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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Sun, 06 Dec 2009 03:41:04 -0700

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/06/t1260096099w3rlpqnk7prrvt6.htm/, Retrieved Mon, 29 Apr 2024 15:57:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64340, Retrieved Mon, 29 Apr 2024 15:57:17 +0000

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Estimated Impact

145

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

-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Classical Decomposition] [] [2009-11-27 14:58:37] [b98453cac15ba1066b407e146608df68]
-   PD    [Classical Decomposition] [workshop 9 bereke...] [2009-12-03 17:49:36] [eaf42bcf5162b5692bb3c7f9d4636222]
-   PD      [Classical Decomposition] [review workshop 9] [2009-12-04 10:30:04] [eaf42bcf5162b5692bb3c7f9d4636222]
-    D          [Classical Decomposition] [review workshop 9] [2009-12-06 10:41:04] [78d370e6d5f4594e9982a5085e7604c6] [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	'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64340&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64340&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64340&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	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	102.86	NA	NA	0.999475561748494	NA
2	102.55	NA	NA	0.998783384067919	NA
3	102.28	NA	NA	0.999724161541092	NA
4	102.26	NA	NA	1.00020201637734	NA
5	102.57	NA	NA	1.00024741222967	NA
6	103.08	NA	NA	0.998121731017254	NA
7	102.76	102.652125682148	102.7475	0.999071760209716	1.00105087271340
8	102.51	102.741488000615	102.7325	1.00008748935940	0.997746888767921
9	102.87	102.914331482291	102.758333333333	1.00151810703714	0.999569238981074
10	103.14	102.997087229921	102.79875	1.00192937394590	1.00138754186087
11	103.12	102.822335652294	102.80625	1.00015646570412	1.00289493859304
12	103.16	102.810540777981	102.740416666667	1.00068253676196	1.00339906024591
13	102.48	102.595333517181	102.649166666667	0.999475561748494	0.99887584051606
14	102.57	102.477672163829	102.6025	0.998783384067919	1.00090095563474
15	102.88	102.519213455635	102.5475	0.999724161541092	1.00351920905559
16	102.63	102.462361561055	102.441666666667	1.00020201637734	1.00163609774741
17	102.38	102.340730752034	102.315416666667	1.00024741222967	1.00038371084199
18	101.69	101.980592562360	102.1725	0.998121731017254	0.997150511140806
19	101.96	101.944033572099	102.03875	0.999071760209716	1.00015661954252
20	102.19	101.949752071538	101.940833333333	1.00008748935940	1.00235653273873
21	101.87	101.998777012775	101.844166666667	1.00151810703714	0.99873746512903
22	101.6	101.948401151857	101.752083333333	1.00192937394590	0.996582573655682
23	101.63	101.702160410705	101.68625	1.00015646570412	0.99929047317762
24	101.22	101.735640953076	101.66625	1.00068253676196	0.99493156038292
25	101.21	101.610850088859	101.664166666667	0.999475561748494	0.99605504639998
26	101.49	101.495119009752	101.61875	0.998783384067919	0.99994956398099
27	101.64	101.528653432241	101.556666666667	0.999724161541092	1.00109670092131
28	101.66	101.543425958509	101.522916666667	1.00020201637734	1.00114802155227
29	101.77	101.517193715965	101.492083333333	1.00024741222967	1.00249028046168
