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

Sun, 24 Apr 2016 21:33:36 +0100

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/2016/Apr/24/t1461530127agayshh3x47k7lc.htm/, Retrieved Tue, 30 Apr 2024 09:11:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=294659, Retrieved Tue, 30 Apr 2024 09:11:18 +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

117

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

-       [Classical Decomposition] [Uitvoer Belgi�] [2016-04-24 20:33:36] [30ac29e28bcab64021946a7872e1db5d] [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	'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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294659&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294659&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294659&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	'George Udny Yule' @ yule.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	13566.7	NA	NA	0.959079	NA
2	13941.5	NA	NA	0.989014	NA
3	14964.1	NA	NA	1.10301	NA
4	14086	NA	NA	1.0166	NA
5	13505.1	NA	NA	1.01918	NA
6	15300.4	NA	NA	1.04222	NA
7	14725.2	14719	14732.6	0.999077	1.00042
8	12484.9	12987.5	14836.4	0.875381	0.961302
9	16082.6	15450.7	15033.5	1.02775	1.0409
10	15915.8	15870.3	15291.2	1.03787	1.00287
11	15916.1	15552.4	15530.4	1.00141	1.02339
12	15713	14702.7	15819.5	0.929402	1.06872
13	14746	15424.9	16083	0.959079	0.955988
14	15253.2	16136.4	16315.7	0.989014	0.945265
15	18384.3	18283.8	16576.4	1.10301	1.00549
16	16848.5	17095.9	16816.6	1.0166	0.985531
17	16485.5	17362.1	17035.3	1.01918	0.94951
18	19257.1	17924.6	17198.5	1.04222	1.07434
19	17093.4	17390.6	17406.6	0.999077	0.982913
20	15700.1	15519.1	17728.3	0.875381	1.01167
21	19124.3	18562.8	18061.6	1.02775	1.03025
22	18640.8	19024.8	18330.6	1.03787	0.979816
23	18439.2	18663.4	18637.1	1.00141	0.987986
24	17106.3	17547.4	18880.3	0.929402	0.974864
25	18347.7	18236.2	19014.3	0.959079	1.00612
26	19372.7	18970.1	19180.9	0.989014	1.02122
27	22263.8	21274.7	19287.9	1.10301	1.04649
28	19422.9	19681	19359.6	1.0166	0.986885
29	21268.6	19827.6	19454.4	1.01918	1.07268
30	20310	20375.4	19550	1.04222	0.99679
31	19256	19596.4	19614.5	0.999077	0.98263
32	17535.9	17231.6	19684.7	0.875381	1.01766
33	19857.4	20282.2	19734.6	1.02775	0.979057
34	19628.4	20499.2	19751.2	1.03787	0.957518
35	19727.5	19741.2	19713.4	1.00141	0.999305
36	18112.2	18271.2	19659.1	0.929402	0.991295
37	18889.3	18859.8	19664.5	0.959079	1.00156
38	20516.1	19471.2	19687.5	0.989014	1.05366
39	22317	21699.4	19673	1.10301	1.02846
40	19768.8	20022	19695	1.0166	0.987353
41	20015.8	20124	19745.2	1.01918	0.994625
42	20260.5	20549.9	19717.4	1.04222	0.985918
