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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 12:43:18 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/12/t1386870258mdceuakyu9646xg.htm/, Retrieved Tue, 07 Dec 2021 12:11:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232262, Retrieved Tue, 07 Dec 2021 12:11:06 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact41
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 17:43:18] [4b42de28d069c82084b3ad7a06d83fce] [Current]
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Dataseries X:
9.27
9.30
9.35
9.33
9.37
9.42
9.45
9.38
9.40
9.43
9.45
9.49
9.47
9.48
9.52
9.53
9.53
9.54
9.57
9.61
9.61
9.63
9.64
9.60
9.64
9.66
9.67
9.70
9.72
9.73
9.77
9.72
9.68
9.62
9.79
9.77
9.79
9.77
9.78
9.81
9.74
9.70
9.78
9.85
9.83
9.90
9.93
9.85
9.95
9.97
10.02
9.97
9.95
9.95
9.98
10.00
10.04
10.05
10.06
10.09
10.14
10.13
10.12
10.10
10.12
10.06
10.21
10.18
10.26
10.39
10.41
10.46




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 4 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232262&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232262&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232262&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
19.27NANA0.0238333NA
29.3NANA0.0148333NA
39.35NANA0.021NA
49.33NANA0.00583333NA
59.37NANA-0.0201667NA
69.42NANA-0.05225NA
79.459.407089.3950.01208330.0429167
89.389.410759.41083-8.33333e-05-0.03075
99.49.4129.42542-0.0134167-0.012
109.439.428589.44083-0.012250.00141667
119.459.478929.455830.0230833-0.0289167
129.499.4659.4675-0.00250.025
139.479.501339.47750.0238333-0.0313333
149.489.506929.492080.0148333-0.0269167
159.529.531429.510420.021-0.0114167
169.539.533339.52750.00583333-0.00333333
179.539.523589.54375-0.02016670.00641667
189.549.5049.55625-0.052250.036
199.579.589.567920.0120833-0.01
209.619.582429.5825-8.33333e-050.0275833
219.619.582839.59625-0.01341670.0271667
229.639.597339.60958-0.012250.0326667
239.649.647679.624580.0230833-0.00766667
249.69.637929.64042-0.0025-0.0379167
259.649.68059.656670.0238333-0.0405
269.669.684429.669580.0148333-0.0244167
279.679.698089.677080.021-0.0280833
289.79.685429.679580.005833330.0145833
299.729.665259.68542-0.02016670.05475
309.739.64659.69875-0.052250.0835
319.779.724179.712080.01208330.0458333
329.729.722839.72292-8.33333e-05-0.00283333
339.689.718679.73208-0.0134167-0.0386667
349.629.7299.74125-0.01225-0.109
359.799.769759.746670.02308330.02025
369.779.743759.74625-0.00250.02625
379.799.769259.745420.02383330.02075
389.779.766089.751250.01483330.00391667
399.789.783929.762920.021-0.00391667
