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Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSun, 22 Dec 2013 13:52:07 -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/22/t1387738681yk4zc4gifzkjaww.htm/, Retrieved Fri, 29 Mar 2024 10:42:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232560, Retrieved Fri, 29 Mar 2024 10:42:10 +0000
QR Codes:

Original text written by user:
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User-defined keywords
Estimated Impact95
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-22 18:52:07] [2bef26084a4a59f589de449f00add791] [Current]
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Dataseries X:
1.49
1.55
1.57
1.6
1.61
1.68
1.72
1.72
1.73
1.74
1.74
1.75
1.75
1.75
1.75
1.76
1.76
1.77
1.78
1.78
1.78
1.78
1.78
1.79
1.79
1.79
1.79
1.79
1.79
1.8
1.8
1.8
1.8
1.8
1.81
1.81
1.82
1.82
1.82
1.82
1.83
1.83
1.84
1.84
1.84
1.85
1.85
1.85
1.86
1.86
1.86
1.86
1.87
1.87
1.87
1.87
1.88
1.9
1.9
1.91
1.91
1.91
1.92
1.92
1.92
1.92
1.92
1.92
1.92
1.92
1.93
1.93
1.93
1.94
1.95
1.95
1.95
1.95
1.98
1.98
2.01
2.02
2.11
2.14




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=232560&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=232560&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232560&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
11.49NANA0.00110532NA
21.55NANA-0.00083912NA
31.57NANA-0.00125579NA
41.6NANA-0.00347801NA
51.61NANA-0.00465856NA
61.68NANA-0.00660301NA
71.721.677491.669170.008327550.0425058
81.721.69091.688330.002563660.029103
91.731.704721.704170.0005497690.0252836
101.741.720481.718330.002146990.0195197
111.741.731941.731250.0006886570.00806134
121.751.74271.741250.001452550.00729745
131.751.748611.74750.001105320.00139468
141.751.751661.7525-0.00083912-0.00166088
151.751.755831.75708-0.00125579-0.00582755
161.761.757361.76083-0.003478010.00264468
171.761.759511.76417-0.004658560.000491898
181.771.76091.7675-0.006603010.00910301
191.781.779161.770830.008327550.00083912
201.781.776731.774170.002563660.00326968
211.781.778051.77750.0005497690.00195023
221.781.782561.780420.00214699-0.00256366
231.781.783611.782920.000688657-0.00360532
241.791.786871.785420.001452550.00313079
251.791.788611.78750.001105320.00139468
261.791.788331.78917-0.000839120.00167245
271.791.789581.79083-0.001255790.000422454
281.791.789021.7925-0.003478010.000978009
291.791.789921.79458-0.004658567.52315e-05
301.81.790061.79667-0.006603010.00993634
311.81.807081.798750.00832755-0.00707755
321.81.803811.801250.00256366-0.00381366
331.81.80431.803750.000549769-0.00429977
341.81.80841.806250.00214699-0.00839699
351.811.809861.809170.0006886570.000144676
361.811.813541.812080.00145255-0.00353588
371.821.816111.8150.001105320.00389468
