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*Unverified author*

R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Tue, 20 May 2008 09:54:05 -0600

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/20/t1211298931be6b7ydkdk8fkrn.htm/, Retrieved Tue, 14 May 2024 02:18:50 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=12961, Retrieved Tue, 14 May 2024 02:18:50 +0000

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No (this computation is public)

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Estimated Impact

234

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

-       [Classical Decomposition] [gemiddelde prijs ...] [2008-05-20 15:54:05] [10bf337d6aaebcf0c700ebf73b3b2ad5] [Current]

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12961&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12961&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12961&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	'George Udny Yule' @ 72.249.76.132

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	58.1	NA	NA	0.545685763888883	NA
2	57.9	NA	NA	0.644435763888889	NA
3	57.3	NA	NA	0.274435763888886	NA
4	55.9	NA	NA	0.528602430555558	NA
5	55	NA	NA	0.240477430555555	NA
6	55.9	NA	NA	-0.228585069444441	NA
7	56.6	56.4237065972222	56.8916666666667	-0.467960069444447	0.176293402777780
8	57.3	56.0692274305556	56.9125	-0.843272569444441	1.23077256944445
9	56.2	56.2894357638889	56.9083333333333	-0.618897569444441	-0.0894357638888863
10	57.7	56.4731857638889	56.9416666666667	-0.46848090277778	1.22681423611112
11	56.8	57.3583940972222	57.0625	0.295894097222223	-0.558394097222227
12	57.9	57.1601649305555	57.0625	0.097664930555554	0.739835069444453
13	58.3	57.4373524305556	56.8916666666667	0.545685763888883	0.862647569444441
14	58.2	57.2194357638889	56.575	0.644435763888889	0.9805642361111
15	56.9	56.4369357638889	56.1625	0.274435763888886	0.463064236111101
16	57.1	56.2494357638889	55.7208333333333	0.528602430555558	0.850564236111111
17	56.7	55.5571440972222	55.3166666666667	0.240477430555555	1.14285590277778
18	54.2	54.7005815972222	54.9291666666667	-0.228585069444441	-0.500581597222222
19	54.2	53.9866232638889	54.4545833333333	-0.467960069444447	0.213376736111115
20	52.1	53.1225607638889	53.9658333333333	-0.843272569444441	-1.02256076388888
21	51.5	52.9386024305556	53.5575	-0.618897569444441	-1.43860243055556
22	51.8	52.7256857638889	53.1941666666667	-0.46848090277778	-0.925685763888886
23	53	53.0892274305556	52.7933333333333	0.295894097222223	-0.0892274305555532
24	52.4	52.5726649305555	52.475	0.097664930555554	-0.172664930555548
25	52.41	52.7652690972222	52.2195833333333	0.545685763888883	-0.355269097222219
26	52.36	52.6644357638889	52.02	0.644435763888889	-0.304435763888875
27	52.94	52.2356857638889	51.96125	0.274435763888886	0.70431423611111
28	52.34	52.4823524305556	51.95375	0.528602430555558	-0.142352430555547
29	51.84	52.1571440972222	51.9166666666667	0.240477430555555	-0.317144097222219
30	51.42	51.6422482638889	51.8708333333333	-0.228585069444441	-0.222248263888879
31	50.85	51.3337065972222	51.8016666666667	-0.467960069444447	-0.483706597222216
