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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 computationTue, 14 Dec 2010 19:37:04 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t12923553563eugo8ztd0lfi9n.htm/, Retrieved Thu, 02 May 2024 23:21:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110098, Retrieved Thu, 02 May 2024 23:21:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDGP2W92
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [Iko opgave 9] [2010-12-14 19:31:15] [74be16979710d4c4e7c6647856088456]
-    D    [Classical Decomposition] [opgave 9.2 ad] [2010-12-14 19:37:04] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD      [Classical Decomposition] [iko 9.2 multi] [2010-12-14 19:39:13] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,02
101,15
101,51
101,75
101,8
101,8
101,8
101,82
101,99
102,25
102,34
102,35
102,35
102,39
102,49
102,67
102,68
102,7
102,71
102,72
102,83
102,92
103,04
103,08
103,09
103,11
103,18
103,18
103,22
103,25
103,25
103,25
103,47
103,57
103,66
103,7
103,7
103,75
103,85
104,02
104,13
104,17
104,18
104,2
104,5
104,78
104,88
104,89
104,9
104,95
105,24
105,35
105,44
105,46
105,47
105,48
105,75
106,1
106,19
106,23
106,24
106,25
106,35
106,48
106,52
106,55
106,55
106,56
106,89
107,09
107,24
107,28
107,3
107,31
107,47
107,35
107,31
107,32
107,32
107,34
107,53
107,72
107,75
107,79
107,81
107,9
107,8
107,86
107,8
107,74
107,75
107,83
107,8
107,81
107,86
107,83

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 3 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110098&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110098&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110098&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 time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1101.02NANA0.0258978174603173NA
2101.15NANA-0.00672123015872303NA
3101.51NANA0.0257787698412637NA
4101.75NANA0.0338144841269788NA
5101.8NANA-0.00499503968253818NA
6101.8NANA-0.0576140873015867NA
7101.8101.73845734127101.85375-0.115292658730150.0615426587301755
8101.82101.777802579365101.960833333333-0.1830307539682530.0421974206349205
9101.99102.019826388889102.053333333333-0.0335069444444475-0.0298263888888926
10102.25102.235183531746102.13250.1026835317460310.0148164682539829
11102.34102.333814484127102.20750.1263144841269840.00618551587304239
12102.35102.368338293651102.2816666666670.0866716269841243-0.0183382936507854
13102.35102.382981150794102.3570833333330.0258978174603173-0.0329811507936455
14102.39102.425778769841102.4325-0.00672123015872303-0.0357787698412864
15102.49102.530778769841102.5050.0257787698412637-0.0407787698412676
16102.67102.601731150794102.5679166666670.03381448412697880.0682688492063477
17102.68102.620004960317102.625-0.004995039682538180.0599950396825619
18102.7102.626969246032102.684583333333-0.05761408730158670.0730307539682684
19102.71102.630540674603102.745833333333-0.115292658730150.0794593253968259
20102.72102.623635912698102.806666666667-0.1830307539682530.0963640873015947
21102.83102.831909722222102.865416666667-0.0335069444444475-0.00190972222220864
22102.92103.018100198413102.9154166666670.102683531746031-0.098100198412709
23103.04103.085481150794102.9591666666670.126314484126984-0.0454811507936341
24103.08103.091254960317103.0045833333330.0866716269841243-0.0112549603174728
25103.09103.07589781746103.050.02589781746031730.0141021825396876
26103.11103.087862103175103.094583333333-0.006721230158723030.0221378968253987
27103.18103.169112103175103.1433333333330.02577876984126370.0108878968254089
28103.18103.23089781746103.1970833333330.0338144841269788-0.0508978174602959
29103.22103.245004960317103.25-0.00499503968253818-0.0250049603174602
30103.25103.244052579365103.301666666667-0.05761408730158670.00594742063492504
31103.25103.237624007936103.352916666667-0.115292658730150.0123759920635109