381.821.817491.81833-0.000839120.00250579
391.821.820411.82167-0.00125579-0.00041088
401.821.821941.82542-0.00347801-0.00193866
411.831.824511.82917-0.004658560.0054919
421.831.82591.8325-0.006603010.00410301
431.841.844161.835830.00832755-0.00416088
441.841.841731.839170.00256366-0.00173032
451.841.843051.84250.000549769-0.00304977
461.851.847981.845830.002146990.00201968
471.851.849861.849170.0006886570.000144676
481.851.853951.85250.00145255-0.00395255
491.861.856521.855420.001105320.00347801
501.861.857081.85792-0.000839120.00292245
511.861.859581.86083-0.001255790.000422454
521.861.861111.86458-0.00347801-0.00110532
531.871.864091.86875-0.004658560.00590856
541.871.866731.87333-0.006603010.00326968
551.871.886241.877920.00832755-0.0162442
561.871.884651.882080.00256366-0.014647
571.881.887221.886670.000549769-0.00721644
581.91.893811.891670.002146990.00618634
591.91.896941.896250.0006886570.00306134
601.911.901871.900420.001452550.00813079
611.911.905691.904580.001105320.00431134
621.911.907911.90875-0.000839120.00208912
631.921.911241.9125-0.001255790.00875579
641.921.911521.915-0.003478010.00847801
651.921.912421.91708-0.004658560.00757523
661.921.912561.91917-0.006603010.00743634
671.921.929161.920830.00832755-0.00916088
681.921.925481.922920.00256366-0.00548032
691.921.925971.925420.000549769-0.00596644
701.921.930061.927920.00214699-0.0100637
711.931.931111.930420.000688657-0.00110532
721.931.934371.932920.00145255-0.00436921
731.931.937771.936670.00110532-0.00777199
741.941.940831.94167-0.00083912-0.000827546
751.951.946661.94792-0.001255790.00333912
761.951.952361.95583-0.00347801-0.00235532
771.951.962841.9675-0.00465856-0.0128414
781.951.977151.98375-0.00660301-0.027147
791.98NANA0.00832755NA
801.98NANA0.00256366NA
812.01NANA0.000549769NA
822.02NANA0.00214699NA
832.11NANA0.000688657NA
842.14NANA0.00145255NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 1.49 & NA & NA & 0.00110532 & NA \tabularnewline
2 & 1.55 & NA & NA & -0.00083912 & NA \tabularnewline
3 & 1.57 & NA & NA & -0.00125579 & NA \tabularnewline
4 & 1.6 & NA & NA & -0.00347801 & NA \tabularnewline
5 & 1.61 & NA & NA & -0.00465856 & NA \tabularnewline
6 & 1.68 & NA & NA & -0.00660301 & NA \tabularnewline
7 & 1.72 & 1.67749 & 1.66917 & 0.00832755 & 0.0425058 \tabularnewline
8 & 1.72 & 1.6909 & 1.68833 & 0.00256366 & 0.029103 \tabularnewline
9 & 1.73 & 1.70472 & 1.70417 & 0.000549769 & 0.0252836 \tabularnewline
10 & 1.74 & 1.72048 & 1.71833 & 0.00214699 & 0.0195197 \tabularnewline
11 & 1.74 & 1.73194 & 1.73125 & 0.000688657 & 0.00806134 \tabularnewline
12 & 1.75 & 1.7427 & 1.74125 & 0.00145255 & 0.00729745 \tabularnewline
13 & 1.75 & 1.74861 & 1.7475 & 0.00110532 & 0.00139468 \tabularnewline
14 & 1.75 & 1.75166 & 1.7525 & -0.00083912 & -0.00166088 \tabularnewline
