FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 26 May 2015 06:31:55 +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/May/26/t1432618355r6zhy32a79sieo3.htm/, Retrieved Tue, 30 Apr 2024 10:19:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279377, Retrieved Tue, 30 Apr 2024 10:19:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [model] [2015-05-26 05:31:55] [b43493158838656c32486372ca9c54cf] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,8
100,66
101,44
102,17
102,75
104,28
104,96
105,16
105,29
105,15
105,23
104,45
104,6
105,1
105,94
106,2
106,89
107,57
107,42
107,2
107,08
107,17
107,23
106,61
106,97
108,23
109,8
111,93
113,51
115,27
115,58
115,55
115,44
114,93
115,09
113,78
114,51
114,85
116,12
115,47
115,93
116,6
116,98
117,37
117,48
117,18
117,03
114,95
115,64
116,02
116,07
114,5
114,36
116
116,16
116,42
116,78
115,74
115,44
113,52
113,37
114,35
114,11
113,47
114,33
115,76
116,2
116,48
116,53
116,45
116,23
114,46
115,08
115,57
116,17
115,21
114,97
114,24
114,16
117,2
117,71
117,14
116,67
114,71
115,92
117,74
118,38
118,59
119,66
121,2
121,4
122,66
122,95
122,9
123,29
122,02

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'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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279377&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279377&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279377&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'Gwilym Jenkins' @ jenkins.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1100.8NANA0.98913NA
2100.66NANA0.994587NA
3101.44NANA0.998756NA
4102.17NANA0.995523NA
5102.75NANA0.999041NA
6104.28NANA1.00588NA
7104.96104.376103.6871.006651.00559
8105.16105.042104.031.009731.00112
9105.29105.345104.4021.009030.999479
10105.15105.182104.7581.004050.999695
11105.23105.228105.0981.001231.00002
12104.45103.975105.4080.9864011.00457
13104.6104.499105.6480.989131.00097
14105.1105.262105.8350.9945870.99846
15105.94105.863105.9950.9987561.00073
16106.2105.678106.1530.9955231.00494
17106.89106.219106.3210.9990411.00632
18107.57107.12106.4941.005881.0042
19107.42107.392106.6831.006651.00026
20107.2107.952106.9121.009730.993033
21107.08108.171107.2031.009030.989914
22107.17108.039107.6031.004050.99196
23107.23108.25108.1181.001230.990573
24106.61107.236108.7140.9864010.994164
25106.97108.186109.3750.989130.988759
26108.23109.467110.0630.9945870.988699
27109.8110.621110.7590.9987560.992575
28111.93110.932111.4310.9955231.009
29113.51111.974112.0820.9990411.01372
30115.27113.371112.7081.005881.01675
31115.58114.074113.3211.006651.0132
32115.55115.019113.9111.009731.00462
33115.44115.483114.451.009030.999627
34114.93115.326114.8611.004050.996567
35115.09115.251115.1091.001230.998606
36113.78113.698115.2650.9864011.00072
37114.51114.125115.3790.989131.00337
38114.85114.888115.5130.9945870.999669
39116.12115.53115.6740.9987561.0051
40115.47115.334115.8530.9955231.00118
41115.93115.916116.0270.9990411.00012