43	19434.3	19681.7	19699.9	0.999077	0.987429
44	17910	17199.2	19647.7	0.875381	1.04133
45	19134.4	20082.5	19540.3	1.02775	0.952788
46	20880.1	20263.5	19524	1.03787	1.03043
47	19680	19596.8	19569.2	1.00141	1.00425
48	17493.4	18185.6	19567	0.929402	0.961936
49	19087.8	18809.8	19612.4	0.959079	1.01478
50	19064.6	19421.6	19637.4	0.989014	0.981617
51	21191	21686.9	19661.6	1.10301	0.977136
52	20503.9	20076.7	19748.8	1.0166	1.02128
53	20364.1	20162	19782.5	1.01918	1.01002
54	19860.4	20682.7	19844.9	1.04222	0.960242
55	20924.1	19910.1	19928.5	0.999077	1.05093
56	17018.8	17502.4	19994	0.875381	0.972371
57	20607.4	20580	20024.3	1.02775	1.00133
58	21500.2	20799.5	20040.5	1.03787	1.03369
59	19868.3	20081.2	20052.9	1.00141	0.989396
60	18801.9	18661.8	20079.3	0.929402	1.00751
61	19787.5	19288.4	20111.4	0.959079	1.02588
62	19936.2	19885.4	20106.2	0.989014	1.00256
63	21047.6	22231.7	20155.6	1.10301	0.946737
64	21034.4	20556	20220.3	1.0166	1.02327
65	20132.8	20596.5	20208.8	1.01918	0.977487
66	20725.3	20997.6	20147	1.04222	0.987034
67	20827.8	NA	NA	0.999077	NA
68	16992.3	NA	NA	0.875381	NA
69	21818.2	NA	NA	1.02775	NA
70	21841.4	NA	NA	1.03787	NA
71	19252.2	NA	NA	1.00141	NA
72	17933.7	NA	NA	0.929402	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 13566.7 & NA & NA & 0.959079 & NA \tabularnewline
2 & 13941.5 & NA & NA & 0.989014 & NA \tabularnewline
3 & 14964.1 & NA & NA & 1.10301 & NA \tabularnewline
4 & 14086 & NA & NA & 1.0166 & NA \tabularnewline
5 & 13505.1 & NA & NA & 1.01918 & NA \tabularnewline
6 & 15300.4 & NA & NA & 1.04222 & NA \tabularnewline
7 & 14725.2 & 14719 & 14732.6 & 0.999077 & 1.00042 \tabularnewline
8 & 12484.9 & 12987.5 & 14836.4 & 0.875381 & 0.961302 \tabularnewline
9 & 16082.6 & 15450.7 & 15033.5 & 1.02775 & 1.0409 \tabularnewline
10 & 15915.8 & 15870.3 & 15291.2 & 1.03787 & 1.00287 \tabularnewline
11 & 15916.1 & 15552.4 & 15530.4 & 1.00141 & 1.02339 \tabularnewline
12 & 15713 & 14702.7 & 15819.5 & 0.929402 & 1.06872 \tabularnewline
13 & 14746 & 15424.9 & 16083 & 0.959079 & 0.955988 \tabularnewline
14 & 15253.2 & 16136.4 & 16315.7 & 0.989014 & 0.945265 \tabularnewline
15 & 18384.3 & 18283.8 & 16576.4 & 1.10301 & 1.00549 \tabularnewline
16 & 16848.5 & 17095.9 & 16816.6 & 1.0166 & 0.985531 \tabularnewline
17 & 16485.5 & 17362.1 & 17035.3 & 1.01918 & 0.94951 \tabularnewline
18 & 19257.1 & 17924.6 & 17198.5 & 1.04222 & 1.07434 \tabularnewline
19 & 17093.4 & 17390.6 & 17406.6 & 0.999077 & 0.982913 \tabularnewline
20 & 15700.1 & 15519.1 & 17728.3 & 0.875381 & 1.01167 \tabularnewline
21 & 19124.3 & 18562.8 & 18061.6 & 1.02775 & 1.03025 \tabularnewline
