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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationThu, 02 Apr 2015 19:00:10 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Apr/02/t142799763159xxyjvadtj55v6.htm/, Retrieved Thu, 09 May 2024 18:00:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=278614, Retrieved Thu, 09 May 2024 18:00:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2015-04-02 18:00:10] [f6ba6fe2e657f2a4c34c9d874eedca96] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,97
103,9
106,85
106,93
107,13
107,07
107,2
107,78
108
108,11
107,26
105,3
105,55
105,38
106,12
106,85
107,92
107,97
107,76
107,99
108,41
107,61
106,54
106,24
106,19
106,71
106,36
107,53
107,89
108
108,05
108,86
109,27
108,87
108,88
108,19
108,19
108,91
110,39
111,21
111,44
111,87
111,88
111,93
111,76
111,66
110,25
109,05
109,47
109,68
110,93
111,86
112,66
112,96
113,14
113,53
113,62
112,51
111
108,49
108,52
110,66
111,15
112,14
113,38
113,75
113,89
113,92
116,4
115,86
115,16
114,45
114,65
114,85
116,51
118,18
118,75
119,06
119,28
119,68
119,28
117,3
114,23
112,56
112,83
112,35
112,8
113,84
115,02
115,46
115
115,3
116,09
115,49
112,89
110,66

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278614&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278614&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278614&T=0

As an alternative you can also use a QR Code:  
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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1101.97NANA-1.86356NA
2103.9NANA-1.50618NA
3106.85NANA-0.781949NA
4106.93NANA0.175967NA
5107.13NANA0.877098NA
6107.07NANA1.09882NA
7107.2107.56106.6070.952158-0.359658
8107.78108.011106.8181.19293-0.231265
9108108.393106.851.54293-0.392515
10108.11107.594106.8160.7778120.516354
11107.26106.307106.845-0.5388540.953438
12105.3104.989106.916-1.927190.311354
13105.55105.113106.977-1.863560.43689
14105.38105.503107.009-1.50618-0.122574
15106.12106.253107.035-0.781949-0.132634
16106.85107.207107.0310.175967-0.356801
17107.92107.857106.980.8770980.0629018
18107.97108.088106.9891.09882-0.117991
19107.76108.007107.0550.952158-0.247158
20107.99108.33107.1371.19293-0.340015
21108.41108.745107.2021.54293-0.335432
22107.61108.019107.2410.777812-0.408646
23106.54106.729107.268-0.538854-0.189063
24106.24105.341107.268-1.927190.899271
25106.19105.418107.281-1.863560.772307
26106.71105.823107.33-1.506180.886592
27106.36106.62107.402-0.781949-0.259717
28107.53107.666107.490.175967-0.135967
29107.89108.517107.640.877098-0.627098
30108108.918107.8191.09882-0.917574
31108.05108.935107.9830.952158-0.885491
32108.86109.351108.1581.19293-0.491265
33109.27109.961108.4181.54293-0.690848
34108.87109.517108.7390.777812-0.646979
35108.88108.502109.04-0.5388540.378438
36108.19107.422109.35-1.927190.767604
37108.19107.807109.67-1.863560.38314
38108.91108.452109.958-1.506180.458259
39110.39109.408110.19-0.7819490.982366
40111.21110.586110.410.1759670.624449
41111.44111.46110.5830.877098-0.0200149
42111.87111.775110.6761.098820.0953423