30	101.82	101.292304452013	101.482916666667	0.998121731017254	1.00520963118414
31	101.78	101.443665132194	101.537916666667	0.999071760209716	1.00331548418886
32	101.28	101.650142527851	101.64125	1.00008748935940	0.996358661988597
33	101.29	101.916569068156	101.762083333333	1.00151810703714	0.993852137352302
34	101.37	102.094098381652	101.8975	1.00192937394590	0.99290753928846
35	101.12	102.066384056966	102.050416666667	1.00015646570412	0.990727759529154
36	101.51	102.305196096916	102.235416666667	1.00068253676196	0.992227216922954
37	102.24	102.387525889968	102.44125	0.999475561748494	0.998559141959086
38	102.94	102.578798981466	102.70375	0.998783384067919	1.00352120537695
39	103.09	103.026990019351	103.055416666667	0.999724161541092	1.00061158712525
40	103.46	103.453395058949	103.4325	1.00020201637734	1.00006384460411
41	103.64	103.825264619685	103.799583333333	1.00024741222967	0.998215611389354
42	104.39	103.946476488410	104.142083333333	0.998121731017254	1.00426684507810
43	104.15	104.313082483496	104.41	0.999071760209716	0.998436605652774
44	105.21	104.530811200327	104.521666666667	1.00008748935940	1.00649749860232
45	105.8	104.669491964874	104.510833333333	1.00151810703714	1.01080074063515
46	105.91	104.645678520634	104.444166666667	1.00192937394590	1.01208192729255
47	105.39	104.341740016443	104.325416666667	1.00015646570412	1.01004641079775
48	105.46	104.168133419521	104.097083333333	1.00068253676196	1.01240174454577
49	104.72	103.737650794630	103.792083333333	0.999475561748494	1.00946955322244
50	103.14	103.285854385437	103.411666666667	0.998783384067919	0.998587857104879
51	102.63	102.863285187899	102.891666666667	0.999724161541092	0.997732084995413
52	102.32	102.308580501037	102.287916666667	1.00020201637734	1.00011161819377
53	101.93	101.739748765186	101.714583333333	1.00024741222967	1.00186997940454
54	100.62	100.990372628380	101.180416666667	0.998121731017254	0.996332594694514
55	100.6	NA	NA	0.999071760209716	NA
56	99.63	NA	NA	1.00008748935940	NA
57	98.9	NA	NA	1.00151810703714	NA
58	98.32	NA	NA	1.00192937394590	NA
59	99.22	NA	NA	1.00015646570412	NA
60	98.81	NA	NA	1.00068253676196	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 102.86 & NA & NA & 0.999475561748494 & NA \tabularnewline
2 & 102.55 & NA & NA & 0.998783384067919 & NA \tabularnewline
3 & 102.28 & NA & NA & 0.999724161541092 & NA \tabularnewline
4 & 102.26 & NA & NA & 1.00020201637734 & NA \tabularnewline
5 & 102.57 & NA & NA & 1.00024741222967 & NA \tabularnewline
6 & 103.08 & NA & NA & 0.998121731017254 & NA \tabularnewline
7 & 102.76 & 102.652125682148 & 102.7475 & 0.999071760209716 & 1.00105087271340 \tabularnewline
8 & 102.51 & 102.741488000615 & 102.7325 & 1.00008748935940 & 0.997746888767921 \tabularnewline
9 & 102.87 & 102.914331482291 & 102.758333333333 & 1.00151810703714 & 0.999569238981074 \tabularnewline
10 & 103.14 & 102.997087229921 & 102.79875 & 1.00192937394590 & 1.00138754186087 \tabularnewline
11 & 103.12 & 102.822335652294 & 102.80625 & 1.00015646570412 & 1.00289493859304 \tabularnewline
12 & 103.16 & 102.810540777981 & 102.740416666667 & 1.00068253676196 & 1.00339906024591 \tabularnewline
