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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Mon, 14 Dec 2009 05:12:34 -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/14/t12607928495jlibbv8dsn89mx.htm/, Retrieved Fri, 17 Apr 2026 13:45:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67528, Retrieved Fri, 17 Apr 2026 13:45:08 +0000

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Estimated Impact

342

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]
-    D      [Classical Decomposition] [] [2009-12-14 12:12:34] [9adf7044e3e2072a25a3bb76b79e4d2e] [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	1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67528&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]1 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=67528&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67528&T=0

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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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	95.1	NA	NA	0.965174011311693	NA
2	97	NA	NA	0.974505675453896	NA
3	112.7	NA	NA	1.05513816877183	NA
4	102.9	NA	NA	1.00231085470890	NA
5	97.4	NA	NA	1.00104366051728	NA
6	111.4	NA	NA	1.08588163191988	NA
7	87.4	84.4747140159778	102.529166666667	0.823909105694911	1.03462913154662
8	96.8	96.5718598066724	102.4625	0.942509306396705	1.00236238790248
9	114.1	110.092737041569	102.083333333333	1.07845946489700	1.03639897659114
10	110.3	109.555392550455	101.745833333333	1.07675556788195	1.00679662983455
11	103.9	105.470068464427	101.770833333333	1.03634867682549	0.985113611024565
12	101.6	97.6205104418725	101.904166666667	0.957963875620452	1.04076489192809
13	94.6	98.1943909758234	101.7375	0.965174011311693	0.963395149762593
14	95.9	98.835177692597	101.420833333333	0.974505675453896	0.970302297611826
15	104.7	106.925064177916	101.3375	1.05513816877183	0.979190434020097
16	102.8	101.350332591982	101.116666666667	1.00231085470890	1.01430352886807
17	98.1	101.243053215567	101.1375	1.00104366051728	0.968955369126665
18	113.9	110.076725929078	101.370833333333	1.08588163191988	1.03473281057964
19	80.9	83.6954333201747	101.583333333333	0.823909105694911	0.966599930136202
20	95.7	96.104532275584	101.966666666667	0.942509306396705	0.995790705536925
21	113.2	110.667915422848	102.616666666667	1.07845946489700	1.02288002414681
22	105.9	110.883391084176	102.979166666667	1.07675556788195	0.95505737121267
23	108.8	107.141180705808	103.383333333333	1.03634867682549	1.01548255566407
24	102.3	99.5364381931134	103.904166666667	0.957963875620452	1.02776432286561
25	99	100.494722369450	104.120833333333	0.965174011311693	0.98512635953205
26	100.7	101.843963965561	104.508333333333	0.974505675453896	0.988767483893814
27	115.5	110.552101633069	104.775	1.05513816877183	1.04475625785346
28	100.7	105.526627819935	105.283333333333	1.00231085470890	0.954261517498964
29	109.9	106.006352633528	105.895833333333	1.00104366051728	1.03673032105852
30	114.6	115.162271571903	106.054166666667	1.08588163191988	0.995117571369265
31	85.4	87.6090015722255	106.333333333333	0.823909105694911	0.974785678040123
