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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationWed, 04 Dec 2013 13:05:25 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Dec/04/t1386180335gqre9gq9oz3xkhx.htm/, Retrieved Thu, 28 Mar 2024 18:54:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=230736, Retrieved Thu, 28 Mar 2024 18:54:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact77
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [(Partial) Autocorrelation Function] [WS9] [2013-12-04 17:50:02] [b007041690f75f30ec26eb43925b7b35]
- R P     [(Partial) Autocorrelation Function] [WS9] [2013-12-04 17:55:07] [b007041690f75f30ec26eb43925b7b35]
- RMP         [Classical Decomposition] [WS9 (1)] [2013-12-04 18:05:25] [9254bdaed6fbf9720c8f2260171d2ee9] [Current]
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Dataseries X:
655362
873127
1107897
1555964
1671159
1493308
2957796
2638691
1305669
1280496
921900
867888
652586
913831
1108544
1555827
1699283
1509458
3268975
2425016
1312703
1365498
934453
775019
651142
843192
1146766
1652601
1465906
1652734
2922334
2702805
1458956
1410363
1019279
936574
708917
885295
1099663
1576220
1487870
1488635
2882530
2677026
1404398
1344370
936865
872705
628151
953712
1160384
1400618
1661511
1495347
2918786
2775677
1407026
1370199
964526
850851
683118
847224
1073256
1514326
1503734
1507712
2865698
2788128
1391596
1366378
946295
859626




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230736&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230736&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230736&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net







Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1655362NANA-789447NA
2873127NANA-566057NA
31107897NANA-338946NA
41555964NANA81817.9NA
51671159NANA104641NA
61493308NANA71623.2NA
72957796297505014439901531070-17258.1
826386912630380144557011848108313.2
9130566913665101447290-80779.7-60843.7
10128049613436001447310-103709-63108.4
119219009477321448480-500748-25832.1
128678888560551450320-59427011833.2
136525866745161463960-789447-21930.4
149138319019691468030-56605711861.8
15110854411204701459420-338946-11925.6
1615558271545070146325081817.910758.5
17169928315719601467320104641127326
1815094581535590146397071623.2-26134.2
193268975299110014600401531070277871
202425016264184014570401184810-216828
21131270313749101455690-80779.7-62202.4
22136549813576001461310-1037097897.3
239344539548701455620-500748-20417.5
247750198575941451860-594270-82575.3
256511426539441443390-789447-2801.57
268431928744651440520-566057-31272.9
27114676611192401458190-33894627522.2
2816526011547970146615081817.9104630
29146590615762001471560104641-110292
3016527341553450148182071623.299287.9
312922334302203014909601531070-99692.7
32270280526799301495120118481022873.4
33145895614141401494910-80779.744820.8
34141036313860601489770-10370924302.5
3510192799867551487500-50074832524.3
369365748873101481580-59427049263.6
377089176836371473080-78944725279.7
388852959042951470350-566057-18999.8
39109966311280601467000-338946-28394.9