15 & 1.75 & 1.75583 & 1.75708 & -0.00125579 & -0.00582755 \tabularnewline
16 & 1.76 & 1.75736 & 1.76083 & -0.00347801 & 0.00264468 \tabularnewline
17 & 1.76 & 1.75951 & 1.76417 & -0.00465856 & 0.000491898 \tabularnewline
18 & 1.77 & 1.7609 & 1.7675 & -0.00660301 & 0.00910301 \tabularnewline
19 & 1.78 & 1.77916 & 1.77083 & 0.00832755 & 0.00083912 \tabularnewline
20 & 1.78 & 1.77673 & 1.77417 & 0.00256366 & 0.00326968 \tabularnewline
21 & 1.78 & 1.77805 & 1.7775 & 0.000549769 & 0.00195023 \tabularnewline
22 & 1.78 & 1.78256 & 1.78042 & 0.00214699 & -0.00256366 \tabularnewline
23 & 1.78 & 1.78361 & 1.78292 & 0.000688657 & -0.00360532 \tabularnewline
24 & 1.79 & 1.78687 & 1.78542 & 0.00145255 & 0.00313079 \tabularnewline
25 & 1.79 & 1.78861 & 1.7875 & 0.00110532 & 0.00139468 \tabularnewline
26 & 1.79 & 1.78833 & 1.78917 & -0.00083912 & 0.00167245 \tabularnewline
27 & 1.79 & 1.78958 & 1.79083 & -0.00125579 & 0.000422454 \tabularnewline
28 & 1.79 & 1.78902 & 1.7925 & -0.00347801 & 0.000978009 \tabularnewline
29 & 1.79 & 1.78992 & 1.79458 & -0.00465856 & 7.52315e-05 \tabularnewline
30 & 1.8 & 1.79006 & 1.79667 & -0.00660301 & 0.00993634 \tabularnewline
31 & 1.8 & 1.80708 & 1.79875 & 0.00832755 & -0.00707755 \tabularnewline
32 & 1.8 & 1.80381 & 1.80125 & 0.00256366 & -0.00381366 \tabularnewline
33 & 1.8 & 1.8043 & 1.80375 & 0.000549769 & -0.00429977 \tabularnewline
34 & 1.8 & 1.8084 & 1.80625 & 0.00214699 & -0.00839699 \tabularnewline
35 & 1.81 & 1.80986 & 1.80917 & 0.000688657 & 0.000144676 \tabularnewline
36 & 1.81 & 1.81354 & 1.81208 & 0.00145255 & -0.00353588 \tabularnewline
37 & 1.82 & 1.81611 & 1.815 & 0.00110532 & 0.00389468 \tabularnewline
38 & 1.82 & 1.81749 & 1.81833 & -0.00083912 & 0.00250579 \tabularnewline
39 & 1.82 & 1.82041 & 1.82167 & -0.00125579 & -0.00041088 \tabularnewline
40 & 1.82 & 1.82194 & 1.82542 & -0.00347801 & -0.00193866 \tabularnewline
41 & 1.83 & 1.82451 & 1.82917 & -0.00465856 & 0.0054919 \tabularnewline
42 & 1.83 & 1.8259 & 1.8325 & -0.00660301 & 0.00410301 \tabularnewline
43 & 1.84 & 1.84416 & 1.83583 & 0.00832755 & -0.00416088 \tabularnewline
44 & 1.84 & 1.84173 & 1.83917 & 0.00256366 & -0.00173032 \tabularnewline
45 & 1.84 & 1.84305 & 1.8425 & 0.000549769 & -0.00304977 \tabularnewline
46 & 1.85 & 1.84798 & 1.84583 & 0.00214699 & 0.00201968 \tabularnewline
47 & 1.85 & 1.84986 & 1.84917 & 0.000688657 & 0.000144676 \tabularnewline
48 & 1.85 & 1.85395 & 1.8525 & 0.00145255 & -0.00395255 \tabularnewline
49 & 1.86 & 1.85652 & 1.85542 & 0.00110532 & 0.00347801 \tabularnewline
50 & 1.86 & 1.85708 & 1.85792 & -0.00083912 & 0.00292245 \tabularnewline
51 & 1.86 & 1.85958 & 1.86083 & -0.00125579 & 0.000422454 \tabularnewline
52 & 1.86 & 1.86111 & 1.86458 & -0.00347801 & -0.00110532 \tabularnewline
