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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 06 May 2012 16:39:16 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/06/t1336336797ekx8mmv50zohyl2.htm/, Retrieved Sat, 27 Apr 2024 14:54:26 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166266, Retrieved Sat, 27 Apr 2024 14:54:26 +0000

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Estimated Impact

146

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-       [Classical Decomposition] [] [2012-05-06 20:39:16] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 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=166266&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=166266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166266&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	65	NA	NA	1.02238503742154	NA
2	65.3	NA	NA	1.03256598920881	NA
3	62.9	NA	NA	0.992786660083957	NA
4	63.5	NA	NA	0.967806011666513	NA
5	62.1	NA	NA	0.973035281116718	NA
6	59.3	NA	NA	0.998729369607664	NA
7	61.6	63.560094445717	62.3666666666667	1.01913566722154	0.96916155548839
8	61.5	63.5248171241143	62.2541666666666	1.02041068936399	0.968125573346269
9	60.1	62.7592871208099	62.1833333333333	1.00926218902401	0.957627193634452
10	59.5	60.9445997304188	62.125	0.980999593246178	0.976296509669293
11	62.7	60.8045437719606	62.0875	0.979336320063791	1.03117293725857
12	65.5	62.5502601864929	62.3291666666667	1.00354719197529	1.04715791436698
13	63.8	64.1631809735133	62.7583333333333	1.02238503742154	0.994339729296414
14	63.8	65.1635186356524	63.1083333333333	1.03256598920881	0.979075429562418
15	62.7	63.1040020815865	63.5625	0.992786660083957	0.99359783740714
16	62.3	62.1855687746221	64.2541666666667	0.967806011666513	1.00184015725244
17	62.4	63.137826803461	64.8875	0.973035281116718	0.988314029151529
18	64.8	65.3002552828477	65.3833333333333	0.998729369607664	0.992339152723356
19	66.4	67.3648676033441	66.1	1.01913566722154	0.985676991024084
20	65.1	68.7969390191616	67.4208333333333	1.02041068936399	0.946263030421573
21	67.4	69.8030961483733	69.1625	1.00926218902401	0.965573215502285
22	68.8	69.4057212221671	70.75	0.980999593246178	0.991272747959377
23	68.6	70.6427932206015	72.1333333333333	0.979336320063791	0.971082779608922
24	71.5	73.8234403096819	73.5625	1.00354719197529	0.968527065388238
25	75	76.7768563727015	75.0958333333333	1.02238503742154	0.976856875148991
26	84.3	79.1892066557387	76.6916666666667	1.03256598920881	1.06453901434421
27	84	77.4952720417202	78.0583333333333	0.992786660083957	1.08393709431432
28	79.1	76.1381054428143	78.6708333333333	0.967806011666513	1.03890160570662
29	78.8	76.5859852512284	78.7083333333333	0.973035281116718	1.02890887597135
30	82.7	78.450191982682	78.55	0.998729369607664	1.05417205375681
31	85.3	79.7940763448335	78.2958333333333	1.01913566722154	1.06900165911279
32	84.5	79.302917408405	77.7166666666667	1.02041068936399	1.06553456999356
33	80.8	77.4398467119884	76.7291666666667	1.00926218902401	1.04339049508335
34	70.1	74.5559690867095	76	0.980999593246178	0.94023323496034
