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, 27 Nov 2014 11:56:57 +0000

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/Nov/27/t1417089454c35nx9vw5hgvasz.htm/, Retrieved Sun, 19 May 2024 17:01:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=259810, Retrieved Sun, 19 May 2024 17:01:51 +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

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

-       [Classical Decomposition] [Addititief1] [2014-11-27 11:56:57] [d0f5aeb11a4aa291a6c63b9267d14d48] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259810&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259810&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259810&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	39.66	NA	NA	-0.116285	NA
2	40.05	NA	NA	-0.0867014	NA
3	39.99	NA	NA	-0.103201	NA
4	40.06	NA	NA	-0.166785	NA
5	40.08	NA	NA	-0.0365347	NA
6	40.1	NA	NA	-0.0148681	NA
7	40.1	40.2014	40.1917	0.00971528	-0.101382
8	40.12	40.3131	40.2708	0.0422986	-0.193132
9	40.07	40.4016	40.3438	0.0578819	-0.331632
10	40.24	40.5258	40.4225	0.103299	-0.285799
11	40.58	40.656	40.5129	0.143049	-0.0759653
12	40.72	40.7802	40.6121	0.168132	-0.0602153
13	40.72	40.595	40.7112	-0.116285	0.125035
14	40.89	40.7245	40.8112	-0.0867014	0.165451
15	40.9	40.8114	40.9146	-0.103201	0.0886181
16	41.04	40.8478	41.0146	-0.166785	0.192201
17	41.27	41.0564	41.0929	-0.0365347	0.213618
18	41.29	41.1364	41.1512	-0.0148681	0.153618
19	41.29	41.2151	41.2054	0.00971528	0.0748681
20	41.33	41.2969	41.2546	0.0422986	0.0331181
21	41.34	41.3641	41.3062	0.0578819	-0.0241319
22	41.37	41.4616	41.3583	0.103299	-0.0916319
23	41.33	41.5439	41.4008	0.143049	-0.213882
24	41.37	41.6081	41.44	0.168132	-0.238132
25	41.37	41.362	41.4783	-0.116285	0.00795139
26	41.42	41.4325	41.5192	-0.0867014	-0.0124653
27	41.61	41.4585	41.5617	-0.103201	0.151535
28	41.58	41.4407	41.6075	-0.166785	0.139285
29	41.75	41.6243	41.6608	-0.0365347	0.125701
30	41.75	41.7022	41.7171	-0.0148681	0.0477847
31	41.75	41.7826	41.7729	0.00971528	-0.0326319
32	41.85	41.8698	41.8275	0.0422986	-0.0197986
33	41.84	41.9254	41.8675	0.0578819	-0.0853819
34	41.97	41.9987	41.8954	0.103299	-0.0287153
35	42.01	42.063	41.92	0.143049	-0.0530486
36	42.04	42.1098	41.9417	0.168132	-0.0697986
37	42.04	41.8487	41.965	-0.116285	0.191285
38	42.06	41.9012	41.9879	-0.0867014	0.158785
39	41.93	41.9118	42.015	-0.103201	0.0182014
40	41.93	41.874	42.0408	-0.166785	0.0559514
41	41.99	42.0235	42.06	-0.0365347	-0.0334653
42	42.03	42.0618	42.0767	-0.0148681	-0.0317986
43	42.03	42.1014	42.0917	0.00971528	-0.0713819
44	42.12	42.1494	42.1071	0.0422986	-0.0293819
45	42.22	42.187	42.1292	0.0578819	0.0329514
