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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sat, 25 May 2013 08:12:18 -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/2013/May/25/t1369484133lxs0ljvodg7wfcw.htm/, Retrieved Thu, 02 May 2024 14:53:12 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=210489, Retrieved Thu, 02 May 2024 14:53:12 +0000

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Estimated Impact

116

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

-     [Variability] [] [2013-04-28 12:09:59] [b6e284768173daa602d243042729bd3c]
- RMPD  [Classical Decomposition] [] [2013-05-25 12:05:24] [b6e284768173daa602d243042729bd3c]
- R  D      [Classical Decomposition] [] [2013-05-25 12:12:18] [4d26c4233714d8e4ecf99606d744931b] [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	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210489&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210489&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210489&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	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	102.42	NA	NA	0.995542582112873	NA
2	102.46	NA	NA	0.999797379172134	NA
3	102.76	NA	NA	1.00219327610714	NA
4	102.4	NA	NA	1.00228243531629	NA
5	102.47	NA	NA	1.00314368363459	NA
6	102.27	NA	NA	0.999679607043032	NA
7	102.17	102.339134785738	102.68125	0.996668182221564	0.99834731077127
8	101.84	102.503750514853	102.879166666667	0.996350902092448	0.993524622157543
9	102.13	103.512044999361	103.135416666667	1.00365178466202	0.986648462028074
10	103.34	103.791066310676	103.43	1.00349092439985	0.995654093105414
11	103.43	103.842093546154	103.759166666667	1.00079922460975	0.996031536614095
12	103.59	103.727732939255	104.1025	0.996400018628319	0.998672168615358
13	104.21	103.992718889874	104.458333333333	0.995542582112873	1.00208938772296
14	105.42	104.847917989299	104.869166666667	0.999797379172134	1.00545630301175
15	105.95	105.604446147663	105.373333333333	1.00219327610714	1.00327215249871
16	106.28	106.114147133024	105.8725	1.00228243531629	1.00156296659265
17	106.49	106.657998232843	106.32375	1.00314368363459	0.998424888563194
18	106.49	106.726627914253	106.760833333333	0.999679607043032	0.997782859639833
19	106.49	106.806284634137	107.163333333333	0.996668182221564	0.997038707645152
20	107.38	107.150897180696	107.543333333333	0.996350902092448	1.00213813253395
21	108.69	108.331246318713	107.937083333333	1.00365178466202	1.0033116362405
22	108.76	108.716534264605	108.338333333333	1.00349092439985	1.00039980795643
23	108.84	108.844838670172	108.757916666667	1.00079922460975	0.999955545249267
24	108.67	108.825979701236	109.219166666667	0.996400018628319	0.998566705287981
25	108.79	109.214754542465	109.70375	0.995542582112873	0.996110831872081
26	109.96	110.193501309939	110.215833333333	0.999797379172134	0.997880988378047
27	110.86	110.981213073978	110.738333333333	1.00219327610714	0.998907805468868
28	111	111.518537547786	111.264583333333	1.00228243531629	0.995350212088611
29	111.84	112.15856943144	111.807083333333	1.00314368363459	0.997159651437651
30	112.21	112.319835315659	112.355833333333	0.999679607043032	0.999022120043621
31	112.4	112.536296125092	112.9125	0.996668182221564	0.99878886963775
32	113.76	113.041821889317	113.455833333333	0.996350902092448	1.00635320714652
33	114.85	114.384102956712	113.967916666667	1.00365178466202	1.0040730925998