409.819.786679.780830.005833330.0233333
419.749.778179.79833-0.0201667-0.0381667
429.79.755259.8075-0.05225-0.05525
439.789.829589.81750.0120833-0.0495833
449.859.832429.8325-8.33333e-050.0175833
459.839.837429.85083-0.0134167-0.00741667
469.99.855259.8675-0.012250.04475
479.939.9069.882920.02308330.024
489.859.899589.90208-0.0025-0.0495833
499.959.944679.920830.02383330.00533333
509.979.950259.935420.01483330.01975
5110.029.971429.950420.0210.0485833
529.979.971259.965420.00583333-0.00125
539.959.956929.97708-0.0201667-0.00691667
549.959.940259.9925-0.052250.00975
559.9810.022510.01040.0120833-0.0425
561010.024910.025-8.33333e-05-0.0249167
5710.0410.022410.0358-0.01341670.0175833
5810.0510.033210.0454-0.012250.0168333
5910.0610.08110.05790.0230833-0.021
6010.0910.067110.0696-0.00250.0229167
6110.1410.107610.08380.02383330.0324167
6210.1310.115710.10080.01483330.0143333
6310.1210.138510.11750.021-0.0185
6410.110.146710.14080.00583333-0.0466667
6510.1210.149410.1696-0.0201667-0.0294167
6610.0610.147310.1996-0.05225-0.0873333
6710.21NANA0.0120833NA
6810.18NANA-8.33333e-05NA
6910.26NANA-0.0134167NA
7010.39NANA-0.01225NA
7110.41NANA0.0230833NA
7210.46NANA-0.0025NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 9.27 & NA & NA & 0.0238333 & NA \tabularnewline
2 & 9.3 & NA & NA & 0.0148333 & NA \tabularnewline
3 & 9.35 & NA & NA & 0.021 & NA \tabularnewline
4 & 9.33 & NA & NA & 0.00583333 & NA \tabularnewline
5 & 9.37 & NA & NA & -0.0201667 & NA \tabularnewline
6 & 9.42 & NA & NA & -0.05225 & NA \tabularnewline
7 & 9.45 & 9.40708 & 9.395 & 0.0120833 & 0.0429167 \tabularnewline
8 & 9.38 & 9.41075 & 9.41083 & -8.33333e-05 & -0.03075 \tabularnewline
9 & 9.4 & 9.412 & 9.42542 & -0.0134167 & -0.012 \tabularnewline
10 & 9.43 & 9.42858 & 9.44083 & -0.01225 & 0.00141667 \tabularnewline
11 & 9.45 & 9.47892 & 9.45583 & 0.0230833 & -0.0289167 \tabularnewline
12 & 9.49 & 9.465 & 9.4675 & -0.0025 & 0.025 \tabularnewline
13 & 9.47 & 9.50133 & 9.4775 & 0.0238333 & -0.0313333 \tabularnewline
14 & 9.48 & 9.50692 & 9.49208 & 0.0148333 & -0.0269167 \tabularnewline
15 & 9.52 & 9.53142 & 9.51042 & 0.021 & -0.0114167 \tabularnewline
16 & 9.53 & 9.53333 & 9.5275 & 0.00583333 & -0.00333333 \tabularnewline
17 & 9.53 & 9.52358 & 9.54375 & -0.0201667 & 0.00641667 \tabularnewline
18 & 9.54 & 9.504 & 9.55625 & -0.05225 & 0.036 \tabularnewline
19 & 9.57 & 9.58 & 9.56792 & 0.0120833 & -0.01 \tabularnewline
20 & 9.61 & 9.58242 & 9.5825 & -8.33333e-05 & 0.0275833 \tabularnewline
21 & 9.61 & 9.58283 & 9.59625 & -0.0134167 & 0.0271667 \tabularnewline
