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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationSun, 09 Aug 2015 15:52:17 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/09/t1439132042aim0fohc1ichzbx.htm/, Retrieved Wed, 15 May 2024 08:01:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=279954, Retrieved Wed, 15 May 2024 08:01:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsClassic Decomposition Reeks B Sebastiaan Lunders Reeks B Sebastiaan Lunders MAR204A Aantal verkochte exemplaren "Financial Times" Ottevaere
Estimated Impact161

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Datareeks - Aanta...] [2014-09-20 19:16:40] [ce8eed4eee7214d9613cef9db4d6a404]
- R PD  [Univariate Data Series] [Reeks B beschrijv...] [2015-08-08 13:11:55] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP     [Histogram] [Histogram & Frequ...] [2015-08-08 13:19:29] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP       [Kernel Density Estimation] [Dichtheidsgrafiek...] [2015-08-08 13:26:11] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMPD        [Notched Boxplots] [Notched Boxplots ...] [2015-08-08 13:32:37] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP           [Harrell-Davis Quantiles] [Decielen Reeks B ...] [2015-08-08 13:36:12] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- R P             [Harrell-Davis Quantiles] [Percentielen Reek...] [2015-08-08 13:40:38] [ae4fb4fa0c3c4ff80e7ff1f0f4c7f14a]
- RMP               [Central Tendency] [Central tendency ...] [2015-08-08 13:58:36] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RM                  [Mean versus Median] [Mean versus Media...] [2015-08-08 14:14:22] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                   [Mean Plot] [Mean plot Reeks B...] [2015-08-08 14:23:08] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                     [(Partial) Autocorrelation Function] [Autocorrelation R...] [2015-08-08 15:43:39] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                       [Variability] [Variability Reeks...] [2015-08-09 13:39:05] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                         [Standard Deviation-Mean Plot] [Standard Deviatio...] [2015-08-09 13:45:20] [039d3b62ab99f9eeb4c9cc4c099c66fc]
- RMP                             [Classical Decomposition] [Classic Decomposi...] [2015-08-09 14:52:17] [2cf7618d5ff65529ef2e27cea5366de0] [Current]
- RMP                               [Exponential Smoothing] [Exponential Smoot...] [2015-08-09 15:17:07] [039d3b62ab99f9eeb4c9cc4c099c66fc]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
982800
946400
1001000
800800
1037400
1019200
1092000
1128400
1255800
1092000
1037400
1292200
1092000
819000
964600
728000
1019200
837200
1110200
1001000
1055600
1183000
1164800
1383200
1001000
837200
928200
673400
964600
746200
1055600
1001000
891800
1274000
1146600
1310400
982800
910000
819000
673400
891800
800800
1092000
1055600
910000
1219400
1128400
1456000
1164800
709800
709800
709800
837200
837200
1128400
1037400
928200
1164800
1073800
1547000
1219400
709800
746200
618800
855400
982800
1237600
1219400
982800
1146600
1019200
1456000
1110200
891800
800800
600600
891800
1073800
1255800
1183000
873600
1255800
982800
1510600
1255800
910000
837200
564200
891800
855400
1292200
1292200
982800
1274000
946400
1474200
1255800
928200
709800
491400
964600
928200
1219400
1401400
1037400
1164800
873600
1510600