32	100.5	100.675702411608	106.816666666667	0.942509306396705	0.998254768455553
33	114.8	115.552438082610	107.145833333333	1.07845946489700	0.993488340920402
34	116.5	115.760196510375	107.508333333333	1.07675556788195	1.00639082786594
35	112.9	111.623388733079	107.708333333333	1.03634867682549	1.01143677218019
36	102	103.260522759588	107.791666666667	0.957963875620452	0.987792791224555
37	106	104.427806465545	108.195833333333	0.965174011311693	1.01505531512791
38	105.3	105.875981197751	108.645833333333	0.974505675453896	0.99455985020176
39	118.8	114.697915354535	108.704166666667	1.05513816877183	1.03576424761327
40	106.1	109.105712830292	108.854166666667	1.00231085470890	0.972451370763994
41	109.3	109.230547423444	109.116666666667	1.00104366051728	1.00063583473849
42	117.2	118.415391960863	109.05	1.08588163191988	0.989736199486087
43	92.5	89.9399777504207	109.1625	0.823909105694911	1.0284636744817
44	104.2	103.365781056949	109.670833333333	0.942509306396705	1.00807055230968
45	112.5	118.208144514919	109.608333333333	1.07845946489700	0.951711072546285
46	122.4	118.120085796650	109.7	1.07675556788195	1.03623358529148
47	113.3	114.162442991301	110.158333333333	1.03634867682549	0.992445475335818
48	100	105.467831189663	110.095833333333	0.957963875620452	0.948156408186392
49	110.7	106.350111371407	110.1875	0.965174011311693	1.04090158978209
50	112.8	107.341800151247	110.15	0.974505675453896	1.05084878249724
51	109.8	116.219072881181	110.145833333333	1.05513816877183	0.944767474717824
52	117.3	110.300133265487	110.045833333333	1.00231085470890	1.06346199707361
53	109.1	109.301454682731	109.1875	1.00104366051728	0.998156889280974
54	115.9	117.677897352518	108.370833333333	1.08588163191988	0.984891832769652
55	96	NA	NA	0.823909105694911	NA
56	99.8	NA	NA	0.942509306396705	NA
57	116.8	NA	NA	1.07845946489700	NA
58	115.7	NA	NA	1.07675556788195	NA
59	99.4	NA	NA	1.03634867682549	NA
60	94.3	NA	NA	0.957963875620452	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 95.1 & NA & NA & 0.965174011311693 & NA \tabularnewline
2 & 97 & NA & NA & 0.974505675453896 & NA \tabularnewline
3 & 112.7 & NA & NA & 1.05513816877183 & NA \tabularnewline
4 & 102.9 & NA & NA & 1.00231085470890 & NA \tabularnewline
5 & 97.4 & NA & NA & 1.00104366051728 & NA \tabularnewline
6 & 111.4 & NA & NA & 1.08588163191988 & NA \tabularnewline
7 & 87.4 & 84.4747140159778 & 102.529166666667 & 0.823909105694911 & 1.03462913154662 \tabularnewline
8 & 96.8 & 96.5718598066724 & 102.4625 & 0.942509306396705 & 1.00236238790248 \tabularnewline
9 & 114.1 & 110.092737041569 & 102.083333333333 & 1.07845946489700 & 1.03639897659114 \tabularnewline
10 & 110.3 & 109.555392550455 & 101.745833333333 & 1.07675556788195 & 1.00679662983455 \tabularnewline
11 & 103.9 & 105.470068464427 & 101.770833333333 & 1.03634867682549 & 0.985113611024565 \tabularnewline
12 & 101.6 & 97.6205104418725 & 101.904166666667 & 0.957963875620452 & 1.04076489192809 \tabularnewline
13 & 94.6 & 98.1943909758234 & 101.7375 & 0.965174011311693 & 0.963395149762593 \tabularnewline
14 & 95.9 & 98.835177692597 & 101.420833333333 & 0.974505675453896 & 0.970302297611826 \tabularnewline