4015762201543800146198081817.932421
41148787015604401455800104641-72568.8
4214886351521330144970071623.2-32690.6
432882530297474014436801531070-92210.9
44267702626279701443160118481049056.2
45140439813677601448540-80779.736635.6
46134437013400501443760-1037094323.8
479368659429261443670-500748-6061.08
488727058569191451190-59427015786.2
496281516635321452980-789447-35380.9
509537128925431458600-56605761168.8
51116038411238701462820-33894636510.4
5214006181545820146401081817.9-145205
5316615111570880146623010464190635.4
5414953471538100146648071623.2-42752.5
552918786299892014678601531070-80135
562775677265052014657101184810125159
57140702613768601457640-80779.730163.8
58137019913550401458750-10370915158.8
599645269561661456910-5007488360.42
608508518565851450850-594270-5733.72
616831186597111449160-78944723407.2
628472248814081447460-566057-34183.7
63107325611083901447340-338946-35138.1
6415143261528360144654081817.9-14030
65150373415502601445620104641-46526.6
6615077121516850144523071623.2-9136.54
672865698NANA1531070NA
682788128NANA1184810NA
691391596NANA-80779.7NA
701366378NANA-103709NA
71946295NANA-500748NA
72859626NANA-594270NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 655362 & NA & NA & -789447 & NA \tabularnewline
2 & 873127 & NA & NA & -566057 & NA \tabularnewline
3 & 1107897 & NA & NA & -338946 & NA \tabularnewline
4 & 1555964 & NA & NA & 81817.9 & NA \tabularnewline
5 & 1671159 & NA & NA & 104641 & NA \tabularnewline
6 & 1493308 & NA & NA & 71623.2 & NA \tabularnewline
7 & 2957796 & 2975050 & 1443990 & 1531070 & -17258.1 \tabularnewline
8 & 2638691 & 2630380 & 1445570 & 1184810 & 8313.2 \tabularnewline
9 & 1305669 & 1366510 & 1447290 & -80779.7 & -60843.7 \tabularnewline
10 & 1280496 & 1343600 & 1447310 & -103709 & -63108.4 \tabularnewline
11 & 921900 & 947732 & 1448480 & -500748 & -25832.1 \tabularnewline
12 & 867888 & 856055 & 1450320 & -594270 & 11833.2 \tabularnewline
13 & 652586 & 674516 & 1463960 & -789447 & -21930.4 \tabularnewline
14 & 913831 & 901969 & 1468030 & -566057 & 11861.8 \tabularnewline
15 & 1108544 & 1120470 & 1459420 & -338946 & -11925.6 \tabularnewline
16 & 1555827 & 1545070 & 1463250 & 81817.9 & 10758.5 \tabularnewline
17 & 1699283 & 1571960 & 1467320 & 104641 & 127326 \tabularnewline
18 & 1509458 & 1535590 & 1463970 & 71623.2 & -26134.2 \tabularnewline
19 & 3268975 & 2991100 & 1460040 & 1531070 & 277871 \tabularnewline
20 & 2425016 & 2641840 & 1457040 & 1184810 & -216828 \tabularnewline
21 & 1312703 & 1374910 & 1455690 & -80779.7 & -62202.4 \tabularnewline
22 & 1365498 & 1357600 & 1461310 & -103709 & 7897.3 \tabularnewline
23 & 934453 & 954870 & 1455620 & -500748 & -20417.5 \tabularnewline
24 & 775019 & 857594 & 1451860 & -594270 & -82575.3 \tabularnewline
25 & 651142 & 653944 & 1443390 & -789447 & -2801.57 \tabularnewline
26 & 843192 & 874465 & 1440520 & -566057 & -31272.9 \tabularnewline
27 & 1146766 & 1119240 & 1458190 & -338946 & 27522.2 \tabularnewline
28 & 1652601 & 1547970 & 1466150 & 81817.9 & 104630 \tabularnewline
29 & 1465906 & 1576200 & 1471560 & 104641 & -110292 \tabularnewline