43111.88111.717110.7650.9521580.162842
44111.93112.043110.851.19293-0.113348
45111.76112.448110.9051.54293-0.687932
46111.66111.732110.9550.777812-0.0723958
47110.25110.494111.032-0.538854-0.243646
48109.05109.202111.129-1.92719-0.151562
49109.47109.363111.227-1.863560.10689
50109.68109.84111.346-1.50618-0.159658
51110.93110.708111.49-0.7819490.221949
52111.86111.779111.6030.1759670.0811161
53112.66112.547111.670.8770980.113318
54112.96112.776111.6781.098820.183676
55113.14112.567111.6150.9521580.573259
56113.53112.809111.6161.192930.721235
57113.62113.209111.6661.542930.411235
58112.51112.464111.6870.7778120.0455208
59111111.189111.728-0.538854-0.189479
60108.49109.864111.791-1.92719-1.37406
61108.52109.992111.855-1.86356-1.47186
62110.66110.397111.903-1.506180.263259
63111.15111.253112.035-0.781949-0.103051
64112.14112.466112.290.175967-0.326384
65113.38113.48112.6030.877098-0.100432
66113.75114.124113.0251.09882-0.373824
67113.89114.481113.5290.952158-0.590908
68113.92115.152113.9591.19293-1.23168
69116.4115.9114.3571.542930.500402
70115.86115.609114.8320.7778120.250521
71115.16114.768115.307-0.5388540.391771
72114.45113.825115.752-1.927190.625104
73114.65114.334116.198-1.863560.31564
74114.85115.156116.663-1.50618-0.306324
75116.51116.241117.022-0.7819490.269449
76118.18117.378117.2020.1759670.801533
77118.75118.101117.2240.8770980.649152
78119.06118.205117.1061.098820.854926
79119.28117.904116.9520.9521581.37618
80119.68117.965116.7721.192931.7154
81119.28118.056116.5131.542931.22415
82117.3116.955116.1770.7778120.344688
83114.23115.302115.841-0.538854-1.0724
84112.56113.609115.536-1.92719-1.04865
85112.83113.344115.207-1.86356-0.513943
86112.35113.34114.847-1.50618-0.990491
87112.8113.749114.531-0.781949-0.949301
88113.84114.499114.3230.175967-0.658884
89115.02115.069114.1920.877098-0.0487649
90115.46115.155114.0571.098820.304509
91115NANA0.952158NA
92115.3NANA1.19293NA
93116.09NANA1.54293NA
94115.49NANA0.777812NA
95112.89NANA-0.538854NA
96110.66NANA-1.92719NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 101.97 & NA & NA & -1.86356 & NA \tabularnewline
2 & 103.9 & NA & NA & -1.50618 & NA \tabularnewline
3 & 106.85 & NA & NA & -0.781949 & NA \tabularnewline
4 & 106.93 & NA & NA & 0.175967 & NA \tabularnewline
5 & 107.13 & NA & NA & 0.877098 & NA \tabularnewline
6 & 107.07 & NA & NA & 1.09882 & NA \tabularnewline
7 & 107.2 & 107.56 & 106.607 & 0.952158 & -0.359658 \tabularnewline
8 & 107.78 & 108.011 & 106.818 & 1.19293 & -0.231265 \tabularnewline
9 & 108 & 108.393 & 106.85 & 1.54293 & -0.392515 \tabularnewline
10 & 108.11 & 107.594 & 106.816 & 0.777812 & 0.516354 \tabularnewline
11 & 107.26 & 106.307 & 106.845 & -0.538854 & 0.953438 \tabularnewline
12 & 105.3 & 104.989 & 106.916 & -1.92719 & 0.311354 \tabularnewline
13 & 105.55 & 105.113 & 106.977 & -1.86356 & 0.43689 \tabularnewline
14 & 105.38 & 105.503 & 107.009 & -1.50618 & -0.122574 \tabularnewline
15 & 106.12 & 106.253 & 107.035 & -0.781949 & -0.132634 \tabularnewline
16 & 106.85 & 107.207 & 107.031 & 0.175967 & -0.356801 \tabularnewline