42116.6116.84116.1571.005880.997944
43116.98117.026116.2531.006650.999608
44117.37117.481116.3491.009730.999059
45117.48117.446116.3951.009031.00029
46117.18116.824116.3531.004051.00305
47117.03116.39116.2471.001231.0055
48114.95114.577116.1570.9864011.00325
49115.64114.836116.0980.989131.00701
50116.02115.396116.0240.9945871.00541
51116.07115.811115.9550.9987561.00224
52114.5115.347115.8660.9955230.992656
53114.36115.629115.740.9990410.989029
54116116.294115.6141.005880.997475
55116.16116.227115.461.006650.999422
56116.42116.417115.2951.009731.00003
57116.78116.183115.1441.009031.00513
58115.74115.485115.021.004051.00221
59115.44115.117114.9751.001231.00281
60113.52113.401114.9640.9864011.00105
61113.37113.706114.9560.989130.997043
62114.35114.338114.960.9945871.00011
63114.11114.809114.9520.9987560.993911
64113.47114.457114.9710.9955230.991381
65114.33114.923115.0340.9990410.994837
66115.76115.783115.1061.005880.999803
67116.2115.982115.2161.006651.00188
68116.48116.46115.3381.009731.00017
69116.53116.517115.4751.009031.00011
70116.45116.102115.6331.004051.003
71116.23115.875115.7321.001231.00307
72114.46114.123115.6960.9864011.00296
73115.08114.291115.5480.989131.0069
74115.57114.867115.4920.9945871.00612
75116.17115.428115.5720.9987561.00643
76115.21115.132115.650.9955231.00068
77114.97115.586115.6970.9990410.994673
78114.24116.406115.7251.005880.981393
79114.16116.541115.7711.006650.979573
80117.2117.024115.8961.009731.00151
81117.71117.127116.0791.009031.00498
82117.14116.783116.3121.004051.00306
83116.67116.791116.6481.001230.998961
84114.71115.54117.1330.9864010.992812
85115.92116.445117.7250.989130.995489
86117.74117.614118.2540.9945871.00107
87118.38118.552118.70.9987560.998546
88118.59118.625119.1580.9955230.999706
89119.66119.559119.6740.9990411.00084
90121.2120.962120.2551.005881.00197
91121.4NANA1.00665NA
92122.66NANA1.00973NA
93122.95NANA1.00903NA
94122.9NANA1.00405NA
95123.29NANA1.00123NA
96122.02NANA0.986401NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 100.8 & NA & NA & 0.98913 & NA \tabularnewline
2 & 100.66 & NA & NA & 0.994587 & NA \tabularnewline
3 & 101.44 & NA & NA & 0.998756 & NA \tabularnewline
4 & 102.17 & NA & NA & 0.995523 & NA \tabularnewline
5 & 102.75 & NA & NA & 0.999041 & NA \tabularnewline
6 & 104.28 & NA & NA & 1.00588 & NA \tabularnewline
7 & 104.96 & 104.376 & 103.687 & 1.00665 & 1.00559 \tabularnewline
8 & 105.16 & 105.042 & 104.03 & 1.00973 & 1.00112 \tabularnewline
9 & 105.29 & 105.345 & 104.402 & 1.00903 & 0.999479 \tabularnewline
10 & 105.15 & 105.182 & 104.758 & 1.00405 & 0.999695 \tabularnewline
11 & 105.23 & 105.228 & 105.098 & 1.00123 & 1.00002 \tabularnewline
12 & 104.45 & 103.975 & 105.408 & 0.986401 & 1.00457 \tabularnewline
13 & 104.6 & 104.499 & 105.648 & 0.98913 & 1.00097 \tabularnewline
14 & 105.1 & 105.262 & 105.835 & 0.994587 & 0.99846 \tabularnewline
15 & 105.94 & 105.863 & 105.995 & 0.998756 & 1.00073 \tabularnewline
16 & 106.2 & 105.678 & 106.153 & 0.995523 & 1.00494 \tabularnewline
