Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 28 Nov 2010 09:41:43 +0000

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/2010/Nov/28/t12909372570u5zpni85zwpvfx.htm/, Retrieved Fri, 03 May 2024 01:14:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102465, Retrieved Fri, 03 May 2024 01:14:48 +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

217

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

-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
-  M D    [Classical Decomposition] [WS8 - Classical D...] [2010-11-28 09:41:43] [934c3727858e074bf543f25f5906ed72] [Current]
-   PD      [Classical Decomposition] [ws 8 classical de...] [2010-11-29 18:48:39] [8214fe6d084e5ad7598b249a26cc9f06] 
- R  D        [Classical Decomposition] [paper classical d...] [2010-12-10 11:47:05] [8214fe6d084e5ad7598b249a26cc9f06] 
-    D          [Classical Decomposition] [paper classical d...] [2010-12-21 13:31:40] [8214fe6d084e5ad7598b249a26cc9f06] 
-    D            [Classical Decomposition] [CD laag geschoolden] [2010-12-21 19:07:58] [8214fe6d084e5ad7598b249a26cc9f06] 
-    D              [Classical Decomposition] [cd middengeschoold] [2010-12-21 19:12:54] [8214fe6d084e5ad7598b249a26cc9f06] 
-    D                [Classical Decomposition] [cd hoog geschoold] [2010-12-21 19:15:16] [8214fe6d084e5ad7598b249a26cc9f06] 
- R PD      [Classical Decomposition] [WS 8 - Classical ...] [2010-11-29 19:46:45] [18fa53e8b37a5effc0c5f8a5122cdd2d] 
-   PD      [Classical Decomposition] [Olieprijs classic...] [2010-11-30 19:52:26] [a8a0ff0853b70f438be515083758c362] 
- R  D      [Classical Decomposition] [Classical Decompo...] [2010-12-14 17:27:41] [8ef49741e164ec6343c90c7935194465] 
- R  D      [Classical Decomposition] [Paper; Classical ...] [2010-12-21 12:03:05] [8ffb4cfa64b4677df0d2c448735a40bb] 

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	13 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 13 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102465&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]13 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102465&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102465&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	13 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	167.16	NA	NA	0.999982204104269	NA
2	179.84	NA	NA	1.03716151365447	NA
3	174.44	NA	NA	1.05682814473984	NA
4	180.35	NA	NA	0.985682997956348	NA
5	193.17	NA	NA	0.983051682033842	NA
6	195.16	NA	NA	1.03398001321637	NA
7	202.43	193.914943701812	192.925416666667	0.989527035145743	1.06037081029508
8	189.91	195.964984695419	194.969166666667	0.995818028752133	0.978142014360496
9	195.98	197.842953812578	196.835833333333	1.00712047924496	0.988612649212912
10	212.09	199.571854037366	198.611666666667	0.960187370699353	1.11213996332746
11	205.81	200.42208125752	199.46625	0.955831257520136	1.07948303406991
12	204.31	201.728995939599	200.734166666667	0.994829272932542	1.02310396663975
13	196.07	204.394982204104	203.395	0.999982204104269	0.964003487319606
14	199.98	208.840494846988	207.803333333333	1.03716151365447	0.927871128448571
15	199.1	217.20932814474	216.1525	1.05682814473984	0.871578736689774
16	198.31	227.705682997956	226.72	0.985682997956348	0.887396100908084
17	195.72	237.663885015367	236.680833333333	0.983051682033842	0.841193226043899
18	223.04	249.394396679883	248.360416666667	1.03398001321637	0.868536816829029
19	238.41	263.426193701812	262.436666666667	0.989527035145743	0.91806258970965
20	259.73	280.038318028752	279.0425	0.995818028752133	0.9346989969479
21	326.54	299.451287145912	298.444166666667	1.00712047924496	1.08640527725365
