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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 computationSat, 23 Jul 2016 13:39:26 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Jul/23/t1469277658bnry0bphaiiq59c.htm/, Retrieved Wed, 08 May 2024 02:35:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=295937, Retrieved Wed, 08 May 2024 02:35:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact166

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Classical Decomposition] [] [2016-07-23 12:39:26] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
181896,00
181580,00
181234,00
180598,00
187123,00
186807,00
181896,00
178638,00
178954,00
178954,00
179269,00
179936,00
181580,00
179616,00
181580,00
179936,00
185158,00
187469,00
177656,00
175025,00
177305,00
176989,00
175025,00
175345,00
179269,00
178638,00
179269,00
179269,00
183545,00
184176,00
172398,00
172398,00
176989,00
174709,00
170785,00
172398,00
176327,00
174363,00
174047,00
169803,00
176007,00
177305,00
164545,00
164229,00
170785,00
167176,00
160967,00
163598,00
166509,00
167176,00
165212,00
161287,00
169456,00
169456,00
155078,00
154101,00
158025,00
150838,00
143616,00
145932,00
150838,00
146910,00
144283,00
138710,00
146247,00
146563,00
132190,00
131839,00
134470,00
126301,00
117465,00
121043,00
125950,00
120728,00
120412,00
115154,00
123670,00
125319,00
109266,00
105688,00
107968,00
99132,00
89981,00
92928,00
98470,00
91946,00
92928,00
89004,00
97172,00
98150,00
78524,00
77221,00
80799,00
71333,00
62817,00
65764,00
72950,00
64462,00
63799,00
57244,00
64462,00
66742,00
46448,00
46448,00
49391,00
41542,00
32706,00
37297,00
45466,00
36631,00
40244,00
35333,00
43186,00
45813,00
24853,00
23240,00
26502,00
18649,00
12444,00
15040,00

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295937&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295937&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295937&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ yule.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1181896NANA2386.82NA
2181580NANA-265.476NA
3181234NANA1304.64NA
4180598NANA-1251.18NA
5187123NANA7281.42NA
6186807NANA10160.5NA
7181896178085181394-3309.183811.26
8178638177913181299-3385.83724.916
91789541824031812321171.18-3448.68
10178954178413181218-2804.9540.564
11179269173605181109-7504.115664.24
12179936177271181055-3783.872665.29
131815801832921809062386.82-1712.32
14179616180313180578-265.476-696.816
151815801816641803591304.64-83.686
16179936178957180208-1251.18978.726
171851581872311799507281.42-2073.17
1818746918974217958210160.5-2273.12
19177656175985179294-3309.181671.14
20175025175771179157-3385.83-746.167
211773051801911790201171.18-2886.14
22176989176091178896-2804.9898.022
23175025171297178801-7504.113728.24
24175345174813178596-3783.87532.416
251792691806271782402386.82-1357.98
26178638177646177912-265.476991.851
271792691790941777891304.64175.356
28179269176430177681-1251.182839.35
291835451846911774097281.42-1145.58
3018417618727017711010160.5-3094.2
31172398173555176864-3309.18-1157.15
32172398173178176564-3385.83-779.792
331769891773391761681171.18-350.098
34174709172751175556-2804.91957.98
35170785167343174847-7504.113441.69
36172398170463174247-3783.871934.83
371763271760201736342386.82306.643
38174363172700172966-265.4761662.52
391740471736721723671304.64375.272
40169803170544171795-1251.18-740.524
411760071783531710727281.42-2346.17
4217730518045617029610160.5-3151.5
43164545166211169520-3309.18-1666.07
44164229165426168812-3385.83-1196.88
451707851693151681441171.181469.69
46167176164616167421-2804.92559.73
47160967159289166793-7504.111677.74
48163598162410166193-3783.871188.5