46	42.21	42.2562	42.1529	0.103299	-0.0462153
47	42.23	42.316	42.1729	0.143049	-0.0859653
48	42.22	42.361	42.1929	0.168132	-0.141049
49	42.22	42.0958	42.2121	-0.116285	0.124201
50	42.25	42.1408	42.2275	-0.0867014	0.109201
51	42.27	42.136	42.2392	-0.103201	0.134035
52	42.16	42.0832	42.25	-0.166785	0.0767847
53	42.24	42.2185	42.255	-0.0365347	0.0215347
54	42.26	42.2405	42.2554	-0.0148681	0.0194514
55	42.26	42.2105	42.2008	0.00971528	0.0494514
56	42.26	42.1319	42.0896	0.0422986	0.128118
57	42.36	42.0329	41.975	0.0578819	0.327118
58	42.33	41.9587	41.8554	0.103299	0.371285
59	42.23	41.8822	41.7392	0.143049	0.347785
60	42.23	41.8019	41.6338	0.168132	0.428118
61	40.9	41.4295	41.5458	-0.116285	-0.529549
62	40.9	41.402	41.4887	-0.0867014	-0.502049
63	40.87	41.3435	41.4467	-0.103201	-0.473465
64	40.69	41.2353	41.4021	-0.166785	-0.545299
65	40.92	41.3285	41.365	-0.0365347	-0.408465
66	41.05	41.3201	41.335	-0.0148681	-0.270132
67	41.36	NA	NA	0.00971528	NA
68	41.79	NA	NA	0.0422986	NA
69	41.82	NA	NA	0.0578819	NA
70	41.8	NA	NA	0.103299	NA
71	41.87	NA	NA	0.143049	NA
72	41.87	NA	NA	0.168132	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 39.66 & NA & NA & -0.116285 & NA \tabularnewline
2 & 40.05 & NA & NA & -0.0867014 & NA \tabularnewline
3 & 39.99 & NA & NA & -0.103201 & NA \tabularnewline
4 & 40.06 & NA & NA & -0.166785 & NA \tabularnewline
5 & 40.08 & NA & NA & -0.0365347 & NA \tabularnewline
6 & 40.1 & NA & NA & -0.0148681 & NA \tabularnewline
7 & 40.1 & 40.2014 & 40.1917 & 0.00971528 & -0.101382 \tabularnewline
8 & 40.12 & 40.3131 & 40.2708 & 0.0422986 & -0.193132 \tabularnewline
9 & 40.07 & 40.4016 & 40.3438 & 0.0578819 & -0.331632 \tabularnewline
10 & 40.24 & 40.5258 & 40.4225 & 0.103299 & -0.285799 \tabularnewline
11 & 40.58 & 40.656 & 40.5129 & 0.143049 & -0.0759653 \tabularnewline
12 & 40.72 & 40.7802 & 40.6121 & 0.168132 & -0.0602153 \tabularnewline
13 & 40.72 & 40.595 & 40.7112 & -0.116285 & 0.125035 \tabularnewline
14 & 40.89 & 40.7245 & 40.8112 & -0.0867014 & 0.165451 \tabularnewline
15 & 40.9 & 40.8114 & 40.9146 & -0.103201 & 0.0886181 \tabularnewline
16 & 41.04 & 40.8478 & 41.0146 & -0.166785 & 0.192201 \tabularnewline
17 & 41.27 & 41.0564 & 41.0929 & -0.0365347 & 0.213618 \tabularnewline
18 & 41.29 & 41.1364 & 41.1512 & -0.0148681 & 0.153618 \tabularnewline
19 & 41.29 & 41.2151 & 41.2054 & 0.00971528 & 0.0748681 \tabularnewline
20 & 41.33 & 41.2969 & 41.2546 & 0.0422986 & 0.0331181 \tabularnewline
21 & 41.34 & 41.3641 & 41.3062 & 0.0578819 & -0.0241319 \tabularnewline
22 & 41.37 & 41.4616 & 41.3583 & 0.103299 & -0.0916319 \tabularnewline
23 & 41.33 & 41.5439 & 41.4008 & 0.143049 & -0.213882 \tabularnewline