17 & 107.92 & 107.857 & 106.98 & 0.877098 & 0.0629018 \tabularnewline
18 & 107.97 & 108.088 & 106.989 & 1.09882 & -0.117991 \tabularnewline
19 & 107.76 & 108.007 & 107.055 & 0.952158 & -0.247158 \tabularnewline
20 & 107.99 & 108.33 & 107.137 & 1.19293 & -0.340015 \tabularnewline
21 & 108.41 & 108.745 & 107.202 & 1.54293 & -0.335432 \tabularnewline
22 & 107.61 & 108.019 & 107.241 & 0.777812 & -0.408646 \tabularnewline
23 & 106.54 & 106.729 & 107.268 & -0.538854 & -0.189063 \tabularnewline
24 & 106.24 & 105.341 & 107.268 & -1.92719 & 0.899271 \tabularnewline
25 & 106.19 & 105.418 & 107.281 & -1.86356 & 0.772307 \tabularnewline
26 & 106.71 & 105.823 & 107.33 & -1.50618 & 0.886592 \tabularnewline
27 & 106.36 & 106.62 & 107.402 & -0.781949 & -0.259717 \tabularnewline
28 & 107.53 & 107.666 & 107.49 & 0.175967 & -0.135967 \tabularnewline
29 & 107.89 & 108.517 & 107.64 & 0.877098 & -0.627098 \tabularnewline
30 & 108 & 108.918 & 107.819 & 1.09882 & -0.917574 \tabularnewline
31 & 108.05 & 108.935 & 107.983 & 0.952158 & -0.885491 \tabularnewline
32 & 108.86 & 109.351 & 108.158 & 1.19293 & -0.491265 \tabularnewline
33 & 109.27 & 109.961 & 108.418 & 1.54293 & -0.690848 \tabularnewline
34 & 108.87 & 109.517 & 108.739 & 0.777812 & -0.646979 \tabularnewline
35 & 108.88 & 108.502 & 109.04 & -0.538854 & 0.378438 \tabularnewline
36 & 108.19 & 107.422 & 109.35 & -1.92719 & 0.767604 \tabularnewline
37 & 108.19 & 107.807 & 109.67 & -1.86356 & 0.38314 \tabularnewline
38 & 108.91 & 108.452 & 109.958 & -1.50618 & 0.458259 \tabularnewline
39 & 110.39 & 109.408 & 110.19 & -0.781949 & 0.982366 \tabularnewline
40 & 111.21 & 110.586 & 110.41 & 0.175967 & 0.624449 \tabularnewline
41 & 111.44 & 111.46 & 110.583 & 0.877098 & -0.0200149 \tabularnewline
42 & 111.87 & 111.775 & 110.676 & 1.09882 & 0.0953423 \tabularnewline
43 & 111.88 & 111.717 & 110.765 & 0.952158 & 0.162842 \tabularnewline
44 & 111.93 & 112.043 & 110.85 & 1.19293 & -0.113348 \tabularnewline
45 & 111.76 & 112.448 & 110.905 & 1.54293 & -0.687932 \tabularnewline
46 & 111.66 & 111.732 & 110.955 & 0.777812 & -0.0723958 \tabularnewline
47 & 110.25 & 110.494 & 111.032 & -0.538854 & -0.243646 \tabularnewline
48 & 109.05 & 109.202 & 111.129 & -1.92719 & -0.151562 \tabularnewline
49 & 109.47 & 109.363 & 111.227 & -1.86356 & 0.10689 \tabularnewline
50 & 109.68 & 109.84 & 111.346 & -1.50618 & -0.159658 \tabularnewline
51 & 110.93 & 110.708 & 111.49 & -0.781949 & 0.221949 \tabularnewline
52 & 111.86 & 111.779 & 111.603 & 0.175967 & 0.0811161 \tabularnewline
53 & 112.66 & 112.547 & 111.67 & 0.877098 & 0.113318 \tabularnewline
54 & 112.96 & 112.776 & 111.678 & 1.09882 & 0.183676 \tabularnewline
55 & 113.14 & 112.567 & 111.615 & 0.952158 & 0.573259 \tabularnewline
56 & 113.53 & 112.809 & 111.616 & 1.19293 & 0.721235 \tabularnewline
57 & 113.62 & 113.209 & 111.666 & 1.54293 & 0.411235 \tabularnewline
58 & 112.51 & 112.464 & 111.687 & 0.777812 & 0.0455208 \tabularnewline
59 & 111 & 111.189 & 111.728 & -0.538854 & -0.189479 \tabularnewline