22 & 9.63 & 9.59733 & 9.60958 & -0.01225 & 0.0326667 \tabularnewline
23 & 9.64 & 9.64767 & 9.62458 & 0.0230833 & -0.00766667 \tabularnewline
24 & 9.6 & 9.63792 & 9.64042 & -0.0025 & -0.0379167 \tabularnewline
25 & 9.64 & 9.6805 & 9.65667 & 0.0238333 & -0.0405 \tabularnewline
26 & 9.66 & 9.68442 & 9.66958 & 0.0148333 & -0.0244167 \tabularnewline
27 & 9.67 & 9.69808 & 9.67708 & 0.021 & -0.0280833 \tabularnewline
28 & 9.7 & 9.68542 & 9.67958 & 0.00583333 & 0.0145833 \tabularnewline
29 & 9.72 & 9.66525 & 9.68542 & -0.0201667 & 0.05475 \tabularnewline
30 & 9.73 & 9.6465 & 9.69875 & -0.05225 & 0.0835 \tabularnewline
31 & 9.77 & 9.72417 & 9.71208 & 0.0120833 & 0.0458333 \tabularnewline
32 & 9.72 & 9.72283 & 9.72292 & -8.33333e-05 & -0.00283333 \tabularnewline
33 & 9.68 & 9.71867 & 9.73208 & -0.0134167 & -0.0386667 \tabularnewline
34 & 9.62 & 9.729 & 9.74125 & -0.01225 & -0.109 \tabularnewline
35 & 9.79 & 9.76975 & 9.74667 & 0.0230833 & 0.02025 \tabularnewline
36 & 9.77 & 9.74375 & 9.74625 & -0.0025 & 0.02625 \tabularnewline
37 & 9.79 & 9.76925 & 9.74542 & 0.0238333 & 0.02075 \tabularnewline
38 & 9.77 & 9.76608 & 9.75125 & 0.0148333 & 0.00391667 \tabularnewline
39 & 9.78 & 9.78392 & 9.76292 & 0.021 & -0.00391667 \tabularnewline
40 & 9.81 & 9.78667 & 9.78083 & 0.00583333 & 0.0233333 \tabularnewline
41 & 9.74 & 9.77817 & 9.79833 & -0.0201667 & -0.0381667 \tabularnewline
42 & 9.7 & 9.75525 & 9.8075 & -0.05225 & -0.05525 \tabularnewline
43 & 9.78 & 9.82958 & 9.8175 & 0.0120833 & -0.0495833 \tabularnewline
44 & 9.85 & 9.83242 & 9.8325 & -8.33333e-05 & 0.0175833 \tabularnewline
45 & 9.83 & 9.83742 & 9.85083 & -0.0134167 & -0.00741667 \tabularnewline
46 & 9.9 & 9.85525 & 9.8675 & -0.01225 & 0.04475 \tabularnewline
47 & 9.93 & 9.906 & 9.88292 & 0.0230833 & 0.024 \tabularnewline
48 & 9.85 & 9.89958 & 9.90208 & -0.0025 & -0.0495833 \tabularnewline
49 & 9.95 & 9.94467 & 9.92083 & 0.0238333 & 0.00533333 \tabularnewline
50 & 9.97 & 9.95025 & 9.93542 & 0.0148333 & 0.01975 \tabularnewline
51 & 10.02 & 9.97142 & 9.95042 & 0.021 & 0.0485833 \tabularnewline
52 & 9.97 & 9.97125 & 9.96542 & 0.00583333 & -0.00125 \tabularnewline
53 & 9.95 & 9.95692 & 9.97708 & -0.0201667 & -0.00691667 \tabularnewline
54 & 9.95 & 9.94025 & 9.9925 & -0.05225 & 0.00975 \tabularnewline
55 & 9.98 & 10.0225 & 10.0104 & 0.0120833 & -0.0425 \tabularnewline
56 & 10 & 10.0249 & 10.025 & -8.33333e-05 & -0.0249167 \tabularnewline
57 & 10.04 & 10.0224 & 10.0358 & -0.0134167 & 0.0175833 \tabularnewline
58 & 10.05 & 10.0332 & 10.0454 & -0.01225 & 0.0168333 \tabularnewline
59 & 10.06 & 10.081 & 10.0579 & 0.0230833 & -0.021 \tabularnewline