34	115.23	114.882567873824	114.482916666667	1.00349092439985	1.00302423711975
35	115.39	115.098165825275	115.00625	1.00079922460975	1.00253552411225
36	115.29	115.109942485385	115.525833333333	0.996400018628319	1.00156422208827
37	115.53	115.55843483757	116.075833333333	0.995542582112873	0.999753935421416
38	116.26	116.575541246988	116.599166666667	0.999797379172134	0.99729324656259
39	116.85	117.399843426912	117.142916666667	1.00219327610714	0.995316489265553
40	117.37	118.040472877925	117.771666666667	1.00228243531629	0.994319974652946
41	118.03	118.813591819286	118.44125	1.00314368363459	0.99340486380988
42	118.49	119.115157444534	119.153333333333	0.999679607043032	0.994751654970316
43	119.32	119.498438656319	119.897916666667	0.996668182221564	0.998506769976867
44	119.4	120.240872303144	120.68125	0.996350902092448	0.993006768106071
45	122.26	121.972965013488	121.529166666667	1.00365178466202	1.00235326727099
46	122.91	122.886662359568	122.459166666667	1.00349092439985	1.00018991190731
47	123.78	123.567012263858	123.468333333333	1.00079922460975	1.00172366177866
48	123.99	124.05595398597	124.504166666667	0.996400018628319	0.99946835291777
49	124.7	124.939349626938	125.49875	0.995542582112873	0.998084273468266
50	125.89	126.456038846657	126.481666666667	0.999797379172134	0.995523829056964
51	127.57	127.700719983167	127.42125	1.00219327610714	0.998976356725443
52	128.97	128.579055067594	128.28625	1.00228243531629	1.00304050245353
53	130.65	129.505431580691	129.099583333333	1.00314368363459	1.00883799548281
54	130.73	129.834222031053	129.875833333333	0.999679607043032	1.00689939797793
55	130.95	130.210545223155	130.645833333333	0.996668182221564	1.00567891621664
56	131.36	130.922999412203	131.4025	0.996350902092448	1.00333784430359
57	132.85	132.588255389263	132.105833333333	1.00365178466202	1.00197411610831
58	133.08	133.200876577525	132.7375	1.00349092439985	0.999092524158772
59	133.13	133.381516659864	133.275	1.00079922460975	0.998114306493413
60	133.27	133.258123324677	133.739583333333	0.996400018628319	1.0000891253383
61	133.9	133.58978504668	134.187916666667	0.995542582112873	1.00232214576295
62	134.85	134.553147871227	134.580416666667	0.999797379172134	1.00220620723832
63	135.49	135.234707936302	134.93875	1.00219327610714	1.0018877702891
64	136.21	135.655586678609	135.346666666667	1.00228243531629	1.00408691845994
65	136.31	136.237361650949	135.810416666667	1.00314368363459	1.00053317495415
66	136.22	136.233004582468	136.276666666667	0.999679607043032	0.999904541615981
67	136.22	NA	NA	0.996668182221564	NA
68	135.51	NA	NA	0.996350902092448	NA
69	137.3	NA	NA	1.00365178466202	NA
70	138.42	NA	NA	1.00349092439985	NA
71	138.92	NA	NA	1.00079922460975	NA
72	138.67	NA	NA	0.996400018628319	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 102.42 & NA & NA & 0.995542582112873 & NA \tabularnewline
2 & 102.46 & NA & NA & 0.999797379172134 & NA \tabularnewline
3 & 102.76 & NA & NA & 1.00219327610714 & NA \tabularnewline
4 & 102.4 & NA & NA & 1.00228243531629 & NA \tabularnewline
5 & 102.47 & NA & NA & 1.00314368363459 & NA \tabularnewline
6 & 102.27 & NA & NA & 0.999679607043032 & NA \tabularnewline
7 & 102.17 & 102.339134785738 & 102.68125 & 0.996668182221564 & 0.99834731077127 \tabularnewline
8 & 101.84 & 102.503750514853 & 102.879166666667 & 0.996350902092448 & 0.993524622157543 \tabularnewline