22	335.15	316.260187370699	315.3	0.960187370699353	1.10702967716330
23	321.81	328.629164590853	327.673333333333	0.955831257520136	1.02748906244151
24	368.62	339.441079272932	338.44625	0.994829272932542	1.09481473118860
25	369.59	348.416232204104	347.41625	0.999982204104269	1.06384366678920
26	425	355.094244846988	354.057083333333	1.03716151365447	1.15736208221459
27	439.72	356.72307814474	355.66625	1.05682814473984	1.16984734235277
28	362.23	351.286932997956	350.30125	0.985682997956348	1.04907240486157
29	328.76	343.253885015367	342.270833333333	0.983051682033842	0.97708586117988
30	348.55	333.161480013216	332.1275	1.03398001321637	1.01495808317140
31	328.18	321.504110368479	320.514583333333	0.989527035145743	1.03475289920842
32	329.34	307.737901362085	306.742083333333	0.995818028752133	1.07817965762691
33	295.55	290.705453812578	289.698333333333	1.00712047924496	1.01298622530989
34	237.38	276.596020704033	275.635833333333	0.960187370699353	0.896917421734397
35	226.85	268.224164590853	267.268333333333	0.955831257520136	0.88799403709152
36	220.14	261.296495939599	260.301666666667	0.994829272932542	0.85010673591638
37	239.36	253.036232204104	252.03625	0.999982204104269	0.949721556726096
38	224.69	243.815078180321	242.777916666667	1.03716151365447	0.892335500171742
39	230.98	234.525161478073	233.468333333333	1.05682814473984	0.936142631792353
40	233.47	228.496099664623	227.510416666667	0.985682997956348	1.04110020506525
41	256.7	226.229301682034	225.24625	0.983051682033842	1.15928962361112
42	253.41	225.042730013216	224.00875	1.03398001321637	1.09407381083447
43	224.95	222.829110368479	221.839583333333	0.989527035145743	1.02475322191683
44	210.37	219.981651362085	218.985833333333	0.995818028752133	0.964690056260092
45	191.09	217.067120479245	216.06	1.00712047924496	0.878177208271354
46	198.85	213.666020704033	212.705833333333	0.960187370699353	0.973621611937199
47	211.04	208.841247924187	207.885416666667	0.955831257520136	1.06208561130187
48	206.25	201.762329272933	200.7675	0.994829272932542	1.03264724372992
49	201.19	NA	195.577916666667	NA	NA
50	194.37	NA	195.876666666667	NA	NA
51	191.08	NA	200.742916666667	NA	NA
52	192.87	NA	NA	NA	NA
53	181.61	NA	NA	NA	NA
54	157.67	NA	NA	NA	NA
55	196.14	NA	NA	NA	NA
56	246.35	NA	NA	NA	NA
57	271.9	NA	NA	NA	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 167.16 & NA & NA & 0.999982204104269 & NA \tabularnewline
2 & 179.84 & NA & NA & 1.03716151365447 & NA \tabularnewline
3 & 174.44 & NA & NA & 1.05682814473984 & NA \tabularnewline
4 & 180.35 & NA & NA & 0.985682997956348 & NA \tabularnewline
5 & 193.17 & NA & NA & 0.983051682033842 & NA \tabularnewline
6 & 195.16 & NA & NA & 1.03398001321637 & NA \tabularnewline
7 & 202.43 & 193.914943701812 & 192.925416666667 & 0.989527035145743 & 1.06037081029508 \tabularnewline
8 & 189.91 & 195.964984695419 & 194.969166666667 & 0.995818028752133 & 0.978142014360496 \tabularnewline
9 & 195.98 & 197.842953812578 & 196.835833333333 & 1.00712047924496 & 0.988612649212912 \tabularnewline
10 & 212.09 & 199.571854037366 & 198.611666666667 & 0.960187370699353 & 1.11213996332746 \tabularnewline
11 & 205.81 & 200.42208125752 & 199.46625 & 0.955831257520136 & 1.07948303406991 \tabularnewline
12 & 204.31 & 201.728995939599 & 200.734166666667 & 0.994829272932542 & 1.02310396663975 \tabularnewline
13 & 196.07 & 204.394982204104 & 203.395 & 0.999982204104269 & 0.964003487319606 \tabularnewline
14 & 199.98 & 208.840494846988 & 207.803333333333 & 1.03716151365447 & 0.927871128448571 \tabularnewline
15 & 199.1 & 217.20932814474 & 216.1525 & 1.05682814473984 & 0.871578736689774 \tabularnewline
