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

Wed, 03 Jun 2009 07:06:50 -0600

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/2009/Jun/03/t1244034495uhifymzfqnthrd0.htm/, Retrieved Sat, 11 May 2024 20:17:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=41481, Retrieved Sat, 11 May 2024 20:17:24 +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

118

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

-       [Classical Decomposition] [decompositie prij...] [2009-06-03 13:06:50] [16e291b2db388e9b7dc52bb84b5ee0ff] [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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41481&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41481&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41481&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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	106.8	NA	NA	0.943353544186046	NA
2	114.3	NA	NA	0.941668404876309	NA
3	105.7	NA	NA	0.989597587183469	NA
4	90.1	NA	NA	1.01967889364651	NA
5	91.6	NA	NA	1.04339512685611	NA
6	97.7	NA	NA	1.07713444164794	NA
7	100.8	105.824066266178	102.133333333333	1.03613641905527	0.952524350618494
8	104.6	107.398046286489	102.404166666667	1.04876637135360	0.97394695356911
9	95.9	102.495342509423	103.108333333333	0.994054885729477	0.93565227113791
10	102.7	104.753994769180	105.291666666667	0.994893499984301	0.980392205817962
11	104	105.038444304931	108.666666666667	0.966611450658877	0.99011367398096
12	107.9	105.897984628496	112.095833333333	0.944709374822101	1.01890513193927
13	113.8	108.725426607209	115.254166666667	0.943353544186046	1.04667329024262
14	113.8	111.944755248025	118.879166666667	0.941668404876309	1.01657285995994
15	123.1	121.856572891804	123.1375	0.989597587183469	1.01020402165175
16	125.1	130.629363600231	128.108333333333	1.01967889364651	0.957671357741949
17	137.6	138.615042602835	132.85	1.04339512685611	0.992677255052737
18	134	146.835864697481	136.320833333333	1.07713444164794	0.912583586278963
19	140.3	144.47195469694	139.433333333333	1.03613641905527	0.971122736549862
20	152.1	149.960481523922	142.9875	1.04876637135360	1.01426721529789
21	150.6	146.382865714380	147.258333333333	0.994054885729477	1.02880893378497
22	167.3	151.232102776780	152.008333333333	0.994893499984301	1.1062466032555
23	153.2	150.598064012653	155.8	0.966611450658877	1.01727735349326
24	142	150.838596846596	159.666666666667	0.944709374822101	0.94140361266033
25	154.4	155.220964416279	164.541666666667	0.943353544186046	0.994710995261714
26	158.5	159.742274032205	169.6375	0.941668404876309	0.99222326062571
27	180.9	173.109481261348	174.929166666667	0.989597587183469	1.04500342027419
28	181.3	182.531019286838	179.008333333333	1.01967889364651	0.993255835136144
29	172.4	189.884870648727	181.9875	1.04339512685611	0.907918568820196
30	192	200.122603137839	185.791666666667	1.07713444164794	0.959411865474063
31	199.3	197.483284236855	190.595833333333	1.03613641905527	1.00919933942847
32	215.4	204.793483306193	195.270833333333	1.04876637135360	1.05179128028185
33	214.3	197.593259910877	198.775	0.994054885729477	1.08455116382340
34	201.5	201.478369915571	202.5125	0.994893499984301	1.00010735685641
35	190.5	200.708812633894	207.641666666667	0.966611450658877	0.949136201346
36	196	200.585418009103	212.325	0.944709374822101	0.97713982374883
