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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 computationSun, 25 May 2008 08:20:53 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/25/t12117253223bwmury4hjjqg5j.htm/, Retrieved Wed, 15 May 2024 21:37:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13150, Retrieved Wed, 15 May 2024 21:37:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [Classical Decompo...] [2008-05-25 14:20:53] [9d456519644b7519961e155943b4a156] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
120,05
120,05
120,08
120,12
120,18
120,2
120,25
120,25
120,24
120,29
120,25
120,26
120,32
120,31
120,36
120,4
120,4
120,39
120,44
120,5
120,53
120,64
120,78
120,94
121
121,05
121,15
121,07
121,18
121,46
121,71
121,71
121,74
121,76
121,76
121,82
121,82
121,82
121,94
121,99
122,18
122,41
122,48
122,52
122,62
122,63
122,74
122,58
122,59
122,61
122,63
122,37
122,36
122,47
122,46
122,45
122,49
122,5
122,37
122,37
122,51
122,51
122,55
122,56
122,72
122,97
123,03
123,05
123,08
123,08
123,12
123,07
123,04
123,06
123,39
124,02
124,05
123,99
124,46
124,46
124,6
124,84
124,84
124,99

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 5 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13150&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13150&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13150&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 time5 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1120.05NANA0.999946242484007NA
2120.05NANA0.999662380256842NA
3120.08NANA0.999818813414997NA
4120.12NANA0.9990416352703NA
5120.18NANA0.999391118272827NA
6120.2NANA1.00041001636649NA
7120.25120.282983293415120.196251.000721597332820.999725785871686
8120.25120.281810659693120.2183333333331.000528017022020.99973553225115
9120.24120.302040478502120.2408333333331.000509037932220.999484294046427
10120.29120.300568283810120.2641666666671.000302680492060.999912151006756
11120.25120.293534652118120.2851.000070953586220.999638096492517
12120.26120.253662655382120.3020833333330.99959750756921.00005269980538
13120.32120.311448674337120.3179166666670.9999462424840071.00007107657465
14120.31120.295622106182120.336250.9996623802568421.00011952133890
15120.36120.336942609112120.358750.9998188134149971.00019160691960
16120.4120.270043529363120.3854166666670.99904163527031.00108053898397
17120.4120.348760527244120.4220833333330.9993911182728271.00042575820916
18120.39120.521895696712120.47251.000410016366490.998905628757753
19120.44120.616140191860120.5291666666671.000721597332820.998539663169622
20120.5120.652006025991120.5883333333331.000528017022020.998740128481924
21120.53120.713499820351120.6520833333331.000509037932220.99847987324844
22120.64120.749454111681120.7129166666671.000302680492060.999093543631427
23120.78120.781902634453120.7733333333331.000070953586220.99998424735485
24120.94120.801775288699120.8504166666670.99959750756921.00114422748317
25121120.941414807102120.9479166666670.9999462424840071.00048440968705
26121.05121.010380708066121.051250.9996623802568421.00032740407643
27121.15121.130132201088121.1520833333330.9998188134149971.00016402028588
28121.07121.132965741828121.2491666666670.99904163527030.999480193179105
29121.18121.262786987497121.3366666666670.9993911182728270.999317292719771
30121.46121.463948462123121.4141666666671.000410016366490.99996749272378
31121.71121.572663251977121.4851.000721597332821.00112966800553
32121.71121.615431129048121.551251.000528017022021.0007776058521
33121.74121.678157284424121.616251.000509037932221.00050824829169
34121.76121.724332432377121.68751.000302680492061.00029301920914
35121.76121.776139840810121.76751.000070953586220.999867463028218
36121.82121.799706800423121.848750.99959750756921.00016661123504
37121.82121.913862527918121.9204166666670.9999462424840070.999230091427081
38121.82121.945065033606121.986250.9996623802568420.998974414966512