16 & 198.31 & 227.705682997956 & 226.72 & 0.985682997956348 & 0.887396100908084 \tabularnewline
17 & 195.72 & 237.663885015367 & 236.680833333333 & 0.983051682033842 & 0.841193226043899 \tabularnewline
18 & 223.04 & 249.394396679883 & 248.360416666667 & 1.03398001321637 & 0.868536816829029 \tabularnewline
19 & 238.41 & 263.426193701812 & 262.436666666667 & 0.989527035145743 & 0.91806258970965 \tabularnewline
20 & 259.73 & 280.038318028752 & 279.0425 & 0.995818028752133 & 0.9346989969479 \tabularnewline
21 & 326.54 & 299.451287145912 & 298.444166666667 & 1.00712047924496 & 1.08640527725365 \tabularnewline
22 & 335.15 & 316.260187370699 & 315.3 & 0.960187370699353 & 1.10702967716330 \tabularnewline
23 & 321.81 & 328.629164590853 & 327.673333333333 & 0.955831257520136 & 1.02748906244151 \tabularnewline
24 & 368.62 & 339.441079272932 & 338.44625 & 0.994829272932542 & 1.09481473118860 \tabularnewline
25 & 369.59 & 348.416232204104 & 347.41625 & 0.999982204104269 & 1.06384366678920 \tabularnewline
26 & 425 & 355.094244846988 & 354.057083333333 & 1.03716151365447 & 1.15736208221459 \tabularnewline
27 & 439.72 & 356.72307814474 & 355.66625 & 1.05682814473984 & 1.16984734235277 \tabularnewline
28 & 362.23 & 351.286932997956 & 350.30125 & 0.985682997956348 & 1.04907240486157 \tabularnewline
29 & 328.76 & 343.253885015367 & 342.270833333333 & 0.983051682033842 & 0.97708586117988 \tabularnewline
30 & 348.55 & 333.161480013216 & 332.1275 & 1.03398001321637 & 1.01495808317140 \tabularnewline
31 & 328.18 & 321.504110368479 & 320.514583333333 & 0.989527035145743 & 1.03475289920842 \tabularnewline
32 & 329.34 & 307.737901362085 & 306.742083333333 & 0.995818028752133 & 1.07817965762691 \tabularnewline
33 & 295.55 & 290.705453812578 & 289.698333333333 & 1.00712047924496 & 1.01298622530989 \tabularnewline
34 & 237.38 & 276.596020704033 & 275.635833333333 & 0.960187370699353 & 0.896917421734397 \tabularnewline
35 & 226.85 & 268.224164590853 & 267.268333333333 & 0.955831257520136 & 0.88799403709152 \tabularnewline
36 & 220.14 & 261.296495939599 & 260.301666666667 & 0.994829272932542 & 0.85010673591638 \tabularnewline
37 & 239.36 & 253.036232204104 & 252.03625 & 0.999982204104269 & 0.949721556726096 \tabularnewline
38 & 224.69 & 243.815078180321 & 242.777916666667 & 1.03716151365447 & 0.892335500171742 \tabularnewline
39 & 230.98 & 234.525161478073 & 233.468333333333 & 1.05682814473984 & 0.936142631792353 \tabularnewline
40 & 233.47 & 228.496099664623 & 227.510416666667 & 0.985682997956348 & 1.04110020506525 \tabularnewline
41 & 256.7 & 226.229301682034 & 225.24625 & 0.983051682033842 & 1.15928962361112 \tabularnewline
42 & 253.41 & 225.042730013216 & 224.00875 & 1.03398001321637 & 1.09407381083447 \tabularnewline
43 & 224.95 & 222.829110368479 & 221.839583333333 & 0.989527035145743 & 1.02475322191683 \tabularnewline
44 & 210.37 & 219.981651362085 & 218.985833333333 & 0.995818028752133 & 0.964690056260092 \tabularnewline
45 & 191.09 & 217.067120479245 & 216.06 & 1.00712047924496 & 0.878177208271354 \tabularnewline
46 & 198.85 & 213.666020704033 & 212.705833333333 & 0.960187370699353 & 0.973621611937199 \tabularnewline
47 & 211.04 & 208.841247924187 & 207.885416666667 & 0.955831257520136 & 1.06208561130187 \tabularnewline
48 & 206.25 & 201.762329272933 & 200.7675 & 0.994829272932542 & 1.03264724372992 \tabularnewline
49 & 201.19 & NA & 195.577916666667 & NA & NA \tabularnewline
50 & 194.37 & NA & 195.876666666667 & NA & NA \tabularnewline
51 & 191.08 & NA & 200.742916666667 & NA & NA \tabularnewline
