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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSat, 18 Dec 2010 18:38:08 +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/18/t1292697406cv14ds07c47g1ck.htm/, Retrieved Tue, 30 Apr 2024 05:50:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112153, Retrieved Tue, 30 Apr 2024 05:50:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Classical Decomposition] [HPC Retail Sales] [2008-03-02 16:19:32] [74be16979710d4c4e7c6647856088456]
-  M D  [Classical Decomposition] [Workshop 8, Class...] [2010-11-28 20:55:54] [d946de7cca328fbcf207448a112523ab]
- R  D    [Classical Decomposition] [Paper Decompositi...] [2010-12-18 18:33:03] [3635fb7041b1998c5a1332cf9de22bce]
-    D        [Classical Decomposition] [Paper Decompositi...] [2010-12-18 18:38:08] [23a9b79f355c69a75648521a893cf584] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
130.678
120.877
137.114
134.406
120.262
130.846
120.343
98.881
115.678
120.796
94.261
89.151
119.880
131.468
155.089
149.581
122.788
143.900
112.115
109.600
117.446
118.456
101.901
89.940
129.143
126.102
143.048
142.258
131.011
146.471
114.073
114.642
118.226
111.338
108.701
80.512
146.865
137.179
166.536
137.070
127.090
139.966
122.243
109.097
116.591
111.964
109.754
77.609
138.445
127.901
156.615
133.264
143.521
152.139
131.523
113.925
86.495
127.877
107.017
78.716
138.278
144.238
143.679
159.932
136.781
148.173
125.673
105.573
122.405
128.045
94.467
85.573
121.501
125.074
144.979
142.120
124.213
144.407
125.170
109.267
122.354
122.589
104.982
90.542

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=112153&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=112153&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112153&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
1130.678NANA8.5238420138889NA
2120.877NANA8.05986284722222NA
3137.114NANA27.6053767361111NA
4134.406NANA19.9263975694444NA
5120.262NANA6.70266145833333NA
6130.846NANA21.5605503472222NA
7120.343114.979022569444117.3245-2.345477430555565.36397743055556
898.881102.629647569444117.315875-14.6862274305556-3.74864756944444
9115.678107.923300347222118.506125-10.58282465277787.75469965277779
10120.796116.135529513889119.887375-3.751845486111114.66047048611112
1194.26199.729564236111120.624916666667-20.8953524305556-5.46856423611109
1289.15181.1571197916666121.274083333333-40.11696354166677.99388020833335
13119.88129.999008680556121.4751666666678.5238420138889-10.1190086805556
14131.468129.638821180556121.5789583333338.059862847222221.82917881944445
15155.089149.704626736111122.0992527.60537673611115.38437326388889
16149.581142.001814236111122.07541666666719.92639756944447.57918576388889
17122.788128.998911458333122.296256.70266145833333-6.21091145833333
18143.9144.208008680556122.64745833333321.5605503472222-0.30800868055556
19112.115120.720814236111123.066291666667-2.34547743055556-8.60581423611112
20109.6108.542439236111123.228666666667-14.68622743055561.05756076388889
21117.446111.920550347222122.503375-10.58282465277785.52544965277778
22118.456117.944696180556121.696541666667-3.751845486111110.511303819444436
23101.901100.838689236111121.734041666667-20.89535243055561.06231076388887
2489.9482.066828125122.183791666667-40.11696354166677.873171875
25129.143130.896342013889122.37258.5238420138889-1.7533420138889
26126.102130.724029513889122.6641666666678.05986284722222-4.62202951388886
27143.048150.512126736111122.9067527.6053767361111-7.4641267361111
28142.258142.569064236111122.64266666666719.9263975694444-0.311064236111093
29131.011129.332078125122.6294166666676.702661458333331.67892187500001
30146.471144.080467013889122.51991666666721.56055034722222.39053298611113
31114.073120.520022569444122.8655-2.34547743055556-6.44702256944443
32114.642109.379230902778124.065458333333-14.68622743055565.26276909722223
33118.226114.922842013889125.505666666667-10.58282465277783.30315798611113
