Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 22 May 2014 08:08:35 -0400

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/May/22/t1400760534d0ozjmoubevg0kz.htm/, Retrieved Wed, 15 May 2024 23:36:23 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=235094, Retrieved Wed, 15 May 2024 23:36:23 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

100

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

-       [Classical Decomposition] [] [2014-05-22 12:08:35] [0c294eb9167d3ec9e00e44a88645ee85] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

2,58
2,59
2,6
2,6
2,61
2,62
2,64
2,65
2,66
2,67
2,68
2,69
2,69
2,71
2,72
2,73
2,73
2,74
2,74
2,74
2,74
2,74
2,75
2,75
2,75
2,75
2,77
2,78
2,79
2,8
2,82
2,83
2,84
2,87
2,89
2,9
2,9
2,91
2,92
2,92
2,92
2,92
2,94
2,95
2,95
2,97
2,99
3
3
3,01
3,03
3,03
3,04
3,04
3,05
3,05
3,09
3,09
3,09
3,1
3,1
3,11
3,12
3,12
3,12
3,13
3,15
3,16
3,16
3,18
3,19
3,19
3,2
3,21
3,26
3,27
3,28
3,29
3,29
3,3
3,3
3,31
3,31
3,31

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	'Gwilym Jenkins' @ jenkins.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 & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235094&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235094&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235094&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	2.58	NA	NA	-0.00532407	NA
2	2.59	NA	NA	-0.00435185	NA
3	2.6	NA	NA	0.00668981	NA
4	2.6	NA	NA	0.00280093	NA
5	2.61	NA	NA	-0.00101852	NA
6	2.62	NA	NA	-0.00303241	NA
7	2.64	2.63627	2.63708	-0.000810185	0.00372685
8	2.65	2.64391	2.64667	-0.00275463	0.00608796
9	2.66	2.65502	2.65667	-0.00164352	0.00497685
10	2.67	2.66954	2.66708	0.0024537	0.000462963
11	2.68	2.68231	2.6775	0.00481481	-0.00231481
12	2.69	2.68968	2.6875	0.00217593	0.000324074
13	2.69	2.69134	2.69667	-0.00532407	-0.00134259
14	2.71	2.70023	2.70458	-0.00435185	0.00976852
15	2.72	2.71836	2.71167	0.00668981	0.00164352
16	2.73	2.72072	2.71792	0.00280093	0.00928241
17	2.73	2.72273	2.72375	-0.00101852	0.00726852
18	2.74	2.72613	2.72917	-0.00303241	0.0138657
19	2.74	2.73336	2.73417	-0.000810185	0.00664352
20	2.74	2.73558	2.73833	-0.00275463	0.0044213
21	2.74	2.74044	2.74208	-0.00164352	-0.000439815
22	2.74	2.7487	2.74625	0.0024537	-0.0087037
23	2.75	2.75565	2.75083	0.00481481	-0.00564815
24	2.75	2.75801	2.75583	0.00217593	-0.00800926
25	2.75	2.75634	2.76167	-0.00532407	-0.00634259
26	2.75	2.7644	2.76875	-0.00435185	-0.0143981
27	2.77	2.78336	2.77667	0.00668981	-0.0133565
28	2.78	2.78905	2.78625	0.00280093	-0.00905093
29	2.79	2.79648	2.7975	-0.00101852	-0.00648148
30	2.8	2.80655	2.80958	-0.00303241	-0.00655093
31	2.82	2.82127	2.82208	-0.000810185	-0.00127315
32	2.83	2.83225	2.835	-0.00275463	-0.00224537
33	2.84	2.84627	2.84792	-0.00164352	-0.00627315
34	2.87	2.86245	2.86	0.0024537	0.0075463
35	2.89	2.87606	2.87125	0.00481481	0.0139352