39121.94122.034551636056122.0566666666670.9998188134149970.999225206019207
40121.99122.012538648214122.1295833333330.99904163527030.999815275967015
41122.18122.132257260395122.2066666666670.9993911182728271.00039091015491
42122.41122.329303126280122.2791666666671.000410016366491.00065966920155
43122.48122.431198989023122.3429166666671.000721597332821.00039859946958
44122.52122.472550130297122.4079166666671.000528017022021.00038743269126
45122.62122.531924996793122.4695833333331.000509037932221.00071879229196
46122.63122.551249314918122.5141666666671.000302680492061.00064259389866
47122.74122.546194475071122.53751.000070953586221.00158148954163
48122.58122.498175558837122.54750.99959750756921.00066796457000
49122.59122.542578727880122.5491666666670.9999462424840071.00038697791913
50122.61122.504042914566122.5454166666670.9996623802568421.00086492725393
51122.63122.514881257668122.5370833333330.9998188134149971.00093963068935
52122.37122.408825163538122.526250.99904163527030.999682823820212
53122.36122.430825356979122.5054166666670.9993911182728270.999421507150899
54122.47122.531469317088122.481251.000410016366490.999498338529438
55122.46122.557540090686122.4691666666671.000721597332820.999204128194694
56122.45122.526328511212122.4616666666671.000528017022020.999377044002383
57122.49122.516500482458122.4541666666671.000509037932220.99978369866627
58122.5122.495815874707122.458751.000302680492061.00003415729152
59122.37122.490357180163122.4816666666671.000070953586220.9990174150608
60122.37122.468187633610122.51750.99959750756920.999198260090994
61122.51122.555494700178122.5620833333330.9999462424840070.999628782860453
62122.51122.569437495275122.6108333333330.9996623802568420.999515070832586
63122.55122.638192244656122.6604166666670.9998188134149970.999280874554316
64122.56122.591566529323122.7091666666670.99904163527030.999742506518057
65122.72122.689834221798122.7645833333330.9993911182728271.00024587023362
66122.97122.875360260214122.8251.000410016366491.00077020925583
67123.03122.964917174267122.876251.000721597332821.00052927962893
68123.05122.986154512368122.921251.000528017022021.00051912744068
69123.08123.041767727373122.9791666666671.000509037932221.00031072597000
70123.08123.112252401560123.0751.000302680492060.999738024437609
71123.12123.199990860978123.191251.000070953586220.999350723482858
72123.07123.239543710284123.2891666666670.99959750756920.998624275089152
73123.04123.384616792905123.391250.9999462424840070.997206971161704
74123.06123.467884059531123.5095833333330.9996623802568420.996696435978978
75123.39123.609266267185123.6316666666670.9998188134149970.998226134060928
76124.02123.649718128013123.7683333333330.99904163527031.00299460344587
77124.05123.837884768914123.9133333333330.9993911182728271.00171284604451
78123.99124.115868680508124.0651.000410016366490.99898587761705
79124.46NANA1.00072159733282NA
80124.46NANA1.00052801702202NA
81124.6NANA1.00050903793222NA
82124.84NANA1.00030268049206NA
83124.84NANA1.00007095358622NA
84124.99NANA0.9995975075692NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 120.05 & NA & NA & 0.999946242484007 & NA \tabularnewline
2 & 120.05 & NA & NA & 0.999662380256842 & NA \tabularnewline
3 & 120.08 & NA & NA & 0.999818813414997 & NA \tabularnewline
4 & 120.12 & NA & NA & 0.9990416352703 & NA \tabularnewline
5 & 120.18 & NA & NA & 0.999391118272827 & NA \tabularnewline
6 & 120.2 & NA & NA & 1.00041001636649 & NA \tabularnewline
7 & 120.25 & 120.282983293415 & 120.19625 & 1.00072159733282 & 0.999725785871686 \tabularnewline
8 & 120.25 & 120.281810659693 & 120.218333333333 & 1.00052801702202 & 0.99973553225115 \tabularnewline
9 & 120.24 & 120.302040478502 & 120.240833333333 & 1.00050903793222 & 0.999484294046427 \tabularnewline
10 & 120.29 & 120.300568283810 & 120.264166666667 & 1.00030268049206 & 0.999912151006756 \tabularnewline