52 & 192.87 & NA & NA & NA & NA \tabularnewline
53 & 181.61 & NA & NA & NA & NA \tabularnewline
54 & 157.67 & NA & NA & NA & NA \tabularnewline
55 & 196.14 & NA & NA & NA & NA \tabularnewline
56 & 246.35 & NA & NA & NA & NA \tabularnewline
57 & 271.9 & NA & NA & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102465&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]167.16[/C][C]NA[/C][C]NA[/C][C]0.999982204104269[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]179.84[/C][C]NA[/C][C]NA[/C][C]1.03716151365447[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]174.44[/C][C]NA[/C][C]NA[/C][C]1.05682814473984[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]180.35[/C][C]NA[/C][C]NA[/C][C]0.985682997956348[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]193.17[/C][C]NA[/C][C]NA[/C][C]0.983051682033842[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]195.16[/C][C]NA[/C][C]NA[/C][C]1.03398001321637[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]202.43[/C][C]193.914943701812[/C][C]192.925416666667[/C][C]0.989527035145743[/C][C]1.06037081029508[/C][/ROW]
[ROW][C]8[/C][C]189.91[/C][C]195.964984695419[/C][C]194.969166666667[/C][C]0.995818028752133[/C][C]0.978142014360496[/C][/ROW]
[ROW][C]9[/C][C]195.98[/C][C]197.842953812578[/C][C]196.835833333333[/C][C]1.00712047924496[/C][C]0.988612649212912[/C][/ROW]
[ROW][C]10[/C][C]212.09[/C][C]199.571854037366[/C][C]198.611666666667[/C][C]0.960187370699353[/C][C]1.11213996332746[/C][/ROW]
[ROW][C]11[/C][C]205.81[/C][C]200.42208125752[/C][C]199.46625[/C][C]0.955831257520136[/C][C]1.07948303406991[/C][/ROW]
[ROW][C]12[/C][C]204.31[/C][C]201.728995939599[/C][C]200.734166666667[/C][C]0.994829272932542[/C][C]1.02310396663975[/C][/ROW]
[ROW][C]13[/C][C]196.07[/C][C]204.394982204104[/C][C]203.395[/C][C]0.999982204104269[/C][C]0.964003487319606[/C][/ROW]
[ROW][C]14[/C][C]199.98[/C][C]208.840494846988[/C][C]207.803333333333[/C][C]1.03716151365447[/C][C]0.927871128448571[/C][/ROW]
[ROW][C]15[/C][C]199.1[/C][C]217.20932814474[/C][C]216.1525[/C][C]1.05682814473984[/C][C]0.871578736689774[/C][/ROW]
[ROW][C]16[/C][C]198.31[/C][C]227.705682997956[/C][C]226.72[/C][C]0.985682997956348[/C][C]0.887396100908084[/C][/ROW]
[ROW][C]17[/C][C]195.72[/C][C]237.663885015367[/C][C]236.680833333333[/C][C]0.983051682033842[/C][C]0.841193226043899[/C][/ROW]
[ROW][C]18[/C][C]223.04[/C][C]249.394396679883[/C][C]248.360416666667[/C][C]1.03398001321637[/C][C]0.868536816829029[/C][/ROW]
[ROW][C]19[/C][C]238.41[/C][C]263.426193701812[/C][C]262.436666666667[/C][C]0.989527035145743[/C][C]0.91806258970965[/C][/ROW]
[ROW][C]20[/C][C]259.73[/C][C]280.038318028752[/C][C]279.0425[/C][C]0.995818028752133[/C][C]0.9346989969479[/C][/ROW]
[ROW][C]21[/C][C]326.54[/C][C]299.451287145912[/C][C]298.444166666667[/C][C]1.00712047924496[/C][C]1.08640527725365[/C][/ROW]
[ROW][C]22[/C][C]335.15[/C][C]316.260187370699[/C][C]315.3[/C][C]0.960187370699353[/C][C]1.10702967716330[/C][/ROW]
[ROW][C]23[/C][C]321.81[/C][C]328.629164590853[/C][C]327.673333333333[/C][C]0.955831257520136[/C][C]1.02748906244151[/C][/ROW]
[ROW][C]24[/C][C]368.62[/C][C]339.441079272932[/C][C]338.44625[/C][C]0.994829272932542[/C][C]1.09481473118860[/C][/ROW]
[ROW][C]25[/C][C]369.59[/C][C]348.416232204104[/C][C]347.41625[/C][C]0.999982204104269[/C][C]1.06384366678920[/C][/ROW]
[ROW][C]26[/C][C]425[/C][C]355.094244846988[/C][C]354.057083333333[/C][C]1.03716151365447[/C][C]1.15736208221459[/C][/ROW]
[ROW][C]27[/C][C]439.72[/C][C]356.72307814474[/C][C]355.66625[/C][C]1.05682814473984[/C][C]1.16984734235277[/C][/ROW]
[ROW][C]28[/C][C]362.23[/C][C]351.286932997956[/C][C]350.30125[/C][C]0.985682997956348[/C][C]1.04907240486157[/C][/ROW]