491665091678591654722386.82-1349.69
50167176164390164655-265.4762786.06
511652121650061637021304.64205.606
52161287161238162489-1251.1848.8511
531694561683671610867281.421088.96
5416945616978715962710160.5-331.079
55155078154928158238-3309.18149.638
56154101153354156740-3385.83746.666
571580251561951550241171.181830.11
58150838150406153211-2804.9431.939
59143616143799151303-7504.11-183.098
60145932145598149382-3783.87333.583
611508381498621474752386.82976.434
62146910145328145594-265.4761581.98
631442831449891436841304.64-706.103
64138710140429141681-1251.18-1719.44
651462471468501395697281.42-603.042
6614656314760213744210160.5-1039.45
67132190132059135368-3309.18131.263
68131839129854133240-3385.831984.83
691344701323261311541171.182144.36
70126301126373129178-2804.9-72.436
71117465119752127256-7504.11-2287.01
72121043121646125430-3783.87-603.376
731259501259771235902386.82-26.7323
74120728121280121545-265.476-551.649
751204121206561193511304.64-243.894
76115154115864117115-1251.18-709.774
771236701221191148387281.421550.83
7812531912268211252110160.52637.38
79109266106895110205-3309.182370.51
80105688104475107860-3385.831213.42
811079681066871055161171.181280.82
8299132100476103281-2804.9-1344.35
838998193583.5101088-7504.11-3602.47
849292895067.698851.5-3783.87-2139.58
859847098825.396438.52386.82-355.316
86919469370693971.5-265.476-1759.98
879292892957.991653.31304.64-29.936
888900488111.889363-1251.18892.226
899717294354.387072.87281.422817.75
909815094969.784809.210160.53180.34
917852479304.882614-3309.18-780.82
927722177019.780405.5-3385.83201.333
938079979217.878046.61171.181581.19
947133372704.775509.6-2804.9-1371.69
956281765319.272823.3-7504.11-2502.22
966576466367.970151.8-3783.87-603.876
977295069893.467506.62386.823056.6
986446264622.464887.9-265.476-160.399
996379963601.6622971304.64197.356
1005724458495.959747-1251.18-1251.86
1016446264532.557251.17281.42-70.5424
1026674264970.954810.410160.51771.13
1034644849169.952479.1-3309.18-2721.9
1044644846788.550174.3-3385.83-340.459
1054939149204.448033.21171.18186.61
1064154243333.946138.8-2804.9-1791.89
1073270636835.244339.3-7504.11-4129.22
1083729738796.942580.8-3783.87-1499.92
1094546643195.8408092386.822270.23
1103663138676.738942.2-265.476-2045.69
1114024438326.137021.51304.641917.9
1123533333862.735113.9-1251.181470.31
1134318640597.233315.87281.422588.83
1144581341704.631544.110160.54108.38
11524853NANA-3309.18NA
11623240NANA-3385.83NA
11726502NANA1171.18NA
11818649NANA-2804.9NA
11912444NANA-7504.11NA
12015040NANA-3783.87NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 181896 & NA & NA & 2386.82 & NA \tabularnewline
2 & 181580 & NA & NA & -265.476 & NA \tabularnewline
3 & 181234 & NA & NA & 1304.64 & NA \tabularnewline
4 & 180598 & NA & NA & -1251.18 & NA \tabularnewline
5 & 187123 & NA & NA & 7281.42 & NA \tabularnewline
6 & 186807 & NA & NA & 10160.5 & NA \tabularnewline
7 & 181896 & 178085 & 181394 & -3309.18 & 3811.26 \tabularnewline
8 & 178638 & 177913 & 181299 & -3385.83 & 724.916 \tabularnewline
9 & 178954 & 182403 & 181232 & 1171.18 & -3448.68 \tabularnewline
10 & 178954 & 178413 & 181218 & -2804.9 & 540.564 \tabularnewline
11 & 179269 & 173605 & 181109 & -7504.11 & 5664.24 \tabularnewline
12 & 179936 & 177271 & 181055 & -3783.87 & 2665.29 \tabularnewline
13 & 181580 & 183292 & 180906 & 2386.82 & -1712.32 \tabularnewline
14 & 179616 & 180313 & 180578 & -265.476 & -696.816 \tabularnewline
15 & 181580 & 181664 & 180359 & 1304.64 & -83.686 \tabularnewline
16 & 179936 & 178957 & 180208 & -1251.18 & 978.726 \tabularnewline
17 & 185158 & 187231 & 179950 & 7281.42 & -2073.17 \tabularnewline