11 & 120.25 & 120.293534652118 & 120.285 & 1.00007095358622 & 0.999638096492517 \tabularnewline
12 & 120.26 & 120.253662655382 & 120.302083333333 & 0.9995975075692 & 1.00005269980538 \tabularnewline
13 & 120.32 & 120.311448674337 & 120.317916666667 & 0.999946242484007 & 1.00007107657465 \tabularnewline
14 & 120.31 & 120.295622106182 & 120.33625 & 0.999662380256842 & 1.00011952133890 \tabularnewline
15 & 120.36 & 120.336942609112 & 120.35875 & 0.999818813414997 & 1.00019160691960 \tabularnewline
16 & 120.4 & 120.270043529363 & 120.385416666667 & 0.9990416352703 & 1.00108053898397 \tabularnewline
17 & 120.4 & 120.348760527244 & 120.422083333333 & 0.999391118272827 & 1.00042575820916 \tabularnewline
18 & 120.39 & 120.521895696712 & 120.4725 & 1.00041001636649 & 0.998905628757753 \tabularnewline
19 & 120.44 & 120.616140191860 & 120.529166666667 & 1.00072159733282 & 0.998539663169622 \tabularnewline
20 & 120.5 & 120.652006025991 & 120.588333333333 & 1.00052801702202 & 0.998740128481924 \tabularnewline
21 & 120.53 & 120.713499820351 & 120.652083333333 & 1.00050903793222 & 0.99847987324844 \tabularnewline
22 & 120.64 & 120.749454111681 & 120.712916666667 & 1.00030268049206 & 0.999093543631427 \tabularnewline
23 & 120.78 & 120.781902634453 & 120.773333333333 & 1.00007095358622 & 0.99998424735485 \tabularnewline
24 & 120.94 & 120.801775288699 & 120.850416666667 & 0.9995975075692 & 1.00114422748317 \tabularnewline
25 & 121 & 120.941414807102 & 120.947916666667 & 0.999946242484007 & 1.00048440968705 \tabularnewline
26 & 121.05 & 121.010380708066 & 121.05125 & 0.999662380256842 & 1.00032740407643 \tabularnewline
27 & 121.15 & 121.130132201088 & 121.152083333333 & 0.999818813414997 & 1.00016402028588 \tabularnewline
28 & 121.07 & 121.132965741828 & 121.249166666667 & 0.9990416352703 & 0.999480193179105 \tabularnewline
29 & 121.18 & 121.262786987497 & 121.336666666667 & 0.999391118272827 & 0.999317292719771 \tabularnewline
30 & 121.46 & 121.463948462123 & 121.414166666667 & 1.00041001636649 & 0.99996749272378 \tabularnewline
31 & 121.71 & 121.572663251977 & 121.485 & 1.00072159733282 & 1.00112966800553 \tabularnewline
32 & 121.71 & 121.615431129048 & 121.55125 & 1.00052801702202 & 1.0007776058521 \tabularnewline
33 & 121.74 & 121.678157284424 & 121.61625 & 1.00050903793222 & 1.00050824829169 \tabularnewline
34 & 121.76 & 121.724332432377 & 121.6875 & 1.00030268049206 & 1.00029301920914 \tabularnewline
35 & 121.76 & 121.776139840810 & 121.7675 & 1.00007095358622 & 0.999867463028218 \tabularnewline
36 & 121.82 & 121.799706800423 & 121.84875 & 0.9995975075692 & 1.00016661123504 \tabularnewline
37 & 121.82 & 121.913862527918 & 121.920416666667 & 0.999946242484007 & 0.999230091427081 \tabularnewline
38 & 121.82 & 121.945065033606 & 121.98625 & 0.999662380256842 & 0.998974414966512 \tabularnewline
39 & 121.94 & 122.034551636056 & 122.056666666667 & 0.999818813414997 & 0.999225206019207 \tabularnewline
40 & 121.99 & 122.012538648214 & 122.129583333333 & 0.9990416352703 & 0.999815275967015 \tabularnewline
41 & 122.18 & 122.132257260395 & 122.206666666667 & 0.999391118272827 & 1.00039091015491 \tabularnewline
42 & 122.41 & 122.329303126280 & 122.279166666667 & 1.00041001636649 & 1.00065966920155 \tabularnewline
43 & 122.48 & 122.431198989023 & 122.342916666667 & 1.00072159733282 & 1.00039859946958 \tabularnewline
44 & 122.52 & 122.472550130297 & 122.407916666667 & 1.00052801702202 & 1.00038743269126 \tabularnewline
45 & 122.62 & 122.531924996793 & 122.469583333333 & 1.00050903793222 & 1.00071879229196 \tabularnewline
46 & 122.63 & 122.551249314918 & 122.514166666667 & 1.00030268049206 & 1.00064259389866 \tabularnewline
47 & 122.74 & 122.546194475071 & 122.5375 & 1.00007095358622 & 1.00158148954163 \tabularnewline
48 & 122.58 & 122.498175558837 & 122.5475 & 0.9995975075692 & 1.00066796457000 \tabularnewline