35	68.2	74.2867404448388	75.8541666666667	0.979336320063791	0.918064241230796
36	68.1	76.0981472781592	75.8291666666667	1.00354719197529	0.894896951315729
37	72.3	77.2710091407885	75.5791666666667	1.02238503742154	0.935667863069689
38	73.1	77.9974534098602	75.5375	1.03256598920881	0.937210085768761
39	71.5	75.4641959996317	76.0125	0.992786660083957	0.94746918128365
40	74.1	74.8396323771617	77.3291666666667	0.967806011666513	0.990117103015227
41	80.3	77.177915047241	79.3166666666667	0.973035281116718	1.04045308752961
42	80.6	81.4338959743849	81.5375	0.998729369607664	0.989759841839727
43	81.4	85.5054824798875	83.9	1.01913566722154	0.95198573985179
44	87.4	87.7595709965091	86.0041666666666	1.02041068936399	0.995902771715652
45	89.3	88.4828571635594	87.6708333333333	1.00926218902401	1.00923504125698
46	93.2	87.2640013175527	88.9541666666667	0.980999593246178	1.06802345288805
47	92.8	87.9199181337269	89.775	0.979336320063791	1.05550598737877
48	96.8	90.8711982333621	90.55	1.00354719197529	1.06524401440611
49	100.3	93.8293868093615	91.775	1.02238503742154	1.06896147796197
50	95.6	96.0802652958794	93.05	1.03256598920881	0.995001415801669
51	89	93.6032356015824	94.2833333333333	0.992786660083957	0.950821832471948
52	87.4	92.4899945149298	95.5666666666667	0.967806011666513	0.944967079502765
53	86.7	94.4290197187062	97.0458333333333	0.973035281116718	0.918149952824565
54	92.8	98.7701732818246	98.8958333333333	0.998729369607664	0.939554897157164
55	98.6	NA	NA	1.01913566722154	NA
56	100.8	NA	NA	1.02041068936399	NA
57	105.5	NA	NA	1.00926218902401	NA
58	107.8	NA	NA	0.980999593246178	NA
59	113.7	NA	NA	0.979336320063791	NA
60	120.3	NA	NA	1.00354719197529	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 65 & NA & NA & 1.02238503742154 & NA \tabularnewline
2 & 65.3 & NA & NA & 1.03256598920881 & NA \tabularnewline
3 & 62.9 & NA & NA & 0.992786660083957 & NA \tabularnewline
4 & 63.5 & NA & NA & 0.967806011666513 & NA \tabularnewline
5 & 62.1 & NA & NA & 0.973035281116718 & NA \tabularnewline
6 & 59.3 & NA & NA & 0.998729369607664 & NA \tabularnewline
7 & 61.6 & 63.560094445717 & 62.3666666666667 & 1.01913566722154 & 0.96916155548839 \tabularnewline
8 & 61.5 & 63.5248171241143 & 62.2541666666666 & 1.02041068936399 & 0.968125573346269 \tabularnewline
9 & 60.1 & 62.7592871208099 & 62.1833333333333 & 1.00926218902401 & 0.957627193634452 \tabularnewline
10 & 59.5 & 60.9445997304188 & 62.125 & 0.980999593246178 & 0.976296509669293 \tabularnewline
11 & 62.7 & 60.8045437719606 & 62.0875 & 0.979336320063791 & 1.03117293725857 \tabularnewline
12 & 65.5 & 62.5502601864929 & 62.3291666666667 & 1.00354719197529 & 1.04715791436698 \tabularnewline
13 & 63.8 & 64.1631809735133 & 62.7583333333333 & 1.02238503742154 & 0.994339729296414 \tabularnewline
14 & 63.8 & 65.1635186356524 & 63.1083333333333 & 1.03256598920881 & 0.979075429562418 \tabularnewline
15 & 62.7 & 63.1040020815865 & 63.5625 & 0.992786660083957 & 0.99359783740714 \tabularnewline
16 & 62.3 & 62.1855687746221 & 64.2541666666667 & 0.967806011666513 & 1.00184015725244 \tabularnewline