60 & 10.09 & 10.0671 & 10.0696 & -0.0025 & 0.0229167 \tabularnewline
61 & 10.14 & 10.1076 & 10.0838 & 0.0238333 & 0.0324167 \tabularnewline
62 & 10.13 & 10.1157 & 10.1008 & 0.0148333 & 0.0143333 \tabularnewline
63 & 10.12 & 10.1385 & 10.1175 & 0.021 & -0.0185 \tabularnewline
64 & 10.1 & 10.1467 & 10.1408 & 0.00583333 & -0.0466667 \tabularnewline
65 & 10.12 & 10.1494 & 10.1696 & -0.0201667 & -0.0294167 \tabularnewline
66 & 10.06 & 10.1473 & 10.1996 & -0.05225 & -0.0873333 \tabularnewline
67 & 10.21 & NA & NA & 0.0120833 & NA \tabularnewline
68 & 10.18 & NA & NA & -8.33333e-05 & NA \tabularnewline
69 & 10.26 & NA & NA & -0.0134167 & NA \tabularnewline
70 & 10.39 & NA & NA & -0.01225 & NA \tabularnewline
71 & 10.41 & NA & NA & 0.0230833 & NA \tabularnewline
72 & 10.46 & NA & NA & -0.0025 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232262&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]9.27[/C][C]NA[/C][C]NA[/C][C]0.0238333[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]9.3[/C][C]NA[/C][C]NA[/C][C]0.0148333[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]9.35[/C][C]NA[/C][C]NA[/C][C]0.021[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]9.33[/C][C]NA[/C][C]NA[/C][C]0.00583333[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]9.37[/C][C]NA[/C][C]NA[/C][C]-0.0201667[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]9.42[/C][C]NA[/C][C]NA[/C][C]-0.05225[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]9.45[/C][C]9.40708[/C][C]9.395[/C][C]0.0120833[/C][C]0.0429167[/C][/ROW]
[ROW][C]8[/C][C]9.38[/C][C]9.41075[/C][C]9.41083[/C][C]-8.33333e-05[/C][C]-0.03075[/C][/ROW]
[ROW][C]9[/C][C]9.4[/C][C]9.412[/C][C]9.42542[/C][C]-0.0134167[/C][C]-0.012[/C][/ROW]
[ROW][C]10[/C][C]9.43[/C][C]9.42858[/C][C]9.44083[/C][C]-0.01225[/C][C]0.00141667[/C][/ROW]
[ROW][C]11[/C][C]9.45[/C][C]9.47892[/C][C]9.45583[/C][C]0.0230833[/C][C]-0.0289167[/C][/ROW]
[ROW][C]12[/C][C]9.49[/C][C]9.465[/C][C]9.4675[/C][C]-0.0025[/C][C]0.025[/C][/ROW]
[ROW][C]13[/C][C]9.47[/C][C]9.50133[/C][C]9.4775[/C][C]0.0238333[/C][C]-0.0313333[/C][/ROW]
[ROW][C]14[/C][C]9.48[/C][C]9.50692[/C][C]9.49208[/C][C]0.0148333[/C][C]-0.0269167[/C][/ROW]
[ROW][C]15[/C][C]9.52[/C][C]9.53142[/C][C]9.51042[/C][C]0.021[/C][C]-0.0114167[/C][/ROW]
[ROW][C]16[/C][C]9.53[/C][C]9.53333[/C][C]9.5275[/C][C]0.00583333[/C][C]-0.00333333[/C][/ROW]
[ROW][C]17[/C][C]9.53[/C][C]9.52358[/C][C]9.54375[/C][C]-0.0201667[/C][C]0.00641667[/C][/ROW]
[ROW][C]18[/C][C]9.54[/C][C]9.504[/C][C]9.55625[/C][C]-0.05225[/C][C]0.036[/C][/ROW]
[ROW][C]19[/C][C]9.57[/C][C]9.58[/C][C]9.56792[/C][C]0.0120833[/C][C]-0.01[/C][/ROW]