37	215.7	204.149568241395	216.408333333333	0.943353544186046	1.05657828159081
38	209.4	207.143507362666	219.975	0.941668404876309	1.01089337853773
39	214.1	219.10927577226	221.4125	0.989597587183469	0.97713800223836
40	237.8	225.803642335962	221.445833333333	1.01967889364651	1.05312738776016
41	239	231.590243365105	221.958333333333	1.04339512685611	1.03199511571484
42	237.8	240.461287977555	223.241666666667	1.07713444164794	0.988932572057907
43	251.5	230.937538867102	222.883333333333	1.03613641905527	1.08903905893243
44	248.8	232.301751254821	221.5	1.04876637135360	1.07102076784209
45	215.4	219.88494072336	221.2	0.994054885729477	0.979603238363637
46	201.2	219.651757848617	220.779166666667	0.994893499984301	0.91599540095038
47	203.1	212.598133476998	219.941666666667	0.966611450658877	0.955323533082545
48	214.2	207.477860156242	219.620833333333	0.944709374822101	1.03239931161183
49	188.9	207.588878037907	220.054166666667	0.943353544186046	0.90997167953047
50	203	207.492709396141	220.345833333333	0.941668404876309	0.978347627686698
51	213.3	220.259682967361	222.575	0.989597587183469	0.968402374535371
52	228.5	232.996627198226	228.5	1.01967889364651	0.980700891457966
53	228.2	247.488976610575	237.195833333333	1.04339512685611	0.922061269658382
54	240.9	265.513639866216	246.5	1.07713444164794	0.907298021003297
55	258.8	265.635157200216	256.370833333333	1.03613641905527	0.974268627420188
56	248.5	280.750387751477	267.695833333333	1.04876637135360	0.885127895958508
57	269.2	278.231820620323	279.895833333333	0.994054885729477	0.967538505839531
58	289.6	291.520377053733	293.016666666667	0.994893499984301	0.993412546069192
59	323.4	298.256018196219	308.558333333333	0.966611450658877	1.08430335104668
60	317.2	309.069544551174	327.158333333333	0.944709374822101	1.02630623298919
61	322.8	326.647956593721	346.2625	0.943353544186046	0.988219866323833
62	340.9	341.543130448637	362.7	0.941668404876309	0.998116986139372
63	368.2	369.899208119341	373.7875	0.989597587183469	0.995406294249777
64	388.5	384.121536560752	376.708333333333	1.01967889364651	1.01139864085323
65	441.2	386.508334825066	370.433333333333	1.04339512685611	1.14150190370329
66	474.3	386.26041077495	358.6	1.07713444164794	1.22792806813522
67	483.9	NA	NA	1.03613641905527	NA
68	417.9	NA	NA	1.04876637135360	NA
69	365.9	NA	NA	0.994054885729477	NA
70	263	NA	NA	0.994893499984301	NA
71	199.4	NA	NA	0.966611450658877	NA
72	157.2	NA	NA	0.944709374822101	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 106.8 & NA & NA & 0.943353544186046 & NA \tabularnewline
2 & 114.3 & NA & NA & 0.941668404876309 & NA \tabularnewline
3 & 105.7 & NA & NA & 0.989597587183469 & NA \tabularnewline
4 & 90.1 & NA & NA & 1.01967889364651 & NA \tabularnewline
5 & 91.6 & NA & NA & 1.04339512685611 & NA \tabularnewline
6 & 97.7 & NA & NA & 1.07713444164794 & NA \tabularnewline
7 & 100.8 & 105.824066266178 & 102.133333333333 & 1.03613641905527 & 0.952524350618494 \tabularnewline
8 & 104.6 & 107.398046286489 & 102.404166666667 & 1.04876637135360 & 0.97394695356911 \tabularnewline
9 & 95.9 & 102.495342509423 & 103.108333333333 & 0.994054885729477 & 0.93565227113791 \tabularnewline
10 & 102.7 & 104.753994769180 & 105.291666666667 & 0.994893499984301 & 0.980392205817962 \tabularnewline