17 & 62.4 & 63.137826803461 & 64.8875 & 0.973035281116718 & 0.988314029151529 \tabularnewline
18 & 64.8 & 65.3002552828477 & 65.3833333333333 & 0.998729369607664 & 0.992339152723356 \tabularnewline
19 & 66.4 & 67.3648676033441 & 66.1 & 1.01913566722154 & 0.985676991024084 \tabularnewline
20 & 65.1 & 68.7969390191616 & 67.4208333333333 & 1.02041068936399 & 0.946263030421573 \tabularnewline
21 & 67.4 & 69.8030961483733 & 69.1625 & 1.00926218902401 & 0.965573215502285 \tabularnewline
22 & 68.8 & 69.4057212221671 & 70.75 & 0.980999593246178 & 0.991272747959377 \tabularnewline
23 & 68.6 & 70.6427932206015 & 72.1333333333333 & 0.979336320063791 & 0.971082779608922 \tabularnewline
24 & 71.5 & 73.8234403096819 & 73.5625 & 1.00354719197529 & 0.968527065388238 \tabularnewline
25 & 75 & 76.7768563727015 & 75.0958333333333 & 1.02238503742154 & 0.976856875148991 \tabularnewline
26 & 84.3 & 79.1892066557387 & 76.6916666666667 & 1.03256598920881 & 1.06453901434421 \tabularnewline
27 & 84 & 77.4952720417202 & 78.0583333333333 & 0.992786660083957 & 1.08393709431432 \tabularnewline
28 & 79.1 & 76.1381054428143 & 78.6708333333333 & 0.967806011666513 & 1.03890160570662 \tabularnewline
29 & 78.8 & 76.5859852512284 & 78.7083333333333 & 0.973035281116718 & 1.02890887597135 \tabularnewline
30 & 82.7 & 78.450191982682 & 78.55 & 0.998729369607664 & 1.05417205375681 \tabularnewline
31 & 85.3 & 79.7940763448335 & 78.2958333333333 & 1.01913566722154 & 1.06900165911279 \tabularnewline
32 & 84.5 & 79.302917408405 & 77.7166666666667 & 1.02041068936399 & 1.06553456999356 \tabularnewline
33 & 80.8 & 77.4398467119884 & 76.7291666666667 & 1.00926218902401 & 1.04339049508335 \tabularnewline
34 & 70.1 & 74.5559690867095 & 76 & 0.980999593246178 & 0.94023323496034 \tabularnewline
35 & 68.2 & 74.2867404448388 & 75.8541666666667 & 0.979336320063791 & 0.918064241230796 \tabularnewline
36 & 68.1 & 76.0981472781592 & 75.8291666666667 & 1.00354719197529 & 0.894896951315729 \tabularnewline
37 & 72.3 & 77.2710091407885 & 75.5791666666667 & 1.02238503742154 & 0.935667863069689 \tabularnewline
38 & 73.1 & 77.9974534098602 & 75.5375 & 1.03256598920881 & 0.937210085768761 \tabularnewline
39 & 71.5 & 75.4641959996317 & 76.0125 & 0.992786660083957 & 0.94746918128365 \tabularnewline
40 & 74.1 & 74.8396323771617 & 77.3291666666667 & 0.967806011666513 & 0.990117103015227 \tabularnewline
41 & 80.3 & 77.177915047241 & 79.3166666666667 & 0.973035281116718 & 1.04045308752961 \tabularnewline
42 & 80.6 & 81.4338959743849 & 81.5375 & 0.998729369607664 & 0.989759841839727 \tabularnewline
43 & 81.4 & 85.5054824798875 & 83.9 & 1.01913566722154 & 0.95198573985179 \tabularnewline
44 & 87.4 & 87.7595709965091 & 86.0041666666666 & 1.02041068936399 & 0.995902771715652 \tabularnewline
45 & 89.3 & 88.4828571635594 & 87.6708333333333 & 1.00926218902401 & 1.00923504125698 \tabularnewline
46 & 93.2 & 87.2640013175527 & 88.9541666666667 & 0.980999593246178 & 1.06802345288805 \tabularnewline
47 & 92.8 & 87.9199181337269 & 89.775 & 0.979336320063791 & 1.05550598737877 \tabularnewline
