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rwasp_decompose.wasp

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Classical Decomposition

Date of computation

Sun, 30 Apr 2017 13:41:43 +0100

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Apr/30/t1493556346frxlm8rczwzhi52.htm/, Retrieved Mon, 13 May 2024 09:36:49 +0200

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Mon, 13 May 2024 09:36:49 +0200

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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' @ yule.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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=0

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

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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' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	101.03	NA	NA	-0.111215	NA
2	100.65	NA	NA	-0.509715	NA
3	100.66	NA	NA	-0.427799	NA
4	100.54	NA	NA	-0.309549	NA
5	100.51	NA	NA	-0.156215	NA
6	100.53	NA	NA	-0.113382	NA
7	100.53	100.588	100.917	-0.329715	-0.0577847
8	101.02	101.005	100.949	0.0557014	0.0151319
9	101.07	101.205	100.982	0.223368	-0.135451
10	101.37	101.496	101.033	0.463035	-0.125951
11	101.45	101.711	101.108	0.603118	-0.260618
12	101.44	101.807	101.195	0.612368	-0.366951
13	101.45	101.173	101.284	-0.111215	0.277049
14	100.99	100.862	101.372	-0.509715	0.128049
15	101.11	101.04	101.468	-0.427799	0.0698819
16	101.31	101.269	101.579	-0.309549	0.0407986
17	101.53	101.543	101.699	-0.156215	-0.0125347
18	101.6	101.714	101.827	-0.113382	-0.113701
19	101.61	101.628	101.958	-0.329715	-0.0182014
20	102.04	102.135	102.08	0.0557014	-0.0952847
21	102.36	102.412	102.189	0.223368	-0.0521181
22	102.74	102.756	102.293	0.463035	-0.0159514
23	102.96	102.996	102.393	0.603118	-0.0364514
24	103.01	103.104	102.492	0.612368	-0.0940347
25	103.02	102.478	102.59	-0.111215	0.541632
26	102.34	102.18	102.69	-0.509715	0.160132
27	102.38	102.356	102.784	-0.427799	0.0236319
28	102.54	102.56	102.869	-0.309549	-0.0196181
29	102.71	102.793	102.95	-0.156215	-0.0833681
30	102.78	102.913	103.026	-0.113382	-0.132868
31	102.78	102.595	102.925	-0.329715	0.184715
32	103.27	102.705	102.649	0.0557014	0.565132
33	103.4	102.6	102.377	0.223368	0.799965
34	103.74	102.572	102.109	0.463035	1.16822
35	103.89	102.451	101.848	0.603118	1.43855
36	103.92	102.204	101.591	0.612368	1.71638
37	99.68	101.225	101.337	-0.111215	-1.54545
38	99.06	100.572	101.081	-0.509715	-1.51153
39	99.12	100.401	100.829	-0.427799	-1.28137
40	99.37	100.276	100.585	-0.309549	-0.905868
41	99.63	100.191	100.348	-0.156215	-0.561285
42	99.69	100.002	100.115	-0.113382	-0.311618
43	99.76	99.7349	100.065	-0.329715	0.0251319
