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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Fri, 04 Dec 2009 05:19:05 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/04/t1259929209lh7p9vmb3g2ce8d.htm/, Retrieved Sat, 27 Apr 2024 16:22:39 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=63382, Retrieved Sat, 27 Apr 2024 16:22:39 +0000

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Estimated Impact

117

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
-    D      [Classical Decomposition] [] [2009-12-04 12:19:05] [1c773da0103d9327c2f1f790e2d74438] [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' @ 72.249.127.135

\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' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63382&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' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63382&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63382&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' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	1.4816	NA	NA	0.981860655178136	NA
2	1.4562	NA	NA	1.00184099483241	NA
3	1.4268	NA	NA	1.00952760851050	NA
4	1.4088	NA	NA	1.01710725137427	NA
5	1.4016	NA	NA	1.01001172492984	NA
6	1.365	NA	NA	1.02474042705716	NA
7	1.319	1.37440241909337	1.35915	1.01122202780662	0.959689812587847
8	1.305	1.35029162149220	1.35212083333333	0.998647153570865	0.966457896374898
9	1.2785	1.32594739111901	1.3542625	0.97909186078697	0.964216234040047
10	1.3239	1.35328362355783	1.36421666666667	0.99198584552148	0.978287165346332
11	1.3449	1.37115790912445	1.37762916666667	0.995302612851992	0.980849828491882
12	1.2732	1.36227688912274	1.39197916666667	0.97866183757976	0.934611759302395
13	1.3322	1.38500445802215	1.41059166666667	0.981860655178136	0.961874160248149
14	1.4369	1.43421469651468	1.43157916666667	1.00184099483241	1.00187231625212
15	1.4975	1.46389495327590	1.45007916666667	1.00952760851050	1.02295591404895
16	1.577	1.48947304864688	1.46442083333333	1.01710725137427	1.05876370266158
17	1.5553	1.49002400558494	1.47525416666667	1.01001172492984	1.04380868641740
18	1.5557	1.52487353198596	1.48805833333333	1.02474042705716	1.02021575387559
19	1.575	1.51679512088389	1.4999625	1.01122202780662	1.03837359331839
20	1.5527	1.49973084596447	1.5017625	0.998647153570865	1.03531910687712
21	1.4748	1.46291418334427	1.49415416666667	0.97909186078697	1.00812475317490
22	1.4718	1.46809771862823	1.47995833333333	0.99198584552148	1.0025218221681
23	1.457	1.45563836548448	1.46250833333333	0.995302612851992	1.00093542087637
24	1.4684	1.41425606597120	1.44509166666667	0.97866183757976	1.03828439229046
25	1.4227	1.40136880227512	1.42725833333333	0.981860655178136	1.01522168731761
26	1.3896	1.41102207748431	1.40842916666667	1.00184099483241	0.984818042306961
27	1.3622	1.40519512920605	1.39193333333333	1.00952760851050	0.96940273396027
28	1.3716	1.40136613299658	1.37779583333333	1.01710725137427	0.97875920339752
29	1.3419	1.3786449626183	1.36497916666667	1.01001172492984	0.97334704466006
30	1.3511	1.38525691855121	1.3518125	1.02474042705716	0.975342538922723
31	1.3516	1.35257687699321	1.33756666666667	1.01122202780662	0.999277766011066
