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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 13 Dec 2010 13:11:59 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/13/t1292245883mas1tapeqwpl3ax.htm/, Retrieved Mon, 06 May 2024 19:51:11 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108896, Retrieved Mon, 06 May 2024 19:51:11 +0000

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No (this computation is public)

User-defined keywords

KDGP2W92

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Classical Decomposition] [additief model ei...] [2010-12-13 13:11:59] [6828a15931dcaf58ef367cb5857a54a7] [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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108896&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108896&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	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	96.92	NA	NA	-1.95264756944444	NA
2	99.06	NA	NA	0.309956597222212	NA
3	99.65	NA	NA	0.164852430555552	NA
4	99.82	NA	NA	0.405373263888894	NA
5	99.99	NA	NA	0.498810763888895	NA
6	100.33	NA	NA	0.522664930555561	NA
7	99.31	99.4246440972222	100.110833333333	-0.686189236111111	-0.114644097222211
8	101.1	101.014123263889	100.34	0.674123263888895	0.0858767361111177
9	101.1	100.815998263889	100.5475	0.268498263888880	0.284001736111122
10	100.93	100.777977430556	100.744166666667	0.0338107638888877	0.152022569444455
11	100.85	100.883498263889	100.965416666667	-0.0819184027777874	-0.0334982638888874
12	100.93	101.026414930556	101.18375	-0.157335069444439	-0.0964149305555253
13	99.6	99.4352690972222	101.387916666667	-1.95264756944444	0.164730902777777
14	101.88	101.897039930556	101.587083333333	0.309956597222212	-0.0170399305555406
15	101.81	101.929019097222	101.764166666667	0.164852430555552	-0.119019097222207
16	102.38	102.320789930556	101.915416666667	0.405373263888894	0.059210069444461
17	102.74	102.572560763889	102.07375	0.498810763888895	0.167439236111107
18	102.82	102.769331597222	102.246666666667	0.522664930555561	0.0506684027777737
19	101.72	101.718394097222	102.404583333333	-0.686189236111111	0.00160590277776862
20	103.47	103.224539930556	102.550416666667	0.674123263888895	0.245460069444434
21	102.98	102.972248263889	102.70375	0.268498263888880	0.00775173611110347
22	102.68	102.891310763889	102.8575	0.0338107638888877	-0.211310763888889
23	102.9	102.907248263889	102.989166666667	-0.0819184027777874	-0.00724826388888289
24	103.03	102.943498263889	103.100833333333	-0.157335069444439	0.0865017361111171
25	101.29	101.259435763889	103.212083333333	-1.95264756944444	0.0305642361111182
26	103.69	103.627039930556	103.317083333333	0.309956597222212	0.0629600694444576
27	103.68	103.593185763889	103.428333333333	0.164852430555552	0.0868142361111097
28	104.2	103.989956597222	103.584583333333	0.405373263888894	0.210043402777785
29	104.08	104.300894097222	103.802083333333	0.498810763888895	-0.220894097222214
30	104.16	104.580998263889	104.058333333333	0.522664930555561	-0.42099826388889
31	103.05	103.654227430556	104.340416666667	-0.686189236111111	-0.604227430555554
32	104.66	105.319539930556	104.645416666667	0.674123263888895	-0.659539930555553
33	104.46	105.259748263889	104.99125	0.268498263888880	-0.799748263888901