9 & 102.13 & 103.512044999361 & 103.135416666667 & 1.00365178466202 & 0.986648462028074 \tabularnewline
10 & 103.34 & 103.791066310676 & 103.43 & 1.00349092439985 & 0.995654093105414 \tabularnewline
11 & 103.43 & 103.842093546154 & 103.759166666667 & 1.00079922460975 & 0.996031536614095 \tabularnewline
12 & 103.59 & 103.727732939255 & 104.1025 & 0.996400018628319 & 0.998672168615358 \tabularnewline
13 & 104.21 & 103.992718889874 & 104.458333333333 & 0.995542582112873 & 1.00208938772296 \tabularnewline
14 & 105.42 & 104.847917989299 & 104.869166666667 & 0.999797379172134 & 1.00545630301175 \tabularnewline
15 & 105.95 & 105.604446147663 & 105.373333333333 & 1.00219327610714 & 1.00327215249871 \tabularnewline
16 & 106.28 & 106.114147133024 & 105.8725 & 1.00228243531629 & 1.00156296659265 \tabularnewline
17 & 106.49 & 106.657998232843 & 106.32375 & 1.00314368363459 & 0.998424888563194 \tabularnewline
18 & 106.49 & 106.726627914253 & 106.760833333333 & 0.999679607043032 & 0.997782859639833 \tabularnewline
19 & 106.49 & 106.806284634137 & 107.163333333333 & 0.996668182221564 & 0.997038707645152 \tabularnewline
20 & 107.38 & 107.150897180696 & 107.543333333333 & 0.996350902092448 & 1.00213813253395 \tabularnewline
21 & 108.69 & 108.331246318713 & 107.937083333333 & 1.00365178466202 & 1.0033116362405 \tabularnewline
22 & 108.76 & 108.716534264605 & 108.338333333333 & 1.00349092439985 & 1.00039980795643 \tabularnewline
23 & 108.84 & 108.844838670172 & 108.757916666667 & 1.00079922460975 & 0.999955545249267 \tabularnewline
24 & 108.67 & 108.825979701236 & 109.219166666667 & 0.996400018628319 & 0.998566705287981 \tabularnewline
25 & 108.79 & 109.214754542465 & 109.70375 & 0.995542582112873 & 0.996110831872081 \tabularnewline
26 & 109.96 & 110.193501309939 & 110.215833333333 & 0.999797379172134 & 0.997880988378047 \tabularnewline
27 & 110.86 & 110.981213073978 & 110.738333333333 & 1.00219327610714 & 0.998907805468868 \tabularnewline
28 & 111 & 111.518537547786 & 111.264583333333 & 1.00228243531629 & 0.995350212088611 \tabularnewline
29 & 111.84 & 112.15856943144 & 111.807083333333 & 1.00314368363459 & 0.997159651437651 \tabularnewline
30 & 112.21 & 112.319835315659 & 112.355833333333 & 0.999679607043032 & 0.999022120043621 \tabularnewline
31 & 112.4 & 112.536296125092 & 112.9125 & 0.996668182221564 & 0.99878886963775 \tabularnewline
32 & 113.76 & 113.041821889317 & 113.455833333333 & 0.996350902092448 & 1.00635320714652 \tabularnewline
33 & 114.85 & 114.384102956712 & 113.967916666667 & 1.00365178466202 & 1.0040730925998 \tabularnewline
34 & 115.23 & 114.882567873824 & 114.482916666667 & 1.00349092439985 & 1.00302423711975 \tabularnewline
35 & 115.39 & 115.098165825275 & 115.00625 & 1.00079922460975 & 1.00253552411225 \tabularnewline
36 & 115.29 & 115.109942485385 & 115.525833333333 & 0.996400018628319 & 1.00156422208827 \tabularnewline
37 & 115.53 & 115.55843483757 & 116.075833333333 & 0.995542582112873 & 0.999753935421416 \tabularnewline
38 & 116.26 & 116.575541246988 & 116.599166666667 & 0.999797379172134 & 0.99729324656259 \tabularnewline
39 & 116.85 & 117.399843426912 & 117.142916666667 & 1.00219327610714 & 0.995316489265553 \tabularnewline
40 & 117.37 & 118.040472877925 & 117.771666666667 & 1.00228243531629 & 0.994319974652946 \tabularnewline
41 & 118.03 & 118.813591819286 & 118.44125 & 1.00314368363459 & 0.99340486380988 \tabularnewline