17 & 106.89 & 106.219 & 106.321 & 0.999041 & 1.00632 \tabularnewline
18 & 107.57 & 107.12 & 106.494 & 1.00588 & 1.0042 \tabularnewline
19 & 107.42 & 107.392 & 106.683 & 1.00665 & 1.00026 \tabularnewline
20 & 107.2 & 107.952 & 106.912 & 1.00973 & 0.993033 \tabularnewline
21 & 107.08 & 108.171 & 107.203 & 1.00903 & 0.989914 \tabularnewline
22 & 107.17 & 108.039 & 107.603 & 1.00405 & 0.99196 \tabularnewline
23 & 107.23 & 108.25 & 108.118 & 1.00123 & 0.990573 \tabularnewline
24 & 106.61 & 107.236 & 108.714 & 0.986401 & 0.994164 \tabularnewline
25 & 106.97 & 108.186 & 109.375 & 0.98913 & 0.988759 \tabularnewline
26 & 108.23 & 109.467 & 110.063 & 0.994587 & 0.988699 \tabularnewline
27 & 109.8 & 110.621 & 110.759 & 0.998756 & 0.992575 \tabularnewline
28 & 111.93 & 110.932 & 111.431 & 0.995523 & 1.009 \tabularnewline
29 & 113.51 & 111.974 & 112.082 & 0.999041 & 1.01372 \tabularnewline
30 & 115.27 & 113.371 & 112.708 & 1.00588 & 1.01675 \tabularnewline
31 & 115.58 & 114.074 & 113.321 & 1.00665 & 1.0132 \tabularnewline
32 & 115.55 & 115.019 & 113.911 & 1.00973 & 1.00462 \tabularnewline
33 & 115.44 & 115.483 & 114.45 & 1.00903 & 0.999627 \tabularnewline
34 & 114.93 & 115.326 & 114.861 & 1.00405 & 0.996567 \tabularnewline
35 & 115.09 & 115.251 & 115.109 & 1.00123 & 0.998606 \tabularnewline
36 & 113.78 & 113.698 & 115.265 & 0.986401 & 1.00072 \tabularnewline
37 & 114.51 & 114.125 & 115.379 & 0.98913 & 1.00337 \tabularnewline
38 & 114.85 & 114.888 & 115.513 & 0.994587 & 0.999669 \tabularnewline
39 & 116.12 & 115.53 & 115.674 & 0.998756 & 1.0051 \tabularnewline
40 & 115.47 & 115.334 & 115.853 & 0.995523 & 1.00118 \tabularnewline
41 & 115.93 & 115.916 & 116.027 & 0.999041 & 1.00012 \tabularnewline
42 & 116.6 & 116.84 & 116.157 & 1.00588 & 0.997944 \tabularnewline
43 & 116.98 & 117.026 & 116.253 & 1.00665 & 0.999608 \tabularnewline
44 & 117.37 & 117.481 & 116.349 & 1.00973 & 0.999059 \tabularnewline
45 & 117.48 & 117.446 & 116.395 & 1.00903 & 1.00029 \tabularnewline
46 & 117.18 & 116.824 & 116.353 & 1.00405 & 1.00305 \tabularnewline
47 & 117.03 & 116.39 & 116.247 & 1.00123 & 1.0055 \tabularnewline
48 & 114.95 & 114.577 & 116.157 & 0.986401 & 1.00325 \tabularnewline
49 & 115.64 & 114.836 & 116.098 & 0.98913 & 1.00701 \tabularnewline
50 & 116.02 & 115.396 & 116.024 & 0.994587 & 1.00541 \tabularnewline
51 & 116.07 & 115.811 & 115.955 & 0.998756 & 1.00224 \tabularnewline
52 & 114.5 & 115.347 & 115.866 & 0.995523 & 0.992656 \tabularnewline
53 & 114.36 & 115.629 & 115.74 & 0.999041 & 0.989029 \tabularnewline
54 & 116 & 116.294 & 115.614 & 1.00588 & 0.997475 \tabularnewline
55 & 116.16 & 116.227 & 115.46 & 1.00665 & 0.999422 \tabularnewline
56 & 116.42 & 116.417 & 115.295 & 1.00973 & 1.00003 \tabularnewline
57 & 116.78 & 116.183 & 115.144 & 1.00903 & 1.00513 \tabularnewline
58 & 115.74 & 115.485 & 115.02 & 1.00405 & 1.00221 \tabularnewline
59 & 115.44 & 115.117 & 114.975 & 1.00123 & 1.00281 \tabularnewline