34	104.95	105.391727430556	105.357916666667	0.0338107638888877	-0.441727430555559
35	105.85	105.674331597222	105.75625	-0.0819184027777874	0.175668402777788
36	106.23	106.069748263889	106.227083333333	-0.157335069444439	0.160251736111121
37	104.86	104.777352430556	106.73	-1.95264756944444	0.0826475694444468
38	107.44	107.527456597222	107.2175	0.309956597222212	-0.0874565972222143
39	108.23	107.854435763889	107.689583333333	0.164852430555552	0.375564236111117
40	108.45	108.542873263889	108.1375	0.405373263888894	-0.092873263888876
41	109.39	108.988394097222	108.489583333333	0.498810763888895	0.401605902777789
42	110.15	109.274331597222	108.751666666667	0.522664930555561	0.87566840277779
43	109.13	108.277144097222	108.963333333333	-0.686189236111111	0.852855902777776
44	110.28	109.816206597222	109.142083333333	0.674123263888895	0.463793402777782
45	110.17	109.526414930556	109.257916666667	0.268498263888880	0.643585069444455
46	109.99	109.353394097222	109.319583333333	0.0338107638888877	0.636605902777774
47	109.26	109.259331597222	109.34125	-0.0819184027777874	0.000668402777790789
48	109.11	109.124748263889	109.282083333333	-0.157335069444439	-0.0147482638888903
49	107.06	107.202352430556	109.155	-1.95264756944444	-0.142352430555547
50	109.53	109.352873263889	109.042916666667	0.309956597222212	0.177126736111106
51	108.92	109.127769097222	108.962916666667	0.164852430555552	-0.207769097222226
52	109.24	109.280789930556	108.875416666667	0.405373263888894	-0.0407899305555475
53	109.12	109.332560763889	108.83375	0.498810763888895	-0.212560763888888
54	109	109.369748263889	108.847083333333	0.522664930555561	-0.36974826388888
55	107.23	NA	NA	-0.686189236111111	NA
56	109.49	NA	NA	0.674123263888895	NA
57	109.04	NA	NA	0.268498263888880	NA
58	109.02	NA	NA	0.0338107638888877	NA
59	109.23	NA	NA	-0.0819184027777874	NA
60	109.46	NA	NA	-0.157335069444439	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 96.92 & NA & NA & -1.95264756944444 & NA \tabularnewline
2 & 99.06 & NA & NA & 0.309956597222212 & NA \tabularnewline
3 & 99.65 & NA & NA & 0.164852430555552 & NA \tabularnewline
4 & 99.82 & NA & NA & 0.405373263888894 & NA \tabularnewline
5 & 99.99 & NA & NA & 0.498810763888895 & NA \tabularnewline
6 & 100.33 & NA & NA & 0.522664930555561 & NA \tabularnewline
7 & 99.31 & 99.4246440972222 & 100.110833333333 & -0.686189236111111 & -0.114644097222211 \tabularnewline
8 & 101.1 & 101.014123263889 & 100.34 & 0.674123263888895 & 0.0858767361111177 \tabularnewline
9 & 101.1 & 100.815998263889 & 100.5475 & 0.268498263888880 & 0.284001736111122 \tabularnewline
10 & 100.93 & 100.777977430556 & 100.744166666667 & 0.0338107638888877 & 0.152022569444455 \tabularnewline
11 & 100.85 & 100.883498263889 & 100.965416666667 & -0.0819184027777874 & -0.0334982638888874 \tabularnewline
12 & 100.93 & 101.026414930556 & 101.18375 & -0.157335069444439 & -0.0964149305555253 \tabularnewline
13 & 99.6 & 99.4352690972222 & 101.387916666667 & -1.95264756944444 & 0.164730902777777 \tabularnewline
14 & 101.88 & 101.897039930556 & 101.587083333333 & 0.309956597222212 & -0.0170399305555406 \tabularnewline
15 & 101.81 & 101.929019097222 & 101.764166666667 & 0.164852430555552 & -0.119019097222207 \tabularnewline
16 & 102.38 & 102.320789930556 & 101.915416666667 & 0.405373263888894 & 0.059210069444461 \tabularnewline