53 & 1.87 & 1.86409 & 1.86875 & -0.00465856 & 0.00590856 \tabularnewline
54 & 1.87 & 1.86673 & 1.87333 & -0.00660301 & 0.00326968 \tabularnewline
55 & 1.87 & 1.88624 & 1.87792 & 0.00832755 & -0.0162442 \tabularnewline
56 & 1.87 & 1.88465 & 1.88208 & 0.00256366 & -0.014647 \tabularnewline
57 & 1.88 & 1.88722 & 1.88667 & 0.000549769 & -0.00721644 \tabularnewline
58 & 1.9 & 1.89381 & 1.89167 & 0.00214699 & 0.00618634 \tabularnewline
59 & 1.9 & 1.89694 & 1.89625 & 0.000688657 & 0.00306134 \tabularnewline
60 & 1.91 & 1.90187 & 1.90042 & 0.00145255 & 0.00813079 \tabularnewline
61 & 1.91 & 1.90569 & 1.90458 & 0.00110532 & 0.00431134 \tabularnewline
62 & 1.91 & 1.90791 & 1.90875 & -0.00083912 & 0.00208912 \tabularnewline
63 & 1.92 & 1.91124 & 1.9125 & -0.00125579 & 0.00875579 \tabularnewline
64 & 1.92 & 1.91152 & 1.915 & -0.00347801 & 0.00847801 \tabularnewline
65 & 1.92 & 1.91242 & 1.91708 & -0.00465856 & 0.00757523 \tabularnewline
66 & 1.92 & 1.91256 & 1.91917 & -0.00660301 & 0.00743634 \tabularnewline
67 & 1.92 & 1.92916 & 1.92083 & 0.00832755 & -0.00916088 \tabularnewline
68 & 1.92 & 1.92548 & 1.92292 & 0.00256366 & -0.00548032 \tabularnewline
69 & 1.92 & 1.92597 & 1.92542 & 0.000549769 & -0.00596644 \tabularnewline
70 & 1.92 & 1.93006 & 1.92792 & 0.00214699 & -0.0100637 \tabularnewline
71 & 1.93 & 1.93111 & 1.93042 & 0.000688657 & -0.00110532 \tabularnewline
72 & 1.93 & 1.93437 & 1.93292 & 0.00145255 & -0.00436921 \tabularnewline
73 & 1.93 & 1.93777 & 1.93667 & 0.00110532 & -0.00777199 \tabularnewline
74 & 1.94 & 1.94083 & 1.94167 & -0.00083912 & -0.000827546 \tabularnewline
75 & 1.95 & 1.94666 & 1.94792 & -0.00125579 & 0.00333912 \tabularnewline
76 & 1.95 & 1.95236 & 1.95583 & -0.00347801 & -0.00235532 \tabularnewline
77 & 1.95 & 1.96284 & 1.9675 & -0.00465856 & -0.0128414 \tabularnewline
78 & 1.95 & 1.97715 & 1.98375 & -0.00660301 & -0.027147 \tabularnewline
79 & 1.98 & NA & NA & 0.00832755 & NA \tabularnewline
80 & 1.98 & NA & NA & 0.00256366 & NA \tabularnewline
81 & 2.01 & NA & NA & 0.000549769 & NA \tabularnewline
82 & 2.02 & NA & NA & 0.00214699 & NA \tabularnewline
83 & 2.11 & NA & NA & 0.000688657 & NA \tabularnewline
84 & 2.14 & NA & NA & 0.00145255 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232560&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]1.49[/C][C]NA[/C][C]NA[/C][C]0.00110532[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]1.55[/C][C]NA[/C][C]NA[/C][C]-0.00083912[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1.57[/C][C]NA[/C][C]NA[/C][C]-0.00125579[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1.6[/C][C]NA[/C][C]NA[/C][C]-0.00347801[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1.61[/C][C]NA[/C][C]NA[/C][C]-0.00465856[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1.68[/C][C]NA[/C][C]NA[/C][C]-0.00660301[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1.72[/C][C]1.67749[/C][C]1.66917[/C][C]0.00832755[/C][C]0.0425058[/C][/ROW]