15 & 104.7 & 106.925064177916 & 101.3375 & 1.05513816877183 & 0.979190434020097 \tabularnewline
16 & 102.8 & 101.350332591982 & 101.116666666667 & 1.00231085470890 & 1.01430352886807 \tabularnewline
17 & 98.1 & 101.243053215567 & 101.1375 & 1.00104366051728 & 0.968955369126665 \tabularnewline
18 & 113.9 & 110.076725929078 & 101.370833333333 & 1.08588163191988 & 1.03473281057964 \tabularnewline
19 & 80.9 & 83.6954333201747 & 101.583333333333 & 0.823909105694911 & 0.966599930136202 \tabularnewline
20 & 95.7 & 96.104532275584 & 101.966666666667 & 0.942509306396705 & 0.995790705536925 \tabularnewline
21 & 113.2 & 110.667915422848 & 102.616666666667 & 1.07845946489700 & 1.02288002414681 \tabularnewline
22 & 105.9 & 110.883391084176 & 102.979166666667 & 1.07675556788195 & 0.95505737121267 \tabularnewline
23 & 108.8 & 107.141180705808 & 103.383333333333 & 1.03634867682549 & 1.01548255566407 \tabularnewline
24 & 102.3 & 99.5364381931134 & 103.904166666667 & 0.957963875620452 & 1.02776432286561 \tabularnewline
25 & 99 & 100.494722369450 & 104.120833333333 & 0.965174011311693 & 0.98512635953205 \tabularnewline
26 & 100.7 & 101.843963965561 & 104.508333333333 & 0.974505675453896 & 0.988767483893814 \tabularnewline
27 & 115.5 & 110.552101633069 & 104.775 & 1.05513816877183 & 1.04475625785346 \tabularnewline
28 & 100.7 & 105.526627819935 & 105.283333333333 & 1.00231085470890 & 0.954261517498964 \tabularnewline
29 & 109.9 & 106.006352633528 & 105.895833333333 & 1.00104366051728 & 1.03673032105852 \tabularnewline
30 & 114.6 & 115.162271571903 & 106.054166666667 & 1.08588163191988 & 0.995117571369265 \tabularnewline
31 & 85.4 & 87.6090015722255 & 106.333333333333 & 0.823909105694911 & 0.974785678040123 \tabularnewline
32 & 100.5 & 100.675702411608 & 106.816666666667 & 0.942509306396705 & 0.998254768455553 \tabularnewline
33 & 114.8 & 115.552438082610 & 107.145833333333 & 1.07845946489700 & 0.993488340920402 \tabularnewline
34 & 116.5 & 115.760196510375 & 107.508333333333 & 1.07675556788195 & 1.00639082786594 \tabularnewline
35 & 112.9 & 111.623388733079 & 107.708333333333 & 1.03634867682549 & 1.01143677218019 \tabularnewline
36 & 102 & 103.260522759588 & 107.791666666667 & 0.957963875620452 & 0.987792791224555 \tabularnewline
37 & 106 & 104.427806465545 & 108.195833333333 & 0.965174011311693 & 1.01505531512791 \tabularnewline
38 & 105.3 & 105.875981197751 & 108.645833333333 & 0.974505675453896 & 0.99455985020176 \tabularnewline
39 & 118.8 & 114.697915354535 & 108.704166666667 & 1.05513816877183 & 1.03576424761327 \tabularnewline
40 & 106.1 & 109.105712830292 & 108.854166666667 & 1.00231085470890 & 0.972451370763994 \tabularnewline
41 & 109.3 & 109.230547423444 & 109.116666666667 & 1.00104366051728 & 1.00063583473849 \tabularnewline
42 & 117.2 & 118.415391960863 & 109.05 & 1.08588163191988 & 0.989736199486087 \tabularnewline
43 & 92.5 & 89.9399777504207 & 109.1625 & 0.823909105694911 & 1.0284636744817 \tabularnewline
44 & 104.2 & 103.365781056949 & 109.670833333333 & 0.942509306396705 & 1.00807055230968 \tabularnewline
45 & 112.5 & 118.208144514919 & 109.608333333333 & 1.07845946489700 & 0.951711072546285 \tabularnewline