44	100.16	100.27	100.215	0.0557014	-0.110285
45	100.46	100.608	100.385	0.223368	-0.148368
46	100.83	101.008	100.545	0.463035	-0.177618
47	101.09	101.288	100.685	0.603118	-0.198118
48	101.14	101.426	100.813	0.612368	-0.285701
49	101.25	100.809	100.92	-0.111215	0.441215
50	101.09	100.492	101.002	-0.509715	0.598049
51	101.18	100.641	101.068	-0.427799	0.539465
52	101.14	100.8	101.11	-0.309549	0.339965
53	101.23	100.97	101.126	-0.156215	0.260382
54	101.17	101.022	101.136	-0.113382	0.147549
55	100.84	100.836	101.166	-0.329715	0.00388194
56	101.04	101.277	101.221	0.0557014	-0.236951
57	101.18	101.506	101.283	0.223368	-0.326285
58	101.1	101.811	101.348	0.463035	-0.710951
59	101.21	102.016	101.412	0.603118	-0.805618
60	101.26	102.092	101.48	0.612368	-0.831951
61	101.85	101.427	101.538	-0.111215	0.423299
62	101.82	101.057	101.567	-0.509715	0.763049
63	101.93	101.144	101.572	-0.427799	0.786132
64	101.95	101.268	101.577	-0.309549	0.682465
65	101.97	101.435	101.592	-0.156215	0.534549
66	102.04	101.492	101.605	-0.113382	0.548382
67	101.37	NA	NA	-0.329715	NA
68	101.2	NA	NA	0.0557014	NA
69	101.14	NA	NA	0.223368	NA
70	101.27	NA	NA	0.463035	NA
71	101.39	NA	NA	0.603118	NA
72	101.4	NA	NA	0.612368	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 101.03 & NA & NA & -0.111215 & NA \tabularnewline
2 & 100.65 & NA & NA & -0.509715 & NA \tabularnewline
3 & 100.66 & NA & NA & -0.427799 & NA \tabularnewline
4 & 100.54 & NA & NA & -0.309549 & NA \tabularnewline
5 & 100.51 & NA & NA & -0.156215 & NA \tabularnewline
6 & 100.53 & NA & NA & -0.113382 & NA \tabularnewline
7 & 100.53 & 100.588 & 100.917 & -0.329715 & -0.0577847 \tabularnewline
8 & 101.02 & 101.005 & 100.949 & 0.0557014 & 0.0151319 \tabularnewline
9 & 101.07 & 101.205 & 100.982 & 0.223368 & -0.135451 \tabularnewline
10 & 101.37 & 101.496 & 101.033 & 0.463035 & -0.125951 \tabularnewline
11 & 101.45 & 101.711 & 101.108 & 0.603118 & -0.260618 \tabularnewline
12 & 101.44 & 101.807 & 101.195 & 0.612368 & -0.366951 \tabularnewline
13 & 101.45 & 101.173 & 101.284 & -0.111215 & 0.277049 \tabularnewline
14 & 100.99 & 100.862 & 101.372 & -0.509715 & 0.128049 \tabularnewline
15 & 101.11 & 101.04 & 101.468 & -0.427799 & 0.0698819 \tabularnewline
16 & 101.31 & 101.269 & 101.579 & -0.309549 & 0.0407986 \tabularnewline
17 & 101.53 & 101.543 & 101.699 & -0.156215 & -0.0125347 \tabularnewline
18 & 101.6 & 101.714 & 101.827 & -0.113382 & -0.113701 \tabularnewline
19 & 101.61 & 101.628 & 101.958 & -0.329715 & -0.0182014 \tabularnewline
20 & 102.04 & 102.135 & 102.08 & 0.0557014 & -0.0952847 \tabularnewline
21 & 102.36 & 102.412 & 102.189 & 0.223368 & -0.0521181 \tabularnewline
22 & 102.74 & 102.756 & 102.293 & 0.463035 & -0.0159514 \tabularnewline