13 & 102.48 & 102.595333517181 & 102.649166666667 & 0.999475561748494 & 0.99887584051606 \tabularnewline
14 & 102.57 & 102.477672163829 & 102.6025 & 0.998783384067919 & 1.00090095563474 \tabularnewline
15 & 102.88 & 102.519213455635 & 102.5475 & 0.999724161541092 & 1.00351920905559 \tabularnewline
16 & 102.63 & 102.462361561055 & 102.441666666667 & 1.00020201637734 & 1.00163609774741 \tabularnewline
17 & 102.38 & 102.340730752034 & 102.315416666667 & 1.00024741222967 & 1.00038371084199 \tabularnewline
18 & 101.69 & 101.980592562360 & 102.1725 & 0.998121731017254 & 0.997150511140806 \tabularnewline
19 & 101.96 & 101.944033572099 & 102.03875 & 0.999071760209716 & 1.00015661954252 \tabularnewline
20 & 102.19 & 101.949752071538 & 101.940833333333 & 1.00008748935940 & 1.00235653273873 \tabularnewline
21 & 101.87 & 101.998777012775 & 101.844166666667 & 1.00151810703714 & 0.99873746512903 \tabularnewline
22 & 101.6 & 101.948401151857 & 101.752083333333 & 1.00192937394590 & 0.996582573655682 \tabularnewline
23 & 101.63 & 101.702160410705 & 101.68625 & 1.00015646570412 & 0.99929047317762 \tabularnewline
24 & 101.22 & 101.735640953076 & 101.66625 & 1.00068253676196 & 0.99493156038292 \tabularnewline
25 & 101.21 & 101.610850088859 & 101.664166666667 & 0.999475561748494 & 0.99605504639998 \tabularnewline
26 & 101.49 & 101.495119009752 & 101.61875 & 0.998783384067919 & 0.99994956398099 \tabularnewline
27 & 101.64 & 101.528653432241 & 101.556666666667 & 0.999724161541092 & 1.00109670092131 \tabularnewline
28 & 101.66 & 101.543425958509 & 101.522916666667 & 1.00020201637734 & 1.00114802155227 \tabularnewline
29 & 101.77 & 101.517193715965 & 101.492083333333 & 1.00024741222967 & 1.00249028046168 \tabularnewline
30 & 101.82 & 101.292304452013 & 101.482916666667 & 0.998121731017254 & 1.00520963118414 \tabularnewline
31 & 101.78 & 101.443665132194 & 101.537916666667 & 0.999071760209716 & 1.00331548418886 \tabularnewline
32 & 101.28 & 101.650142527851 & 101.64125 & 1.00008748935940 & 0.996358661988597 \tabularnewline
33 & 101.29 & 101.916569068156 & 101.762083333333 & 1.00151810703714 & 0.993852137352302 \tabularnewline
34 & 101.37 & 102.094098381652 & 101.8975 & 1.00192937394590 & 0.99290753928846 \tabularnewline
35 & 101.12 & 102.066384056966 & 102.050416666667 & 1.00015646570412 & 0.990727759529154 \tabularnewline
36 & 101.51 & 102.305196096916 & 102.235416666667 & 1.00068253676196 & 0.992227216922954 \tabularnewline
37 & 102.24 & 102.387525889968 & 102.44125 & 0.999475561748494 & 0.998559141959086 \tabularnewline
38 & 102.94 & 102.578798981466 & 102.70375 & 0.998783384067919 & 1.00352120537695 \tabularnewline
39 & 103.09 & 103.026990019351 & 103.055416666667 & 0.999724161541092 & 1.00061158712525 \tabularnewline
40 & 103.46 & 103.453395058949 & 103.4325 & 1.00020201637734 & 1.00006384460411 \tabularnewline
41 & 103.64 & 103.825264619685 & 103.799583333333 & 1.00024741222967 & 0.998215611389354 \tabularnewline
42 & 104.39 & 103.946476488410 & 104.142083333333 & 0.998121731017254 & 1.00426684507810 \tabularnewline
43 & 104.15 & 104.313082483496 & 104.41 & 0.999071760209716 & 0.998436605652774 \tabularnewline
44 & 105.21 & 104.530811200327 & 104.521666666667 & 1.00008748935940 & 1.00649749860232 \tabularnewline
