Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 06 May 2013 14:27:33 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/May/06/t1367864940qbwrl4pifsuxwcq.htm/, Retrieved Wed, 11 Feb 2026 22:38:32 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=208748, Retrieved Wed, 11 Feb 2026 22:38:32 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

355

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

-       [Classical Decomposition] [multiplicatief ge...] [2013-05-06 18:27:33] [2ad6cfb061f4abd47c32d0a7b72d8383] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

4,69
4,69
4,69
4,69
4,69
4,69
4,69
4,73
4,78
4,79
4,79
4,8
4,8
4,81
5,16
5,26
5,29
5,29
5,29
5,3
5,3
5,3
5,3
5,3
5,3
5,3
5,3
5,35
5,44
5,47
5,47
5,48
5,48
5,48
5,48
5,48
5,48
5,48
5,5
5,55
5,57
5,58
5,58
5,58
5,59
5,59
5,59
5,55
5,61
5,61
5,61
5,63
5,69
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,7
5,71
5,74
5,77
5,79
5,79
5,8
5,8
5,8
5,8

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208748&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208748&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208748&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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	4.69	NA	NA	0.990704330887249	NA
2	4.69	NA	NA	0.987728711706571	NA
3	4.69	NA	NA	0.999100359542284	NA
4	4.69	NA	NA	1.00453554145679	NA
5	4.69	NA	NA	1.00972300656743	NA
6	4.69	NA	NA	1.00940966399803	NA
7	4.69	4.75145186056685	4.73125	1.00426987805904	0.9870667193165
8	4.73	4.75744588633082	4.74083333333333	1.00350414195763	0.994230961951733
9	4.78	4.77839649530497	4.76541666666667	1.00272375524455	1.00033557380527
10	4.79	4.80790618722694	4.80875	0.999824525547582	0.996275678740466
11	4.79	4.84029539847875	4.8575	0.996458136588524	0.989609022933898
12	4.8	4.86832808199043	4.9075	0.992017948444305	0.985964774592083
13	4.8	4.91141672037354	4.9575	0.990704330887249	0.977314749141249
14	4.81	4.94481686298102	5.00625	0.987728711706571	0.972735721723019
15	5.16	5.04712198295444	5.05166666666667	0.999100359542284	1.02236482839662
16	5.26	5.11769002724676	5.09458333333333	1.00453554145679	1.02780746235031
17	5.29	5.18703122832076	5.13708333333333	1.00972300656743	1.01985119563519
18	5.29	5.22790088478982	5.17916666666667	1.00940966399803	1.01187840331688
19	5.29	5.24312565503326	5.22083333333333	1.00426987805904	1.00894015288795
20	5.3	5.28052242032623	5.26208333333333	1.00350414195763	1.00368857058514
21	5.3	5.30273745898493	5.28833333333333	1.00272375524455	0.999483764941013
22	5.3	5.29698701764063	5.29791666666666	0.999824525547582	1.00056881059918
23	5.3	5.28911675083383	5.30791666666667	0.996458136588524	1.00205766854446
24	5.3	5.27918884897111	5.32166666666667	0.992017948444305	1.0039421114918
25	5.3	5.28705877916828	5.33666666666667	0.990704330887249	1.00244771646623
26	5.3	5.28599482214966	5.35166666666666	0.987728711706571	1.00264948762183
27	5.3	5.36183859621026	5.36666666666667	0.999100359542284	0.988466904570017
28	5.35	5.40607543893998	5.38166666666667	1.00453554145679	0.989627329552957
29	5.44	5.44913849210888	5.39666666666667	1.00972300656743	0.998322947357254
30	5.47	5.46258863166936	5.41166666666667	1.00940966399803	1.00135675022052
31	5.47	5.44983787160041	5.42666666666666	1.00426987805904	1.00369958315726
32	5.48	5.46073503915279	5.44166666666667	1.00350414195763	1.0035279061718