32	1.3242	1.32416867636671	1.3259625	0.998647153570865	1.00002365531964
33	1.3074	1.29016158360725	1.3177125	0.97909186078697	1.01336143984737
34	1.2999	1.29953452382799	1.31003333333333	0.99198584552148	1.00028123621598
35	1.3213	1.29641068289926	1.30252916666667	0.995302612851992	1.01919863622620
36	1.2881	1.26857817368979	1.2962375	0.97866183757976	1.01538874522287
37	1.2611	1.26459970409487	1.2879625	0.981860655178136	0.99723255977086
38	1.2727	1.28003554174745	1.27768333333333	1.00184099483241	0.994269267135007
39	1.2811	1.27993799118011	1.26785833333333	1.00952760851050	1.00090786337143
40	1.2684	1.28093639648699	1.25939166666667	1.01710725137427	0.99021309994675
41	1.265	1.26251886454449	1.25000416666667	1.01001172492984	1.00196522644151
42	1.277	1.27046037221013	1.2397875	1.02474042705716	1.00514744728204
43	1.2271	1.24657552792838	1.23274166666667	1.01122202780662	0.984376776623598
44	1.202	1.22663413770129	1.22829583333333	0.998647153570865	0.97991728996924
45	1.1938	1.19857569912947	1.22417083333333	0.97909186078697	0.996015521478587
46	1.2103	1.20954074126741	1.2193125	0.99198584552148	1.00062772481049
47	1.1856	1.20889040647581	1.21459583333333	0.995302612851992	0.980734062946445
48	1.1786	1.18639096812138	1.21225833333333	0.97866183757976	0.993433051725171
49	1.2015	1.19268659327520	1.21472083333333	0.981860655178136	1.00738954120428
50	1.2256	1.22467130377053	1.22242083333333	1.00184099483241	1.00075832284680
51	1.2292	1.24356134635345	1.231825	1.00952760851050	0.988451437160248
52	1.2037	1.26176392479858	1.24054166666667	1.01710725137427	0.953981942535048
53	1.2165	1.26376875405409	1.25124166666667	1.01001172492984	0.962596991021929
54	1.2694	1.29396962550753	1.26272916666667	1.02474042705716	0.98101220846054
55	1.2938	NA	NA	1.01122202780662	NA
56	1.3201	NA	NA	0.998647153570865	NA
57	1.3014	NA	NA	0.97909186078697	NA
58	1.3119	NA	NA	0.99198584552148	NA
59	1.3408	NA	NA	0.995302612851992	NA
60	1.2991	NA	NA	0.97866183757976	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.4816 & NA & NA & 0.981860655178136 & NA \tabularnewline
2 & 1.4562 & NA & NA & 1.00184099483241 & NA \tabularnewline
3 & 1.4268 & NA & NA & 1.00952760851050 & NA \tabularnewline
4 & 1.4088 & NA & NA & 1.01710725137427 & NA \tabularnewline
5 & 1.4016 & NA & NA & 1.01001172492984 & NA \tabularnewline
6 & 1.365 & NA & NA & 1.02474042705716 & NA \tabularnewline
7 & 1.319 & 1.37440241909337 & 1.35915 & 1.01122202780662 & 0.959689812587847 \tabularnewline
8 & 1.305 & 1.35029162149220 & 1.35212083333333 & 0.998647153570865 & 0.966457896374898 \tabularnewline
9 & 1.2785 & 1.32594739111901 & 1.3542625 & 0.97909186078697 & 0.964216234040047 \tabularnewline
10 & 1.3239 & 1.35328362355783 & 1.36421666666667 & 0.99198584552148 & 0.978287165346332 \tabularnewline
11 & 1.3449 & 1.37115790912445 & 1.37762916666667 & 0.995302612851992 & 0.980849828491882 \tabularnewline
12 & 1.2732 & 1.36227688912274 & 1.39197916666667 & 0.97866183757976 & 0.934611759302395 \tabularnewline
13 & 1.3322 & 1.38500445802215 & 1.41059166666667 & 0.981860655178136 & 0.961874160248149 \tabularnewline
14 & 1.4369 & 1.43421469651468 & 1.43157916666667 & 1.00184099483241 & 1.00187231625212 \tabularnewline