17 & 102.74 & 102.572560763889 & 102.07375 & 0.498810763888895 & 0.167439236111107 \tabularnewline
18 & 102.82 & 102.769331597222 & 102.246666666667 & 0.522664930555561 & 0.0506684027777737 \tabularnewline
19 & 101.72 & 101.718394097222 & 102.404583333333 & -0.686189236111111 & 0.00160590277776862 \tabularnewline
20 & 103.47 & 103.224539930556 & 102.550416666667 & 0.674123263888895 & 0.245460069444434 \tabularnewline
21 & 102.98 & 102.972248263889 & 102.70375 & 0.268498263888880 & 0.00775173611110347 \tabularnewline
22 & 102.68 & 102.891310763889 & 102.8575 & 0.0338107638888877 & -0.211310763888889 \tabularnewline
23 & 102.9 & 102.907248263889 & 102.989166666667 & -0.0819184027777874 & -0.00724826388888289 \tabularnewline
24 & 103.03 & 102.943498263889 & 103.100833333333 & -0.157335069444439 & 0.0865017361111171 \tabularnewline
25 & 101.29 & 101.259435763889 & 103.212083333333 & -1.95264756944444 & 0.0305642361111182 \tabularnewline
26 & 103.69 & 103.627039930556 & 103.317083333333 & 0.309956597222212 & 0.0629600694444576 \tabularnewline
27 & 103.68 & 103.593185763889 & 103.428333333333 & 0.164852430555552 & 0.0868142361111097 \tabularnewline
28 & 104.2 & 103.989956597222 & 103.584583333333 & 0.405373263888894 & 0.210043402777785 \tabularnewline
29 & 104.08 & 104.300894097222 & 103.802083333333 & 0.498810763888895 & -0.220894097222214 \tabularnewline
30 & 104.16 & 104.580998263889 & 104.058333333333 & 0.522664930555561 & -0.42099826388889 \tabularnewline
31 & 103.05 & 103.654227430556 & 104.340416666667 & -0.686189236111111 & -0.604227430555554 \tabularnewline
32 & 104.66 & 105.319539930556 & 104.645416666667 & 0.674123263888895 & -0.659539930555553 \tabularnewline
33 & 104.46 & 105.259748263889 & 104.99125 & 0.268498263888880 & -0.799748263888901 \tabularnewline
34 & 104.95 & 105.391727430556 & 105.357916666667 & 0.0338107638888877 & -0.441727430555559 \tabularnewline
35 & 105.85 & 105.674331597222 & 105.75625 & -0.0819184027777874 & 0.175668402777788 \tabularnewline
36 & 106.23 & 106.069748263889 & 106.227083333333 & -0.157335069444439 & 0.160251736111121 \tabularnewline
37 & 104.86 & 104.777352430556 & 106.73 & -1.95264756944444 & 0.0826475694444468 \tabularnewline
38 & 107.44 & 107.527456597222 & 107.2175 & 0.309956597222212 & -0.0874565972222143 \tabularnewline
39 & 108.23 & 107.854435763889 & 107.689583333333 & 0.164852430555552 & 0.375564236111117 \tabularnewline
40 & 108.45 & 108.542873263889 & 108.1375 & 0.405373263888894 & -0.092873263888876 \tabularnewline
41 & 109.39 & 108.988394097222 & 108.489583333333 & 0.498810763888895 & 0.401605902777789 \tabularnewline
42 & 110.15 & 109.274331597222 & 108.751666666667 & 0.522664930555561 & 0.87566840277779 \tabularnewline
43 & 109.13 & 108.277144097222 & 108.963333333333 & -0.686189236111111 & 0.852855902777776 \tabularnewline
44 & 110.28 & 109.816206597222 & 109.142083333333 & 0.674123263888895 & 0.463793402777782 \tabularnewline
45 & 110.17 & 109.526414930556 & 109.257916666667 & 0.268498263888880 & 0.643585069444455 \tabularnewline
46 & 109.99 & 109.353394097222 & 109.319583333333 & 0.0338107638888877 & 0.636605902777774 \tabularnewline
47 & 109.26 & 109.259331597222 & 109.34125 & -0.0819184027777874 & 0.000668402777790789 \tabularnewline