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279954&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279954&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279954&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'Gertrude Mary Cox' @ cox.wessa.net






Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1982800NANA123727NA
2946400NANA-174109NA
31001000NANA-199418NA
4800800NANA-380660NA
51037400NANA-98085.7NA
61019200NANA-130220NA
7109200012020801061670140410-110077
811284001156770106091095858.1-28366.4
9125580010218801054080-32205.5233922
10109200012365801049530187048-144581
1110374001096000104574050263.3-58604.9
12129220014547901037400417391-162591
13109200011543001030580123727-62301.8
148190008519161026020-174109-32916.4
159646008129571012370-199418151643
167280006271651007820-380660100835
1710192009188391016920-98085.7100361
188372008958051026020-130220-58604.9
19111020011664401026020140410-56235.2
2010010001118850102299095858.1-117850
2110556009900281022230-32205.565572.1
22118300012054901018440187048-22489.3
2311648001064150101389050263.3100645
24138320014252201007820417391-42016.4
25100100011254901001760123727-124485
26837200825375999483-17410911825.3
27928200793240992658-199418134960
28673400608965989625-38066064434.6
29964600894573992658-98085.770027.3
30746200858647988867-130220-112447
3110556001125490985075140410-69885.2
321001000108321098735095858.1-82208.1
33891800953628985833-32205.5-61827.9
3412740001168330981283187048105669
351146600102851097825050263.3118087
3613104001394880977492417391-84483.1
379828001105010981283123727-122210
38910000810966985075-17410999033.6
39819000788690988108-19941830309.6
40673400605932986592-38066067468
41891800885473983558-98085.76327.34
42800800858647988867-130220-57846.6
43109200011429301002520140410-50926.8
4410556001097620100176095858.1-42016.4
45910000956661988867-32205.5-46661.2
461219400117288098583318704846519
471128400103534098507550263.393061.7
481456000140171098431741739154291.9
491164800111108098735012372753723.2
50709800814000988108-174109-104200
51709800788690988108-199418-78890.4
52709800605932986592-380660103868
53837200883956982042-98085.7-46756
54837200853338983558-130220-16138.3
5511284001130040989625140410-1635.16
561037400108776099190095858.1-50358.1
57928200961211993417-32205.5-33011.2
5811648001178190991142187048-13389.3
591073800103837098810850263.335428.4
6015470001412320994933417391134675
6112194001129280100555012372790123.2
627098008435751017680-174109-133775
637462008281241027540-199418-81923.7
646188006483991029060-380660-29598.7
658554009279391026020-98085.7-72539.3
669828008897381019960-13022093061.7
6712376001152030101162014041085573.2
6812194001110510101465095858.1108892
699828009923031024510-32205.5-9502.86
70114660012130701026020187048-66472.7
7110192001077050102678050263.3-57846.6
721456000144948010320904173916516.93
73111020011603701036640123727-50168.5
748918008617751035880-17410930025.3
758008008303991029820-199418-29598.7
766006006491571029820-380660-48557
778918009347641032850-98085.7-42964.3
7810738009033881033610-130220170412
7912558001182360104195014041073439.8
8011830001144630104878095858.138366.9
8187360010188401051050-32205.5-145245
8212558001238100105105018704817702.3
839828001099800104953050263.3-116997
8415106001457820104043041739152775.3
8512558001156580103285012372799223.2
869100008648081038920-17410945191.9
878372008485991048020-199418-11398.7
885642006726651053320-380660-108465
898918009544811052570-98085.7-62681
908554009193131049530-130220-63913.3
91129220011884301048020140410103773
9212922001144630104878095858.1147567
9398280010120201044220-32205.5-29219.5
9412740001222930103588018704851069