24 & 41.37 & 41.6081 & 41.44 & 0.168132 & -0.238132 \tabularnewline
25 & 41.37 & 41.362 & 41.4783 & -0.116285 & 0.00795139 \tabularnewline
26 & 41.42 & 41.4325 & 41.5192 & -0.0867014 & -0.0124653 \tabularnewline
27 & 41.61 & 41.4585 & 41.5617 & -0.103201 & 0.151535 \tabularnewline
28 & 41.58 & 41.4407 & 41.6075 & -0.166785 & 0.139285 \tabularnewline
29 & 41.75 & 41.6243 & 41.6608 & -0.0365347 & 0.125701 \tabularnewline
30 & 41.75 & 41.7022 & 41.7171 & -0.0148681 & 0.0477847 \tabularnewline
31 & 41.75 & 41.7826 & 41.7729 & 0.00971528 & -0.0326319 \tabularnewline
32 & 41.85 & 41.8698 & 41.8275 & 0.0422986 & -0.0197986 \tabularnewline
33 & 41.84 & 41.9254 & 41.8675 & 0.0578819 & -0.0853819 \tabularnewline
34 & 41.97 & 41.9987 & 41.8954 & 0.103299 & -0.0287153 \tabularnewline
35 & 42.01 & 42.063 & 41.92 & 0.143049 & -0.0530486 \tabularnewline
36 & 42.04 & 42.1098 & 41.9417 & 0.168132 & -0.0697986 \tabularnewline
37 & 42.04 & 41.8487 & 41.965 & -0.116285 & 0.191285 \tabularnewline
38 & 42.06 & 41.9012 & 41.9879 & -0.0867014 & 0.158785 \tabularnewline
39 & 41.93 & 41.9118 & 42.015 & -0.103201 & 0.0182014 \tabularnewline
40 & 41.93 & 41.874 & 42.0408 & -0.166785 & 0.0559514 \tabularnewline
41 & 41.99 & 42.0235 & 42.06 & -0.0365347 & -0.0334653 \tabularnewline
42 & 42.03 & 42.0618 & 42.0767 & -0.0148681 & -0.0317986 \tabularnewline
43 & 42.03 & 42.1014 & 42.0917 & 0.00971528 & -0.0713819 \tabularnewline
44 & 42.12 & 42.1494 & 42.1071 & 0.0422986 & -0.0293819 \tabularnewline
45 & 42.22 & 42.187 & 42.1292 & 0.0578819 & 0.0329514 \tabularnewline
46 & 42.21 & 42.2562 & 42.1529 & 0.103299 & -0.0462153 \tabularnewline
47 & 42.23 & 42.316 & 42.1729 & 0.143049 & -0.0859653 \tabularnewline
48 & 42.22 & 42.361 & 42.1929 & 0.168132 & -0.141049 \tabularnewline
49 & 42.22 & 42.0958 & 42.2121 & -0.116285 & 0.124201 \tabularnewline
50 & 42.25 & 42.1408 & 42.2275 & -0.0867014 & 0.109201 \tabularnewline
51 & 42.27 & 42.136 & 42.2392 & -0.103201 & 0.134035 \tabularnewline
52 & 42.16 & 42.0832 & 42.25 & -0.166785 & 0.0767847 \tabularnewline
53 & 42.24 & 42.2185 & 42.255 & -0.0365347 & 0.0215347 \tabularnewline
54 & 42.26 & 42.2405 & 42.2554 & -0.0148681 & 0.0194514 \tabularnewline
55 & 42.26 & 42.2105 & 42.2008 & 0.00971528 & 0.0494514 \tabularnewline
56 & 42.26 & 42.1319 & 42.0896 & 0.0422986 & 0.128118 \tabularnewline
57 & 42.36 & 42.0329 & 41.975 & 0.0578819 & 0.327118 \tabularnewline
58 & 42.33 & 41.9587 & 41.8554 & 0.103299 & 0.371285 \tabularnewline
59 & 42.23 & 41.8822 & 41.7392 & 0.143049 & 0.347785 \tabularnewline
60 & 42.23 & 41.8019 & 41.6338 & 0.168132 & 0.428118 \tabularnewline
61 & 40.9 & 41.4295 & 41.5458 & -0.116285 & -0.529549 \tabularnewline