23 & 102.96 & 102.996 & 102.393 & 0.603118 & -0.0364514 \tabularnewline
24 & 103.01 & 103.104 & 102.492 & 0.612368 & -0.0940347 \tabularnewline
25 & 103.02 & 102.478 & 102.59 & -0.111215 & 0.541632 \tabularnewline
26 & 102.34 & 102.18 & 102.69 & -0.509715 & 0.160132 \tabularnewline
27 & 102.38 & 102.356 & 102.784 & -0.427799 & 0.0236319 \tabularnewline
28 & 102.54 & 102.56 & 102.869 & -0.309549 & -0.0196181 \tabularnewline
29 & 102.71 & 102.793 & 102.95 & -0.156215 & -0.0833681 \tabularnewline
30 & 102.78 & 102.913 & 103.026 & -0.113382 & -0.132868 \tabularnewline
31 & 102.78 & 102.595 & 102.925 & -0.329715 & 0.184715 \tabularnewline
32 & 103.27 & 102.705 & 102.649 & 0.0557014 & 0.565132 \tabularnewline
33 & 103.4 & 102.6 & 102.377 & 0.223368 & 0.799965 \tabularnewline
34 & 103.74 & 102.572 & 102.109 & 0.463035 & 1.16822 \tabularnewline
35 & 103.89 & 102.451 & 101.848 & 0.603118 & 1.43855 \tabularnewline
36 & 103.92 & 102.204 & 101.591 & 0.612368 & 1.71638 \tabularnewline
37 & 99.68 & 101.225 & 101.337 & -0.111215 & -1.54545 \tabularnewline
38 & 99.06 & 100.572 & 101.081 & -0.509715 & -1.51153 \tabularnewline
39 & 99.12 & 100.401 & 100.829 & -0.427799 & -1.28137 \tabularnewline
40 & 99.37 & 100.276 & 100.585 & -0.309549 & -0.905868 \tabularnewline
41 & 99.63 & 100.191 & 100.348 & -0.156215 & -0.561285 \tabularnewline
42 & 99.69 & 100.002 & 100.115 & -0.113382 & -0.311618 \tabularnewline
43 & 99.76 & 99.7349 & 100.065 & -0.329715 & 0.0251319 \tabularnewline
44 & 100.16 & 100.27 & 100.215 & 0.0557014 & -0.110285 \tabularnewline
45 & 100.46 & 100.608 & 100.385 & 0.223368 & -0.148368 \tabularnewline
46 & 100.83 & 101.008 & 100.545 & 0.463035 & -0.177618 \tabularnewline
47 & 101.09 & 101.288 & 100.685 & 0.603118 & -0.198118 \tabularnewline
48 & 101.14 & 101.426 & 100.813 & 0.612368 & -0.285701 \tabularnewline
49 & 101.25 & 100.809 & 100.92 & -0.111215 & 0.441215 \tabularnewline
50 & 101.09 & 100.492 & 101.002 & -0.509715 & 0.598049 \tabularnewline
51 & 101.18 & 100.641 & 101.068 & -0.427799 & 0.539465 \tabularnewline
52 & 101.14 & 100.8 & 101.11 & -0.309549 & 0.339965 \tabularnewline
53 & 101.23 & 100.97 & 101.126 & -0.156215 & 0.260382 \tabularnewline
54 & 101.17 & 101.022 & 101.136 & -0.113382 & 0.147549 \tabularnewline
55 & 100.84 & 100.836 & 101.166 & -0.329715 & 0.00388194 \tabularnewline
56 & 101.04 & 101.277 & 101.221 & 0.0557014 & -0.236951 \tabularnewline
57 & 101.18 & 101.506 & 101.283 & 0.223368 & -0.326285 \tabularnewline
58 & 101.1 & 101.811 & 101.348 & 0.463035 & -0.710951 \tabularnewline
59 & 101.21 & 102.016 & 101.412 & 0.603118 & -0.805618 \tabularnewline
60 & 101.26 & 102.092 & 101.48 & 0.612368 & -0.831951 \tabularnewline