33	5.48	5.47236489424714	5.4575	1.00272375524455	1.00139521137578
34	5.48	5.47320609026839	5.47416666666667	0.999824525547582	1.00124130347361
35	5.48	5.46847921541977	5.48791666666667	0.996458136588524	1.00210676206792
36	5.48	5.45403201238442	5.49791666666667	0.992017948444305	1.00476124591066
37	5.48	5.45589130889032	5.50708333333333	0.990704330887249	1.00441883639991
38	5.48	5.44814695232149	5.51583333333333	0.987728711706571	1.00584658379395
39	5.5	5.51961319465464	5.52458333333333	0.999100359542284	0.996446636029923
40	5.55	5.55884855253653	5.53375	1.00453554145679	0.998408204063682
41	5.57	5.59681048181937	5.54291666666667	1.00972300656743	0.995209685604602
42	5.58	5.60264422254909	5.55041666666667	1.00940966399803	0.995958297252224
43	5.58	5.58248518466071	5.55875	1.00426987805904	0.999554824674226
44	5.58	5.58909994397821	5.56958333333333	1.00350414195763	0.998371840892197
45	5.59	5.59478075269991	5.57958333333333	1.00272375524455	0.999145497757423
46	5.59	5.58651953649712	5.5875	0.999824525547582	1.00062301106801
47	5.59	5.57601365599328	5.59583333333333	0.996458136588524	1.00250830519249
48	5.55	5.56108728265403	5.60583333333333	0.992017948444305	0.998006274296644
49	5.61	5.56363040487431	5.61583333333333	0.990704330887249	1.00833441327897
50	5.61	5.55679711060922	5.62583333333333	0.987728711706571	1.00957438040867
51	5.61	5.63034681783725	5.63541666666667	0.999100359542284	0.996386222999126
52	5.63	5.67018457504799	5.64458333333333	1.00453554145679	0.992913004062544
53	5.69	5.70872144838059	5.65375	1.00972300656743	0.996720553183427
54	5.7	5.71788515918886	5.66458333333333	1.00940966399803	0.996872067435611
55	5.7	5.69881311220255	5.67458333333333	1.00426987805904	1.00020826929645
56	5.7	5.70199415994844	5.68208333333333	1.00350414195763	0.999650269731518
57	5.7	5.70508036577681	5.68958333333333	1.00272375524455	0.999109501452901
58	5.7	5.69566704720273	5.69666666666667	0.999824525547582	1.00076074545112
59	5.7	5.68188733300581	5.70208333333333	0.996458136588524	1.00318779059362
60	5.7	5.66152909993402	5.70708333333333	0.992017948444305	1.0067951430412
61	5.7	5.66063687060702	5.71375	0.990704330887249	1.00695383404602
62	5.7	5.65104289185122	5.72125	0.987728711706571	1.00866337578492
63	5.7	5.72401247654433	5.72916666666667	0.999100359542284	0.995804957336705
64	5.71	5.76352266910835	5.7375	1.00453554145679	0.99071354930289
65	5.74	5.80170010856868	5.74583333333333	1.00972300656743	0.989365167551913
66	5.77	5.80831144158868	5.75416666666667	1.00940966399803	0.993404031107153
67	5.79	NA	NA	1.00426987805904	NA
68	5.79	NA	NA	1.00350414195763	NA
69	5.8	NA	NA	1.00272375524455	NA
70	5.8	NA	NA	0.999824525547582	NA
71	5.8	NA	NA	0.996458136588524	NA
72	5.8	NA	NA	0.992017948444305	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 4.69 & NA & NA & 0.990704330887249 & NA \tabularnewline
2 & 4.69 & NA & NA & 0.987728711706571 & NA \tabularnewline
3 & 4.69 & NA & NA & 0.999100359542284 & NA \tabularnewline
4 & 4.69 & NA & NA & 1.00453554145679 & NA \tabularnewline
5 & 4.69 & NA & NA & 1.00972300656743 & NA \tabularnewline
6 & 4.69 & NA & NA & 1.00940966399803 & NA \tabularnewline
7 & 4.69 & 4.75145186056685 & 4.73125 & 1.00426987805904 & 0.9870667193165 \tabularnewline
8 & 4.73 & 4.75744588633082 & 4.74083333333333 & 1.00350414195763 & 0.994230961951733 \tabularnewline