36	2.9	2.88384	2.88167	0.00217593	0.0161574
37	2.9	2.88634	2.89167	-0.00532407	0.0136574
38	2.91	2.89731	2.90167	-0.00435185	0.0126852
39	2.92	2.91794	2.91125	0.00668981	0.00206019
40	2.92	2.9228	2.92	0.00280093	-0.00280093
41	2.92	2.92731	2.92833	-0.00101852	-0.00731481
42	2.92	2.93363	2.93667	-0.00303241	-0.0136343
43	2.94	2.94419	2.945	-0.000810185	-0.00418981
44	2.95	2.95058	2.95333	-0.00275463	-0.000578704
45	2.95	2.96044	2.96208	-0.00164352	-0.0104398
46	2.97	2.9737	2.97125	0.0024537	-0.0037037
47	2.99	2.98565	2.98083	0.00481481	0.00435185
48	3	2.99301	2.99083	0.00217593	0.00699074
49	3	2.99509	3.00042	-0.00532407	0.00490741
50	3.01	3.00481	3.00917	-0.00435185	0.00518519
51	3.03	3.02586	3.01917	0.00668981	0.00414352
52	3.03	3.0328	3.03	0.00280093	-0.00280093
53	3.04	3.03815	3.03917	-0.00101852	0.00185185
54	3.04	3.04447	3.0475	-0.00303241	-0.00446759
55	3.05	3.05502	3.05583	-0.000810185	-0.00502315
56	3.05	3.06141	3.06417	-0.00275463	-0.011412
57	3.09	3.07044	3.07208	-0.00164352	0.0195602
58	3.09	3.08204	3.07958	0.0024537	0.00796296
59	3.09	3.09148	3.08667	0.00481481	-0.00148148
60	3.1	3.09593	3.09375	0.00217593	0.00407407
61	3.1	3.09634	3.10167	-0.00532407	0.00365741
62	3.11	3.10606	3.11042	-0.00435185	0.00393519
63	3.12	3.12461	3.11792	0.00668981	-0.00460648
64	3.12	3.12738	3.12458	0.00280093	-0.00738426
65	3.12	3.13148	3.1325	-0.00101852	-0.0114815
66	3.13	3.13738	3.14042	-0.00303241	-0.00738426
67	3.15	3.14752	3.14833	-0.000810185	0.00247685
68	3.16	3.15391	3.15667	-0.00275463	0.00608796
69	3.16	3.16502	3.16667	-0.00164352	-0.00502315
70	3.18	3.1812	3.17875	0.0024537	-0.0012037
71	3.19	3.19648	3.19167	0.00481481	-0.00648148
72	3.19	3.20718	3.205	0.00217593	-0.0171759
73	3.2	3.21218	3.2175	-0.00532407	-0.0121759
74	3.21	3.22481	3.22917	-0.00435185	-0.0148148
75	3.26	3.24752	3.24083	0.00668981	0.0124769
76	3.27	3.25488	3.25208	0.00280093	0.0151157
77	3.28	3.26148	3.2625	-0.00101852	0.0185185
78	3.29	3.26947	3.2725	-0.00303241	0.0205324
79	3.29	NA	NA	-0.000810185	NA
80	3.3	NA	NA	-0.00275463	NA
81	3.3	NA	NA	-0.00164352	NA
82	3.31	NA	NA	0.0024537	NA
83	3.31	NA	NA	0.00481481	NA
84	3.31	NA	NA	0.00217593	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 2.58 & NA & NA & -0.00532407 & NA \tabularnewline
2 & 2.59 & NA & NA & -0.00435185 & NA \tabularnewline
3 & 2.6 & NA & NA & 0.00668981 & NA \tabularnewline
4 & 2.6 & NA & NA & 0.00280093 & NA \tabularnewline
5 & 2.61 & NA & NA & -0.00101852 & NA \tabularnewline
6 & 2.62 & NA & NA & -0.00303241 & NA \tabularnewline
7 & 2.64 & 2.63627 & 2.63708 & -0.000810185 & 0.00372685 \tabularnewline
8 & 2.65 & 2.64391 & 2.64667 & -0.00275463 & 0.00608796 \tabularnewline
9 & 2.66 & 2.65502 & 2.65667 & -0.00164352 & 0.00497685 \tabularnewline
10 & 2.67 & 2.66954 & 2.66708 & 0.0024537 & 0.000462963 \tabularnewline