22 & 18640.8 & 19024.8 & 18330.6 & 1.03787 & 0.979816 \tabularnewline
23 & 18439.2 & 18663.4 & 18637.1 & 1.00141 & 0.987986 \tabularnewline
24 & 17106.3 & 17547.4 & 18880.3 & 0.929402 & 0.974864 \tabularnewline
25 & 18347.7 & 18236.2 & 19014.3 & 0.959079 & 1.00612 \tabularnewline
26 & 19372.7 & 18970.1 & 19180.9 & 0.989014 & 1.02122 \tabularnewline
27 & 22263.8 & 21274.7 & 19287.9 & 1.10301 & 1.04649 \tabularnewline
28 & 19422.9 & 19681 & 19359.6 & 1.0166 & 0.986885 \tabularnewline
29 & 21268.6 & 19827.6 & 19454.4 & 1.01918 & 1.07268 \tabularnewline
30 & 20310 & 20375.4 & 19550 & 1.04222 & 0.99679 \tabularnewline
31 & 19256 & 19596.4 & 19614.5 & 0.999077 & 0.98263 \tabularnewline
32 & 17535.9 & 17231.6 & 19684.7 & 0.875381 & 1.01766 \tabularnewline
33 & 19857.4 & 20282.2 & 19734.6 & 1.02775 & 0.979057 \tabularnewline
34 & 19628.4 & 20499.2 & 19751.2 & 1.03787 & 0.957518 \tabularnewline
35 & 19727.5 & 19741.2 & 19713.4 & 1.00141 & 0.999305 \tabularnewline
36 & 18112.2 & 18271.2 & 19659.1 & 0.929402 & 0.991295 \tabularnewline
37 & 18889.3 & 18859.8 & 19664.5 & 0.959079 & 1.00156 \tabularnewline
38 & 20516.1 & 19471.2 & 19687.5 & 0.989014 & 1.05366 \tabularnewline
39 & 22317 & 21699.4 & 19673 & 1.10301 & 1.02846 \tabularnewline
40 & 19768.8 & 20022 & 19695 & 1.0166 & 0.987353 \tabularnewline
41 & 20015.8 & 20124 & 19745.2 & 1.01918 & 0.994625 \tabularnewline
42 & 20260.5 & 20549.9 & 19717.4 & 1.04222 & 0.985918 \tabularnewline
43 & 19434.3 & 19681.7 & 19699.9 & 0.999077 & 0.987429 \tabularnewline
44 & 17910 & 17199.2 & 19647.7 & 0.875381 & 1.04133 \tabularnewline
45 & 19134.4 & 20082.5 & 19540.3 & 1.02775 & 0.952788 \tabularnewline
46 & 20880.1 & 20263.5 & 19524 & 1.03787 & 1.03043 \tabularnewline
47 & 19680 & 19596.8 & 19569.2 & 1.00141 & 1.00425 \tabularnewline
48 & 17493.4 & 18185.6 & 19567 & 0.929402 & 0.961936 \tabularnewline
49 & 19087.8 & 18809.8 & 19612.4 & 0.959079 & 1.01478 \tabularnewline
50 & 19064.6 & 19421.6 & 19637.4 & 0.989014 & 0.981617 \tabularnewline
51 & 21191 & 21686.9 & 19661.6 & 1.10301 & 0.977136 \tabularnewline
52 & 20503.9 & 20076.7 & 19748.8 & 1.0166 & 1.02128 \tabularnewline
53 & 20364.1 & 20162 & 19782.5 & 1.01918 & 1.01002 \tabularnewline
54 & 19860.4 & 20682.7 & 19844.9 & 1.04222 & 0.960242 \tabularnewline
55 & 20924.1 & 19910.1 & 19928.5 & 0.999077 & 1.05093 \tabularnewline
56 & 17018.8 & 17502.4 & 19994 & 0.875381 & 0.972371 \tabularnewline
57 & 20607.4 & 20580 & 20024.3 & 1.02775 & 1.00133 \tabularnewline
58 & 21500.2 & 20799.5 & 20040.5 & 1.03787 & 1.03369 \tabularnewline
59 & 19868.3 & 20081.2 & 20052.9 & 1.00141 & 0.989396 \tabularnewline
60 & 18801.9 & 18661.8 & 20079.3 & 0.929402 & 1.00751 \tabularnewline