18 & 187469 & 189742 & 179582 & 10160.5 & -2273.12 \tabularnewline
19 & 177656 & 175985 & 179294 & -3309.18 & 1671.14 \tabularnewline
20 & 175025 & 175771 & 179157 & -3385.83 & -746.167 \tabularnewline
21 & 177305 & 180191 & 179020 & 1171.18 & -2886.14 \tabularnewline
22 & 176989 & 176091 & 178896 & -2804.9 & 898.022 \tabularnewline
23 & 175025 & 171297 & 178801 & -7504.11 & 3728.24 \tabularnewline
24 & 175345 & 174813 & 178596 & -3783.87 & 532.416 \tabularnewline
25 & 179269 & 180627 & 178240 & 2386.82 & -1357.98 \tabularnewline
26 & 178638 & 177646 & 177912 & -265.476 & 991.851 \tabularnewline
27 & 179269 & 179094 & 177789 & 1304.64 & 175.356 \tabularnewline
28 & 179269 & 176430 & 177681 & -1251.18 & 2839.35 \tabularnewline
29 & 183545 & 184691 & 177409 & 7281.42 & -1145.58 \tabularnewline
30 & 184176 & 187270 & 177110 & 10160.5 & -3094.2 \tabularnewline
31 & 172398 & 173555 & 176864 & -3309.18 & -1157.15 \tabularnewline
32 & 172398 & 173178 & 176564 & -3385.83 & -779.792 \tabularnewline
33 & 176989 & 177339 & 176168 & 1171.18 & -350.098 \tabularnewline
34 & 174709 & 172751 & 175556 & -2804.9 & 1957.98 \tabularnewline
35 & 170785 & 167343 & 174847 & -7504.11 & 3441.69 \tabularnewline
36 & 172398 & 170463 & 174247 & -3783.87 & 1934.83 \tabularnewline
37 & 176327 & 176020 & 173634 & 2386.82 & 306.643 \tabularnewline
38 & 174363 & 172700 & 172966 & -265.476 & 1662.52 \tabularnewline
39 & 174047 & 173672 & 172367 & 1304.64 & 375.272 \tabularnewline
40 & 169803 & 170544 & 171795 & -1251.18 & -740.524 \tabularnewline
41 & 176007 & 178353 & 171072 & 7281.42 & -2346.17 \tabularnewline
42 & 177305 & 180456 & 170296 & 10160.5 & -3151.5 \tabularnewline
43 & 164545 & 166211 & 169520 & -3309.18 & -1666.07 \tabularnewline
44 & 164229 & 165426 & 168812 & -3385.83 & -1196.88 \tabularnewline
45 & 170785 & 169315 & 168144 & 1171.18 & 1469.69 \tabularnewline
46 & 167176 & 164616 & 167421 & -2804.9 & 2559.73 \tabularnewline
47 & 160967 & 159289 & 166793 & -7504.11 & 1677.74 \tabularnewline
48 & 163598 & 162410 & 166193 & -3783.87 & 1188.5 \tabularnewline
49 & 166509 & 167859 & 165472 & 2386.82 & -1349.69 \tabularnewline
50 & 167176 & 164390 & 164655 & -265.476 & 2786.06 \tabularnewline
51 & 165212 & 165006 & 163702 & 1304.64 & 205.606 \tabularnewline
52 & 161287 & 161238 & 162489 & -1251.18 & 48.8511 \tabularnewline
53 & 169456 & 168367 & 161086 & 7281.42 & 1088.96 \tabularnewline
54 & 169456 & 169787 & 159627 & 10160.5 & -331.079 \tabularnewline
55 & 155078 & 154928 & 158238 & -3309.18 & 149.638 \tabularnewline
56 & 154101 & 153354 & 156740 & -3385.83 & 746.666 \tabularnewline
57 & 158025 & 156195 & 155024 & 1171.18 & 1830.11 \tabularnewline
58 & 150838 & 150406 & 153211 & -2804.9 & 431.939 \tabularnewline
59 & 143616 & 143799 & 151303 & -7504.11 & -183.098 \tabularnewline
60 & 145932 & 145598 & 149382 & -3783.87 & 333.583 \tabularnewline
61 & 150838 & 149862 & 147475 & 2386.82 & 976.434 \tabularnewline
62 & 146910 & 145328 & 145594 & -265.476 & 1581.98 \tabularnewline
63 & 144283 & 144989 & 143684 & 1304.64 & -706.103 \tabularnewline
64 & 138710 & 140429 & 141681 & -1251.18 & -1719.44 \tabularnewline
65 & 146247 & 146850 & 139569 & 7281.42 & -603.042 \tabularnewline
66 & 146563 & 147602 & 137442 & 10160.5 & -1039.45 \tabularnewline
67 & 132190 & 132059 & 135368 & -3309.18 & 131.263 \tabularnewline
68 & 131839 & 129854 & 133240 & -3385.83 & 1984.83 \tabularnewline
69 & 134470 & 132326 & 131154 & 1171.18 & 2144.36 \tabularnewline
70 & 126301 & 126373 & 129178 & -2804.9 & -72.436 \tabularnewline
71 & 117465 & 119752 & 127256 & -7504.11 & -2287.01 \tabularnewline
72 & 121043 & 121646 & 125430 & -3783.87 & -603.376 \tabularnewline