11 & 2.68 & 2.68231 & 2.6775 & 0.00481481 & -0.00231481 \tabularnewline
12 & 2.69 & 2.68968 & 2.6875 & 0.00217593 & 0.000324074 \tabularnewline
13 & 2.69 & 2.69134 & 2.69667 & -0.00532407 & -0.00134259 \tabularnewline
14 & 2.71 & 2.70023 & 2.70458 & -0.00435185 & 0.00976852 \tabularnewline
15 & 2.72 & 2.71836 & 2.71167 & 0.00668981 & 0.00164352 \tabularnewline
16 & 2.73 & 2.72072 & 2.71792 & 0.00280093 & 0.00928241 \tabularnewline
17 & 2.73 & 2.72273 & 2.72375 & -0.00101852 & 0.00726852 \tabularnewline
18 & 2.74 & 2.72613 & 2.72917 & -0.00303241 & 0.0138657 \tabularnewline
19 & 2.74 & 2.73336 & 2.73417 & -0.000810185 & 0.00664352 \tabularnewline
20 & 2.74 & 2.73558 & 2.73833 & -0.00275463 & 0.0044213 \tabularnewline
21 & 2.74 & 2.74044 & 2.74208 & -0.00164352 & -0.000439815 \tabularnewline
22 & 2.74 & 2.7487 & 2.74625 & 0.0024537 & -0.0087037 \tabularnewline
23 & 2.75 & 2.75565 & 2.75083 & 0.00481481 & -0.00564815 \tabularnewline
24 & 2.75 & 2.75801 & 2.75583 & 0.00217593 & -0.00800926 \tabularnewline
25 & 2.75 & 2.75634 & 2.76167 & -0.00532407 & -0.00634259 \tabularnewline
26 & 2.75 & 2.7644 & 2.76875 & -0.00435185 & -0.0143981 \tabularnewline
27 & 2.77 & 2.78336 & 2.77667 & 0.00668981 & -0.0133565 \tabularnewline
28 & 2.78 & 2.78905 & 2.78625 & 0.00280093 & -0.00905093 \tabularnewline
29 & 2.79 & 2.79648 & 2.7975 & -0.00101852 & -0.00648148 \tabularnewline
30 & 2.8 & 2.80655 & 2.80958 & -0.00303241 & -0.00655093 \tabularnewline
31 & 2.82 & 2.82127 & 2.82208 & -0.000810185 & -0.00127315 \tabularnewline
32 & 2.83 & 2.83225 & 2.835 & -0.00275463 & -0.00224537 \tabularnewline
33 & 2.84 & 2.84627 & 2.84792 & -0.00164352 & -0.00627315 \tabularnewline
34 & 2.87 & 2.86245 & 2.86 & 0.0024537 & 0.0075463 \tabularnewline
35 & 2.89 & 2.87606 & 2.87125 & 0.00481481 & 0.0139352 \tabularnewline
36 & 2.9 & 2.88384 & 2.88167 & 0.00217593 & 0.0161574 \tabularnewline
37 & 2.9 & 2.88634 & 2.89167 & -0.00532407 & 0.0136574 \tabularnewline
38 & 2.91 & 2.89731 & 2.90167 & -0.00435185 & 0.0126852 \tabularnewline
39 & 2.92 & 2.91794 & 2.91125 & 0.00668981 & 0.00206019 \tabularnewline
40 & 2.92 & 2.9228 & 2.92 & 0.00280093 & -0.00280093 \tabularnewline
41 & 2.92 & 2.92731 & 2.92833 & -0.00101852 & -0.00731481 \tabularnewline
42 & 2.92 & 2.93363 & 2.93667 & -0.00303241 & -0.0136343 \tabularnewline
43 & 2.94 & 2.94419 & 2.945 & -0.000810185 & -0.00418981 \tabularnewline
44 & 2.95 & 2.95058 & 2.95333 & -0.00275463 & -0.000578704 \tabularnewline
45 & 2.95 & 2.96044 & 2.96208 & -0.00164352 & -0.0104398 \tabularnewline
46 & 2.97 & 2.9737 & 2.97125 & 0.0024537 & -0.0037037 \tabularnewline
47 & 2.99 & 2.98565 & 2.98083 & 0.00481481 & 0.00435185 \tabularnewline
48 & 3 & 2.99301 & 2.99083 & 0.00217593 & 0.00699074 \tabularnewline
49 & 3 & 2.99509 & 3.00042 & -0.00532407 & 0.00490741 \tabularnewline
50 & 3.01 & 3.00481 & 3.00917 & -0.00435185 & 0.00518519 \tabularnewline