61 & 19787.5 & 19288.4 & 20111.4 & 0.959079 & 1.02588 \tabularnewline
62 & 19936.2 & 19885.4 & 20106.2 & 0.989014 & 1.00256 \tabularnewline
63 & 21047.6 & 22231.7 & 20155.6 & 1.10301 & 0.946737 \tabularnewline
64 & 21034.4 & 20556 & 20220.3 & 1.0166 & 1.02327 \tabularnewline
65 & 20132.8 & 20596.5 & 20208.8 & 1.01918 & 0.977487 \tabularnewline
66 & 20725.3 & 20997.6 & 20147 & 1.04222 & 0.987034 \tabularnewline
67 & 20827.8 & NA & NA & 0.999077 & NA \tabularnewline
68 & 16992.3 & NA & NA & 0.875381 & NA \tabularnewline
69 & 21818.2 & NA & NA & 1.02775 & NA \tabularnewline
70 & 21841.4 & NA & NA & 1.03787 & NA \tabularnewline
71 & 19252.2 & NA & NA & 1.00141 & NA \tabularnewline
72 & 17933.7 & NA & NA & 0.929402 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=294659&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]13566.7[/C][C]NA[/C][C]NA[/C][C]0.959079[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]13941.5[/C][C]NA[/C][C]NA[/C][C]0.989014[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]14964.1[/C][C]NA[/C][C]NA[/C][C]1.10301[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]14086[/C][C]NA[/C][C]NA[/C][C]1.0166[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]13505.1[/C][C]NA[/C][C]NA[/C][C]1.01918[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]15300.4[/C][C]NA[/C][C]NA[/C][C]1.04222[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]14725.2[/C][C]14719[/C][C]14732.6[/C][C]0.999077[/C][C]1.00042[/C][/ROW]
[ROW][C]8[/C][C]12484.9[/C][C]12987.5[/C][C]14836.4[/C][C]0.875381[/C][C]0.961302[/C][/ROW]
[ROW][C]9[/C][C]16082.6[/C][C]15450.7[/C][C]15033.5[/C][C]1.02775[/C][C]1.0409[/C][/ROW]
[ROW][C]10[/C][C]15915.8[/C][C]15870.3[/C][C]15291.2[/C][C]1.03787[/C][C]1.00287[/C][/ROW]
[ROW][C]11[/C][C]15916.1[/C][C]15552.4[/C][C]15530.4[/C][C]1.00141[/C][C]1.02339[/C][/ROW]
[ROW][C]12[/C][C]15713[/C][C]14702.7[/C][C]15819.5[/C][C]0.929402[/C][C]1.06872[/C][/ROW]
[ROW][C]13[/C][C]14746[/C][C]15424.9[/C][C]16083[/C][C]0.959079[/C][C]0.955988[/C][/ROW]
[ROW][C]14[/C][C]15253.2[/C][C]16136.4[/C][C]16315.7[/C][C]0.989014[/C][C]0.945265[/C][/ROW]
[ROW][C]15[/C][C]18384.3[/C][C]18283.8[/C][C]16576.4[/C][C]1.10301[/C][C]1.00549[/C][/ROW]
[ROW][C]16[/C][C]16848.5[/C][C]17095.9[/C][C]16816.6[/C][C]1.0166[/C][C]0.985531[/C][/ROW]
[ROW][C]17[/C][C]16485.5[/C][C]17362.1[/C][C]17035.3[/C][C]1.01918[/C][C]0.94951[/C][/ROW]
[ROW][C]18[/C][C]19257.1[/C][C]17924.6[/C][C]17198.5[/C][C]1.04222[/C][C]1.07434[/C][/ROW]
[ROW][C]19[/C][C]17093.4[/C][C]17390.6[/C][C]17406.6[/C][C]0.999077[/C][C]0.982913[/C][/ROW]
[ROW][C]20[/C][C]15700.1[/C][C]15519.1[/C][C]17728.3[/C][C]0.875381[/C][C]1.01167[/C][/ROW]