49 & 122.59 & 122.542578727880 & 122.549166666667 & 0.999946242484007 & 1.00038697791913 \tabularnewline
50 & 122.61 & 122.504042914566 & 122.545416666667 & 0.999662380256842 & 1.00086492725393 \tabularnewline
51 & 122.63 & 122.514881257668 & 122.537083333333 & 0.999818813414997 & 1.00093963068935 \tabularnewline
52 & 122.37 & 122.408825163538 & 122.52625 & 0.9990416352703 & 0.999682823820212 \tabularnewline
53 & 122.36 & 122.430825356979 & 122.505416666667 & 0.999391118272827 & 0.999421507150899 \tabularnewline
54 & 122.47 & 122.531469317088 & 122.48125 & 1.00041001636649 & 0.999498338529438 \tabularnewline
55 & 122.46 & 122.557540090686 & 122.469166666667 & 1.00072159733282 & 0.999204128194694 \tabularnewline
56 & 122.45 & 122.526328511212 & 122.461666666667 & 1.00052801702202 & 0.999377044002383 \tabularnewline
57 & 122.49 & 122.516500482458 & 122.454166666667 & 1.00050903793222 & 0.99978369866627 \tabularnewline
58 & 122.5 & 122.495815874707 & 122.45875 & 1.00030268049206 & 1.00003415729152 \tabularnewline
59 & 122.37 & 122.490357180163 & 122.481666666667 & 1.00007095358622 & 0.9990174150608 \tabularnewline
60 & 122.37 & 122.468187633610 & 122.5175 & 0.9995975075692 & 0.999198260090994 \tabularnewline
61 & 122.51 & 122.555494700178 & 122.562083333333 & 0.999946242484007 & 0.999628782860453 \tabularnewline
62 & 122.51 & 122.569437495275 & 122.610833333333 & 0.999662380256842 & 0.999515070832586 \tabularnewline
63 & 122.55 & 122.638192244656 & 122.660416666667 & 0.999818813414997 & 0.999280874554316 \tabularnewline
64 & 122.56 & 122.591566529323 & 122.709166666667 & 0.9990416352703 & 0.999742506518057 \tabularnewline
65 & 122.72 & 122.689834221798 & 122.764583333333 & 0.999391118272827 & 1.00024587023362 \tabularnewline
66 & 122.97 & 122.875360260214 & 122.825 & 1.00041001636649 & 1.00077020925583 \tabularnewline
67 & 123.03 & 122.964917174267 & 122.87625 & 1.00072159733282 & 1.00052927962893 \tabularnewline
68 & 123.05 & 122.986154512368 & 122.92125 & 1.00052801702202 & 1.00051912744068 \tabularnewline
69 & 123.08 & 123.041767727373 & 122.979166666667 & 1.00050903793222 & 1.00031072597000 \tabularnewline
70 & 123.08 & 123.112252401560 & 123.075 & 1.00030268049206 & 0.999738024437609 \tabularnewline
71 & 123.12 & 123.199990860978 & 123.19125 & 1.00007095358622 & 0.999350723482858 \tabularnewline
72 & 123.07 & 123.239543710284 & 123.289166666667 & 0.9995975075692 & 0.998624275089152 \tabularnewline
73 & 123.04 & 123.384616792905 & 123.39125 & 0.999946242484007 & 0.997206971161704 \tabularnewline
74 & 123.06 & 123.467884059531 & 123.509583333333 & 0.999662380256842 & 0.996696435978978 \tabularnewline
75 & 123.39 & 123.609266267185 & 123.631666666667 & 0.999818813414997 & 0.998226134060928 \tabularnewline
76 & 124.02 & 123.649718128013 & 123.768333333333 & 0.9990416352703 & 1.00299460344587 \tabularnewline
77 & 124.05 & 123.837884768914 & 123.913333333333 & 0.999391118272827 & 1.00171284604451 \tabularnewline
78 & 123.99 & 124.115868680508 & 124.065 & 1.00041001636649 & 0.99898587761705 \tabularnewline
79 & 124.46 & NA & NA & 1.00072159733282 & NA \tabularnewline
80 & 124.46 & NA & NA & 1.00052801702202 & NA \tabularnewline
81 & 124.6 & NA & NA & 1.00050903793222 & NA \tabularnewline
82 & 124.84 & NA & NA & 1.00030268049206 & NA \tabularnewline
83 & 124.84 & NA & NA & 1.00007095358622 & NA \tabularnewline
84 & 124.99 & NA & NA & 0.9995975075692 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13150&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]120.05[/C][C]NA[/C][C]NA[/C][C]0.999946242484007[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]120.05[/C][C]NA[/C][C]NA[/C][C]0.999662380256842[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]120.08[/C][C]NA[/C][C]NA[/C][C]0.999818813414997[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]120.12[/C][C]NA[/C][C]NA[/C][C]0.9990416352703[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]120.18[/C][C]NA[/C][C]NA[/C][C]0.999391118272827[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]120.2[/C][C]NA[/C][C]NA[/C][C]1.00041001636649[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]120.25[/C][C]120.282983293415[/C][C]120.19625[/C][C]1.00072159733282[/C][C]0.999725785871686[/C][/ROW]
