Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 12 Dec 2013 13:46:21 -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/t1386874084yxv5pgl16y9xzs3.htm/, Retrieved Tue, 07 Dec 2021 11:13:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=232265, Retrieved Tue, 07 Dec 2021 11:13:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact40
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2013-12-12 18:46:21] [3c7daf9c150a57900c7784703a011e78] [Current]
Feedback Forum

Post a new message
Dataseries X:
102,78
102,78
102,78
102,78
102,78
102,78
102,78
101,67
101,67
101,67
101,67
101,67
101,67
101,67
101,67
101,67
101,67
101,67
101,67
105,79
105,79
105,79
105,79
105,79
105,79
105,79
105,79
105,79
105,79
105,79
105,79
104,47
104,47
104,47
104,47
104,47
104,47
104,47
104,47
105,5
105,5
105,5
105,5
106,61
106,61
106,61
106,61
106,61
106,61
106,61
106,61
112,06
112,06
112,06
112,06
111,18
111,18
111,18
111,18
111,18
111,18
111,18
111,18
117,21
117,21
117,21
117,21
107,98
107,98
107,98
107,98
107,98




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232265&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232265&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232265&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'Gwilym Jenkins' @ jenkins.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1102.78NANA-0.817035NA
2102.78NANA-0.989868NA
3102.78NANA-1.09503NA
4102.78NANA1.3018NA
5102.78NANA1.19663NA
6102.78NANA1.09147NA
7102.78102.262102.271-0.009284720.518035
8101.67102.413102.1790.234715-0.743465
9101.67102.181102.0860.0947153-0.510965
10101.67101.898101.994-0.0955347-0.228215
11101.67101.565101.901-0.3360350.104785
12101.67101.232101.809-0.5765350.437785
13101.67100.899101.716-0.8170350.770785
14101.67100.852101.842-0.9898680.818201
15101.67101.09102.185-1.095030.580035
16101.67103.83102.5281.3018-2.16013
17101.67104.068102.8721.19663-2.3983
18101.67104.306103.2151.09147-2.63647
19101.67103.549103.558-0.00928472-1.87905
20105.79104.136103.9020.2347151.65362
21105.79104.34104.2450.09471531.45028
22105.79104.493104.588-0.09553471.2972
23105.79104.596104.932-0.3360351.19437
24105.79104.698105.275-0.5765351.09153
25105.79104.801105.618-0.8170350.988701
26105.79104.745105.735-0.9898681.04487
27105.79104.53105.625-1.095031.26003
28105.79106.817105.5151.3018-1.0268
29105.79106.602105.4051.19663-0.811632
30105.79106.386105.2951.09147-0.596465
31105.79105.176105.185-0.009284720.614285
32104.47105.31105.0750.234715-0.839715
33104.47105.06104.9650.0947153-0.589715
34104.47104.802104.898-0.0955347-0.332382
35104.47104.538104.874-0.336035-0.0677153
36104.47104.273104.85-0.5765350.196951
37104.47104.008104.825-0.8170350.461618
38104.47103.913104.902-0.9898680.557368
39104.47103.986105.081-1.095030.484201
40105.5106.561105.2591.3018-1.06097
41105.5106.634105.4371.19663-1.13413
42105.5106.707105.6161.09147-1.2073
43105.5105.785105.794-0.00928472-0.284882
44106.61106.207105.9730.2347150.402785
45106.61106.246106.1510.09471530.364451
46106.61106.418106.513-0.09553470.192201
47106.61106.724107.06-0.336035-0.113965