62 & 40.9 & 41.402 & 41.4887 & -0.0867014 & -0.502049 \tabularnewline
63 & 40.87 & 41.3435 & 41.4467 & -0.103201 & -0.473465 \tabularnewline
64 & 40.69 & 41.2353 & 41.4021 & -0.166785 & -0.545299 \tabularnewline
65 & 40.92 & 41.3285 & 41.365 & -0.0365347 & -0.408465 \tabularnewline
66 & 41.05 & 41.3201 & 41.335 & -0.0148681 & -0.270132 \tabularnewline
67 & 41.36 & NA & NA & 0.00971528 & NA \tabularnewline
68 & 41.79 & NA & NA & 0.0422986 & NA \tabularnewline
69 & 41.82 & NA & NA & 0.0578819 & NA \tabularnewline
70 & 41.8 & NA & NA & 0.103299 & NA \tabularnewline
71 & 41.87 & NA & NA & 0.143049 & NA \tabularnewline
72 & 41.87 & NA & NA & 0.168132 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=259810&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]39.66[/C][C]NA[/C][C]NA[/C][C]-0.116285[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]40.05[/C][C]NA[/C][C]NA[/C][C]-0.0867014[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]39.99[/C][C]NA[/C][C]NA[/C][C]-0.103201[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]40.06[/C][C]NA[/C][C]NA[/C][C]-0.166785[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]40.08[/C][C]NA[/C][C]NA[/C][C]-0.0365347[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]40.1[/C][C]NA[/C][C]NA[/C][C]-0.0148681[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]40.1[/C][C]40.2014[/C][C]40.1917[/C][C]0.00971528[/C][C]-0.101382[/C][/ROW]
[ROW][C]8[/C][C]40.12[/C][C]40.3131[/C][C]40.2708[/C][C]0.0422986[/C][C]-0.193132[/C][/ROW]
[ROW][C]9[/C][C]40.07[/C][C]40.4016[/C][C]40.3438[/C][C]0.0578819[/C][C]-0.331632[/C][/ROW]
[ROW][C]10[/C][C]40.24[/C][C]40.5258[/C][C]40.4225[/C][C]0.103299[/C][C]-0.285799[/C][/ROW]
[ROW][C]11[/C][C]40.58[/C][C]40.656[/C][C]40.5129[/C][C]0.143049[/C][C]-0.0759653[/C][/ROW]
[ROW][C]12[/C][C]40.72[/C][C]40.7802[/C][C]40.6121[/C][C]0.168132[/C][C]-0.0602153[/C][/ROW]
[ROW][C]13[/C][C]40.72[/C][C]40.595[/C][C]40.7112[/C][C]-0.116285[/C][C]0.125035[/C][/ROW]
[ROW][C]14[/C][C]40.89[/C][C]40.7245[/C][C]40.8112[/C][C]-0.0867014[/C][C]0.165451[/C][/ROW]
[ROW][C]15[/C][C]40.9[/C][C]40.8114[/C][C]40.9146[/C][C]-0.103201[/C][C]0.0886181[/C][/ROW]
[ROW][C]16[/C][C]41.04[/C][C]40.8478[/C][C]41.0146[/C][C]-0.166785[/C][C]0.192201[/C][/ROW]
[ROW][C]17[/C][C]41.27[/C][C]41.0564[/C][C]41.0929[/C][C]-0.0365347[/C][C]0.213618[/C][/ROW]
[ROW][C]18[/C][C]41.29[/C][C]41.1364[/C][C]41.1512[/C][C]-0.0148681[/C][C]0.153618[/C][/ROW]
[ROW][C]19[/C][C]41.29[/C][C]41.2151[/C][C]41.2054[/C][C]0.00971528[/C][C]0.0748681[/C][/ROW]
[ROW][C]20[/C][C]41.33[/C][C]41.2969[/C][C]41.2546[/C][C]0.0422986[/C][C]0.0331181[/C][/ROW]