61 & 101.85 & 101.427 & 101.538 & -0.111215 & 0.423299 \tabularnewline
62 & 101.82 & 101.057 & 101.567 & -0.509715 & 0.763049 \tabularnewline
63 & 101.93 & 101.144 & 101.572 & -0.427799 & 0.786132 \tabularnewline
64 & 101.95 & 101.268 & 101.577 & -0.309549 & 0.682465 \tabularnewline
65 & 101.97 & 101.435 & 101.592 & -0.156215 & 0.534549 \tabularnewline
66 & 102.04 & 101.492 & 101.605 & -0.113382 & 0.548382 \tabularnewline
67 & 101.37 & NA & NA & -0.329715 & NA \tabularnewline
68 & 101.2 & NA & NA & 0.0557014 & NA \tabularnewline
69 & 101.14 & NA & NA & 0.223368 & NA \tabularnewline
70 & 101.27 & NA & NA & 0.463035 & NA \tabularnewline
71 & 101.39 & NA & NA & 0.603118 & NA \tabularnewline
72 & 101.4 & NA & NA & 0.612368 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]101.03[/C][C]NA[/C][C]NA[/C][C]-0.111215[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]100.65[/C][C]NA[/C][C]NA[/C][C]-0.509715[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]100.66[/C][C]NA[/C][C]NA[/C][C]-0.427799[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]100.54[/C][C]NA[/C][C]NA[/C][C]-0.309549[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]100.51[/C][C]NA[/C][C]NA[/C][C]-0.156215[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]100.53[/C][C]NA[/C][C]NA[/C][C]-0.113382[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]100.53[/C][C]100.588[/C][C]100.917[/C][C]-0.329715[/C][C]-0.0577847[/C][/ROW]
[ROW][C]8[/C][C]101.02[/C][C]101.005[/C][C]100.949[/C][C]0.0557014[/C][C]0.0151319[/C][/ROW]
[ROW][C]9[/C][C]101.07[/C][C]101.205[/C][C]100.982[/C][C]0.223368[/C][C]-0.135451[/C][/ROW]
[ROW][C]10[/C][C]101.37[/C][C]101.496[/C][C]101.033[/C][C]0.463035[/C][C]-0.125951[/C][/ROW]
[ROW][C]11[/C][C]101.45[/C][C]101.711[/C][C]101.108[/C][C]0.603118[/C][C]-0.260618[/C][/ROW]
[ROW][C]12[/C][C]101.44[/C][C]101.807[/C][C]101.195[/C][C]0.612368[/C][C]-0.366951[/C][/ROW]
[ROW][C]13[/C][C]101.45[/C][C]101.173[/C][C]101.284[/C][C]-0.111215[/C][C]0.277049[/C][/ROW]
[ROW][C]14[/C][C]100.99[/C][C]100.862[/C][C]101.372[/C][C]-0.509715[/C][C]0.128049[/C][/ROW]
[ROW][C]15[/C][C]101.11[/C][C]101.04[/C][C]101.468[/C][C]-0.427799[/C][C]0.0698819[/C][/ROW]
[ROW][C]16[/C][C]101.31[/C][C]101.269[/C][C]101.579[/C][C]-0.309549[/C][C]0.0407986[/C][/ROW]
[ROW][C]17[/C][C]101.53[/C][C]101.543[/C][C]101.699[/C][C]-0.156215[/C][C]-0.0125347[/C][/ROW]
[ROW][C]18[/C][C]101.6[/C][C]101.714[/C][C]101.827[/C][C]-0.113382[/C][C]-0.113701[/C][/ROW]
[ROW][C]19[/C][C]101.61[/C][C]101.628[/C][C]101.958[/C][C]-0.329715[/C][C]-0.0182014[/C][/ROW]
[ROW][C]20[/C][C]102.04[/C][C]102.135[/C][C]102.08[/C][C]0.0557014[/C][C]-0.0952847[/C][/ROW]
[ROW][C]21[/C][C]102.36[/C][C]102.412[/C][C]102.189[/C][C]0.223368[/C][C]-0.0521181[/C][/ROW]