34111.338122.516321180556126.268166666667-3.75184548611111-11.1783211805556
35108.701104.993272569444125.888625-20.89535243055563.70772743055556
3680.51285.3372447916666125.454208333333-40.1169635416667-4.82524479166665
37146.865134.047425347222125.5235833333338.523842013888912.8175746527778
38137.179133.692821180556125.6329583333338.059862847222223.48617881944443
39166.536152.939168402778125.33379166666727.605376736111113.5968315972222
40137.07145.218147569444125.2917519.9263975694444-8.14814756944443
41127.09132.064369791667125.3617083333336.70266145833333-4.97436979166665
42139.966146.845175347222125.28462521.5605503472222-6.8791753472222
43122.243122.467355902778124.812833333333-2.34547743055556-0.224355902777774
44109.097109.389189236111124.075416666667-14.6862274305556-0.292189236111085
45116.591112.692633680556123.275458333333-10.58282465277783.89836631944446
46111.964118.951654513889122.7035-3.75184548611111-6.98765451388888
47109.754102.334189236111123.229541666667-20.89535243055567.41981076388892
4877.60984.3044114583333124.421375-40.1169635416667-6.69541145833331
49138.445133.839092013889125.315258.52384201388894.60590798611112
50127.901133.962946180556125.9030833333338.05986284722222-6.06194618055552
51156.615152.455626736111124.8502527.60537673611114.15937326388891
52133.264144.185689236111124.25929166666719.9263975694444-10.9216892361111
53143.521131.510953125124.8082916666676.7026614583333312.010046875
54152.139146.300925347222124.74037521.56055034722225.83807465277778
55131.523122.434064236111124.779541666667-2.345477430555569.08893576388891
56113.925110.767064236111125.453291666667-14.68622743055563.15793576388893
5786.495115.012175347222125.595-10.5828246527778-28.5171753472222
58127.877122.415321180556126.167166666667-3.751845486111115.46167881944447
59107.017106.102147569444126.9975-20.89535243055560.91485243055557
6078.71686.434453125126.551416666667-40.1169635416667-7.718453125
61138.278134.666258680556126.1424166666678.52384201388893.61174131944445
62144.238133.610529513889125.5506666666678.0598628472222210.6274704861111
63143.679154.304293402778126.69891666666727.6053767361111-10.6252934027778
64159.932148.128564236111128.20216666666719.926397569444411.8034357638889
65136.781134.388911458333127.686256.702661458333332.39208854166668
66148.173149.009592013889127.44904166666721.5605503472222-0.83659201388889
67125.673124.690230902778127.035708333333-2.345477430555560.982769097222246
68105.573110.851939236111125.538166666667-14.6862274305556-5.27893923611113
69122.405114.211008680556124.793833333333-10.58282465277788.19399131944445
70128.045120.353987847222124.105833333333-3.751845486111117.69101215277777
7194.467101.944647569444122.84-20.8953524305556-7.47764756944446
7285.57382.042453125122.159416666667-40.11696354166673.530546875
73121.501130.505383680556121.9815416666678.5238420138889-9.00438368055555
74125.074130.174362847222122.11458.05986284722222-5.10036284722223
75144.979149.871668402778122.26629166666727.6053767361111-4.89266840277774
76142.12141.963230902778122.03683333333319.92639756944440.156769097222238
77124.213128.950286458333122.2476256.70266145833333-4.73728645833333
78144.407144.453342013889122.89279166666721.5605503472222-0.0463420138888893
79125.17NANA-2.34547743055556NA
80109.267NANA-14.6862274305556NA
81122.354NANA-10.5828246527778NA
82122.589NANA-3.75184548611111NA
83104.982NANA-20.8953524305556NA
8490.542NANA-40.1169635416667NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 130.678 & NA & NA & 8.5238420138889 & NA \tabularnewline
2 & 120.877 & NA & NA & 8.05986284722222 & NA \tabularnewline
3 & 137.114 & NA & NA & 27.6053767361111 & NA \tabularnewline
4 & 134.406 & NA & NA & 19.9263975694444 & NA \tabularnewline
5 & 120.262 & NA & NA & 6.70266145833333 & NA \tabularnewline
6 & 130.846 & NA & NA & 21.5605503472222 & NA \tabularnewline
7 & 120.343 & 114.979022569444 & 117.3245 & -2.34547743055556 & 5.36397743055556 \tabularnewline