[ROW][C]20[/C][C]9.61[/C][C]9.58242[/C][C]9.5825[/C][C]-8.33333e-05[/C][C]0.0275833[/C][/ROW]
[ROW][C]21[/C][C]9.61[/C][C]9.58283[/C][C]9.59625[/C][C]-0.0134167[/C][C]0.0271667[/C][/ROW]
[ROW][C]22[/C][C]9.63[/C][C]9.59733[/C][C]9.60958[/C][C]-0.01225[/C][C]0.0326667[/C][/ROW]
[ROW][C]23[/C][C]9.64[/C][C]9.64767[/C][C]9.62458[/C][C]0.0230833[/C][C]-0.00766667[/C][/ROW]
[ROW][C]24[/C][C]9.6[/C][C]9.63792[/C][C]9.64042[/C][C]-0.0025[/C][C]-0.0379167[/C][/ROW]
[ROW][C]25[/C][C]9.64[/C][C]9.6805[/C][C]9.65667[/C][C]0.0238333[/C][C]-0.0405[/C][/ROW]
[ROW][C]26[/C][C]9.66[/C][C]9.68442[/C][C]9.66958[/C][C]0.0148333[/C][C]-0.0244167[/C][/ROW]
[ROW][C]27[/C][C]9.67[/C][C]9.69808[/C][C]9.67708[/C][C]0.021[/C][C]-0.0280833[/C][/ROW]
[ROW][C]28[/C][C]9.7[/C][C]9.68542[/C][C]9.67958[/C][C]0.00583333[/C][C]0.0145833[/C][/ROW]
[ROW][C]29[/C][C]9.72[/C][C]9.66525[/C][C]9.68542[/C][C]-0.0201667[/C][C]0.05475[/C][/ROW]
[ROW][C]30[/C][C]9.73[/C][C]9.6465[/C][C]9.69875[/C][C]-0.05225[/C][C]0.0835[/C][/ROW]
[ROW][C]31[/C][C]9.77[/C][C]9.72417[/C][C]9.71208[/C][C]0.0120833[/C][C]0.0458333[/C][/ROW]
[ROW][C]32[/C][C]9.72[/C][C]9.72283[/C][C]9.72292[/C][C]-8.33333e-05[/C][C]-0.00283333[/C][/ROW]
[ROW][C]33[/C][C]9.68[/C][C]9.71867[/C][C]9.73208[/C][C]-0.0134167[/C][C]-0.0386667[/C][/ROW]
[ROW][C]34[/C][C]9.62[/C][C]9.729[/C][C]9.74125[/C][C]-0.01225[/C][C]-0.109[/C][/ROW]
[ROW][C]35[/C][C]9.79[/C][C]9.76975[/C][C]9.74667[/C][C]0.0230833[/C][C]0.02025[/C][/ROW]
[ROW][C]36[/C][C]9.77[/C][C]9.74375[/C][C]9.74625[/C][C]-0.0025[/C][C]0.02625[/C][/ROW]
[ROW][C]37[/C][C]9.79[/C][C]9.76925[/C][C]9.74542[/C][C]0.0238333[/C][C]0.02075[/C][/ROW]
[ROW][C]38[/C][C]9.77[/C][C]9.76608[/C][C]9.75125[/C][C]0.0148333[/C][C]0.00391667[/C][/ROW]
[ROW][C]39[/C][C]9.78[/C][C]9.78392[/C][C]9.76292[/C][C]0.021[/C][C]-0.00391667[/C][/ROW]
[ROW][C]40[/C][C]9.81[/C][C]9.78667[/C][C]9.78083[/C][C]0.00583333[/C][C]0.0233333[/C][/ROW]
[ROW][C]41[/C][C]9.74[/C][C]9.77817[/C][C]9.79833[/C][C]-0.0201667[/C][C]-0.0381667[/C][/ROW]
[ROW][C]42[/C][C]9.7[/C][C]9.75525[/C][C]9.8075[/C][C]-0.05225[/C][C]-0.05525[/C][/ROW]
[ROW][C]43[/C][C]9.78[/C][C]9.82958[/C][C]9.8175[/C][C]0.0120833[/C][C]-0.0495833[/C][/ROW]
[ROW][C]44[/C][C]9.85[/C][C]9.83242[/C][C]9.8325[/C][C]-8.33333e-05[/C][C]0.0175833[/C][/ROW]
[ROW][C]45[/C][C]9.83[/C][C]9.83742[/C][C]9.85083[/C][C]-0.0134167[/C][C]-0.00741667[/C][/ROW]
[ROW][C]46[/C][C]9.9[/C][C]9.85525[/C][C]9.8675[/C][C]-0.01225[/C][C]0.04475[/C][/ROW]
[ROW][C]47[/C][C]9.93[/C][C]9.906[/C][C]9.88292[/C][C]0.0230833[/C][C]0.024[/C][/ROW]