60 & 113.52 & 113.401 & 114.964 & 0.986401 & 1.00105 \tabularnewline
61 & 113.37 & 113.706 & 114.956 & 0.98913 & 0.997043 \tabularnewline
62 & 114.35 & 114.338 & 114.96 & 0.994587 & 1.00011 \tabularnewline
63 & 114.11 & 114.809 & 114.952 & 0.998756 & 0.993911 \tabularnewline
64 & 113.47 & 114.457 & 114.971 & 0.995523 & 0.991381 \tabularnewline
65 & 114.33 & 114.923 & 115.034 & 0.999041 & 0.994837 \tabularnewline
66 & 115.76 & 115.783 & 115.106 & 1.00588 & 0.999803 \tabularnewline
67 & 116.2 & 115.982 & 115.216 & 1.00665 & 1.00188 \tabularnewline
68 & 116.48 & 116.46 & 115.338 & 1.00973 & 1.00017 \tabularnewline
69 & 116.53 & 116.517 & 115.475 & 1.00903 & 1.00011 \tabularnewline
70 & 116.45 & 116.102 & 115.633 & 1.00405 & 1.003 \tabularnewline
71 & 116.23 & 115.875 & 115.732 & 1.00123 & 1.00307 \tabularnewline
72 & 114.46 & 114.123 & 115.696 & 0.986401 & 1.00296 \tabularnewline
73 & 115.08 & 114.291 & 115.548 & 0.98913 & 1.0069 \tabularnewline
74 & 115.57 & 114.867 & 115.492 & 0.994587 & 1.00612 \tabularnewline
75 & 116.17 & 115.428 & 115.572 & 0.998756 & 1.00643 \tabularnewline
76 & 115.21 & 115.132 & 115.65 & 0.995523 & 1.00068 \tabularnewline
77 & 114.97 & 115.586 & 115.697 & 0.999041 & 0.994673 \tabularnewline
78 & 114.24 & 116.406 & 115.725 & 1.00588 & 0.981393 \tabularnewline
79 & 114.16 & 116.541 & 115.771 & 1.00665 & 0.979573 \tabularnewline
80 & 117.2 & 117.024 & 115.896 & 1.00973 & 1.00151 \tabularnewline
81 & 117.71 & 117.127 & 116.079 & 1.00903 & 1.00498 \tabularnewline
82 & 117.14 & 116.783 & 116.312 & 1.00405 & 1.00306 \tabularnewline
83 & 116.67 & 116.791 & 116.648 & 1.00123 & 0.998961 \tabularnewline
84 & 114.71 & 115.54 & 117.133 & 0.986401 & 0.992812 \tabularnewline
85 & 115.92 & 116.445 & 117.725 & 0.98913 & 0.995489 \tabularnewline
86 & 117.74 & 117.614 & 118.254 & 0.994587 & 1.00107 \tabularnewline
87 & 118.38 & 118.552 & 118.7 & 0.998756 & 0.998546 \tabularnewline
88 & 118.59 & 118.625 & 119.158 & 0.995523 & 0.999706 \tabularnewline
89 & 119.66 & 119.559 & 119.674 & 0.999041 & 1.00084 \tabularnewline
90 & 121.2 & 120.962 & 120.255 & 1.00588 & 1.00197 \tabularnewline
91 & 121.4 & NA & NA & 1.00665 & NA \tabularnewline
92 & 122.66 & NA & NA & 1.00973 & NA \tabularnewline
93 & 122.95 & NA & NA & 1.00903 & NA \tabularnewline
94 & 122.9 & NA & NA & 1.00405 & NA \tabularnewline
95 & 123.29 & NA & NA & 1.00123 & NA \tabularnewline
96 & 122.02 & NA & NA & 0.986401 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279377&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]100.8[/C][C]NA[/C][C]NA[/C][C]0.98913[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]100.66[/C][C]NA[/C][C]NA[/C][C]0.994587[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]101.44[/C][C]NA[/C][C]NA[/C][C]0.998756[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]102.17[/C][C]NA[/C][C]NA[/C][C]0.995523[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]102.75[/C][C]NA[/C][C]NA[/C][C]0.999041[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]104.28[/C][C]NA[/C][C]NA[/C][C]1.00588[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]104.96[/C][C]104.376[/C][C]103.687[/C][C]1.00665[/C][C]1.00559[/C][/ROW]