42 & 118.49 & 119.115157444534 & 119.153333333333 & 0.999679607043032 & 0.994751654970316 \tabularnewline
43 & 119.32 & 119.498438656319 & 119.897916666667 & 0.996668182221564 & 0.998506769976867 \tabularnewline
44 & 119.4 & 120.240872303144 & 120.68125 & 0.996350902092448 & 0.993006768106071 \tabularnewline
45 & 122.26 & 121.972965013488 & 121.529166666667 & 1.00365178466202 & 1.00235326727099 \tabularnewline
46 & 122.91 & 122.886662359568 & 122.459166666667 & 1.00349092439985 & 1.00018991190731 \tabularnewline
47 & 123.78 & 123.567012263858 & 123.468333333333 & 1.00079922460975 & 1.00172366177866 \tabularnewline
48 & 123.99 & 124.05595398597 & 124.504166666667 & 0.996400018628319 & 0.99946835291777 \tabularnewline
49 & 124.7 & 124.939349626938 & 125.49875 & 0.995542582112873 & 0.998084273468266 \tabularnewline
50 & 125.89 & 126.456038846657 & 126.481666666667 & 0.999797379172134 & 0.995523829056964 \tabularnewline
51 & 127.57 & 127.700719983167 & 127.42125 & 1.00219327610714 & 0.998976356725443 \tabularnewline
52 & 128.97 & 128.579055067594 & 128.28625 & 1.00228243531629 & 1.00304050245353 \tabularnewline
53 & 130.65 & 129.505431580691 & 129.099583333333 & 1.00314368363459 & 1.00883799548281 \tabularnewline
54 & 130.73 & 129.834222031053 & 129.875833333333 & 0.999679607043032 & 1.00689939797793 \tabularnewline
55 & 130.95 & 130.210545223155 & 130.645833333333 & 0.996668182221564 & 1.00567891621664 \tabularnewline
56 & 131.36 & 130.922999412203 & 131.4025 & 0.996350902092448 & 1.00333784430359 \tabularnewline
57 & 132.85 & 132.588255389263 & 132.105833333333 & 1.00365178466202 & 1.00197411610831 \tabularnewline
58 & 133.08 & 133.200876577525 & 132.7375 & 1.00349092439985 & 0.999092524158772 \tabularnewline
59 & 133.13 & 133.381516659864 & 133.275 & 1.00079922460975 & 0.998114306493413 \tabularnewline
60 & 133.27 & 133.258123324677 & 133.739583333333 & 0.996400018628319 & 1.0000891253383 \tabularnewline
61 & 133.9 & 133.58978504668 & 134.187916666667 & 0.995542582112873 & 1.00232214576295 \tabularnewline
62 & 134.85 & 134.553147871227 & 134.580416666667 & 0.999797379172134 & 1.00220620723832 \tabularnewline
63 & 135.49 & 135.234707936302 & 134.93875 & 1.00219327610714 & 1.0018877702891 \tabularnewline
64 & 136.21 & 135.655586678609 & 135.346666666667 & 1.00228243531629 & 1.00408691845994 \tabularnewline
65 & 136.31 & 136.237361650949 & 135.810416666667 & 1.00314368363459 & 1.00053317495415 \tabularnewline
66 & 136.22 & 136.233004582468 & 136.276666666667 & 0.999679607043032 & 0.999904541615981 \tabularnewline
67 & 136.22 & NA & NA & 0.996668182221564 & NA \tabularnewline
68 & 135.51 & NA & NA & 0.996350902092448 & NA \tabularnewline
69 & 137.3 & NA & NA & 1.00365178466202 & NA \tabularnewline
70 & 138.42 & NA & NA & 1.00349092439985 & NA \tabularnewline
71 & 138.92 & NA & NA & 1.00079922460975 & NA \tabularnewline
72 & 138.67 & NA & NA & 0.996400018628319 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=210489&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]102.42[/C][C]NA[/C][C]NA[/C][C]0.995542582112873[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]102.46[/C][C]NA[/C][C]NA[/C][C]0.999797379172134[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]102.76[/C][C]NA[/C][C]NA[/C][C]1.00219327610714[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]102.4[/C][C]NA[/C][C]NA[/C][C]1.00228243531629[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]102.47[/C][C]NA[/C][C]NA[/C][C]1.00314368363459[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]102.27[/C][C]NA[/C][C]NA[/C][C]0.999679607043032[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]102.17[/C][C]102.339134785738[/C][C]102.68125[/C][C]0.996668182221564[/C][C]0.99834731077127[/C][/ROW]