32103.25103.221969246032103.405-0.1830307539682530.0280307539682667
33103.47103.426076388889103.459583333333-0.03350694444444750.0439236111111256
34103.57103.625183531746103.52250.102683531746031-0.0551835317460245
35103.66103.721731150794103.5954166666670.126314484126984-0.0617311507936478
36103.7103.758338293651103.6716666666670.0866716269841243-0.0583382936507917
37103.7103.77464781746103.748750.0258978174603173-0.0746478174603027
38103.75103.820362103175103.827083333333-0.00672123015872303-0.0703621031746025
39103.85103.935362103175103.9095833333330.0257787698412637-0.085362103174603
40104.02104.036731150794104.0029166666670.0338144841269788-0.0167311507936461
41104.13104.099171626984104.104166666667-0.004995039682538180.0308283730158792
42104.17104.146969246032104.204583333333-0.05761408730158670.0230307539682713
43104.18104.188874007936104.304166666667-0.11529265873015-0.00887400793648396
44104.2104.221135912698104.404166666667-0.183030753968253-0.0211359126984263
45104.5104.478576388889104.512083333333-0.03350694444444750.0214236111111177
46104.78104.728100198413104.6254166666670.1026835317460310.0518998015873109
47104.88104.861731150794104.7354166666670.1263144841269840.0182688492063363
48104.89104.930421626984104.843750.0866716269841243-0.0404216269841271
49104.9104.97714781746104.951250.0258978174603173-0.0771478174603146
50104.95105.051612103175105.058333333333-0.00672123015872303-0.101612103174588
51105.24105.189528769841105.163750.02577876984126370.0504712301587347
52105.35105.30464781746105.2708333333330.03381448412697880.0453521825396876
53105.44105.375421626984105.380416666667-0.004995039682538180.0645783730158627
54105.46105.433219246032105.490833333333-0.05761408730158670.0267807539682394
55105.47105.48720734127105.6025-0.11529265873015-0.0172073412698381
56105.48105.529469246032105.7125-0.183030753968253-0.0494692460317196
57105.75105.779409722222105.812916666667-0.0335069444444475-0.0294097222221978
58106.1106.008933531746105.906250.1026835317460310.0910664682539846
59106.19106.12464781746105.9983333333330.1263144841269840.0653521825396979
60106.23106.175421626984106.088750.08667162698412430.054578373015886
61106.24106.205064484127106.1791666666670.02589781746031730.0349355158730162
62106.25106.262445436508106.269166666667-0.00672123015872303-0.0124454365079174
63106.35106.387445436508106.3616666666670.0257787698412637-0.0374454365079231
64106.48106.484231150794106.4504166666670.0338144841269788-0.0042311507936148
65106.52106.530421626984106.535416666667-0.00499503968253818-0.0104216269841118
66106.55106.565302579365106.622916666667-0.0576140873015867-0.0153025793650698
67106.55106.595540674603106.710833333333-0.11529265873015-0.0455406746031599
68106.56106.616135912698106.799166666667-0.183030753968253-0.0561359126983945
69106.89106.856493055556106.89-0.03350694444444750.0335069444444684
70107.09107.075600198413106.9729166666670.1026835317460310.0143998015873308
71107.24107.16839781746107.0420833333330.1263144841269840.0716021825397064
72107.28107.193754960317107.1070833333330.08667162698412430.0862450396825665
73107.3107.19714781746107.171250.02589781746031730.102852182539706
74107.31107.229112103175107.235833333333-0.006721230158723030.0808878968254021
75107.47107.320778769841107.2950.02577876984126370.149221230158744
76107.35107.381731150794107.3479166666670.0338144841269788-0.0317311507936466
77107.31107.390421626984107.395416666667-0.00499503968253818-0.0804216269840907
78107.32107.380302579365107.437916666667-0.0576140873015867-0.0603025793650716
79107.32107.365124007936107.480416666667-0.11529265873015-0.0451240079364936
80107.34107.343219246032107.52625-0.183030753968253-0.00321924603173329
81107.53107.531076388889107.564583333333-0.0335069444444475-0.00107638888886186
82107.72107.702266865079107.5995833333330.1026835317460310.0177331349206753