73 & 125950 & 125977 & 123590 & 2386.82 & -26.7323 \tabularnewline
74 & 120728 & 121280 & 121545 & -265.476 & -551.649 \tabularnewline
75 & 120412 & 120656 & 119351 & 1304.64 & -243.894 \tabularnewline
76 & 115154 & 115864 & 117115 & -1251.18 & -709.774 \tabularnewline
77 & 123670 & 122119 & 114838 & 7281.42 & 1550.83 \tabularnewline
78 & 125319 & 122682 & 112521 & 10160.5 & 2637.38 \tabularnewline
79 & 109266 & 106895 & 110205 & -3309.18 & 2370.51 \tabularnewline
80 & 105688 & 104475 & 107860 & -3385.83 & 1213.42 \tabularnewline
81 & 107968 & 106687 & 105516 & 1171.18 & 1280.82 \tabularnewline
82 & 99132 & 100476 & 103281 & -2804.9 & -1344.35 \tabularnewline
83 & 89981 & 93583.5 & 101088 & -7504.11 & -3602.47 \tabularnewline
84 & 92928 & 95067.6 & 98851.5 & -3783.87 & -2139.58 \tabularnewline
85 & 98470 & 98825.3 & 96438.5 & 2386.82 & -355.316 \tabularnewline
86 & 91946 & 93706 & 93971.5 & -265.476 & -1759.98 \tabularnewline
87 & 92928 & 92957.9 & 91653.3 & 1304.64 & -29.936 \tabularnewline
88 & 89004 & 88111.8 & 89363 & -1251.18 & 892.226 \tabularnewline
89 & 97172 & 94354.3 & 87072.8 & 7281.42 & 2817.75 \tabularnewline
90 & 98150 & 94969.7 & 84809.2 & 10160.5 & 3180.34 \tabularnewline
91 & 78524 & 79304.8 & 82614 & -3309.18 & -780.82 \tabularnewline
92 & 77221 & 77019.7 & 80405.5 & -3385.83 & 201.333 \tabularnewline
93 & 80799 & 79217.8 & 78046.6 & 1171.18 & 1581.19 \tabularnewline
94 & 71333 & 72704.7 & 75509.6 & -2804.9 & -1371.69 \tabularnewline
95 & 62817 & 65319.2 & 72823.3 & -7504.11 & -2502.22 \tabularnewline
96 & 65764 & 66367.9 & 70151.8 & -3783.87 & -603.876 \tabularnewline
97 & 72950 & 69893.4 & 67506.6 & 2386.82 & 3056.6 \tabularnewline
98 & 64462 & 64622.4 & 64887.9 & -265.476 & -160.399 \tabularnewline
99 & 63799 & 63601.6 & 62297 & 1304.64 & 197.356 \tabularnewline
100 & 57244 & 58495.9 & 59747 & -1251.18 & -1251.86 \tabularnewline
101 & 64462 & 64532.5 & 57251.1 & 7281.42 & -70.5424 \tabularnewline
102 & 66742 & 64970.9 & 54810.4 & 10160.5 & 1771.13 \tabularnewline
103 & 46448 & 49169.9 & 52479.1 & -3309.18 & -2721.9 \tabularnewline
104 & 46448 & 46788.5 & 50174.3 & -3385.83 & -340.459 \tabularnewline
105 & 49391 & 49204.4 & 48033.2 & 1171.18 & 186.61 \tabularnewline
106 & 41542 & 43333.9 & 46138.8 & -2804.9 & -1791.89 \tabularnewline
107 & 32706 & 36835.2 & 44339.3 & -7504.11 & -4129.22 \tabularnewline
108 & 37297 & 38796.9 & 42580.8 & -3783.87 & -1499.92 \tabularnewline
109 & 45466 & 43195.8 & 40809 & 2386.82 & 2270.23 \tabularnewline
110 & 36631 & 38676.7 & 38942.2 & -265.476 & -2045.69 \tabularnewline
111 & 40244 & 38326.1 & 37021.5 & 1304.64 & 1917.9 \tabularnewline
112 & 35333 & 33862.7 & 35113.9 & -1251.18 & 1470.31 \tabularnewline
113 & 43186 & 40597.2 & 33315.8 & 7281.42 & 2588.83 \tabularnewline
114 & 45813 & 41704.6 & 31544.1 & 10160.5 & 4108.38 \tabularnewline
115 & 24853 & NA & NA & -3309.18 & NA \tabularnewline
116 & 23240 & NA & NA & -3385.83 & NA \tabularnewline
117 & 26502 & NA & NA & 1171.18 & NA \tabularnewline
118 & 18649 & NA & NA & -2804.9 & NA \tabularnewline
119 & 12444 & NA & NA & -7504.11 & NA \tabularnewline
120 & 15040 & NA & NA & -3783.87 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=295937&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]181896[/C][C]NA[/C][C]NA[/C][C]2386.82[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]181580[/C][C]NA[/C][C]NA[/C][C]-265.476[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]181234[/C][C]NA[/C][C]NA[/C][C]1304.64[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]180598[/C][C]NA[/C][C]NA[/C][C]-1251.18[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]187123[/C][C]NA[/C][C]NA[/C][C]7281.42[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]186807[/C][C]NA[/C][C]NA[/C][C]10160.5[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]181896[/C][C]178085[/C][C]181394[/C][C]-3309.18[/C][C]3811.26[/C][/ROW]