51 & 3.03 & 3.02586 & 3.01917 & 0.00668981 & 0.00414352 \tabularnewline
52 & 3.03 & 3.0328 & 3.03 & 0.00280093 & -0.00280093 \tabularnewline
53 & 3.04 & 3.03815 & 3.03917 & -0.00101852 & 0.00185185 \tabularnewline
54 & 3.04 & 3.04447 & 3.0475 & -0.00303241 & -0.00446759 \tabularnewline
55 & 3.05 & 3.05502 & 3.05583 & -0.000810185 & -0.00502315 \tabularnewline
56 & 3.05 & 3.06141 & 3.06417 & -0.00275463 & -0.011412 \tabularnewline
57 & 3.09 & 3.07044 & 3.07208 & -0.00164352 & 0.0195602 \tabularnewline
58 & 3.09 & 3.08204 & 3.07958 & 0.0024537 & 0.00796296 \tabularnewline
59 & 3.09 & 3.09148 & 3.08667 & 0.00481481 & -0.00148148 \tabularnewline
60 & 3.1 & 3.09593 & 3.09375 & 0.00217593 & 0.00407407 \tabularnewline
61 & 3.1 & 3.09634 & 3.10167 & -0.00532407 & 0.00365741 \tabularnewline
62 & 3.11 & 3.10606 & 3.11042 & -0.00435185 & 0.00393519 \tabularnewline
63 & 3.12 & 3.12461 & 3.11792 & 0.00668981 & -0.00460648 \tabularnewline
64 & 3.12 & 3.12738 & 3.12458 & 0.00280093 & -0.00738426 \tabularnewline
65 & 3.12 & 3.13148 & 3.1325 & -0.00101852 & -0.0114815 \tabularnewline
66 & 3.13 & 3.13738 & 3.14042 & -0.00303241 & -0.00738426 \tabularnewline
67 & 3.15 & 3.14752 & 3.14833 & -0.000810185 & 0.00247685 \tabularnewline
68 & 3.16 & 3.15391 & 3.15667 & -0.00275463 & 0.00608796 \tabularnewline
69 & 3.16 & 3.16502 & 3.16667 & -0.00164352 & -0.00502315 \tabularnewline
70 & 3.18 & 3.1812 & 3.17875 & 0.0024537 & -0.0012037 \tabularnewline
71 & 3.19 & 3.19648 & 3.19167 & 0.00481481 & -0.00648148 \tabularnewline
72 & 3.19 & 3.20718 & 3.205 & 0.00217593 & -0.0171759 \tabularnewline
73 & 3.2 & 3.21218 & 3.2175 & -0.00532407 & -0.0121759 \tabularnewline
74 & 3.21 & 3.22481 & 3.22917 & -0.00435185 & -0.0148148 \tabularnewline
75 & 3.26 & 3.24752 & 3.24083 & 0.00668981 & 0.0124769 \tabularnewline
76 & 3.27 & 3.25488 & 3.25208 & 0.00280093 & 0.0151157 \tabularnewline
77 & 3.28 & 3.26148 & 3.2625 & -0.00101852 & 0.0185185 \tabularnewline
78 & 3.29 & 3.26947 & 3.2725 & -0.00303241 & 0.0205324 \tabularnewline
79 & 3.29 & NA & NA & -0.000810185 & NA \tabularnewline
80 & 3.3 & NA & NA & -0.00275463 & NA \tabularnewline
81 & 3.3 & NA & NA & -0.00164352 & NA \tabularnewline
82 & 3.31 & NA & NA & 0.0024537 & NA \tabularnewline
83 & 3.31 & NA & NA & 0.00481481 & NA \tabularnewline
84 & 3.31 & NA & NA & 0.00217593 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=235094&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]2.58[/C][C]NA[/C][C]NA[/C][C]-0.00532407[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]2.59[/C][C]NA[/C][C]NA[/C][C]-0.00435185[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]2.6[/C][C]NA[/C][C]NA[/C][C]0.00668981[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]2.6[/C][C]NA[/C][C]NA[/C][C]0.00280093[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]2.61[/C][C]NA[/C][C]NA[/C][C]-0.00101852[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]2.62[/C][C]NA[/C][C]NA[/C][C]-0.00303241[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]2.64[/C][C]2.63627[/C][C]2.63708[/C][C]-0.000810185[/C][C]0.00372685[/C][/ROW]