[ROW][C]22[/C][C]102.74[/C][C]102.756[/C][C]102.293[/C][C]0.463035[/C][C]-0.0159514[/C][/ROW]
[ROW][C]23[/C][C]102.96[/C][C]102.996[/C][C]102.393[/C][C]0.603118[/C][C]-0.0364514[/C][/ROW]
[ROW][C]24[/C][C]103.01[/C][C]103.104[/C][C]102.492[/C][C]0.612368[/C][C]-0.0940347[/C][/ROW]
[ROW][C]25[/C][C]103.02[/C][C]102.478[/C][C]102.59[/C][C]-0.111215[/C][C]0.541632[/C][/ROW]
[ROW][C]26[/C][C]102.34[/C][C]102.18[/C][C]102.69[/C][C]-0.509715[/C][C]0.160132[/C][/ROW]
[ROW][C]27[/C][C]102.38[/C][C]102.356[/C][C]102.784[/C][C]-0.427799[/C][C]0.0236319[/C][/ROW]
[ROW][C]28[/C][C]102.54[/C][C]102.56[/C][C]102.869[/C][C]-0.309549[/C][C]-0.0196181[/C][/ROW]
[ROW][C]29[/C][C]102.71[/C][C]102.793[/C][C]102.95[/C][C]-0.156215[/C][C]-0.0833681[/C][/ROW]
[ROW][C]30[/C][C]102.78[/C][C]102.913[/C][C]103.026[/C][C]-0.113382[/C][C]-0.132868[/C][/ROW]
[ROW][C]31[/C][C]102.78[/C][C]102.595[/C][C]102.925[/C][C]-0.329715[/C][C]0.184715[/C][/ROW]
[ROW][C]32[/C][C]103.27[/C][C]102.705[/C][C]102.649[/C][C]0.0557014[/C][C]0.565132[/C][/ROW]
[ROW][C]33[/C][C]103.4[/C][C]102.6[/C][C]102.377[/C][C]0.223368[/C][C]0.799965[/C][/ROW]
[ROW][C]34[/C][C]103.74[/C][C]102.572[/C][C]102.109[/C][C]0.463035[/C][C]1.16822[/C][/ROW]
[ROW][C]35[/C][C]103.89[/C][C]102.451[/C][C]101.848[/C][C]0.603118[/C][C]1.43855[/C][/ROW]
[ROW][C]36[/C][C]103.92[/C][C]102.204[/C][C]101.591[/C][C]0.612368[/C][C]1.71638[/C][/ROW]
[ROW][C]37[/C][C]99.68[/C][C]101.225[/C][C]101.337[/C][C]-0.111215[/C][C]-1.54545[/C][/ROW]
[ROW][C]38[/C][C]99.06[/C][C]100.572[/C][C]101.081[/C][C]-0.509715[/C][C]-1.51153[/C][/ROW]
[ROW][C]39[/C][C]99.12[/C][C]100.401[/C][C]100.829[/C][C]-0.427799[/C][C]-1.28137[/C][/ROW]
[ROW][C]40[/C][C]99.37[/C][C]100.276[/C][C]100.585[/C][C]-0.309549[/C][C]-0.905868[/C][/ROW]
[ROW][C]41[/C][C]99.63[/C][C]100.191[/C][C]100.348[/C][C]-0.156215[/C][C]-0.561285[/C][/ROW]
[ROW][C]42[/C][C]99.69[/C][C]100.002[/C][C]100.115[/C][C]-0.113382[/C][C]-0.311618[/C][/ROW]
[ROW][C]43[/C][C]99.76[/C][C]99.7349[/C][C]100.065[/C][C]-0.329715[/C][C]0.0251319[/C][/ROW]
[ROW][C]44[/C][C]100.16[/C][C]100.27[/C][C]100.215[/C][C]0.0557014[/C][C]-0.110285[/C][/ROW]
[ROW][C]45[/C][C]100.46[/C][C]100.608[/C][C]100.385[/C][C]0.223368[/C][C]-0.148368[/C][/ROW]
[ROW][C]46[/C][C]100.83[/C][C]101.008[/C][C]100.545[/C][C]0.463035[/C][C]-0.177618[/C][/ROW]
[ROW][C]47[/C][C]101.09[/C][C]101.288[/C][C]100.685[/C][C]0.603118[/C][C]-0.198118[/C][/ROW]
[ROW][C]48[/C][C]101.14[/C][C]101.426[/C][C]100.813[/C][C]0.612368[/C][C]-0.285701[/C][/ROW]
[ROW][C]49[/C][C]101.25[/C][C]100.809[/C][C]100.92[/C][C]-0.111215[/C][C]0.441215[/C][/ROW]
[ROW][C]50[/C][C]101.09[/C][C]100.492[/C][C]101.002[/C][C]-0.509715[/C][C]0.598049[/C][/ROW]