[ROW][C]8[/C][C]178638[/C][C]177913[/C][C]181299[/C][C]-3385.83[/C][C]724.916[/C][/ROW]
[ROW][C]9[/C][C]178954[/C][C]182403[/C][C]181232[/C][C]1171.18[/C][C]-3448.68[/C][/ROW]
[ROW][C]10[/C][C]178954[/C][C]178413[/C][C]181218[/C][C]-2804.9[/C][C]540.564[/C][/ROW]
[ROW][C]11[/C][C]179269[/C][C]173605[/C][C]181109[/C][C]-7504.11[/C][C]5664.24[/C][/ROW]
[ROW][C]12[/C][C]179936[/C][C]177271[/C][C]181055[/C][C]-3783.87[/C][C]2665.29[/C][/ROW]
[ROW][C]13[/C][C]181580[/C][C]183292[/C][C]180906[/C][C]2386.82[/C][C]-1712.32[/C][/ROW]
[ROW][C]14[/C][C]179616[/C][C]180313[/C][C]180578[/C][C]-265.476[/C][C]-696.816[/C][/ROW]
[ROW][C]15[/C][C]181580[/C][C]181664[/C][C]180359[/C][C]1304.64[/C][C]-83.686[/C][/ROW]
[ROW][C]16[/C][C]179936[/C][C]178957[/C][C]180208[/C][C]-1251.18[/C][C]978.726[/C][/ROW]
[ROW][C]17[/C][C]185158[/C][C]187231[/C][C]179950[/C][C]7281.42[/C][C]-2073.17[/C][/ROW]
[ROW][C]18[/C][C]187469[/C][C]189742[/C][C]179582[/C][C]10160.5[/C][C]-2273.12[/C][/ROW]
[ROW][C]19[/C][C]177656[/C][C]175985[/C][C]179294[/C][C]-3309.18[/C][C]1671.14[/C][/ROW]
[ROW][C]20[/C][C]175025[/C][C]175771[/C][C]179157[/C][C]-3385.83[/C][C]-746.167[/C][/ROW]
[ROW][C]21[/C][C]177305[/C][C]180191[/C][C]179020[/C][C]1171.18[/C][C]-2886.14[/C][/ROW]
[ROW][C]22[/C][C]176989[/C][C]176091[/C][C]178896[/C][C]-2804.9[/C][C]898.022[/C][/ROW]
[ROW][C]23[/C][C]175025[/C][C]171297[/C][C]178801[/C][C]-7504.11[/C][C]3728.24[/C][/ROW]
[ROW][C]24[/C][C]175345[/C][C]174813[/C][C]178596[/C][C]-3783.87[/C][C]532.416[/C][/ROW]
[ROW][C]25[/C][C]179269[/C][C]180627[/C][C]178240[/C][C]2386.82[/C][C]-1357.98[/C][/ROW]
[ROW][C]26[/C][C]178638[/C][C]177646[/C][C]177912[/C][C]-265.476[/C][C]991.851[/C][/ROW]
[ROW][C]27[/C][C]179269[/C][C]179094[/C][C]177789[/C][C]1304.64[/C][C]175.356[/C][/ROW]
[ROW][C]28[/C][C]179269[/C][C]176430[/C][C]177681[/C][C]-1251.18[/C][C]2839.35[/C][/ROW]
[ROW][C]29[/C][C]183545[/C][C]184691[/C][C]177409[/C][C]7281.42[/C][C]-1145.58[/C][/ROW]
[ROW][C]30[/C][C]184176[/C][C]187270[/C][C]177110[/C][C]10160.5[/C][C]-3094.2[/C][/ROW]
[ROW][C]31[/C][C]172398[/C][C]173555[/C][C]176864[/C][C]-3309.18[/C][C]-1157.15[/C][/ROW]
[ROW][C]32[/C][C]172398[/C][C]173178[/C][C]176564[/C][C]-3385.83[/C][C]-779.792[/C][/ROW]
[ROW][C]33[/C][C]176989[/C][C]177339[/C][C]176168[/C][C]1171.18[/C][C]-350.098[/C][/ROW]
[ROW][C]34[/C][C]174709[/C][C]172751[/C][C]175556[/C][C]-2804.9[/C][C]1957.98[/C][/ROW]
[ROW][C]35[/C][C]170785[/C][C]167343[/C][C]174847[/C][C]-7504.11[/C][C]3441.69[/C][/ROW]
[ROW][C]36[/C][C]172398[/C][C]170463[/C][C]174247[/C][C]-3783.87[/C][C]1934.83[/C][/ROW]
[ROW][C]37[/C][C]176327[/C][C]176020[/C][C]173634[/C][C]2386.82[/C][C]306.643[/C][/ROW]
[ROW][C]38[/C][C]174363[/C][C]172700[/C][C]172966[/C][C]-265.476[/C][C]1662.52[/C][/ROW]
[ROW][C]39[/C][C]174047[/C][C]173672[/C][C]172367[/C][C]1304.64[/C][C]375.272[/C][/ROW]
[ROW][C]40[/C][C]169803[/C][C]170544[/C][C]171795[/C][C]-1251.18[/C][C]-740.524[/C][/ROW]
[ROW][C]41[/C][C]176007[/C][C]178353[/C][C]171072[/C][C]7281.42[/C][C]-2346.17[/C][/ROW]
[ROW][C]42[/C][C]177305[/C][C]180456[/C][C]170296[/C][C]10160.5[/C][C]-3151.5[/C][/ROW]
[ROW][C]43[/C][C]164545[/C][C]166211[/C][C]169520[/C][C]-3309.18[/C][C]-1666.07[/C][/ROW]
[ROW][C]44[/C][C]164229[/C][C]165426[/C][C]168812[/C][C]-3385.83[/C][C]-1196.88[/C][/ROW]
[ROW][C]45[/C][C]170785[/C][C]169315[/C][C]168144[/C][C]1171.18[/C][C]1469.69[/C][/ROW]