83107.75107.767564484127107.641250.126314484126984-0.0175644841269644
84107.79107.765838293651107.6791666666670.08667162698412430.0241617063492043
85107.81107.740481150794107.7145833333330.02589781746031730.0695188492063465
86107.9107.746195436508107.752916666667-0.006721230158723030.153804563492059
87107.8107.810362103175107.7845833333330.0257787698412637-0.0103621031746144
88107.86107.83339781746107.7995833333330.03381448412697880.0266021825396763
89107.8107.802921626984107.807916666667-0.00499503968253818-0.00292162698411857
90107.74107.756552579365107.814166666667-0.0576140873015867-0.0165525793650545
91107.75NANA-0.11529265873015NA
92107.83NANA-0.183030753968253NA
93107.8NANA-0.0335069444444475NA
94107.81NANA0.102683531746031NA
95107.86NANA0.126314484126984NA
96107.83NANA0.0866716269841243NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 101.02 & NA & NA & 0.0258978174603173 & NA \tabularnewline
2 & 101.15 & NA & NA & -0.00672123015872303 & NA \tabularnewline
3 & 101.51 & NA & NA & 0.0257787698412637 & NA \tabularnewline
4 & 101.75 & NA & NA & 0.0338144841269788 & NA \tabularnewline
5 & 101.8 & NA & NA & -0.00499503968253818 & NA \tabularnewline
6 & 101.8 & NA & NA & -0.0576140873015867 & NA \tabularnewline
7 & 101.8 & 101.73845734127 & 101.85375 & -0.11529265873015 & 0.0615426587301755 \tabularnewline
8 & 101.82 & 101.777802579365 & 101.960833333333 & -0.183030753968253 & 0.0421974206349205 \tabularnewline
9 & 101.99 & 102.019826388889 & 102.053333333333 & -0.0335069444444475 & -0.0298263888888926 \tabularnewline
10 & 102.25 & 102.235183531746 & 102.1325 & 0.102683531746031 & 0.0148164682539829 \tabularnewline
11 & 102.34 & 102.333814484127 & 102.2075 & 0.126314484126984 & 0.00618551587304239 \tabularnewline
12 & 102.35 & 102.368338293651 & 102.281666666667 & 0.0866716269841243 & -0.0183382936507854 \tabularnewline
13 & 102.35 & 102.382981150794 & 102.357083333333 & 0.0258978174603173 & -0.0329811507936455 \tabularnewline
14 & 102.39 & 102.425778769841 & 102.4325 & -0.00672123015872303 & -0.0357787698412864 \tabularnewline
15 & 102.49 & 102.530778769841 & 102.505 & 0.0257787698412637 & -0.0407787698412676 \tabularnewline
16 & 102.67 & 102.601731150794 & 102.567916666667 & 0.0338144841269788 & 0.0682688492063477 \tabularnewline
17 & 102.68 & 102.620004960317 & 102.625 & -0.00499503968253818 & 0.0599950396825619 \tabularnewline
18 & 102.7 & 102.626969246032 & 102.684583333333 & -0.0576140873015867 & 0.0730307539682684 \tabularnewline
19 & 102.71 & 102.630540674603 & 102.745833333333 & -0.11529265873015 & 0.0794593253968259 \tabularnewline
20 & 102.72 & 102.623635912698 & 102.806666666667 & -0.183030753968253 & 0.0963640873015947 \tabularnewline
21 & 102.83 & 102.831909722222 & 102.865416666667 & -0.0335069444444475 & -0.00190972222220864 \tabularnewline
22 & 102.92 & 103.018100198413 & 102.915416666667 & 0.102683531746031 & -0.098100198412709 \tabularnewline
23 & 103.04 & 103.085481150794 & 102.959166666667 & 0.126314484126984 & -0.0454811507936341 \tabularnewline
24 & 103.08 & 103.091254960317 & 103.004583333333 & 0.0866716269841243 & -0.0112549603174728 \tabularnewline
25 & 103.09 & 103.07589781746 & 103.05 & 0.0258978174603173 & 0.0141021825396876 \tabularnewline
26 & 103.11 & 103.087862103175 & 103.094583333333 & -0.00672123015872303 & 0.0221378968253987 \tabularnewline
27 & 103.18 & 103.169112103175 & 103.143333333333 & 0.0257787698412637 & 0.0108878968254089 \tabularnewline
28 & 103.18 & 103.23089781746 & 103.197083333333 & 0.0338144841269788 & -0.0508978174602959 \tabularnewline
29 & 103.22 & 103.245004960317 & 103.25 & -0.00499503968253818 & -0.0250049603174602 \tabularnewline
30 & 103.25 & 103.244052579365 & 103.301666666667 & -0.0576140873015867 & 0.00594742063492504 \tabularnewline
31 & 103.25 & 103.237624007936 & 103.352916666667 & -0.11529265873015 & 0.0123759920635109 \tabularnewline