[ROW][C]8[/C][C]1.72[/C][C]1.6909[/C][C]1.68833[/C][C]0.00256366[/C][C]0.029103[/C][/ROW]
[ROW][C]9[/C][C]1.73[/C][C]1.70472[/C][C]1.70417[/C][C]0.000549769[/C][C]0.0252836[/C][/ROW]
[ROW][C]10[/C][C]1.74[/C][C]1.72048[/C][C]1.71833[/C][C]0.00214699[/C][C]0.0195197[/C][/ROW]
[ROW][C]11[/C][C]1.74[/C][C]1.73194[/C][C]1.73125[/C][C]0.000688657[/C][C]0.00806134[/C][/ROW]
[ROW][C]12[/C][C]1.75[/C][C]1.7427[/C][C]1.74125[/C][C]0.00145255[/C][C]0.00729745[/C][/ROW]
[ROW][C]13[/C][C]1.75[/C][C]1.74861[/C][C]1.7475[/C][C]0.00110532[/C][C]0.00139468[/C][/ROW]
[ROW][C]14[/C][C]1.75[/C][C]1.75166[/C][C]1.7525[/C][C]-0.00083912[/C][C]-0.00166088[/C][/ROW]
[ROW][C]15[/C][C]1.75[/C][C]1.75583[/C][C]1.75708[/C][C]-0.00125579[/C][C]-0.00582755[/C][/ROW]
[ROW][C]16[/C][C]1.76[/C][C]1.75736[/C][C]1.76083[/C][C]-0.00347801[/C][C]0.00264468[/C][/ROW]
[ROW][C]17[/C][C]1.76[/C][C]1.75951[/C][C]1.76417[/C][C]-0.00465856[/C][C]0.000491898[/C][/ROW]
[ROW][C]18[/C][C]1.77[/C][C]1.7609[/C][C]1.7675[/C][C]-0.00660301[/C][C]0.00910301[/C][/ROW]
[ROW][C]19[/C][C]1.78[/C][C]1.77916[/C][C]1.77083[/C][C]0.00832755[/C][C]0.00083912[/C][/ROW]
[ROW][C]20[/C][C]1.78[/C][C]1.77673[/C][C]1.77417[/C][C]0.00256366[/C][C]0.00326968[/C][/ROW]
[ROW][C]21[/C][C]1.78[/C][C]1.77805[/C][C]1.7775[/C][C]0.000549769[/C][C]0.00195023[/C][/ROW]
[ROW][C]22[/C][C]1.78[/C][C]1.78256[/C][C]1.78042[/C][C]0.00214699[/C][C]-0.00256366[/C][/ROW]
[ROW][C]23[/C][C]1.78[/C][C]1.78361[/C][C]1.78292[/C][C]0.000688657[/C][C]-0.00360532[/C][/ROW]
[ROW][C]24[/C][C]1.79[/C][C]1.78687[/C][C]1.78542[/C][C]0.00145255[/C][C]0.00313079[/C][/ROW]
[ROW][C]25[/C][C]1.79[/C][C]1.78861[/C][C]1.7875[/C][C]0.00110532[/C][C]0.00139468[/C][/ROW]
[ROW][C]26[/C][C]1.79[/C][C]1.78833[/C][C]1.78917[/C][C]-0.00083912[/C][C]0.00167245[/C][/ROW]
[ROW][C]27[/C][C]1.79[/C][C]1.78958[/C][C]1.79083[/C][C]-0.00125579[/C][C]0.000422454[/C][/ROW]
[ROW][C]28[/C][C]1.79[/C][C]1.78902[/C][C]1.7925[/C][C]-0.00347801[/C][C]0.000978009[/C][/ROW]
[ROW][C]29[/C][C]1.79[/C][C]1.78992[/C][C]1.79458[/C][C]-0.00465856[/C][C]7.52315e-05[/C][/ROW]
[ROW][C]30[/C][C]1.8[/C][C]1.79006[/C][C]1.79667[/C][C]-0.00660301[/C][C]0.00993634[/C][/ROW]
[ROW][C]31[/C][C]1.8[/C][C]1.80708[/C][C]1.79875[/C][C]0.00832755[/C][C]-0.00707755[/C][/ROW]
[ROW][C]32[/C][C]1.8[/C][C]1.80381[/C][C]1.80125[/C][C]0.00256366[/C][C]-0.00381366[/C][/ROW]
[ROW][C]33[/C][C]1.8[/C][C]1.8043[/C][C]1.80375[/C][C]0.000549769[/C][C]-0.00429977[/C][/ROW]
[ROW][C]34[/C][C]1.8[/C][C]1.8084[/C][C]1.80625[/C][C]0.00214699[/C][C]-0.00839699[/C][/ROW]