[ROW][C]46[/C][C]167176[/C][C]164616[/C][C]167421[/C][C]-2804.9[/C][C]2559.73[/C][/ROW]
[ROW][C]47[/C][C]160967[/C][C]159289[/C][C]166793[/C][C]-7504.11[/C][C]1677.74[/C][/ROW]
[ROW][C]48[/C][C]163598[/C][C]162410[/C][C]166193[/C][C]-3783.87[/C][C]1188.5[/C][/ROW]
[ROW][C]49[/C][C]166509[/C][C]167859[/C][C]165472[/C][C]2386.82[/C][C]-1349.69[/C][/ROW]
[ROW][C]50[/C][C]167176[/C][C]164390[/C][C]164655[/C][C]-265.476[/C][C]2786.06[/C][/ROW]
[ROW][C]51[/C][C]165212[/C][C]165006[/C][C]163702[/C][C]1304.64[/C][C]205.606[/C][/ROW]
[ROW][C]52[/C][C]161287[/C][C]161238[/C][C]162489[/C][C]-1251.18[/C][C]48.8511[/C][/ROW]
[ROW][C]53[/C][C]169456[/C][C]168367[/C][C]161086[/C][C]7281.42[/C][C]1088.96[/C][/ROW]
[ROW][C]54[/C][C]169456[/C][C]169787[/C][C]159627[/C][C]10160.5[/C][C]-331.079[/C][/ROW]
[ROW][C]55[/C][C]155078[/C][C]154928[/C][C]158238[/C][C]-3309.18[/C][C]149.638[/C][/ROW]
[ROW][C]56[/C][C]154101[/C][C]153354[/C][C]156740[/C][C]-3385.83[/C][C]746.666[/C][/ROW]
[ROW][C]57[/C][C]158025[/C][C]156195[/C][C]155024[/C][C]1171.18[/C][C]1830.11[/C][/ROW]
[ROW][C]58[/C][C]150838[/C][C]150406[/C][C]153211[/C][C]-2804.9[/C][C]431.939[/C][/ROW]
[ROW][C]59[/C][C]143616[/C][C]143799[/C][C]151303[/C][C]-7504.11[/C][C]-183.098[/C][/ROW]
[ROW][C]60[/C][C]145932[/C][C]145598[/C][C]149382[/C][C]-3783.87[/C][C]333.583[/C][/ROW]
[ROW][C]61[/C][C]150838[/C][C]149862[/C][C]147475[/C][C]2386.82[/C][C]976.434[/C][/ROW]
[ROW][C]62[/C][C]146910[/C][C]145328[/C][C]145594[/C][C]-265.476[/C][C]1581.98[/C][/ROW]
[ROW][C]63[/C][C]144283[/C][C]144989[/C][C]143684[/C][C]1304.64[/C][C]-706.103[/C][/ROW]
[ROW][C]64[/C][C]138710[/C][C]140429[/C][C]141681[/C][C]-1251.18[/C][C]-1719.44[/C][/ROW]
[ROW][C]65[/C][C]146247[/C][C]146850[/C][C]139569[/C][C]7281.42[/C][C]-603.042[/C][/ROW]
[ROW][C]66[/C][C]146563[/C][C]147602[/C][C]137442[/C][C]10160.5[/C][C]-1039.45[/C][/ROW]
[ROW][C]67[/C][C]132190[/C][C]132059[/C][C]135368[/C][C]-3309.18[/C][C]131.263[/C][/ROW]
[ROW][C]68[/C][C]131839[/C][C]129854[/C][C]133240[/C][C]-3385.83[/C][C]1984.83[/C][/ROW]
[ROW][C]69[/C][C]134470[/C][C]132326[/C][C]131154[/C][C]1171.18[/C][C]2144.36[/C][/ROW]
[ROW][C]70[/C][C]126301[/C][C]126373[/C][C]129178[/C][C]-2804.9[/C][C]-72.436[/C][/ROW]
[ROW][C]71[/C][C]117465[/C][C]119752[/C][C]127256[/C][C]-7504.11[/C][C]-2287.01[/C][/ROW]
[ROW][C]72[/C][C]121043[/C][C]121646[/C][C]125430[/C][C]-3783.87[/C][C]-603.376[/C][/ROW]
[ROW][C]73[/C][C]125950[/C][C]125977[/C][C]123590[/C][C]2386.82[/C][C]-26.7323[/C][/ROW]
[ROW][C]74[/C][C]120728[/C][C]121280[/C][C]121545[/C][C]-265.476[/C][C]-551.649[/C][/ROW]
[ROW][C]75[/C][C]120412[/C][C]120656[/C][C]119351[/C][C]1304.64[/C][C]-243.894[/C][/ROW]
[ROW][C]76[/C][C]115154[/C][C]115864[/C][C]117115[/C][C]-1251.18[/C][C]-709.774[/C][/ROW]
[ROW][C]77[/C][C]123670[/C][C]122119[/C][C]114838[/C][C]7281.42[/C][C]1550.83[/C][/ROW]
[ROW][C]78[/C][C]125319[/C][C]122682[/C][C]112521[/C][C]10160.5[/C][C]2637.38[/C][/ROW]
[ROW][C]79[/C][C]109266[/C][C]106895[/C][C]110205[/C][C]-3309.18[/C][C]2370.51[/C][/ROW]
[ROW][C]80[/C][C]105688[/C][C]104475[/C][C]107860[/C][C]-3385.83[/C][C]1213.42[/C][/ROW]
[ROW][C]81[/C][C]107968[/C][C]106687[/C][C]105516[/C][C]1171.18[/C][C]1280.82[/C][/ROW]
[ROW][C]82[/C][C]99132[/C][C]100476[/C][C]103281[/C][C]-2804.9[/C][C]-1344.35[/C][/ROW]
[ROW][C]83[/C][C]89981[/C][C]93583.5[/C][C]101088[/C][C]-7504.11[/C][C]-3602.47[/C][/ROW]
[ROW][C]84[/C][C]92928[/C][C]95067.6[/C][C]98851.5[/C][C]-3783.87[/C][C]-2139.58[/C][/ROW]
[ROW][C]85[/C][C]98470[/C][C]98825.3[/C][C]96438.5[/C][C]2386.82[/C][C]-355.316[/C][/ROW]
[ROW][C]86[/C][C]91946[/C][C]93706[/C][C]93971.5[/C][C]-265.476[/C][C]-1759.98[/C][/ROW]