9 & 4.78 & 4.77839649530497 & 4.76541666666667 & 1.00272375524455 & 1.00033557380527 \tabularnewline
10 & 4.79 & 4.80790618722694 & 4.80875 & 0.999824525547582 & 0.996275678740466 \tabularnewline
11 & 4.79 & 4.84029539847875 & 4.8575 & 0.996458136588524 & 0.989609022933898 \tabularnewline
12 & 4.8 & 4.86832808199043 & 4.9075 & 0.992017948444305 & 0.985964774592083 \tabularnewline
13 & 4.8 & 4.91141672037354 & 4.9575 & 0.990704330887249 & 0.977314749141249 \tabularnewline
14 & 4.81 & 4.94481686298102 & 5.00625 & 0.987728711706571 & 0.972735721723019 \tabularnewline
15 & 5.16 & 5.04712198295444 & 5.05166666666667 & 0.999100359542284 & 1.02236482839662 \tabularnewline
16 & 5.26 & 5.11769002724676 & 5.09458333333333 & 1.00453554145679 & 1.02780746235031 \tabularnewline
17 & 5.29 & 5.18703122832076 & 5.13708333333333 & 1.00972300656743 & 1.01985119563519 \tabularnewline
18 & 5.29 & 5.22790088478982 & 5.17916666666667 & 1.00940966399803 & 1.01187840331688 \tabularnewline
19 & 5.29 & 5.24312565503326 & 5.22083333333333 & 1.00426987805904 & 1.00894015288795 \tabularnewline
20 & 5.3 & 5.28052242032623 & 5.26208333333333 & 1.00350414195763 & 1.00368857058514 \tabularnewline
21 & 5.3 & 5.30273745898493 & 5.28833333333333 & 1.00272375524455 & 0.999483764941013 \tabularnewline
22 & 5.3 & 5.29698701764063 & 5.29791666666666 & 0.999824525547582 & 1.00056881059918 \tabularnewline
23 & 5.3 & 5.28911675083383 & 5.30791666666667 & 0.996458136588524 & 1.00205766854446 \tabularnewline
24 & 5.3 & 5.27918884897111 & 5.32166666666667 & 0.992017948444305 & 1.0039421114918 \tabularnewline
25 & 5.3 & 5.28705877916828 & 5.33666666666667 & 0.990704330887249 & 1.00244771646623 \tabularnewline
26 & 5.3 & 5.28599482214966 & 5.35166666666666 & 0.987728711706571 & 1.00264948762183 \tabularnewline
27 & 5.3 & 5.36183859621026 & 5.36666666666667 & 0.999100359542284 & 0.988466904570017 \tabularnewline
28 & 5.35 & 5.40607543893998 & 5.38166666666667 & 1.00453554145679 & 0.989627329552957 \tabularnewline
29 & 5.44 & 5.44913849210888 & 5.39666666666667 & 1.00972300656743 & 0.998322947357254 \tabularnewline
30 & 5.47 & 5.46258863166936 & 5.41166666666667 & 1.00940966399803 & 1.00135675022052 \tabularnewline
31 & 5.47 & 5.44983787160041 & 5.42666666666666 & 1.00426987805904 & 1.00369958315726 \tabularnewline
32 & 5.48 & 5.46073503915279 & 5.44166666666667 & 1.00350414195763 & 1.0035279061718 \tabularnewline
33 & 5.48 & 5.47236489424714 & 5.4575 & 1.00272375524455 & 1.00139521137578 \tabularnewline
34 & 5.48 & 5.47320609026839 & 5.47416666666667 & 0.999824525547582 & 1.00124130347361 \tabularnewline
35 & 5.48 & 5.46847921541977 & 5.48791666666667 & 0.996458136588524 & 1.00210676206792 \tabularnewline
36 & 5.48 & 5.45403201238442 & 5.49791666666667 & 0.992017948444305 & 1.00476124591066 \tabularnewline
37 & 5.48 & 5.45589130889032 & 5.50708333333333 & 0.990704330887249 & 1.00441883639991 \tabularnewline
38 & 5.48 & 5.44814695232149 & 5.51583333333333 & 0.987728711706571 & 1.00584658379395 \tabularnewline
39 & 5.5 & 5.51961319465464 & 5.52458333333333 & 0.999100359542284 & 0.996446636029923 \tabularnewline
40 & 5.55 & 5.55884855253653 & 5.53375 & 1.00453554145679 & 0.998408204063682 \tabularnewline
41 & 5.57 & 5.59681048181937 & 5.54291666666667 & 1.00972300656743 & 0.995209685604602 \tabularnewline