[ROW][C]35[/C][C]1.81[/C][C]1.80986[/C][C]1.80917[/C][C]0.000688657[/C][C]0.000144676[/C][/ROW]
[ROW][C]36[/C][C]1.81[/C][C]1.81354[/C][C]1.81208[/C][C]0.00145255[/C][C]-0.00353588[/C][/ROW]
[ROW][C]37[/C][C]1.82[/C][C]1.81611[/C][C]1.815[/C][C]0.00110532[/C][C]0.00389468[/C][/ROW]
[ROW][C]38[/C][C]1.82[/C][C]1.81749[/C][C]1.81833[/C][C]-0.00083912[/C][C]0.00250579[/C][/ROW]
[ROW][C]39[/C][C]1.82[/C][C]1.82041[/C][C]1.82167[/C][C]-0.00125579[/C][C]-0.00041088[/C][/ROW]
[ROW][C]40[/C][C]1.82[/C][C]1.82194[/C][C]1.82542[/C][C]-0.00347801[/C][C]-0.00193866[/C][/ROW]
[ROW][C]41[/C][C]1.83[/C][C]1.82451[/C][C]1.82917[/C][C]-0.00465856[/C][C]0.0054919[/C][/ROW]
[ROW][C]42[/C][C]1.83[/C][C]1.8259[/C][C]1.8325[/C][C]-0.00660301[/C][C]0.00410301[/C][/ROW]
[ROW][C]43[/C][C]1.84[/C][C]1.84416[/C][C]1.83583[/C][C]0.00832755[/C][C]-0.00416088[/C][/ROW]
[ROW][C]44[/C][C]1.84[/C][C]1.84173[/C][C]1.83917[/C][C]0.00256366[/C][C]-0.00173032[/C][/ROW]
[ROW][C]45[/C][C]1.84[/C][C]1.84305[/C][C]1.8425[/C][C]0.000549769[/C][C]-0.00304977[/C][/ROW]
[ROW][C]46[/C][C]1.85[/C][C]1.84798[/C][C]1.84583[/C][C]0.00214699[/C][C]0.00201968[/C][/ROW]
[ROW][C]47[/C][C]1.85[/C][C]1.84986[/C][C]1.84917[/C][C]0.000688657[/C][C]0.000144676[/C][/ROW]
[ROW][C]48[/C][C]1.85[/C][C]1.85395[/C][C]1.8525[/C][C]0.00145255[/C][C]-0.00395255[/C][/ROW]
[ROW][C]49[/C][C]1.86[/C][C]1.85652[/C][C]1.85542[/C][C]0.00110532[/C][C]0.00347801[/C][/ROW]
[ROW][C]50[/C][C]1.86[/C][C]1.85708[/C][C]1.85792[/C][C]-0.00083912[/C][C]0.00292245[/C][/ROW]
[ROW][C]51[/C][C]1.86[/C][C]1.85958[/C][C]1.86083[/C][C]-0.00125579[/C][C]0.000422454[/C][/ROW]
[ROW][C]52[/C][C]1.86[/C][C]1.86111[/C][C]1.86458[/C][C]-0.00347801[/C][C]-0.00110532[/C][/ROW]
[ROW][C]53[/C][C]1.87[/C][C]1.86409[/C][C]1.86875[/C][C]-0.00465856[/C][C]0.00590856[/C][/ROW]
[ROW][C]54[/C][C]1.87[/C][C]1.86673[/C][C]1.87333[/C][C]-0.00660301[/C][C]0.00326968[/C][/ROW]
[ROW][C]55[/C][C]1.87[/C][C]1.88624[/C][C]1.87792[/C][C]0.00832755[/C][C]-0.0162442[/C][/ROW]
[ROW][C]56[/C][C]1.87[/C][C]1.88465[/C][C]1.88208[/C][C]0.00256366[/C][C]-0.014647[/C][/ROW]
[ROW][C]57[/C][C]1.88[/C][C]1.88722[/C][C]1.88667[/C][C]0.000549769[/C][C]-0.00721644[/C][/ROW]
[ROW][C]58[/C][C]1.9[/C][C]1.89381[/C][C]1.89167[/C][C]0.00214699[/C][C]0.00618634[/C][/ROW]
[ROW][C]59[/C][C]1.9[/C][C]1.89694[/C][C]1.89625[/C][C]0.000688657[/C][C]0.00306134[/C][/ROW]
[ROW][C]60[/C][C]1.91[/C][C]1.90187[/C][C]1.90042[/C][C]0.00145255[/C][C]0.00813079[/C][/ROW]
[ROW][C]61[/C][C]1.91[/C][C]1.90569[/C][C]1.90458[/C][C]0.00110532[/C][C]0.00431134[/C][/ROW]
[ROW][C]62[/C][C]1.91[/C][C]1.90791[/C][C]1.90875[/C][C]-0.00083912[/C][C]0.00208912[/C][/ROW]
[ROW][C]63[/C][C]1.92[/C][C]1.91124[/C][C]1.9125[/C][C]-0.00125579[/C][C]0.00875579[/C][/ROW]