48106.61107.03107.607-0.576535-0.420132
49106.61107.336108.153-0.817035-0.726299
50106.61107.627108.617-0.989868-1.01722
51106.61107.903108.998-1.09503-1.29288
52112.06110.681109.3791.30181.37945
53112.06110.956109.761.196631.10378
54112.06111.232110.141.091470.828118
55112.06110.512110.521-0.009284721.54803
56111.18111.137110.9020.2347150.0432014
57111.18111.378111.2830.0947153-0.197632
58111.18111.592111.688-0.0955347-0.412382
59111.18111.781112.117-0.336035-0.601049
60111.18111.97112.546-0.576535-0.789715
61111.18112.158112.975-0.817035-0.978382
62111.18112.067113.057-0.989868-0.886799
63111.18111.695112.79-1.09503-0.514965
64117.21113.825112.5231.30183.38487
65117.21113.453112.2571.196633.7567
66117.21113.081111.991.091474.12853
67117.21NANA-0.00928472NA
68107.98NANA0.234715NA
69107.98NANA0.0947153NA
70107.98NANA-0.0955347NA
71107.98NANA-0.336035NA
72107.98NANA-0.576535NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 102.78 & NA & NA & -0.817035 & NA \tabularnewline
2 & 102.78 & NA & NA & -0.989868 & NA \tabularnewline
3 & 102.78 & NA & NA & -1.09503 & NA \tabularnewline
4 & 102.78 & NA & NA & 1.3018 & NA \tabularnewline
5 & 102.78 & NA & NA & 1.19663 & NA \tabularnewline
6 & 102.78 & NA & NA & 1.09147 & NA \tabularnewline
7 & 102.78 & 102.262 & 102.271 & -0.00928472 & 0.518035 \tabularnewline
8 & 101.67 & 102.413 & 102.179 & 0.234715 & -0.743465 \tabularnewline
9 & 101.67 & 102.181 & 102.086 & 0.0947153 & -0.510965 \tabularnewline
10 & 101.67 & 101.898 & 101.994 & -0.0955347 & -0.228215 \tabularnewline
11 & 101.67 & 101.565 & 101.901 & -0.336035 & 0.104785 \tabularnewline
12 & 101.67 & 101.232 & 101.809 & -0.576535 & 0.437785 \tabularnewline
13 & 101.67 & 100.899 & 101.716 & -0.817035 & 0.770785 \tabularnewline
14 & 101.67 & 100.852 & 101.842 & -0.989868 & 0.818201 \tabularnewline
15 & 101.67 & 101.09 & 102.185 & -1.09503 & 0.580035 \tabularnewline
16 & 101.67 & 103.83 & 102.528 & 1.3018 & -2.16013 \tabularnewline
17 & 101.67 & 104.068 & 102.872 & 1.19663 & -2.3983 \tabularnewline
18 & 101.67 & 104.306 & 103.215 & 1.09147 & -2.63647 \tabularnewline
19 & 101.67 & 103.549 & 103.558 & -0.00928472 & -1.87905 \tabularnewline
20 & 105.79 & 104.136 & 103.902 & 0.234715 & 1.65362 \tabularnewline
21 & 105.79 & 104.34 & 104.245 & 0.0947153 & 1.45028 \tabularnewline
22 & 105.79 & 104.493 & 104.588 & -0.0955347 & 1.2972 \tabularnewline
23 & 105.79 & 104.596 & 104.932 & -0.336035 & 1.19437 \tabularnewline
24 & 105.79 & 104.698 & 105.275 & -0.576535 & 1.09153 \tabularnewline
25 & 105.79 & 104.801 & 105.618 & -0.817035 & 0.988701 \tabularnewline
26 & 105.79 & 104.745 & 105.735 & -0.989868 & 1.04487 \tabularnewline
27 & 105.79 & 104.53 & 105.625 & -1.09503 & 1.26003 \tabularnewline
28 & 105.79 & 106.817 & 105.515 & 1.3018 & -1.0268 \tabularnewline
29 & 105.79 & 106.602 & 105.405 & 1.19663 & -0.811632 \tabularnewline
30 & 105.79 & 106.386 & 105.295 & 1.09147 & -0.596465 \tabularnewline
31 & 105.79 & 105.176 & 105.185 & -0.00928472 & 0.614285 \tabularnewline
32 & 104.47 & 105.31 & 105.075 & 0.234715 & -0.839715 \tabularnewline