45 & 105.8 & 104.669491964874 & 104.510833333333 & 1.00151810703714 & 1.01080074063515 \tabularnewline
46 & 105.91 & 104.645678520634 & 104.444166666667 & 1.00192937394590 & 1.01208192729255 \tabularnewline
47 & 105.39 & 104.341740016443 & 104.325416666667 & 1.00015646570412 & 1.01004641079775 \tabularnewline
48 & 105.46 & 104.168133419521 & 104.097083333333 & 1.00068253676196 & 1.01240174454577 \tabularnewline
49 & 104.72 & 103.737650794630 & 103.792083333333 & 0.999475561748494 & 1.00946955322244 \tabularnewline
50 & 103.14 & 103.285854385437 & 103.411666666667 & 0.998783384067919 & 0.998587857104879 \tabularnewline
51 & 102.63 & 102.863285187899 & 102.891666666667 & 0.999724161541092 & 0.997732084995413 \tabularnewline
52 & 102.32 & 102.308580501037 & 102.287916666667 & 1.00020201637734 & 1.00011161819377 \tabularnewline
53 & 101.93 & 101.739748765186 & 101.714583333333 & 1.00024741222967 & 1.00186997940454 \tabularnewline
54 & 100.62 & 100.990372628380 & 101.180416666667 & 0.998121731017254 & 0.996332594694514 \tabularnewline
55 & 100.6 & NA & NA & 0.999071760209716 & NA \tabularnewline
56 & 99.63 & NA & NA & 1.00008748935940 & NA \tabularnewline
57 & 98.9 & NA & NA & 1.00151810703714 & NA \tabularnewline
58 & 98.32 & NA & NA & 1.00192937394590 & NA \tabularnewline
59 & 99.22 & NA & NA & 1.00015646570412 & NA \tabularnewline
60 & 98.81 & NA & NA & 1.00068253676196 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64340&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]102.86[/C][C]NA[/C][C]NA[/C][C]0.999475561748494[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]102.55[/C][C]NA[/C][C]NA[/C][C]0.998783384067919[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]102.28[/C][C]NA[/C][C]NA[/C][C]0.999724161541092[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]102.26[/C][C]NA[/C][C]NA[/C][C]1.00020201637734[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]102.57[/C][C]NA[/C][C]NA[/C][C]1.00024741222967[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]103.08[/C][C]NA[/C][C]NA[/C][C]0.998121731017254[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]102.76[/C][C]102.652125682148[/C][C]102.7475[/C][C]0.999071760209716[/C][C]1.00105087271340[/C][/ROW]
[ROW][C]8[/C][C]102.51[/C][C]102.741488000615[/C][C]102.7325[/C][C]1.00008748935940[/C][C]0.997746888767921[/C][/ROW]
[ROW][C]9[/C][C]102.87[/C][C]102.914331482291[/C][C]102.758333333333[/C][C]1.00151810703714[/C][C]0.999569238981074[/C][/ROW]
[ROW][C]10[/C][C]103.14[/C][C]102.997087229921[/C][C]102.79875[/C][C]1.00192937394590[/C][C]1.00138754186087[/C][/ROW]
[ROW][C]11[/C][C]103.12[/C][C]102.822335652294[/C][C]102.80625[/C][C]1.00015646570412[/C][C]1.00289493859304[/C][/ROW]
[ROW][C]12[/C][C]103.16[/C][C]102.810540777981[/C][C]102.740416666667[/C][C]1.00068253676196[/C][C]1.00339906024591[/C][/ROW]
[ROW][C]13[/C][C]102.48[/C][C]102.595333517181[/C][C]102.649166666667[/C][C]0.999475561748494[/C][C]0.99887584051606[/C][/ROW]
[ROW][C]14[/C][C]102.57[/C][C]102.477672163829[/C][C]102.6025[/C][C]0.998783384067919[/C][C]1.00090095563474[/C][/ROW]
[ROW][C]15[/C][C]102.88[/C][C]102.519213455635[/C][C]102.5475[/C][C]0.999724161541092[/C][C]1.00351920905559[/C][/ROW]