46 & 122.4 & 118.120085796650 & 109.7 & 1.07675556788195 & 1.03623358529148 \tabularnewline
47 & 113.3 & 114.162442991301 & 110.158333333333 & 1.03634867682549 & 0.992445475335818 \tabularnewline
48 & 100 & 105.467831189663 & 110.095833333333 & 0.957963875620452 & 0.948156408186392 \tabularnewline
49 & 110.7 & 106.350111371407 & 110.1875 & 0.965174011311693 & 1.04090158978209 \tabularnewline
50 & 112.8 & 107.341800151247 & 110.15 & 0.974505675453896 & 1.05084878249724 \tabularnewline
51 & 109.8 & 116.219072881181 & 110.145833333333 & 1.05513816877183 & 0.944767474717824 \tabularnewline
52 & 117.3 & 110.300133265487 & 110.045833333333 & 1.00231085470890 & 1.06346199707361 \tabularnewline
53 & 109.1 & 109.301454682731 & 109.1875 & 1.00104366051728 & 0.998156889280974 \tabularnewline
54 & 115.9 & 117.677897352518 & 108.370833333333 & 1.08588163191988 & 0.984891832769652 \tabularnewline
55 & 96 & NA & NA & 0.823909105694911 & NA \tabularnewline
56 & 99.8 & NA & NA & 0.942509306396705 & NA \tabularnewline
57 & 116.8 & NA & NA & 1.07845946489700 & NA \tabularnewline
58 & 115.7 & NA & NA & 1.07675556788195 & NA \tabularnewline
59 & 99.4 & NA & NA & 1.03634867682549 & NA \tabularnewline
60 & 94.3 & NA & NA & 0.957963875620452 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67528&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]95.1[/C][C]NA[/C][C]NA[/C][C]0.965174011311693[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]97[/C][C]NA[/C][C]NA[/C][C]0.974505675453896[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]112.7[/C][C]NA[/C][C]NA[/C][C]1.05513816877183[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]102.9[/C][C]NA[/C][C]NA[/C][C]1.00231085470890[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]97.4[/C][C]NA[/C][C]NA[/C][C]1.00104366051728[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]111.4[/C][C]NA[/C][C]NA[/C][C]1.08588163191988[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]87.4[/C][C]84.4747140159778[/C][C]102.529166666667[/C][C]0.823909105694911[/C][C]1.03462913154662[/C][/ROW]
[ROW][C]8[/C][C]96.8[/C][C]96.5718598066724[/C][C]102.4625[/C][C]0.942509306396705[/C][C]1.00236238790248[/C][/ROW]
[ROW][C]9[/C][C]114.1[/C][C]110.092737041569[/C][C]102.083333333333[/C][C]1.07845946489700[/C][C]1.03639897659114[/C][/ROW]
[ROW][C]10[/C][C]110.3[/C][C]109.555392550455[/C][C]101.745833333333[/C][C]1.07675556788195[/C][C]1.00679662983455[/C][/ROW]
[ROW][C]11[/C][C]103.9[/C][C]105.470068464427[/C][C]101.770833333333[/C][C]1.03634867682549[/C][C]0.985113611024565[/C][/ROW]
[ROW][C]12[/C][C]101.6[/C][C]97.6205104418725[/C][C]101.904166666667[/C][C]0.957963875620452[/C][C]1.04076489192809[/C][/ROW]
[ROW][C]13[/C][C]94.6[/C][C]98.1943909758234[/C][C]101.7375[/C][C]0.965174011311693[/C][C]0.963395149762593[/C][/ROW]
[ROW][C]14[/C][C]95.9[/C][C]98.835177692597[/C][C]101.420833333333[/C][C]0.974505675453896[/C][C]0.970302297611826[/C][/ROW]
[ROW][C]15[/C][C]104.7[/C][C]106.925064177916[/C][C]101.3375[/C][C]1.05513816877183[/C][C]0.979190434020097[/C][/ROW]
[ROW][C]16[/C][C]102.8[/C][C]101.350332591982[/C][C]101.116666666667[/C][C]1.00231085470890[/C][C]1.01430352886807[/C][/ROW]