30 & 1652734 & 1553450 & 1481820 & 71623.2 & 99287.9 \tabularnewline
31 & 2922334 & 3022030 & 1490960 & 1531070 & -99692.7 \tabularnewline
32 & 2702805 & 2679930 & 1495120 & 1184810 & 22873.4 \tabularnewline
33 & 1458956 & 1414140 & 1494910 & -80779.7 & 44820.8 \tabularnewline
34 & 1410363 & 1386060 & 1489770 & -103709 & 24302.5 \tabularnewline
35 & 1019279 & 986755 & 1487500 & -500748 & 32524.3 \tabularnewline
36 & 936574 & 887310 & 1481580 & -594270 & 49263.6 \tabularnewline
37 & 708917 & 683637 & 1473080 & -789447 & 25279.7 \tabularnewline
38 & 885295 & 904295 & 1470350 & -566057 & -18999.8 \tabularnewline
39 & 1099663 & 1128060 & 1467000 & -338946 & -28394.9 \tabularnewline
40 & 1576220 & 1543800 & 1461980 & 81817.9 & 32421 \tabularnewline
41 & 1487870 & 1560440 & 1455800 & 104641 & -72568.8 \tabularnewline
42 & 1488635 & 1521330 & 1449700 & 71623.2 & -32690.6 \tabularnewline
43 & 2882530 & 2974740 & 1443680 & 1531070 & -92210.9 \tabularnewline
44 & 2677026 & 2627970 & 1443160 & 1184810 & 49056.2 \tabularnewline
45 & 1404398 & 1367760 & 1448540 & -80779.7 & 36635.6 \tabularnewline
46 & 1344370 & 1340050 & 1443760 & -103709 & 4323.8 \tabularnewline
47 & 936865 & 942926 & 1443670 & -500748 & -6061.08 \tabularnewline
48 & 872705 & 856919 & 1451190 & -594270 & 15786.2 \tabularnewline
49 & 628151 & 663532 & 1452980 & -789447 & -35380.9 \tabularnewline
50 & 953712 & 892543 & 1458600 & -566057 & 61168.8 \tabularnewline
51 & 1160384 & 1123870 & 1462820 & -338946 & 36510.4 \tabularnewline
52 & 1400618 & 1545820 & 1464010 & 81817.9 & -145205 \tabularnewline
53 & 1661511 & 1570880 & 1466230 & 104641 & 90635.4 \tabularnewline
54 & 1495347 & 1538100 & 1466480 & 71623.2 & -42752.5 \tabularnewline
55 & 2918786 & 2998920 & 1467860 & 1531070 & -80135 \tabularnewline
56 & 2775677 & 2650520 & 1465710 & 1184810 & 125159 \tabularnewline
57 & 1407026 & 1376860 & 1457640 & -80779.7 & 30163.8 \tabularnewline
58 & 1370199 & 1355040 & 1458750 & -103709 & 15158.8 \tabularnewline
59 & 964526 & 956166 & 1456910 & -500748 & 8360.42 \tabularnewline
60 & 850851 & 856585 & 1450850 & -594270 & -5733.72 \tabularnewline
61 & 683118 & 659711 & 1449160 & -789447 & 23407.2 \tabularnewline
62 & 847224 & 881408 & 1447460 & -566057 & -34183.7 \tabularnewline
63 & 1073256 & 1108390 & 1447340 & -338946 & -35138.1 \tabularnewline
64 & 1514326 & 1528360 & 1446540 & 81817.9 & -14030 \tabularnewline
65 & 1503734 & 1550260 & 1445620 & 104641 & -46526.6 \tabularnewline
66 & 1507712 & 1516850 & 1445230 & 71623.2 & -9136.54 \tabularnewline
67 & 2865698 & NA & NA & 1531070 & NA \tabularnewline
68 & 2788128 & NA & NA & 1184810 & NA \tabularnewline
69 & 1391596 & NA & NA & -80779.7 & NA \tabularnewline
70 & 1366378 & NA & NA & -103709 & NA \tabularnewline
71 & 946295 & NA & NA & -500748 & NA \tabularnewline