48 & 96.8 & 90.8711982333621 & 90.55 & 1.00354719197529 & 1.06524401440611 \tabularnewline
49 & 100.3 & 93.8293868093615 & 91.775 & 1.02238503742154 & 1.06896147796197 \tabularnewline
50 & 95.6 & 96.0802652958794 & 93.05 & 1.03256598920881 & 0.995001415801669 \tabularnewline
51 & 89 & 93.6032356015824 & 94.2833333333333 & 0.992786660083957 & 0.950821832471948 \tabularnewline
52 & 87.4 & 92.4899945149298 & 95.5666666666667 & 0.967806011666513 & 0.944967079502765 \tabularnewline
53 & 86.7 & 94.4290197187062 & 97.0458333333333 & 0.973035281116718 & 0.918149952824565 \tabularnewline
54 & 92.8 & 98.7701732818246 & 98.8958333333333 & 0.998729369607664 & 0.939554897157164 \tabularnewline
55 & 98.6 & NA & NA & 1.01913566722154 & NA \tabularnewline
56 & 100.8 & NA & NA & 1.02041068936399 & NA \tabularnewline
57 & 105.5 & NA & NA & 1.00926218902401 & NA \tabularnewline
58 & 107.8 & NA & NA & 0.980999593246178 & NA \tabularnewline
59 & 113.7 & NA & NA & 0.979336320063791 & NA \tabularnewline
60 & 120.3 & NA & NA & 1.00354719197529 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166266&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]65[/C][C]NA[/C][C]NA[/C][C]1.02238503742154[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]65.3[/C][C]NA[/C][C]NA[/C][C]1.03256598920881[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]62.9[/C][C]NA[/C][C]NA[/C][C]0.992786660083957[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]63.5[/C][C]NA[/C][C]NA[/C][C]0.967806011666513[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]62.1[/C][C]NA[/C][C]NA[/C][C]0.973035281116718[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]59.3[/C][C]NA[/C][C]NA[/C][C]0.998729369607664[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]61.6[/C][C]63.560094445717[/C][C]62.3666666666667[/C][C]1.01913566722154[/C][C]0.96916155548839[/C][/ROW]
[ROW][C]8[/C][C]61.5[/C][C]63.5248171241143[/C][C]62.2541666666666[/C][C]1.02041068936399[/C][C]0.968125573346269[/C][/ROW]
[ROW][C]9[/C][C]60.1[/C][C]62.7592871208099[/C][C]62.1833333333333[/C][C]1.00926218902401[/C][C]0.957627193634452[/C][/ROW]
[ROW][C]10[/C][C]59.5[/C][C]60.9445997304188[/C][C]62.125[/C][C]0.980999593246178[/C][C]0.976296509669293[/C][/ROW]
[ROW][C]11[/C][C]62.7[/C][C]60.8045437719606[/C][C]62.0875[/C][C]0.979336320063791[/C][C]1.03117293725857[/C][/ROW]
[ROW][C]12[/C][C]65.5[/C][C]62.5502601864929[/C][C]62.3291666666667[/C][C]1.00354719197529[/C][C]1.04715791436698[/C][/ROW]
[ROW][C]13[/C][C]63.8[/C][C]64.1631809735133[/C][C]62.7583333333333[/C][C]1.02238503742154[/C][C]0.994339729296414[/C][/ROW]
[ROW][C]14[/C][C]63.8[/C][C]65.1635186356524[/C][C]63.1083333333333[/C][C]1.03256598920881[/C][C]0.979075429562418[/C][/ROW]
[ROW][C]15[/C][C]62.7[/C][C]63.1040020815865[/C][C]63.5625[/C][C]0.992786660083957[/C][C]0.99359783740714[/C][/ROW]
[ROW][C]16[/C][C]62.3[/C][C]62.1855687746221[/C][C]64.2541666666667[/C][C]0.967806011666513[/C][C]1.00184015725244[/C][/ROW]
[ROW][C]17[/C][C]62.4[/C][C]63.137826803461[/C][C]64.8875[/C][C]0.973035281116718[/C][C]0.988314029151529[/C][/ROW]