[ROW][C]17[/C][C]98.1[/C][C]101.243053215567[/C][C]101.1375[/C][C]1.00104366051728[/C][C]0.968955369126665[/C][/ROW]
[ROW][C]18[/C][C]113.9[/C][C]110.076725929078[/C][C]101.370833333333[/C][C]1.08588163191988[/C][C]1.03473281057964[/C][/ROW]
[ROW][C]19[/C][C]80.9[/C][C]83.6954333201747[/C][C]101.583333333333[/C][C]0.823909105694911[/C][C]0.966599930136202[/C][/ROW]
[ROW][C]20[/C][C]95.7[/C][C]96.104532275584[/C][C]101.966666666667[/C][C]0.942509306396705[/C][C]0.995790705536925[/C][/ROW]
[ROW][C]21[/C][C]113.2[/C][C]110.667915422848[/C][C]102.616666666667[/C][C]1.07845946489700[/C][C]1.02288002414681[/C][/ROW]
[ROW][C]22[/C][C]105.9[/C][C]110.883391084176[/C][C]102.979166666667[/C][C]1.07675556788195[/C][C]0.95505737121267[/C][/ROW]
[ROW][C]23[/C][C]108.8[/C][C]107.141180705808[/C][C]103.383333333333[/C][C]1.03634867682549[/C][C]1.01548255566407[/C][/ROW]
[ROW][C]24[/C][C]102.3[/C][C]99.5364381931134[/C][C]103.904166666667[/C][C]0.957963875620452[/C][C]1.02776432286561[/C][/ROW]
[ROW][C]25[/C][C]99[/C][C]100.494722369450[/C][C]104.120833333333[/C][C]0.965174011311693[/C][C]0.98512635953205[/C][/ROW]
[ROW][C]26[/C][C]100.7[/C][C]101.843963965561[/C][C]104.508333333333[/C][C]0.974505675453896[/C][C]0.988767483893814[/C][/ROW]
[ROW][C]27[/C][C]115.5[/C][C]110.552101633069[/C][C]104.775[/C][C]1.05513816877183[/C][C]1.04475625785346[/C][/ROW]
[ROW][C]28[/C][C]100.7[/C][C]105.526627819935[/C][C]105.283333333333[/C][C]1.00231085470890[/C][C]0.954261517498964[/C][/ROW]
[ROW][C]29[/C][C]109.9[/C][C]106.006352633528[/C][C]105.895833333333[/C][C]1.00104366051728[/C][C]1.03673032105852[/C][/ROW]
[ROW][C]30[/C][C]114.6[/C][C]115.162271571903[/C][C]106.054166666667[/C][C]1.08588163191988[/C][C]0.995117571369265[/C][/ROW]
[ROW][C]31[/C][C]85.4[/C][C]87.6090015722255[/C][C]106.333333333333[/C][C]0.823909105694911[/C][C]0.974785678040123[/C][/ROW]
[ROW][C]32[/C][C]100.5[/C][C]100.675702411608[/C][C]106.816666666667[/C][C]0.942509306396705[/C][C]0.998254768455553[/C][/ROW]
[ROW][C]33[/C][C]114.8[/C][C]115.552438082610[/C][C]107.145833333333[/C][C]1.07845946489700[/C][C]0.993488340920402[/C][/ROW]
[ROW][C]34[/C][C]116.5[/C][C]115.760196510375[/C][C]107.508333333333[/C][C]1.07675556788195[/C][C]1.00639082786594[/C][/ROW]
[ROW][C]35[/C][C]112.9[/C][C]111.623388733079[/C][C]107.708333333333[/C][C]1.03634867682549[/C][C]1.01143677218019[/C][/ROW]
[ROW][C]36[/C][C]102[/C][C]103.260522759588[/C][C]107.791666666667[/C][C]0.957963875620452[/C][C]0.987792791224555[/C][/ROW]
[ROW][C]37[/C][C]106[/C][C]104.427806465545[/C][C]108.195833333333[/C][C]0.965174011311693[/C][C]1.01505531512791[/C][/ROW]
[ROW][C]38[/C][C]105.3[/C][C]105.875981197751[/C][C]108.645833333333[/C][C]0.974505675453896[/C][C]0.99455985020176[/C][/ROW]
[ROW][C]39[/C][C]118.8[/C][C]114.697915354535[/C][C]108.704166666667[/C][C]1.05513816877183[/C][C]1.03576424761327[/C][/ROW]
[ROW][C]40[/C][C]106.1[/C][C]109.105712830292[/C][C]108.854166666667[/C][C]1.00231085470890[/C][C]0.972451370763994[/C][/ROW]
[ROW][C]41[/C][C]109.3[/C][C]109.230547423444[/C][C]109.116666666667[/C][C]1.00104366051728[/C][C]1.00063583473849[/C][/ROW]