11 & 104 & 105.038444304931 & 108.666666666667 & 0.966611450658877 & 0.99011367398096 \tabularnewline
12 & 107.9 & 105.897984628496 & 112.095833333333 & 0.944709374822101 & 1.01890513193927 \tabularnewline
13 & 113.8 & 108.725426607209 & 115.254166666667 & 0.943353544186046 & 1.04667329024262 \tabularnewline
14 & 113.8 & 111.944755248025 & 118.879166666667 & 0.941668404876309 & 1.01657285995994 \tabularnewline
15 & 123.1 & 121.856572891804 & 123.1375 & 0.989597587183469 & 1.01020402165175 \tabularnewline
16 & 125.1 & 130.629363600231 & 128.108333333333 & 1.01967889364651 & 0.957671357741949 \tabularnewline
17 & 137.6 & 138.615042602835 & 132.85 & 1.04339512685611 & 0.992677255052737 \tabularnewline
18 & 134 & 146.835864697481 & 136.320833333333 & 1.07713444164794 & 0.912583586278963 \tabularnewline
19 & 140.3 & 144.47195469694 & 139.433333333333 & 1.03613641905527 & 0.971122736549862 \tabularnewline
20 & 152.1 & 149.960481523922 & 142.9875 & 1.04876637135360 & 1.01426721529789 \tabularnewline
21 & 150.6 & 146.382865714380 & 147.258333333333 & 0.994054885729477 & 1.02880893378497 \tabularnewline
22 & 167.3 & 151.232102776780 & 152.008333333333 & 0.994893499984301 & 1.1062466032555 \tabularnewline
23 & 153.2 & 150.598064012653 & 155.8 & 0.966611450658877 & 1.01727735349326 \tabularnewline
24 & 142 & 150.838596846596 & 159.666666666667 & 0.944709374822101 & 0.94140361266033 \tabularnewline
25 & 154.4 & 155.220964416279 & 164.541666666667 & 0.943353544186046 & 0.994710995261714 \tabularnewline
26 & 158.5 & 159.742274032205 & 169.6375 & 0.941668404876309 & 0.99222326062571 \tabularnewline
27 & 180.9 & 173.109481261348 & 174.929166666667 & 0.989597587183469 & 1.04500342027419 \tabularnewline
28 & 181.3 & 182.531019286838 & 179.008333333333 & 1.01967889364651 & 0.993255835136144 \tabularnewline
29 & 172.4 & 189.884870648727 & 181.9875 & 1.04339512685611 & 0.907918568820196 \tabularnewline
30 & 192 & 200.122603137839 & 185.791666666667 & 1.07713444164794 & 0.959411865474063 \tabularnewline
31 & 199.3 & 197.483284236855 & 190.595833333333 & 1.03613641905527 & 1.00919933942847 \tabularnewline
32 & 215.4 & 204.793483306193 & 195.270833333333 & 1.04876637135360 & 1.05179128028185 \tabularnewline
33 & 214.3 & 197.593259910877 & 198.775 & 0.994054885729477 & 1.08455116382340 \tabularnewline
34 & 201.5 & 201.478369915571 & 202.5125 & 0.994893499984301 & 1.00010735685641 \tabularnewline
35 & 190.5 & 200.708812633894 & 207.641666666667 & 0.966611450658877 & 0.949136201346 \tabularnewline
36 & 196 & 200.585418009103 & 212.325 & 0.944709374822101 & 0.97713982374883 \tabularnewline
37 & 215.7 & 204.149568241395 & 216.408333333333 & 0.943353544186046 & 1.05657828159081 \tabularnewline
38 & 209.4 & 207.143507362666 & 219.975 & 0.941668404876309 & 1.01089337853773 \tabularnewline
39 & 214.1 & 219.10927577226 & 221.4125 & 0.989597587183469 & 0.97713800223836 \tabularnewline
40 & 237.8 & 225.803642335962 & 221.445833333333 & 1.01967889364651 & 1.05312738776016 \tabularnewline
41 & 239 & 231.590243365105 & 221.958333333333 & 1.04339512685611 & 1.03199511571484 \tabularnewline
42 & 237.8 & 240.461287977555 & 223.241666666667 & 1.07713444164794 & 0.988932572057907 \tabularnewline
43 & 251.5 & 230.937538867102 & 222.883333333333 & 1.03613641905527 & 1.08903905893243 \tabularnewline