[ROW][C]8[/C][C]2.65[/C][C]2.64391[/C][C]2.64667[/C][C]-0.00275463[/C][C]0.00608796[/C][/ROW]
[ROW][C]9[/C][C]2.66[/C][C]2.65502[/C][C]2.65667[/C][C]-0.00164352[/C][C]0.00497685[/C][/ROW]
[ROW][C]10[/C][C]2.67[/C][C]2.66954[/C][C]2.66708[/C][C]0.0024537[/C][C]0.000462963[/C][/ROW]
[ROW][C]11[/C][C]2.68[/C][C]2.68231[/C][C]2.6775[/C][C]0.00481481[/C][C]-0.00231481[/C][/ROW]
[ROW][C]12[/C][C]2.69[/C][C]2.68968[/C][C]2.6875[/C][C]0.00217593[/C][C]0.000324074[/C][/ROW]
[ROW][C]13[/C][C]2.69[/C][C]2.69134[/C][C]2.69667[/C][C]-0.00532407[/C][C]-0.00134259[/C][/ROW]
[ROW][C]14[/C][C]2.71[/C][C]2.70023[/C][C]2.70458[/C][C]-0.00435185[/C][C]0.00976852[/C][/ROW]
[ROW][C]15[/C][C]2.72[/C][C]2.71836[/C][C]2.71167[/C][C]0.00668981[/C][C]0.00164352[/C][/ROW]
[ROW][C]16[/C][C]2.73[/C][C]2.72072[/C][C]2.71792[/C][C]0.00280093[/C][C]0.00928241[/C][/ROW]
[ROW][C]17[/C][C]2.73[/C][C]2.72273[/C][C]2.72375[/C][C]-0.00101852[/C][C]0.00726852[/C][/ROW]
[ROW][C]18[/C][C]2.74[/C][C]2.72613[/C][C]2.72917[/C][C]-0.00303241[/C][C]0.0138657[/C][/ROW]
[ROW][C]19[/C][C]2.74[/C][C]2.73336[/C][C]2.73417[/C][C]-0.000810185[/C][C]0.00664352[/C][/ROW]
[ROW][C]20[/C][C]2.74[/C][C]2.73558[/C][C]2.73833[/C][C]-0.00275463[/C][C]0.0044213[/C][/ROW]
[ROW][C]21[/C][C]2.74[/C][C]2.74044[/C][C]2.74208[/C][C]-0.00164352[/C][C]-0.000439815[/C][/ROW]
[ROW][C]22[/C][C]2.74[/C][C]2.7487[/C][C]2.74625[/C][C]0.0024537[/C][C]-0.0087037[/C][/ROW]
[ROW][C]23[/C][C]2.75[/C][C]2.75565[/C][C]2.75083[/C][C]0.00481481[/C][C]-0.00564815[/C][/ROW]
[ROW][C]24[/C][C]2.75[/C][C]2.75801[/C][C]2.75583[/C][C]0.00217593[/C][C]-0.00800926[/C][/ROW]
[ROW][C]25[/C][C]2.75[/C][C]2.75634[/C][C]2.76167[/C][C]-0.00532407[/C][C]-0.00634259[/C][/ROW]
[ROW][C]26[/C][C]2.75[/C][C]2.7644[/C][C]2.76875[/C][C]-0.00435185[/C][C]-0.0143981[/C][/ROW]
[ROW][C]27[/C][C]2.77[/C][C]2.78336[/C][C]2.77667[/C][C]0.00668981[/C][C]-0.0133565[/C][/ROW]
[ROW][C]28[/C][C]2.78[/C][C]2.78905[/C][C]2.78625[/C][C]0.00280093[/C][C]-0.00905093[/C][/ROW]
[ROW][C]29[/C][C]2.79[/C][C]2.79648[/C][C]2.7975[/C][C]-0.00101852[/C][C]-0.00648148[/C][/ROW]
[ROW][C]30[/C][C]2.8[/C][C]2.80655[/C][C]2.80958[/C][C]-0.00303241[/C][C]-0.00655093[/C][/ROW]
[ROW][C]31[/C][C]2.82[/C][C]2.82127[/C][C]2.82208[/C][C]-0.000810185[/C][C]-0.00127315[/C][/ROW]
[ROW][C]32[/C][C]2.83[/C][C]2.83225[/C][C]2.835[/C][C]-0.00275463[/C][C]-0.00224537[/C][/ROW]
[ROW][C]33[/C][C]2.84[/C][C]2.84627[/C][C]2.84792[/C][C]-0.00164352[/C][C]-0.00627315[/C][/ROW]
[ROW][C]34[/C][C]2.87[/C][C]2.86245[/C][C]2.86[/C][C]0.0024537[/C][C]0.0075463[/C][/ROW]