[ROW][C]29[/C][C]328.76[/C][C]343.253885015367[/C][C]342.270833333333[/C][C]0.983051682033842[/C][C]0.97708586117988[/C][/ROW]
[ROW][C]30[/C][C]348.55[/C][C]333.161480013216[/C][C]332.1275[/C][C]1.03398001321637[/C][C]1.01495808317140[/C][/ROW]
[ROW][C]31[/C][C]328.18[/C][C]321.504110368479[/C][C]320.514583333333[/C][C]0.989527035145743[/C][C]1.03475289920842[/C][/ROW]
[ROW][C]32[/C][C]329.34[/C][C]307.737901362085[/C][C]306.742083333333[/C][C]0.995818028752133[/C][C]1.07817965762691[/C][/ROW]
[ROW][C]33[/C][C]295.55[/C][C]290.705453812578[/C][C]289.698333333333[/C][C]1.00712047924496[/C][C]1.01298622530989[/C][/ROW]
[ROW][C]34[/C][C]237.38[/C][C]276.596020704033[/C][C]275.635833333333[/C][C]0.960187370699353[/C][C]0.896917421734397[/C][/ROW]
[ROW][C]35[/C][C]226.85[/C][C]268.224164590853[/C][C]267.268333333333[/C][C]0.955831257520136[/C][C]0.88799403709152[/C][/ROW]
[ROW][C]36[/C][C]220.14[/C][C]261.296495939599[/C][C]260.301666666667[/C][C]0.994829272932542[/C][C]0.85010673591638[/C][/ROW]
[ROW][C]37[/C][C]239.36[/C][C]253.036232204104[/C][C]252.03625[/C][C]0.999982204104269[/C][C]0.949721556726096[/C][/ROW]
[ROW][C]38[/C][C]224.69[/C][C]243.815078180321[/C][C]242.777916666667[/C][C]1.03716151365447[/C][C]0.892335500171742[/C][/ROW]
[ROW][C]39[/C][C]230.98[/C][C]234.525161478073[/C][C]233.468333333333[/C][C]1.05682814473984[/C][C]0.936142631792353[/C][/ROW]
[ROW][C]40[/C][C]233.47[/C][C]228.496099664623[/C][C]227.510416666667[/C][C]0.985682997956348[/C][C]1.04110020506525[/C][/ROW]
[ROW][C]41[/C][C]256.7[/C][C]226.229301682034[/C][C]225.24625[/C][C]0.983051682033842[/C][C]1.15928962361112[/C][/ROW]
[ROW][C]42[/C][C]253.41[/C][C]225.042730013216[/C][C]224.00875[/C][C]1.03398001321637[/C][C]1.09407381083447[/C][/ROW]
[ROW][C]43[/C][C]224.95[/C][C]222.829110368479[/C][C]221.839583333333[/C][C]0.989527035145743[/C][C]1.02475322191683[/C][/ROW]
[ROW][C]44[/C][C]210.37[/C][C]219.981651362085[/C][C]218.985833333333[/C][C]0.995818028752133[/C][C]0.964690056260092[/C][/ROW]
[ROW][C]45[/C][C]191.09[/C][C]217.067120479245[/C][C]216.06[/C][C]1.00712047924496[/C][C]0.878177208271354[/C][/ROW]
[ROW][C]46[/C][C]198.85[/C][C]213.666020704033[/C][C]212.705833333333[/C][C]0.960187370699353[/C][C]0.973621611937199[/C][/ROW]
[ROW][C]47[/C][C]211.04[/C][C]208.841247924187[/C][C]207.885416666667[/C][C]0.955831257520136[/C][C]1.06208561130187[/C][/ROW]
[ROW][C]48[/C][C]206.25[/C][C]201.762329272933[/C][C]200.7675[/C][C]0.994829272932542[/C][C]1.03264724372992[/C][/ROW]
[ROW][C]49[/C][C]201.19[/C][C]NA[/C][C]195.577916666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]50[/C][C]194.37[/C][C]NA[/C][C]195.876666666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]51[/C][C]191.08[/C][C]NA[/C][C]200.742916666667[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]52[/C][C]192.87[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]53[/C][C]181.61[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]54[/C][C]157.67[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]55[/C][C]196.14[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]246.35[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]271.9[/C][C]NA[/C][C]NA[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102465&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102465&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	167.16	NA	NA	0.999982204104269	NA
2	179.84	NA	NA	1.03716151365447	NA
3	174.44	NA	NA	1.05682814473984	NA
4	180.35	NA	NA	0.985682997956348	NA
5	193.17	NA	NA	0.983051682033842	NA
6	195.16	NA	NA	1.03398001321637	NA