[ROW][C]8[/C][C]105.16[/C][C]105.042[/C][C]104.03[/C][C]1.00973[/C][C]1.00112[/C][/ROW]
[ROW][C]9[/C][C]105.29[/C][C]105.345[/C][C]104.402[/C][C]1.00903[/C][C]0.999479[/C][/ROW]
[ROW][C]10[/C][C]105.15[/C][C]105.182[/C][C]104.758[/C][C]1.00405[/C][C]0.999695[/C][/ROW]
[ROW][C]11[/C][C]105.23[/C][C]105.228[/C][C]105.098[/C][C]1.00123[/C][C]1.00002[/C][/ROW]
[ROW][C]12[/C][C]104.45[/C][C]103.975[/C][C]105.408[/C][C]0.986401[/C][C]1.00457[/C][/ROW]
[ROW][C]13[/C][C]104.6[/C][C]104.499[/C][C]105.648[/C][C]0.98913[/C][C]1.00097[/C][/ROW]
[ROW][C]14[/C][C]105.1[/C][C]105.262[/C][C]105.835[/C][C]0.994587[/C][C]0.99846[/C][/ROW]
[ROW][C]15[/C][C]105.94[/C][C]105.863[/C][C]105.995[/C][C]0.998756[/C][C]1.00073[/C][/ROW]
[ROW][C]16[/C][C]106.2[/C][C]105.678[/C][C]106.153[/C][C]0.995523[/C][C]1.00494[/C][/ROW]
[ROW][C]17[/C][C]106.89[/C][C]106.219[/C][C]106.321[/C][C]0.999041[/C][C]1.00632[/C][/ROW]
[ROW][C]18[/C][C]107.57[/C][C]107.12[/C][C]106.494[/C][C]1.00588[/C][C]1.0042[/C][/ROW]
[ROW][C]19[/C][C]107.42[/C][C]107.392[/C][C]106.683[/C][C]1.00665[/C][C]1.00026[/C][/ROW]
[ROW][C]20[/C][C]107.2[/C][C]107.952[/C][C]106.912[/C][C]1.00973[/C][C]0.993033[/C][/ROW]
[ROW][C]21[/C][C]107.08[/C][C]108.171[/C][C]107.203[/C][C]1.00903[/C][C]0.989914[/C][/ROW]
[ROW][C]22[/C][C]107.17[/C][C]108.039[/C][C]107.603[/C][C]1.00405[/C][C]0.99196[/C][/ROW]
[ROW][C]23[/C][C]107.23[/C][C]108.25[/C][C]108.118[/C][C]1.00123[/C][C]0.990573[/C][/ROW]
[ROW][C]24[/C][C]106.61[/C][C]107.236[/C][C]108.714[/C][C]0.986401[/C][C]0.994164[/C][/ROW]
[ROW][C]25[/C][C]106.97[/C][C]108.186[/C][C]109.375[/C][C]0.98913[/C][C]0.988759[/C][/ROW]
[ROW][C]26[/C][C]108.23[/C][C]109.467[/C][C]110.063[/C][C]0.994587[/C][C]0.988699[/C][/ROW]
[ROW][C]27[/C][C]109.8[/C][C]110.621[/C][C]110.759[/C][C]0.998756[/C][C]0.992575[/C][/ROW]
[ROW][C]28[/C][C]111.93[/C][C]110.932[/C][C]111.431[/C][C]0.995523[/C][C]1.009[/C][/ROW]
[ROW][C]29[/C][C]113.51[/C][C]111.974[/C][C]112.082[/C][C]0.999041[/C][C]1.01372[/C][/ROW]
[ROW][C]30[/C][C]115.27[/C][C]113.371[/C][C]112.708[/C][C]1.00588[/C][C]1.01675[/C][/ROW]
[ROW][C]31[/C][C]115.58[/C][C]114.074[/C][C]113.321[/C][C]1.00665[/C][C]1.0132[/C][/ROW]
[ROW][C]32[/C][C]115.55[/C][C]115.019[/C][C]113.911[/C][C]1.00973[/C][C]1.00462[/C][/ROW]
[ROW][C]33[/C][C]115.44[/C][C]115.483[/C][C]114.45[/C][C]1.00903[/C][C]0.999627[/C][/ROW]
[ROW][C]34[/C][C]114.93[/C][C]115.326[/C][C]114.861[/C][C]1.00405[/C][C]0.996567[/C][/ROW]
[ROW][C]35[/C][C]115.09[/C][C]115.251[/C][C]115.109[/C][C]1.00123[/C][C]0.998606[/C][/ROW]
[ROW][C]36[/C][C]113.78[/C][C]113.698[/C][C]115.265[/C][C]0.986401[/C][C]1.00072[/C][/ROW]
[ROW][C]37[/C][C]114.51[/C][C]114.125[/C][C]115.379[/C][C]0.98913[/C][C]1.00337[/C][/ROW]
[ROW][C]38[/C][C]114.85[/C][C]114.888[/C][C]115.513[/C][C]0.994587[/C][C]0.999669[/C][/ROW]