[ROW][C]21[/C][C]41.34[/C][C]41.3641[/C][C]41.3062[/C][C]0.0578819[/C][C]-0.0241319[/C][/ROW]
[ROW][C]22[/C][C]41.37[/C][C]41.4616[/C][C]41.3583[/C][C]0.103299[/C][C]-0.0916319[/C][/ROW]
[ROW][C]23[/C][C]41.33[/C][C]41.5439[/C][C]41.4008[/C][C]0.143049[/C][C]-0.213882[/C][/ROW]
[ROW][C]24[/C][C]41.37[/C][C]41.6081[/C][C]41.44[/C][C]0.168132[/C][C]-0.238132[/C][/ROW]
[ROW][C]25[/C][C]41.37[/C][C]41.362[/C][C]41.4783[/C][C]-0.116285[/C][C]0.00795139[/C][/ROW]
[ROW][C]26[/C][C]41.42[/C][C]41.4325[/C][C]41.5192[/C][C]-0.0867014[/C][C]-0.0124653[/C][/ROW]
[ROW][C]27[/C][C]41.61[/C][C]41.4585[/C][C]41.5617[/C][C]-0.103201[/C][C]0.151535[/C][/ROW]
[ROW][C]28[/C][C]41.58[/C][C]41.4407[/C][C]41.6075[/C][C]-0.166785[/C][C]0.139285[/C][/ROW]
[ROW][C]29[/C][C]41.75[/C][C]41.6243[/C][C]41.6608[/C][C]-0.0365347[/C][C]0.125701[/C][/ROW]
[ROW][C]30[/C][C]41.75[/C][C]41.7022[/C][C]41.7171[/C][C]-0.0148681[/C][C]0.0477847[/C][/ROW]
[ROW][C]31[/C][C]41.75[/C][C]41.7826[/C][C]41.7729[/C][C]0.00971528[/C][C]-0.0326319[/C][/ROW]
[ROW][C]32[/C][C]41.85[/C][C]41.8698[/C][C]41.8275[/C][C]0.0422986[/C][C]-0.0197986[/C][/ROW]
[ROW][C]33[/C][C]41.84[/C][C]41.9254[/C][C]41.8675[/C][C]0.0578819[/C][C]-0.0853819[/C][/ROW]
[ROW][C]34[/C][C]41.97[/C][C]41.9987[/C][C]41.8954[/C][C]0.103299[/C][C]-0.0287153[/C][/ROW]
[ROW][C]35[/C][C]42.01[/C][C]42.063[/C][C]41.92[/C][C]0.143049[/C][C]-0.0530486[/C][/ROW]
[ROW][C]36[/C][C]42.04[/C][C]42.1098[/C][C]41.9417[/C][C]0.168132[/C][C]-0.0697986[/C][/ROW]
[ROW][C]37[/C][C]42.04[/C][C]41.8487[/C][C]41.965[/C][C]-0.116285[/C][C]0.191285[/C][/ROW]
[ROW][C]38[/C][C]42.06[/C][C]41.9012[/C][C]41.9879[/C][C]-0.0867014[/C][C]0.158785[/C][/ROW]
[ROW][C]39[/C][C]41.93[/C][C]41.9118[/C][C]42.015[/C][C]-0.103201[/C][C]0.0182014[/C][/ROW]
[ROW][C]40[/C][C]41.93[/C][C]41.874[/C][C]42.0408[/C][C]-0.166785[/C][C]0.0559514[/C][/ROW]
[ROW][C]41[/C][C]41.99[/C][C]42.0235[/C][C]42.06[/C][C]-0.0365347[/C][C]-0.0334653[/C][/ROW]
[ROW][C]42[/C][C]42.03[/C][C]42.0618[/C][C]42.0767[/C][C]-0.0148681[/C][C]-0.0317986[/C][/ROW]
[ROW][C]43[/C][C]42.03[/C][C]42.1014[/C][C]42.0917[/C][C]0.00971528[/C][C]-0.0713819[/C][/ROW]
[ROW][C]44[/C][C]42.12[/C][C]42.1494[/C][C]42.1071[/C][C]0.0422986[/C][C]-0.0293819[/C][/ROW]
[ROW][C]45[/C][C]42.22[/C][C]42.187[/C][C]42.1292[/C][C]0.0578819[/C][C]0.0329514[/C][/ROW]
[ROW][C]46[/C][C]42.21[/C][C]42.2562[/C][C]42.1529[/C][C]0.103299[/C][C]-0.0462153[/C][/ROW]
[ROW][C]47[/C][C]42.23[/C][C]42.316[/C][C]42.1729[/C][C]0.143049[/C][C]-0.0859653[/C][/ROW]
[ROW][C]48[/C][C]42.22[/C][C]42.361[/C][C]42.1929[/C][C]0.168132[/C][C]-0.141049[/C][/ROW]
[ROW][C]49[/C][C]42.22[/C][C]42.0958[/C][C]42.2121[/C][C]-0.116285[/C][C]0.124201[/C][/ROW]