33 & 104.47 & 105.06 & 104.965 & 0.0947153 & -0.589715 \tabularnewline
34 & 104.47 & 104.802 & 104.898 & -0.0955347 & -0.332382 \tabularnewline
35 & 104.47 & 104.538 & 104.874 & -0.336035 & -0.0677153 \tabularnewline
36 & 104.47 & 104.273 & 104.85 & -0.576535 & 0.196951 \tabularnewline
37 & 104.47 & 104.008 & 104.825 & -0.817035 & 0.461618 \tabularnewline
38 & 104.47 & 103.913 & 104.902 & -0.989868 & 0.557368 \tabularnewline
39 & 104.47 & 103.986 & 105.081 & -1.09503 & 0.484201 \tabularnewline
40 & 105.5 & 106.561 & 105.259 & 1.3018 & -1.06097 \tabularnewline
41 & 105.5 & 106.634 & 105.437 & 1.19663 & -1.13413 \tabularnewline
42 & 105.5 & 106.707 & 105.616 & 1.09147 & -1.2073 \tabularnewline
43 & 105.5 & 105.785 & 105.794 & -0.00928472 & -0.284882 \tabularnewline
44 & 106.61 & 106.207 & 105.973 & 0.234715 & 0.402785 \tabularnewline
45 & 106.61 & 106.246 & 106.151 & 0.0947153 & 0.364451 \tabularnewline
46 & 106.61 & 106.418 & 106.513 & -0.0955347 & 0.192201 \tabularnewline
47 & 106.61 & 106.724 & 107.06 & -0.336035 & -0.113965 \tabularnewline
48 & 106.61 & 107.03 & 107.607 & -0.576535 & -0.420132 \tabularnewline
49 & 106.61 & 107.336 & 108.153 & -0.817035 & -0.726299 \tabularnewline
50 & 106.61 & 107.627 & 108.617 & -0.989868 & -1.01722 \tabularnewline
51 & 106.61 & 107.903 & 108.998 & -1.09503 & -1.29288 \tabularnewline
52 & 112.06 & 110.681 & 109.379 & 1.3018 & 1.37945 \tabularnewline
53 & 112.06 & 110.956 & 109.76 & 1.19663 & 1.10378 \tabularnewline
54 & 112.06 & 111.232 & 110.14 & 1.09147 & 0.828118 \tabularnewline
55 & 112.06 & 110.512 & 110.521 & -0.00928472 & 1.54803 \tabularnewline
56 & 111.18 & 111.137 & 110.902 & 0.234715 & 0.0432014 \tabularnewline
57 & 111.18 & 111.378 & 111.283 & 0.0947153 & -0.197632 \tabularnewline
58 & 111.18 & 111.592 & 111.688 & -0.0955347 & -0.412382 \tabularnewline
59 & 111.18 & 111.781 & 112.117 & -0.336035 & -0.601049 \tabularnewline
60 & 111.18 & 111.97 & 112.546 & -0.576535 & -0.789715 \tabularnewline
61 & 111.18 & 112.158 & 112.975 & -0.817035 & -0.978382 \tabularnewline
62 & 111.18 & 112.067 & 113.057 & -0.989868 & -0.886799 \tabularnewline
63 & 111.18 & 111.695 & 112.79 & -1.09503 & -0.514965 \tabularnewline
64 & 117.21 & 113.825 & 112.523 & 1.3018 & 3.38487 \tabularnewline
65 & 117.21 & 113.453 & 112.257 & 1.19663 & 3.7567 \tabularnewline
66 & 117.21 & 113.081 & 111.99 & 1.09147 & 4.12853 \tabularnewline
67 & 117.21 & NA & NA & -0.00928472 & NA \tabularnewline
68 & 107.98 & NA & NA & 0.234715 & NA \tabularnewline
69 & 107.98 & NA & NA & 0.0947153 & NA \tabularnewline
70 & 107.98 & NA & NA & -0.0955347 & NA \tabularnewline
71 & 107.98 & NA & NA & -0.336035 & NA \tabularnewline
72 & 107.98 & NA & NA & -0.576535 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=232265&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]102.78[/C][C]NA[/C][C]NA[/C][C]-0.817035[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]102.78[/C][C]NA[/C][C]NA[/C][C]-0.989868[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]102.78[/C][C]NA[/C][C]NA[/C][C]-1.09503[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]102.78[/C][C]NA[/C][C]NA[/C][C]1.3018[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]102.78[/C][C]NA[/C][C]NA[/C][C]1.19663[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]102.78[/C][C]NA[/C][C]NA[/C][C]1.09147[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]102.78[/C][C]102.262[/C][C]102.271[/C][C]-0.00928472[/C][C]0.518035[/C][/ROW]