72 & 859626 & NA & NA & -594270 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=230736&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]655362[/C][C]NA[/C][C]NA[/C][C]-789447[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]873127[/C][C]NA[/C][C]NA[/C][C]-566057[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]1107897[/C][C]NA[/C][C]NA[/C][C]-338946[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]1555964[/C][C]NA[/C][C]NA[/C][C]81817.9[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]1671159[/C][C]NA[/C][C]NA[/C][C]104641[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]1493308[/C][C]NA[/C][C]NA[/C][C]71623.2[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2957796[/C][C]2975050[/C][C]1443990[/C][C]1531070[/C][C]-17258.1[/C][/ROW]
[ROW][C]8[/C][C]2638691[/C][C]2630380[/C][C]1445570[/C][C]1184810[/C][C]8313.2[/C][/ROW]
[ROW][C]9[/C][C]1305669[/C][C]1366510[/C][C]1447290[/C][C]-80779.7[/C][C]-60843.7[/C][/ROW]
[ROW][C]10[/C][C]1280496[/C][C]1343600[/C][C]1447310[/C][C]-103709[/C][C]-63108.4[/C][/ROW]
[ROW][C]11[/C][C]921900[/C][C]947732[/C][C]1448480[/C][C]-500748[/C][C]-25832.1[/C][/ROW]
[ROW][C]12[/C][C]867888[/C][C]856055[/C][C]1450320[/C][C]-594270[/C][C]11833.2[/C][/ROW]
[ROW][C]13[/C][C]652586[/C][C]674516[/C][C]1463960[/C][C]-789447[/C][C]-21930.4[/C][/ROW]
[ROW][C]14[/C][C]913831[/C][C]901969[/C][C]1468030[/C][C]-566057[/C][C]11861.8[/C][/ROW]
[ROW][C]15[/C][C]1108544[/C][C]1120470[/C][C]1459420[/C][C]-338946[/C][C]-11925.6[/C][/ROW]
[ROW][C]16[/C][C]1555827[/C][C]1545070[/C][C]1463250[/C][C]81817.9[/C][C]10758.5[/C][/ROW]
[ROW][C]17[/C][C]1699283[/C][C]1571960[/C][C]1467320[/C][C]104641[/C][C]127326[/C][/ROW]
[ROW][C]18[/C][C]1509458[/C][C]1535590[/C][C]1463970[/C][C]71623.2[/C][C]-26134.2[/C][/ROW]
[ROW][C]19[/C][C]3268975[/C][C]2991100[/C][C]1460040[/C][C]1531070[/C][C]277871[/C][/ROW]
[ROW][C]20[/C][C]2425016[/C][C]2641840[/C][C]1457040[/C][C]1184810[/C][C]-216828[/C][/ROW]
[ROW][C]21[/C][C]1312703[/C][C]1374910[/C][C]1455690[/C][C]-80779.7[/C][C]-62202.4[/C][/ROW]
[ROW][C]22[/C][C]1365498[/C][C]1357600[/C][C]1461310[/C][C]-103709[/C][C]7897.3[/C][/ROW]
[ROW][C]23[/C][C]934453[/C][C]954870[/C][C]1455620[/C][C]-500748[/C][C]-20417.5[/C][/ROW]
[ROW][C]24[/C][C]775019[/C][C]857594[/C][C]1451860[/C][C]-594270[/C][C]-82575.3[/C][/ROW]
[ROW][C]25[/C][C]651142[/C][C]653944[/C][C]1443390[/C][C]-789447[/C][C]-2801.57[/C][/ROW]
[ROW][C]26[/C][C]843192[/C][C]874465[/C][C]1440520[/C][C]-566057[/C][C]-31272.9[/C][/ROW]
[ROW][C]27[/C][C]1146766[/C][C]1119240[/C][C]1458190[/C][C]-338946[/C][C]27522.2[/C][/ROW]
[ROW][C]28[/C][C]1652601[/C][C]1547970[/C][C]1466150[/C][C]81817.9[/C][C]104630[/C][/ROW]
[ROW][C]29[/C][C]1465906[/C][C]1576200[/C][C]1471560[/C][C]104641[/C][C]-110292[/C][/ROW]
[ROW][C]30[/C][C]1652734[/C][C]1553450[/C][C]1481820[/C][C]71623.2[/C][C]99287.9[/C][/ROW]
[ROW][C]31[/C][C]2922334[/C][C]3022030[/C][C]1490960[/C][C]1531070[/C][C]-99692.7[/C][/ROW]
[ROW][C]32[/C][C]2702805[/C][C]2679930[/C][C]1495120[/C][C]1184810[/C][C]22873.4[/C][/ROW]
[ROW][C]33[/C][C]1458956[/C][C]1414140[/C][C]1494910[/C][C]-80779.7[/C][C]44820.8[/C][/ROW]
[ROW][C]34[/C][C]1410363[/C][C]1386060[/C][C]1489770[/C][C]-103709[/C][C]24302.5[/C][/ROW]
[ROW][C]35[/C][C]1019279[/C][C]986755[/C][C]1487500[/C][C]-500748[/C][C]32524.3[/C][/ROW]