8 & 98.881 & 102.629647569444 & 117.315875 & -14.6862274305556 & -3.74864756944444 \tabularnewline
9 & 115.678 & 107.923300347222 & 118.506125 & -10.5828246527778 & 7.75469965277779 \tabularnewline
10 & 120.796 & 116.135529513889 & 119.887375 & -3.75184548611111 & 4.66047048611112 \tabularnewline
11 & 94.261 & 99.729564236111 & 120.624916666667 & -20.8953524305556 & -5.46856423611109 \tabularnewline
12 & 89.151 & 81.1571197916666 & 121.274083333333 & -40.1169635416667 & 7.99388020833335 \tabularnewline
13 & 119.88 & 129.999008680556 & 121.475166666667 & 8.5238420138889 & -10.1190086805556 \tabularnewline
14 & 131.468 & 129.638821180556 & 121.578958333333 & 8.05986284722222 & 1.82917881944445 \tabularnewline
15 & 155.089 & 149.704626736111 & 122.09925 & 27.6053767361111 & 5.38437326388889 \tabularnewline
16 & 149.581 & 142.001814236111 & 122.075416666667 & 19.9263975694444 & 7.57918576388889 \tabularnewline
17 & 122.788 & 128.998911458333 & 122.29625 & 6.70266145833333 & -6.21091145833333 \tabularnewline
18 & 143.9 & 144.208008680556 & 122.647458333333 & 21.5605503472222 & -0.30800868055556 \tabularnewline
19 & 112.115 & 120.720814236111 & 123.066291666667 & -2.34547743055556 & -8.60581423611112 \tabularnewline
20 & 109.6 & 108.542439236111 & 123.228666666667 & -14.6862274305556 & 1.05756076388889 \tabularnewline
21 & 117.446 & 111.920550347222 & 122.503375 & -10.5828246527778 & 5.52544965277778 \tabularnewline
22 & 118.456 & 117.944696180556 & 121.696541666667 & -3.75184548611111 & 0.511303819444436 \tabularnewline
23 & 101.901 & 100.838689236111 & 121.734041666667 & -20.8953524305556 & 1.06231076388887 \tabularnewline
24 & 89.94 & 82.066828125 & 122.183791666667 & -40.1169635416667 & 7.873171875 \tabularnewline
25 & 129.143 & 130.896342013889 & 122.3725 & 8.5238420138889 & -1.7533420138889 \tabularnewline
26 & 126.102 & 130.724029513889 & 122.664166666667 & 8.05986284722222 & -4.62202951388886 \tabularnewline
27 & 143.048 & 150.512126736111 & 122.90675 & 27.6053767361111 & -7.4641267361111 \tabularnewline
28 & 142.258 & 142.569064236111 & 122.642666666667 & 19.9263975694444 & -0.311064236111093 \tabularnewline
29 & 131.011 & 129.332078125 & 122.629416666667 & 6.70266145833333 & 1.67892187500001 \tabularnewline
30 & 146.471 & 144.080467013889 & 122.519916666667 & 21.5605503472222 & 2.39053298611113 \tabularnewline
31 & 114.073 & 120.520022569444 & 122.8655 & -2.34547743055556 & -6.44702256944443 \tabularnewline
32 & 114.642 & 109.379230902778 & 124.065458333333 & -14.6862274305556 & 5.26276909722223 \tabularnewline
33 & 118.226 & 114.922842013889 & 125.505666666667 & -10.5828246527778 & 3.30315798611113 \tabularnewline
34 & 111.338 & 122.516321180556 & 126.268166666667 & -3.75184548611111 & -11.1783211805556 \tabularnewline
35 & 108.701 & 104.993272569444 & 125.888625 & -20.8953524305556 & 3.70772743055556 \tabularnewline
36 & 80.512 & 85.3372447916666 & 125.454208333333 & -40.1169635416667 & -4.82524479166665 \tabularnewline
37 & 146.865 & 134.047425347222 & 125.523583333333 & 8.5238420138889 & 12.8175746527778 \tabularnewline
38 & 137.179 & 133.692821180556 & 125.632958333333 & 8.05986284722222 & 3.48617881944443 \tabularnewline
39 & 166.536 & 152.939168402778 & 125.333791666667 & 27.6053767361111 & 13.5968315972222 \tabularnewline
40 & 137.07 & 145.218147569444 & 125.29175 & 19.9263975694444 & -8.14814756944443 \tabularnewline
41 & 127.09 & 132.064369791667 & 125.361708333333 & 6.70266145833333 & -4.97436979166665 \tabularnewline
42 & 139.966 & 146.845175347222 & 125.284625 & 21.5605503472222 & -6.8791753472222 \tabularnewline
43 & 122.243 & 122.467355902778 & 124.812833333333 & -2.34547743055556 & -0.224355902777774 \tabularnewline
44 & 109.097 & 109.389189236111 & 124.075416666667 & -14.6862274305556 & -0.292189236111085 \tabularnewline
45 & 116.591 & 112.692633680556 & 123.275458333333 & -10.5828246527778 & 3.89836631944446 \tabularnewline
46 & 111.964 & 118.951654513889 & 122.7035 & -3.75184548611111 & -6.98765451388888 \tabularnewline