[ROW][C]18[/C][C]64.8[/C][C]65.3002552828477[/C][C]65.3833333333333[/C][C]0.998729369607664[/C][C]0.992339152723356[/C][/ROW]
[ROW][C]19[/C][C]66.4[/C][C]67.3648676033441[/C][C]66.1[/C][C]1.01913566722154[/C][C]0.985676991024084[/C][/ROW]
[ROW][C]20[/C][C]65.1[/C][C]68.7969390191616[/C][C]67.4208333333333[/C][C]1.02041068936399[/C][C]0.946263030421573[/C][/ROW]
[ROW][C]21[/C][C]67.4[/C][C]69.8030961483733[/C][C]69.1625[/C][C]1.00926218902401[/C][C]0.965573215502285[/C][/ROW]
[ROW][C]22[/C][C]68.8[/C][C]69.4057212221671[/C][C]70.75[/C][C]0.980999593246178[/C][C]0.991272747959377[/C][/ROW]
[ROW][C]23[/C][C]68.6[/C][C]70.6427932206015[/C][C]72.1333333333333[/C][C]0.979336320063791[/C][C]0.971082779608922[/C][/ROW]
[ROW][C]24[/C][C]71.5[/C][C]73.8234403096819[/C][C]73.5625[/C][C]1.00354719197529[/C][C]0.968527065388238[/C][/ROW]
[ROW][C]25[/C][C]75[/C][C]76.7768563727015[/C][C]75.0958333333333[/C][C]1.02238503742154[/C][C]0.976856875148991[/C][/ROW]
[ROW][C]26[/C][C]84.3[/C][C]79.1892066557387[/C][C]76.6916666666667[/C][C]1.03256598920881[/C][C]1.06453901434421[/C][/ROW]
[ROW][C]27[/C][C]84[/C][C]77.4952720417202[/C][C]78.0583333333333[/C][C]0.992786660083957[/C][C]1.08393709431432[/C][/ROW]
[ROW][C]28[/C][C]79.1[/C][C]76.1381054428143[/C][C]78.6708333333333[/C][C]0.967806011666513[/C][C]1.03890160570662[/C][/ROW]
[ROW][C]29[/C][C]78.8[/C][C]76.5859852512284[/C][C]78.7083333333333[/C][C]0.973035281116718[/C][C]1.02890887597135[/C][/ROW]
[ROW][C]30[/C][C]82.7[/C][C]78.450191982682[/C][C]78.55[/C][C]0.998729369607664[/C][C]1.05417205375681[/C][/ROW]
[ROW][C]31[/C][C]85.3[/C][C]79.7940763448335[/C][C]78.2958333333333[/C][C]1.01913566722154[/C][C]1.06900165911279[/C][/ROW]
[ROW][C]32[/C][C]84.5[/C][C]79.302917408405[/C][C]77.7166666666667[/C][C]1.02041068936399[/C][C]1.06553456999356[/C][/ROW]
[ROW][C]33[/C][C]80.8[/C][C]77.4398467119884[/C][C]76.7291666666667[/C][C]1.00926218902401[/C][C]1.04339049508335[/C][/ROW]
[ROW][C]34[/C][C]70.1[/C][C]74.5559690867095[/C][C]76[/C][C]0.980999593246178[/C][C]0.94023323496034[/C][/ROW]
[ROW][C]35[/C][C]68.2[/C][C]74.2867404448388[/C][C]75.8541666666667[/C][C]0.979336320063791[/C][C]0.918064241230796[/C][/ROW]
[ROW][C]36[/C][C]68.1[/C][C]76.0981472781592[/C][C]75.8291666666667[/C][C]1.00354719197529[/C][C]0.894896951315729[/C][/ROW]
[ROW][C]37[/C][C]72.3[/C][C]77.2710091407885[/C][C]75.5791666666667[/C][C]1.02238503742154[/C][C]0.935667863069689[/C][/ROW]
[ROW][C]38[/C][C]73.1[/C][C]77.9974534098602[/C][C]75.5375[/C][C]1.03256598920881[/C][C]0.937210085768761[/C][/ROW]
[ROW][C]39[/C][C]71.5[/C][C]75.4641959996317[/C][C]76.0125[/C][C]0.992786660083957[/C][C]0.94746918128365[/C][/ROW]
[ROW][C]40[/C][C]74.1[/C][C]74.8396323771617[/C][C]77.3291666666667[/C][C]0.967806011666513[/C][C]0.990117103015227[/C][/ROW]
[ROW][C]41[/C][C]80.3[/C][C]77.177915047241[/C][C]79.3166666666667[/C][C]0.973035281116718[/C][C]1.04045308752961[/C][/ROW]
[ROW][C]42[/C][C]80.6[/C][C]81.4338959743849[/C][C]81.5375[/C][C]0.998729369607664[/C][C]0.989759841839727[/C][/ROW]