[ROW][C]21[/C][C]19124.3[/C][C]18562.8[/C][C]18061.6[/C][C]1.02775[/C][C]1.03025[/C][/ROW]
[ROW][C]22[/C][C]18640.8[/C][C]19024.8[/C][C]18330.6[/C][C]1.03787[/C][C]0.979816[/C][/ROW]
[ROW][C]23[/C][C]18439.2[/C][C]18663.4[/C][C]18637.1[/C][C]1.00141[/C][C]0.987986[/C][/ROW]
[ROW][C]24[/C][C]17106.3[/C][C]17547.4[/C][C]18880.3[/C][C]0.929402[/C][C]0.974864[/C][/ROW]
[ROW][C]25[/C][C]18347.7[/C][C]18236.2[/C][C]19014.3[/C][C]0.959079[/C][C]1.00612[/C][/ROW]
[ROW][C]26[/C][C]19372.7[/C][C]18970.1[/C][C]19180.9[/C][C]0.989014[/C][C]1.02122[/C][/ROW]
[ROW][C]27[/C][C]22263.8[/C][C]21274.7[/C][C]19287.9[/C][C]1.10301[/C][C]1.04649[/C][/ROW]
[ROW][C]28[/C][C]19422.9[/C][C]19681[/C][C]19359.6[/C][C]1.0166[/C][C]0.986885[/C][/ROW]
[ROW][C]29[/C][C]21268.6[/C][C]19827.6[/C][C]19454.4[/C][C]1.01918[/C][C]1.07268[/C][/ROW]
[ROW][C]30[/C][C]20310[/C][C]20375.4[/C][C]19550[/C][C]1.04222[/C][C]0.99679[/C][/ROW]
[ROW][C]31[/C][C]19256[/C][C]19596.4[/C][C]19614.5[/C][C]0.999077[/C][C]0.98263[/C][/ROW]
[ROW][C]32[/C][C]17535.9[/C][C]17231.6[/C][C]19684.7[/C][C]0.875381[/C][C]1.01766[/C][/ROW]
[ROW][C]33[/C][C]19857.4[/C][C]20282.2[/C][C]19734.6[/C][C]1.02775[/C][C]0.979057[/C][/ROW]
[ROW][C]34[/C][C]19628.4[/C][C]20499.2[/C][C]19751.2[/C][C]1.03787[/C][C]0.957518[/C][/ROW]
[ROW][C]35[/C][C]19727.5[/C][C]19741.2[/C][C]19713.4[/C][C]1.00141[/C][C]0.999305[/C][/ROW]
[ROW][C]36[/C][C]18112.2[/C][C]18271.2[/C][C]19659.1[/C][C]0.929402[/C][C]0.991295[/C][/ROW]
[ROW][C]37[/C][C]18889.3[/C][C]18859.8[/C][C]19664.5[/C][C]0.959079[/C][C]1.00156[/C][/ROW]
[ROW][C]38[/C][C]20516.1[/C][C]19471.2[/C][C]19687.5[/C][C]0.989014[/C][C]1.05366[/C][/ROW]
[ROW][C]39[/C][C]22317[/C][C]21699.4[/C][C]19673[/C][C]1.10301[/C][C]1.02846[/C][/ROW]
[ROW][C]40[/C][C]19768.8[/C][C]20022[/C][C]19695[/C][C]1.0166[/C][C]0.987353[/C][/ROW]
[ROW][C]41[/C][C]20015.8[/C][C]20124[/C][C]19745.2[/C][C]1.01918[/C][C]0.994625[/C][/ROW]
[ROW][C]42[/C][C]20260.5[/C][C]20549.9[/C][C]19717.4[/C][C]1.04222[/C][C]0.985918[/C][/ROW]
[ROW][C]43[/C][C]19434.3[/C][C]19681.7[/C][C]19699.9[/C][C]0.999077[/C][C]0.987429[/C][/ROW]
[ROW][C]44[/C][C]17910[/C][C]17199.2[/C][C]19647.7[/C][C]0.875381[/C][C]1.04133[/C][/ROW]
[ROW][C]45[/C][C]19134.4[/C][C]20082.5[/C][C]19540.3[/C][C]1.02775[/C][C]0.952788[/C][/ROW]
[ROW][C]46[/C][C]20880.1[/C][C]20263.5[/C][C]19524[/C][C]1.03787[/C][C]1.03043[/C][/ROW]
[ROW][C]47[/C][C]19680[/C][C]19596.8[/C][C]19569.2[/C][C]1.00141[/C][C]1.00425[/C][/ROW]
[ROW][C]48[/C][C]17493.4[/C][C]18185.6[/C][C]19567[/C][C]0.929402[/C][C]0.961936[/C][/ROW]
[ROW][C]49[/C][C]19087.8[/C][C]18809.8[/C][C]19612.4[/C][C]0.959079[/C][C]1.01478[/C][/ROW]