47 & 109.754 & 102.334189236111 & 123.229541666667 & -20.8953524305556 & 7.41981076388892 \tabularnewline
48 & 77.609 & 84.3044114583333 & 124.421375 & -40.1169635416667 & -6.69541145833331 \tabularnewline
49 & 138.445 & 133.839092013889 & 125.31525 & 8.5238420138889 & 4.60590798611112 \tabularnewline
50 & 127.901 & 133.962946180556 & 125.903083333333 & 8.05986284722222 & -6.06194618055552 \tabularnewline
51 & 156.615 & 152.455626736111 & 124.85025 & 27.6053767361111 & 4.15937326388891 \tabularnewline
52 & 133.264 & 144.185689236111 & 124.259291666667 & 19.9263975694444 & -10.9216892361111 \tabularnewline
53 & 143.521 & 131.510953125 & 124.808291666667 & 6.70266145833333 & 12.010046875 \tabularnewline
54 & 152.139 & 146.300925347222 & 124.740375 & 21.5605503472222 & 5.83807465277778 \tabularnewline
55 & 131.523 & 122.434064236111 & 124.779541666667 & -2.34547743055556 & 9.08893576388891 \tabularnewline
56 & 113.925 & 110.767064236111 & 125.453291666667 & -14.6862274305556 & 3.15793576388893 \tabularnewline
57 & 86.495 & 115.012175347222 & 125.595 & -10.5828246527778 & -28.5171753472222 \tabularnewline
58 & 127.877 & 122.415321180556 & 126.167166666667 & -3.75184548611111 & 5.46167881944447 \tabularnewline
59 & 107.017 & 106.102147569444 & 126.9975 & -20.8953524305556 & 0.91485243055557 \tabularnewline
60 & 78.716 & 86.434453125 & 126.551416666667 & -40.1169635416667 & -7.718453125 \tabularnewline
61 & 138.278 & 134.666258680556 & 126.142416666667 & 8.5238420138889 & 3.61174131944445 \tabularnewline
62 & 144.238 & 133.610529513889 & 125.550666666667 & 8.05986284722222 & 10.6274704861111 \tabularnewline
63 & 143.679 & 154.304293402778 & 126.698916666667 & 27.6053767361111 & -10.6252934027778 \tabularnewline
64 & 159.932 & 148.128564236111 & 128.202166666667 & 19.9263975694444 & 11.8034357638889 \tabularnewline
65 & 136.781 & 134.388911458333 & 127.68625 & 6.70266145833333 & 2.39208854166668 \tabularnewline
66 & 148.173 & 149.009592013889 & 127.449041666667 & 21.5605503472222 & -0.83659201388889 \tabularnewline
67 & 125.673 & 124.690230902778 & 127.035708333333 & -2.34547743055556 & 0.982769097222246 \tabularnewline
68 & 105.573 & 110.851939236111 & 125.538166666667 & -14.6862274305556 & -5.27893923611113 \tabularnewline
69 & 122.405 & 114.211008680556 & 124.793833333333 & -10.5828246527778 & 8.19399131944445 \tabularnewline
70 & 128.045 & 120.353987847222 & 124.105833333333 & -3.75184548611111 & 7.69101215277777 \tabularnewline
71 & 94.467 & 101.944647569444 & 122.84 & -20.8953524305556 & -7.47764756944446 \tabularnewline
72 & 85.573 & 82.042453125 & 122.159416666667 & -40.1169635416667 & 3.530546875 \tabularnewline
73 & 121.501 & 130.505383680556 & 121.981541666667 & 8.5238420138889 & -9.00438368055555 \tabularnewline
74 & 125.074 & 130.174362847222 & 122.1145 & 8.05986284722222 & -5.10036284722223 \tabularnewline
75 & 144.979 & 149.871668402778 & 122.266291666667 & 27.6053767361111 & -4.89266840277774 \tabularnewline
76 & 142.12 & 141.963230902778 & 122.036833333333 & 19.9263975694444 & 0.156769097222238 \tabularnewline
77 & 124.213 & 128.950286458333 & 122.247625 & 6.70266145833333 & -4.73728645833333 \tabularnewline
78 & 144.407 & 144.453342013889 & 122.892791666667 & 21.5605503472222 & -0.0463420138888893 \tabularnewline
79 & 125.17 & NA & NA & -2.34547743055556 & NA \tabularnewline
80 & 109.267 & NA & NA & -14.6862274305556 & NA \tabularnewline
81 & 122.354 & NA & NA & -10.5828246527778 & NA \tabularnewline
82 & 122.589 & NA & NA & -3.75184548611111 & NA \tabularnewline
83 & 104.982 & NA & NA & -20.8953524305556 & NA \tabularnewline