959464001086150103588050263.3-139747
9614742001459340104195041739114858.6
9712558001165680104195012372790123.2
989282008693581043470-17410958841.9
997098008508741050290-199418-141074
1004914006673571048020-380660-175957
1019646009423481040430-98085.722252.3
1029282009086971038920-13022019503.4
1031219400NANA140410NA
1041401400NANA95858.1NA
1051037400NANA-32205.5NA
1061164800NANA187048NA
107873600NANA50263.3NA
1081510600NANA417391NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 982800 & NA & NA & 123727 & NA \tabularnewline
2 & 946400 & NA & NA & -174109 & NA \tabularnewline
3 & 1001000 & NA & NA & -199418 & NA \tabularnewline
4 & 800800 & NA & NA & -380660 & NA \tabularnewline
5 & 1037400 & NA & NA & -98085.7 & NA \tabularnewline
6 & 1019200 & NA & NA & -130220 & NA \tabularnewline
7 & 1092000 & 1202080 & 1061670 & 140410 & -110077 \tabularnewline
8 & 1128400 & 1156770 & 1060910 & 95858.1 & -28366.4 \tabularnewline
9 & 1255800 & 1021880 & 1054080 & -32205.5 & 233922 \tabularnewline
10 & 1092000 & 1236580 & 1049530 & 187048 & -144581 \tabularnewline
11 & 1037400 & 1096000 & 1045740 & 50263.3 & -58604.9 \tabularnewline
12 & 1292200 & 1454790 & 1037400 & 417391 & -162591 \tabularnewline
13 & 1092000 & 1154300 & 1030580 & 123727 & -62301.8 \tabularnewline
14 & 819000 & 851916 & 1026020 & -174109 & -32916.4 \tabularnewline
15 & 964600 & 812957 & 1012370 & -199418 & 151643 \tabularnewline
16 & 728000 & 627165 & 1007820 & -380660 & 100835 \tabularnewline
17 & 1019200 & 918839 & 1016920 & -98085.7 & 100361 \tabularnewline
18 & 837200 & 895805 & 1026020 & -130220 & -58604.9 \tabularnewline
19 & 1110200 & 1166440 & 1026020 & 140410 & -56235.2 \tabularnewline
20 & 1001000 & 1118850 & 1022990 & 95858.1 & -117850 \tabularnewline
21 & 1055600 & 990028 & 1022230 & -32205.5 & 65572.1 \tabularnewline
22 & 1183000 & 1205490 & 1018440 & 187048 & -22489.3 \tabularnewline
23 & 1164800 & 1064150 & 1013890 & 50263.3 & 100645 \tabularnewline
24 & 1383200 & 1425220 & 1007820 & 417391 & -42016.4 \tabularnewline
25 & 1001000 & 1125490 & 1001760 & 123727 & -124485 \tabularnewline
26 & 837200 & 825375 & 999483 & -174109 & 11825.3 \tabularnewline
27 & 928200 & 793240 & 992658 & -199418 & 134960 \tabularnewline
28 & 673400 & 608965 & 989625 & -380660 & 64434.6 \tabularnewline
29 & 964600 & 894573 & 992658 & -98085.7 & 70027.3 \tabularnewline
30 & 746200 & 858647 & 988867 & -130220 & -112447 \tabularnewline
31 & 1055600 & 1125490 & 985075 & 140410 & -69885.2 \tabularnewline
32 & 1001000 & 1083210 & 987350 & 95858.1 & -82208.1 \tabularnewline
33 & 891800 & 953628 & 985833 & -32205.5 & -61827.9 \tabularnewline
34 & 1274000 & 1168330 & 981283 & 187048 & 105669 \tabularnewline
35 & 1146600 & 1028510 & 978250 & 50263.3 & 118087 \tabularnewline
36 & 1310400 & 1394880 & 977492 & 417391 & -84483.1 \tabularnewline
37 & 982800 & 1105010 & 981283 & 123727 & -122210 \tabularnewline
38 & 910000 & 810966 & 985075 & -174109 & 99033.6 \tabularnewline
39 & 819000 & 788690 & 988108 & -199418 & 30309.6 \tabularnewline
40 & 673400 & 605932 & 986592 & -380660 & 67468 \tabularnewline
41 & 891800 & 885473 & 983558 & -98085.7 & 6327.34 \tabularnewline
42 & 800800 & 858647 & 988867 & -130220 & -57846.6 \tabularnewline
43 & 1092000 & 1142930 & 1002520 & 140410 & -50926.8 \tabularnewline
44 & 1055600 & 1097620 & 1001760 & 95858.1 & -42016.4 \tabularnewline
45 & 910000 & 956661 & 988867 & -32205.5 & -46661.2 \tabularnewline
46 & 1219400 & 1172880 & 985833 & 187048 & 46519 \tabularnewline
47 & 1128400 & 1035340 & 985075 & 50263.3 & 93061.7 \tabularnewline