[ROW][C]42[/C][C]117.2[/C][C]118.415391960863[/C][C]109.05[/C][C]1.08588163191988[/C][C]0.989736199486087[/C][/ROW]
[ROW][C]43[/C][C]92.5[/C][C]89.9399777504207[/C][C]109.1625[/C][C]0.823909105694911[/C][C]1.0284636744817[/C][/ROW]
[ROW][C]44[/C][C]104.2[/C][C]103.365781056949[/C][C]109.670833333333[/C][C]0.942509306396705[/C][C]1.00807055230968[/C][/ROW]
[ROW][C]45[/C][C]112.5[/C][C]118.208144514919[/C][C]109.608333333333[/C][C]1.07845946489700[/C][C]0.951711072546285[/C][/ROW]
[ROW][C]46[/C][C]122.4[/C][C]118.120085796650[/C][C]109.7[/C][C]1.07675556788195[/C][C]1.03623358529148[/C][/ROW]
[ROW][C]47[/C][C]113.3[/C][C]114.162442991301[/C][C]110.158333333333[/C][C]1.03634867682549[/C][C]0.992445475335818[/C][/ROW]
[ROW][C]48[/C][C]100[/C][C]105.467831189663[/C][C]110.095833333333[/C][C]0.957963875620452[/C][C]0.948156408186392[/C][/ROW]
[ROW][C]49[/C][C]110.7[/C][C]106.350111371407[/C][C]110.1875[/C][C]0.965174011311693[/C][C]1.04090158978209[/C][/ROW]
[ROW][C]50[/C][C]112.8[/C][C]107.341800151247[/C][C]110.15[/C][C]0.974505675453896[/C][C]1.05084878249724[/C][/ROW]
[ROW][C]51[/C][C]109.8[/C][C]116.219072881181[/C][C]110.145833333333[/C][C]1.05513816877183[/C][C]0.944767474717824[/C][/ROW]
[ROW][C]52[/C][C]117.3[/C][C]110.300133265487[/C][C]110.045833333333[/C][C]1.00231085470890[/C][C]1.06346199707361[/C][/ROW]
[ROW][C]53[/C][C]109.1[/C][C]109.301454682731[/C][C]109.1875[/C][C]1.00104366051728[/C][C]0.998156889280974[/C][/ROW]
[ROW][C]54[/C][C]115.9[/C][C]117.677897352518[/C][C]108.370833333333[/C][C]1.08588163191988[/C][C]0.984891832769652[/C][/ROW]
[ROW][C]55[/C][C]96[/C][C]NA[/C][C]NA[/C][C]0.823909105694911[/C][C]NA[/C][/ROW]
[ROW][C]56[/C][C]99.8[/C][C]NA[/C][C]NA[/C][C]0.942509306396705[/C][C]NA[/C][/ROW]
[ROW][C]57[/C][C]116.8[/C][C]NA[/C][C]NA[/C][C]1.07845946489700[/C][C]NA[/C][/ROW]
[ROW][C]58[/C][C]115.7[/C][C]NA[/C][C]NA[/C][C]1.07675556788195[/C][C]NA[/C][/ROW]
[ROW][C]59[/C][C]99.4[/C][C]NA[/C][C]NA[/C][C]1.03634867682549[/C][C]NA[/C][/ROW]
[ROW][C]60[/C][C]94.3[/C][C]NA[/C][C]NA[/C][C]0.957963875620452[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67528&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67528&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	95.1	NA	NA	0.965174011311693	NA
2	97	NA	NA	0.974505675453896	NA
3	112.7	NA	NA	1.05513816877183	NA
4	102.9	NA	NA	1.00231085470890	NA
5	97.4	NA	NA	1.00104366051728	NA
6	111.4	NA	NA	1.08588163191988	NA
7	87.4	84.4747140159778	102.529166666667	0.823909105694911	1.03462913154662
8	96.8	96.5718598066724	102.4625	0.942509306396705	1.00236238790248
9	114.1	110.092737041569	102.083333333333	1.07845946489700	1.03639897659114
10	110.3	109.555392550455	101.745833333333	1.07675556788195	1.00679662983455
11	103.9	105.470068464427	101.770833333333	1.03634867682549	0.985113611024565
12	101.6	97.6205104418725	101.904166666667	0.957963875620452	1.04076489192809
13	94.6	98.1943909758234	101.7375	0.965174011311693	0.963395149762593
14	95.9	98.835177692597	101.420833333333	0.974505675453896	0.970302297611826
15	104.7	106.925064177916	101.3375	1.05513816877183	0.979190434020097
16	102.8	101.350332591982	101.116666666667	1.00231085470890	1.01430352886807