84 & 90.542 & NA & NA & -40.1169635416667 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112153&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]130.678[/C][C]NA[/C][C]NA[/C][C]8.5238420138889[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]120.877[/C][C]NA[/C][C]NA[/C][C]8.05986284722222[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]137.114[/C][C]NA[/C][C]NA[/C][C]27.6053767361111[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]134.406[/C][C]NA[/C][C]NA[/C][C]19.9263975694444[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]120.262[/C][C]NA[/C][C]NA[/C][C]6.70266145833333[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]130.846[/C][C]NA[/C][C]NA[/C][C]21.5605503472222[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]120.343[/C][C]114.979022569444[/C][C]117.3245[/C][C]-2.34547743055556[/C][C]5.36397743055556[/C][/ROW]
[ROW][C]8[/C][C]98.881[/C][C]102.629647569444[/C][C]117.315875[/C][C]-14.6862274305556[/C][C]-3.74864756944444[/C][/ROW]
[ROW][C]9[/C][C]115.678[/C][C]107.923300347222[/C][C]118.506125[/C][C]-10.5828246527778[/C][C]7.75469965277779[/C][/ROW]
[ROW][C]10[/C][C]120.796[/C][C]116.135529513889[/C][C]119.887375[/C][C]-3.75184548611111[/C][C]4.66047048611112[/C][/ROW]
[ROW][C]11[/C][C]94.261[/C][C]99.729564236111[/C][C]120.624916666667[/C][C]-20.8953524305556[/C][C]-5.46856423611109[/C][/ROW]
[ROW][C]12[/C][C]89.151[/C][C]81.1571197916666[/C][C]121.274083333333[/C][C]-40.1169635416667[/C][C]7.99388020833335[/C][/ROW]
[ROW][C]13[/C][C]119.88[/C][C]129.999008680556[/C][C]121.475166666667[/C][C]8.5238420138889[/C][C]-10.1190086805556[/C][/ROW]
[ROW][C]14[/C][C]131.468[/C][C]129.638821180556[/C][C]121.578958333333[/C][C]8.05986284722222[/C][C]1.82917881944445[/C][/ROW]
[ROW][C]15[/C][C]155.089[/C][C]149.704626736111[/C][C]122.09925[/C][C]27.6053767361111[/C][C]5.38437326388889[/C][/ROW]
[ROW][C]16[/C][C]149.581[/C][C]142.001814236111[/C][C]122.075416666667[/C][C]19.9263975694444[/C][C]7.57918576388889[/C][/ROW]
[ROW][C]17[/C][C]122.788[/C][C]128.998911458333[/C][C]122.29625[/C][C]6.70266145833333[/C][C]-6.21091145833333[/C][/ROW]
[ROW][C]18[/C][C]143.9[/C][C]144.208008680556[/C][C]122.647458333333[/C][C]21.5605503472222[/C][C]-0.30800868055556[/C][/ROW]
[ROW][C]19[/C][C]112.115[/C][C]120.720814236111[/C][C]123.066291666667[/C][C]-2.34547743055556[/C][C]-8.60581423611112[/C][/ROW]
[ROW][C]20[/C][C]109.6[/C][C]108.542439236111[/C][C]123.228666666667[/C][C]-14.6862274305556[/C][C]1.05756076388889[/C][/ROW]
[ROW][C]21[/C][C]117.446[/C][C]111.920550347222[/C][C]122.503375[/C][C]-10.5828246527778[/C][C]5.52544965277778[/C][/ROW]
[ROW][C]22[/C][C]118.456[/C][C]117.944696180556[/C][C]121.696541666667[/C][C]-3.75184548611111[/C][C]0.511303819444436[/C][/ROW]
[ROW][C]23[/C][C]101.901[/C][C]100.838689236111[/C][C]121.734041666667[/C][C]-20.8953524305556[/C][C]1.06231076388887[/C][/ROW]
[ROW][C]24[/C][C]89.94[/C][C]82.066828125[/C][C]122.183791666667[/C][C]-40.1169635416667[/C][C]7.873171875[/C][/ROW]
[ROW][C]25[/C][C]129.143[/C][C]130.896342013889[/C][C]122.3725[/C][C]8.5238420138889[/C][C]-1.7533420138889[/C][/ROW]
[ROW][C]26[/C][C]126.102[/C][C]130.724029513889[/C][C]122.664166666667[/C][C]8.05986284722222[/C][C]-4.62202951388886[/C][/ROW]
[ROW][C]27[/C][C]143.048[/C][C]150.512126736111[/C][C]122.90675[/C][C]27.6053767361111[/C][C]-7.4641267361111[/C][/ROW]
[ROW][C]28[/C][C]142.258[/C][C]142.569064236111[/C][C]122.642666666667[/C][C]19.9263975694444[/C][C]-0.311064236111093[/C][/ROW]
[ROW][C]29[/C][C]131.011[/C][C]129.332078125[/C][C]122.629416666667[/C][C]6.70266145833333[/C][C]1.67892187500001[/C][/ROW]
[ROW][C]30[/C][C]146.471[/C][C]144.080467013889[/C][C]122.519916666667[/C][C]21.5605503472222[/C][C]2.39053298611113[/C][/ROW]
[ROW][C]31[/C][C]114.073[/C][C]120.520022569444[/C][C]122.8655[/C][C]-2.34547743055556[/C][C]-6.44702256944443[/C][/ROW]
[ROW][C]32[/C][C]114.642[/C][C]109.379230902778[/C][C]124.065458333333[/C][C]-14.6862274305556[/C][C]5.26276909722223[/C][/ROW]
[ROW][C]33[/C][C]118.226[/C][C]114.922842013889[/C][C]125.505666666667[/C][C]-10.5828246527778[/C][C]3.30315798611113[/C][/ROW]
[ROW][C]34[/C][C]111.338[/C][C]122.516321180556[/C][C]126.268166666667[/C][C]-3.75184548611111[/C][C]-11.1783211805556[/C][/ROW]