[ROW][C]51[/C][C]101.18[/C][C]100.641[/C][C]101.068[/C][C]-0.427799[/C][C]0.539465[/C][/ROW]
[ROW][C]52[/C][C]101.14[/C][C]100.8[/C][C]101.11[/C][C]-0.309549[/C][C]0.339965[/C][/ROW]
[ROW][C]53[/C][C]101.23[/C][C]100.97[/C][C]101.126[/C][C]-0.156215[/C][C]0.260382[/C][/ROW]
[ROW][C]54[/C][C]101.17[/C][C]101.022[/C][C]101.136[/C][C]-0.113382[/C][C]0.147549[/C][/ROW]
[ROW][C]55[/C][C]100.84[/C][C]100.836[/C][C]101.166[/C][C]-0.329715[/C][C]0.00388194[/C][/ROW]
[ROW][C]56[/C][C]101.04[/C][C]101.277[/C][C]101.221[/C][C]0.0557014[/C][C]-0.236951[/C][/ROW]
[ROW][C]57[/C][C]101.18[/C][C]101.506[/C][C]101.283[/C][C]0.223368[/C][C]-0.326285[/C][/ROW]
[ROW][C]58[/C][C]101.1[/C][C]101.811[/C][C]101.348[/C][C]0.463035[/C][C]-0.710951[/C][/ROW]
[ROW][C]59[/C][C]101.21[/C][C]102.016[/C][C]101.412[/C][C]0.603118[/C][C]-0.805618[/C][/ROW]
[ROW][C]60[/C][C]101.26[/C][C]102.092[/C][C]101.48[/C][C]0.612368[/C][C]-0.831951[/C][/ROW]
[ROW][C]61[/C][C]101.85[/C][C]101.427[/C][C]101.538[/C][C]-0.111215[/C][C]0.423299[/C][/ROW]
[ROW][C]62[/C][C]101.82[/C][C]101.057[/C][C]101.567[/C][C]-0.509715[/C][C]0.763049[/C][/ROW]
[ROW][C]63[/C][C]101.93[/C][C]101.144[/C][C]101.572[/C][C]-0.427799[/C][C]0.786132[/C][/ROW]
[ROW][C]64[/C][C]101.95[/C][C]101.268[/C][C]101.577[/C][C]-0.309549[/C][C]0.682465[/C][/ROW]
[ROW][C]65[/C][C]101.97[/C][C]101.435[/C][C]101.592[/C][C]-0.156215[/C][C]0.534549[/C][/ROW]
[ROW][C]66[/C][C]102.04[/C][C]101.492[/C][C]101.605[/C][C]-0.113382[/C][C]0.548382[/C][/ROW]
[ROW][C]67[/C][C]101.37[/C][C]NA[/C][C]NA[/C][C]-0.329715[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]101.2[/C][C]NA[/C][C]NA[/C][C]0.0557014[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]101.14[/C][C]NA[/C][C]NA[/C][C]0.223368[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]101.27[/C][C]NA[/C][C]NA[/C][C]0.463035[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]101.39[/C][C]NA[/C][C]NA[/C][C]0.603118[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]101.4[/C][C]NA[/C][C]NA[/C][C]0.612368[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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	101.03	NA	NA	-0.111215	NA
2	100.65	NA	NA	-0.509715	NA
3	100.66	NA	NA	-0.427799	NA
4	100.54	NA	NA	-0.309549	NA
5	100.51	NA	NA	-0.156215	NA
6	100.53	NA	NA	-0.113382	NA
7	100.53	100.588	100.917	-0.329715	-0.0577847
8	101.02	101.005	100.949	0.0557014	0.0151319
9	101.07	101.205	100.982	0.223368	-0.135451
10	101.37	101.496	101.033	0.463035	-0.125951
11	101.45	101.711	101.108	0.603118	-0.260618
12	101.44	101.807	101.195	0.612368	-0.366951
13	101.45	101.173	101.284	-0.111215	0.277049
14	100.99	100.862	101.372	-0.509715	0.128049
15	101.11	101.04	101.468	-0.427799	0.0698819