32 & 103.25 & 103.221969246032 & 103.405 & -0.183030753968253 & 0.0280307539682667 \tabularnewline
33 & 103.47 & 103.426076388889 & 103.459583333333 & -0.0335069444444475 & 0.0439236111111256 \tabularnewline
34 & 103.57 & 103.625183531746 & 103.5225 & 0.102683531746031 & -0.0551835317460245 \tabularnewline
35 & 103.66 & 103.721731150794 & 103.595416666667 & 0.126314484126984 & -0.0617311507936478 \tabularnewline
36 & 103.7 & 103.758338293651 & 103.671666666667 & 0.0866716269841243 & -0.0583382936507917 \tabularnewline
37 & 103.7 & 103.77464781746 & 103.74875 & 0.0258978174603173 & -0.0746478174603027 \tabularnewline
38 & 103.75 & 103.820362103175 & 103.827083333333 & -0.00672123015872303 & -0.0703621031746025 \tabularnewline
39 & 103.85 & 103.935362103175 & 103.909583333333 & 0.0257787698412637 & -0.085362103174603 \tabularnewline
40 & 104.02 & 104.036731150794 & 104.002916666667 & 0.0338144841269788 & -0.0167311507936461 \tabularnewline
41 & 104.13 & 104.099171626984 & 104.104166666667 & -0.00499503968253818 & 0.0308283730158792 \tabularnewline
42 & 104.17 & 104.146969246032 & 104.204583333333 & -0.0576140873015867 & 0.0230307539682713 \tabularnewline
43 & 104.18 & 104.188874007936 & 104.304166666667 & -0.11529265873015 & -0.00887400793648396 \tabularnewline
44 & 104.2 & 104.221135912698 & 104.404166666667 & -0.183030753968253 & -0.0211359126984263 \tabularnewline
45 & 104.5 & 104.478576388889 & 104.512083333333 & -0.0335069444444475 & 0.0214236111111177 \tabularnewline
46 & 104.78 & 104.728100198413 & 104.625416666667 & 0.102683531746031 & 0.0518998015873109 \tabularnewline
47 & 104.88 & 104.861731150794 & 104.735416666667 & 0.126314484126984 & 0.0182688492063363 \tabularnewline
48 & 104.89 & 104.930421626984 & 104.84375 & 0.0866716269841243 & -0.0404216269841271 \tabularnewline
49 & 104.9 & 104.97714781746 & 104.95125 & 0.0258978174603173 & -0.0771478174603146 \tabularnewline
50 & 104.95 & 105.051612103175 & 105.058333333333 & -0.00672123015872303 & -0.101612103174588 \tabularnewline
51 & 105.24 & 105.189528769841 & 105.16375 & 0.0257787698412637 & 0.0504712301587347 \tabularnewline
52 & 105.35 & 105.30464781746 & 105.270833333333 & 0.0338144841269788 & 0.0453521825396876 \tabularnewline
53 & 105.44 & 105.375421626984 & 105.380416666667 & -0.00499503968253818 & 0.0645783730158627 \tabularnewline
54 & 105.46 & 105.433219246032 & 105.490833333333 & -0.0576140873015867 & 0.0267807539682394 \tabularnewline
55 & 105.47 & 105.48720734127 & 105.6025 & -0.11529265873015 & -0.0172073412698381 \tabularnewline
56 & 105.48 & 105.529469246032 & 105.7125 & -0.183030753968253 & -0.0494692460317196 \tabularnewline
57 & 105.75 & 105.779409722222 & 105.812916666667 & -0.0335069444444475 & -0.0294097222221978 \tabularnewline
58 & 106.1 & 106.008933531746 & 105.90625 & 0.102683531746031 & 0.0910664682539846 \tabularnewline
59 & 106.19 & 106.12464781746 & 105.998333333333 & 0.126314484126984 & 0.0653521825396979 \tabularnewline
60 & 106.23 & 106.175421626984 & 106.08875 & 0.0866716269841243 & 0.054578373015886 \tabularnewline
61 & 106.24 & 106.205064484127 & 106.179166666667 & 0.0258978174603173 & 0.0349355158730162 \tabularnewline
62 & 106.25 & 106.262445436508 & 106.269166666667 & -0.00672123015872303 & -0.0124454365079174 \tabularnewline
63 & 106.35 & 106.387445436508 & 106.361666666667 & 0.0257787698412637 & -0.0374454365079231 \tabularnewline
64 & 106.48 & 106.484231150794 & 106.450416666667 & 0.0338144841269788 & -0.0042311507936148 \tabularnewline
65 & 106.52 & 106.530421626984 & 106.535416666667 & -0.00499503968253818 & -0.0104216269841118 \tabularnewline
66 & 106.55 & 106.565302579365 & 106.622916666667 & -0.0576140873015867 & -0.0153025793650698 \tabularnewline
67 & 106.55 & 106.595540674603 & 106.710833333333 & -0.11529265873015 & -0.0455406746031599 \tabularnewline