[ROW][C]8[/C][C]120.25[/C][C]120.281810659693[/C][C]120.218333333333[/C][C]1.00052801702202[/C][C]0.99973553225115[/C][/ROW]
[ROW][C]9[/C][C]120.24[/C][C]120.302040478502[/C][C]120.240833333333[/C][C]1.00050903793222[/C][C]0.999484294046427[/C][/ROW]
[ROW][C]10[/C][C]120.29[/C][C]120.300568283810[/C][C]120.264166666667[/C][C]1.00030268049206[/C][C]0.999912151006756[/C][/ROW]
[ROW][C]11[/C][C]120.25[/C][C]120.293534652118[/C][C]120.285[/C][C]1.00007095358622[/C][C]0.999638096492517[/C][/ROW]
[ROW][C]12[/C][C]120.26[/C][C]120.253662655382[/C][C]120.302083333333[/C][C]0.9995975075692[/C][C]1.00005269980538[/C][/ROW]
[ROW][C]13[/C][C]120.32[/C][C]120.311448674337[/C][C]120.317916666667[/C][C]0.999946242484007[/C][C]1.00007107657465[/C][/ROW]
[ROW][C]14[/C][C]120.31[/C][C]120.295622106182[/C][C]120.33625[/C][C]0.999662380256842[/C][C]1.00011952133890[/C][/ROW]
[ROW][C]15[/C][C]120.36[/C][C]120.336942609112[/C][C]120.35875[/C][C]0.999818813414997[/C][C]1.00019160691960[/C][/ROW]
[ROW][C]16[/C][C]120.4[/C][C]120.270043529363[/C][C]120.385416666667[/C][C]0.9990416352703[/C][C]1.00108053898397[/C][/ROW]
[ROW][C]17[/C][C]120.4[/C][C]120.348760527244[/C][C]120.422083333333[/C][C]0.999391118272827[/C][C]1.00042575820916[/C][/ROW]
[ROW][C]18[/C][C]120.39[/C][C]120.521895696712[/C][C]120.4725[/C][C]1.00041001636649[/C][C]0.998905628757753[/C][/ROW]
[ROW][C]19[/C][C]120.44[/C][C]120.616140191860[/C][C]120.529166666667[/C][C]1.00072159733282[/C][C]0.998539663169622[/C][/ROW]
[ROW][C]20[/C][C]120.5[/C][C]120.652006025991[/C][C]120.588333333333[/C][C]1.00052801702202[/C][C]0.998740128481924[/C][/ROW]
[ROW][C]21[/C][C]120.53[/C][C]120.713499820351[/C][C]120.652083333333[/C][C]1.00050903793222[/C][C]0.99847987324844[/C][/ROW]
[ROW][C]22[/C][C]120.64[/C][C]120.749454111681[/C][C]120.712916666667[/C][C]1.00030268049206[/C][C]0.999093543631427[/C][/ROW]
[ROW][C]23[/C][C]120.78[/C][C]120.781902634453[/C][C]120.773333333333[/C][C]1.00007095358622[/C][C]0.99998424735485[/C][/ROW]
[ROW][C]24[/C][C]120.94[/C][C]120.801775288699[/C][C]120.850416666667[/C][C]0.9995975075692[/C][C]1.00114422748317[/C][/ROW]
[ROW][C]25[/C][C]121[/C][C]120.941414807102[/C][C]120.947916666667[/C][C]0.999946242484007[/C][C]1.00048440968705[/C][/ROW]
[ROW][C]26[/C][C]121.05[/C][C]121.010380708066[/C][C]121.05125[/C][C]0.999662380256842[/C][C]1.00032740407643[/C][/ROW]
[ROW][C]27[/C][C]121.15[/C][C]121.130132201088[/C][C]121.152083333333[/C][C]0.999818813414997[/C][C]1.00016402028588[/C][/ROW]
[ROW][C]28[/C][C]121.07[/C][C]121.132965741828[/C][C]121.249166666667[/C][C]0.9990416352703[/C][C]0.999480193179105[/C][/ROW]
[ROW][C]29[/C][C]121.18[/C][C]121.262786987497[/C][C]121.336666666667[/C][C]0.999391118272827[/C][C]0.999317292719771[/C][/ROW]
[ROW][C]30[/C][C]121.46[/C][C]121.463948462123[/C][C]121.414166666667[/C][C]1.00041001636649[/C][C]0.99996749272378[/C][/ROW]
[ROW][C]31[/C][C]121.71[/C][C]121.572663251977[/C][C]121.485[/C][C]1.00072159733282[/C][C]1.00112966800553[/C][/ROW]
[ROW][C]32[/C][C]121.71[/C][C]121.615431129048[/C][C]121.55125[/C][C]1.00052801702202[/C][C]1.0007776058521[/C][/ROW]
[ROW][C]33[/C][C]121.74[/C][C]121.678157284424[/C][C]121.61625[/C][C]1.00050903793222[/C][C]1.00050824829169[/C][/ROW]
[ROW][C]34[/C][C]121.76[/C][C]121.724332432377[/C][C]121.6875[/C][C]1.00030268049206[/C][C]1.00029301920914[/C][/ROW]
[ROW][C]35[/C][C]121.76[/C][C]121.776139840810[/C][C]121.7675[/C][C]1.00007095358622[/C][C]0.999867463028218[/C][/ROW]
[ROW][C]36[/C][C]121.82[/C][C]121.799706800423[/C][C]121.84875[/C][C]0.9995975075692[/C][C]1.00016661123504[/C][/ROW]