32	50.66	50.8321440972222	51.6754166666667	-0.843272569444441	-0.172144097222215
33	51.53	50.8527690972222	51.4716666666667	-0.618897569444441	0.677230902777787
34	51.59	50.7815190972222	51.25	-0.46848090277778	0.808480902777781
35	52.32	51.3383940972222	51.0425	0.295894097222223	0.981605902777787
36	51.98	50.9064149305555	50.80875	0.097664930555554	1.07358506944445
37	51.17	51.0844357638889	50.53875	0.545685763888883	0.085564236111118
38	50.57	50.8702690972222	50.2258333333333	0.644435763888889	-0.300269097222213
39	49.84	50.1098524305555	49.8354166666667	0.274435763888886	-0.269852430555545
40	50.12	49.8627690972222	49.3341666666667	0.528602430555558	0.257230902777778
41	49.08	48.9729774305556	48.7325	0.240477430555555	0.107022569444446
42	48.57	47.8459982638889	48.0745833333333	-0.228585069444441	0.724001736111113
43	47.22	46.9982899305556	47.46625	-0.467960069444447	0.221710069444441
44	46.78	46.0838107638889	46.9270833333333	-0.843272569444441	0.696189236111117
45	46.04	45.7652690972222	46.3841666666667	-0.618897569444441	0.274730902777783
46	45.05	45.3302690972222	45.79875	-0.46848090277778	-0.280269097222231
47	44.42	45.5108940972222	45.215	0.295894097222223	-1.09089409722223
48	44.09	44.7776649305556	44.68	0.097664930555554	-0.687664930555549
49	44.46	44.7523524305556	44.2066666666667	0.545685763888883	-0.292352430555553
50	44.34	44.4152690972222	43.7708333333333	0.644435763888889	-0.0752690972222112
51	43.04	43.6369357638889	43.3625	0.274435763888886	-0.596935763888887
52	42.87	43.5348524305556	43.00625	0.528602430555558	-0.664852430555555
53	42.32	42.9521440972222	42.7116666666667	0.240477430555555	-0.632144097222223
54	42.49	42.1905815972222	42.4191666666667	-0.228585069444441	0.299418402777782
55	41.94	41.5907899305556	42.05875	-0.467960069444447	0.349210069444439
56	41.6	40.8008940972222	41.6441666666667	-0.843272569444441	0.799105902777782
57	41.42	40.6327690972222	41.2516666666667	-0.618897569444441	0.787230902777779
58	41.12	40.4219357638889	40.8904166666667	-0.46848090277778	0.698064236111115
59	41.28	40.7808940972222	40.485	0.295894097222223	0.499105902777778
60	40.21	40.1226649305556	40.025	0.097664930555554	0.0873350694444426
61	39.69	40.0819357638889	39.53625	0.545685763888883	-0.391935763888888
62	39.16	39.7098524305556	39.0654166666667	0.644435763888889	-0.54985243055556
63	38.8	38.9073524305556	38.6329166666667	0.274435763888886	-0.107352430555565
64	38.44	38.7398524305556	38.21125	0.528602430555558	-0.299852430555553
65	37.02	38.0463107638889	37.8058333333333	0.240477430555555	-1.02631076388889
66	36.75	37.2276649305556	37.45625	-0.228585069444441	-0.477664930555555
67	35.95	NA	NA	-0.467960069444447	NA
68	36.29	NA	NA	-0.843272569444441	NA
69	36.35	NA	NA	-0.618897569444441	NA
70	36.07	NA	NA	-0.46848090277778	NA
71	36.6	NA	NA	0.295894097222223	NA
72	36.5	NA	NA	0.097664930555554	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 58.1 & NA & NA & 0.545685763888883 & NA \tabularnewline
2 & 57.9 & NA & NA & 0.644435763888889 & NA \tabularnewline
3 & 57.3 & NA & NA & 0.274435763888886 & NA \tabularnewline
4 & 55.9 & NA & NA & 0.528602430555558 & NA \tabularnewline