[ROW][C]8[/C][C]101.67[/C][C]102.413[/C][C]102.179[/C][C]0.234715[/C][C]-0.743465[/C][/ROW]
[ROW][C]9[/C][C]101.67[/C][C]102.181[/C][C]102.086[/C][C]0.0947153[/C][C]-0.510965[/C][/ROW]
[ROW][C]10[/C][C]101.67[/C][C]101.898[/C][C]101.994[/C][C]-0.0955347[/C][C]-0.228215[/C][/ROW]
[ROW][C]11[/C][C]101.67[/C][C]101.565[/C][C]101.901[/C][C]-0.336035[/C][C]0.104785[/C][/ROW]
[ROW][C]12[/C][C]101.67[/C][C]101.232[/C][C]101.809[/C][C]-0.576535[/C][C]0.437785[/C][/ROW]
[ROW][C]13[/C][C]101.67[/C][C]100.899[/C][C]101.716[/C][C]-0.817035[/C][C]0.770785[/C][/ROW]
[ROW][C]14[/C][C]101.67[/C][C]100.852[/C][C]101.842[/C][C]-0.989868[/C][C]0.818201[/C][/ROW]
[ROW][C]15[/C][C]101.67[/C][C]101.09[/C][C]102.185[/C][C]-1.09503[/C][C]0.580035[/C][/ROW]
[ROW][C]16[/C][C]101.67[/C][C]103.83[/C][C]102.528[/C][C]1.3018[/C][C]-2.16013[/C][/ROW]
[ROW][C]17[/C][C]101.67[/C][C]104.068[/C][C]102.872[/C][C]1.19663[/C][C]-2.3983[/C][/ROW]
[ROW][C]18[/C][C]101.67[/C][C]104.306[/C][C]103.215[/C][C]1.09147[/C][C]-2.63647[/C][/ROW]
[ROW][C]19[/C][C]101.67[/C][C]103.549[/C][C]103.558[/C][C]-0.00928472[/C][C]-1.87905[/C][/ROW]
[ROW][C]20[/C][C]105.79[/C][C]104.136[/C][C]103.902[/C][C]0.234715[/C][C]1.65362[/C][/ROW]
[ROW][C]21[/C][C]105.79[/C][C]104.34[/C][C]104.245[/C][C]0.0947153[/C][C]1.45028[/C][/ROW]
[ROW][C]22[/C][C]105.79[/C][C]104.493[/C][C]104.588[/C][C]-0.0955347[/C][C]1.2972[/C][/ROW]
[ROW][C]23[/C][C]105.79[/C][C]104.596[/C][C]104.932[/C][C]-0.336035[/C][C]1.19437[/C][/ROW]
[ROW][C]24[/C][C]105.79[/C][C]104.698[/C][C]105.275[/C][C]-0.576535[/C][C]1.09153[/C][/ROW]
[ROW][C]25[/C][C]105.79[/C][C]104.801[/C][C]105.618[/C][C]-0.817035[/C][C]0.988701[/C][/ROW]
[ROW][C]26[/C][C]105.79[/C][C]104.745[/C][C]105.735[/C][C]-0.989868[/C][C]1.04487[/C][/ROW]
[ROW][C]27[/C][C]105.79[/C][C]104.53[/C][C]105.625[/C][C]-1.09503[/C][C]1.26003[/C][/ROW]
[ROW][C]28[/C][C]105.79[/C][C]106.817[/C][C]105.515[/C][C]1.3018[/C][C]-1.0268[/C][/ROW]
[ROW][C]29[/C][C]105.79[/C][C]106.602[/C][C]105.405[/C][C]1.19663[/C][C]-0.811632[/C][/ROW]
[ROW][C]30[/C][C]105.79[/C][C]106.386[/C][C]105.295[/C][C]1.09147[/C][C]-0.596465[/C][/ROW]
[ROW][C]31[/C][C]105.79[/C][C]105.176[/C][C]105.185[/C][C]-0.00928472[/C][C]0.614285[/C][/ROW]
[ROW][C]32[/C][C]104.47[/C][C]105.31[/C][C]105.075[/C][C]0.234715[/C][C]-0.839715[/C][/ROW]
[ROW][C]33[/C][C]104.47[/C][C]105.06[/C][C]104.965[/C][C]0.0947153[/C][C]-0.589715[/C][/ROW]
[ROW][C]34[/C][C]104.47[/C][C]104.802[/C][C]104.898[/C][C]-0.0955347[/C][C]-0.332382[/C][/ROW]
[ROW][C]35[/C][C]104.47[/C][C]104.538[/C][C]104.874[/C][C]-0.336035[/C][C]-0.0677153[/C][/ROW]
[ROW][C]36[/C][C]104.47[/C][C]104.273[/C][C]104.85[/C][C]-0.576535[/C][C]0.196951[/C][/ROW]
[ROW][C]37[/C][C]104.47[/C][C]104.008[/C][C]104.825[/C][C]-0.817035[/C][C]0.461618[/C][/ROW]