[ROW][C]50[/C][C]19064.6[/C][C]19421.6[/C][C]19637.4[/C][C]0.989014[/C][C]0.981617[/C][/ROW]
[ROW][C]51[/C][C]21191[/C][C]21686.9[/C][C]19661.6[/C][C]1.10301[/C][C]0.977136[/C][/ROW]
[ROW][C]52[/C][C]20503.9[/C][C]20076.7[/C][C]19748.8[/C][C]1.0166[/C][C]1.02128[/C][/ROW]
[ROW][C]53[/C][C]20364.1[/C][C]20162[/C][C]19782.5[/C][C]1.01918[/C][C]1.01002[/C][/ROW]
[ROW][C]54[/C][C]19860.4[/C][C]20682.7[/C][C]19844.9[/C][C]1.04222[/C][C]0.960242[/C][/ROW]
[ROW][C]55[/C][C]20924.1[/C][C]19910.1[/C][C]19928.5[/C][C]0.999077[/C][C]1.05093[/C][/ROW]
[ROW][C]56[/C][C]17018.8[/C][C]17502.4[/C][C]19994[/C][C]0.875381[/C][C]0.972371[/C][/ROW]
[ROW][C]57[/C][C]20607.4[/C][C]20580[/C][C]20024.3[/C][C]1.02775[/C][C]1.00133[/C][/ROW]
[ROW][C]58[/C][C]21500.2[/C][C]20799.5[/C][C]20040.5[/C][C]1.03787[/C][C]1.03369[/C][/ROW]
[ROW][C]59[/C][C]19868.3[/C][C]20081.2[/C][C]20052.9[/C][C]1.00141[/C][C]0.989396[/C][/ROW]
[ROW][C]60[/C][C]18801.9[/C][C]18661.8[/C][C]20079.3[/C][C]0.929402[/C][C]1.00751[/C][/ROW]
[ROW][C]61[/C][C]19787.5[/C][C]19288.4[/C][C]20111.4[/C][C]0.959079[/C][C]1.02588[/C][/ROW]
[ROW][C]62[/C][C]19936.2[/C][C]19885.4[/C][C]20106.2[/C][C]0.989014[/C][C]1.00256[/C][/ROW]
[ROW][C]63[/C][C]21047.6[/C][C]22231.7[/C][C]20155.6[/C][C]1.10301[/C][C]0.946737[/C][/ROW]
[ROW][C]64[/C][C]21034.4[/C][C]20556[/C][C]20220.3[/C][C]1.0166[/C][C]1.02327[/C][/ROW]
[ROW][C]65[/C][C]20132.8[/C][C]20596.5[/C][C]20208.8[/C][C]1.01918[/C][C]0.977487[/C][/ROW]
[ROW][C]66[/C][C]20725.3[/C][C]20997.6[/C][C]20147[/C][C]1.04222[/C][C]0.987034[/C][/ROW]
[ROW][C]67[/C][C]20827.8[/C][C]NA[/C][C]NA[/C][C]0.999077[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]16992.3[/C][C]NA[/C][C]NA[/C][C]0.875381[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]21818.2[/C][C]NA[/C][C]NA[/C][C]1.02775[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]21841.4[/C][C]NA[/C][C]NA[/C][C]1.03787[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]19252.2[/C][C]NA[/C][C]NA[/C][C]1.00141[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]17933.7[/C][C]NA[/C][C]NA[/C][C]0.929402[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=294659&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=294659&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	13566.7	NA	NA	0.959079	NA
2	13941.5	NA	NA	0.989014	NA
3	14964.1	NA	NA	1.10301	NA
4	14086	NA	NA	1.0166	NA
5	13505.1	NA	NA	1.01918	NA
6	15300.4	NA	NA	1.04222	NA
7	14725.2	14719	14732.6	0.999077	1.00042
8	12484.9	12987.5	14836.4	0.875381	0.961302
9	16082.6	15450.7	15033.5	1.02775	1.0409
10	15915.8	15870.3	15291.2	1.03787	1.00287
11	15916.1	15552.4	15530.4	1.00141	1.02339
12	15713	14702.7	15819.5	0.929402	1.06872