[ROW][C]8[/C][C]101.84[/C][C]102.503750514853[/C][C]102.879166666667[/C][C]0.996350902092448[/C][C]0.993524622157543[/C][/ROW]
[ROW][C]9[/C][C]102.13[/C][C]103.512044999361[/C][C]103.135416666667[/C][C]1.00365178466202[/C][C]0.986648462028074[/C][/ROW]
[ROW][C]10[/C][C]103.34[/C][C]103.791066310676[/C][C]103.43[/C][C]1.00349092439985[/C][C]0.995654093105414[/C][/ROW]
[ROW][C]11[/C][C]103.43[/C][C]103.842093546154[/C][C]103.759166666667[/C][C]1.00079922460975[/C][C]0.996031536614095[/C][/ROW]
[ROW][C]12[/C][C]103.59[/C][C]103.727732939255[/C][C]104.1025[/C][C]0.996400018628319[/C][C]0.998672168615358[/C][/ROW]
[ROW][C]13[/C][C]104.21[/C][C]103.992718889874[/C][C]104.458333333333[/C][C]0.995542582112873[/C][C]1.00208938772296[/C][/ROW]
[ROW][C]14[/C][C]105.42[/C][C]104.847917989299[/C][C]104.869166666667[/C][C]0.999797379172134[/C][C]1.00545630301175[/C][/ROW]
[ROW][C]15[/C][C]105.95[/C][C]105.604446147663[/C][C]105.373333333333[/C][C]1.00219327610714[/C][C]1.00327215249871[/C][/ROW]
[ROW][C]16[/C][C]106.28[/C][C]106.114147133024[/C][C]105.8725[/C][C]1.00228243531629[/C][C]1.00156296659265[/C][/ROW]
[ROW][C]17[/C][C]106.49[/C][C]106.657998232843[/C][C]106.32375[/C][C]1.00314368363459[/C][C]0.998424888563194[/C][/ROW]
[ROW][C]18[/C][C]106.49[/C][C]106.726627914253[/C][C]106.760833333333[/C][C]0.999679607043032[/C][C]0.997782859639833[/C][/ROW]
[ROW][C]19[/C][C]106.49[/C][C]106.806284634137[/C][C]107.163333333333[/C][C]0.996668182221564[/C][C]0.997038707645152[/C][/ROW]
[ROW][C]20[/C][C]107.38[/C][C]107.150897180696[/C][C]107.543333333333[/C][C]0.996350902092448[/C][C]1.00213813253395[/C][/ROW]
[ROW][C]21[/C][C]108.69[/C][C]108.331246318713[/C][C]107.937083333333[/C][C]1.00365178466202[/C][C]1.0033116362405[/C][/ROW]
[ROW][C]22[/C][C]108.76[/C][C]108.716534264605[/C][C]108.338333333333[/C][C]1.00349092439985[/C][C]1.00039980795643[/C][/ROW]
[ROW][C]23[/C][C]108.84[/C][C]108.844838670172[/C][C]108.757916666667[/C][C]1.00079922460975[/C][C]0.999955545249267[/C][/ROW]
[ROW][C]24[/C][C]108.67[/C][C]108.825979701236[/C][C]109.219166666667[/C][C]0.996400018628319[/C][C]0.998566705287981[/C][/ROW]
[ROW][C]25[/C][C]108.79[/C][C]109.214754542465[/C][C]109.70375[/C][C]0.995542582112873[/C][C]0.996110831872081[/C][/ROW]
[ROW][C]26[/C][C]109.96[/C][C]110.193501309939[/C][C]110.215833333333[/C][C]0.999797379172134[/C][C]0.997880988378047[/C][/ROW]
[ROW][C]27[/C][C]110.86[/C][C]110.981213073978[/C][C]110.738333333333[/C][C]1.00219327610714[/C][C]0.998907805468868[/C][/ROW]
[ROW][C]28[/C][C]111[/C][C]111.518537547786[/C][C]111.264583333333[/C][C]1.00228243531629[/C][C]0.995350212088611[/C][/ROW]
[ROW][C]29[/C][C]111.84[/C][C]112.15856943144[/C][C]111.807083333333[/C][C]1.00314368363459[/C][C]0.997159651437651[/C][/ROW]
[ROW][C]30[/C][C]112.21[/C][C]112.319835315659[/C][C]112.355833333333[/C][C]0.999679607043032[/C][C]0.999022120043621[/C][/ROW]
[ROW][C]31[/C][C]112.4[/C][C]112.536296125092[/C][C]112.9125[/C][C]0.996668182221564[/C][C]0.99878886963775[/C][/ROW]