[ROW][C]35[/C][C]2.89[/C][C]2.87606[/C][C]2.87125[/C][C]0.00481481[/C][C]0.0139352[/C][/ROW]
[ROW][C]36[/C][C]2.9[/C][C]2.88384[/C][C]2.88167[/C][C]0.00217593[/C][C]0.0161574[/C][/ROW]
[ROW][C]37[/C][C]2.9[/C][C]2.88634[/C][C]2.89167[/C][C]-0.00532407[/C][C]0.0136574[/C][/ROW]
[ROW][C]38[/C][C]2.91[/C][C]2.89731[/C][C]2.90167[/C][C]-0.00435185[/C][C]0.0126852[/C][/ROW]
[ROW][C]39[/C][C]2.92[/C][C]2.91794[/C][C]2.91125[/C][C]0.00668981[/C][C]0.00206019[/C][/ROW]
[ROW][C]40[/C][C]2.92[/C][C]2.9228[/C][C]2.92[/C][C]0.00280093[/C][C]-0.00280093[/C][/ROW]
[ROW][C]41[/C][C]2.92[/C][C]2.92731[/C][C]2.92833[/C][C]-0.00101852[/C][C]-0.00731481[/C][/ROW]
[ROW][C]42[/C][C]2.92[/C][C]2.93363[/C][C]2.93667[/C][C]-0.00303241[/C][C]-0.0136343[/C][/ROW]
[ROW][C]43[/C][C]2.94[/C][C]2.94419[/C][C]2.945[/C][C]-0.000810185[/C][C]-0.00418981[/C][/ROW]
[ROW][C]44[/C][C]2.95[/C][C]2.95058[/C][C]2.95333[/C][C]-0.00275463[/C][C]-0.000578704[/C][/ROW]
[ROW][C]45[/C][C]2.95[/C][C]2.96044[/C][C]2.96208[/C][C]-0.00164352[/C][C]-0.0104398[/C][/ROW]
[ROW][C]46[/C][C]2.97[/C][C]2.9737[/C][C]2.97125[/C][C]0.0024537[/C][C]-0.0037037[/C][/ROW]
[ROW][C]47[/C][C]2.99[/C][C]2.98565[/C][C]2.98083[/C][C]0.00481481[/C][C]0.00435185[/C][/ROW]
[ROW][C]48[/C][C]3[/C][C]2.99301[/C][C]2.99083[/C][C]0.00217593[/C][C]0.00699074[/C][/ROW]
[ROW][C]49[/C][C]3[/C][C]2.99509[/C][C]3.00042[/C][C]-0.00532407[/C][C]0.00490741[/C][/ROW]
[ROW][C]50[/C][C]3.01[/C][C]3.00481[/C][C]3.00917[/C][C]-0.00435185[/C][C]0.00518519[/C][/ROW]
[ROW][C]51[/C][C]3.03[/C][C]3.02586[/C][C]3.01917[/C][C]0.00668981[/C][C]0.00414352[/C][/ROW]
[ROW][C]52[/C][C]3.03[/C][C]3.0328[/C][C]3.03[/C][C]0.00280093[/C][C]-0.00280093[/C][/ROW]
[ROW][C]53[/C][C]3.04[/C][C]3.03815[/C][C]3.03917[/C][C]-0.00101852[/C][C]0.00185185[/C][/ROW]
[ROW][C]54[/C][C]3.04[/C][C]3.04447[/C][C]3.0475[/C][C]-0.00303241[/C][C]-0.00446759[/C][/ROW]
[ROW][C]55[/C][C]3.05[/C][C]3.05502[/C][C]3.05583[/C][C]-0.000810185[/C][C]-0.00502315[/C][/ROW]
[ROW][C]56[/C][C]3.05[/C][C]3.06141[/C][C]3.06417[/C][C]-0.00275463[/C][C]-0.011412[/C][/ROW]
[ROW][C]57[/C][C]3.09[/C][C]3.07044[/C][C]3.07208[/C][C]-0.00164352[/C][C]0.0195602[/C][/ROW]
[ROW][C]58[/C][C]3.09[/C][C]3.08204[/C][C]3.07958[/C][C]0.0024537[/C][C]0.00796296[/C][/ROW]
[ROW][C]59[/C][C]3.09[/C][C]3.09148[/C][C]3.08667[/C][C]0.00481481[/C][C]-0.00148148[/C][/ROW]
[ROW][C]60[/C][C]3.1[/C][C]3.09593[/C][C]3.09375[/C][C]0.00217593[/C][C]0.00407407[/C][/ROW]
[ROW][C]61[/C][C]3.1[/C][C]3.09634[/C][C]3.10167[/C][C]-0.00532407[/C][C]0.00365741[/C][/ROW]
[ROW][C]62[/C][C]3.11[/C][C]3.10606[/C][C]3.11042[/C][C]-0.00435185[/C][C]0.00393519[/C][/ROW]
[ROW][C]63[/C][C]3.12[/C][C]3.12461[/C][C]3.11792[/C][C]0.00668981[/C][C]-0.00460648[/C][/ROW]
[ROW][C]64[/C][C]3.12[/C][C]3.12738[/C][C]3.12458[/C][C]0.00280093[/C][C]-0.00738426[/C][/ROW]