48 & 1456000 & 1401710 & 984317 & 417391 & 54291.9 \tabularnewline
49 & 1164800 & 1111080 & 987350 & 123727 & 53723.2 \tabularnewline
50 & 709800 & 814000 & 988108 & -174109 & -104200 \tabularnewline
51 & 709800 & 788690 & 988108 & -199418 & -78890.4 \tabularnewline
52 & 709800 & 605932 & 986592 & -380660 & 103868 \tabularnewline
53 & 837200 & 883956 & 982042 & -98085.7 & -46756 \tabularnewline
54 & 837200 & 853338 & 983558 & -130220 & -16138.3 \tabularnewline
55 & 1128400 & 1130040 & 989625 & 140410 & -1635.16 \tabularnewline
56 & 1037400 & 1087760 & 991900 & 95858.1 & -50358.1 \tabularnewline
57 & 928200 & 961211 & 993417 & -32205.5 & -33011.2 \tabularnewline
58 & 1164800 & 1178190 & 991142 & 187048 & -13389.3 \tabularnewline
59 & 1073800 & 1038370 & 988108 & 50263.3 & 35428.4 \tabularnewline
60 & 1547000 & 1412320 & 994933 & 417391 & 134675 \tabularnewline
61 & 1219400 & 1129280 & 1005550 & 123727 & 90123.2 \tabularnewline
62 & 709800 & 843575 & 1017680 & -174109 & -133775 \tabularnewline
63 & 746200 & 828124 & 1027540 & -199418 & -81923.7 \tabularnewline
64 & 618800 & 648399 & 1029060 & -380660 & -29598.7 \tabularnewline
65 & 855400 & 927939 & 1026020 & -98085.7 & -72539.3 \tabularnewline
66 & 982800 & 889738 & 1019960 & -130220 & 93061.7 \tabularnewline
67 & 1237600 & 1152030 & 1011620 & 140410 & 85573.2 \tabularnewline
68 & 1219400 & 1110510 & 1014650 & 95858.1 & 108892 \tabularnewline
69 & 982800 & 992303 & 1024510 & -32205.5 & -9502.86 \tabularnewline
70 & 1146600 & 1213070 & 1026020 & 187048 & -66472.7 \tabularnewline
71 & 1019200 & 1077050 & 1026780 & 50263.3 & -57846.6 \tabularnewline
72 & 1456000 & 1449480 & 1032090 & 417391 & 6516.93 \tabularnewline
73 & 1110200 & 1160370 & 1036640 & 123727 & -50168.5 \tabularnewline
74 & 891800 & 861775 & 1035880 & -174109 & 30025.3 \tabularnewline
75 & 800800 & 830399 & 1029820 & -199418 & -29598.7 \tabularnewline
76 & 600600 & 649157 & 1029820 & -380660 & -48557 \tabularnewline
77 & 891800 & 934764 & 1032850 & -98085.7 & -42964.3 \tabularnewline
78 & 1073800 & 903388 & 1033610 & -130220 & 170412 \tabularnewline
79 & 1255800 & 1182360 & 1041950 & 140410 & 73439.8 \tabularnewline
80 & 1183000 & 1144630 & 1048780 & 95858.1 & 38366.9 \tabularnewline
81 & 873600 & 1018840 & 1051050 & -32205.5 & -145245 \tabularnewline
82 & 1255800 & 1238100 & 1051050 & 187048 & 17702.3 \tabularnewline
83 & 982800 & 1099800 & 1049530 & 50263.3 & -116997 \tabularnewline
84 & 1510600 & 1457820 & 1040430 & 417391 & 52775.3 \tabularnewline
85 & 1255800 & 1156580 & 1032850 & 123727 & 99223.2 \tabularnewline
86 & 910000 & 864808 & 1038920 & -174109 & 45191.9 \tabularnewline
87 & 837200 & 848599 & 1048020 & -199418 & -11398.7 \tabularnewline
88 & 564200 & 672665 & 1053320 & -380660 & -108465 \tabularnewline
89 & 891800 & 954481 & 1052570 & -98085.7 & -62681 \tabularnewline
90 & 855400 & 919313 & 1049530 & -130220 & -63913.3 \tabularnewline
91 & 1292200 & 1188430 & 1048020 & 140410 & 103773 \tabularnewline
92 & 1292200 & 1144630 & 1048780 & 95858.1 & 147567 \tabularnewline
93 & 982800 & 1012020 & 1044220 & -32205.5 & -29219.5 \tabularnewline
94 & 1274000 & 1222930 & 1035880 & 187048 & 51069 \tabularnewline
95 & 946400 & 1086150 & 1035880 & 50263.3 & -139747 \tabularnewline
96 & 1474200 & 1459340 & 1041950 & 417391 & 14858.6 \tabularnewline
97 & 1255800 & 1165680 & 1041950 & 123727 & 90123.2 \tabularnewline
98 & 928200 & 869358 & 1043470 & -174109 & 58841.9 \tabularnewline
99 & 709800 & 850874 & 1050290 & -199418 & -141074 \tabularnewline