60 & 108.49 & 109.864 & 111.791 & -1.92719 & -1.37406 \tabularnewline
61 & 108.52 & 109.992 & 111.855 & -1.86356 & -1.47186 \tabularnewline
62 & 110.66 & 110.397 & 111.903 & -1.50618 & 0.263259 \tabularnewline
63 & 111.15 & 111.253 & 112.035 & -0.781949 & -0.103051 \tabularnewline
64 & 112.14 & 112.466 & 112.29 & 0.175967 & -0.326384 \tabularnewline
65 & 113.38 & 113.48 & 112.603 & 0.877098 & -0.100432 \tabularnewline
66 & 113.75 & 114.124 & 113.025 & 1.09882 & -0.373824 \tabularnewline
67 & 113.89 & 114.481 & 113.529 & 0.952158 & -0.590908 \tabularnewline
68 & 113.92 & 115.152 & 113.959 & 1.19293 & -1.23168 \tabularnewline
69 & 116.4 & 115.9 & 114.357 & 1.54293 & 0.500402 \tabularnewline
70 & 115.86 & 115.609 & 114.832 & 0.777812 & 0.250521 \tabularnewline
71 & 115.16 & 114.768 & 115.307 & -0.538854 & 0.391771 \tabularnewline
72 & 114.45 & 113.825 & 115.752 & -1.92719 & 0.625104 \tabularnewline
73 & 114.65 & 114.334 & 116.198 & -1.86356 & 0.31564 \tabularnewline
74 & 114.85 & 115.156 & 116.663 & -1.50618 & -0.306324 \tabularnewline
75 & 116.51 & 116.241 & 117.022 & -0.781949 & 0.269449 \tabularnewline
76 & 118.18 & 117.378 & 117.202 & 0.175967 & 0.801533 \tabularnewline
77 & 118.75 & 118.101 & 117.224 & 0.877098 & 0.649152 \tabularnewline
78 & 119.06 & 118.205 & 117.106 & 1.09882 & 0.854926 \tabularnewline
79 & 119.28 & 117.904 & 116.952 & 0.952158 & 1.37618 \tabularnewline
80 & 119.68 & 117.965 & 116.772 & 1.19293 & 1.7154 \tabularnewline
81 & 119.28 & 118.056 & 116.513 & 1.54293 & 1.22415 \tabularnewline
82 & 117.3 & 116.955 & 116.177 & 0.777812 & 0.344688 \tabularnewline
83 & 114.23 & 115.302 & 115.841 & -0.538854 & -1.0724 \tabularnewline
84 & 112.56 & 113.609 & 115.536 & -1.92719 & -1.04865 \tabularnewline
85 & 112.83 & 113.344 & 115.207 & -1.86356 & -0.513943 \tabularnewline
86 & 112.35 & 113.34 & 114.847 & -1.50618 & -0.990491 \tabularnewline
87 & 112.8 & 113.749 & 114.531 & -0.781949 & -0.949301 \tabularnewline
88 & 113.84 & 114.499 & 114.323 & 0.175967 & -0.658884 \tabularnewline
89 & 115.02 & 115.069 & 114.192 & 0.877098 & -0.0487649 \tabularnewline
90 & 115.46 & 115.155 & 114.057 & 1.09882 & 0.304509 \tabularnewline
91 & 115 & NA & NA & 0.952158 & NA \tabularnewline
92 & 115.3 & NA & NA & 1.19293 & NA \tabularnewline
93 & 116.09 & NA & NA & 1.54293 & NA \tabularnewline
94 & 115.49 & NA & NA & 0.777812 & NA \tabularnewline
95 & 112.89 & NA & NA & -0.538854 & NA \tabularnewline
96 & 110.66 & NA & NA & -1.92719 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=278614&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]101.97[/C][C]NA[/C][C]NA[/C][C]-1.86356[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]103.9[/C][C]NA[/C][C]NA[/C][C]-1.50618[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]106.85[/C][C]NA[/C][C]NA[/C][C]-0.781949[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]106.93[/C][C]NA[/C][C]NA[/C][C]0.175967[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]107.13[/C][C]NA[/C][C]NA[/C][C]0.877098[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]107.07[/C][C]NA[/C][C]NA[/C][C]1.09882[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]107.2[/C][C]107.56[/C][C]106.607[/C][C]0.952158[/C][C]-0.359658[/C][/ROW]