[ROW][C]87[/C][C]92928[/C][C]92957.9[/C][C]91653.3[/C][C]1304.64[/C][C]-29.936[/C][/ROW]
[ROW][C]88[/C][C]89004[/C][C]88111.8[/C][C]89363[/C][C]-1251.18[/C][C]892.226[/C][/ROW]
[ROW][C]89[/C][C]97172[/C][C]94354.3[/C][C]87072.8[/C][C]7281.42[/C][C]2817.75[/C][/ROW]
[ROW][C]90[/C][C]98150[/C][C]94969.7[/C][C]84809.2[/C][C]10160.5[/C][C]3180.34[/C][/ROW]
[ROW][C]91[/C][C]78524[/C][C]79304.8[/C][C]82614[/C][C]-3309.18[/C][C]-780.82[/C][/ROW]
[ROW][C]92[/C][C]77221[/C][C]77019.7[/C][C]80405.5[/C][C]-3385.83[/C][C]201.333[/C][/ROW]
[ROW][C]93[/C][C]80799[/C][C]79217.8[/C][C]78046.6[/C][C]1171.18[/C][C]1581.19[/C][/ROW]
[ROW][C]94[/C][C]71333[/C][C]72704.7[/C][C]75509.6[/C][C]-2804.9[/C][C]-1371.69[/C][/ROW]
[ROW][C]95[/C][C]62817[/C][C]65319.2[/C][C]72823.3[/C][C]-7504.11[/C][C]-2502.22[/C][/ROW]
[ROW][C]96[/C][C]65764[/C][C]66367.9[/C][C]70151.8[/C][C]-3783.87[/C][C]-603.876[/C][/ROW]
[ROW][C]97[/C][C]72950[/C][C]69893.4[/C][C]67506.6[/C][C]2386.82[/C][C]3056.6[/C][/ROW]
[ROW][C]98[/C][C]64462[/C][C]64622.4[/C][C]64887.9[/C][C]-265.476[/C][C]-160.399[/C][/ROW]
[ROW][C]99[/C][C]63799[/C][C]63601.6[/C][C]62297[/C][C]1304.64[/C][C]197.356[/C][/ROW]
[ROW][C]100[/C][C]57244[/C][C]58495.9[/C][C]59747[/C][C]-1251.18[/C][C]-1251.86[/C][/ROW]
[ROW][C]101[/C][C]64462[/C][C]64532.5[/C][C]57251.1[/C][C]7281.42[/C][C]-70.5424[/C][/ROW]
[ROW][C]102[/C][C]66742[/C][C]64970.9[/C][C]54810.4[/C][C]10160.5[/C][C]1771.13[/C][/ROW]
[ROW][C]103[/C][C]46448[/C][C]49169.9[/C][C]52479.1[/C][C]-3309.18[/C][C]-2721.9[/C][/ROW]
[ROW][C]104[/C][C]46448[/C][C]46788.5[/C][C]50174.3[/C][C]-3385.83[/C][C]-340.459[/C][/ROW]
[ROW][C]105[/C][C]49391[/C][C]49204.4[/C][C]48033.2[/C][C]1171.18[/C][C]186.61[/C][/ROW]
[ROW][C]106[/C][C]41542[/C][C]43333.9[/C][C]46138.8[/C][C]-2804.9[/C][C]-1791.89[/C][/ROW]
[ROW][C]107[/C][C]32706[/C][C]36835.2[/C][C]44339.3[/C][C]-7504.11[/C][C]-4129.22[/C][/ROW]
[ROW][C]108[/C][C]37297[/C][C]38796.9[/C][C]42580.8[/C][C]-3783.87[/C][C]-1499.92[/C][/ROW]
[ROW][C]109[/C][C]45466[/C][C]43195.8[/C][C]40809[/C][C]2386.82[/C][C]2270.23[/C][/ROW]
[ROW][C]110[/C][C]36631[/C][C]38676.7[/C][C]38942.2[/C][C]-265.476[/C][C]-2045.69[/C][/ROW]
[ROW][C]111[/C][C]40244[/C][C]38326.1[/C][C]37021.5[/C][C]1304.64[/C][C]1917.9[/C][/ROW]
[ROW][C]112[/C][C]35333[/C][C]33862.7[/C][C]35113.9[/C][C]-1251.18[/C][C]1470.31[/C][/ROW]
[ROW][C]113[/C][C]43186[/C][C]40597.2[/C][C]33315.8[/C][C]7281.42[/C][C]2588.83[/C][/ROW]
[ROW][C]114[/C][C]45813[/C][C]41704.6[/C][C]31544.1[/C][C]10160.5[/C][C]4108.38[/C][/ROW]
[ROW][C]115[/C][C]24853[/C][C]NA[/C][C]NA[/C][C]-3309.18[/C][C]NA[/C][/ROW]
[ROW][C]116[/C][C]23240[/C][C]NA[/C][C]NA[/C][C]-3385.83[/C][C]NA[/C][/ROW]
[ROW][C]117[/C][C]26502[/C][C]NA[/C][C]NA[/C][C]1171.18[/C][C]NA[/C][/ROW]
[ROW][C]118[/C][C]18649[/C][C]NA[/C][C]NA[/C][C]-2804.9[/C][C]NA[/C][/ROW]
[ROW][C]119[/C][C]12444[/C][C]NA[/C][C]NA[/C][C]-7504.11[/C][C]NA[/C][/ROW]
[ROW][C]120[/C][C]15040[/C][C]NA[/C][C]NA[/C][C]-3783.87[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=295937&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=295937&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
1181896NANA2386.82NA
2181580NANA-265.476NA
3181234NANA1304.64NA
4180598NANA-1251.18NA
5187123NANA7281.42NA
6186807NANA10160.5NA
7181896178085181394-3309.183811.26
8178638177913181299-3385.83724.916
91789541824031812321171.18-3448.68
10178954178413181218-2804.9540.564
11179269173605181109-7504.115664.24
12179936177271181055-3783.872665.29
131815801832921809062386.82-1712.32
14179616180313180578-265.476-696.816
151815801816641803591304.64-83.686
16179936178957180208-1251.18978.726
171851581872311799507281.42-2073.17
1818746918974217958210160.5-2273.12