[ROW][C]16[/C][C]102.63[/C][C]102.462361561055[/C][C]102.441666666667[/C][C]1.00020201637734[/C][C]1.00163609774741[/C][/ROW]
[ROW][C]17[/C][C]102.38[/C][C]102.340730752034[/C][C]102.315416666667[/C][C]1.00024741222967[/C][C]1.00038371084199[/C][/ROW]
[ROW][C]18[/C][C]101.69[/C][C]101.980592562360[/C][C]102.1725[/C][C]0.998121731017254[/C][C]0.997150511140806[/C][/ROW]
[ROW][C]19[/C][C]101.96[/C][C]101.944033572099[/C][C]102.03875[/C][C]0.999071760209716[/C][C]1.00015661954252[/C][/ROW]
[ROW][C]20[/C][C]102.19[/C][C]101.949752071538[/C][C]101.940833333333[/C][C]1.00008748935940[/C][C]1.00235653273873[/C][/ROW]
[ROW][C]21[/C][C]101.87[/C][C]101.998777012775[/C][C]101.844166666667[/C][C]1.00151810703714[/C][C]0.99873746512903[/C][/ROW]
[ROW][C]22[/C][C]101.6[/C][C]101.948401151857[/C][C]101.752083333333[/C][C]1.00192937394590[/C][C]0.996582573655682[/C][/ROW]
[ROW][C]23[/C][C]101.63[/C][C]101.702160410705[/C][C]101.68625[/C][C]1.00015646570412[/C][C]0.99929047317762[/C][/ROW]
[ROW][C]24[/C][C]101.22[/C][C]101.735640953076[/C][C]101.66625[/C][C]1.00068253676196[/C][C]0.99493156038292[/C][/ROW]
[ROW][C]25[/C][C]101.21[/C][C]101.610850088859[/C][C]101.664166666667[/C][C]0.999475561748494[/C][C]0.99605504639998[/C][/ROW]
[ROW][C]26[/C][C]101.49[/C][C]101.495119009752[/C][C]101.61875[/C][C]0.998783384067919[/C][C]0.99994956398099[/C][/ROW]
[ROW][C]27[/C][C]101.64[/C][C]101.528653432241[/C][C]101.556666666667[/C][C]0.999724161541092[/C][C]1.00109670092131[/C][/ROW]
[ROW][C]28[/C][C]101.66[/C][C]101.543425958509[/C][C]101.522916666667[/C][C]1.00020201637734[/C][C]1.00114802155227[/C][/ROW]
[ROW][C]29[/C][C]101.77[/C][C]101.517193715965[/C][C]101.492083333333[/C][C]1.00024741222967[/C][C]1.00249028046168[/C][/ROW]
[ROW][C]30[/C][C]101.82[/C][C]101.292304452013[/C][C]101.482916666667[/C][C]0.998121731017254[/C][C]1.00520963118414[/C][/ROW]
[ROW][C]31[/C][C]101.78[/C][C]101.443665132194[/C][C]101.537916666667[/C][C]0.999071760209716[/C][C]1.00331548418886[/C][/ROW]
[ROW][C]32[/C][C]101.28[/C][C]101.650142527851[/C][C]101.64125[/C][C]1.00008748935940[/C][C]0.996358661988597[/C][/ROW]
[ROW][C]33[/C][C]101.29[/C][C]101.916569068156[/C][C]101.762083333333[/C][C]1.00151810703714[/C][C]0.993852137352302[/C][/ROW]
[ROW][C]34[/C][C]101.37[/C][C]102.094098381652[/C][C]101.8975[/C][C]1.00192937394590[/C][C]0.99290753928846[/C][/ROW]
[ROW][C]35[/C][C]101.12[/C][C]102.066384056966[/C][C]102.050416666667[/C][C]1.00015646570412[/C][C]0.990727759529154[/C][/ROW]
[ROW][C]36[/C][C]101.51[/C][C]102.305196096916[/C][C]102.235416666667[/C][C]1.00068253676196[/C][C]0.992227216922954[/C][/ROW]
[ROW][C]37[/C][C]102.24[/C][C]102.387525889968[/C][C]102.44125[/C][C]0.999475561748494[/C][C]0.998559141959086[/C][/ROW]
[ROW][C]38[/C][C]102.94[/C][C]102.578798981466[/C][C]102.70375[/C][C]0.998783384067919[/C][C]1.00352120537695[/C][/ROW]
[ROW][C]39[/C][C]103.09[/C][C]103.026990019351[/C][C]103.055416666667[/C][C]0.999724161541092[/C][C]1.00061158712525[/C][/ROW]
[ROW][C]40[/C][C]103.46[/C][C]103.453395058949[/C][C]103.4325[/C][C]1.00020201637734[/C][C]1.00006384460411[/C][/ROW]
[ROW][C]41[/C][C]103.64[/C][C]103.825264619685[/C][C]103.799583333333[/C][C]1.00024741222967[/C][C]0.998215611389354[/C][/ROW]