15 & 1.4975 & 1.46389495327590 & 1.45007916666667 & 1.00952760851050 & 1.02295591404895 \tabularnewline
16 & 1.577 & 1.48947304864688 & 1.46442083333333 & 1.01710725137427 & 1.05876370266158 \tabularnewline
17 & 1.5553 & 1.49002400558494 & 1.47525416666667 & 1.01001172492984 & 1.04380868641740 \tabularnewline
18 & 1.5557 & 1.52487353198596 & 1.48805833333333 & 1.02474042705716 & 1.02021575387559 \tabularnewline
19 & 1.575 & 1.51679512088389 & 1.4999625 & 1.01122202780662 & 1.03837359331839 \tabularnewline
20 & 1.5527 & 1.49973084596447 & 1.5017625 & 0.998647153570865 & 1.03531910687712 \tabularnewline
21 & 1.4748 & 1.46291418334427 & 1.49415416666667 & 0.97909186078697 & 1.00812475317490 \tabularnewline
22 & 1.4718 & 1.46809771862823 & 1.47995833333333 & 0.99198584552148 & 1.0025218221681 \tabularnewline
23 & 1.457 & 1.45563836548448 & 1.46250833333333 & 0.995302612851992 & 1.00093542087637 \tabularnewline
24 & 1.4684 & 1.41425606597120 & 1.44509166666667 & 0.97866183757976 & 1.03828439229046 \tabularnewline
25 & 1.4227 & 1.40136880227512 & 1.42725833333333 & 0.981860655178136 & 1.01522168731761 \tabularnewline
26 & 1.3896 & 1.41102207748431 & 1.40842916666667 & 1.00184099483241 & 0.984818042306961 \tabularnewline
27 & 1.3622 & 1.40519512920605 & 1.39193333333333 & 1.00952760851050 & 0.96940273396027 \tabularnewline
28 & 1.3716 & 1.40136613299658 & 1.37779583333333 & 1.01710725137427 & 0.97875920339752 \tabularnewline
29 & 1.3419 & 1.3786449626183 & 1.36497916666667 & 1.01001172492984 & 0.97334704466006 \tabularnewline
30 & 1.3511 & 1.38525691855121 & 1.3518125 & 1.02474042705716 & 0.975342538922723 \tabularnewline
31 & 1.3516 & 1.35257687699321 & 1.33756666666667 & 1.01122202780662 & 0.999277766011066 \tabularnewline
32 & 1.3242 & 1.32416867636671 & 1.3259625 & 0.998647153570865 & 1.00002365531964 \tabularnewline
33 & 1.3074 & 1.29016158360725 & 1.3177125 & 0.97909186078697 & 1.01336143984737 \tabularnewline
34 & 1.2999 & 1.29953452382799 & 1.31003333333333 & 0.99198584552148 & 1.00028123621598 \tabularnewline
35 & 1.3213 & 1.29641068289926 & 1.30252916666667 & 0.995302612851992 & 1.01919863622620 \tabularnewline
36 & 1.2881 & 1.26857817368979 & 1.2962375 & 0.97866183757976 & 1.01538874522287 \tabularnewline
37 & 1.2611 & 1.26459970409487 & 1.2879625 & 0.981860655178136 & 0.99723255977086 \tabularnewline
38 & 1.2727 & 1.28003554174745 & 1.27768333333333 & 1.00184099483241 & 0.994269267135007 \tabularnewline
39 & 1.2811 & 1.27993799118011 & 1.26785833333333 & 1.00952760851050 & 1.00090786337143 \tabularnewline
40 & 1.2684 & 1.28093639648699 & 1.25939166666667 & 1.01710725137427 & 0.99021309994675 \tabularnewline
41 & 1.265 & 1.26251886454449 & 1.25000416666667 & 1.01001172492984 & 1.00196522644151 \tabularnewline
42 & 1.277 & 1.27046037221013 & 1.2397875 & 1.02474042705716 & 1.00514744728204 \tabularnewline
43 & 1.2271 & 1.24657552792838 & 1.23274166666667 & 1.01122202780662 & 0.984376776623598 \tabularnewline
44 & 1.202 & 1.22663413770129 & 1.22829583333333 & 0.998647153570865 & 0.97991728996924 \tabularnewline
45 & 1.1938 & 1.19857569912947 & 1.22417083333333 & 0.97909186078697 & 0.996015521478587 \tabularnewline