[ROW][C]8[/C][C]107.78[/C][C]108.011[/C][C]106.818[/C][C]1.19293[/C][C]-0.231265[/C][/ROW]
[ROW][C]9[/C][C]108[/C][C]108.393[/C][C]106.85[/C][C]1.54293[/C][C]-0.392515[/C][/ROW]
[ROW][C]10[/C][C]108.11[/C][C]107.594[/C][C]106.816[/C][C]0.777812[/C][C]0.516354[/C][/ROW]
[ROW][C]11[/C][C]107.26[/C][C]106.307[/C][C]106.845[/C][C]-0.538854[/C][C]0.953438[/C][/ROW]
[ROW][C]12[/C][C]105.3[/C][C]104.989[/C][C]106.916[/C][C]-1.92719[/C][C]0.311354[/C][/ROW]
[ROW][C]13[/C][C]105.55[/C][C]105.113[/C][C]106.977[/C][C]-1.86356[/C][C]0.43689[/C][/ROW]
[ROW][C]14[/C][C]105.38[/C][C]105.503[/C][C]107.009[/C][C]-1.50618[/C][C]-0.122574[/C][/ROW]
[ROW][C]15[/C][C]106.12[/C][C]106.253[/C][C]107.035[/C][C]-0.781949[/C][C]-0.132634[/C][/ROW]
[ROW][C]16[/C][C]106.85[/C][C]107.207[/C][C]107.031[/C][C]0.175967[/C][C]-0.356801[/C][/ROW]
[ROW][C]17[/C][C]107.92[/C][C]107.857[/C][C]106.98[/C][C]0.877098[/C][C]0.0629018[/C][/ROW]
[ROW][C]18[/C][C]107.97[/C][C]108.088[/C][C]106.989[/C][C]1.09882[/C][C]-0.117991[/C][/ROW]
[ROW][C]19[/C][C]107.76[/C][C]108.007[/C][C]107.055[/C][C]0.952158[/C][C]-0.247158[/C][/ROW]
[ROW][C]20[/C][C]107.99[/C][C]108.33[/C][C]107.137[/C][C]1.19293[/C][C]-0.340015[/C][/ROW]
[ROW][C]21[/C][C]108.41[/C][C]108.745[/C][C]107.202[/C][C]1.54293[/C][C]-0.335432[/C][/ROW]
[ROW][C]22[/C][C]107.61[/C][C]108.019[/C][C]107.241[/C][C]0.777812[/C][C]-0.408646[/C][/ROW]
[ROW][C]23[/C][C]106.54[/C][C]106.729[/C][C]107.268[/C][C]-0.538854[/C][C]-0.189063[/C][/ROW]
[ROW][C]24[/C][C]106.24[/C][C]105.341[/C][C]107.268[/C][C]-1.92719[/C][C]0.899271[/C][/ROW]
[ROW][C]25[/C][C]106.19[/C][C]105.418[/C][C]107.281[/C][C]-1.86356[/C][C]0.772307[/C][/ROW]
[ROW][C]26[/C][C]106.71[/C][C]105.823[/C][C]107.33[/C][C]-1.50618[/C][C]0.886592[/C][/ROW]
[ROW][C]27[/C][C]106.36[/C][C]106.62[/C][C]107.402[/C][C]-0.781949[/C][C]-0.259717[/C][/ROW]
[ROW][C]28[/C][C]107.53[/C][C]107.666[/C][C]107.49[/C][C]0.175967[/C][C]-0.135967[/C][/ROW]
[ROW][C]29[/C][C]107.89[/C][C]108.517[/C][C]107.64[/C][C]0.877098[/C][C]-0.627098[/C][/ROW]
[ROW][C]30[/C][C]108[/C][C]108.918[/C][C]107.819[/C][C]1.09882[/C][C]-0.917574[/C][/ROW]
[ROW][C]31[/C][C]108.05[/C][C]108.935[/C][C]107.983[/C][C]0.952158[/C][C]-0.885491[/C][/ROW]
[ROW][C]32[/C][C]108.86[/C][C]109.351[/C][C]108.158[/C][C]1.19293[/C][C]-0.491265[/C][/ROW]
[ROW][C]33[/C][C]109.27[/C][C]109.961[/C][C]108.418[/C][C]1.54293[/C][C]-0.690848[/C][/ROW]
[ROW][C]34[/C][C]108.87[/C][C]109.517[/C][C]108.739[/C][C]0.777812[/C][C]-0.646979[/C][/ROW]
[ROW][C]35[/C][C]108.88[/C][C]108.502[/C][C]109.04[/C][C]-0.538854[/C][C]0.378438[/C][/ROW]
[ROW][C]36[/C][C]108.19[/C][C]107.422[/C][C]109.35[/C][C]-1.92719[/C][C]0.767604[/C][/ROW]
[ROW][C]37[/C][C]108.19[/C][C]107.807[/C][C]109.67[/C][C]-1.86356[/C][C]0.38314[/C][/ROW]
[ROW][C]38[/C][C]108.91[/C][C]108.452[/C][C]109.958[/C][C]-1.50618[/C][C]0.458259[/C][/ROW]