[ROW][C]35[/C][C]108.701[/C][C]104.993272569444[/C][C]125.888625[/C][C]-20.8953524305556[/C][C]3.70772743055556[/C][/ROW]
[ROW][C]36[/C][C]80.512[/C][C]85.3372447916666[/C][C]125.454208333333[/C][C]-40.1169635416667[/C][C]-4.82524479166665[/C][/ROW]
[ROW][C]37[/C][C]146.865[/C][C]134.047425347222[/C][C]125.523583333333[/C][C]8.5238420138889[/C][C]12.8175746527778[/C][/ROW]
[ROW][C]38[/C][C]137.179[/C][C]133.692821180556[/C][C]125.632958333333[/C][C]8.05986284722222[/C][C]3.48617881944443[/C][/ROW]
[ROW][C]39[/C][C]166.536[/C][C]152.939168402778[/C][C]125.333791666667[/C][C]27.6053767361111[/C][C]13.5968315972222[/C][/ROW]
[ROW][C]40[/C][C]137.07[/C][C]145.218147569444[/C][C]125.29175[/C][C]19.9263975694444[/C][C]-8.14814756944443[/C][/ROW]
[ROW][C]41[/C][C]127.09[/C][C]132.064369791667[/C][C]125.361708333333[/C][C]6.70266145833333[/C][C]-4.97436979166665[/C][/ROW]
[ROW][C]42[/C][C]139.966[/C][C]146.845175347222[/C][C]125.284625[/C][C]21.5605503472222[/C][C]-6.8791753472222[/C][/ROW]
[ROW][C]43[/C][C]122.243[/C][C]122.467355902778[/C][C]124.812833333333[/C][C]-2.34547743055556[/C][C]-0.224355902777774[/C][/ROW]
[ROW][C]44[/C][C]109.097[/C][C]109.389189236111[/C][C]124.075416666667[/C][C]-14.6862274305556[/C][C]-0.292189236111085[/C][/ROW]
[ROW][C]45[/C][C]116.591[/C][C]112.692633680556[/C][C]123.275458333333[/C][C]-10.5828246527778[/C][C]3.89836631944446[/C][/ROW]
[ROW][C]46[/C][C]111.964[/C][C]118.951654513889[/C][C]122.7035[/C][C]-3.75184548611111[/C][C]-6.98765451388888[/C][/ROW]
[ROW][C]47[/C][C]109.754[/C][C]102.334189236111[/C][C]123.229541666667[/C][C]-20.8953524305556[/C][C]7.41981076388892[/C][/ROW]
[ROW][C]48[/C][C]77.609[/C][C]84.3044114583333[/C][C]124.421375[/C][C]-40.1169635416667[/C][C]-6.69541145833331[/C][/ROW]
[ROW][C]49[/C][C]138.445[/C][C]133.839092013889[/C][C]125.31525[/C][C]8.5238420138889[/C][C]4.60590798611112[/C][/ROW]
[ROW][C]50[/C][C]127.901[/C][C]133.962946180556[/C][C]125.903083333333[/C][C]8.05986284722222[/C][C]-6.06194618055552[/C][/ROW]
[ROW][C]51[/C][C]156.615[/C][C]152.455626736111[/C][C]124.85025[/C][C]27.6053767361111[/C][C]4.15937326388891[/C][/ROW]
[ROW][C]52[/C][C]133.264[/C][C]144.185689236111[/C][C]124.259291666667[/C][C]19.9263975694444[/C][C]-10.9216892361111[/C][/ROW]
[ROW][C]53[/C][C]143.521[/C][C]131.510953125[/C][C]124.808291666667[/C][C]6.70266145833333[/C][C]12.010046875[/C][/ROW]
[ROW][C]54[/C][C]152.139[/C][C]146.300925347222[/C][C]124.740375[/C][C]21.5605503472222[/C][C]5.83807465277778[/C][/ROW]
[ROW][C]55[/C][C]131.523[/C][C]122.434064236111[/C][C]124.779541666667[/C][C]-2.34547743055556[/C][C]9.08893576388891[/C][/ROW]
[ROW][C]56[/C][C]113.925[/C][C]110.767064236111[/C][C]125.453291666667[/C][C]-14.6862274305556[/C][C]3.15793576388893[/C][/ROW]
[ROW][C]57[/C][C]86.495[/C][C]115.012175347222[/C][C]125.595[/C][C]-10.5828246527778[/C][C]-28.5171753472222[/C][/ROW]
[ROW][C]58[/C][C]127.877[/C][C]122.415321180556[/C][C]126.167166666667[/C][C]-3.75184548611111[/C][C]5.46167881944447[/C][/ROW]
[ROW][C]59[/C][C]107.017[/C][C]106.102147569444[/C][C]126.9975[/C][C]-20.8953524305556[/C][C]0.91485243055557[/C][/ROW]
[ROW][C]60[/C][C]78.716[/C][C]86.434453125[/C][C]126.551416666667[/C][C]-40.1169635416667[/C][C]-7.718453125[/C][/ROW]
[ROW][C]61[/C][C]138.278[/C][C]134.666258680556[/C][C]126.142416666667[/C][C]8.5238420138889[/C][C]3.61174131944445[/C][/ROW]
[ROW][C]62[/C][C]144.238[/C][C]133.610529513889[/C][C]125.550666666667[/C][C]8.05986284722222[/C][C]10.6274704861111[/C][/ROW]
[ROW][C]63[/C][C]143.679[/C][C]154.304293402778[/C][C]126.698916666667[/C][C]27.6053767361111[/C][C]-10.6252934027778[/C][/ROW]
[ROW][C]64[/C][C]159.932[/C][C]148.128564236111[/C][C]128.202166666667[/C][C]19.9263975694444[/C][C]11.8034357638889[/C][/ROW]
[ROW][C]65[/C][C]136.781[/C][C]134.388911458333[/C][C]127.68625[/C][C]6.70266145833333[/C][C]2.39208854166668[/C][/ROW]
[ROW][C]66[/C][C]148.173[/C][C]149.009592013889[/C][C]127.449041666667[/C][C]21.5605503472222[/C][C]-0.83659201388889[/C][/ROW]