16	101.31	101.269	101.579	-0.309549	0.0407986
17	101.53	101.543	101.699	-0.156215	-0.0125347
18	101.6	101.714	101.827	-0.113382	-0.113701
19	101.61	101.628	101.958	-0.329715	-0.0182014
20	102.04	102.135	102.08	0.0557014	-0.0952847
21	102.36	102.412	102.189	0.223368	-0.0521181
22	102.74	102.756	102.293	0.463035	-0.0159514
23	102.96	102.996	102.393	0.603118	-0.0364514
24	103.01	103.104	102.492	0.612368	-0.0940347
25	103.02	102.478	102.59	-0.111215	0.541632
26	102.34	102.18	102.69	-0.509715	0.160132
27	102.38	102.356	102.784	-0.427799	0.0236319
28	102.54	102.56	102.869	-0.309549	-0.0196181
29	102.71	102.793	102.95	-0.156215	-0.0833681
30	102.78	102.913	103.026	-0.113382	-0.132868
31	102.78	102.595	102.925	-0.329715	0.184715
32	103.27	102.705	102.649	0.0557014	0.565132
33	103.4	102.6	102.377	0.223368	0.799965
34	103.74	102.572	102.109	0.463035	1.16822
35	103.89	102.451	101.848	0.603118	1.43855
36	103.92	102.204	101.591	0.612368	1.71638
37	99.68	101.225	101.337	-0.111215	-1.54545
38	99.06	100.572	101.081	-0.509715	-1.51153
39	99.12	100.401	100.829	-0.427799	-1.28137
40	99.37	100.276	100.585	-0.309549	-0.905868
41	99.63	100.191	100.348	-0.156215	-0.561285
42	99.69	100.002	100.115	-0.113382	-0.311618
43	99.76	99.7349	100.065	-0.329715	0.0251319
44	100.16	100.27	100.215	0.0557014	-0.110285
45	100.46	100.608	100.385	0.223368	-0.148368
46	100.83	101.008	100.545	0.463035	-0.177618
47	101.09	101.288	100.685	0.603118	-0.198118
48	101.14	101.426	100.813	0.612368	-0.285701
49	101.25	100.809	100.92	-0.111215	0.441215
50	101.09	100.492	101.002	-0.509715	0.598049
51	101.18	100.641	101.068	-0.427799	0.539465
52	101.14	100.8	101.11	-0.309549	0.339965
53	101.23	100.97	101.126	-0.156215	0.260382
54	101.17	101.022	101.136	-0.113382	0.147549
55	100.84	100.836	101.166	-0.329715	0.00388194
56	101.04	101.277	101.221	0.0557014	-0.236951
57	101.18	101.506	101.283	0.223368	-0.326285
58	101.1	101.811	101.348	0.463035	-0.710951
59	101.21	102.016	101.412	0.603118	-0.805618
60	101.26	102.092	101.48	0.612368	-0.831951
61	101.85	101.427	101.538	-0.111215	0.423299
62	101.82	101.057	101.567	-0.509715	0.763049
63	101.93	101.144	101.572	-0.427799	0.786132
64	101.95	101.268	101.577	-0.309549	0.682465
65	101.97	101.435	101.592	-0.156215	0.534549
66	102.04	101.492	101.605	-0.113382	0.548382
67	101.37	NA	NA	-0.329715	NA
68	101.2	NA	NA	0.0557014	NA
69	101.14	NA	NA	0.223368	NA
70	101.27	NA	NA	0.463035	NA
71	101.39	NA	NA	0.603118	NA
72	101.4	NA	NA	0.612368	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6))
a<-table.element(a,signif(m$trend[i],6))
a<-table.element(a,signif(m$seasonal[i],6))
a<-table.element(a,signif(m$random[i],6))
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