[ROW][C]42[/C][C]104.39[/C][C]103.946476488410[/C][C]104.142083333333[/C][C]0.998121731017254[/C][C]1.00426684507810[/C][/ROW]
[ROW][C]43[/C][C]104.15[/C][C]104.313082483496[/C][C]104.41[/C][C]0.999071760209716[/C][C]0.998436605652774[/C][/ROW]
[ROW][C]44[/C][C]105.21[/C][C]104.530811200327[/C][C]104.521666666667[/C][C]1.00008748935940[/C][C]1.00649749860232[/C][/ROW]
[ROW][C]45[/C][C]105.8[/C][C]104.669491964874[/C][C]104.510833333333[/C][C]1.00151810703714[/C][C]1.01080074063515[/C][/ROW]
[ROW][C]46[/C][C]105.91[/C][C]104.645678520634[/C][C]104.444166666667[/C][C]1.00192937394590[/C][C]1.01208192729255[/C][/ROW]
[ROW][C]47[/C][C]105.39[/C][C]104.341740016443[/C][C]104.325416666667[/C][C]1.00015646570412[/C][C]1.01004641079775[/C][/ROW]
[ROW][C]48[/C][C]105.46[/C][C]104.168133419521[/C][C]104.097083333333[/C][C]1.00068253676196[/C][C]1.01240174454577[/C][/ROW]
[ROW][C]49[/C][C]104.72[/C][C]103.737650794630[/C][C]103.792083333333[/C][C]0.999475561748494[/C][C]1.00946955322244[/C][/ROW]
[ROW][C]50[/C][C]103.14[/C][C]103.285854385437[/C][C]103.411666666667[/C][C]0.998783384067919[/C][C]0.998587857104879[/C][/ROW]
[ROW][C]51[/C][C]102.63[/C][C]102.863285187899[/C][C]102.891666666667[/C][C]0.999724161541092[/C][C]0.997732084995413[/C][/ROW]
[ROW][C]52[/C][C]102.32[/C][C]102.308580501037[/C][C]102.287916666667[/C][C]1.00020201637734[/C][C]1.00011161819377[/C][/ROW]
[ROW][C]53[/C][C]101.93[/C][C]101.739748765186[/C][C]101.714583333333[/C][C]1.00024741222967[/C][C]1.00186997940454[/C][/ROW]
[ROW][C]54[/C][C]100.62[/C][C]100.990372628380[/C][C]101.180416666667[/C][C]0.998121731017254[/C][C]0.996332594694514[/C][/ROW]
[ROW][C]55[/C][C]100.6[/C][C]NA[/C][C]NA[/C][C]0.999071760209716[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]99.63[/C][C]NA[/C][C]NA[/C][C]1.00008748935940[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]98.9[/C][C]NA[/C][C]NA[/C][C]1.00151810703714[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]98.32[/C][C]NA[/C][C]NA[/C][C]1.00192937394590[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]99.22[/C][C]NA[/C][C]NA[/C][C]1.00015646570412[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]98.81[/C][C]NA[/C][C]NA[/C][C]1.00068253676196[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64340&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64340&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	102.86	NA	NA	0.999475561748494	NA
2	102.55	NA	NA	0.998783384067919	NA
3	102.28	NA	NA	0.999724161541092	NA
4	102.26	NA	NA	1.00020201637734	NA
5	102.57	NA	NA	1.00024741222967	NA
6	103.08	NA	NA	0.998121731017254	NA
7	102.76	102.652125682148	102.7475	0.999071760209716	1.00105087271340
8	102.51	102.741488000615	102.7325	1.00008748935940	0.997746888767921
9	102.87	102.914331482291	102.758333333333	1.00151810703714	0.999569238981074
10	103.14	102.997087229921	102.79875	1.00192937394590	1.00138754186087
11	103.12	102.822335652294	102.80625	1.00015646570412	1.00289493859304
12	103.16	102.810540777981	102.740416666667	1.00068253676196	1.00339906024591
13	102.48	102.595333517181	102.649166666667	0.999475561748494	0.99887584051606
14	102.57	102.477672163829	102.6025	0.998783384067919	1.00090095563474
15	102.88	102.519213455635	102.5475	0.999724161541092	1.00351920905559