[ROW][C]32[/C][C]113.76[/C][C]113.041821889317[/C][C]113.455833333333[/C][C]0.996350902092448[/C][C]1.00635320714652[/C][/ROW]
[ROW][C]33[/C][C]114.85[/C][C]114.384102956712[/C][C]113.967916666667[/C][C]1.00365178466202[/C][C]1.0040730925998[/C][/ROW]
[ROW][C]34[/C][C]115.23[/C][C]114.882567873824[/C][C]114.482916666667[/C][C]1.00349092439985[/C][C]1.00302423711975[/C][/ROW]
[ROW][C]35[/C][C]115.39[/C][C]115.098165825275[/C][C]115.00625[/C][C]1.00079922460975[/C][C]1.00253552411225[/C][/ROW]
[ROW][C]36[/C][C]115.29[/C][C]115.109942485385[/C][C]115.525833333333[/C][C]0.996400018628319[/C][C]1.00156422208827[/C][/ROW]
[ROW][C]37[/C][C]115.53[/C][C]115.55843483757[/C][C]116.075833333333[/C][C]0.995542582112873[/C][C]0.999753935421416[/C][/ROW]
[ROW][C]38[/C][C]116.26[/C][C]116.575541246988[/C][C]116.599166666667[/C][C]0.999797379172134[/C][C]0.99729324656259[/C][/ROW]
[ROW][C]39[/C][C]116.85[/C][C]117.399843426912[/C][C]117.142916666667[/C][C]1.00219327610714[/C][C]0.995316489265553[/C][/ROW]
[ROW][C]40[/C][C]117.37[/C][C]118.040472877925[/C][C]117.771666666667[/C][C]1.00228243531629[/C][C]0.994319974652946[/C][/ROW]
[ROW][C]41[/C][C]118.03[/C][C]118.813591819286[/C][C]118.44125[/C][C]1.00314368363459[/C][C]0.99340486380988[/C][/ROW]
[ROW][C]42[/C][C]118.49[/C][C]119.115157444534[/C][C]119.153333333333[/C][C]0.999679607043032[/C][C]0.994751654970316[/C][/ROW]
[ROW][C]43[/C][C]119.32[/C][C]119.498438656319[/C][C]119.897916666667[/C][C]0.996668182221564[/C][C]0.998506769976867[/C][/ROW]
[ROW][C]44[/C][C]119.4[/C][C]120.240872303144[/C][C]120.68125[/C][C]0.996350902092448[/C][C]0.993006768106071[/C][/ROW]
[ROW][C]45[/C][C]122.26[/C][C]121.972965013488[/C][C]121.529166666667[/C][C]1.00365178466202[/C][C]1.00235326727099[/C][/ROW]
[ROW][C]46[/C][C]122.91[/C][C]122.886662359568[/C][C]122.459166666667[/C][C]1.00349092439985[/C][C]1.00018991190731[/C][/ROW]
[ROW][C]47[/C][C]123.78[/C][C]123.567012263858[/C][C]123.468333333333[/C][C]1.00079922460975[/C][C]1.00172366177866[/C][/ROW]
[ROW][C]48[/C][C]123.99[/C][C]124.05595398597[/C][C]124.504166666667[/C][C]0.996400018628319[/C][C]0.99946835291777[/C][/ROW]
[ROW][C]49[/C][C]124.7[/C][C]124.939349626938[/C][C]125.49875[/C][C]0.995542582112873[/C][C]0.998084273468266[/C][/ROW]
[ROW][C]50[/C][C]125.89[/C][C]126.456038846657[/C][C]126.481666666667[/C][C]0.999797379172134[/C][C]0.995523829056964[/C][/ROW]
[ROW][C]51[/C][C]127.57[/C][C]127.700719983167[/C][C]127.42125[/C][C]1.00219327610714[/C][C]0.998976356725443[/C][/ROW]
[ROW][C]52[/C][C]128.97[/C][C]128.579055067594[/C][C]128.28625[/C][C]1.00228243531629[/C][C]1.00304050245353[/C][/ROW]
[ROW][C]53[/C][C]130.65[/C][C]129.505431580691[/C][C]129.099583333333[/C][C]1.00314368363459[/C][C]1.00883799548281[/C][/ROW]
[ROW][C]54[/C][C]130.73[/C][C]129.834222031053[/C][C]129.875833333333[/C][C]0.999679607043032[/C][C]1.00689939797793[/C][/ROW]
[ROW][C]55[/C][C]130.95[/C][C]130.210545223155[/C][C]130.645833333333[/C][C]0.996668182221564[/C][C]1.00567891621664[/C][/ROW]
[ROW][C]56[/C][C]131.36[/C][C]130.922999412203[/C][C]131.4025[/C][C]0.996350902092448[/C][C]1.00333784430359[/C][/ROW]
[ROW][C]57[/C][C]132.85[/C][C]132.588255389263[/C][C]132.105833333333[/C][C]1.00365178466202[/C][C]1.00197411610831[/C][/ROW]
[ROW][C]58[/C][C]133.08[/C][C]133.200876577525[/C][C]132.7375[/C][C]1.00349092439985[/C][C]0.999092524158772[/C][/ROW]