48 & 109.11 & 109.124748263889 & 109.282083333333 & -0.157335069444439 & -0.0147482638888903 \tabularnewline
49 & 107.06 & 107.202352430556 & 109.155 & -1.95264756944444 & -0.142352430555547 \tabularnewline
50 & 109.53 & 109.352873263889 & 109.042916666667 & 0.309956597222212 & 0.177126736111106 \tabularnewline
51 & 108.92 & 109.127769097222 & 108.962916666667 & 0.164852430555552 & -0.207769097222226 \tabularnewline
52 & 109.24 & 109.280789930556 & 108.875416666667 & 0.405373263888894 & -0.0407899305555475 \tabularnewline
53 & 109.12 & 109.332560763889 & 108.83375 & 0.498810763888895 & -0.212560763888888 \tabularnewline
54 & 109 & 109.369748263889 & 108.847083333333 & 0.522664930555561 & -0.36974826388888 \tabularnewline
55 & 107.23 & NA & NA & -0.686189236111111 & NA \tabularnewline
56 & 109.49 & NA & NA & 0.674123263888895 & NA \tabularnewline
57 & 109.04 & NA & NA & 0.268498263888880 & NA \tabularnewline
58 & 109.02 & NA & NA & 0.0338107638888877 & NA \tabularnewline
59 & 109.23 & NA & NA & -0.0819184027777874 & NA \tabularnewline
60 & 109.46 & NA & NA & -0.157335069444439 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108896&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]96.92[/C][C]NA[/C][C]NA[/C][C]-1.95264756944444[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]99.06[/C][C]NA[/C][C]NA[/C][C]0.309956597222212[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]99.65[/C][C]NA[/C][C]NA[/C][C]0.164852430555552[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]99.82[/C][C]NA[/C][C]NA[/C][C]0.405373263888894[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]99.99[/C][C]NA[/C][C]NA[/C][C]0.498810763888895[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.33[/C][C]NA[/C][C]NA[/C][C]0.522664930555561[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]99.31[/C][C]99.4246440972222[/C][C]100.110833333333[/C][C]-0.686189236111111[/C][C]-0.114644097222211[/C][/ROW]
[ROW][C]8[/C][C]101.1[/C][C]101.014123263889[/C][C]100.34[/C][C]0.674123263888895[/C][C]0.0858767361111177[/C][/ROW]
[ROW][C]9[/C][C]101.1[/C][C]100.815998263889[/C][C]100.5475[/C][C]0.268498263888880[/C][C]0.284001736111122[/C][/ROW]
[ROW][C]10[/C][C]100.93[/C][C]100.777977430556[/C][C]100.744166666667[/C][C]0.0338107638888877[/C][C]0.152022569444455[/C][/ROW]
[ROW][C]11[/C][C]100.85[/C][C]100.883498263889[/C][C]100.965416666667[/C][C]-0.0819184027777874[/C][C]-0.0334982638888874[/C][/ROW]
[ROW][C]12[/C][C]100.93[/C][C]101.026414930556[/C][C]101.18375[/C][C]-0.157335069444439[/C][C]-0.0964149305555253[/C][/ROW]
[ROW][C]13[/C][C]99.6[/C][C]99.4352690972222[/C][C]101.387916666667[/C][C]-1.95264756944444[/C][C]0.164730902777777[/C][/ROW]
[ROW][C]14[/C][C]101.88[/C][C]101.897039930556[/C][C]101.587083333333[/C][C]0.309956597222212[/C][C]-0.0170399305555406[/C][/ROW]
[ROW][C]15[/C][C]101.81[/C][C]101.929019097222[/C][C]101.764166666667[/C][C]0.164852430555552[/C][C]-0.119019097222207[/C][/ROW]
[ROW][C]16[/C][C]102.38[/C][C]102.320789930556[/C][C]101.915416666667[/C][C]0.405373263888894[/C][C]0.059210069444461[/C][/ROW]
[ROW][C]17[/C][C]102.74[/C][C]102.572560763889[/C][C]102.07375[/C][C]0.498810763888895[/C][C]0.167439236111107[/C][/ROW]