[ROW][C]65[/C][C]3.12[/C][C]3.13148[/C][C]3.1325[/C][C]-0.00101852[/C][C]-0.0114815[/C][/ROW]
[ROW][C]66[/C][C]3.13[/C][C]3.13738[/C][C]3.14042[/C][C]-0.00303241[/C][C]-0.00738426[/C][/ROW]
[ROW][C]67[/C][C]3.15[/C][C]3.14752[/C][C]3.14833[/C][C]-0.000810185[/C][C]0.00247685[/C][/ROW]
[ROW][C]68[/C][C]3.16[/C][C]3.15391[/C][C]3.15667[/C][C]-0.00275463[/C][C]0.00608796[/C][/ROW]
[ROW][C]69[/C][C]3.16[/C][C]3.16502[/C][C]3.16667[/C][C]-0.00164352[/C][C]-0.00502315[/C][/ROW]
[ROW][C]70[/C][C]3.18[/C][C]3.1812[/C][C]3.17875[/C][C]0.0024537[/C][C]-0.0012037[/C][/ROW]
[ROW][C]71[/C][C]3.19[/C][C]3.19648[/C][C]3.19167[/C][C]0.00481481[/C][C]-0.00648148[/C][/ROW]
[ROW][C]72[/C][C]3.19[/C][C]3.20718[/C][C]3.205[/C][C]0.00217593[/C][C]-0.0171759[/C][/ROW]
[ROW][C]73[/C][C]3.2[/C][C]3.21218[/C][C]3.2175[/C][C]-0.00532407[/C][C]-0.0121759[/C][/ROW]
[ROW][C]74[/C][C]3.21[/C][C]3.22481[/C][C]3.22917[/C][C]-0.00435185[/C][C]-0.0148148[/C][/ROW]
[ROW][C]75[/C][C]3.26[/C][C]3.24752[/C][C]3.24083[/C][C]0.00668981[/C][C]0.0124769[/C][/ROW]
[ROW][C]76[/C][C]3.27[/C][C]3.25488[/C][C]3.25208[/C][C]0.00280093[/C][C]0.0151157[/C][/ROW]
[ROW][C]77[/C][C]3.28[/C][C]3.26148[/C][C]3.2625[/C][C]-0.00101852[/C][C]0.0185185[/C][/ROW]
[ROW][C]78[/C][C]3.29[/C][C]3.26947[/C][C]3.2725[/C][C]-0.00303241[/C][C]0.0205324[/C][/ROW]
[ROW][C]79[/C][C]3.29[/C][C]NA[/C][C]NA[/C][C]-0.000810185[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]3.3[/C][C]NA[/C][C]NA[/C][C]-0.00275463[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]3.3[/C][C]NA[/C][C]NA[/C][C]-0.00164352[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]3.31[/C][C]NA[/C][C]NA[/C][C]0.0024537[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]3.31[/C][C]NA[/C][C]NA[/C][C]0.00481481[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]3.31[/C][C]NA[/C][C]NA[/C][C]0.00217593[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=235094&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=235094&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	2.58	NA	NA	-0.00532407	NA
2	2.59	NA	NA	-0.00435185	NA
3	2.6	NA	NA	0.00668981	NA
4	2.6	NA	NA	0.00280093	NA
5	2.61	NA	NA	-0.00101852	NA
6	2.62	NA	NA	-0.00303241	NA
7	2.64	2.63627	2.63708	-0.000810185	0.00372685
8	2.65	2.64391	2.64667	-0.00275463	0.00608796
9	2.66	2.65502	2.65667	-0.00164352	0.00497685
10	2.67	2.66954	2.66708	0.0024537	0.000462963
11	2.68	2.68231	2.6775	0.00481481	-0.00231481
12	2.69	2.68968	2.6875	0.00217593	0.000324074
13	2.69	2.69134	2.69667	-0.00532407	-0.00134259
14	2.71	2.70023	2.70458	-0.00435185	0.00976852
15	2.72	2.71836	2.71167	0.00668981	0.00164352
16	2.73	2.72072	2.71792	0.00280093	0.00928241
17	2.73	2.72273	2.72375	-0.00101852	0.00726852
18	2.74	2.72613	2.72917	-0.00303241	0.0138657
19	2.74	2.73336	2.73417	-0.000810185	0.00664352
20	2.74	2.73558	2.73833	-0.00275463	0.0044213
21	2.74	2.74044	2.74208	-0.00164352	-0.000439815