17	98.1	101.243053215567	101.1375	1.00104366051728	0.968955369126665
18	113.9	110.076725929078	101.370833333333	1.08588163191988	1.03473281057964
19	80.9	83.6954333201747	101.583333333333	0.823909105694911	0.966599930136202
20	95.7	96.104532275584	101.966666666667	0.942509306396705	0.995790705536925
21	113.2	110.667915422848	102.616666666667	1.07845946489700	1.02288002414681
22	105.9	110.883391084176	102.979166666667	1.07675556788195	0.95505737121267
23	108.8	107.141180705808	103.383333333333	1.03634867682549	1.01548255566407
24	102.3	99.5364381931134	103.904166666667	0.957963875620452	1.02776432286561
25	99	100.494722369450	104.120833333333	0.965174011311693	0.98512635953205
26	100.7	101.843963965561	104.508333333333	0.974505675453896	0.988767483893814
27	115.5	110.552101633069	104.775	1.05513816877183	1.04475625785346
28	100.7	105.526627819935	105.283333333333	1.00231085470890	0.954261517498964
29	109.9	106.006352633528	105.895833333333	1.00104366051728	1.03673032105852
30	114.6	115.162271571903	106.054166666667	1.08588163191988	0.995117571369265
31	85.4	87.6090015722255	106.333333333333	0.823909105694911	0.974785678040123
32	100.5	100.675702411608	106.816666666667	0.942509306396705	0.998254768455553
33	114.8	115.552438082610	107.145833333333	1.07845946489700	0.993488340920402
34	116.5	115.760196510375	107.508333333333	1.07675556788195	1.00639082786594
35	112.9	111.623388733079	107.708333333333	1.03634867682549	1.01143677218019
36	102	103.260522759588	107.791666666667	0.957963875620452	0.987792791224555
37	106	104.427806465545	108.195833333333	0.965174011311693	1.01505531512791
38	105.3	105.875981197751	108.645833333333	0.974505675453896	0.99455985020176
39	118.8	114.697915354535	108.704166666667	1.05513816877183	1.03576424761327
40	106.1	109.105712830292	108.854166666667	1.00231085470890	0.972451370763994
41	109.3	109.230547423444	109.116666666667	1.00104366051728	1.00063583473849
42	117.2	118.415391960863	109.05	1.08588163191988	0.989736199486087
43	92.5	89.9399777504207	109.1625	0.823909105694911	1.0284636744817
44	104.2	103.365781056949	109.670833333333	0.942509306396705	1.00807055230968
45	112.5	118.208144514919	109.608333333333	1.07845946489700	0.951711072546285
46	122.4	118.120085796650	109.7	1.07675556788195	1.03623358529148
47	113.3	114.162442991301	110.158333333333	1.03634867682549	0.992445475335818
48	100	105.467831189663	110.095833333333	0.957963875620452	0.948156408186392
49	110.7	106.350111371407	110.1875	0.965174011311693	1.04090158978209
50	112.8	107.341800151247	110.15	0.974505675453896	1.05084878249724
51	109.8	116.219072881181	110.145833333333	1.05513816877183	0.944767474717824
52	117.3	110.300133265487	110.045833333333	1.00231085470890	1.06346199707361
53	109.1	109.301454682731	109.1875	1.00104366051728	0.998156889280974
54	115.9	117.677897352518	108.370833333333	1.08588163191988	0.984891832769652
55	96	NA	NA	0.823909105694911	NA
56	99.8	NA	NA	0.942509306396705	NA
57	116.8	NA	NA	1.07845946489700	NA
58	115.7	NA	NA	1.07675556788195	NA
59	99.4	NA	NA	1.03634867682549	NA
60	94.3	NA	NA	0.957963875620452	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