[ROW][C]48[/C][C]9.85[/C][C]9.89958[/C][C]9.90208[/C][C]-0.0025[/C][C]-0.0495833[/C][/ROW]
[ROW][C]49[/C][C]9.95[/C][C]9.94467[/C][C]9.92083[/C][C]0.0238333[/C][C]0.00533333[/C][/ROW]
[ROW][C]50[/C][C]9.97[/C][C]9.95025[/C][C]9.93542[/C][C]0.0148333[/C][C]0.01975[/C][/ROW]
[ROW][C]51[/C][C]10.02[/C][C]9.97142[/C][C]9.95042[/C][C]0.021[/C][C]0.0485833[/C][/ROW]
[ROW][C]52[/C][C]9.97[/C][C]9.97125[/C][C]9.96542[/C][C]0.00583333[/C][C]-0.00125[/C][/ROW]
[ROW][C]53[/C][C]9.95[/C][C]9.95692[/C][C]9.97708[/C][C]-0.0201667[/C][C]-0.00691667[/C][/ROW]
[ROW][C]54[/C][C]9.95[/C][C]9.94025[/C][C]9.9925[/C][C]-0.05225[/C][C]0.00975[/C][/ROW]
[ROW][C]55[/C][C]9.98[/C][C]10.0225[/C][C]10.0104[/C][C]0.0120833[/C][C]-0.0425[/C][/ROW]
[ROW][C]56[/C][C]10[/C][C]10.0249[/C][C]10.025[/C][C]-8.33333e-05[/C][C]-0.0249167[/C][/ROW]
[ROW][C]57[/C][C]10.04[/C][C]10.0224[/C][C]10.0358[/C][C]-0.0134167[/C][C]0.0175833[/C][/ROW]
[ROW][C]58[/C][C]10.05[/C][C]10.0332[/C][C]10.0454[/C][C]-0.01225[/C][C]0.0168333[/C][/ROW]
[ROW][C]59[/C][C]10.06[/C][C]10.081[/C][C]10.0579[/C][C]0.0230833[/C][C]-0.021[/C][/ROW]
[ROW][C]60[/C][C]10.09[/C][C]10.0671[/C][C]10.0696[/C][C]-0.0025[/C][C]0.0229167[/C][/ROW]
[ROW][C]61[/C][C]10.14[/C][C]10.1076[/C][C]10.0838[/C][C]0.0238333[/C][C]0.0324167[/C][/ROW]
[ROW][C]62[/C][C]10.13[/C][C]10.1157[/C][C]10.1008[/C][C]0.0148333[/C][C]0.0143333[/C][/ROW]
[ROW][C]63[/C][C]10.12[/C][C]10.1385[/C][C]10.1175[/C][C]0.021[/C][C]-0.0185[/C][/ROW]
[ROW][C]64[/C][C]10.1[/C][C]10.1467[/C][C]10.1408[/C][C]0.00583333[/C][C]-0.0466667[/C][/ROW]
[ROW][C]65[/C][C]10.12[/C][C]10.1494[/C][C]10.1696[/C][C]-0.0201667[/C][C]-0.0294167[/C][/ROW]
[ROW][C]66[/C][C]10.06[/C][C]10.1473[/C][C]10.1996[/C][C]-0.05225[/C][C]-0.0873333[/C][/ROW]
[ROW][C]67[/C][C]10.21[/C][C]NA[/C][C]NA[/C][C]0.0120833[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]10.18[/C][C]NA[/C][C]NA[/C][C]-8.33333e-05[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]10.26[/C][C]NA[/C][C]NA[/C][C]-0.0134167[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]10.39[/C][C]NA[/C][C]NA[/C][C]-0.01225[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]10.41[/C][C]NA[/C][C]NA[/C][C]0.0230833[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]10.46[/C][C]NA[/C][C]NA[/C][C]-0.0025[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232262&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232262&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
tObservationsFitTrendSeasonalRandom
19.27NANA0.0238333NA
29.3NANA0.0148333NA
39.35NANA0.021NA
49.33NANA0.00583333NA
59.37NANA-0.0201667NA
69.42NANA-0.05225NA