42 & 5.58 & 5.60264422254909 & 5.55041666666667 & 1.00940966399803 & 0.995958297252224 \tabularnewline
43 & 5.58 & 5.58248518466071 & 5.55875 & 1.00426987805904 & 0.999554824674226 \tabularnewline
44 & 5.58 & 5.58909994397821 & 5.56958333333333 & 1.00350414195763 & 0.998371840892197 \tabularnewline
45 & 5.59 & 5.59478075269991 & 5.57958333333333 & 1.00272375524455 & 0.999145497757423 \tabularnewline
46 & 5.59 & 5.58651953649712 & 5.5875 & 0.999824525547582 & 1.00062301106801 \tabularnewline
47 & 5.59 & 5.57601365599328 & 5.59583333333333 & 0.996458136588524 & 1.00250830519249 \tabularnewline
48 & 5.55 & 5.56108728265403 & 5.60583333333333 & 0.992017948444305 & 0.998006274296644 \tabularnewline
49 & 5.61 & 5.56363040487431 & 5.61583333333333 & 0.990704330887249 & 1.00833441327897 \tabularnewline
50 & 5.61 & 5.55679711060922 & 5.62583333333333 & 0.987728711706571 & 1.00957438040867 \tabularnewline
51 & 5.61 & 5.63034681783725 & 5.63541666666667 & 0.999100359542284 & 0.996386222999126 \tabularnewline
52 & 5.63 & 5.67018457504799 & 5.64458333333333 & 1.00453554145679 & 0.992913004062544 \tabularnewline
53 & 5.69 & 5.70872144838059 & 5.65375 & 1.00972300656743 & 0.996720553183427 \tabularnewline
54 & 5.7 & 5.71788515918886 & 5.66458333333333 & 1.00940966399803 & 0.996872067435611 \tabularnewline
55 & 5.7 & 5.69881311220255 & 5.67458333333333 & 1.00426987805904 & 1.00020826929645 \tabularnewline
56 & 5.7 & 5.70199415994844 & 5.68208333333333 & 1.00350414195763 & 0.999650269731518 \tabularnewline
57 & 5.7 & 5.70508036577681 & 5.68958333333333 & 1.00272375524455 & 0.999109501452901 \tabularnewline
58 & 5.7 & 5.69566704720273 & 5.69666666666667 & 0.999824525547582 & 1.00076074545112 \tabularnewline
59 & 5.7 & 5.68188733300581 & 5.70208333333333 & 0.996458136588524 & 1.00318779059362 \tabularnewline
60 & 5.7 & 5.66152909993402 & 5.70708333333333 & 0.992017948444305 & 1.0067951430412 \tabularnewline
61 & 5.7 & 5.66063687060702 & 5.71375 & 0.990704330887249 & 1.00695383404602 \tabularnewline
62 & 5.7 & 5.65104289185122 & 5.72125 & 0.987728711706571 & 1.00866337578492 \tabularnewline
63 & 5.7 & 5.72401247654433 & 5.72916666666667 & 0.999100359542284 & 0.995804957336705 \tabularnewline
64 & 5.71 & 5.76352266910835 & 5.7375 & 1.00453554145679 & 0.99071354930289 \tabularnewline
65 & 5.74 & 5.80170010856868 & 5.74583333333333 & 1.00972300656743 & 0.989365167551913 \tabularnewline
66 & 5.77 & 5.80831144158868 & 5.75416666666667 & 1.00940966399803 & 0.993404031107153 \tabularnewline
67 & 5.79 & NA & NA & 1.00426987805904 & NA \tabularnewline
68 & 5.79 & NA & NA & 1.00350414195763 & NA \tabularnewline
69 & 5.8 & NA & NA & 1.00272375524455 & NA \tabularnewline
70 & 5.8 & NA & NA & 0.999824525547582 & NA \tabularnewline
71 & 5.8 & NA & NA & 0.996458136588524 & NA \tabularnewline
72 & 5.8 & NA & NA & 0.992017948444305 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=208748&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]4.69[/C][C]NA[/C][C]NA[/C][C]0.990704330887249[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]4.69[/C][C]NA[/C][C]NA[/C][C]0.987728711706571[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]4.69[/C][C]NA[/C][C]NA[/C][C]0.999100359542284[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]4.69[/C][C]NA[/C][C]NA[/C][C]1.00453554145679[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]4.69[/C][C]NA[/C][C]NA[/C][C]1.00972300656743[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]4.69[/C][C]NA[/C][C]NA[/C][C]1.00940966399803[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]4.69[/C][C]4.75145186056685[/C][C]4.73125[/C][C]1.00426987805904[/C][C]0.9870667193165[/C][/ROW]