44 & 248.8 & 232.301751254821 & 221.5 & 1.04876637135360 & 1.07102076784209 \tabularnewline
45 & 215.4 & 219.88494072336 & 221.2 & 0.994054885729477 & 0.979603238363637 \tabularnewline
46 & 201.2 & 219.651757848617 & 220.779166666667 & 0.994893499984301 & 0.91599540095038 \tabularnewline
47 & 203.1 & 212.598133476998 & 219.941666666667 & 0.966611450658877 & 0.955323533082545 \tabularnewline
48 & 214.2 & 207.477860156242 & 219.620833333333 & 0.944709374822101 & 1.03239931161183 \tabularnewline
49 & 188.9 & 207.588878037907 & 220.054166666667 & 0.943353544186046 & 0.90997167953047 \tabularnewline
50 & 203 & 207.492709396141 & 220.345833333333 & 0.941668404876309 & 0.978347627686698 \tabularnewline
51 & 213.3 & 220.259682967361 & 222.575 & 0.989597587183469 & 0.968402374535371 \tabularnewline
52 & 228.5 & 232.996627198226 & 228.5 & 1.01967889364651 & 0.980700891457966 \tabularnewline
53 & 228.2 & 247.488976610575 & 237.195833333333 & 1.04339512685611 & 0.922061269658382 \tabularnewline
54 & 240.9 & 265.513639866216 & 246.5 & 1.07713444164794 & 0.907298021003297 \tabularnewline
55 & 258.8 & 265.635157200216 & 256.370833333333 & 1.03613641905527 & 0.974268627420188 \tabularnewline
56 & 248.5 & 280.750387751477 & 267.695833333333 & 1.04876637135360 & 0.885127895958508 \tabularnewline
57 & 269.2 & 278.231820620323 & 279.895833333333 & 0.994054885729477 & 0.967538505839531 \tabularnewline
58 & 289.6 & 291.520377053733 & 293.016666666667 & 0.994893499984301 & 0.993412546069192 \tabularnewline
59 & 323.4 & 298.256018196219 & 308.558333333333 & 0.966611450658877 & 1.08430335104668 \tabularnewline
60 & 317.2 & 309.069544551174 & 327.158333333333 & 0.944709374822101 & 1.02630623298919 \tabularnewline
61 & 322.8 & 326.647956593721 & 346.2625 & 0.943353544186046 & 0.988219866323833 \tabularnewline
62 & 340.9 & 341.543130448637 & 362.7 & 0.941668404876309 & 0.998116986139372 \tabularnewline
63 & 368.2 & 369.899208119341 & 373.7875 & 0.989597587183469 & 0.995406294249777 \tabularnewline
64 & 388.5 & 384.121536560752 & 376.708333333333 & 1.01967889364651 & 1.01139864085323 \tabularnewline
65 & 441.2 & 386.508334825066 & 370.433333333333 & 1.04339512685611 & 1.14150190370329 \tabularnewline
66 & 474.3 & 386.26041077495 & 358.6 & 1.07713444164794 & 1.22792806813522 \tabularnewline
67 & 483.9 & NA & NA & 1.03613641905527 & NA \tabularnewline
68 & 417.9 & NA & NA & 1.04876637135360 & NA \tabularnewline
69 & 365.9 & NA & NA & 0.994054885729477 & NA \tabularnewline
70 & 263 & NA & NA & 0.994893499984301 & NA \tabularnewline
71 & 199.4 & NA & NA & 0.966611450658877 & NA \tabularnewline
72 & 157.2 & NA & NA & 0.944709374822101 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=41481&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]106.8[/C][C]NA[/C][C]NA[/C][C]0.943353544186046[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]114.3[/C][C]NA[/C][C]NA[/C][C]0.941668404876309[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]105.7[/C][C]NA[/C][C]NA[/C][C]0.989597587183469[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]90.1[/C][C]NA[/C][C]NA[/C][C]1.01967889364651[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]91.6[/C][C]NA[/C][C]NA[/C][C]1.04339512685611[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]97.7[/C][C]NA[/C][C]NA[/C][C]1.07713444164794[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]100.8[/C][C]105.824066266178[/C][C]102.133333333333[/C][C]1.03613641905527[/C][C]0.952524350618494[/C][/ROW]