[ROW][C]36[/C][C]936574[/C][C]887310[/C][C]1481580[/C][C]-594270[/C][C]49263.6[/C][/ROW]
[ROW][C]37[/C][C]708917[/C][C]683637[/C][C]1473080[/C][C]-789447[/C][C]25279.7[/C][/ROW]
[ROW][C]38[/C][C]885295[/C][C]904295[/C][C]1470350[/C][C]-566057[/C][C]-18999.8[/C][/ROW]
[ROW][C]39[/C][C]1099663[/C][C]1128060[/C][C]1467000[/C][C]-338946[/C][C]-28394.9[/C][/ROW]
[ROW][C]40[/C][C]1576220[/C][C]1543800[/C][C]1461980[/C][C]81817.9[/C][C]32421[/C][/ROW]
[ROW][C]41[/C][C]1487870[/C][C]1560440[/C][C]1455800[/C][C]104641[/C][C]-72568.8[/C][/ROW]
[ROW][C]42[/C][C]1488635[/C][C]1521330[/C][C]1449700[/C][C]71623.2[/C][C]-32690.6[/C][/ROW]
[ROW][C]43[/C][C]2882530[/C][C]2974740[/C][C]1443680[/C][C]1531070[/C][C]-92210.9[/C][/ROW]
[ROW][C]44[/C][C]2677026[/C][C]2627970[/C][C]1443160[/C][C]1184810[/C][C]49056.2[/C][/ROW]
[ROW][C]45[/C][C]1404398[/C][C]1367760[/C][C]1448540[/C][C]-80779.7[/C][C]36635.6[/C][/ROW]
[ROW][C]46[/C][C]1344370[/C][C]1340050[/C][C]1443760[/C][C]-103709[/C][C]4323.8[/C][/ROW]
[ROW][C]47[/C][C]936865[/C][C]942926[/C][C]1443670[/C][C]-500748[/C][C]-6061.08[/C][/ROW]
[ROW][C]48[/C][C]872705[/C][C]856919[/C][C]1451190[/C][C]-594270[/C][C]15786.2[/C][/ROW]
[ROW][C]49[/C][C]628151[/C][C]663532[/C][C]1452980[/C][C]-789447[/C][C]-35380.9[/C][/ROW]
[ROW][C]50[/C][C]953712[/C][C]892543[/C][C]1458600[/C][C]-566057[/C][C]61168.8[/C][/ROW]
[ROW][C]51[/C][C]1160384[/C][C]1123870[/C][C]1462820[/C][C]-338946[/C][C]36510.4[/C][/ROW]
[ROW][C]52[/C][C]1400618[/C][C]1545820[/C][C]1464010[/C][C]81817.9[/C][C]-145205[/C][/ROW]
[ROW][C]53[/C][C]1661511[/C][C]1570880[/C][C]1466230[/C][C]104641[/C][C]90635.4[/C][/ROW]
[ROW][C]54[/C][C]1495347[/C][C]1538100[/C][C]1466480[/C][C]71623.2[/C][C]-42752.5[/C][/ROW]
[ROW][C]55[/C][C]2918786[/C][C]2998920[/C][C]1467860[/C][C]1531070[/C][C]-80135[/C][/ROW]
[ROW][C]56[/C][C]2775677[/C][C]2650520[/C][C]1465710[/C][C]1184810[/C][C]125159[/C][/ROW]
[ROW][C]57[/C][C]1407026[/C][C]1376860[/C][C]1457640[/C][C]-80779.7[/C][C]30163.8[/C][/ROW]
[ROW][C]58[/C][C]1370199[/C][C]1355040[/C][C]1458750[/C][C]-103709[/C][C]15158.8[/C][/ROW]
[ROW][C]59[/C][C]964526[/C][C]956166[/C][C]1456910[/C][C]-500748[/C][C]8360.42[/C][/ROW]
[ROW][C]60[/C][C]850851[/C][C]856585[/C][C]1450850[/C][C]-594270[/C][C]-5733.72[/C][/ROW]
[ROW][C]61[/C][C]683118[/C][C]659711[/C][C]1449160[/C][C]-789447[/C][C]23407.2[/C][/ROW]
[ROW][C]62[/C][C]847224[/C][C]881408[/C][C]1447460[/C][C]-566057[/C][C]-34183.7[/C][/ROW]
[ROW][C]63[/C][C]1073256[/C][C]1108390[/C][C]1447340[/C][C]-338946[/C][C]-35138.1[/C][/ROW]
[ROW][C]64[/C][C]1514326[/C][C]1528360[/C][C]1446540[/C][C]81817.9[/C][C]-14030[/C][/ROW]
[ROW][C]65[/C][C]1503734[/C][C]1550260[/C][C]1445620[/C][C]104641[/C][C]-46526.6[/C][/ROW]
[ROW][C]66[/C][C]1507712[/C][C]1516850[/C][C]1445230[/C][C]71623.2[/C][C]-9136.54[/C][/ROW]