[ROW][C]43[/C][C]81.4[/C][C]85.5054824798875[/C][C]83.9[/C][C]1.01913566722154[/C][C]0.95198573985179[/C][/ROW]
[ROW][C]44[/C][C]87.4[/C][C]87.7595709965091[/C][C]86.0041666666666[/C][C]1.02041068936399[/C][C]0.995902771715652[/C][/ROW]
[ROW][C]45[/C][C]89.3[/C][C]88.4828571635594[/C][C]87.6708333333333[/C][C]1.00926218902401[/C][C]1.00923504125698[/C][/ROW]
[ROW][C]46[/C][C]93.2[/C][C]87.2640013175527[/C][C]88.9541666666667[/C][C]0.980999593246178[/C][C]1.06802345288805[/C][/ROW]
[ROW][C]47[/C][C]92.8[/C][C]87.9199181337269[/C][C]89.775[/C][C]0.979336320063791[/C][C]1.05550598737877[/C][/ROW]
[ROW][C]48[/C][C]96.8[/C][C]90.8711982333621[/C][C]90.55[/C][C]1.00354719197529[/C][C]1.06524401440611[/C][/ROW]
[ROW][C]49[/C][C]100.3[/C][C]93.8293868093615[/C][C]91.775[/C][C]1.02238503742154[/C][C]1.06896147796197[/C][/ROW]
[ROW][C]50[/C][C]95.6[/C][C]96.0802652958794[/C][C]93.05[/C][C]1.03256598920881[/C][C]0.995001415801669[/C][/ROW]
[ROW][C]51[/C][C]89[/C][C]93.6032356015824[/C][C]94.2833333333333[/C][C]0.992786660083957[/C][C]0.950821832471948[/C][/ROW]
[ROW][C]52[/C][C]87.4[/C][C]92.4899945149298[/C][C]95.5666666666667[/C][C]0.967806011666513[/C][C]0.944967079502765[/C][/ROW]
[ROW][C]53[/C][C]86.7[/C][C]94.4290197187062[/C][C]97.0458333333333[/C][C]0.973035281116718[/C][C]0.918149952824565[/C][/ROW]
[ROW][C]54[/C][C]92.8[/C][C]98.7701732818246[/C][C]98.8958333333333[/C][C]0.998729369607664[/C][C]0.939554897157164[/C][/ROW]
[ROW][C]55[/C][C]98.6[/C][C]NA[/C][C]NA[/C][C]1.01913566722154[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]100.8[/C][C]NA[/C][C]NA[/C][C]1.02041068936399[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]105.5[/C][C]NA[/C][C]NA[/C][C]1.00926218902401[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]107.8[/C][C]NA[/C][C]NA[/C][C]0.980999593246178[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]113.7[/C][C]NA[/C][C]NA[/C][C]0.979336320063791[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]120.3[/C][C]NA[/C][C]NA[/C][C]1.00354719197529[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166266&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
t	Observations	Fit	Trend	Seasonal	Random
1	65	NA	NA	1.02238503742154	NA
2	65.3	NA	NA	1.03256598920881	NA
3	62.9	NA	NA	0.992786660083957	NA
4	63.5	NA	NA	0.967806011666513	NA
5	62.1	NA	NA	0.973035281116718	NA
6	59.3	NA	NA	0.998729369607664	NA
7	61.6	63.560094445717	62.3666666666667	1.01913566722154	0.96916155548839
8	61.5	63.5248171241143	62.2541666666666	1.02041068936399	0.968125573346269
9	60.1	62.7592871208099	62.1833333333333	1.00926218902401	0.957627193634452
10	59.5	60.9445997304188	62.125	0.980999593246178	0.976296509669293
11	62.7	60.8045437719606	62.0875	0.979336320063791	1.03117293725857
12	65.5	62.5502601864929	62.3291666666667	1.00354719197529	1.04715791436698
13	63.8	64.1631809735133	62.7583333333333	1.02238503742154	0.994339729296414
14	63.8	65.1635186356524	63.1083333333333	1.03256598920881	0.979075429562418
15	62.7	63.1040020815865	63.5625	0.992786660083957	0.99359783740714
16	62.3	62.1855687746221	64.2541666666667	0.967806011666513	1.00184015725244