68 & 106.56 & 106.616135912698 & 106.799166666667 & -0.183030753968253 & -0.0561359126983945 \tabularnewline
69 & 106.89 & 106.856493055556 & 106.89 & -0.0335069444444475 & 0.0335069444444684 \tabularnewline
70 & 107.09 & 107.075600198413 & 106.972916666667 & 0.102683531746031 & 0.0143998015873308 \tabularnewline
71 & 107.24 & 107.16839781746 & 107.042083333333 & 0.126314484126984 & 0.0716021825397064 \tabularnewline
72 & 107.28 & 107.193754960317 & 107.107083333333 & 0.0866716269841243 & 0.0862450396825665 \tabularnewline
73 & 107.3 & 107.19714781746 & 107.17125 & 0.0258978174603173 & 0.102852182539706 \tabularnewline
74 & 107.31 & 107.229112103175 & 107.235833333333 & -0.00672123015872303 & 0.0808878968254021 \tabularnewline
75 & 107.47 & 107.320778769841 & 107.295 & 0.0257787698412637 & 0.149221230158744 \tabularnewline
76 & 107.35 & 107.381731150794 & 107.347916666667 & 0.0338144841269788 & -0.0317311507936466 \tabularnewline
77 & 107.31 & 107.390421626984 & 107.395416666667 & -0.00499503968253818 & -0.0804216269840907 \tabularnewline
78 & 107.32 & 107.380302579365 & 107.437916666667 & -0.0576140873015867 & -0.0603025793650716 \tabularnewline
79 & 107.32 & 107.365124007936 & 107.480416666667 & -0.11529265873015 & -0.0451240079364936 \tabularnewline
80 & 107.34 & 107.343219246032 & 107.52625 & -0.183030753968253 & -0.00321924603173329 \tabularnewline
81 & 107.53 & 107.531076388889 & 107.564583333333 & -0.0335069444444475 & -0.00107638888886186 \tabularnewline
82 & 107.72 & 107.702266865079 & 107.599583333333 & 0.102683531746031 & 0.0177331349206753 \tabularnewline
83 & 107.75 & 107.767564484127 & 107.64125 & 0.126314484126984 & -0.0175644841269644 \tabularnewline
84 & 107.79 & 107.765838293651 & 107.679166666667 & 0.0866716269841243 & 0.0241617063492043 \tabularnewline
85 & 107.81 & 107.740481150794 & 107.714583333333 & 0.0258978174603173 & 0.0695188492063465 \tabularnewline
86 & 107.9 & 107.746195436508 & 107.752916666667 & -0.00672123015872303 & 0.153804563492059 \tabularnewline
87 & 107.8 & 107.810362103175 & 107.784583333333 & 0.0257787698412637 & -0.0103621031746144 \tabularnewline
88 & 107.86 & 107.83339781746 & 107.799583333333 & 0.0338144841269788 & 0.0266021825396763 \tabularnewline
89 & 107.8 & 107.802921626984 & 107.807916666667 & -0.00499503968253818 & -0.00292162698411857 \tabularnewline
90 & 107.74 & 107.756552579365 & 107.814166666667 & -0.0576140873015867 & -0.0165525793650545 \tabularnewline
91 & 107.75 & NA & NA & -0.11529265873015 & NA \tabularnewline
92 & 107.83 & NA & NA & -0.183030753968253 & NA \tabularnewline
93 & 107.8 & NA & NA & -0.0335069444444475 & NA \tabularnewline
94 & 107.81 & NA & NA & 0.102683531746031 & NA \tabularnewline
95 & 107.86 & NA & NA & 0.126314484126984 & NA \tabularnewline
96 & 107.83 & NA & NA & 0.0866716269841243 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110098&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]101.02[/C][C]NA[/C][C]NA[/C][C]0.0258978174603173[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]101.15[/C][C]NA[/C][C]NA[/C][C]-0.00672123015872303[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]101.51[/C][C]NA[/C][C]NA[/C][C]0.0257787698412637[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]101.75[/C][C]NA[/C][C]NA[/C][C]0.0338144841269788[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]101.8[/C][C]NA[/C][C]NA[/C][C]-0.00499503968253818[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]101.8[/C][C]NA[/C][C]NA[/C][C]-0.0576140873015867[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]101.8[/C][C]101.73845734127[/C][C]101.85375[/C][C]-0.11529265873015[/C][C]0.0615426587301755[/C][/ROW]
[ROW][C]8[/C][C]101.82[/C][C]101.777802579365[/C][C]101.960833333333[/C][C]-0.183030753968253[/C][C]0.0421974206349205[/C][/ROW]
[ROW][C]9[/C][C]101.99[/C][C]102.019826388889[/C][C]102.053333333333[/C][C]-0.0335069444444475[/C][C]-0.0298263888888926[/C][/ROW]