100 & 491400 & 667357 & 1048020 & -380660 & -175957 \tabularnewline
101 & 964600 & 942348 & 1040430 & -98085.7 & 22252.3 \tabularnewline
102 & 928200 & 908697 & 1038920 & -130220 & 19503.4 \tabularnewline
103 & 1219400 & NA & NA & 140410 & NA \tabularnewline
104 & 1401400 & NA & NA & 95858.1 & NA \tabularnewline
105 & 1037400 & NA & NA & -32205.5 & NA \tabularnewline
106 & 1164800 & NA & NA & 187048 & NA \tabularnewline
107 & 873600 & NA & NA & 50263.3 & NA \tabularnewline
108 & 1510600 & NA & NA & 417391 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=279954&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]982800[/C][C]NA[/C][C]NA[/C][C]123727[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]946400[/C][C]NA[/C][C]NA[/C][C]-174109[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1001000[/C][C]NA[/C][C]NA[/C][C]-199418[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]800800[/C][C]NA[/C][C]NA[/C][C]-380660[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1037400[/C][C]NA[/C][C]NA[/C][C]-98085.7[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1019200[/C][C]NA[/C][C]NA[/C][C]-130220[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]1092000[/C][C]1202080[/C][C]1061670[/C][C]140410[/C][C]-110077[/C][/ROW]
[ROW][C]8[/C][C]1128400[/C][C]1156770[/C][C]1060910[/C][C]95858.1[/C][C]-28366.4[/C][/ROW]
[ROW][C]9[/C][C]1255800[/C][C]1021880[/C][C]1054080[/C][C]-32205.5[/C][C]233922[/C][/ROW]
[ROW][C]10[/C][C]1092000[/C][C]1236580[/C][C]1049530[/C][C]187048[/C][C]-144581[/C][/ROW]
[ROW][C]11[/C][C]1037400[/C][C]1096000[/C][C]1045740[/C][C]50263.3[/C][C]-58604.9[/C][/ROW]
[ROW][C]12[/C][C]1292200[/C][C]1454790[/C][C]1037400[/C][C]417391[/C][C]-162591[/C][/ROW]
[ROW][C]13[/C][C]1092000[/C][C]1154300[/C][C]1030580[/C][C]123727[/C][C]-62301.8[/C][/ROW]
[ROW][C]14[/C][C]819000[/C][C]851916[/C][C]1026020[/C][C]-174109[/C][C]-32916.4[/C][/ROW]
[ROW][C]15[/C][C]964600[/C][C]812957[/C][C]1012370[/C][C]-199418[/C][C]151643[/C][/ROW]
[ROW][C]16[/C][C]728000[/C][C]627165[/C][C]1007820[/C][C]-380660[/C][C]100835[/C][/ROW]
[ROW][C]17[/C][C]1019200[/C][C]918839[/C][C]1016920[/C][C]-98085.7[/C][C]100361[/C][/ROW]
[ROW][C]18[/C][C]837200[/C][C]895805[/C][C]1026020[/C][C]-130220[/C][C]-58604.9[/C][/ROW]
[ROW][C]19[/C][C]1110200[/C][C]1166440[/C][C]1026020[/C][C]140410[/C][C]-56235.2[/C][/ROW]
[ROW][C]20[/C][C]1001000[/C][C]1118850[/C][C]1022990[/C][C]95858.1[/C][C]-117850[/C][/ROW]
[ROW][C]21[/C][C]1055600[/C][C]990028[/C][C]1022230[/C][C]-32205.5[/C][C]65572.1[/C][/ROW]
[ROW][C]22[/C][C]1183000[/C][C]1205490[/C][C]1018440[/C][C]187048[/C][C]-22489.3[/C][/ROW]
[ROW][C]23[/C][C]1164800[/C][C]1064150[/C][C]1013890[/C][C]50263.3[/C][C]100645[/C][/ROW]
[ROW][C]24[/C][C]1383200[/C][C]1425220[/C][C]1007820[/C][C]417391[/C][C]-42016.4[/C][/ROW]
[ROW][C]25[/C][C]1001000[/C][C]1125490[/C][C]1001760[/C][C]123727[/C][C]-124485[/C][/ROW]
[ROW][C]26[/C][C]837200[/C][C]825375[/C][C]999483[/C][C]-174109[/C][C]11825.3[/C][/ROW]
[ROW][C]27[/C][C]928200[/C][C]793240[/C][C]992658[/C][C]-199418[/C][C]134960[/C][/ROW]
[ROW][C]28[/C][C]673400[/C][C]608965[/C][C]989625[/C][C]-380660[/C][C]64434.6[/C][/ROW]
[ROW][C]29[/C][C]964600[/C][C]894573[/C][C]992658[/C][C]-98085.7[/C][C]70027.3[/C][/ROW]
[ROW][C]30[/C][C]746200[/C][C]858647[/C][C]988867[/C][C]-130220[/C][C]-112447[/C][/ROW]
[ROW][C]31[/C][C]1055600[/C][C]1125490[/C][C]985075[/C][C]140410[/C][C]-69885.2[/C][/ROW]
[ROW][C]32[/C][C]1001000[/C][C]1083210[/C][C]987350[/C][C]95858.1[/C][C]-82208.1[/C][/ROW]
[ROW][C]33[/C][C]891800[/C][C]953628[/C][C]985833[/C][C]-32205.5[/C][C]-61827.9[/C][/ROW]