46 & 1.2103 & 1.20954074126741 & 1.2193125 & 0.99198584552148 & 1.00062772481049 \tabularnewline
47 & 1.1856 & 1.20889040647581 & 1.21459583333333 & 0.995302612851992 & 0.980734062946445 \tabularnewline
48 & 1.1786 & 1.18639096812138 & 1.21225833333333 & 0.97866183757976 & 0.993433051725171 \tabularnewline
49 & 1.2015 & 1.19268659327520 & 1.21472083333333 & 0.981860655178136 & 1.00738954120428 \tabularnewline
50 & 1.2256 & 1.22467130377053 & 1.22242083333333 & 1.00184099483241 & 1.00075832284680 \tabularnewline
51 & 1.2292 & 1.24356134635345 & 1.231825 & 1.00952760851050 & 0.988451437160248 \tabularnewline
52 & 1.2037 & 1.26176392479858 & 1.24054166666667 & 1.01710725137427 & 0.953981942535048 \tabularnewline
53 & 1.2165 & 1.26376875405409 & 1.25124166666667 & 1.01001172492984 & 0.962596991021929 \tabularnewline
54 & 1.2694 & 1.29396962550753 & 1.26272916666667 & 1.02474042705716 & 0.98101220846054 \tabularnewline
55 & 1.2938 & NA & NA & 1.01122202780662 & NA \tabularnewline
56 & 1.3201 & NA & NA & 0.998647153570865 & NA \tabularnewline
57 & 1.3014 & NA & NA & 0.97909186078697 & NA \tabularnewline
58 & 1.3119 & NA & NA & 0.99198584552148 & NA \tabularnewline
59 & 1.3408 & NA & NA & 0.995302612851992 & NA \tabularnewline
60 & 1.2991 & NA & NA & 0.97866183757976 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=63382&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]1.4816[/C][C]NA[/C][C]NA[/C][C]0.981860655178136[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.4562[/C][C]NA[/C][C]NA[/C][C]1.00184099483241[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.4268[/C][C]NA[/C][C]NA[/C][C]1.00952760851050[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.4088[/C][C]NA[/C][C]NA[/C][C]1.01710725137427[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.4016[/C][C]NA[/C][C]NA[/C][C]1.01001172492984[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.365[/C][C]NA[/C][C]NA[/C][C]1.02474042705716[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.319[/C][C]1.37440241909337[/C][C]1.35915[/C][C]1.01122202780662[/C][C]0.959689812587847[/C][/ROW]
[ROW][C]8[/C][C]1.305[/C][C]1.35029162149220[/C][C]1.35212083333333[/C][C]0.998647153570865[/C][C]0.966457896374898[/C][/ROW]
[ROW][C]9[/C][C]1.2785[/C][C]1.32594739111901[/C][C]1.3542625[/C][C]0.97909186078697[/C][C]0.964216234040047[/C][/ROW]
[ROW][C]10[/C][C]1.3239[/C][C]1.35328362355783[/C][C]1.36421666666667[/C][C]0.99198584552148[/C][C]0.978287165346332[/C][/ROW]
[ROW][C]11[/C][C]1.3449[/C][C]1.37115790912445[/C][C]1.37762916666667[/C][C]0.995302612851992[/C][C]0.980849828491882[/C][/ROW]
[ROW][C]12[/C][C]1.2732[/C][C]1.36227688912274[/C][C]1.39197916666667[/C][C]0.97866183757976[/C][C]0.934611759302395[/C][/ROW]
[ROW][C]13[/C][C]1.3322[/C][C]1.38500445802215[/C][C]1.41059166666667[/C][C]0.981860655178136[/C][C]0.961874160248149[/C][/ROW]
[ROW][C]14[/C][C]1.4369[/C][C]1.43421469651468[/C][C]1.43157916666667[/C][C]1.00184099483241[/C][C]1.00187231625212[/C][/ROW]
[ROW][C]15[/C][C]1.4975[/C][C]1.46389495327590[/C][C]1.45007916666667[/C][C]1.00952760851050[/C][C]1.02295591404895[/C][/ROW]
[ROW][C]16[/C][C]1.577[/C][C]1.48947304864688[/C][C]1.46442083333333[/C][C]1.01710725137427[/C][C]1.05876370266158[/C][/ROW]