[ROW][C]10[/C][C]102.25[/C][C]102.235183531746[/C][C]102.1325[/C][C]0.102683531746031[/C][C]0.0148164682539829[/C][/ROW]
[ROW][C]11[/C][C]102.34[/C][C]102.333814484127[/C][C]102.2075[/C][C]0.126314484126984[/C][C]0.00618551587304239[/C][/ROW]
[ROW][C]12[/C][C]102.35[/C][C]102.368338293651[/C][C]102.281666666667[/C][C]0.0866716269841243[/C][C]-0.0183382936507854[/C][/ROW]
[ROW][C]13[/C][C]102.35[/C][C]102.382981150794[/C][C]102.357083333333[/C][C]0.0258978174603173[/C][C]-0.0329811507936455[/C][/ROW]
[ROW][C]14[/C][C]102.39[/C][C]102.425778769841[/C][C]102.4325[/C][C]-0.00672123015872303[/C][C]-0.0357787698412864[/C][/ROW]
[ROW][C]15[/C][C]102.49[/C][C]102.530778769841[/C][C]102.505[/C][C]0.0257787698412637[/C][C]-0.0407787698412676[/C][/ROW]
[ROW][C]16[/C][C]102.67[/C][C]102.601731150794[/C][C]102.567916666667[/C][C]0.0338144841269788[/C][C]0.0682688492063477[/C][/ROW]
[ROW][C]17[/C][C]102.68[/C][C]102.620004960317[/C][C]102.625[/C][C]-0.00499503968253818[/C][C]0.0599950396825619[/C][/ROW]
[ROW][C]18[/C][C]102.7[/C][C]102.626969246032[/C][C]102.684583333333[/C][C]-0.0576140873015867[/C][C]0.0730307539682684[/C][/ROW]
[ROW][C]19[/C][C]102.71[/C][C]102.630540674603[/C][C]102.745833333333[/C][C]-0.11529265873015[/C][C]0.0794593253968259[/C][/ROW]
[ROW][C]20[/C][C]102.72[/C][C]102.623635912698[/C][C]102.806666666667[/C][C]-0.183030753968253[/C][C]0.0963640873015947[/C][/ROW]
[ROW][C]21[/C][C]102.83[/C][C]102.831909722222[/C][C]102.865416666667[/C][C]-0.0335069444444475[/C][C]-0.00190972222220864[/C][/ROW]
[ROW][C]22[/C][C]102.92[/C][C]103.018100198413[/C][C]102.915416666667[/C][C]0.102683531746031[/C][C]-0.098100198412709[/C][/ROW]
[ROW][C]23[/C][C]103.04[/C][C]103.085481150794[/C][C]102.959166666667[/C][C]0.126314484126984[/C][C]-0.0454811507936341[/C][/ROW]
[ROW][C]24[/C][C]103.08[/C][C]103.091254960317[/C][C]103.004583333333[/C][C]0.0866716269841243[/C][C]-0.0112549603174728[/C][/ROW]
[ROW][C]25[/C][C]103.09[/C][C]103.07589781746[/C][C]103.05[/C][C]0.0258978174603173[/C][C]0.0141021825396876[/C][/ROW]
[ROW][C]26[/C][C]103.11[/C][C]103.087862103175[/C][C]103.094583333333[/C][C]-0.00672123015872303[/C][C]0.0221378968253987[/C][/ROW]
[ROW][C]27[/C][C]103.18[/C][C]103.169112103175[/C][C]103.143333333333[/C][C]0.0257787698412637[/C][C]0.0108878968254089[/C][/ROW]
[ROW][C]28[/C][C]103.18[/C][C]103.23089781746[/C][C]103.197083333333[/C][C]0.0338144841269788[/C][C]-0.0508978174602959[/C][/ROW]
[ROW][C]29[/C][C]103.22[/C][C]103.245004960317[/C][C]103.25[/C][C]-0.00499503968253818[/C][C]-0.0250049603174602[/C][/ROW]
[ROW][C]30[/C][C]103.25[/C][C]103.244052579365[/C][C]103.301666666667[/C][C]-0.0576140873015867[/C][C]0.00594742063492504[/C][/ROW]
[ROW][C]31[/C][C]103.25[/C][C]103.237624007936[/C][C]103.352916666667[/C][C]-0.11529265873015[/C][C]0.0123759920635109[/C][/ROW]
[ROW][C]32[/C][C]103.25[/C][C]103.221969246032[/C][C]103.405[/C][C]-0.183030753968253[/C][C]0.0280307539682667[/C][/ROW]
[ROW][C]33[/C][C]103.47[/C][C]103.426076388889[/C][C]103.459583333333[/C][C]-0.0335069444444475[/C][C]0.0439236111111256[/C][/ROW]
[ROW][C]34[/C][C]103.57[/C][C]103.625183531746[/C][C]103.5225[/C][C]0.102683531746031[/C][C]-0.0551835317460245[/C][/ROW]
[ROW][C]35[/C][C]103.66[/C][C]103.721731150794[/C][C]103.595416666667[/C][C]0.126314484126984[/C][C]-0.0617311507936478[/C][/ROW]
[ROW][C]36[/C][C]103.7[/C][C]103.758338293651[/C][C]103.671666666667[/C][C]0.0866716269841243[/C][C]-0.0583382936507917[/C][/ROW]
[ROW][C]37[/C][C]103.7[/C][C]103.77464781746[/C][C]103.74875[/C][C]0.0258978174603173[/C][C]-0.0746478174603027[/C][/ROW]
[ROW][C]38[/C][C]103.75[/C][C]103.820362103175[/C][C]103.827083333333[/C][C]-0.00672123015872303[/C][C]-0.0703621031746025[/C][/ROW]
[ROW][C]39[/C][C]103.85[/C][C]103.935362103175[/C][C]103.909583333333[/C][C]0.0257787698412637[/C][C]-0.085362103174603[/C][/ROW]