[ROW][C]39[/C][C]116.12[/C][C]115.53[/C][C]115.674[/C][C]0.998756[/C][C]1.0051[/C][/ROW]
[ROW][C]40[/C][C]115.47[/C][C]115.334[/C][C]115.853[/C][C]0.995523[/C][C]1.00118[/C][/ROW]
[ROW][C]41[/C][C]115.93[/C][C]115.916[/C][C]116.027[/C][C]0.999041[/C][C]1.00012[/C][/ROW]
[ROW][C]42[/C][C]116.6[/C][C]116.84[/C][C]116.157[/C][C]1.00588[/C][C]0.997944[/C][/ROW]
[ROW][C]43[/C][C]116.98[/C][C]117.026[/C][C]116.253[/C][C]1.00665[/C][C]0.999608[/C][/ROW]
[ROW][C]44[/C][C]117.37[/C][C]117.481[/C][C]116.349[/C][C]1.00973[/C][C]0.999059[/C][/ROW]
[ROW][C]45[/C][C]117.48[/C][C]117.446[/C][C]116.395[/C][C]1.00903[/C][C]1.00029[/C][/ROW]
[ROW][C]46[/C][C]117.18[/C][C]116.824[/C][C]116.353[/C][C]1.00405[/C][C]1.00305[/C][/ROW]
[ROW][C]47[/C][C]117.03[/C][C]116.39[/C][C]116.247[/C][C]1.00123[/C][C]1.0055[/C][/ROW]
[ROW][C]48[/C][C]114.95[/C][C]114.577[/C][C]116.157[/C][C]0.986401[/C][C]1.00325[/C][/ROW]
[ROW][C]49[/C][C]115.64[/C][C]114.836[/C][C]116.098[/C][C]0.98913[/C][C]1.00701[/C][/ROW]
[ROW][C]50[/C][C]116.02[/C][C]115.396[/C][C]116.024[/C][C]0.994587[/C][C]1.00541[/C][/ROW]
[ROW][C]51[/C][C]116.07[/C][C]115.811[/C][C]115.955[/C][C]0.998756[/C][C]1.00224[/C][/ROW]
[ROW][C]52[/C][C]114.5[/C][C]115.347[/C][C]115.866[/C][C]0.995523[/C][C]0.992656[/C][/ROW]
[ROW][C]53[/C][C]114.36[/C][C]115.629[/C][C]115.74[/C][C]0.999041[/C][C]0.989029[/C][/ROW]
[ROW][C]54[/C][C]116[/C][C]116.294[/C][C]115.614[/C][C]1.00588[/C][C]0.997475[/C][/ROW]
[ROW][C]55[/C][C]116.16[/C][C]116.227[/C][C]115.46[/C][C]1.00665[/C][C]0.999422[/C][/ROW]
[ROW][C]56[/C][C]116.42[/C][C]116.417[/C][C]115.295[/C][C]1.00973[/C][C]1.00003[/C][/ROW]
[ROW][C]57[/C][C]116.78[/C][C]116.183[/C][C]115.144[/C][C]1.00903[/C][C]1.00513[/C][/ROW]
[ROW][C]58[/C][C]115.74[/C][C]115.485[/C][C]115.02[/C][C]1.00405[/C][C]1.00221[/C][/ROW]
[ROW][C]59[/C][C]115.44[/C][C]115.117[/C][C]114.975[/C][C]1.00123[/C][C]1.00281[/C][/ROW]
[ROW][C]60[/C][C]113.52[/C][C]113.401[/C][C]114.964[/C][C]0.986401[/C][C]1.00105[/C][/ROW]
[ROW][C]61[/C][C]113.37[/C][C]113.706[/C][C]114.956[/C][C]0.98913[/C][C]0.997043[/C][/ROW]
[ROW][C]62[/C][C]114.35[/C][C]114.338[/C][C]114.96[/C][C]0.994587[/C][C]1.00011[/C][/ROW]
[ROW][C]63[/C][C]114.11[/C][C]114.809[/C][C]114.952[/C][C]0.998756[/C][C]0.993911[/C][/ROW]
[ROW][C]64[/C][C]113.47[/C][C]114.457[/C][C]114.971[/C][C]0.995523[/C][C]0.991381[/C][/ROW]
[ROW][C]65[/C][C]114.33[/C][C]114.923[/C][C]115.034[/C][C]0.999041[/C][C]0.994837[/C][/ROW]
[ROW][C]66[/C][C]115.76[/C][C]115.783[/C][C]115.106[/C][C]1.00588[/C][C]0.999803[/C][/ROW]
[ROW][C]67[/C][C]116.2[/C][C]115.982[/C][C]115.216[/C][C]1.00665[/C][C]1.00188[/C][/ROW]
[ROW][C]68[/C][C]116.48[/C][C]116.46[/C][C]115.338[/C][C]1.00973[/C][C]1.00017[/C][/ROW]
[ROW][C]69[/C][C]116.53[/C][C]116.517[/C][C]115.475[/C][C]1.00903[/C][C]1.00011[/C][/ROW]
[ROW][C]70[/C][C]116.45[/C][C]116.102[/C][C]115.633[/C][C]1.00405[/C][C]1.003[/C][/ROW]
[ROW][C]71[/C][C]116.23[/C][C]115.875[/C][C]115.732[/C][C]1.00123[/C][C]1.00307[/C][/ROW]