[ROW][C]67[/C][C]125.673[/C][C]124.690230902778[/C][C]127.035708333333[/C][C]-2.34547743055556[/C][C]0.982769097222246[/C][/ROW]
[ROW][C]68[/C][C]105.573[/C][C]110.851939236111[/C][C]125.538166666667[/C][C]-14.6862274305556[/C][C]-5.27893923611113[/C][/ROW]
[ROW][C]69[/C][C]122.405[/C][C]114.211008680556[/C][C]124.793833333333[/C][C]-10.5828246527778[/C][C]8.19399131944445[/C][/ROW]
[ROW][C]70[/C][C]128.045[/C][C]120.353987847222[/C][C]124.105833333333[/C][C]-3.75184548611111[/C][C]7.69101215277777[/C][/ROW]
[ROW][C]71[/C][C]94.467[/C][C]101.944647569444[/C][C]122.84[/C][C]-20.8953524305556[/C][C]-7.47764756944446[/C][/ROW]
[ROW][C]72[/C][C]85.573[/C][C]82.042453125[/C][C]122.159416666667[/C][C]-40.1169635416667[/C][C]3.530546875[/C][/ROW]
[ROW][C]73[/C][C]121.501[/C][C]130.505383680556[/C][C]121.981541666667[/C][C]8.5238420138889[/C][C]-9.00438368055555[/C][/ROW]
[ROW][C]74[/C][C]125.074[/C][C]130.174362847222[/C][C]122.1145[/C][C]8.05986284722222[/C][C]-5.10036284722223[/C][/ROW]
[ROW][C]75[/C][C]144.979[/C][C]149.871668402778[/C][C]122.266291666667[/C][C]27.6053767361111[/C][C]-4.89266840277774[/C][/ROW]
[ROW][C]76[/C][C]142.12[/C][C]141.963230902778[/C][C]122.036833333333[/C][C]19.9263975694444[/C][C]0.156769097222238[/C][/ROW]
[ROW][C]77[/C][C]124.213[/C][C]128.950286458333[/C][C]122.247625[/C][C]6.70266145833333[/C][C]-4.73728645833333[/C][/ROW]
[ROW][C]78[/C][C]144.407[/C][C]144.453342013889[/C][C]122.892791666667[/C][C]21.5605503472222[/C][C]-0.0463420138888893[/C][/ROW]
[ROW][C]79[/C][C]125.17[/C][C]NA[/C][C]NA[/C][C]-2.34547743055556[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]109.267[/C][C]NA[/C][C]NA[/C][C]-14.6862274305556[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]122.354[/C][C]NA[/C][C]NA[/C][C]-10.5828246527778[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]122.589[/C][C]NA[/C][C]NA[/C][C]-3.75184548611111[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]104.982[/C][C]NA[/C][C]NA[/C][C]-20.8953524305556[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]90.542[/C][C]NA[/C][C]NA[/C][C]-40.1169635416667[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112153&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112153&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
1130.678NANA8.5238420138889NA
2120.877NANA8.05986284722222NA
3137.114NANA27.6053767361111NA
4134.406NANA19.9263975694444NA
5120.262NANA6.70266145833333NA
6130.846NANA21.5605503472222NA
7120.343114.979022569444117.3245-2.345477430555565.36397743055556
898.881102.629647569444117.315875-14.6862274305556-3.74864756944444
9115.678107.923300347222118.506125-10.58282465277787.75469965277779
10120.796116.135529513889119.887375-3.751845486111114.66047048611112
1194.26199.729564236111120.624916666667-20.8953524305556-5.46856423611109
1289.15181.1571197916666121.274083333333-40.11696354166677.99388020833335
13119.88129.999008680556121.4751666666678.5238420138889-10.1190086805556
14131.468129.638821180556121.5789583333338.059862847222221.82917881944445
15155.089149.704626736111122.0992527.60537673611115.38437326388889
16149.581142.001814236111122.07541666666719.92639756944447.57918576388889
17122.788128.998911458333122.296256.70266145833333-6.21091145833333
18143.9144.208008680556122.64745833333321.5605503472222-0.30800868055556
19112.115120.720814236111123.066291666667-2.34547743055556-8.60581423611112
20109.6108.542439236111123.228666666667-14.68622743055561.05756076388889
21117.446111.920550347222122.503375-10.58282465277785.52544965277778
22118.456117.944696180556121.696541666667-3.751845486111110.511303819444436
23101.901100.838689236111121.734041666667-20.89535243055561.06231076388887
2489.9482.066828125122.183791666667-40.11696354166677.873171875
25129.143130.896342013889122.37258.5238420138889-1.7533420138889
26126.102130.724029513889122.6641666666678.05986284722222-4.62202951388886
27143.048150.512126736111122.9067527.6053767361111-7.4641267361111