[ROW][C]59[/C][C]133.13[/C][C]133.381516659864[/C][C]133.275[/C][C]1.00079922460975[/C][C]0.998114306493413[/C][/ROW]
[ROW][C]60[/C][C]133.27[/C][C]133.258123324677[/C][C]133.739583333333[/C][C]0.996400018628319[/C][C]1.0000891253383[/C][/ROW]
[ROW][C]61[/C][C]133.9[/C][C]133.58978504668[/C][C]134.187916666667[/C][C]0.995542582112873[/C][C]1.00232214576295[/C][/ROW]
[ROW][C]62[/C][C]134.85[/C][C]134.553147871227[/C][C]134.580416666667[/C][C]0.999797379172134[/C][C]1.00220620723832[/C][/ROW]
[ROW][C]63[/C][C]135.49[/C][C]135.234707936302[/C][C]134.93875[/C][C]1.00219327610714[/C][C]1.0018877702891[/C][/ROW]
[ROW][C]64[/C][C]136.21[/C][C]135.655586678609[/C][C]135.346666666667[/C][C]1.00228243531629[/C][C]1.00408691845994[/C][/ROW]
[ROW][C]65[/C][C]136.31[/C][C]136.237361650949[/C][C]135.810416666667[/C][C]1.00314368363459[/C][C]1.00053317495415[/C][/ROW]
[ROW][C]66[/C][C]136.22[/C][C]136.233004582468[/C][C]136.276666666667[/C][C]0.999679607043032[/C][C]0.999904541615981[/C][/ROW]
[ROW][C]67[/C][C]136.22[/C][C]NA[/C][C]NA[/C][C]0.996668182221564[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]135.51[/C][C]NA[/C][C]NA[/C][C]0.996350902092448[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]137.3[/C][C]NA[/C][C]NA[/C][C]1.00365178466202[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]138.42[/C][C]NA[/C][C]NA[/C][C]1.00349092439985[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]138.92[/C][C]NA[/C][C]NA[/C][C]1.00079922460975[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]138.67[/C][C]NA[/C][C]NA[/C][C]0.996400018628319[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=210489&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=210489&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	102.42	NA	NA	0.995542582112873	NA
2	102.46	NA	NA	0.999797379172134	NA
3	102.76	NA	NA	1.00219327610714	NA
4	102.4	NA	NA	1.00228243531629	NA
5	102.47	NA	NA	1.00314368363459	NA
6	102.27	NA	NA	0.999679607043032	NA
7	102.17	102.339134785738	102.68125	0.996668182221564	0.99834731077127
8	101.84	102.503750514853	102.879166666667	0.996350902092448	0.993524622157543
9	102.13	103.512044999361	103.135416666667	1.00365178466202	0.986648462028074
10	103.34	103.791066310676	103.43	1.00349092439985	0.995654093105414
11	103.43	103.842093546154	103.759166666667	1.00079922460975	0.996031536614095
12	103.59	103.727732939255	104.1025	0.996400018628319	0.998672168615358
13	104.21	103.992718889874	104.458333333333	0.995542582112873	1.00208938772296
14	105.42	104.847917989299	104.869166666667	0.999797379172134	1.00545630301175
15	105.95	105.604446147663	105.373333333333	1.00219327610714	1.00327215249871
16	106.28	106.114147133024	105.8725	1.00228243531629	1.00156296659265
17	106.49	106.657998232843	106.32375	1.00314368363459	0.998424888563194
18	106.49	106.726627914253	106.760833333333	0.999679607043032	0.997782859639833
19	106.49	106.806284634137	107.163333333333	0.996668182221564	0.997038707645152
20	107.38	107.150897180696	107.543333333333	0.996350902092448	1.00213813253395
21	108.69	108.331246318713	107.937083333333	1.00365178466202	1.0033116362405
22	108.76	108.716534264605	108.338333333333	1.00349092439985	1.00039980795643
23	108.84	108.844838670172	108.757916666667	1.00079922460975	0.999955545249267
24	108.67	108.825979701236	109.219166666667	0.996400018628319	0.998566705287981
25	108.79	109.214754542465	109.70375	0.995542582112873	0.996110831872081