[ROW][C]39[/C][C]110.39[/C][C]109.408[/C][C]110.19[/C][C]-0.781949[/C][C]0.982366[/C][/ROW]
[ROW][C]40[/C][C]111.21[/C][C]110.586[/C][C]110.41[/C][C]0.175967[/C][C]0.624449[/C][/ROW]
[ROW][C]41[/C][C]111.44[/C][C]111.46[/C][C]110.583[/C][C]0.877098[/C][C]-0.0200149[/C][/ROW]
[ROW][C]42[/C][C]111.87[/C][C]111.775[/C][C]110.676[/C][C]1.09882[/C][C]0.0953423[/C][/ROW]
[ROW][C]43[/C][C]111.88[/C][C]111.717[/C][C]110.765[/C][C]0.952158[/C][C]0.162842[/C][/ROW]
[ROW][C]44[/C][C]111.93[/C][C]112.043[/C][C]110.85[/C][C]1.19293[/C][C]-0.113348[/C][/ROW]
[ROW][C]45[/C][C]111.76[/C][C]112.448[/C][C]110.905[/C][C]1.54293[/C][C]-0.687932[/C][/ROW]
[ROW][C]46[/C][C]111.66[/C][C]111.732[/C][C]110.955[/C][C]0.777812[/C][C]-0.0723958[/C][/ROW]
[ROW][C]47[/C][C]110.25[/C][C]110.494[/C][C]111.032[/C][C]-0.538854[/C][C]-0.243646[/C][/ROW]
[ROW][C]48[/C][C]109.05[/C][C]109.202[/C][C]111.129[/C][C]-1.92719[/C][C]-0.151562[/C][/ROW]
[ROW][C]49[/C][C]109.47[/C][C]109.363[/C][C]111.227[/C][C]-1.86356[/C][C]0.10689[/C][/ROW]
[ROW][C]50[/C][C]109.68[/C][C]109.84[/C][C]111.346[/C][C]-1.50618[/C][C]-0.159658[/C][/ROW]
[ROW][C]51[/C][C]110.93[/C][C]110.708[/C][C]111.49[/C][C]-0.781949[/C][C]0.221949[/C][/ROW]
[ROW][C]52[/C][C]111.86[/C][C]111.779[/C][C]111.603[/C][C]0.175967[/C][C]0.0811161[/C][/ROW]
[ROW][C]53[/C][C]112.66[/C][C]112.547[/C][C]111.67[/C][C]0.877098[/C][C]0.113318[/C][/ROW]
[ROW][C]54[/C][C]112.96[/C][C]112.776[/C][C]111.678[/C][C]1.09882[/C][C]0.183676[/C][/ROW]
[ROW][C]55[/C][C]113.14[/C][C]112.567[/C][C]111.615[/C][C]0.952158[/C][C]0.573259[/C][/ROW]
[ROW][C]56[/C][C]113.53[/C][C]112.809[/C][C]111.616[/C][C]1.19293[/C][C]0.721235[/C][/ROW]
[ROW][C]57[/C][C]113.62[/C][C]113.209[/C][C]111.666[/C][C]1.54293[/C][C]0.411235[/C][/ROW]
[ROW][C]58[/C][C]112.51[/C][C]112.464[/C][C]111.687[/C][C]0.777812[/C][C]0.0455208[/C][/ROW]
[ROW][C]59[/C][C]111[/C][C]111.189[/C][C]111.728[/C][C]-0.538854[/C][C]-0.189479[/C][/ROW]
[ROW][C]60[/C][C]108.49[/C][C]109.864[/C][C]111.791[/C][C]-1.92719[/C][C]-1.37406[/C][/ROW]
[ROW][C]61[/C][C]108.52[/C][C]109.992[/C][C]111.855[/C][C]-1.86356[/C][C]-1.47186[/C][/ROW]
[ROW][C]62[/C][C]110.66[/C][C]110.397[/C][C]111.903[/C][C]-1.50618[/C][C]0.263259[/C][/ROW]
[ROW][C]63[/C][C]111.15[/C][C]111.253[/C][C]112.035[/C][C]-0.781949[/C][C]-0.103051[/C][/ROW]
[ROW][C]64[/C][C]112.14[/C][C]112.466[/C][C]112.29[/C][C]0.175967[/C][C]-0.326384[/C][/ROW]
[ROW][C]65[/C][C]113.38[/C][C]113.48[/C][C]112.603[/C][C]0.877098[/C][C]-0.100432[/C][/ROW]
[ROW][C]66[/C][C]113.75[/C][C]114.124[/C][C]113.025[/C][C]1.09882[/C][C]-0.373824[/C][/ROW]
[ROW][C]67[/C][C]113.89[/C][C]114.481[/C][C]113.529[/C][C]0.952158[/C][C]-0.590908[/C][/ROW]
[ROW][C]68[/C][C]113.92[/C][C]115.152[/C][C]113.959[/C][C]1.19293[/C][C]-1.23168[/C][/ROW]
[ROW][C]69[/C][C]116.4[/C][C]115.9[/C][C]114.357[/C][C]1.54293[/C][C]0.500402[/C][/ROW]
[ROW][C]70[/C][C]115.86[/C][C]115.609[/C][C]114.832[/C][C]0.777812[/C][C]0.250521[/C][/ROW]
[ROW][C]71[/C][C]115.16[/C][C]114.768[/C][C]115.307[/C][C]-0.538854[/C][C]0.391771[/C][/ROW]