[ROW][C]38[/C][C]104.47[/C][C]103.913[/C][C]104.902[/C][C]-0.989868[/C][C]0.557368[/C][/ROW]
[ROW][C]39[/C][C]104.47[/C][C]103.986[/C][C]105.081[/C][C]-1.09503[/C][C]0.484201[/C][/ROW]
[ROW][C]40[/C][C]105.5[/C][C]106.561[/C][C]105.259[/C][C]1.3018[/C][C]-1.06097[/C][/ROW]
[ROW][C]41[/C][C]105.5[/C][C]106.634[/C][C]105.437[/C][C]1.19663[/C][C]-1.13413[/C][/ROW]
[ROW][C]42[/C][C]105.5[/C][C]106.707[/C][C]105.616[/C][C]1.09147[/C][C]-1.2073[/C][/ROW]
[ROW][C]43[/C][C]105.5[/C][C]105.785[/C][C]105.794[/C][C]-0.00928472[/C][C]-0.284882[/C][/ROW]
[ROW][C]44[/C][C]106.61[/C][C]106.207[/C][C]105.973[/C][C]0.234715[/C][C]0.402785[/C][/ROW]
[ROW][C]45[/C][C]106.61[/C][C]106.246[/C][C]106.151[/C][C]0.0947153[/C][C]0.364451[/C][/ROW]
[ROW][C]46[/C][C]106.61[/C][C]106.418[/C][C]106.513[/C][C]-0.0955347[/C][C]0.192201[/C][/ROW]
[ROW][C]47[/C][C]106.61[/C][C]106.724[/C][C]107.06[/C][C]-0.336035[/C][C]-0.113965[/C][/ROW]
[ROW][C]48[/C][C]106.61[/C][C]107.03[/C][C]107.607[/C][C]-0.576535[/C][C]-0.420132[/C][/ROW]
[ROW][C]49[/C][C]106.61[/C][C]107.336[/C][C]108.153[/C][C]-0.817035[/C][C]-0.726299[/C][/ROW]
[ROW][C]50[/C][C]106.61[/C][C]107.627[/C][C]108.617[/C][C]-0.989868[/C][C]-1.01722[/C][/ROW]
[ROW][C]51[/C][C]106.61[/C][C]107.903[/C][C]108.998[/C][C]-1.09503[/C][C]-1.29288[/C][/ROW]
[ROW][C]52[/C][C]112.06[/C][C]110.681[/C][C]109.379[/C][C]1.3018[/C][C]1.37945[/C][/ROW]
[ROW][C]53[/C][C]112.06[/C][C]110.956[/C][C]109.76[/C][C]1.19663[/C][C]1.10378[/C][/ROW]
[ROW][C]54[/C][C]112.06[/C][C]111.232[/C][C]110.14[/C][C]1.09147[/C][C]0.828118[/C][/ROW]
[ROW][C]55[/C][C]112.06[/C][C]110.512[/C][C]110.521[/C][C]-0.00928472[/C][C]1.54803[/C][/ROW]
[ROW][C]56[/C][C]111.18[/C][C]111.137[/C][C]110.902[/C][C]0.234715[/C][C]0.0432014[/C][/ROW]
[ROW][C]57[/C][C]111.18[/C][C]111.378[/C][C]111.283[/C][C]0.0947153[/C][C]-0.197632[/C][/ROW]
[ROW][C]58[/C][C]111.18[/C][C]111.592[/C][C]111.688[/C][C]-0.0955347[/C][C]-0.412382[/C][/ROW]
[ROW][C]59[/C][C]111.18[/C][C]111.781[/C][C]112.117[/C][C]-0.336035[/C][C]-0.601049[/C][/ROW]
[ROW][C]60[/C][C]111.18[/C][C]111.97[/C][C]112.546[/C][C]-0.576535[/C][C]-0.789715[/C][/ROW]
[ROW][C]61[/C][C]111.18[/C][C]112.158[/C][C]112.975[/C][C]-0.817035[/C][C]-0.978382[/C][/ROW]
[ROW][C]62[/C][C]111.18[/C][C]112.067[/C][C]113.057[/C][C]-0.989868[/C][C]-0.886799[/C][/ROW]
[ROW][C]63[/C][C]111.18[/C][C]111.695[/C][C]112.79[/C][C]-1.09503[/C][C]-0.514965[/C][/ROW]
[ROW][C]64[/C][C]117.21[/C][C]113.825[/C][C]112.523[/C][C]1.3018[/C][C]3.38487[/C][/ROW]
[ROW][C]65[/C][C]117.21[/C][C]113.453[/C][C]112.257[/C][C]1.19663[/C][C]3.7567[/C][/ROW]
[ROW][C]66[/C][C]117.21[/C][C]113.081[/C][C]111.99[/C][C]1.09147[/C][C]4.12853[/C][/ROW]
[ROW][C]67[/C][C]117.21[/C][C]NA[/C][C]NA[/C][C]-0.00928472[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]107.98[/C][C]NA[/C][C]NA[/C][C]0.234715[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]107.98[/C][C]NA[/C][C]NA[/C][C]0.0947153[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]107.98[/C][C]NA[/C][C]NA[/C][C]-0.0955347[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]107.98[/C][C]NA[/C][C]NA[/C][C]-0.336035[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]107.98[/C][C]NA[/C][C]NA[/C][C]-0.576535[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=232265&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=232265&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