[ROW][C]40[/C][C]104.02[/C][C]104.036731150794[/C][C]104.002916666667[/C][C]0.0338144841269788[/C][C]-0.0167311507936461[/C][/ROW]
[ROW][C]41[/C][C]104.13[/C][C]104.099171626984[/C][C]104.104166666667[/C][C]-0.00499503968253818[/C][C]0.0308283730158792[/C][/ROW]
[ROW][C]42[/C][C]104.17[/C][C]104.146969246032[/C][C]104.204583333333[/C][C]-0.0576140873015867[/C][C]0.0230307539682713[/C][/ROW]
[ROW][C]43[/C][C]104.18[/C][C]104.188874007936[/C][C]104.304166666667[/C][C]-0.11529265873015[/C][C]-0.00887400793648396[/C][/ROW]
[ROW][C]44[/C][C]104.2[/C][C]104.221135912698[/C][C]104.404166666667[/C][C]-0.183030753968253[/C][C]-0.0211359126984263[/C][/ROW]
[ROW][C]45[/C][C]104.5[/C][C]104.478576388889[/C][C]104.512083333333[/C][C]-0.0335069444444475[/C][C]0.0214236111111177[/C][/ROW]
[ROW][C]46[/C][C]104.78[/C][C]104.728100198413[/C][C]104.625416666667[/C][C]0.102683531746031[/C][C]0.0518998015873109[/C][/ROW]
[ROW][C]47[/C][C]104.88[/C][C]104.861731150794[/C][C]104.735416666667[/C][C]0.126314484126984[/C][C]0.0182688492063363[/C][/ROW]
[ROW][C]48[/C][C]104.89[/C][C]104.930421626984[/C][C]104.84375[/C][C]0.0866716269841243[/C][C]-0.0404216269841271[/C][/ROW]
[ROW][C]49[/C][C]104.9[/C][C]104.97714781746[/C][C]104.95125[/C][C]0.0258978174603173[/C][C]-0.0771478174603146[/C][/ROW]
[ROW][C]50[/C][C]104.95[/C][C]105.051612103175[/C][C]105.058333333333[/C][C]-0.00672123015872303[/C][C]-0.101612103174588[/C][/ROW]
[ROW][C]51[/C][C]105.24[/C][C]105.189528769841[/C][C]105.16375[/C][C]0.0257787698412637[/C][C]0.0504712301587347[/C][/ROW]
[ROW][C]52[/C][C]105.35[/C][C]105.30464781746[/C][C]105.270833333333[/C][C]0.0338144841269788[/C][C]0.0453521825396876[/C][/ROW]
[ROW][C]53[/C][C]105.44[/C][C]105.375421626984[/C][C]105.380416666667[/C][C]-0.00499503968253818[/C][C]0.0645783730158627[/C][/ROW]
[ROW][C]54[/C][C]105.46[/C][C]105.433219246032[/C][C]105.490833333333[/C][C]-0.0576140873015867[/C][C]0.0267807539682394[/C][/ROW]
[ROW][C]55[/C][C]105.47[/C][C]105.48720734127[/C][C]105.6025[/C][C]-0.11529265873015[/C][C]-0.0172073412698381[/C][/ROW]
[ROW][C]56[/C][C]105.48[/C][C]105.529469246032[/C][C]105.7125[/C][C]-0.183030753968253[/C][C]-0.0494692460317196[/C][/ROW]
[ROW][C]57[/C][C]105.75[/C][C]105.779409722222[/C][C]105.812916666667[/C][C]-0.0335069444444475[/C][C]-0.0294097222221978[/C][/ROW]
[ROW][C]58[/C][C]106.1[/C][C]106.008933531746[/C][C]105.90625[/C][C]0.102683531746031[/C][C]0.0910664682539846[/C][/ROW]
[ROW][C]59[/C][C]106.19[/C][C]106.12464781746[/C][C]105.998333333333[/C][C]0.126314484126984[/C][C]0.0653521825396979[/C][/ROW]
[ROW][C]60[/C][C]106.23[/C][C]106.175421626984[/C][C]106.08875[/C][C]0.0866716269841243[/C][C]0.054578373015886[/C][/ROW]
[ROW][C]61[/C][C]106.24[/C][C]106.205064484127[/C][C]106.179166666667[/C][C]0.0258978174603173[/C][C]0.0349355158730162[/C][/ROW]
[ROW][C]62[/C][C]106.25[/C][C]106.262445436508[/C][C]106.269166666667[/C][C]-0.00672123015872303[/C][C]-0.0124454365079174[/C][/ROW]
[ROW][C]63[/C][C]106.35[/C][C]106.387445436508[/C][C]106.361666666667[/C][C]0.0257787698412637[/C][C]-0.0374454365079231[/C][/ROW]
[ROW][C]64[/C][C]106.48[/C][C]106.484231150794[/C][C]106.450416666667[/C][C]0.0338144841269788[/C][C]-0.0042311507936148[/C][/ROW]
[ROW][C]65[/C][C]106.52[/C][C]106.530421626984[/C][C]106.535416666667[/C][C]-0.00499503968253818[/C][C]-0.0104216269841118[/C][/ROW]
[ROW][C]66[/C][C]106.55[/C][C]106.565302579365[/C][C]106.622916666667[/C][C]-0.0576140873015867[/C][C]-0.0153025793650698[/C][/ROW]
[ROW][C]67[/C][C]106.55[/C][C]106.595540674603[/C][C]106.710833333333[/C][C]-0.11529265873015[/C][C]-0.0455406746031599[/C][/ROW]
[ROW][C]68[/C][C]106.56[/C][C]106.616135912698[/C][C]106.799166666667[/C][C]-0.183030753968253[/C][C]-0.0561359126983945[/C][/ROW]
[ROW][C]69[/C][C]106.89[/C][C]106.856493055556[/C][C]106.89[/C][C]-0.0335069444444475[/C][C]0.0335069444444684[/C][/ROW]