[ROW][C]50[/C][C]42.25[/C][C]42.1408[/C][C]42.2275[/C][C]-0.0867014[/C][C]0.109201[/C][/ROW]
[ROW][C]51[/C][C]42.27[/C][C]42.136[/C][C]42.2392[/C][C]-0.103201[/C][C]0.134035[/C][/ROW]
[ROW][C]52[/C][C]42.16[/C][C]42.0832[/C][C]42.25[/C][C]-0.166785[/C][C]0.0767847[/C][/ROW]
[ROW][C]53[/C][C]42.24[/C][C]42.2185[/C][C]42.255[/C][C]-0.0365347[/C][C]0.0215347[/C][/ROW]
[ROW][C]54[/C][C]42.26[/C][C]42.2405[/C][C]42.2554[/C][C]-0.0148681[/C][C]0.0194514[/C][/ROW]
[ROW][C]55[/C][C]42.26[/C][C]42.2105[/C][C]42.2008[/C][C]0.00971528[/C][C]0.0494514[/C][/ROW]
[ROW][C]56[/C][C]42.26[/C][C]42.1319[/C][C]42.0896[/C][C]0.0422986[/C][C]0.128118[/C][/ROW]
[ROW][C]57[/C][C]42.36[/C][C]42.0329[/C][C]41.975[/C][C]0.0578819[/C][C]0.327118[/C][/ROW]
[ROW][C]58[/C][C]42.33[/C][C]41.9587[/C][C]41.8554[/C][C]0.103299[/C][C]0.371285[/C][/ROW]
[ROW][C]59[/C][C]42.23[/C][C]41.8822[/C][C]41.7392[/C][C]0.143049[/C][C]0.347785[/C][/ROW]
[ROW][C]60[/C][C]42.23[/C][C]41.8019[/C][C]41.6338[/C][C]0.168132[/C][C]0.428118[/C][/ROW]
[ROW][C]61[/C][C]40.9[/C][C]41.4295[/C][C]41.5458[/C][C]-0.116285[/C][C]-0.529549[/C][/ROW]
[ROW][C]62[/C][C]40.9[/C][C]41.402[/C][C]41.4887[/C][C]-0.0867014[/C][C]-0.502049[/C][/ROW]
[ROW][C]63[/C][C]40.87[/C][C]41.3435[/C][C]41.4467[/C][C]-0.103201[/C][C]-0.473465[/C][/ROW]
[ROW][C]64[/C][C]40.69[/C][C]41.2353[/C][C]41.4021[/C][C]-0.166785[/C][C]-0.545299[/C][/ROW]
[ROW][C]65[/C][C]40.92[/C][C]41.3285[/C][C]41.365[/C][C]-0.0365347[/C][C]-0.408465[/C][/ROW]
[ROW][C]66[/C][C]41.05[/C][C]41.3201[/C][C]41.335[/C][C]-0.0148681[/C][C]-0.270132[/C][/ROW]
[ROW][C]67[/C][C]41.36[/C][C]NA[/C][C]NA[/C][C]0.00971528[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]41.79[/C][C]NA[/C][C]NA[/C][C]0.0422986[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]41.82[/C][C]NA[/C][C]NA[/C][C]0.0578819[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]41.8[/C][C]NA[/C][C]NA[/C][C]0.103299[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]41.87[/C][C]NA[/C][C]NA[/C][C]0.143049[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]41.87[/C][C]NA[/C][C]NA[/C][C]0.168132[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=259810&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=259810&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	39.66	NA	NA	-0.116285	NA
2	40.05	NA	NA	-0.0867014	NA
3	39.99	NA	NA	-0.103201	NA
4	40.06	NA	NA	-0.166785	NA
5	40.08	NA	NA	-0.0365347	NA
6	40.1	NA	NA	-0.0148681	NA
7	40.1	40.2014	40.1917	0.00971528	-0.101382
8	40.12	40.3131	40.2708	0.0422986	-0.193132
9	40.07	40.4016	40.3438	0.0578819	-0.331632
10	40.24	40.5258	40.4225	0.103299	-0.285799
11	40.58	40.656	40.5129	0.143049	-0.0759653