[ROW][C]72[/C][C]114.45[/C][C]113.825[/C][C]115.752[/C][C]-1.92719[/C][C]0.625104[/C][/ROW]
[ROW][C]73[/C][C]114.65[/C][C]114.334[/C][C]116.198[/C][C]-1.86356[/C][C]0.31564[/C][/ROW]
[ROW][C]74[/C][C]114.85[/C][C]115.156[/C][C]116.663[/C][C]-1.50618[/C][C]-0.306324[/C][/ROW]
[ROW][C]75[/C][C]116.51[/C][C]116.241[/C][C]117.022[/C][C]-0.781949[/C][C]0.269449[/C][/ROW]
[ROW][C]76[/C][C]118.18[/C][C]117.378[/C][C]117.202[/C][C]0.175967[/C][C]0.801533[/C][/ROW]
[ROW][C]77[/C][C]118.75[/C][C]118.101[/C][C]117.224[/C][C]0.877098[/C][C]0.649152[/C][/ROW]
[ROW][C]78[/C][C]119.06[/C][C]118.205[/C][C]117.106[/C][C]1.09882[/C][C]0.854926[/C][/ROW]
[ROW][C]79[/C][C]119.28[/C][C]117.904[/C][C]116.952[/C][C]0.952158[/C][C]1.37618[/C][/ROW]
[ROW][C]80[/C][C]119.68[/C][C]117.965[/C][C]116.772[/C][C]1.19293[/C][C]1.7154[/C][/ROW]
[ROW][C]81[/C][C]119.28[/C][C]118.056[/C][C]116.513[/C][C]1.54293[/C][C]1.22415[/C][/ROW]
[ROW][C]82[/C][C]117.3[/C][C]116.955[/C][C]116.177[/C][C]0.777812[/C][C]0.344688[/C][/ROW]
[ROW][C]83[/C][C]114.23[/C][C]115.302[/C][C]115.841[/C][C]-0.538854[/C][C]-1.0724[/C][/ROW]
[ROW][C]84[/C][C]112.56[/C][C]113.609[/C][C]115.536[/C][C]-1.92719[/C][C]-1.04865[/C][/ROW]
[ROW][C]85[/C][C]112.83[/C][C]113.344[/C][C]115.207[/C][C]-1.86356[/C][C]-0.513943[/C][/ROW]
[ROW][C]86[/C][C]112.35[/C][C]113.34[/C][C]114.847[/C][C]-1.50618[/C][C]-0.990491[/C][/ROW]
[ROW][C]87[/C][C]112.8[/C][C]113.749[/C][C]114.531[/C][C]-0.781949[/C][C]-0.949301[/C][/ROW]
[ROW][C]88[/C][C]113.84[/C][C]114.499[/C][C]114.323[/C][C]0.175967[/C][C]-0.658884[/C][/ROW]
[ROW][C]89[/C][C]115.02[/C][C]115.069[/C][C]114.192[/C][C]0.877098[/C][C]-0.0487649[/C][/ROW]
[ROW][C]90[/C][C]115.46[/C][C]115.155[/C][C]114.057[/C][C]1.09882[/C][C]0.304509[/C][/ROW]
[ROW][C]91[/C][C]115[/C][C]NA[/C][C]NA[/C][C]0.952158[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]115.3[/C][C]NA[/C][C]NA[/C][C]1.19293[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]116.09[/C][C]NA[/C][C]NA[/C][C]1.54293[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]115.49[/C][C]NA[/C][C]NA[/C][C]0.777812[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]112.89[/C][C]NA[/C][C]NA[/C][C]-0.538854[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]110.66[/C][C]NA[/C][C]NA[/C][C]-1.92719[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=278614&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=278614&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1101.97NANA-1.86356NA
2103.9NANA-1.50618NA
3106.85NANA-0.781949NA
4106.93NANA0.175967NA
5107.13NANA0.877098NA
6107.07NANA1.09882NA
7107.2107.56106.6070.952158-0.359658
8107.78108.011106.8181.19293-0.231265
9108108.393106.851.54293-0.392515
10108.11107.594106.8160.7778120.516354
11107.26106.307106.845-0.5388540.953438
12105.3104.989106.916-1.927190.311354
13105.55105.113106.977-1.863560.43689
14105.38105.503107.009-1.50618-0.122574
15106.12106.253107.035-0.781949-0.132634
16106.85107.207107.0310.175967-0.356801
17107.92107.857106.980.8770980.0629018
18107.97108.088106.9891.09882-0.117991