22	2.74	2.7487	2.74625	0.0024537	-0.0087037
23	2.75	2.75565	2.75083	0.00481481	-0.00564815
24	2.75	2.75801	2.75583	0.00217593	-0.00800926
25	2.75	2.75634	2.76167	-0.00532407	-0.00634259
26	2.75	2.7644	2.76875	-0.00435185	-0.0143981
27	2.77	2.78336	2.77667	0.00668981	-0.0133565
28	2.78	2.78905	2.78625	0.00280093	-0.00905093
29	2.79	2.79648	2.7975	-0.00101852	-0.00648148
30	2.8	2.80655	2.80958	-0.00303241	-0.00655093
31	2.82	2.82127	2.82208	-0.000810185	-0.00127315
32	2.83	2.83225	2.835	-0.00275463	-0.00224537
33	2.84	2.84627	2.84792	-0.00164352	-0.00627315
34	2.87	2.86245	2.86	0.0024537	0.0075463
35	2.89	2.87606	2.87125	0.00481481	0.0139352
36	2.9	2.88384	2.88167	0.00217593	0.0161574
37	2.9	2.88634	2.89167	-0.00532407	0.0136574
38	2.91	2.89731	2.90167	-0.00435185	0.0126852
39	2.92	2.91794	2.91125	0.00668981	0.00206019
40	2.92	2.9228	2.92	0.00280093	-0.00280093
41	2.92	2.92731	2.92833	-0.00101852	-0.00731481
42	2.92	2.93363	2.93667	-0.00303241	-0.0136343
43	2.94	2.94419	2.945	-0.000810185	-0.00418981
44	2.95	2.95058	2.95333	-0.00275463	-0.000578704
45	2.95	2.96044	2.96208	-0.00164352	-0.0104398
46	2.97	2.9737	2.97125	0.0024537	-0.0037037
47	2.99	2.98565	2.98083	0.00481481	0.00435185
48	3	2.99301	2.99083	0.00217593	0.00699074
49	3	2.99509	3.00042	-0.00532407	0.00490741
50	3.01	3.00481	3.00917	-0.00435185	0.00518519
51	3.03	3.02586	3.01917	0.00668981	0.00414352
52	3.03	3.0328	3.03	0.00280093	-0.00280093
53	3.04	3.03815	3.03917	-0.00101852	0.00185185
54	3.04	3.04447	3.0475	-0.00303241	-0.00446759
55	3.05	3.05502	3.05583	-0.000810185	-0.00502315
56	3.05	3.06141	3.06417	-0.00275463	-0.011412
57	3.09	3.07044	3.07208	-0.00164352	0.0195602
58	3.09	3.08204	3.07958	0.0024537	0.00796296
59	3.09	3.09148	3.08667	0.00481481	-0.00148148
60	3.1	3.09593	3.09375	0.00217593	0.00407407
61	3.1	3.09634	3.10167	-0.00532407	0.00365741
62	3.11	3.10606	3.11042	-0.00435185	0.00393519
63	3.12	3.12461	3.11792	0.00668981	-0.00460648
64	3.12	3.12738	3.12458	0.00280093	-0.00738426
65	3.12	3.13148	3.1325	-0.00101852	-0.0114815
66	3.13	3.13738	3.14042	-0.00303241	-0.00738426
67	3.15	3.14752	3.14833	-0.000810185	0.00247685
68	3.16	3.15391	3.15667	-0.00275463	0.00608796
69	3.16	3.16502	3.16667	-0.00164352	-0.00502315
70	3.18	3.1812	3.17875	0.0024537	-0.0012037
71	3.19	3.19648	3.19167	0.00481481	-0.00648148
72	3.19	3.20718	3.205	0.00217593	-0.0171759
73	3.2	3.21218	3.2175	-0.00532407	-0.0121759
74	3.21	3.22481	3.22917	-0.00435185	-0.0148148
75	3.26	3.24752	3.24083	0.00668981	0.0124769
76	3.27	3.25488	3.25208	0.00280093	0.0151157
77	3.28	3.26148	3.2625	-0.00101852	0.0185185
78	3.29	3.26947	3.2725	-0.00303241	0.0205324
79	3.29	NA	NA	-0.000810185	NA
80	3.3	NA	NA	-0.00275463	NA
81	3.3	NA	NA	-0.00164352	NA
82	3.31	NA	NA	0.0024537	NA
83	3.31	NA	NA	0.00481481	NA
84	3.31	NA	NA	0.00217593	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