[ROW][C]70[/C][C]107.09[/C][C]107.075600198413[/C][C]106.972916666667[/C][C]0.102683531746031[/C][C]0.0143998015873308[/C][/ROW]
[ROW][C]71[/C][C]107.24[/C][C]107.16839781746[/C][C]107.042083333333[/C][C]0.126314484126984[/C][C]0.0716021825397064[/C][/ROW]
[ROW][C]72[/C][C]107.28[/C][C]107.193754960317[/C][C]107.107083333333[/C][C]0.0866716269841243[/C][C]0.0862450396825665[/C][/ROW]
[ROW][C]73[/C][C]107.3[/C][C]107.19714781746[/C][C]107.17125[/C][C]0.0258978174603173[/C][C]0.102852182539706[/C][/ROW]
[ROW][C]74[/C][C]107.31[/C][C]107.229112103175[/C][C]107.235833333333[/C][C]-0.00672123015872303[/C][C]0.0808878968254021[/C][/ROW]
[ROW][C]75[/C][C]107.47[/C][C]107.320778769841[/C][C]107.295[/C][C]0.0257787698412637[/C][C]0.149221230158744[/C][/ROW]
[ROW][C]76[/C][C]107.35[/C][C]107.381731150794[/C][C]107.347916666667[/C][C]0.0338144841269788[/C][C]-0.0317311507936466[/C][/ROW]
[ROW][C]77[/C][C]107.31[/C][C]107.390421626984[/C][C]107.395416666667[/C][C]-0.00499503968253818[/C][C]-0.0804216269840907[/C][/ROW]
[ROW][C]78[/C][C]107.32[/C][C]107.380302579365[/C][C]107.437916666667[/C][C]-0.0576140873015867[/C][C]-0.0603025793650716[/C][/ROW]
[ROW][C]79[/C][C]107.32[/C][C]107.365124007936[/C][C]107.480416666667[/C][C]-0.11529265873015[/C][C]-0.0451240079364936[/C][/ROW]
[ROW][C]80[/C][C]107.34[/C][C]107.343219246032[/C][C]107.52625[/C][C]-0.183030753968253[/C][C]-0.00321924603173329[/C][/ROW]
[ROW][C]81[/C][C]107.53[/C][C]107.531076388889[/C][C]107.564583333333[/C][C]-0.0335069444444475[/C][C]-0.00107638888886186[/C][/ROW]
[ROW][C]82[/C][C]107.72[/C][C]107.702266865079[/C][C]107.599583333333[/C][C]0.102683531746031[/C][C]0.0177331349206753[/C][/ROW]
[ROW][C]83[/C][C]107.75[/C][C]107.767564484127[/C][C]107.64125[/C][C]0.126314484126984[/C][C]-0.0175644841269644[/C][/ROW]
[ROW][C]84[/C][C]107.79[/C][C]107.765838293651[/C][C]107.679166666667[/C][C]0.0866716269841243[/C][C]0.0241617063492043[/C][/ROW]
[ROW][C]85[/C][C]107.81[/C][C]107.740481150794[/C][C]107.714583333333[/C][C]0.0258978174603173[/C][C]0.0695188492063465[/C][/ROW]
[ROW][C]86[/C][C]107.9[/C][C]107.746195436508[/C][C]107.752916666667[/C][C]-0.00672123015872303[/C][C]0.153804563492059[/C][/ROW]
[ROW][C]87[/C][C]107.8[/C][C]107.810362103175[/C][C]107.784583333333[/C][C]0.0257787698412637[/C][C]-0.0103621031746144[/C][/ROW]
[ROW][C]88[/C][C]107.86[/C][C]107.83339781746[/C][C]107.799583333333[/C][C]0.0338144841269788[/C][C]0.0266021825396763[/C][/ROW]
[ROW][C]89[/C][C]107.8[/C][C]107.802921626984[/C][C]107.807916666667[/C][C]-0.00499503968253818[/C][C]-0.00292162698411857[/C][/ROW]
[ROW][C]90[/C][C]107.74[/C][C]107.756552579365[/C][C]107.814166666667[/C][C]-0.0576140873015867[/C][C]-0.0165525793650545[/C][/ROW]
[ROW][C]91[/C][C]107.75[/C][C]NA[/C][C]NA[/C][C]-0.11529265873015[/C][C]NA[/C][/ROW]
[ROW][C]92[/C][C]107.83[/C][C]NA[/C][C]NA[/C][C]-0.183030753968253[/C][C]NA[/C][/ROW]
[ROW][C]93[/C][C]107.8[/C][C]NA[/C][C]NA[/C][C]-0.0335069444444475[/C][C]NA[/C][/ROW]
[ROW][C]94[/C][C]107.81[/C][C]NA[/C][C]NA[/C][C]0.102683531746031[/C][C]NA[/C][/ROW]
[ROW][C]95[/C][C]107.86[/C][C]NA[/C][C]NA[/C][C]0.126314484126984[/C][C]NA[/C][/ROW]
[ROW][C]96[/C][C]107.83[/C][C]NA[/C][C]NA[/C][C]0.0866716269841243[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110098&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110098&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
1101.02NANA0.0258978174603173NA
2101.15NANA-0.00672123015872303NA
3101.51NANA0.0257787698412637NA
4101.75NANA0.0338144841269788NA
5101.8NANA-0.00499503968253818NA
6101.8NANA-0.0576140873015867NA
7101.8101.73845734127101.85375-0.115292658730150.0615426587301755
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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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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')