[ROW][C]67[/C][C]2865698[/C][C]NA[/C][C]NA[/C][C]1531070[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]2788128[/C][C]NA[/C][C]NA[/C][C]1184810[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]1391596[/C][C]NA[/C][C]NA[/C][C]-80779.7[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]1366378[/C][C]NA[/C][C]NA[/C][C]-103709[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]946295[/C][C]NA[/C][C]NA[/C][C]-500748[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]859626[/C][C]NA[/C][C]NA[/C][C]-594270[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=230736&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=230736&T=1

As an alternative you can also use a QR Code:  

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

Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
1655362NANA-789447NA
2873127NANA-566057NA
31107897NANA-338946NA
41555964NANA81817.9NA
51671159NANA104641NA
61493308NANA71623.2NA
72957796297505014439901531070-17258.1
826386912630380144557011848108313.2
9130566913665101447290-80779.7-60843.7
10128049613436001447310-103709-63108.4
119219009477321448480-500748-25832.1
128678888560551450320-59427011833.2
136525866745161463960-789447-21930.4
149138319019691468030-56605711861.8
15110854411204701459420-338946-11925.6
1615558271545070146325081817.910758.5
17169928315719601467320104641127326
1815094581535590146397071623.2-26134.2
193268975299110014600401531070277871
202425016264184014570401184810-216828
21131270313749101455690-80779.7-62202.4
22136549813576001461310-1037097897.3
239344539548701455620-500748-20417.5
247750198575941451860-594270-82575.3
256511426539441443390-789447-2801.57
268431928744651440520-566057-31272.9
27114676611192401458190-33894627522.2
2816526011547970146615081817.9104630
29146590615762001471560104641-110292
3016527341553450148182071623.299287.9
312922334302203014909601531070-99692.7
32270280526799301495120118481022873.4
33145895614141401494910-80779.744820.8
34141036313860601489770-10370924302.5
3510192799867551487500-50074832524.3
369365748873101481580-59427049263.6
377089176836371473080-78944725279.7
388852959042951470350-566057-18999.8
39109966311280601467000-338946-28394.9
4015762201543800146198081817.932421
41148787015604401455800104641-72568.8
4214886351521330144970071623.2-32690.6
432882530297474014436801531070-92210.9
44267702626279701443160118481049056.2
45140439813677601448540-80779.736635.6
46134437013400501443760-1037094323.8
479368659429261443670-500748-6061.08
488727058569191451190-59427015786.2
496281516635321452980-789447-35380.9
509537128925431458600-56605761168.8
51116038411238701462820-33894636510.4
5214006181545820146401081817.9-145205
5316615111570880146623010464190635.4
5414953471538100146648071623.2-42752.5
552918786299892014678601531070-80135
562775677265052014657101184810125159
57140702613768601457640-80779.730163.8
58137019913550401458750-10370915158.8
599645269561661456910-5007488360.42
608508518565851450850-594270-5733.72
616831186597111449160-78944723407.2
628472248814081447460-566057-34183.7
63107325611083901447340-338946-35138.1
6415143261528360144654081817.9-14030
65150373415502601445620104641-46526.6
6615077121516850144523071623.2-9136.54
672865698NANA1531070NA
682788128NANA1184810NA
691391596NANA-80779.7NA
701366378NANA-103709NA
71946295NANA-500748NA
72859626NANA-594270NA



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')