/C][C]0.997226476811111[/C][/ROW]
[ROW][C]46[/C][C]172.28[/C][C]172.347998394748[/C][C]172.05[/C][C]1.00173204530513[/C][C]0.999605458749849[/C][/ROW]
[ROW][C]47[/C][C]172.74[/C][C]172.42108849465[/C][C]172.235[/C][C]1.00108043367869[/C][C]1.00184960846805[/C][/ROW]
[ROW][C]48[/C][C]172.86[/C][C]172.480030144648[/C][C]172.38875[/C][C]1.00052950174909[/C][C]1.002202978832[/C][/ROW]
[ROW][C]49[/C][C]172.86[/C][C]172.497161762844[/C][C]172.547916666667[/C][C]0.99970585038172[/C][C]1.0021034446796[/C][/ROW]
[ROW][C]50[/C][C]173.24[/C][C]172.763094511289[/C][C]172.695[/C][C]1.00039430505393[/C][C]1.0027604592871[/C][/ROW]
[ROW][C]51[/C][C]173.2[/C][C]172.821494018673[/C][C]172.834166666667[/C][C]0.999926677414323[/C][C]1.00219015570648[/C][/ROW]
[ROW][C]52[/C][C]173.38[/C][C]172.910112175174[/C][C]172.92125[/C][C]0.999935590190184[/C][C]1.00271752657444[/C][/ROW]
[ROW][C]53[/C][C]172.89[/C][C]172.995265869556[/C][C]172.918333333333[/C][C]1.0004449067646[/C][C]0.999391510114296[/C][/ROW]
[ROW][C]54[/C][C]172.98[/C][C]172.837877526694[/C][C]172.87125[/C][C]0.999806951859801[/C][C]1.00082228777245[/C][/ROW]
[ROW][C]55[/C][C]172.98[/C][C]NA[/C][C]NA[/C][C]0.999446639429685[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]172.69[/C][C]NA[/C][C]NA[/C][C]0.998746070804874[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]172.77[/C][C]NA[/C][C]NA[/C][C]0.998251027367973[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]172.65[/C][C]NA[/C][C]NA[/C][C]1.00173204530513[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]172.3[/C][C]NA[/C][C]NA[/C][C]1.00108043367869[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]172.17[/C][C]NA[/C][C]NA[/C][C]1.00052950174909[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166353&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166353&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	163.93	NA	NA	0.99970585038172	NA
2	164.28	NA	NA	1.00039430505393	NA
3	164.58	NA	NA	0.999926677414323	NA
4	165.97	NA	NA	0.999935590190184	NA
5	166.3	NA	NA	1.0004449067646	NA
6	166.27	NA	NA	0.999806951859801	NA
7	166.27	165.769052488007	165.860833333333	0.999446639429685	1.00302196039897
8	166.44	165.826387721891	166.034583333333	0.998746070804874	1.00370032952257
9	166.26	165.897258548643	166.187916666667	0.998251027367973	1.00218654277069
10	166.64	166.572595765211	166.284583333333	1.00173204530513	1.00040465380562
11	166.07	166.52347338974	166.34375	1.00108043367869	0.997276820015166
12	166.19	166.505201470036	166.417083333333	1.00052950174909	0.998106957216631
13	166.19	166.442276662365	166.49125	0.99970585038172	0.998484299377392
14	166.19	166.624008125941	166.558333333333	1.00039430505393	0.997395284564195
15	166.35	166.623198527051	166.635416666667	0.999926677414323	0.998360381210621
16	166.52	166.747592460798	166.758333333333	0.999935590190184	0.998635107965043
17	167.17	167.011771623015	166.9375	1.0004449067646	1.00094740852963
18	167.16	167.108150520077	167.140416666667	0.999806951859801	1.00031027499115
19	167.16	167.246984206064	167.339583333333	0.999446639429685	0.999479905682745
20	167.16	167.354885354419	167.565	0.998746070804874	0.998835496472027
21	167.39	167.519832406044	167.813333333333	0.998251027367973	0.99922497292303
22	168.46	168.340235436823	168.049166666667	1.00173204530513	1.00071144348151
23	168.55	168.442628004472	168.260833333333	1.00108043367869	1.00063743956503
24	168.58	168.548782977359	168.459583333333	1.00052950174909	1.00018521060841
25	168.58	168.610805269485	168.660416666667	0.99970585038172	0.999817299553039
26	169.21	168.932001153893	168.865416666667	1.00039430505393	1.00164562572046
27	169.29	169.068019253329	169.080416666667	0.999926677414323	1.0013129670984
28	169.24	169.26034727098	169.27125	0.999935590190184	0.99987978713675
29	169.53	169.511216481749	169.435833333333	1.0004449067646	1.0001108098841
30	169.57	169.566425862962	169.599166666667	0.999806951859801	1.00002107809385
31	169.57	169.663562892985	169.7575	0.999446639429685	0.999448538676253
32	169.67	169.676553824844	169.889583333333	0.998746070804874	0.999961374599518
33	170.04	169.69518776985	169.9925	0.998251027367973	1.00203195055017
34	170.39	170.398794789925	170.104166666667	1.00173204530513	0.999948387018021
35	170.57	170.415590692513	170.231666666667	1.00108043367869	1.00090607500675
36	170.48	170.450205917974	170.36	1.00052950174909	1.00017479639796
37	170.48	170.434851902327	170.485	0.99970585038172	1.00026489944497
38	170.48	170.673104075647	170.605833333333	1.00039430505393	0.998868573483251
39	170.49	170.693733376359	170.70625	0.999926677414323	0.998806439039507
40	170.72	170.816080393384	170.827083333333	0.999935590190184	0.999437521378765
41	171.11	171.072327388346	170.99625	1.0004449067646	1.00022021452697
42	171.07	171.15278622658	171.185833333333	0.999806951859801	0.999516302197557
43	171.07	171.289329426457	171.384166666667	0.999446639429685	0.998719538297036
44	171.07	171.383161173332	171.598333333333	0.998746070804874	0.998172742460883
45	171.05	171.525730591286	171.82625	0.998251027367973	0.997226476811111
46	172.28	172.347998394748	172.05	1.00173204530513	0.999605458749849
47	172.74	172.42108849465	172.235	1.00108043367869	1.00184960846805
48	172.86	172.480030144648	172.38875	1.00052950174909	1.002202978832
49	172.86	172.497161762844	172.547916666667	0.99970585038172	1.0021034446796
50	173.24	172.763094511289	172.695	1.00039430505393	1.0027604592871
51	173.2	172.821494018673	172.834166666667	0.999926677414323	1.00219015570648
52	173.38	172.910112175174	172.92125	0.999935590190184	1.00271752657444
53	172.89	172.995265869556	172.918333333333	1.0004449067646	0.999391510114296
54	172.98	172.837877526694	172.87125	0.999806951859801	1.00082228777245
55	172.98	NA	NA	0.999446639429685	NA
56	172.69	NA	NA	0.998746070804874	NA
57	172.77	NA	NA	0.998251027367973	NA
58	172.65	NA	NA	1.00173204530513	NA
59	172.3	NA	NA	1.00108043367869	NA
60	172.17	NA	NA	1.00052950174909	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