[ROW][C]17[/C][C]1.5553[/C][C]1.49002400558494[/C][C]1.47525416666667[/C][C]1.01001172492984[/C][C]1.04380868641740[/C][/ROW]
[ROW][C]18[/C][C]1.5557[/C][C]1.52487353198596[/C][C]1.48805833333333[/C][C]1.02474042705716[/C][C]1.02021575387559[/C][/ROW]
[ROW][C]19[/C][C]1.575[/C][C]1.51679512088389[/C][C]1.4999625[/C][C]1.01122202780662[/C][C]1.03837359331839[/C][/ROW]
[ROW][C]20[/C][C]1.5527[/C][C]1.49973084596447[/C][C]1.5017625[/C][C]0.998647153570865[/C][C]1.03531910687712[/C][/ROW]
[ROW][C]21[/C][C]1.4748[/C][C]1.46291418334427[/C][C]1.49415416666667[/C][C]0.97909186078697[/C][C]1.00812475317490[/C][/ROW]
[ROW][C]22[/C][C]1.4718[/C][C]1.46809771862823[/C][C]1.47995833333333[/C][C]0.99198584552148[/C][C]1.0025218221681[/C][/ROW]
[ROW][C]23[/C][C]1.457[/C][C]1.45563836548448[/C][C]1.46250833333333[/C][C]0.995302612851992[/C][C]1.00093542087637[/C][/ROW]
[ROW][C]24[/C][C]1.4684[/C][C]1.41425606597120[/C][C]1.44509166666667[/C][C]0.97866183757976[/C][C]1.03828439229046[/C][/ROW]
[ROW][C]25[/C][C]1.4227[/C][C]1.40136880227512[/C][C]1.42725833333333[/C][C]0.981860655178136[/C][C]1.01522168731761[/C][/ROW]
[ROW][C]26[/C][C]1.3896[/C][C]1.41102207748431[/C][C]1.40842916666667[/C][C]1.00184099483241[/C][C]0.984818042306961[/C][/ROW]
[ROW][C]27[/C][C]1.3622[/C][C]1.40519512920605[/C][C]1.39193333333333[/C][C]1.00952760851050[/C][C]0.96940273396027[/C][/ROW]
[ROW][C]28[/C][C]1.3716[/C][C]1.40136613299658[/C][C]1.37779583333333[/C][C]1.01710725137427[/C][C]0.97875920339752[/C][/ROW]
[ROW][C]29[/C][C]1.3419[/C][C]1.3786449626183[/C][C]1.36497916666667[/C][C]1.01001172492984[/C][C]0.97334704466006[/C][/ROW]
[ROW][C]30[/C][C]1.3511[/C][C]1.38525691855121[/C][C]1.3518125[/C][C]1.02474042705716[/C][C]0.975342538922723[/C][/ROW]
[ROW][C]31[/C][C]1.3516[/C][C]1.35257687699321[/C][C]1.33756666666667[/C][C]1.01122202780662[/C][C]0.999277766011066[/C][/ROW]
[ROW][C]32[/C][C]1.3242[/C][C]1.32416867636671[/C][C]1.3259625[/C][C]0.998647153570865[/C][C]1.00002365531964[/C][/ROW]
[ROW][C]33[/C][C]1.3074[/C][C]1.29016158360725[/C][C]1.3177125[/C][C]0.97909186078697[/C][C]1.01336143984737[/C][/ROW]
[ROW][C]34[/C][C]1.2999[/C][C]1.29953452382799[/C][C]1.31003333333333[/C][C]0.99198584552148[/C][C]1.00028123621598[/C][/ROW]
[ROW][C]35[/C][C]1.3213[/C][C]1.29641068289926[/C][C]1.30252916666667[/C][C]0.995302612851992[/C][C]1.01919863622620[/C][/ROW]
[ROW][C]36[/C][C]1.2881[/C][C]1.26857817368979[/C][C]1.2962375[/C][C]0.97866183757976[/C][C]1.01538874522287[/C][/ROW]
[ROW][C]37[/C][C]1.2611[/C][C]1.26459970409487[/C][C]1.2879625[/C][C]0.981860655178136[/C][C]0.99723255977086[/C][/ROW]
[ROW][C]38[/C][C]1.2727[/C][C]1.28003554174745[/C][C]1.27768333333333[/C][C]1.00184099483241[/C][C]0.994269267135007[/C][/ROW]
[ROW][C]39[/C][C]1.2811[/C][C]1.27993799118011[/C][C]1.26785833333333[/C][C]1.00952760851050[/C][C]1.00090786337143[/C][/ROW]
[ROW][C]40[/C][C]1.2684[/C][C]1.28093639648699[/C][C]1.25939166666667[/C][C]1.01710725137427[/C][C]0.99021309994675[/C][/ROW]
[ROW][C]41[/C][C]1.265[/C][C]1.26251886454449[/C][C]1.25000416666667[/C][C]1.01001172492984[/C][C]1.00196522644151[/C][/ROW]
[ROW][C]42[/C][C]1.277[/C][C]1.27046037221013[/C][C]1.2397875[/C][C]1.02474042705716[/C][C]1.00514744728204[/C][/ROW]