16	102.63	102.462361561055	102.441666666667	1.00020201637734	1.00163609774741
17	102.38	102.340730752034	102.315416666667	1.00024741222967	1.00038371084199
18	101.69	101.980592562360	102.1725	0.998121731017254	0.997150511140806
19	101.96	101.944033572099	102.03875	0.999071760209716	1.00015661954252
20	102.19	101.949752071538	101.940833333333	1.00008748935940	1.00235653273873
21	101.87	101.998777012775	101.844166666667	1.00151810703714	0.99873746512903
22	101.6	101.948401151857	101.752083333333	1.00192937394590	0.996582573655682
23	101.63	101.702160410705	101.68625	1.00015646570412	0.99929047317762
24	101.22	101.735640953076	101.66625	1.00068253676196	0.99493156038292
25	101.21	101.610850088859	101.664166666667	0.999475561748494	0.99605504639998
26	101.49	101.495119009752	101.61875	0.998783384067919	0.99994956398099
27	101.64	101.528653432241	101.556666666667	0.999724161541092	1.00109670092131
28	101.66	101.543425958509	101.522916666667	1.00020201637734	1.00114802155227
29	101.77	101.517193715965	101.492083333333	1.00024741222967	1.00249028046168
30	101.82	101.292304452013	101.482916666667	0.998121731017254	1.00520963118414
31	101.78	101.443665132194	101.537916666667	0.999071760209716	1.00331548418886
32	101.28	101.650142527851	101.64125	1.00008748935940	0.996358661988597
33	101.29	101.916569068156	101.762083333333	1.00151810703714	0.993852137352302
34	101.37	102.094098381652	101.8975	1.00192937394590	0.99290753928846
35	101.12	102.066384056966	102.050416666667	1.00015646570412	0.990727759529154
36	101.51	102.305196096916	102.235416666667	1.00068253676196	0.992227216922954
37	102.24	102.387525889968	102.44125	0.999475561748494	0.998559141959086
38	102.94	102.578798981466	102.70375	0.998783384067919	1.00352120537695
39	103.09	103.026990019351	103.055416666667	0.999724161541092	1.00061158712525
40	103.46	103.453395058949	103.4325	1.00020201637734	1.00006384460411
41	103.64	103.825264619685	103.799583333333	1.00024741222967	0.998215611389354
42	104.39	103.946476488410	104.142083333333	0.998121731017254	1.00426684507810
43	104.15	104.313082483496	104.41	0.999071760209716	0.998436605652774
44	105.21	104.530811200327	104.521666666667	1.00008748935940	1.00649749860232
45	105.8	104.669491964874	104.510833333333	1.00151810703714	1.01080074063515
46	105.91	104.645678520634	104.444166666667	1.00192937394590	1.01208192729255
47	105.39	104.341740016443	104.325416666667	1.00015646570412	1.01004641079775
48	105.46	104.168133419521	104.097083333333	1.00068253676196	1.01240174454577
49	104.72	103.737650794630	103.792083333333	0.999475561748494	1.00946955322244
50	103.14	103.285854385437	103.411666666667	0.998783384067919	0.998587857104879
51	102.63	102.863285187899	102.891666666667	0.999724161541092	0.997732084995413
52	102.32	102.308580501037	102.287916666667	1.00020201637734	1.00011161819377
53	101.93	101.739748765186	101.714583333333	1.00024741222967	1.00186997940454
54	100.62	100.990372628380	101.180416666667	0.998121731017254	0.996332594694514
55	100.6	NA	NA	0.999071760209716	NA
56	99.63	NA	NA	1.00008748935940	NA
57	98.9	NA	NA	1.00151810703714	NA
58	98.32	NA	NA	1.00192937394590	NA
59	99.22	NA	NA	1.00015646570412	NA
60	98.81	NA	NA	1.00068253676196	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