[ROW][C]34[/C][C]1274000[/C][C]1168330[/C][C]981283[/C][C]187048[/C][C]105669[/C][/ROW]
[ROW][C]35[/C][C]1146600[/C][C]1028510[/C][C]978250[/C][C]50263.3[/C][C]118087[/C][/ROW]
[ROW][C]36[/C][C]1310400[/C][C]1394880[/C][C]977492[/C][C]417391[/C][C]-84483.1[/C][/ROW]
[ROW][C]37[/C][C]982800[/C][C]1105010[/C][C]981283[/C][C]123727[/C][C]-122210[/C][/ROW]
[ROW][C]38[/C][C]910000[/C][C]810966[/C][C]985075[/C][C]-174109[/C][C]99033.6[/C][/ROW]
[ROW][C]39[/C][C]819000[/C][C]788690[/C][C]988108[/C][C]-199418[/C][C]30309.6[/C][/ROW]
[ROW][C]40[/C][C]673400[/C][C]605932[/C][C]986592[/C][C]-380660[/C][C]67468[/C][/ROW]
[ROW][C]41[/C][C]891800[/C][C]885473[/C][C]983558[/C][C]-98085.7[/C][C]6327.34[/C][/ROW]
[ROW][C]42[/C][C]800800[/C][C]858647[/C][C]988867[/C][C]-130220[/C][C]-57846.6[/C][/ROW]
[ROW][C]43[/C][C]1092000[/C][C]1142930[/C][C]1002520[/C][C]140410[/C][C]-50926.8[/C][/ROW]
[ROW][C]44[/C][C]1055600[/C][C]1097620[/C][C]1001760[/C][C]95858.1[/C][C]-42016.4[/C][/ROW]
[ROW][C]45[/C][C]910000[/C][C]956661[/C][C]988867[/C][C]-32205.5[/C][C]-46661.2[/C][/ROW]
[ROW][C]46[/C][C]1219400[/C][C]1172880[/C][C]985833[/C][C]187048[/C][C]46519[/C][/ROW]
[ROW][C]47[/C][C]1128400[/C][C]1035340[/C][C]985075[/C][C]50263.3[/C][C]93061.7[/C][/ROW]
[ROW][C]48[/C][C]1456000[/C][C]1401710[/C][C]984317[/C][C]417391[/C][C]54291.9[/C][/ROW]
[ROW][C]49[/C][C]1164800[/C][C]1111080[/C][C]987350[/C][C]123727[/C][C]53723.2[/C][/ROW]
[ROW][C]50[/C][C]709800[/C][C]814000[/C][C]988108[/C][C]-174109[/C][C]-104200[/C][/ROW]
[ROW][C]51[/C][C]709800[/C][C]788690[/C][C]988108[/C][C]-199418[/C][C]-78890.4[/C][/ROW]
[ROW][C]52[/C][C]709800[/C][C]605932[/C][C]986592[/C][C]-380660[/C][C]103868[/C][/ROW]
[ROW][C]53[/C][C]837200[/C][C]883956[/C][C]982042[/C][C]-98085.7[/C][C]-46756[/C][/ROW]
[ROW][C]54[/C][C]837200[/C][C]853338[/C][C]983558[/C][C]-130220[/C][C]-16138.3[/C][/ROW]
[ROW][C]55[/C][C]1128400[/C][C]1130040[/C][C]989625[/C][C]140410[/C][C]-1635.16[/C][/ROW]
[ROW][C]56[/C][C]1037400[/C][C]1087760[/C][C]991900[/C][C]95858.1[/C][C]-50358.1[/C][/ROW]
[ROW][C]57[/C][C]928200[/C][C]961211[/C][C]993417[/C][C]-32205.5[/C][C]-33011.2[/C][/ROW]
[ROW][C]58[/C][C]1164800[/C][C]1178190[/C][C]991142[/C][C]187048[/C][C]-13389.3[/C][/ROW]
[ROW][C]59[/C][C]1073800[/C][C]1038370[/C][C]988108[/C][C]50263.3[/C][C]35428.4[/C][/ROW]
[ROW][C]60[/C][C]1547000[/C][C]1412320[/C][C]994933[/C][C]417391[/C][C]134675[/C][/ROW]
[ROW][C]61[/C][C]1219400[/C][C]1129280[/C][C]1005550[/C][C]123727[/C][C]90123.2[/C][/ROW]
[ROW][C]62[/C][C]709800[/C][C]843575[/C][C]1017680[/C][C]-174109[/C][C]-133775[/C][/ROW]
[ROW][C]63[/C][C]746200[/C][C]828124[/C][C]1027540[/C][C]-199418[/C][C]-81923.7[/C][/ROW]
[ROW][C]64[/C][C]618800[/C][C]648399[/C][C]1029060[/C][C]-380660[/C][C]-29598.7[/C][/ROW]
[ROW][C]65[/C][C]855400[/C][C]927939[/C][C]1026020[/C][C]-98085.7[/C][C]-72539.3[/C][/ROW]
[ROW][C]66[/C][C]982800[/C][C]889738[/C][C]1019960[/C][C]-130220[/C][C]93061.7[/C][/ROW]
[ROW][C]67[/C][C]1237600[/C][C]1152030[/C][C]1011620[/C][C]140410[/C][C]85573.2[/C][/ROW]
[ROW][C]68[/C][C]1219400[/C][C]1110510[/C][C]1014650[/C][C]95858.1[/C][C]108892[/C][/ROW]
[ROW][C]69[/C][C]982800[/C][C]992303[/C][C]1024510[/C][C]-32205.5[/C][C]-9502.86[/C][/ROW]
[ROW][C]70[/C][C]1146600[/C][C]1213070[/C][C]1026020[/C][C]187048[/C][C]-66472.7[/C][/ROW]
[ROW][C]71[/C][C]1019200[/C][C]1077050[/C][C]1026780[/C][C]50263.3[/C][C]-57846.6[/C][/ROW]
[ROW][C]72[/C][C]1456000[/C][C]1449480[/C][C]1032090[/C][C]417391[/C][C]6516.93[/C][/ROW]