[ROW][C]37[/C][C]121.82[/C][C]121.913862527918[/C][C]121.920416666667[/C][C]0.999946242484007[/C][C]0.999230091427081[/C][/ROW]
[ROW][C]38[/C][C]121.82[/C][C]121.945065033606[/C][C]121.98625[/C][C]0.999662380256842[/C][C]0.998974414966512[/C][/ROW]
[ROW][C]39[/C][C]121.94[/C][C]122.034551636056[/C][C]122.056666666667[/C][C]0.999818813414997[/C][C]0.999225206019207[/C][/ROW]
[ROW][C]40[/C][C]121.99[/C][C]122.012538648214[/C][C]122.129583333333[/C][C]0.9990416352703[/C][C]0.999815275967015[/C][/ROW]
[ROW][C]41[/C][C]122.18[/C][C]122.132257260395[/C][C]122.206666666667[/C][C]0.999391118272827[/C][C]1.00039091015491[/C][/ROW]
[ROW][C]42[/C][C]122.41[/C][C]122.329303126280[/C][C]122.279166666667[/C][C]1.00041001636649[/C][C]1.00065966920155[/C][/ROW]
[ROW][C]43[/C][C]122.48[/C][C]122.431198989023[/C][C]122.342916666667[/C][C]1.00072159733282[/C][C]1.00039859946958[/C][/ROW]
[ROW][C]44[/C][C]122.52[/C][C]122.472550130297[/C][C]122.407916666667[/C][C]1.00052801702202[/C][C]1.00038743269126[/C][/ROW]
[ROW][C]45[/C][C]122.62[/C][C]122.531924996793[/C][C]122.469583333333[/C][C]1.00050903793222[/C][C]1.00071879229196[/C][/ROW]
[ROW][C]46[/C][C]122.63[/C][C]122.551249314918[/C][C]122.514166666667[/C][C]1.00030268049206[/C][C]1.00064259389866[/C][/ROW]
[ROW][C]47[/C][C]122.74[/C][C]122.546194475071[/C][C]122.5375[/C][C]1.00007095358622[/C][C]1.00158148954163[/C][/ROW]
[ROW][C]48[/C][C]122.58[/C][C]122.498175558837[/C][C]122.5475[/C][C]0.9995975075692[/C][C]1.00066796457000[/C][/ROW]
[ROW][C]49[/C][C]122.59[/C][C]122.542578727880[/C][C]122.549166666667[/C][C]0.999946242484007[/C][C]1.00038697791913[/C][/ROW]
[ROW][C]50[/C][C]122.61[/C][C]122.504042914566[/C][C]122.545416666667[/C][C]0.999662380256842[/C][C]1.00086492725393[/C][/ROW]
[ROW][C]51[/C][C]122.63[/C][C]122.514881257668[/C][C]122.537083333333[/C][C]0.999818813414997[/C][C]1.00093963068935[/C][/ROW]
[ROW][C]52[/C][C]122.37[/C][C]122.408825163538[/C][C]122.52625[/C][C]0.9990416352703[/C][C]0.999682823820212[/C][/ROW]
[ROW][C]53[/C][C]122.36[/C][C]122.430825356979[/C][C]122.505416666667[/C][C]0.999391118272827[/C][C]0.999421507150899[/C][/ROW]
[ROW][C]54[/C][C]122.47[/C][C]122.531469317088[/C][C]122.48125[/C][C]1.00041001636649[/C][C]0.999498338529438[/C][/ROW]
[ROW][C]55[/C][C]122.46[/C][C]122.557540090686[/C][C]122.469166666667[/C][C]1.00072159733282[/C][C]0.999204128194694[/C][/ROW]
[ROW][C]56[/C][C]122.45[/C][C]122.526328511212[/C][C]122.461666666667[/C][C]1.00052801702202[/C][C]0.999377044002383[/C][/ROW]
[ROW][C]57[/C][C]122.49[/C][C]122.516500482458[/C][C]122.454166666667[/C][C]1.00050903793222[/C][C]0.99978369866627[/C][/ROW]
[ROW][C]58[/C][C]122.5[/C][C]122.495815874707[/C][C]122.45875[/C][C]1.00030268049206[/C][C]1.00003415729152[/C][/ROW]
[ROW][C]59[/C][C]122.37[/C][C]122.490357180163[/C][C]122.481666666667[/C][C]1.00007095358622[/C][C]0.9990174150608[/C][/ROW]
[ROW][C]60[/C][C]122.37[/C][C]122.468187633610[/C][C]122.5175[/C][C]0.9995975075692[/C][C]0.999198260090994[/C][/ROW]
[ROW][C]61[/C][C]122.51[/C][C]122.555494700178[/C][C]122.562083333333[/C][C]0.999946242484007[/C][C]0.999628782860453[/C][/ROW]
[ROW][C]62[/C][C]122.51[/C][C]122.569437495275[/C][C]122.610833333333[/C][C]0.999662380256842[/C][C]0.999515070832586[/C][/ROW]
[ROW][C]63[/C][C]122.55[/C][C]122.638192244656[/C][C]122.660416666667[/C][C]0.999818813414997[/C][C]0.999280874554316[/C][/ROW]
[ROW][C]64[/C][C]122.56[/C][C]122.591566529323[/C][C]122.709166666667[/C][C]0.9990416352703[/C][C]0.999742506518057[/C][/ROW]
[ROW][C]65[/C][C]122.72[/C][C]122.689834221798[/C][C]122.764583333333[/C][C]0.999391118272827[/C][C]1.00024587023362[/C][/ROW]
[ROW][C]66[/C][C]122.97[/C][C]122.875360260214[/C][C]122.825[/C][C]1.00041001636649[/C][C]1.00077020925583[/C][/ROW]
[ROW][C]67[/C][C]123.03[/C][C]122.964917174267[/C][C]122.87625[/C][C]1.00072159733282[/C][C]1.00052927962893[/C][/ROW]