[ROW][C]18[/C][C]102.82[/C][C]102.769331597222[/C][C]102.246666666667[/C][C]0.522664930555561[/C][C]0.0506684027777737[/C][/ROW]
[ROW][C]19[/C][C]101.72[/C][C]101.718394097222[/C][C]102.404583333333[/C][C]-0.686189236111111[/C][C]0.00160590277776862[/C][/ROW]
[ROW][C]20[/C][C]103.47[/C][C]103.224539930556[/C][C]102.550416666667[/C][C]0.674123263888895[/C][C]0.245460069444434[/C][/ROW]
[ROW][C]21[/C][C]102.98[/C][C]102.972248263889[/C][C]102.70375[/C][C]0.268498263888880[/C][C]0.00775173611110347[/C][/ROW]
[ROW][C]22[/C][C]102.68[/C][C]102.891310763889[/C][C]102.8575[/C][C]0.0338107638888877[/C][C]-0.211310763888889[/C][/ROW]
[ROW][C]23[/C][C]102.9[/C][C]102.907248263889[/C][C]102.989166666667[/C][C]-0.0819184027777874[/C][C]-0.00724826388888289[/C][/ROW]
[ROW][C]24[/C][C]103.03[/C][C]102.943498263889[/C][C]103.100833333333[/C][C]-0.157335069444439[/C][C]0.0865017361111171[/C][/ROW]
[ROW][C]25[/C][C]101.29[/C][C]101.259435763889[/C][C]103.212083333333[/C][C]-1.95264756944444[/C][C]0.0305642361111182[/C][/ROW]
[ROW][C]26[/C][C]103.69[/C][C]103.627039930556[/C][C]103.317083333333[/C][C]0.309956597222212[/C][C]0.0629600694444576[/C][/ROW]
[ROW][C]27[/C][C]103.68[/C][C]103.593185763889[/C][C]103.428333333333[/C][C]0.164852430555552[/C][C]0.0868142361111097[/C][/ROW]
[ROW][C]28[/C][C]104.2[/C][C]103.989956597222[/C][C]103.584583333333[/C][C]0.405373263888894[/C][C]0.210043402777785[/C][/ROW]
[ROW][C]29[/C][C]104.08[/C][C]104.300894097222[/C][C]103.802083333333[/C][C]0.498810763888895[/C][C]-0.220894097222214[/C][/ROW]
[ROW][C]30[/C][C]104.16[/C][C]104.580998263889[/C][C]104.058333333333[/C][C]0.522664930555561[/C][C]-0.42099826388889[/C][/ROW]
[ROW][C]31[/C][C]103.05[/C][C]103.654227430556[/C][C]104.340416666667[/C][C]-0.686189236111111[/C][C]-0.604227430555554[/C][/ROW]
[ROW][C]32[/C][C]104.66[/C][C]105.319539930556[/C][C]104.645416666667[/C][C]0.674123263888895[/C][C]-0.659539930555553[/C][/ROW]
[ROW][C]33[/C][C]104.46[/C][C]105.259748263889[/C][C]104.99125[/C][C]0.268498263888880[/C][C]-0.799748263888901[/C][/ROW]
[ROW][C]34[/C][C]104.95[/C][C]105.391727430556[/C][C]105.357916666667[/C][C]0.0338107638888877[/C][C]-0.441727430555559[/C][/ROW]
[ROW][C]35[/C][C]105.85[/C][C]105.674331597222[/C][C]105.75625[/C][C]-0.0819184027777874[/C][C]0.175668402777788[/C][/ROW]
[ROW][C]36[/C][C]106.23[/C][C]106.069748263889[/C][C]106.227083333333[/C][C]-0.157335069444439[/C][C]0.160251736111121[/C][/ROW]
[ROW][C]37[/C][C]104.86[/C][C]104.777352430556[/C][C]106.73[/C][C]-1.95264756944444[/C][C]0.0826475694444468[/C][/ROW]
[ROW][C]38[/C][C]107.44[/C][C]107.527456597222[/C][C]107.2175[/C][C]0.309956597222212[/C][C]-0.0874565972222143[/C][/ROW]
[ROW][C]39[/C][C]108.23[/C][C]107.854435763889[/C][C]107.689583333333[/C][C]0.164852430555552[/C][C]0.375564236111117[/C][/ROW]
[ROW][C]40[/C][C]108.45[/C][C]108.542873263889[/C][C]108.1375[/C][C]0.405373263888894[/C][C]-0.092873263888876[/C][/ROW]
[ROW][C]41[/C][C]109.39[/C][C]108.988394097222[/C][C]108.489583333333[/C][C]0.498810763888895[/C][C]0.401605902777789[/C][/ROW]
[ROW][C]42[/C][C]110.15[/C][C]109.274331597222[/C][C]108.751666666667[/C][C]0.522664930555561[/C][C]0.87566840277779[/C][/ROW]
[ROW][C]43[/C][C]109.13[/C][C]108.277144097222[/C][C]108.963333333333[/C][C]-0.686189236111111[/C][C]0.852855902777776[/C][/ROW]