28142.258142.569064236111122.64266666666719.9263975694444-0.311064236111093
29131.011129.332078125122.6294166666676.702661458333331.67892187500001
30146.471144.080467013889122.51991666666721.56055034722222.39053298611113
31114.073120.520022569444122.8655-2.34547743055556-6.44702256944443
32114.642109.379230902778124.065458333333-14.68622743055565.26276909722223
33118.226114.922842013889125.505666666667-10.58282465277783.30315798611113
34111.338122.516321180556126.268166666667-3.75184548611111-11.1783211805556
35108.701104.993272569444125.888625-20.89535243055563.70772743055556
3680.51285.3372447916666125.454208333333-40.1169635416667-4.82524479166665
37146.865134.047425347222125.5235833333338.523842013888912.8175746527778
38137.179133.692821180556125.6329583333338.059862847222223.48617881944443
39166.536152.939168402778125.33379166666727.605376736111113.5968315972222
40137.07145.218147569444125.2917519.9263975694444-8.14814756944443
41127.09132.064369791667125.3617083333336.70266145833333-4.97436979166665
42139.966146.845175347222125.28462521.5605503472222-6.8791753472222
43122.243122.467355902778124.812833333333-2.34547743055556-0.224355902777774
44109.097109.389189236111124.075416666667-14.6862274305556-0.292189236111085
45116.591112.692633680556123.275458333333-10.58282465277783.89836631944446
46111.964118.951654513889122.7035-3.75184548611111-6.98765451388888
47109.754102.334189236111123.229541666667-20.89535243055567.41981076388892
4877.60984.3044114583333124.421375-40.1169635416667-6.69541145833331
49138.445133.839092013889125.315258.52384201388894.60590798611112
50127.901133.962946180556125.9030833333338.05986284722222-6.06194618055552
51156.615152.455626736111124.8502527.60537673611114.15937326388891
52133.264144.185689236111124.25929166666719.9263975694444-10.9216892361111
53143.521131.510953125124.8082916666676.7026614583333312.010046875
54152.139146.300925347222124.74037521.56055034722225.83807465277778
55131.523122.434064236111124.779541666667-2.345477430555569.08893576388891
56113.925110.767064236111125.453291666667-14.68622743055563.15793576388893
5786.495115.012175347222125.595-10.5828246527778-28.5171753472222
58127.877122.415321180556126.167166666667-3.751845486111115.46167881944447
59107.017106.102147569444126.9975-20.89535243055560.91485243055557
6078.71686.434453125126.551416666667-40.1169635416667-7.718453125
61138.278134.666258680556126.1424166666678.52384201388893.61174131944445
62144.238133.610529513889125.5506666666678.0598628472222210.6274704861111
63143.679154.304293402778126.69891666666727.6053767361111-10.6252934027778
64159.932148.128564236111128.20216666666719.926397569444411.8034357638889
65136.781134.388911458333127.686256.702661458333332.39208854166668
66148.173149.009592013889127.44904166666721.5605503472222-0.83659201388889
67125.673124.690230902778127.035708333333-2.345477430555560.982769097222246
68105.573110.851939236111125.538166666667-14.6862274305556-5.27893923611113
69122.405114.211008680556124.793833333333-10.58282465277788.19399131944445
70128.045120.353987847222124.105833333333-3.751845486111117.69101215277777
7194.467101.944647569444122.84-20.8953524305556-7.47764756944446
7285.57382.042453125122.159416666667-40.11696354166673.530546875
73121.501130.505383680556121.9815416666678.5238420138889-9.00438368055555
74125.074130.174362847222122.11458.05986284722222-5.10036284722223
75144.979149.871668402778122.26629166666727.6053767361111-4.89266840277774
76142.12141.963230902778122.03683333333319.92639756944440.156769097222238
77124.213128.950286458333122.2476256.70266145833333-4.73728645833333
78144.407144.453342013889122.89279166666721.5605503472222-0.0463420138888893
79125.17NANA-2.34547743055556NA
80109.267NANA-14.6862274305556NA
81122.354NANA-10.5828246527778NA
82122.589NANA-3.75184548611111NA
83104.982NANA-20.8953524305556NA
8490.542NANA-40.1169635416667NA


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')