[ROW][C]8[/C][C]4.73[/C][C]4.75744588633082[/C][C]4.74083333333333[/C][C]1.00350414195763[/C][C]0.994230961951733[/C][/ROW]
[ROW][C]9[/C][C]4.78[/C][C]4.77839649530497[/C][C]4.76541666666667[/C][C]1.00272375524455[/C][C]1.00033557380527[/C][/ROW]
[ROW][C]10[/C][C]4.79[/C][C]4.80790618722694[/C][C]4.80875[/C][C]0.999824525547582[/C][C]0.996275678740466[/C][/ROW]
[ROW][C]11[/C][C]4.79[/C][C]4.84029539847875[/C][C]4.8575[/C][C]0.996458136588524[/C][C]0.989609022933898[/C][/ROW]
[ROW][C]12[/C][C]4.8[/C][C]4.86832808199043[/C][C]4.9075[/C][C]0.992017948444305[/C][C]0.985964774592083[/C][/ROW]
[ROW][C]13[/C][C]4.8[/C][C]4.91141672037354[/C][C]4.9575[/C][C]0.990704330887249[/C][C]0.977314749141249[/C][/ROW]
[ROW][C]14[/C][C]4.81[/C][C]4.94481686298102[/C][C]5.00625[/C][C]0.987728711706571[/C][C]0.972735721723019[/C][/ROW]
[ROW][C]15[/C][C]5.16[/C][C]5.04712198295444[/C][C]5.05166666666667[/C][C]0.999100359542284[/C][C]1.02236482839662[/C][/ROW]
[ROW][C]16[/C][C]5.26[/C][C]5.11769002724676[/C][C]5.09458333333333[/C][C]1.00453554145679[/C][C]1.02780746235031[/C][/ROW]
[ROW][C]17[/C][C]5.29[/C][C]5.18703122832076[/C][C]5.13708333333333[/C][C]1.00972300656743[/C][C]1.01985119563519[/C][/ROW]
[ROW][C]18[/C][C]5.29[/C][C]5.22790088478982[/C][C]5.17916666666667[/C][C]1.00940966399803[/C][C]1.01187840331688[/C][/ROW]
[ROW][C]19[/C][C]5.29[/C][C]5.24312565503326[/C][C]5.22083333333333[/C][C]1.00426987805904[/C][C]1.00894015288795[/C][/ROW]
[ROW][C]20[/C][C]5.3[/C][C]5.28052242032623[/C][C]5.26208333333333[/C][C]1.00350414195763[/C][C]1.00368857058514[/C][/ROW]
[ROW][C]21[/C][C]5.3[/C][C]5.30273745898493[/C][C]5.28833333333333[/C][C]1.00272375524455[/C][C]0.999483764941013[/C][/ROW]
[ROW][C]22[/C][C]5.3[/C][C]5.29698701764063[/C][C]5.29791666666666[/C][C]0.999824525547582[/C][C]1.00056881059918[/C][/ROW]
[ROW][C]23[/C][C]5.3[/C][C]5.28911675083383[/C][C]5.30791666666667[/C][C]0.996458136588524[/C][C]1.00205766854446[/C][/ROW]
[ROW][C]24[/C][C]5.3[/C][C]5.27918884897111[/C][C]5.32166666666667[/C][C]0.992017948444305[/C][C]1.0039421114918[/C][/ROW]
[ROW][C]25[/C][C]5.3[/C][C]5.28705877916828[/C][C]5.33666666666667[/C][C]0.990704330887249[/C][C]1.00244771646623[/C][/ROW]
[ROW][C]26[/C][C]5.3[/C][C]5.28599482214966[/C][C]5.35166666666666[/C][C]0.987728711706571[/C][C]1.00264948762183[/C][/ROW]
[ROW][C]27[/C][C]5.3[/C][C]5.36183859621026[/C][C]5.36666666666667[/C][C]0.999100359542284[/C][C]0.988466904570017[/C][/ROW]
[ROW][C]28[/C][C]5.35[/C][C]5.40607543893998[/C][C]5.38166666666667[/C][C]1.00453554145679[/C][C]0.989627329552957[/C][/ROW]
[ROW][C]29[/C][C]5.44[/C][C]5.44913849210888[/C][C]5.39666666666667[/C][C]1.00972300656743[/C][C]0.998322947357254[/C][/ROW]
[ROW][C]30[/C][C]5.47[/C][C]5.46258863166936[/C][C]5.41166666666667[/C][C]1.00940966399803[/C][C]1.00135675022052[/C][/ROW]
[ROW][C]31[/C][C]5.47[/C][C]5.44983787160041[/C][C]5.42666666666666[/C][C]1.00426987805904[/C][C]1.00369958315726[/C][/ROW]