[ROW][C]43[/C][C]1.2271[/C][C]1.24657552792838[/C][C]1.23274166666667[/C][C]1.01122202780662[/C][C]0.984376776623598[/C][/ROW]
[ROW][C]44[/C][C]1.202[/C][C]1.22663413770129[/C][C]1.22829583333333[/C][C]0.998647153570865[/C][C]0.97991728996924[/C][/ROW]
[ROW][C]45[/C][C]1.1938[/C][C]1.19857569912947[/C][C]1.22417083333333[/C][C]0.97909186078697[/C][C]0.996015521478587[/C][/ROW]
[ROW][C]46[/C][C]1.2103[/C][C]1.20954074126741[/C][C]1.2193125[/C][C]0.99198584552148[/C][C]1.00062772481049[/C][/ROW]
[ROW][C]47[/C][C]1.1856[/C][C]1.20889040647581[/C][C]1.21459583333333[/C][C]0.995302612851992[/C][C]0.980734062946445[/C][/ROW]
[ROW][C]48[/C][C]1.1786[/C][C]1.18639096812138[/C][C]1.21225833333333[/C][C]0.97866183757976[/C][C]0.993433051725171[/C][/ROW]
[ROW][C]49[/C][C]1.2015[/C][C]1.19268659327520[/C][C]1.21472083333333[/C][C]0.981860655178136[/C][C]1.00738954120428[/C][/ROW]
[ROW][C]50[/C][C]1.2256[/C][C]1.22467130377053[/C][C]1.22242083333333[/C][C]1.00184099483241[/C][C]1.00075832284680[/C][/ROW]
[ROW][C]51[/C][C]1.2292[/C][C]1.24356134635345[/C][C]1.231825[/C][C]1.00952760851050[/C][C]0.988451437160248[/C][/ROW]
[ROW][C]52[/C][C]1.2037[/C][C]1.26176392479858[/C][C]1.24054166666667[/C][C]1.01710725137427[/C][C]0.953981942535048[/C][/ROW]
[ROW][C]53[/C][C]1.2165[/C][C]1.26376875405409[/C][C]1.25124166666667[/C][C]1.01001172492984[/C][C]0.962596991021929[/C][/ROW]
[ROW][C]54[/C][C]1.2694[/C][C]1.29396962550753[/C][C]1.26272916666667[/C][C]1.02474042705716[/C][C]0.98101220846054[/C][/ROW]
[ROW][C]55[/C][C]1.2938[/C][C]NA[/C][C]NA[/C][C]1.01122202780662[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]1.3201[/C][C]NA[/C][C]NA[/C][C]0.998647153570865[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]1.3014[/C][C]NA[/C][C]NA[/C][C]0.97909186078697[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]1.3119[/C][C]NA[/C][C]NA[/C][C]0.99198584552148[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]1.3408[/C][C]NA[/C][C]NA[/C][C]0.995302612851992[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]1.2991[/C][C]NA[/C][C]NA[/C][C]0.97866183757976[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=63382&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=63382&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	1.4816	NA	NA	0.981860655178136	NA
2	1.4562	NA	NA	1.00184099483241	NA
3	1.4268	NA	NA	1.00952760851050	NA
4	1.4088	NA	NA	1.01710725137427	NA
5	1.4016	NA	NA	1.01001172492984	NA
6	1.365	NA	NA	1.02474042705716	NA
7	1.319	1.37440241909337	1.35915	1.01122202780662	0.959689812587847
8	1.305	1.35029162149220	1.35212083333333	0.998647153570865	0.966457896374898
9	1.2785	1.32594739111901	1.3542625	0.97909186078697	0.964216234040047
10	1.3239	1.35328362355783	1.36421666666667	0.99198584552148	0.978287165346332
11	1.3449	1.37115790912445	1.37762916666667	0.995302612851992	0.980849828491882
12	1.2732	1.36227688912274	1.39197916666667	0.97866183757976	0.934611759302395
13	1.3322	1.38500445802215	1.41059166666667	0.981860655178136	0.961874160248149
14	1.4369	1.43421469651468	1.43157916666667	1.00184099483241	1.00187231625212
15	1.4975	1.46389495327590	1.45007916666667	1.00952760851050	1.02295591404895
16	1.577	1.48947304864688	1.46442083333333	1.01710725137427	1.05876370266158