[ROW][C]8[/C][C]104.6[/C][C]107.398046286489[/C][C]102.404166666667[/C][C]1.04876637135360[/C][C]0.97394695356911[/C][/ROW]
[ROW][C]9[/C][C]95.9[/C][C]102.495342509423[/C][C]103.108333333333[/C][C]0.994054885729477[/C][C]0.93565227113791[/C][/ROW]
[ROW][C]10[/C][C]102.7[/C][C]104.753994769180[/C][C]105.291666666667[/C][C]0.994893499984301[/C][C]0.980392205817962[/C][/ROW]
[ROW][C]11[/C][C]104[/C][C]105.038444304931[/C][C]108.666666666667[/C][C]0.966611450658877[/C][C]0.99011367398096[/C][/ROW]
[ROW][C]12[/C][C]107.9[/C][C]105.897984628496[/C][C]112.095833333333[/C][C]0.944709374822101[/C][C]1.01890513193927[/C][/ROW]
[ROW][C]13[/C][C]113.8[/C][C]108.725426607209[/C][C]115.254166666667[/C][C]0.943353544186046[/C][C]1.04667329024262[/C][/ROW]
[ROW][C]14[/C][C]113.8[/C][C]111.944755248025[/C][C]118.879166666667[/C][C]0.941668404876309[/C][C]1.01657285995994[/C][/ROW]
[ROW][C]15[/C][C]123.1[/C][C]121.856572891804[/C][C]123.1375[/C][C]0.989597587183469[/C][C]1.01020402165175[/C][/ROW]
[ROW][C]16[/C][C]125.1[/C][C]130.629363600231[/C][C]128.108333333333[/C][C]1.01967889364651[/C][C]0.957671357741949[/C][/ROW]
[ROW][C]17[/C][C]137.6[/C][C]138.615042602835[/C][C]132.85[/C][C]1.04339512685611[/C][C]0.992677255052737[/C][/ROW]
[ROW][C]18[/C][C]134[/C][C]146.835864697481[/C][C]136.320833333333[/C][C]1.07713444164794[/C][C]0.912583586278963[/C][/ROW]
[ROW][C]19[/C][C]140.3[/C][C]144.47195469694[/C][C]139.433333333333[/C][C]1.03613641905527[/C][C]0.971122736549862[/C][/ROW]
[ROW][C]20[/C][C]152.1[/C][C]149.960481523922[/C][C]142.9875[/C][C]1.04876637135360[/C][C]1.01426721529789[/C][/ROW]
[ROW][C]21[/C][C]150.6[/C][C]146.382865714380[/C][C]147.258333333333[/C][C]0.994054885729477[/C][C]1.02880893378497[/C][/ROW]
[ROW][C]22[/C][C]167.3[/C][C]151.232102776780[/C][C]152.008333333333[/C][C]0.994893499984301[/C][C]1.1062466032555[/C][/ROW]
[ROW][C]23[/C][C]153.2[/C][C]150.598064012653[/C][C]155.8[/C][C]0.966611450658877[/C][C]1.01727735349326[/C][/ROW]
[ROW][C]24[/C][C]142[/C][C]150.838596846596[/C][C]159.666666666667[/C][C]0.944709374822101[/C][C]0.94140361266033[/C][/ROW]
[ROW][C]25[/C][C]154.4[/C][C]155.220964416279[/C][C]164.541666666667[/C][C]0.943353544186046[/C][C]0.994710995261714[/C][/ROW]
[ROW][C]26[/C][C]158.5[/C][C]159.742274032205[/C][C]169.6375[/C][C]0.941668404876309[/C][C]0.99222326062571[/C][/ROW]
[ROW][C]27[/C][C]180.9[/C][C]173.109481261348[/C][C]174.929166666667[/C][C]0.989597587183469[/C][C]1.04500342027419[/C][/ROW]
[ROW][C]28[/C][C]181.3[/C][C]182.531019286838[/C][C]179.008333333333[/C][C]1.01967889364651[/C][C]0.993255835136144[/C][/ROW]
[ROW][C]29[/C][C]172.4[/C][C]189.884870648727[/C][C]181.9875[/C][C]1.04339512685611[/C][C]0.907918568820196[/C][/ROW]
[ROW][C]30[/C][C]192[/C][C]200.122603137839[/C][C]185.791666666667[/C][C]1.07713444164794[/C][C]0.959411865474063[/C][/ROW]
[ROW][C]31[/C][C]199.3[/C][C]197.483284236855[/C][C]190.595833333333[/C][C]1.03613641905527[/C][C]1.00919933942847[/C][/ROW]
[ROW][C]32[/C][C]215.4[/C][C]204.793483306193[/C][C]195.270833333333[/C][C]1.04876637135360[/C][C]1.05179128028185[/C][/ROW]