[ROW][C]32[/C][C]5.48[/C][C]5.46073503915279[/C][C]5.44166666666667[/C][C]1.00350414195763[/C][C]1.0035279061718[/C][/ROW]
[ROW][C]33[/C][C]5.48[/C][C]5.47236489424714[/C][C]5.4575[/C][C]1.00272375524455[/C][C]1.00139521137578[/C][/ROW]
[ROW][C]34[/C][C]5.48[/C][C]5.47320609026839[/C][C]5.47416666666667[/C][C]0.999824525547582[/C][C]1.00124130347361[/C][/ROW]
[ROW][C]35[/C][C]5.48[/C][C]5.46847921541977[/C][C]5.48791666666667[/C][C]0.996458136588524[/C][C]1.00210676206792[/C][/ROW]
[ROW][C]36[/C][C]5.48[/C][C]5.45403201238442[/C][C]5.49791666666667[/C][C]0.992017948444305[/C][C]1.00476124591066[/C][/ROW]
[ROW][C]37[/C][C]5.48[/C][C]5.45589130889032[/C][C]5.50708333333333[/C][C]0.990704330887249[/C][C]1.00441883639991[/C][/ROW]
[ROW][C]38[/C][C]5.48[/C][C]5.44814695232149[/C][C]5.51583333333333[/C][C]0.987728711706571[/C][C]1.00584658379395[/C][/ROW]
[ROW][C]39[/C][C]5.5[/C][C]5.51961319465464[/C][C]5.52458333333333[/C][C]0.999100359542284[/C][C]0.996446636029923[/C][/ROW]
[ROW][C]40[/C][C]5.55[/C][C]5.55884855253653[/C][C]5.53375[/C][C]1.00453554145679[/C][C]0.998408204063682[/C][/ROW]
[ROW][C]41[/C][C]5.57[/C][C]5.59681048181937[/C][C]5.54291666666667[/C][C]1.00972300656743[/C][C]0.995209685604602[/C][/ROW]
[ROW][C]42[/C][C]5.58[/C][C]5.60264422254909[/C][C]5.55041666666667[/C][C]1.00940966399803[/C][C]0.995958297252224[/C][/ROW]
[ROW][C]43[/C][C]5.58[/C][C]5.58248518466071[/C][C]5.55875[/C][C]1.00426987805904[/C][C]0.999554824674226[/C][/ROW]
[ROW][C]44[/C][C]5.58[/C][C]5.58909994397821[/C][C]5.56958333333333[/C][C]1.00350414195763[/C][C]0.998371840892197[/C][/ROW]
[ROW][C]45[/C][C]5.59[/C][C]5.59478075269991[/C][C]5.57958333333333[/C][C]1.00272375524455[/C][C]0.999145497757423[/C][/ROW]
[ROW][C]46[/C][C]5.59[/C][C]5.58651953649712[/C][C]5.5875[/C][C]0.999824525547582[/C][C]1.00062301106801[/C][/ROW]
[ROW][C]47[/C][C]5.59[/C][C]5.57601365599328[/C][C]5.59583333333333[/C][C]0.996458136588524[/C][C]1.00250830519249[/C][/ROW]
[ROW][C]48[/C][C]5.55[/C][C]5.56108728265403[/C][C]5.60583333333333[/C][C]0.992017948444305[/C][C]0.998006274296644[/C][/ROW]
[ROW][C]49[/C][C]5.61[/C][C]5.56363040487431[/C][C]5.61583333333333[/C][C]0.990704330887249[/C][C]1.00833441327897[/C][/ROW]
[ROW][C]50[/C][C]5.61[/C][C]5.55679711060922[/C][C]5.62583333333333[/C][C]0.987728711706571[/C][C]1.00957438040867[/C][/ROW]
[ROW][C]51[/C][C]5.61[/C][C]5.63034681783725[/C][C]5.63541666666667[/C][C]0.999100359542284[/C][C]0.996386222999126[/C][/ROW]
[ROW][C]52[/C][C]5.63[/C][C]5.67018457504799[/C][C]5.64458333333333[/C][C]1.00453554145679[/C][C]0.992913004062544[/C][/ROW]
[ROW][C]53[/C][C]5.69[/C][C]5.70872144838059[/C][C]5.65375[/C][C]1.00972300656743[/C][C]0.996720553183427[/C][/ROW]
[ROW][C]54[/C][C]5.7[/C][C]5.71788515918886[/C][C]5.66458333333333[/C][C]1.00940966399803[/C][C]0.996872067435611[/C][/ROW]
[ROW][C]55[/C][C]5.7[/C][C]5.69881311220255[/C][C]5.67458333333333[/C][C]1.00426987805904[/C][C]1.00020826929645[/C][/ROW]
[ROW][C]56[/C][C]5.7[/C][C]5.70199415994844[/C][C]5.68208333333333[/C][C]1.00350414195763[/C][C]0.999650269731518[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]5.70508036577681[/C][C]5.68958333333333[/C][C]1.00272375524455[/C][C]0.999109501452901[/C][/ROW]