17	1.5553	1.49002400558494	1.47525416666667	1.01001172492984	1.04380868641740
18	1.5557	1.52487353198596	1.48805833333333	1.02474042705716	1.02021575387559
19	1.575	1.51679512088389	1.4999625	1.01122202780662	1.03837359331839
20	1.5527	1.49973084596447	1.5017625	0.998647153570865	1.03531910687712
21	1.4748	1.46291418334427	1.49415416666667	0.97909186078697	1.00812475317490
22	1.4718	1.46809771862823	1.47995833333333	0.99198584552148	1.0025218221681
23	1.457	1.45563836548448	1.46250833333333	0.995302612851992	1.00093542087637
24	1.4684	1.41425606597120	1.44509166666667	0.97866183757976	1.03828439229046
25	1.4227	1.40136880227512	1.42725833333333	0.981860655178136	1.01522168731761
26	1.3896	1.41102207748431	1.40842916666667	1.00184099483241	0.984818042306961
27	1.3622	1.40519512920605	1.39193333333333	1.00952760851050	0.96940273396027
28	1.3716	1.40136613299658	1.37779583333333	1.01710725137427	0.97875920339752
29	1.3419	1.3786449626183	1.36497916666667	1.01001172492984	0.97334704466006
30	1.3511	1.38525691855121	1.3518125	1.02474042705716	0.975342538922723
31	1.3516	1.35257687699321	1.33756666666667	1.01122202780662	0.999277766011066
32	1.3242	1.32416867636671	1.3259625	0.998647153570865	1.00002365531964
33	1.3074	1.29016158360725	1.3177125	0.97909186078697	1.01336143984737
34	1.2999	1.29953452382799	1.31003333333333	0.99198584552148	1.00028123621598
35	1.3213	1.29641068289926	1.30252916666667	0.995302612851992	1.01919863622620
36	1.2881	1.26857817368979	1.2962375	0.97866183757976	1.01538874522287
37	1.2611	1.26459970409487	1.2879625	0.981860655178136	0.99723255977086
38	1.2727	1.28003554174745	1.27768333333333	1.00184099483241	0.994269267135007
39	1.2811	1.27993799118011	1.26785833333333	1.00952760851050	1.00090786337143
40	1.2684	1.28093639648699	1.25939166666667	1.01710725137427	0.99021309994675
41	1.265	1.26251886454449	1.25000416666667	1.01001172492984	1.00196522644151
42	1.277	1.27046037221013	1.2397875	1.02474042705716	1.00514744728204
43	1.2271	1.24657552792838	1.23274166666667	1.01122202780662	0.984376776623598
44	1.202	1.22663413770129	1.22829583333333	0.998647153570865	0.97991728996924
45	1.1938	1.19857569912947	1.22417083333333	0.97909186078697	0.996015521478587
46	1.2103	1.20954074126741	1.2193125	0.99198584552148	1.00062772481049
47	1.1856	1.20889040647581	1.21459583333333	0.995302612851992	0.980734062946445
48	1.1786	1.18639096812138	1.21225833333333	0.97866183757976	0.993433051725171
49	1.2015	1.19268659327520	1.21472083333333	0.981860655178136	1.00738954120428
50	1.2256	1.22467130377053	1.22242083333333	1.00184099483241	1.00075832284680
51	1.2292	1.24356134635345	1.231825	1.00952760851050	0.988451437160248
52	1.2037	1.26176392479858	1.24054166666667	1.01710725137427	0.953981942535048
53	1.2165	1.26376875405409	1.25124166666667	1.01001172492984	0.962596991021929
54	1.2694	1.29396962550753	1.26272916666667	1.02474042705716	0.98101220846054
55	1.2938	NA	NA	1.01122202780662	NA
56	1.3201	NA	NA	0.998647153570865	NA
57	1.3014	NA	NA	0.97909186078697	NA
58	1.3119	NA	NA	0.99198584552148	NA
59	1.3408	NA	NA	0.995302612851992	NA
60	1.2991	NA	NA	0.97866183757976	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