1102.78NANA-0.817035NA
2102.78NANA-0.989868NA
3102.78NANA-1.09503NA
4102.78NANA1.3018NA
5102.78NANA1.19663NA
6102.78NANA1.09147NA
7102.78102.262102.271-0.009284720.518035
8101.67102.413102.1790.234715-0.743465
9101.67102.181102.0860.0947153-0.510965
10101.67101.898101.994-0.0955347-0.228215
11101.67101.565101.901-0.3360350.104785
12101.67101.232101.809-0.5765350.437785
13101.67100.899101.716-0.8170350.770785
14101.67100.852101.842-0.9898680.818201
15101.67101.09102.185-1.095030.580035
16101.67103.83102.5281.3018-2.16013
17101.67104.068102.8721.19663-2.3983
18101.67104.306103.2151.09147-2.63647
19101.67103.549103.558-0.00928472-1.87905
20105.79104.136103.9020.2347151.65362
21105.79104.34104.2450.09471531.45028
22105.79104.493104.588-0.09553471.2972
23105.79104.596104.932-0.3360351.19437
24105.79104.698105.275-0.5765351.09153
25105.79104.801105.618-0.8170350.988701
26105.79104.745105.735-0.9898681.04487
27105.79104.53105.625-1.095031.26003
28105.79106.817105.5151.3018-1.0268
29105.79106.602105.4051.19663-0.811632
30105.79106.386105.2951.09147-0.596465
31105.79105.176105.185-0.009284720.614285
32104.47105.31105.0750.234715-0.839715
33104.47105.06104.9650.0947153-0.589715
34104.47104.802104.898-0.0955347-0.332382
35104.47104.538104.874-0.336035-0.0677153
36104.47104.273104.85-0.5765350.196951
37104.47104.008104.825-0.8170350.461618
38104.47103.913104.902-0.9898680.557368
39104.47103.986105.081-1.095030.484201
40105.5106.561105.2591.3018-1.06097
41105.5106.634105.4371.19663-1.13413
42105.5106.707105.6161.09147-1.2073
43105.5105.785105.794-0.00928472-0.284882
44106.61106.207105.9730.2347150.402785
45106.61106.246106.1510.09471530.364451
46106.61106.418106.513-0.09553470.192201
47106.61106.724107.06-0.336035-0.113965
48106.61107.03107.607-0.576535-0.420132
49106.61107.336108.153-0.817035-0.726299
50106.61107.627108.617-0.989868-1.01722
51106.61107.903108.998-1.09503-1.29288
52112.06110.681109.3791.30181.37945
53112.06110.956109.761.196631.10378
54112.06111.232110.141.091470.828118
55112.06110.512110.521-0.009284721.54803
56111.18111.137110.9020.2347150.0432014
57111.18111.378111.2830.0947153-0.197632
58111.18111.592111.688-0.0955347-0.412382
59111.18111.781112.117-0.336035-0.601049
60111.18111.97112.546-0.576535-0.789715
61111.18112.158112.975-0.817035-0.978382
62111.18112.067113.057-0.989868-0.886799
63111.18111.695112.79-1.09503-0.514965
64117.21113.825112.5231.30183.38487
65117.21113.453112.2571.196633.7567
66117.21113.081111.991.091474.12853
67117.21NANA-0.00928472NA
68107.98NANA0.234715NA
69107.98NANA0.0947153NA
70107.98NANA-0.0955347NA
71107.98NANA-0.336035NA
72107.98NANA-0.576535NA



Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$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')