7	202.43	193.914943701812	192.925416666667	0.989527035145743	1.06037081029508
8	189.91	195.964984695419	194.969166666667	0.995818028752133	0.978142014360496
9	195.98	197.842953812578	196.835833333333	1.00712047924496	0.988612649212912
10	212.09	199.571854037366	198.611666666667	0.960187370699353	1.11213996332746
11	205.81	200.42208125752	199.46625	0.955831257520136	1.07948303406991
12	204.31	201.728995939599	200.734166666667	0.994829272932542	1.02310396663975
13	196.07	204.394982204104	203.395	0.999982204104269	0.964003487319606
14	199.98	208.840494846988	207.803333333333	1.03716151365447	0.927871128448571
15	199.1	217.20932814474	216.1525	1.05682814473984	0.871578736689774
16	198.31	227.705682997956	226.72	0.985682997956348	0.887396100908084
17	195.72	237.663885015367	236.680833333333	0.983051682033842	0.841193226043899
18	223.04	249.394396679883	248.360416666667	1.03398001321637	0.868536816829029
19	238.41	263.426193701812	262.436666666667	0.989527035145743	0.91806258970965
20	259.73	280.038318028752	279.0425	0.995818028752133	0.9346989969479
21	326.54	299.451287145912	298.444166666667	1.00712047924496	1.08640527725365
22	335.15	316.260187370699	315.3	0.960187370699353	1.10702967716330
23	321.81	328.629164590853	327.673333333333	0.955831257520136	1.02748906244151
24	368.62	339.441079272932	338.44625	0.994829272932542	1.09481473118860
25	369.59	348.416232204104	347.41625	0.999982204104269	1.06384366678920
26	425	355.094244846988	354.057083333333	1.03716151365447	1.15736208221459
27	439.72	356.72307814474	355.66625	1.05682814473984	1.16984734235277
28	362.23	351.286932997956	350.30125	0.985682997956348	1.04907240486157
29	328.76	343.253885015367	342.270833333333	0.983051682033842	0.97708586117988
30	348.55	333.161480013216	332.1275	1.03398001321637	1.01495808317140
31	328.18	321.504110368479	320.514583333333	0.989527035145743	1.03475289920842
32	329.34	307.737901362085	306.742083333333	0.995818028752133	1.07817965762691
33	295.55	290.705453812578	289.698333333333	1.00712047924496	1.01298622530989
34	237.38	276.596020704033	275.635833333333	0.960187370699353	0.896917421734397
35	226.85	268.224164590853	267.268333333333	0.955831257520136	0.88799403709152
36	220.14	261.296495939599	260.301666666667	0.994829272932542	0.85010673591638
37	239.36	253.036232204104	252.03625	0.999982204104269	0.949721556726096
38	224.69	243.815078180321	242.777916666667	1.03716151365447	0.892335500171742
39	230.98	234.525161478073	233.468333333333	1.05682814473984	0.936142631792353
40	233.47	228.496099664623	227.510416666667	0.985682997956348	1.04110020506525
41	256.7	226.229301682034	225.24625	0.983051682033842	1.15928962361112
42	253.41	225.042730013216	224.00875	1.03398001321637	1.09407381083447
43	224.95	222.829110368479	221.839583333333	0.989527035145743	1.02475322191683
44	210.37	219.981651362085	218.985833333333	0.995818028752133	0.964690056260092
45	191.09	217.067120479245	216.06	1.00712047924496	0.878177208271354
46	198.85	213.666020704033	212.705833333333	0.960187370699353	0.973621611937199
47	211.04	208.841247924187	207.885416666667	0.955831257520136	1.06208561130187
48	206.25	201.762329272933	200.7675	0.994829272932542	1.03264724372992
49	201.19	NA	195.577916666667	NA	NA
50	194.37	NA	195.876666666667	NA	NA
51	191.08	NA	200.742916666667	NA	NA
52	192.87	NA	NA	NA	NA
53	181.61	NA	NA	NA	NA
54	157.67	NA	NA	NA	NA
55	196.14	NA	NA	NA	NA
56	246.35	NA	NA	NA	NA
57	271.9	NA	NA	NA	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 = 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
a<-table.element(a,m$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