[ROW][C]44[/C][C]110.28[/C][C]109.816206597222[/C][C]109.142083333333[/C][C]0.674123263888895[/C][C]0.463793402777782[/C][/ROW]
[ROW][C]45[/C][C]110.17[/C][C]109.526414930556[/C][C]109.257916666667[/C][C]0.268498263888880[/C][C]0.643585069444455[/C][/ROW]
[ROW][C]46[/C][C]109.99[/C][C]109.353394097222[/C][C]109.319583333333[/C][C]0.0338107638888877[/C][C]0.636605902777774[/C][/ROW]
[ROW][C]47[/C][C]109.26[/C][C]109.259331597222[/C][C]109.34125[/C][C]-0.0819184027777874[/C][C]0.000668402777790789[/C][/ROW]
[ROW][C]48[/C][C]109.11[/C][C]109.124748263889[/C][C]109.282083333333[/C][C]-0.157335069444439[/C][C]-0.0147482638888903[/C][/ROW]
[ROW][C]49[/C][C]107.06[/C][C]107.202352430556[/C][C]109.155[/C][C]-1.95264756944444[/C][C]-0.142352430555547[/C][/ROW]
[ROW][C]50[/C][C]109.53[/C][C]109.352873263889[/C][C]109.042916666667[/C][C]0.309956597222212[/C][C]0.177126736111106[/C][/ROW]
[ROW][C]51[/C][C]108.92[/C][C]109.127769097222[/C][C]108.962916666667[/C][C]0.164852430555552[/C][C]-0.207769097222226[/C][/ROW]
[ROW][C]52[/C][C]109.24[/C][C]109.280789930556[/C][C]108.875416666667[/C][C]0.405373263888894[/C][C]-0.0407899305555475[/C][/ROW]
[ROW][C]53[/C][C]109.12[/C][C]109.332560763889[/C][C]108.83375[/C][C]0.498810763888895[/C][C]-0.212560763888888[/C][/ROW]
[ROW][C]54[/C][C]109[/C][C]109.369748263889[/C][C]108.847083333333[/C][C]0.522664930555561[/C][C]-0.36974826388888[/C][/ROW]
[ROW][C]55[/C][C]107.23[/C][C]NA[/C][C]NA[/C][C]-0.686189236111111[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]109.49[/C][C]NA[/C][C]NA[/C][C]0.674123263888895[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]109.04[/C][C]NA[/C][C]NA[/C][C]0.268498263888880[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]109.02[/C][C]NA[/C][C]NA[/C][C]0.0338107638888877[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]109.23[/C][C]NA[/C][C]NA[/C][C]-0.0819184027777874[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]109.46[/C][C]NA[/C][C]NA[/C][C]-0.157335069444439[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108896&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	96.92	NA	NA	-1.95264756944444	NA
2	99.06	NA	NA	0.309956597222212	NA
3	99.65	NA	NA	0.164852430555552	NA
4	99.82	NA	NA	0.405373263888894	NA
5	99.99	NA	NA	0.498810763888895	NA
6	100.33	NA	NA	0.522664930555561	NA
7	99.31	99.4246440972222	100.110833333333	-0.686189236111111	-0.114644097222211
8	101.1	101.014123263889	100.34	0.674123263888895	0.0858767361111177
9	101.1	100.815998263889	100.5475	0.268498263888880	0.284001736111122
10	100.93	100.777977430556	100.744166666667	0.0338107638888877	0.152022569444455
11	100.85	100.883498263889	100.965416666667	-0.0819184027777874	-0.0334982638888874
12	100.93	101.026414930556	101.18375	-0.157335069444439	-0.0964149305555253
13	99.6	99.4352690972222	101.387916666667	-1.95264756944444	0.164730902777777
14	101.88	101.897039930556	101.587083333333	0.309956597222212	-0.0170399305555406
15	101.81	101.929019097222	101.764166666667	0.164852430555552	-0.119019097222207
16	102.38	102.320789930556	101.915416666667	0.405373263888894	0.059210069444461
17	102.74	102.572560763889	102.07375	0.498810763888895	0.167439236111107
18	102.82	102.769331597222	102.246666666667	0.522664930555561	0.0506684027777737