[ROW][C]58[/C][C]5.7[/C][C]5.69566704720273[/C][C]5.69666666666667[/C][C]0.999824525547582[/C][C]1.00076074545112[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]5.68188733300581[/C][C]5.70208333333333[/C][C]0.996458136588524[/C][C]1.00318779059362[/C][/ROW]
[ROW][C]60[/C][C]5.7[/C][C]5.66152909993402[/C][C]5.70708333333333[/C][C]0.992017948444305[/C][C]1.0067951430412[/C][/ROW]
[ROW][C]61[/C][C]5.7[/C][C]5.66063687060702[/C][C]5.71375[/C][C]0.990704330887249[/C][C]1.00695383404602[/C][/ROW]
[ROW][C]62[/C][C]5.7[/C][C]5.65104289185122[/C][C]5.72125[/C][C]0.987728711706571[/C][C]1.00866337578492[/C][/ROW]
[ROW][C]63[/C][C]5.7[/C][C]5.72401247654433[/C][C]5.72916666666667[/C][C]0.999100359542284[/C][C]0.995804957336705[/C][/ROW]
[ROW][C]64[/C][C]5.71[/C][C]5.76352266910835[/C][C]5.7375[/C][C]1.00453554145679[/C][C]0.99071354930289[/C][/ROW]
[ROW][C]65[/C][C]5.74[/C][C]5.80170010856868[/C][C]5.74583333333333[/C][C]1.00972300656743[/C][C]0.989365167551913[/C][/ROW]
[ROW][C]66[/C][C]5.77[/C][C]5.80831144158868[/C][C]5.75416666666667[/C][C]1.00940966399803[/C][C]0.993404031107153[/C][/ROW]
[ROW][C]67[/C][C]5.79[/C][C]NA[/C][C]NA[/C][C]1.00426987805904[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]5.79[/C][C]NA[/C][C]NA[/C][C]1.00350414195763[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]5.8[/C][C]NA[/C][C]NA[/C][C]1.00272375524455[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]5.8[/C][C]NA[/C][C]NA[/C][C]0.999824525547582[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]5.8[/C][C]NA[/C][C]NA[/C][C]0.996458136588524[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]5.8[/C][C]NA[/C][C]NA[/C][C]0.992017948444305[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=208748&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=208748&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	4.69	NA	NA	0.990704330887249	NA
2	4.69	NA	NA	0.987728711706571	NA
3	4.69	NA	NA	0.999100359542284	NA
4	4.69	NA	NA	1.00453554145679	NA
5	4.69	NA	NA	1.00972300656743	NA
6	4.69	NA	NA	1.00940966399803	NA
7	4.69	4.75145186056685	4.73125	1.00426987805904	0.9870667193165
8	4.73	4.75744588633082	4.74083333333333	1.00350414195763	0.994230961951733
9	4.78	4.77839649530497	4.76541666666667	1.00272375524455	1.00033557380527
10	4.79	4.80790618722694	4.80875	0.999824525547582	0.996275678740466
11	4.79	4.84029539847875	4.8575	0.996458136588524	0.989609022933898
12	4.8	4.86832808199043	4.9075	0.992017948444305	0.985964774592083
13	4.8	4.91141672037354	4.9575	0.990704330887249	0.977314749141249
14	4.81	4.94481686298102	5.00625	0.987728711706571	0.972735721723019
15	5.16	5.04712198295444	5.05166666666667	0.999100359542284	1.02236482839662
16	5.26	5.11769002724676	5.09458333333333	1.00453554145679	1.02780746235031
17	5.29	5.18703122832076	5.13708333333333	1.00972300656743	1.01985119563519
18	5.29	5.22790088478982	5.17916666666667	1.00940966399803	1.01187840331688
19	5.29	5.24312565503326	5.22083333333333	1.00426987805904	1.00894015288795
20	5.3	5.28052242032623	5.26208333333333	1.00350414195763	1.00368857058514
21	5.3	5.30273745898493	5.28833333333333	1.00272375524455	0.999483764941013
22	5.3	5.29698701764063	5.29791666666666	0.999824525547582	1.00056881059918
23	5.3	5.28911675083383	5.30791666666667	0.996458136588524	1.00205766854446
24	5.3	5.27918884897111	5.32166666666667	0.992017948444305	1.0039421114918
25	5.3	5.28705877916828	5.33666666666667	0.990704330887249	1.00244771646623