13	14746	15424.9	16083	0.959079	0.955988
14	15253.2	16136.4	16315.7	0.989014	0.945265
15	18384.3	18283.8	16576.4	1.10301	1.00549
16	16848.5	17095.9	16816.6	1.0166	0.985531
17	16485.5	17362.1	17035.3	1.01918	0.94951
18	19257.1	17924.6	17198.5	1.04222	1.07434
19	17093.4	17390.6	17406.6	0.999077	0.982913
20	15700.1	15519.1	17728.3	0.875381	1.01167
21	19124.3	18562.8	18061.6	1.02775	1.03025
22	18640.8	19024.8	18330.6	1.03787	0.979816
23	18439.2	18663.4	18637.1	1.00141	0.987986
24	17106.3	17547.4	18880.3	0.929402	0.974864
25	18347.7	18236.2	19014.3	0.959079	1.00612
26	19372.7	18970.1	19180.9	0.989014	1.02122
27	22263.8	21274.7	19287.9	1.10301	1.04649
28	19422.9	19681	19359.6	1.0166	0.986885
29	21268.6	19827.6	19454.4	1.01918	1.07268
30	20310	20375.4	19550	1.04222	0.99679
31	19256	19596.4	19614.5	0.999077	0.98263
32	17535.9	17231.6	19684.7	0.875381	1.01766
33	19857.4	20282.2	19734.6	1.02775	0.979057
34	19628.4	20499.2	19751.2	1.03787	0.957518
35	19727.5	19741.2	19713.4	1.00141	0.999305
36	18112.2	18271.2	19659.1	0.929402	0.991295
37	18889.3	18859.8	19664.5	0.959079	1.00156
38	20516.1	19471.2	19687.5	0.989014	1.05366
39	22317	21699.4	19673	1.10301	1.02846
40	19768.8	20022	19695	1.0166	0.987353
41	20015.8	20124	19745.2	1.01918	0.994625
42	20260.5	20549.9	19717.4	1.04222	0.985918
43	19434.3	19681.7	19699.9	0.999077	0.987429
44	17910	17199.2	19647.7	0.875381	1.04133
45	19134.4	20082.5	19540.3	1.02775	0.952788
46	20880.1	20263.5	19524	1.03787	1.03043
47	19680	19596.8	19569.2	1.00141	1.00425
48	17493.4	18185.6	19567	0.929402	0.961936
49	19087.8	18809.8	19612.4	0.959079	1.01478
50	19064.6	19421.6	19637.4	0.989014	0.981617
51	21191	21686.9	19661.6	1.10301	0.977136
52	20503.9	20076.7	19748.8	1.0166	1.02128
53	20364.1	20162	19782.5	1.01918	1.01002
54	19860.4	20682.7	19844.9	1.04222	0.960242
55	20924.1	19910.1	19928.5	0.999077	1.05093
56	17018.8	17502.4	19994	0.875381	0.972371
57	20607.4	20580	20024.3	1.02775	1.00133
58	21500.2	20799.5	20040.5	1.03787	1.03369
59	19868.3	20081.2	20052.9	1.00141	0.989396
60	18801.9	18661.8	20079.3	0.929402	1.00751
61	19787.5	19288.4	20111.4	0.959079	1.02588
62	19936.2	19885.4	20106.2	0.989014	1.00256
63	21047.6	22231.7	20155.6	1.10301	0.946737
64	21034.4	20556	20220.3	1.0166	1.02327
65	20132.8	20596.5	20208.8	1.01918	0.977487
66	20725.3	20997.6	20147	1.04222	0.987034
67	20827.8	NA	NA	0.999077	NA
68	16992.3	NA	NA	0.875381	NA
69	21818.2	NA	NA	1.02775	NA
70	21841.4	NA	NA	1.03787	NA
71	19252.2	NA	NA	1.00141	NA
72	17933.7	NA	NA	0.929402	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 <- '12'
par1 <- 'multiplicative'
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