19	101.72	101.718394097222	102.404583333333	-0.686189236111111	0.00160590277776862
20	103.47	103.224539930556	102.550416666667	0.674123263888895	0.245460069444434
21	102.98	102.972248263889	102.70375	0.268498263888880	0.00775173611110347
22	102.68	102.891310763889	102.8575	0.0338107638888877	-0.211310763888889
23	102.9	102.907248263889	102.989166666667	-0.0819184027777874	-0.00724826388888289
24	103.03	102.943498263889	103.100833333333	-0.157335069444439	0.0865017361111171
25	101.29	101.259435763889	103.212083333333	-1.95264756944444	0.0305642361111182
26	103.69	103.627039930556	103.317083333333	0.309956597222212	0.0629600694444576
27	103.68	103.593185763889	103.428333333333	0.164852430555552	0.0868142361111097
28	104.2	103.989956597222	103.584583333333	0.405373263888894	0.210043402777785
29	104.08	104.300894097222	103.802083333333	0.498810763888895	-0.220894097222214
30	104.16	104.580998263889	104.058333333333	0.522664930555561	-0.42099826388889
31	103.05	103.654227430556	104.340416666667	-0.686189236111111	-0.604227430555554
32	104.66	105.319539930556	104.645416666667	0.674123263888895	-0.659539930555553
33	104.46	105.259748263889	104.99125	0.268498263888880	-0.799748263888901
34	104.95	105.391727430556	105.357916666667	0.0338107638888877	-0.441727430555559
35	105.85	105.674331597222	105.75625	-0.0819184027777874	0.175668402777788
36	106.23	106.069748263889	106.227083333333	-0.157335069444439	0.160251736111121
37	104.86	104.777352430556	106.73	-1.95264756944444	0.0826475694444468
38	107.44	107.527456597222	107.2175	0.309956597222212	-0.0874565972222143
39	108.23	107.854435763889	107.689583333333	0.164852430555552	0.375564236111117
40	108.45	108.542873263889	108.1375	0.405373263888894	-0.092873263888876
41	109.39	108.988394097222	108.489583333333	0.498810763888895	0.401605902777789
42	110.15	109.274331597222	108.751666666667	0.522664930555561	0.87566840277779
43	109.13	108.277144097222	108.963333333333	-0.686189236111111	0.852855902777776
44	110.28	109.816206597222	109.142083333333	0.674123263888895	0.463793402777782
45	110.17	109.526414930556	109.257916666667	0.268498263888880	0.643585069444455
46	109.99	109.353394097222	109.319583333333	0.0338107638888877	0.636605902777774
47	109.26	109.259331597222	109.34125	-0.0819184027777874	0.000668402777790789
48	109.11	109.124748263889	109.282083333333	-0.157335069444439	-0.0147482638888903
49	107.06	107.202352430556	109.155	-1.95264756944444	-0.142352430555547
50	109.53	109.352873263889	109.042916666667	0.309956597222212	0.177126736111106
51	108.92	109.127769097222	108.962916666667	0.164852430555552	-0.207769097222226
52	109.24	109.280789930556	108.875416666667	0.405373263888894	-0.0407899305555475
53	109.12	109.332560763889	108.83375	0.498810763888895	-0.212560763888888
54	109	109.369748263889	108.847083333333	0.522664930555561	-0.36974826388888
55	107.23	NA	NA	-0.686189236111111	NA
56	109.49	NA	NA	0.674123263888895	NA
57	109.04	NA	NA	0.268498263888880	NA
58	109.02	NA	NA	0.0338107638888877	NA
59	109.23	NA	NA	-0.0819184027777874	NA
60	109.46	NA	NA	-0.157335069444439	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 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; par2 = 12 ;

R code (references can be found in the software module):

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code