26	5.3	5.28599482214966	5.35166666666666	0.987728711706571	1.00264948762183
27	5.3	5.36183859621026	5.36666666666667	0.999100359542284	0.988466904570017
28	5.35	5.40607543893998	5.38166666666667	1.00453554145679	0.989627329552957
29	5.44	5.44913849210888	5.39666666666667	1.00972300656743	0.998322947357254
30	5.47	5.46258863166936	5.41166666666667	1.00940966399803	1.00135675022052
31	5.47	5.44983787160041	5.42666666666666	1.00426987805904	1.00369958315726
32	5.48	5.46073503915279	5.44166666666667	1.00350414195763	1.0035279061718
33	5.48	5.47236489424714	5.4575	1.00272375524455	1.00139521137578
34	5.48	5.47320609026839	5.47416666666667	0.999824525547582	1.00124130347361
35	5.48	5.46847921541977	5.48791666666667	0.996458136588524	1.00210676206792
36	5.48	5.45403201238442	5.49791666666667	0.992017948444305	1.00476124591066
37	5.48	5.45589130889032	5.50708333333333	0.990704330887249	1.00441883639991
38	5.48	5.44814695232149	5.51583333333333	0.987728711706571	1.00584658379395
39	5.5	5.51961319465464	5.52458333333333	0.999100359542284	0.996446636029923
40	5.55	5.55884855253653	5.53375	1.00453554145679	0.998408204063682
41	5.57	5.59681048181937	5.54291666666667	1.00972300656743	0.995209685604602
42	5.58	5.60264422254909	5.55041666666667	1.00940966399803	0.995958297252224
43	5.58	5.58248518466071	5.55875	1.00426987805904	0.999554824674226
44	5.58	5.58909994397821	5.56958333333333	1.00350414195763	0.998371840892197
45	5.59	5.59478075269991	5.57958333333333	1.00272375524455	0.999145497757423
46	5.59	5.58651953649712	5.5875	0.999824525547582	1.00062301106801
47	5.59	5.57601365599328	5.59583333333333	0.996458136588524	1.00250830519249
48	5.55	5.56108728265403	5.60583333333333	0.992017948444305	0.998006274296644
49	5.61	5.56363040487431	5.61583333333333	0.990704330887249	1.00833441327897
50	5.61	5.55679711060922	5.62583333333333	0.987728711706571	1.00957438040867
51	5.61	5.63034681783725	5.63541666666667	0.999100359542284	0.996386222999126
52	5.63	5.67018457504799	5.64458333333333	1.00453554145679	0.992913004062544
53	5.69	5.70872144838059	5.65375	1.00972300656743	0.996720553183427
54	5.7	5.71788515918886	5.66458333333333	1.00940966399803	0.996872067435611
55	5.7	5.69881311220255	5.67458333333333	1.00426987805904	1.00020826929645
56	5.7	5.70199415994844	5.68208333333333	1.00350414195763	0.999650269731518
57	5.7	5.70508036577681	5.68958333333333	1.00272375524455	0.999109501452901
58	5.7	5.69566704720273	5.69666666666667	0.999824525547582	1.00076074545112
59	5.7	5.68188733300581	5.70208333333333	0.996458136588524	1.00318779059362
60	5.7	5.66152909993402	5.70708333333333	0.992017948444305	1.0067951430412
61	5.7	5.66063687060702	5.71375	0.990704330887249	1.00695383404602
62	5.7	5.65104289185122	5.72125	0.987728711706571	1.00866337578492
63	5.7	5.72401247654433	5.72916666666667	0.999100359542284	0.995804957336705
64	5.71	5.76352266910835	5.7375	1.00453554145679	0.99071354930289
65	5.74	5.80170010856868	5.74583333333333	1.00972300656743	0.989365167551913
66	5.77	5.80831144158868	5.75416666666667	1.00940966399803	0.993404031107153
67	5.79	NA	NA	1.00426987805904	NA
68	5.79	NA	NA	1.00350414195763	NA
69	5.8	NA	NA	1.00272375524455	NA
70	5.8	NA	NA	0.999824525547582	NA
71	5.8	NA	NA	0.996458136588524	NA
72	5.8	NA	NA	0.992017948444305	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