[ROW][C]73[/C][C]1110200[/C][C]1160370[/C][C]1036640[/C][C]123727[/C][C]-50168.5[/C][/ROW]
[ROW][C]74[/C][C]891800[/C][C]861775[/C][C]1035880[/C][C]-174109[/C][C]30025.3[/C][/ROW]
[ROW][C]75[/C][C]800800[/C][C]830399[/C][C]1029820[/C][C]-199418[/C][C]-29598.7[/C][/ROW]
[ROW][C]76[/C][C]600600[/C][C]649157[/C][C]1029820[/C][C]-380660[/C][C]-48557[/C][/ROW]
[ROW][C]77[/C][C]891800[/C][C]934764[/C][C]1032850[/C][C]-98085.7[/C][C]-42964.3[/C][/ROW]
[ROW][C]78[/C][C]1073800[/C][C]903388[/C][C]1033610[/C][C]-130220[/C][C]170412[/C][/ROW]
[ROW][C]79[/C][C]1255800[/C][C]1182360[/C][C]1041950[/C][C]140410[/C][C]73439.8[/C][/ROW]
[ROW][C]80[/C][C]1183000[/C][C]1144630[/C][C]1048780[/C][C]95858.1[/C][C]38366.9[/C][/ROW]
[ROW][C]81[/C][C]873600[/C][C]1018840[/C][C]1051050[/C][C]-32205.5[/C][C]-145245[/C][/ROW]
[ROW][C]82[/C][C]1255800[/C][C]1238100[/C][C]1051050[/C][C]187048[/C][C]17702.3[/C][/ROW]
[ROW][C]83[/C][C]982800[/C][C]1099800[/C][C]1049530[/C][C]50263.3[/C][C]-116997[/C][/ROW]
[ROW][C]84[/C][C]1510600[/C][C]1457820[/C][C]1040430[/C][C]417391[/C][C]52775.3[/C][/ROW]
[ROW][C]85[/C][C]1255800[/C][C]1156580[/C][C]1032850[/C][C]123727[/C][C]99223.2[/C][/ROW]
[ROW][C]86[/C][C]910000[/C][C]864808[/C][C]1038920[/C][C]-174109[/C][C]45191.9[/C][/ROW]
[ROW][C]87[/C][C]837200[/C][C]848599[/C][C]1048020[/C][C]-199418[/C][C]-11398.7[/C][/ROW]
[ROW][C]88[/C][C]564200[/C][C]672665[/C][C]1053320[/C][C]-380660[/C][C]-108465[/C][/ROW]
[ROW][C]89[/C][C]891800[/C][C]954481[/C][C]1052570[/C][C]-98085.7[/C][C]-62681[/C][/ROW]
[ROW][C]90[/C][C]855400[/C][C]919313[/C][C]1049530[/C][C]-130220[/C][C]-63913.3[/C][/ROW]
[ROW][C]91[/C][C]1292200[/C][C]1188430[/C][C]1048020[/C][C]140410[/C][C]103773[/C][/ROW]
[ROW][C]92[/C][C]1292200[/C][C]1144630[/C][C]1048780[/C][C]95858.1[/C][C]147567[/C][/ROW]
[ROW][C]93[/C][C]982800[/C][C]1012020[/C][C]1044220[/C][C]-32205.5[/C][C]-29219.5[/C][/ROW]
[ROW][C]94[/C][C]1274000[/C][C]1222930[/C][C]1035880[/C][C]187048[/C][C]51069[/C][/ROW]
[ROW][C]95[/C][C]946400[/C][C]1086150[/C][C]1035880[/C][C]50263.3[/C][C]-139747[/C][/ROW]
[ROW][C]96[/C][C]1474200[/C][C]1459340[/C][C]1041950[/C][C]417391[/C][C]14858.6[/C][/ROW]
[ROW][C]97[/C][C]1255800[/C][C]1165680[/C][C]1041950[/C][C]123727[/C][C]90123.2[/C][/ROW]
[ROW][C]98[/C][C]928200[/C][C]869358[/C][C]1043470[/C][C]-174109[/C][C]58841.9[/C][/ROW]
[ROW][C]99[/C][C]709800[/C][C]850874[/C][C]1050290[/C][C]-199418[/C][C]-141074[/C][/ROW]
[ROW][C]100[/C][C]491400[/C][C]667357[/C][C]1048020[/C][C]-380660[/C][C]-175957[/C][/ROW]
[ROW][C]101[/C][C]964600[/C][C]942348[/C][C]1040430[/C][C]-98085.7[/C][C]22252.3[/C][/ROW]
[ROW][C]102[/C][C]928200[/C][C]908697[/C][C]1038920[/C][C]-130220[/C][C]19503.4[/C][/ROW]
[ROW][C]103[/C][C]1219400[/C][C]NA[/C][C]NA[/C][C]140410[/C][C]NA[/C][/ROW]
[ROW][C]104[/C][C]1401400[/C][C]NA[/C][C]NA[/C][C]95858.1[/C][C]NA[/C][/ROW]
[ROW][C]105[/C][C]1037400[/C][C]NA[/C][C]NA[/C][C]-32205.5[/C][C]NA[/C][/ROW]
[ROW][C]106[/C][C]1164800[/C][C]NA[/C][C]NA[/C][C]187048[/C][C]NA[/C][/ROW]
[ROW][C]107[/C][C]873600[/C][C]NA[/C][C]NA[/C][C]50263.3[/C][C]NA[/C][/ROW]
[ROW][C]108[/C][C]1510600[/C][C]NA[/C][C]NA[/C][C]417391[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=279954&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=279954&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
1982800NANA123727NA
2946400NANA-174109NA
31001000NANA-199418NA
4800800NANA-380660NA
51037400NANA-98085.7NA
61019200NANA-130220NA
7109200012020801061670140410-110077
811284001156770106091095858.1-28366.4
9125580010218801054080-32205.5233922
10109200012365801049530187048-144581