[ROW][C]72[/C][C]114.46[/C][C]114.123[/C][C]115.696[/C][C]0.986401[/C][C]1.00296[/C][/ROW]
[ROW][C]73[/C][C]115.08[/C][C]114.291[/C][C]115.548[/C][C]0.98913[/C][C]1.0069[/C][/ROW]
[ROW][C]74[/C][C]115.57[/C][C]114.867[/C][C]115.492[/C][C]0.994587[/C][C]1.00612[/C][/ROW]
[ROW][C]75[/C][C]116.17[/C][C]115.428[/C][C]115.572[/C][C]0.998756[/C][C]1.00643[/C][/ROW]
[ROW][C]76[/C][C]115.21[/C][C]115.132[/C][C]115.65[/C][C]0.995523[/C][C]1.00068[/C][/ROW]
[ROW][C]77[/C][C]114.97[/C][C]115.586[/C][C]115.697[/C][C]0.999041[/C][C]0.994673[/C][/ROW]
[ROW][C]78[/C][C]114.24[/C][C]116.406[/C][C]115.725[/C][C]1.00588[/C][C]0.981393[/C][/ROW]
[ROW][C]79[/C][C]114.16[/C][C]116.541[/C][C]115.771[/C][C]1.00665[/C][C]0.979573[/C][/ROW]
[ROW][C]80[/C][C]117.2[/C][C]117.024[/C][C]115.896[/C][C]1.00973[/C][C]1.00151[/C][/ROW]
[ROW][C]81[/C][C]117.71[/C][C]117.127[/C][C]116.079[/C][C]1.00903[/C][C]1.00498[/C][/ROW]
[ROW][C]82[/C][C]117.14[/C][C]116.783[/C][C]116.312[/C][C]1.00405[/C][C]1.00306[/C][/ROW]
[ROW][C]83[/C][C]116.67[/C][C]116.791[/C][C]116.648[/C][C]1.00123[/C][C]0.998961[/C][/ROW]
[ROW][C]84[/C][C]114.71[/C][C]115.54[/C][C]117.133[/C][C]0.986401[/C][C]0.992812[/C][/ROW]
[ROW][C]85[/C][C]115.92[/C][C]116.445[/C][C]117.725[/C][C]0.98913[/C][C]0.995489[/C][/ROW]
[ROW][C]86[/C][C]117.74[/C][C]117.614[/C][C]118.254[/C][C]0.994587[/C][C]1.00107[/C][/ROW]
[ROW][C]87[/C][C]118.38[/C][C]118.552[/C][C]118.7[/C][C]0.998756[/C][C]0.998546[/C][/ROW]
[ROW][C]88[/C][C]118.59[/C][C]118.625[/C][C]119.158[/C][C]0.995523[/C][C]0.999706[/C][/ROW]
[ROW][C]89[/C][C]119.66[/C][C]119.559[/C][C]119.674[/C][C]0.999041[/C][C]1.00084[/C][/ROW]
[ROW][C]90[/C][C]121.2[/C][C]120.962[/C][C]120.255[/C][C]1.00588[/C][C]1.00197[/C][/ROW]
[ROW][C]91[/C][C]121.4[/C][C]NA[/C][C]NA[/C][C]1.00665[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]122.66[/C][C]NA[/C][C]NA[/C][C]1.00973[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]122.95[/C][C]NA[/C][C]NA[/C][C]1.00903[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]122.9[/C][C]NA[/C][C]NA[/C][C]1.00405[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]123.29[/C][C]NA[/C][C]NA[/C][C]1.00123[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]122.02[/C][C]NA[/C][C]NA[/C][C]0.986401[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279377&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279377&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
1100.8NANA0.98913NA
2100.66NANA0.994587NA
3101.44NANA0.998756NA
4102.17NANA0.995523NA
5102.75NANA0.999041NA
6104.28NANA1.00588NA
7104.96104.376103.6871.006651.00559
8105.16105.042104.031.009731.00112
9105.29105.345104.4021.009030.999479
10105.15105.182104.7581.004050.999695
11105.23105.228105.0981.001231.00002
12104.45103.975105.4080.9864011.00457
13104.6104.499105.6480.989131.00097
14105.1105.262105.8350.9945870.99846
15105.94105.863105.9950.9987561.00073
16106.2105.678106.1530.9955231.00494
17106.89106.219106.3210.9990411.00632
18107.57107.12106.4941.005881.0042
19107.42107.392106.6831.006651.00026