12	40.72	40.7802	40.6121	0.168132	-0.0602153
13	40.72	40.595	40.7112	-0.116285	0.125035
14	40.89	40.7245	40.8112	-0.0867014	0.165451
15	40.9	40.8114	40.9146	-0.103201	0.0886181
16	41.04	40.8478	41.0146	-0.166785	0.192201
17	41.27	41.0564	41.0929	-0.0365347	0.213618
18	41.29	41.1364	41.1512	-0.0148681	0.153618
19	41.29	41.2151	41.2054	0.00971528	0.0748681
20	41.33	41.2969	41.2546	0.0422986	0.0331181
21	41.34	41.3641	41.3062	0.0578819	-0.0241319
22	41.37	41.4616	41.3583	0.103299	-0.0916319
23	41.33	41.5439	41.4008	0.143049	-0.213882
24	41.37	41.6081	41.44	0.168132	-0.238132
25	41.37	41.362	41.4783	-0.116285	0.00795139
26	41.42	41.4325	41.5192	-0.0867014	-0.0124653
27	41.61	41.4585	41.5617	-0.103201	0.151535
28	41.58	41.4407	41.6075	-0.166785	0.139285
29	41.75	41.6243	41.6608	-0.0365347	0.125701
30	41.75	41.7022	41.7171	-0.0148681	0.0477847
31	41.75	41.7826	41.7729	0.00971528	-0.0326319
32	41.85	41.8698	41.8275	0.0422986	-0.0197986
33	41.84	41.9254	41.8675	0.0578819	-0.0853819
34	41.97	41.9987	41.8954	0.103299	-0.0287153
35	42.01	42.063	41.92	0.143049	-0.0530486
36	42.04	42.1098	41.9417	0.168132	-0.0697986
37	42.04	41.8487	41.965	-0.116285	0.191285
38	42.06	41.9012	41.9879	-0.0867014	0.158785
39	41.93	41.9118	42.015	-0.103201	0.0182014
40	41.93	41.874	42.0408	-0.166785	0.0559514
41	41.99	42.0235	42.06	-0.0365347	-0.0334653
42	42.03	42.0618	42.0767	-0.0148681	-0.0317986
43	42.03	42.1014	42.0917	0.00971528	-0.0713819
44	42.12	42.1494	42.1071	0.0422986	-0.0293819
45	42.22	42.187	42.1292	0.0578819	0.0329514
46	42.21	42.2562	42.1529	0.103299	-0.0462153
47	42.23	42.316	42.1729	0.143049	-0.0859653
48	42.22	42.361	42.1929	0.168132	-0.141049
49	42.22	42.0958	42.2121	-0.116285	0.124201
50	42.25	42.1408	42.2275	-0.0867014	0.109201
51	42.27	42.136	42.2392	-0.103201	0.134035
52	42.16	42.0832	42.25	-0.166785	0.0767847
53	42.24	42.2185	42.255	-0.0365347	0.0215347
54	42.26	42.2405	42.2554	-0.0148681	0.0194514
55	42.26	42.2105	42.2008	0.00971528	0.0494514
56	42.26	42.1319	42.0896	0.0422986	0.128118
57	42.36	42.0329	41.975	0.0578819	0.327118
58	42.33	41.9587	41.8554	0.103299	0.371285
59	42.23	41.8822	41.7392	0.143049	0.347785
60	42.23	41.8019	41.6338	0.168132	0.428118
61	40.9	41.4295	41.5458	-0.116285	-0.529549
62	40.9	41.402	41.4887	-0.0867014	-0.502049
63	40.87	41.3435	41.4467	-0.103201	-0.473465
64	40.69	41.2353	41.4021	-0.166785	-0.545299
65	40.92	41.3285	41.365	-0.0365347	-0.408465
66	41.05	41.3201	41.335	-0.0148681	-0.270132
67	41.36	NA	NA	0.00971528	NA
68	41.79	NA	NA	0.0422986	NA
69	41.82	NA	NA	0.0578819	NA
70	41.8	NA	NA	0.103299	NA
71	41.87	NA	NA	0.143049	NA
72	41.87	NA	NA	0.168132	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