17	62.4	63.137826803461	64.8875	0.973035281116718	0.988314029151529
18	64.8	65.3002552828477	65.3833333333333	0.998729369607664	0.992339152723356
19	66.4	67.3648676033441	66.1	1.01913566722154	0.985676991024084
20	65.1	68.7969390191616	67.4208333333333	1.02041068936399	0.946263030421573
21	67.4	69.8030961483733	69.1625	1.00926218902401	0.965573215502285
22	68.8	69.4057212221671	70.75	0.980999593246178	0.991272747959377
23	68.6	70.6427932206015	72.1333333333333	0.979336320063791	0.971082779608922
24	71.5	73.8234403096819	73.5625	1.00354719197529	0.968527065388238
25	75	76.7768563727015	75.0958333333333	1.02238503742154	0.976856875148991
26	84.3	79.1892066557387	76.6916666666667	1.03256598920881	1.06453901434421
27	84	77.4952720417202	78.0583333333333	0.992786660083957	1.08393709431432
28	79.1	76.1381054428143	78.6708333333333	0.967806011666513	1.03890160570662
29	78.8	76.5859852512284	78.7083333333333	0.973035281116718	1.02890887597135
30	82.7	78.450191982682	78.55	0.998729369607664	1.05417205375681
31	85.3	79.7940763448335	78.2958333333333	1.01913566722154	1.06900165911279
32	84.5	79.302917408405	77.7166666666667	1.02041068936399	1.06553456999356
33	80.8	77.4398467119884	76.7291666666667	1.00926218902401	1.04339049508335
34	70.1	74.5559690867095	76	0.980999593246178	0.94023323496034
35	68.2	74.2867404448388	75.8541666666667	0.979336320063791	0.918064241230796
36	68.1	76.0981472781592	75.8291666666667	1.00354719197529	0.894896951315729
37	72.3	77.2710091407885	75.5791666666667	1.02238503742154	0.935667863069689
38	73.1	77.9974534098602	75.5375	1.03256598920881	0.937210085768761
39	71.5	75.4641959996317	76.0125	0.992786660083957	0.94746918128365
40	74.1	74.8396323771617	77.3291666666667	0.967806011666513	0.990117103015227
41	80.3	77.177915047241	79.3166666666667	0.973035281116718	1.04045308752961
42	80.6	81.4338959743849	81.5375	0.998729369607664	0.989759841839727
43	81.4	85.5054824798875	83.9	1.01913566722154	0.95198573985179
44	87.4	87.7595709965091	86.0041666666666	1.02041068936399	0.995902771715652
45	89.3	88.4828571635594	87.6708333333333	1.00926218902401	1.00923504125698
46	93.2	87.2640013175527	88.9541666666667	0.980999593246178	1.06802345288805
47	92.8	87.9199181337269	89.775	0.979336320063791	1.05550598737877
48	96.8	90.8711982333621	90.55	1.00354719197529	1.06524401440611
49	100.3	93.8293868093615	91.775	1.02238503742154	1.06896147796197
50	95.6	96.0802652958794	93.05	1.03256598920881	0.995001415801669
51	89	93.6032356015824	94.2833333333333	0.992786660083957	0.950821832471948
52	87.4	92.4899945149298	95.5666666666667	0.967806011666513	0.944967079502765
53	86.7	94.4290197187062	97.0458333333333	0.973035281116718	0.918149952824565
54	92.8	98.7701732818246	98.8958333333333	0.998729369607664	0.939554897157164
55	98.6	NA	NA	1.01913566722154	NA
56	100.8	NA	NA	1.02041068936399	NA
57	105.5	NA	NA	1.00926218902401	NA
58	107.8	NA	NA	0.980999593246178	NA
59	113.7	NA	NA	0.979336320063791	NA
60	120.3	NA	NA	1.00354719197529	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code