[ROW][C]33[/C][C]214.3[/C][C]197.593259910877[/C][C]198.775[/C][C]0.994054885729477[/C][C]1.08455116382340[/C][/ROW]
[ROW][C]34[/C][C]201.5[/C][C]201.478369915571[/C][C]202.5125[/C][C]0.994893499984301[/C][C]1.00010735685641[/C][/ROW]
[ROW][C]35[/C][C]190.5[/C][C]200.708812633894[/C][C]207.641666666667[/C][C]0.966611450658877[/C][C]0.949136201346[/C][/ROW]
[ROW][C]36[/C][C]196[/C][C]200.585418009103[/C][C]212.325[/C][C]0.944709374822101[/C][C]0.97713982374883[/C][/ROW]
[ROW][C]37[/C][C]215.7[/C][C]204.149568241395[/C][C]216.408333333333[/C][C]0.943353544186046[/C][C]1.05657828159081[/C][/ROW]
[ROW][C]38[/C][C]209.4[/C][C]207.143507362666[/C][C]219.975[/C][C]0.941668404876309[/C][C]1.01089337853773[/C][/ROW]
[ROW][C]39[/C][C]214.1[/C][C]219.10927577226[/C][C]221.4125[/C][C]0.989597587183469[/C][C]0.97713800223836[/C][/ROW]
[ROW][C]40[/C][C]237.8[/C][C]225.803642335962[/C][C]221.445833333333[/C][C]1.01967889364651[/C][C]1.05312738776016[/C][/ROW]
[ROW][C]41[/C][C]239[/C][C]231.590243365105[/C][C]221.958333333333[/C][C]1.04339512685611[/C][C]1.03199511571484[/C][/ROW]
[ROW][C]42[/C][C]237.8[/C][C]240.461287977555[/C][C]223.241666666667[/C][C]1.07713444164794[/C][C]0.988932572057907[/C][/ROW]
[ROW][C]43[/C][C]251.5[/C][C]230.937538867102[/C][C]222.883333333333[/C][C]1.03613641905527[/C][C]1.08903905893243[/C][/ROW]
[ROW][C]44[/C][C]248.8[/C][C]232.301751254821[/C][C]221.5[/C][C]1.04876637135360[/C][C]1.07102076784209[/C][/ROW]
[ROW][C]45[/C][C]215.4[/C][C]219.88494072336[/C][C]221.2[/C][C]0.994054885729477[/C][C]0.979603238363637[/C][/ROW]
[ROW][C]46[/C][C]201.2[/C][C]219.651757848617[/C][C]220.779166666667[/C][C]0.994893499984301[/C][C]0.91599540095038[/C][/ROW]
[ROW][C]47[/C][C]203.1[/C][C]212.598133476998[/C][C]219.941666666667[/C][C]0.966611450658877[/C][C]0.955323533082545[/C][/ROW]
[ROW][C]48[/C][C]214.2[/C][C]207.477860156242[/C][C]219.620833333333[/C][C]0.944709374822101[/C][C]1.03239931161183[/C][/ROW]
[ROW][C]49[/C][C]188.9[/C][C]207.588878037907[/C][C]220.054166666667[/C][C]0.943353544186046[/C][C]0.90997167953047[/C][/ROW]
[ROW][C]50[/C][C]203[/C][C]207.492709396141[/C][C]220.345833333333[/C][C]0.941668404876309[/C][C]0.978347627686698[/C][/ROW]
[ROW][C]51[/C][C]213.3[/C][C]220.259682967361[/C][C]222.575[/C][C]0.989597587183469[/C][C]0.968402374535371[/C][/ROW]
[ROW][C]52[/C][C]228.5[/C][C]232.996627198226[/C][C]228.5[/C][C]1.01967889364651[/C][C]0.980700891457966[/C][/ROW]
[ROW][C]53[/C][C]228.2[/C][C]247.488976610575[/C][C]237.195833333333[/C][C]1.04339512685611[/C][C]0.922061269658382[/C][/ROW]
[ROW][C]54[/C][C]240.9[/C][C]265.513639866216[/C][C]246.5[/C][C]1.07713444164794[/C][C]0.907298021003297[/C][/ROW]
[ROW][C]55[/C][C]258.8[/C][C]265.635157200216[/C][C]256.370833333333[/C][C]1.03613641905527[/C][C]0.974268627420188[/C][/ROW]
[ROW][C]56[/C][C]248.5[/C][C]280.750387751477[/C][C]267.695833333333[/C][C]1.04876637135360[/C][C]0.885127895958508[/C][/ROW]
[ROW][C]57[/C][C]269.2[/C][C]278.231820620323[/C][C]279.895833333333[/C][C]0.994054885729477[/C][C]0.967538505839531[/C][/ROW]
[ROW][C]58[/C][C]289.6[/C][C]291.520377053733[/C][C]293.016666666667[/C][C]0.994893499984301[/C][C]0.993412546069192[/C][/ROW]
[ROW][C]59[/C][C]323.4[/C][C]298.256018196219[/C][C]308.558333333333[/C][C]0.966611450658877[/C][C]1.08430335104668[/C][/ROW]