[ROW][C]64[/C][C]1.92[/C][C]1.91152[/C][C]1.915[/C][C]-0.00347801[/C][C]0.00847801[/C][/ROW]
[ROW][C]65[/C][C]1.92[/C][C]1.91242[/C][C]1.91708[/C][C]-0.00465856[/C][C]0.00757523[/C][/ROW]
[ROW][C]66[/C][C]1.92[/C][C]1.91256[/C][C]1.91917[/C][C]-0.00660301[/C][C]0.00743634[/C][/ROW]
[ROW][C]67[/C][C]1.92[/C][C]1.92916[/C][C]1.92083[/C][C]0.00832755[/C][C]-0.00916088[/C][/ROW]
[ROW][C]68[/C][C]1.92[/C][C]1.92548[/C][C]1.92292[/C][C]0.00256366[/C][C]-0.00548032[/C][/ROW]
[ROW][C]69[/C][C]1.92[/C][C]1.92597[/C][C]1.92542[/C][C]0.000549769[/C][C]-0.00596644[/C][/ROW]
[ROW][C]70[/C][C]1.92[/C][C]1.93006[/C][C]1.92792[/C][C]0.00214699[/C][C]-0.0100637[/C][/ROW]
[ROW][C]71[/C][C]1.93[/C][C]1.93111[/C][C]1.93042[/C][C]0.000688657[/C][C]-0.00110532[/C][/ROW]
[ROW][C]72[/C][C]1.93[/C][C]1.93437[/C][C]1.93292[/C][C]0.00145255[/C][C]-0.00436921[/C][/ROW]
[ROW][C]73[/C][C]1.93[/C][C]1.93777[/C][C]1.93667[/C][C]0.00110532[/C][C]-0.00777199[/C][/ROW]
[ROW][C]74[/C][C]1.94[/C][C]1.94083[/C][C]1.94167[/C][C]-0.00083912[/C][C]-0.000827546[/C][/ROW]
[ROW][C]75[/C][C]1.95[/C][C]1.94666[/C][C]1.94792[/C][C]-0.00125579[/C][C]0.00333912[/C][/ROW]
[ROW][C]76[/C][C]1.95[/C][C]1.95236[/C][C]1.95583[/C][C]-0.00347801[/C][C]-0.00235532[/C][/ROW]
[ROW][C]77[/C][C]1.95[/C][C]1.96284[/C][C]1.9675[/C][C]-0.00465856[/C][C]-0.0128414[/C][/ROW]
[ROW][C]78[/C][C]1.95[/C][C]1.97715[/C][C]1.98375[/C][C]-0.00660301[/C][C]-0.027147[/C][/ROW]
[ROW][C]79[/C][C]1.98[/C][C]NA[/C][C]NA[/C][C]0.00832755[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]1.98[/C][C]NA[/C][C]NA[/C][C]0.00256366[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]2.01[/C][C]NA[/C][C]NA[/C][C]0.000549769[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]2.02[/C][C]NA[/C][C]NA[/C][C]0.00214699[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]2.11[/C][C]NA[/C][C]NA[/C][C]0.000688657[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]2.14[/C][C]NA[/C][C]NA[/C][C]0.00145255[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232560&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232560&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
11.49NANA0.00110532NA
21.55NANA-0.00083912NA
31.57NANA-0.00125579NA
41.6NANA-0.00347801NA
51.61NANA-0.00465856NA
61.68NANA-0.00660301NA
71.721.677491.669170.008327550.0425058
81.721.69091.688330.002563660.029103
91.731.704721.704170.0005497690.0252836
101.741.720481.718330.002146990.0195197
111.741.731941.731250.0006886570.00806134
121.751.74271.741250.001452550.00729745
131.751.748611.74750.001105320.00139468
141.751.751661.7525-0.00083912-0.00166088
151.751.755831.75708-0.00125579-0.00582755
161.761.757361.76083-0.003478010.00264468
171.761.759511.76417-0.004658560.000491898
181.771.76091.7675-0.006603010.00910301