79.459.407089.3950.01208330.0429167
89.389.410759.41083-8.33333e-05-0.03075
99.49.4129.42542-0.0134167-0.012
109.439.428589.44083-0.012250.00141667
119.459.478929.455830.0230833-0.0289167
129.499.4659.4675-0.00250.025
139.479.501339.47750.0238333-0.0313333
149.489.506929.492080.0148333-0.0269167
159.529.531429.510420.021-0.0114167
169.539.533339.52750.00583333-0.00333333
179.539.523589.54375-0.02016670.00641667
189.549.5049.55625-0.052250.036
199.579.589.567920.0120833-0.01
209.619.582429.5825-8.33333e-050.0275833
219.619.582839.59625-0.01341670.0271667
229.639.597339.60958-0.012250.0326667
239.649.647679.624580.0230833-0.00766667
249.69.637929.64042-0.0025-0.0379167
259.649.68059.656670.0238333-0.0405
269.669.684429.669580.0148333-0.0244167
279.679.698089.677080.021-0.0280833
289.79.685429.679580.005833330.0145833
299.729.665259.68542-0.02016670.05475
309.739.64659.69875-0.052250.0835
319.779.724179.712080.01208330.0458333
329.729.722839.72292-8.33333e-05-0.00283333
339.689.718679.73208-0.0134167-0.0386667
349.629.7299.74125-0.01225-0.109
359.799.769759.746670.02308330.02025
369.779.743759.74625-0.00250.02625
379.799.769259.745420.02383330.02075
389.779.766089.751250.01483330.00391667
399.789.783929.762920.021-0.00391667
409.819.786679.780830.005833330.0233333
419.749.778179.79833-0.0201667-0.0381667
429.79.755259.8075-0.05225-0.05525
439.789.829589.81750.0120833-0.0495833
449.859.832429.8325-8.33333e-050.0175833
459.839.837429.85083-0.0134167-0.00741667
469.99.855259.8675-0.012250.04475
479.939.9069.882920.02308330.024
489.859.899589.90208-0.0025-0.0495833
499.959.944679.920830.02383330.00533333
509.979.950259.935420.01483330.01975
5110.029.971429.950420.0210.0485833
529.979.971259.965420.00583333-0.00125
539.959.956929.97708-0.0201667-0.00691667
549.959.940259.9925-0.052250.00975
559.9810.022510.01040.0120833-0.0425
561010.024910.025-8.33333e-05-0.0249167
5710.0410.022410.0358-0.01341670.0175833
5810.0510.033210.0454-0.012250.0168333
5910.0610.08110.05790.0230833-0.021
6010.0910.067110.0696-0.00250.0229167
6110.1410.107610.08380.02383330.0324167
6210.1310.115710.10080.01483330.0143333
6310.1210.138510.11750.021-0.0185
6410.110.146710.14080.00583333-0.0466667
6510.1210.149410.1696-0.0201667-0.0294167
6610.0610.147310.1996-0.05225-0.0873333
6710.21NANA0.0120833NA
6810.18NANA-8.33333e-05NA
6910.26NANA-0.0134167NA
7010.39NANA-0.01225NA
7110.41NANA0.0230833NA
7210.46NANA-0.0025NA



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- '12'
par1 <- 'additive'
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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')