[ROW][C]60[/C][C]317.2[/C][C]309.069544551174[/C][C]327.158333333333[/C][C]0.944709374822101[/C][C]1.02630623298919[/C][/ROW]
[ROW][C]61[/C][C]322.8[/C][C]326.647956593721[/C][C]346.2625[/C][C]0.943353544186046[/C][C]0.988219866323833[/C][/ROW]
[ROW][C]62[/C][C]340.9[/C][C]341.543130448637[/C][C]362.7[/C][C]0.941668404876309[/C][C]0.998116986139372[/C][/ROW]
[ROW][C]63[/C][C]368.2[/C][C]369.899208119341[/C][C]373.7875[/C][C]0.989597587183469[/C][C]0.995406294249777[/C][/ROW]
[ROW][C]64[/C][C]388.5[/C][C]384.121536560752[/C][C]376.708333333333[/C][C]1.01967889364651[/C][C]1.01139864085323[/C][/ROW]
[ROW][C]65[/C][C]441.2[/C][C]386.508334825066[/C][C]370.433333333333[/C][C]1.04339512685611[/C][C]1.14150190370329[/C][/ROW]
[ROW][C]66[/C][C]474.3[/C][C]386.26041077495[/C][C]358.6[/C][C]1.07713444164794[/C][C]1.22792806813522[/C][/ROW]
[ROW][C]67[/C][C]483.9[/C][C]NA[/C][C]NA[/C][C]1.03613641905527[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]417.9[/C][C]NA[/C][C]NA[/C][C]1.04876637135360[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]365.9[/C][C]NA[/C][C]NA[/C][C]0.994054885729477[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]263[/C][C]NA[/C][C]NA[/C][C]0.994893499984301[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]199.4[/C][C]NA[/C][C]NA[/C][C]0.966611450658877[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]157.2[/C][C]NA[/C][C]NA[/C][C]0.944709374822101[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=41481&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=41481&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	106.8	NA	NA	0.943353544186046	NA
2	114.3	NA	NA	0.941668404876309	NA
3	105.7	NA	NA	0.989597587183469	NA
4	90.1	NA	NA	1.01967889364651	NA
5	91.6	NA	NA	1.04339512685611	NA
6	97.7	NA	NA	1.07713444164794	NA
7	100.8	105.824066266178	102.133333333333	1.03613641905527	0.952524350618494
8	104.6	107.398046286489	102.404166666667	1.04876637135360	0.97394695356911
9	95.9	102.495342509423	103.108333333333	0.994054885729477	0.93565227113791
10	102.7	104.753994769180	105.291666666667	0.994893499984301	0.980392205817962
11	104	105.038444304931	108.666666666667	0.966611450658877	0.99011367398096
12	107.9	105.897984628496	112.095833333333	0.944709374822101	1.01890513193927
13	113.8	108.725426607209	115.254166666667	0.943353544186046	1.04667329024262
14	113.8	111.944755248025	118.879166666667	0.941668404876309	1.01657285995994
15	123.1	121.856572891804	123.1375	0.989597587183469	1.01020402165175
16	125.1	130.629363600231	128.108333333333	1.01967889364651	0.957671357741949
17	137.6	138.615042602835	132.85	1.04339512685611	0.992677255052737
18	134	146.835864697481	136.320833333333	1.07713444164794	0.912583586278963
19	140.3	144.47195469694	139.433333333333	1.03613641905527	0.971122736549862
20	152.1	149.960481523922	142.9875	1.04876637135360	1.01426721529789
21	150.6	146.382865714380	147.258333333333	0.994054885729477	1.02880893378497
22	167.3	151.232102776780	152.008333333333	0.994893499984301	1.1062466032555
23	153.2	150.598064012653	155.8	0.966611450658877	1.01727735349326
24	142	150.838596846596	159.666666666667	0.944709374822101	0.94140361266033
25	154.4	155.220964416279	164.541666666667	0.943353544186046	0.994710995261714
26	158.5	159.742274032205	169.6375	0.941668404876309	0.99222326062571
27	180.9	173.109481261348	174.929166666667	0.989597587183469	1.04500342027419