19107.76108.007107.0550.952158-0.247158
20107.99108.33107.1371.19293-0.340015
21108.41108.745107.2021.54293-0.335432
22107.61108.019107.2410.777812-0.408646
23106.54106.729107.268-0.538854-0.189063
24106.24105.341107.268-1.927190.899271
25106.19105.418107.281-1.863560.772307
26106.71105.823107.33-1.506180.886592
27106.36106.62107.402-0.781949-0.259717
28107.53107.666107.490.175967-0.135967
29107.89108.517107.640.877098-0.627098
30108108.918107.8191.09882-0.917574
31108.05108.935107.9830.952158-0.885491
32108.86109.351108.1581.19293-0.491265
33109.27109.961108.4181.54293-0.690848
34108.87109.517108.7390.777812-0.646979
35108.88108.502109.04-0.5388540.378438
36108.19107.422109.35-1.927190.767604
37108.19107.807109.67-1.863560.38314
38108.91108.452109.958-1.506180.458259
39110.39109.408110.19-0.7819490.982366
40111.21110.586110.410.1759670.624449
41111.44111.46110.5830.877098-0.0200149
42111.87111.775110.6761.098820.0953423
43111.88111.717110.7650.9521580.162842
44111.93112.043110.851.19293-0.113348
45111.76112.448110.9051.54293-0.687932
46111.66111.732110.9550.777812-0.0723958
47110.25110.494111.032-0.538854-0.243646
48109.05109.202111.129-1.92719-0.151562
49109.47109.363111.227-1.863560.10689
50109.68109.84111.346-1.50618-0.159658
51110.93110.708111.49-0.7819490.221949
52111.86111.779111.6030.1759670.0811161
53112.66112.547111.670.8770980.113318
54112.96112.776111.6781.098820.183676
55113.14112.567111.6150.9521580.573259
56113.53112.809111.6161.192930.721235
57113.62113.209111.6661.542930.411235
58112.51112.464111.6870.7778120.0455208
59111111.189111.728-0.538854-0.189479
60108.49109.864111.791-1.92719-1.37406
61108.52109.992111.855-1.86356-1.47186
62110.66110.397111.903-1.506180.263259
63111.15111.253112.035-0.781949-0.103051
64112.14112.466112.290.175967-0.326384
65113.38113.48112.6030.877098-0.100432
66113.75114.124113.0251.09882-0.373824
67113.89114.481113.5290.952158-0.590908
68113.92115.152113.9591.19293-1.23168
69116.4115.9114.3571.542930.500402
70115.86115.609114.8320.7778120.250521
71115.16114.768115.307-0.5388540.391771
72114.45113.825115.752-1.927190.625104
73114.65114.334116.198-1.863560.31564
74114.85115.156116.663-1.50618-0.306324
75116.51116.241117.022-0.7819490.269449
76118.18117.378117.2020.1759670.801533
77118.75118.101117.2240.8770980.649152
78119.06118.205117.1061.098820.854926
79119.28117.904116.9520.9521581.37618
80119.68117.965116.7721.192931.7154
81119.28118.056116.5131.542931.22415
82117.3116.955116.1770.7778120.344688
83114.23115.302115.841-0.538854-1.0724
84112.56113.609115.536-1.92719-1.04865
85112.83113.344115.207-1.86356-0.513943
86112.35113.34114.847-1.50618-0.990491
87112.8113.749114.531-0.781949-0.949301
88113.84114.499114.3230.175967-0.658884
89115.02115.069114.1920.877098-0.0487649
90115.46115.155114.0571.098820.304509
91115NANA0.952158NA
92115.3NANA1.19293NA
93116.09NANA1.54293NA
94115.49NANA0.777812NA
95112.89NANA-0.538854NA
96110.66NANA-1.92719NA


Figures (Output of Computation)

Input Parameters & R Code

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')