20107.2107.952106.9121.009730.993033
21107.08108.171107.2031.009030.989914
22107.17108.039107.6031.004050.99196
23107.23108.25108.1181.001230.990573
24106.61107.236108.7140.9864010.994164
25106.97108.186109.3750.989130.988759
26108.23109.467110.0630.9945870.988699
27109.8110.621110.7590.9987560.992575
28111.93110.932111.4310.9955231.009
29113.51111.974112.0820.9990411.01372
30115.27113.371112.7081.005881.01675
31115.58114.074113.3211.006651.0132
32115.55115.019113.9111.009731.00462
33115.44115.483114.451.009030.999627
34114.93115.326114.8611.004050.996567
35115.09115.251115.1091.001230.998606
36113.78113.698115.2650.9864011.00072
37114.51114.125115.3790.989131.00337
38114.85114.888115.5130.9945870.999669
39116.12115.53115.6740.9987561.0051
40115.47115.334115.8530.9955231.00118
41115.93115.916116.0270.9990411.00012
42116.6116.84116.1571.005880.997944
43116.98117.026116.2531.006650.999608
44117.37117.481116.3491.009730.999059
45117.48117.446116.3951.009031.00029
46117.18116.824116.3531.004051.00305
47117.03116.39116.2471.001231.0055
48114.95114.577116.1570.9864011.00325
49115.64114.836116.0980.989131.00701
50116.02115.396116.0240.9945871.00541
51116.07115.811115.9550.9987561.00224
52114.5115.347115.8660.9955230.992656
53114.36115.629115.740.9990410.989029
54116116.294115.6141.005880.997475
55116.16116.227115.461.006650.999422
56116.42116.417115.2951.009731.00003
57116.78116.183115.1441.009031.00513
58115.74115.485115.021.004051.00221
59115.44115.117114.9751.001231.00281
60113.52113.401114.9640.9864011.00105
61113.37113.706114.9560.989130.997043
62114.35114.338114.960.9945871.00011
63114.11114.809114.9520.9987560.993911
64113.47114.457114.9710.9955230.991381
65114.33114.923115.0340.9990410.994837
66115.76115.783115.1061.005880.999803
67116.2115.982115.2161.006651.00188
68116.48116.46115.3381.009731.00017
69116.53116.517115.4751.009031.00011
70116.45116.102115.6331.004051.003
71116.23115.875115.7321.001231.00307
72114.46114.123115.6960.9864011.00296
73115.08114.291115.5480.989131.0069
74115.57114.867115.4920.9945871.00612
75116.17115.428115.5720.9987561.00643
76115.21115.132115.650.9955231.00068
77114.97115.586115.6970.9990410.994673
78114.24116.406115.7251.005880.981393
79114.16116.541115.7711.006650.979573
80117.2117.024115.8961.009731.00151
81117.71117.127116.0791.009031.00498
82117.14116.783116.3121.004051.00306
83116.67116.791116.6481.001230.998961
84114.71115.54117.1330.9864010.992812
85115.92116.445117.7250.989130.995489
86117.74117.614118.2540.9945871.00107
87118.38118.552118.70.9987560.998546
88118.59118.625119.1580.9955230.999706
89119.66119.559119.6740.9990411.00084
90121.2120.962120.2551.005881.00197
91121.4NANA1.00665NA
92122.66NANA1.00973NA
93122.95NANA1.00903NA
94122.9NANA1.00405NA
95123.29NANA1.00123NA
96122.02NANA0.986401NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = 12 ; par6 = White Noise ; par7 = 0.95 ;
Parameters (R input):
par1 = multiplicative ; 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')