28	181.3	182.531019286838	179.008333333333	1.01967889364651	0.993255835136144
29	172.4	189.884870648727	181.9875	1.04339512685611	0.907918568820196
30	192	200.122603137839	185.791666666667	1.07713444164794	0.959411865474063
31	199.3	197.483284236855	190.595833333333	1.03613641905527	1.00919933942847
32	215.4	204.793483306193	195.270833333333	1.04876637135360	1.05179128028185
33	214.3	197.593259910877	198.775	0.994054885729477	1.08455116382340
34	201.5	201.478369915571	202.5125	0.994893499984301	1.00010735685641
35	190.5	200.708812633894	207.641666666667	0.966611450658877	0.949136201346
36	196	200.585418009103	212.325	0.944709374822101	0.97713982374883
37	215.7	204.149568241395	216.408333333333	0.943353544186046	1.05657828159081
38	209.4	207.143507362666	219.975	0.941668404876309	1.01089337853773
39	214.1	219.10927577226	221.4125	0.989597587183469	0.97713800223836
40	237.8	225.803642335962	221.445833333333	1.01967889364651	1.05312738776016
41	239	231.590243365105	221.958333333333	1.04339512685611	1.03199511571484
42	237.8	240.461287977555	223.241666666667	1.07713444164794	0.988932572057907
43	251.5	230.937538867102	222.883333333333	1.03613641905527	1.08903905893243
44	248.8	232.301751254821	221.5	1.04876637135360	1.07102076784209
45	215.4	219.88494072336	221.2	0.994054885729477	0.979603238363637
46	201.2	219.651757848617	220.779166666667	0.994893499984301	0.91599540095038
47	203.1	212.598133476998	219.941666666667	0.966611450658877	0.955323533082545
48	214.2	207.477860156242	219.620833333333	0.944709374822101	1.03239931161183
49	188.9	207.588878037907	220.054166666667	0.943353544186046	0.90997167953047
50	203	207.492709396141	220.345833333333	0.941668404876309	0.978347627686698
51	213.3	220.259682967361	222.575	0.989597587183469	0.968402374535371
52	228.5	232.996627198226	228.5	1.01967889364651	0.980700891457966
53	228.2	247.488976610575	237.195833333333	1.04339512685611	0.922061269658382
54	240.9	265.513639866216	246.5	1.07713444164794	0.907298021003297
55	258.8	265.635157200216	256.370833333333	1.03613641905527	0.974268627420188
56	248.5	280.750387751477	267.695833333333	1.04876637135360	0.885127895958508
57	269.2	278.231820620323	279.895833333333	0.994054885729477	0.967538505839531
58	289.6	291.520377053733	293.016666666667	0.994893499984301	0.993412546069192
59	323.4	298.256018196219	308.558333333333	0.966611450658877	1.08430335104668
60	317.2	309.069544551174	327.158333333333	0.944709374822101	1.02630623298919
61	322.8	326.647956593721	346.2625	0.943353544186046	0.988219866323833
62	340.9	341.543130448637	362.7	0.941668404876309	0.998116986139372
63	368.2	369.899208119341	373.7875	0.989597587183469	0.995406294249777
64	388.5	384.121536560752	376.708333333333	1.01967889364651	1.01139864085323
65	441.2	386.508334825066	370.433333333333	1.04339512685611	1.14150190370329
66	474.3	386.26041077495	358.6	1.07713444164794	1.22792806813522
67	483.9	NA	NA	1.03613641905527	NA
68	417.9	NA	NA	1.04876637135360	NA
69	365.9	NA	NA	0.994054885729477	NA
70	263	NA	NA	0.994893499984301	NA
71	199.4	NA	NA	0.966611450658877	NA
72	157.2	NA	NA	0.944709374822101	NA

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; par2 = 12 ;

R code (references can be found in the software module):

par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code