26	109.96	110.193501309939	110.215833333333	0.999797379172134	0.997880988378047
27	110.86	110.981213073978	110.738333333333	1.00219327610714	0.998907805468868
28	111	111.518537547786	111.264583333333	1.00228243531629	0.995350212088611
29	111.84	112.15856943144	111.807083333333	1.00314368363459	0.997159651437651
30	112.21	112.319835315659	112.355833333333	0.999679607043032	0.999022120043621
31	112.4	112.536296125092	112.9125	0.996668182221564	0.99878886963775
32	113.76	113.041821889317	113.455833333333	0.996350902092448	1.00635320714652
33	114.85	114.384102956712	113.967916666667	1.00365178466202	1.0040730925998
34	115.23	114.882567873824	114.482916666667	1.00349092439985	1.00302423711975
35	115.39	115.098165825275	115.00625	1.00079922460975	1.00253552411225
36	115.29	115.109942485385	115.525833333333	0.996400018628319	1.00156422208827
37	115.53	115.55843483757	116.075833333333	0.995542582112873	0.999753935421416
38	116.26	116.575541246988	116.599166666667	0.999797379172134	0.99729324656259
39	116.85	117.399843426912	117.142916666667	1.00219327610714	0.995316489265553
40	117.37	118.040472877925	117.771666666667	1.00228243531629	0.994319974652946
41	118.03	118.813591819286	118.44125	1.00314368363459	0.99340486380988
42	118.49	119.115157444534	119.153333333333	0.999679607043032	0.994751654970316
43	119.32	119.498438656319	119.897916666667	0.996668182221564	0.998506769976867
44	119.4	120.240872303144	120.68125	0.996350902092448	0.993006768106071
45	122.26	121.972965013488	121.529166666667	1.00365178466202	1.00235326727099
46	122.91	122.886662359568	122.459166666667	1.00349092439985	1.00018991190731
47	123.78	123.567012263858	123.468333333333	1.00079922460975	1.00172366177866
48	123.99	124.05595398597	124.504166666667	0.996400018628319	0.99946835291777
49	124.7	124.939349626938	125.49875	0.995542582112873	0.998084273468266
50	125.89	126.456038846657	126.481666666667	0.999797379172134	0.995523829056964
51	127.57	127.700719983167	127.42125	1.00219327610714	0.998976356725443
52	128.97	128.579055067594	128.28625	1.00228243531629	1.00304050245353
53	130.65	129.505431580691	129.099583333333	1.00314368363459	1.00883799548281
54	130.73	129.834222031053	129.875833333333	0.999679607043032	1.00689939797793
55	130.95	130.210545223155	130.645833333333	0.996668182221564	1.00567891621664
56	131.36	130.922999412203	131.4025	0.996350902092448	1.00333784430359
57	132.85	132.588255389263	132.105833333333	1.00365178466202	1.00197411610831
58	133.08	133.200876577525	132.7375	1.00349092439985	0.999092524158772
59	133.13	133.381516659864	133.275	1.00079922460975	0.998114306493413
60	133.27	133.258123324677	133.739583333333	0.996400018628319	1.0000891253383
61	133.9	133.58978504668	134.187916666667	0.995542582112873	1.00232214576295
62	134.85	134.553147871227	134.580416666667	0.999797379172134	1.00220620723832
63	135.49	135.234707936302	134.93875	1.00219327610714	1.0018877702891
64	136.21	135.655586678609	135.346666666667	1.00228243531629	1.00408691845994
65	136.31	136.237361650949	135.810416666667	1.00314368363459	1.00053317495415
66	136.22	136.233004582468	136.276666666667	0.999679607043032	0.999904541615981
67	136.22	NA	NA	0.996668182221564	NA
68	135.51	NA	NA	0.996350902092448	NA
69	137.3	NA	NA	1.00365178466202	NA
70	138.42	NA	NA	1.00349092439985	NA
71	138.92	NA	NA	1.00079922460975	NA
72	138.67	NA	NA	0.996400018628319	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