[ROW][C]68[/C][C]123.05[/C][C]122.986154512368[/C][C]122.92125[/C][C]1.00052801702202[/C][C]1.00051912744068[/C][/ROW]
[ROW][C]69[/C][C]123.08[/C][C]123.041767727373[/C][C]122.979166666667[/C][C]1.00050903793222[/C][C]1.00031072597000[/C][/ROW]
[ROW][C]70[/C][C]123.08[/C][C]123.112252401560[/C][C]123.075[/C][C]1.00030268049206[/C][C]0.999738024437609[/C][/ROW]
[ROW][C]71[/C][C]123.12[/C][C]123.199990860978[/C][C]123.19125[/C][C]1.00007095358622[/C][C]0.999350723482858[/C][/ROW]
[ROW][C]72[/C][C]123.07[/C][C]123.239543710284[/C][C]123.289166666667[/C][C]0.9995975075692[/C][C]0.998624275089152[/C][/ROW]
[ROW][C]73[/C][C]123.04[/C][C]123.384616792905[/C][C]123.39125[/C][C]0.999946242484007[/C][C]0.997206971161704[/C][/ROW]
[ROW][C]74[/C][C]123.06[/C][C]123.467884059531[/C][C]123.509583333333[/C][C]0.999662380256842[/C][C]0.996696435978978[/C][/ROW]
[ROW][C]75[/C][C]123.39[/C][C]123.609266267185[/C][C]123.631666666667[/C][C]0.999818813414997[/C][C]0.998226134060928[/C][/ROW]
[ROW][C]76[/C][C]124.02[/C][C]123.649718128013[/C][C]123.768333333333[/C][C]0.9990416352703[/C][C]1.00299460344587[/C][/ROW]
[ROW][C]77[/C][C]124.05[/C][C]123.837884768914[/C][C]123.913333333333[/C][C]0.999391118272827[/C][C]1.00171284604451[/C][/ROW]
[ROW][C]78[/C][C]123.99[/C][C]124.115868680508[/C][C]124.065[/C][C]1.00041001636649[/C][C]0.99898587761705[/C][/ROW]
[ROW][C]79[/C][C]124.46[/C][C]NA[/C][C]NA[/C][C]1.00072159733282[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]124.46[/C][C]NA[/C][C]NA[/C][C]1.00052801702202[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]124.6[/C][C]NA[/C][C]NA[/C][C]1.00050903793222[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]124.84[/C][C]NA[/C][C]NA[/C][C]1.00030268049206[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]124.84[/C][C]NA[/C][C]NA[/C][C]1.00007095358622[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]124.99[/C][C]NA[/C][C]NA[/C][C]0.9995975075692[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13150&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13150&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
1120.05NANA0.999946242484007NA
2120.05NANA0.999662380256842NA
3120.08NANA0.999818813414997NA
4120.12NANA0.9990416352703NA
5120.18NANA0.999391118272827NA
6120.2NANA1.00041001636649NA
7120.25120.282983293415120.196251.000721597332820.999725785871686
8120.25120.281810659693120.2183333333331.000528017022020.99973553225115
9120.24120.302040478502120.2408333333331.000509037932220.999484294046427
10120.29120.300568283810120.2641666666671.000302680492060.999912151006756
11120.25120.293534652118120.2851.000070953586220.999638096492517
12120.26120.253662655382120.3020833333330.99959750756921.00005269980538
13120.32120.311448674337120.3179166666670.9999462424840071.00007107657465
14120.31120.295622106182120.336250.9996623802568421.00011952133890
15120.36120.336942609112120.358750.9998188134149971.00019160691960
16120.4120.270043529363120.3854166666670.99904163527031.00108053898397
17120.4120.348760527244120.4220833333330.9993911182728271.00042575820916
18120.39120.521895696712120.47251.000410016366490.998905628757753
19120.44120.616140191860120.5291666666671.000721597332820.998539663169622
20120.5120.652006025991120.5883333333331.000528017022020.998740128481924
21120.53120.713499820351120.6520833333331.000509037932220.99847987324844
22120.64120.749454111681120.7129166666671.000302680492060.999093543631427
23120.78120.781902634453120.7733333333331.000070953586220.99998424735485
24120.94120.801775288699120.8504166666670.99959750756921.00114422748317
25121120.941414807102120.9479166666670.9999462424840071.00048440968705
26121.05121.010380708066121.051250.9996623802568421.00032740407643
27121.15121.130132201088121.1520833333330.9998188134149971.00016402028588
28121.07121.132965741828121.2491666666670.99904163527030.999480193179105
29121.18121.262786987497121.3366666666670.9993911182728270.999317292719771