191.781.779161.770830.008327550.00083912
201.781.776731.774170.002563660.00326968
211.781.778051.77750.0005497690.00195023
221.781.782561.780420.00214699-0.00256366
231.781.783611.782920.000688657-0.00360532
241.791.786871.785420.001452550.00313079
251.791.788611.78750.001105320.00139468
261.791.788331.78917-0.000839120.00167245
271.791.789581.79083-0.001255790.000422454
281.791.789021.7925-0.003478010.000978009
291.791.789921.79458-0.004658567.52315e-05
301.81.790061.79667-0.006603010.00993634
311.81.807081.798750.00832755-0.00707755
321.81.803811.801250.00256366-0.00381366
331.81.80431.803750.000549769-0.00429977
341.81.80841.806250.00214699-0.00839699
351.811.809861.809170.0006886570.000144676
361.811.813541.812080.00145255-0.00353588
371.821.816111.8150.001105320.00389468
381.821.817491.81833-0.000839120.00250579
391.821.820411.82167-0.00125579-0.00041088
401.821.821941.82542-0.00347801-0.00193866
411.831.824511.82917-0.004658560.0054919
421.831.82591.8325-0.006603010.00410301
431.841.844161.835830.00832755-0.00416088
441.841.841731.839170.00256366-0.00173032
451.841.843051.84250.000549769-0.00304977
461.851.847981.845830.002146990.00201968
471.851.849861.849170.0006886570.000144676
481.851.853951.85250.00145255-0.00395255
491.861.856521.855420.001105320.00347801
501.861.857081.85792-0.000839120.00292245
511.861.859581.86083-0.001255790.000422454
521.861.861111.86458-0.00347801-0.00110532
531.871.864091.86875-0.004658560.00590856
541.871.866731.87333-0.006603010.00326968
551.871.886241.877920.00832755-0.0162442
561.871.884651.882080.00256366-0.014647
571.881.887221.886670.000549769-0.00721644
581.91.893811.891670.002146990.00618634
591.91.896941.896250.0006886570.00306134
601.911.901871.900420.001452550.00813079
611.911.905691.904580.001105320.00431134
621.911.907911.90875-0.000839120.00208912
631.921.911241.9125-0.001255790.00875579
641.921.911521.915-0.003478010.00847801
651.921.912421.91708-0.004658560.00757523
661.921.912561.91917-0.006603010.00743634
671.921.929161.920830.00832755-0.00916088
681.921.925481.922920.00256366-0.00548032
691.921.925971.925420.000549769-0.00596644
701.921.930061.927920.00214699-0.0100637
711.931.931111.930420.000688657-0.00110532
721.931.934371.932920.00145255-0.00436921
731.931.937771.936670.00110532-0.00777199
741.941.940831.94167-0.00083912-0.000827546
751.951.946661.94792-0.001255790.00333912
761.951.952361.95583-0.00347801-0.00235532
771.951.962841.9675-0.00465856-0.0128414
781.951.977151.98375-0.00660301-0.027147
791.98NANA0.00832755NA
801.98NANA0.00256366NA
812.01NANA0.000549769NA
822.02NANA0.00214699NA
832.11NANA0.000688657NA
842.14NANA0.00145255NA



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 <- 'multiplicative'
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')