1110374001096000104574050263.3-58604.9
12129220014547901037400417391-162591
13109200011543001030580123727-62301.8
148190008519161026020-174109-32916.4
159646008129571012370-199418151643
167280006271651007820-380660100835
1710192009188391016920-98085.7100361
188372008958051026020-130220-58604.9
19111020011664401026020140410-56235.2
2010010001118850102299095858.1-117850
2110556009900281022230-32205.565572.1
22118300012054901018440187048-22489.3
2311648001064150101389050263.3100645
24138320014252201007820417391-42016.4
25100100011254901001760123727-124485
26837200825375999483-17410911825.3
27928200793240992658-199418134960
28673400608965989625-38066064434.6
29964600894573992658-98085.770027.3
30746200858647988867-130220-112447
3110556001125490985075140410-69885.2
321001000108321098735095858.1-82208.1
33891800953628985833-32205.5-61827.9
3412740001168330981283187048105669
351146600102851097825050263.3118087
3613104001394880977492417391-84483.1
379828001105010981283123727-122210
38910000810966985075-17410999033.6
39819000788690988108-19941830309.6
40673400605932986592-38066067468
41891800885473983558-98085.76327.34
42800800858647988867-130220-57846.6
43109200011429301002520140410-50926.8
4410556001097620100176095858.1-42016.4
45910000956661988867-32205.5-46661.2
461219400117288098583318704846519
471128400103534098507550263.393061.7
481456000140171098431741739154291.9
491164800111108098735012372753723.2
50709800814000988108-174109-104200
51709800788690988108-199418-78890.4
52709800605932986592-380660103868
53837200883956982042-98085.7-46756
54837200853338983558-130220-16138.3
5511284001130040989625140410-1635.16
561037400108776099190095858.1-50358.1
57928200961211993417-32205.5-33011.2
5811648001178190991142187048-13389.3
591073800103837098810850263.335428.4
6015470001412320994933417391134675
6112194001129280100555012372790123.2
627098008435751017680-174109-133775
637462008281241027540-199418-81923.7
646188006483991029060-380660-29598.7
658554009279391026020-98085.7-72539.3
669828008897381019960-13022093061.7
6712376001152030101162014041085573.2
6812194001110510101465095858.1108892
699828009923031024510-32205.5-9502.86
70114660012130701026020187048-66472.7
7110192001077050102678050263.3-57846.6
721456000144948010320904173916516.93
73111020011603701036640123727-50168.5
748918008617751035880-17410930025.3
758008008303991029820-199418-29598.7
766006006491571029820-380660-48557
778918009347641032850-98085.7-42964.3
7810738009033881033610-130220170412
7912558001182360104195014041073439.8
8011830001144630104878095858.138366.9
8187360010188401051050-32205.5-145245
8212558001238100105105018704817702.3
839828001099800104953050263.3-116997
8415106001457820104043041739152775.3
8512558001156580103285012372799223.2
869100008648081038920-17410945191.9
878372008485991048020-199418-11398.7
885642006726651053320-380660-108465
898918009544811052570-98085.7-62681
908554009193131049530-130220-63913.3
91129220011884301048020140410103773
9212922001144630104878095858.1147567
9398280010120201044220-32205.5-29219.5
9412740001222930103588018704851069
959464001086150103588050263.3-139747
9614742001459340104195041739114858.6
9712558001165680104195012372790123.2
989282008693581043470-17410958841.9
997098008508741050290-199418-141074
1004914006673571048020-380660-175957
1019646009423481040430-98085.722252.3
1029282009086971038920-13022019503.4
1031219400NANA140410NA
1041401400NANA95858.1NA
1051037400NANA-32205.5NA
1061164800NANA187048NA
107873600NANA50263.3NA
1081510600NANA417391NA


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')