30121.46121.463948462123121.4141666666671.000410016366490.99996749272378
31121.71121.572663251977121.4851.000721597332821.00112966800553
32121.71121.615431129048121.551251.000528017022021.0007776058521
33121.74121.678157284424121.616251.000509037932221.00050824829169
34121.76121.724332432377121.68751.000302680492061.00029301920914
35121.76121.776139840810121.76751.000070953586220.999867463028218
36121.82121.799706800423121.848750.99959750756921.00016661123504
37121.82121.913862527918121.9204166666670.9999462424840070.999230091427081
38121.82121.945065033606121.986250.9996623802568420.998974414966512
39121.94122.034551636056122.0566666666670.9998188134149970.999225206019207
40121.99122.012538648214122.1295833333330.99904163527030.999815275967015
41122.18122.132257260395122.2066666666670.9993911182728271.00039091015491
42122.41122.329303126280122.2791666666671.000410016366491.00065966920155
43122.48122.431198989023122.3429166666671.000721597332821.00039859946958
44122.52122.472550130297122.4079166666671.000528017022021.00038743269126
45122.62122.531924996793122.4695833333331.000509037932221.00071879229196
46122.63122.551249314918122.5141666666671.000302680492061.00064259389866
47122.74122.546194475071122.53751.000070953586221.00158148954163
48122.58122.498175558837122.54750.99959750756921.00066796457000
49122.59122.542578727880122.5491666666670.9999462424840071.00038697791913
50122.61122.504042914566122.5454166666670.9996623802568421.00086492725393
51122.63122.514881257668122.5370833333330.9998188134149971.00093963068935
52122.37122.408825163538122.526250.99904163527030.999682823820212
53122.36122.430825356979122.5054166666670.9993911182728270.999421507150899
54122.47122.531469317088122.481251.000410016366490.999498338529438
55122.46122.557540090686122.4691666666671.000721597332820.999204128194694
56122.45122.526328511212122.4616666666671.000528017022020.999377044002383
57122.49122.516500482458122.4541666666671.000509037932220.99978369866627
58122.5122.495815874707122.458751.000302680492061.00003415729152
59122.37122.490357180163122.4816666666671.000070953586220.9990174150608
60122.37122.468187633610122.51750.99959750756920.999198260090994
61122.51122.555494700178122.5620833333330.9999462424840070.999628782860453
62122.51122.569437495275122.6108333333330.9996623802568420.999515070832586
63122.55122.638192244656122.6604166666670.9998188134149970.999280874554316
64122.56122.591566529323122.7091666666670.99904163527030.999742506518057
65122.72122.689834221798122.7645833333330.9993911182728271.00024587023362
66122.97122.875360260214122.8251.000410016366491.00077020925583
67123.03122.964917174267122.876251.000721597332821.00052927962893
68123.05122.986154512368122.921251.000528017022021.00051912744068
69123.08123.041767727373122.9791666666671.000509037932221.00031072597000
70123.08123.112252401560123.0751.000302680492060.999738024437609
71123.12123.199990860978123.191251.000070953586220.999350723482858
72123.07123.239543710284123.2891666666670.99959750756920.998624275089152
73123.04123.384616792905123.391250.9999462424840070.997206971161704
74123.06123.467884059531123.5095833333330.9996623802568420.996696435978978
75123.39123.609266267185123.6316666666670.9998188134149970.998226134060928
76124.02123.649718128013123.7683333333330.99904163527031.00299460344587
77124.05123.837884768914123.9133333333330.9993911182728271.00171284604451
78123.99124.115868680508124.0651.000410016366490.99898587761705
79124.46NANA1.00072159733282NA
80124.46NANA1.00052801702202NA
81124.6NANA1.00050903793222NA
82124.84NANA1.00030268049206NA
83124.84NANA1.00007095358622NA
84124.99NANA0.9995975075692NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = multiplicative ; par2 = 12 ;
Parameters (R input):
par1 = multiplicative ; 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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')