19177656175985179294-3309.181671.14
20175025175771179157-3385.83-746.167
211773051801911790201171.18-2886.14
22176989176091178896-2804.9898.022
23175025171297178801-7504.113728.24
24175345174813178596-3783.87532.416
251792691806271782402386.82-1357.98
26178638177646177912-265.476991.851
271792691790941777891304.64175.356
28179269176430177681-1251.182839.35
291835451846911774097281.42-1145.58
3018417618727017711010160.5-3094.2
31172398173555176864-3309.18-1157.15
32172398173178176564-3385.83-779.792
331769891773391761681171.18-350.098
34174709172751175556-2804.91957.98
35170785167343174847-7504.113441.69
36172398170463174247-3783.871934.83
371763271760201736342386.82306.643
38174363172700172966-265.4761662.52
391740471736721723671304.64375.272
40169803170544171795-1251.18-740.524
411760071783531710727281.42-2346.17
4217730518045617029610160.5-3151.5
43164545166211169520-3309.18-1666.07
44164229165426168812-3385.83-1196.88
451707851693151681441171.181469.69
46167176164616167421-2804.92559.73
47160967159289166793-7504.111677.74
48163598162410166193-3783.871188.5
491665091678591654722386.82-1349.69
50167176164390164655-265.4762786.06
511652121650061637021304.64205.606
52161287161238162489-1251.1848.8511
531694561683671610867281.421088.96
5416945616978715962710160.5-331.079
55155078154928158238-3309.18149.638
56154101153354156740-3385.83746.666
571580251561951550241171.181830.11
58150838150406153211-2804.9431.939
59143616143799151303-7504.11-183.098
60145932145598149382-3783.87333.583
611508381498621474752386.82976.434
62146910145328145594-265.4761581.98
631442831449891436841304.64-706.103
64138710140429141681-1251.18-1719.44
651462471468501395697281.42-603.042
6614656314760213744210160.5-1039.45
67132190132059135368-3309.18131.263
68131839129854133240-3385.831984.83
691344701323261311541171.182144.36
70126301126373129178-2804.9-72.436
71117465119752127256-7504.11-2287.01
72121043121646125430-3783.87-603.376
731259501259771235902386.82-26.7323
74120728121280121545-265.476-551.649
751204121206561193511304.64-243.894
76115154115864117115-1251.18-709.774
771236701221191148387281.421550.83
7812531912268211252110160.52637.38
79109266106895110205-3309.182370.51
80105688104475107860-3385.831213.42
811079681066871055161171.181280.82
8299132100476103281-2804.9-1344.35
838998193583.5101088-7504.11-3602.47
849292895067.698851.5-3783.87-2139.58
859847098825.396438.52386.82-355.316
86919469370693971.5-265.476-1759.98
879292892957.991653.31304.64-29.936
888900488111.889363-1251.18892.226
899717294354.387072.87281.422817.75
909815094969.784809.210160.53180.34
917852479304.882614-3309.18-780.82
927722177019.780405.5-3385.83201.333
938079979217.878046.61171.181581.19
947133372704.775509.6-2804.9-1371.69
956281765319.272823.3-7504.11-2502.22
966576466367.970151.8-3783.87-603.876
977295069893.467506.62386.823056.6
986446264622.464887.9-265.476-160.399
996379963601.6622971304.64197.356
1005724458495.959747-1251.18-1251.86
1016446264532.557251.17281.42-70.5424
1026674264970.954810.410160.51771.13
1034644849169.952479.1-3309.18-2721.9
1044644846788.550174.3-3385.83-340.459
1054939149204.448033.21171.18186.61
1064154243333.946138.8-2804.9-1791.89
1073270636835.244339.3-7504.11-4129.22
1083729738796.942580.8-3783.87-1499.92
1094546643195.8408092386.822270.23
1103663138676.738942.2-265.476-2045.69
1114024438326.137021.51304.641917.9
1123533333862.735113.9-1251.181470.31
1134318640597.233315.87281.422588.83
1144581341704.631544.110160.54108.38
11524853NANA-3309.18NA
11623240NANA-3385.83NA
11726502NANA1171.18NA
11818649NANA-2804.9NA
11912444NANA-7504.11NA
12015040NANA-3783.87NA


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')