5 & 55 & NA & NA & 0.240477430555555 & NA \tabularnewline
6 & 55.9 & NA & NA & -0.228585069444441 & NA \tabularnewline
7 & 56.6 & 56.4237065972222 & 56.8916666666667 & -0.467960069444447 & 0.176293402777780 \tabularnewline
8 & 57.3 & 56.0692274305556 & 56.9125 & -0.843272569444441 & 1.23077256944445 \tabularnewline
9 & 56.2 & 56.2894357638889 & 56.9083333333333 & -0.618897569444441 & -0.0894357638888863 \tabularnewline
10 & 57.7 & 56.4731857638889 & 56.9416666666667 & -0.46848090277778 & 1.22681423611112 \tabularnewline
11 & 56.8 & 57.3583940972222 & 57.0625 & 0.295894097222223 & -0.558394097222227 \tabularnewline
12 & 57.9 & 57.1601649305555 & 57.0625 & 0.097664930555554 & 0.739835069444453 \tabularnewline
13 & 58.3 & 57.4373524305556 & 56.8916666666667 & 0.545685763888883 & 0.862647569444441 \tabularnewline
14 & 58.2 & 57.2194357638889 & 56.575 & 0.644435763888889 & 0.9805642361111 \tabularnewline
15 & 56.9 & 56.4369357638889 & 56.1625 & 0.274435763888886 & 0.463064236111101 \tabularnewline
16 & 57.1 & 56.2494357638889 & 55.7208333333333 & 0.528602430555558 & 0.850564236111111 \tabularnewline
17 & 56.7 & 55.5571440972222 & 55.3166666666667 & 0.240477430555555 & 1.14285590277778 \tabularnewline
18 & 54.2 & 54.7005815972222 & 54.9291666666667 & -0.228585069444441 & -0.500581597222222 \tabularnewline
19 & 54.2 & 53.9866232638889 & 54.4545833333333 & -0.467960069444447 & 0.213376736111115 \tabularnewline
20 & 52.1 & 53.1225607638889 & 53.9658333333333 & -0.843272569444441 & -1.02256076388888 \tabularnewline
21 & 51.5 & 52.9386024305556 & 53.5575 & -0.618897569444441 & -1.43860243055556 \tabularnewline
22 & 51.8 & 52.7256857638889 & 53.1941666666667 & -0.46848090277778 & -0.925685763888886 \tabularnewline
23 & 53 & 53.0892274305556 & 52.7933333333333 & 0.295894097222223 & -0.0892274305555532 \tabularnewline
24 & 52.4 & 52.5726649305555 & 52.475 & 0.097664930555554 & -0.172664930555548 \tabularnewline
25 & 52.41 & 52.7652690972222 & 52.2195833333333 & 0.545685763888883 & -0.355269097222219 \tabularnewline
26 & 52.36 & 52.6644357638889 & 52.02 & 0.644435763888889 & -0.304435763888875 \tabularnewline
27 & 52.94 & 52.2356857638889 & 51.96125 & 0.274435763888886 & 0.70431423611111 \tabularnewline
28 & 52.34 & 52.4823524305556 & 51.95375 & 0.528602430555558 & -0.142352430555547 \tabularnewline
29 & 51.84 & 52.1571440972222 & 51.9166666666667 & 0.240477430555555 & -0.317144097222219 \tabularnewline
30 & 51.42 & 51.6422482638889 & 51.8708333333333 & -0.228585069444441 & -0.222248263888879 \tabularnewline
31 & 50.85 & 51.3337065972222 & 51.8016666666667 & -0.467960069444447 & -0.483706597222216 \tabularnewline
32 & 50.66 & 50.8321440972222 & 51.6754166666667 & -0.843272569444441 & -0.172144097222215 \tabularnewline
33 & 51.53 & 50.8527690972222 & 51.4716666666667 & -0.618897569444441 & 0.677230902777787 \tabularnewline
34 & 51.59 & 50.7815190972222 & 51.25 & -0.46848090277778 & 0.808480902777781 \tabularnewline
35 & 52.32 & 51.3383940972222 & 51.0425 & 0.295894097222223 & 0.981605902777787 \tabularnewline
36 & 51.98 & 50.9064149305555 & 50.80875 & 0.097664930555554 & 1.07358506944445 \tabularnewline
37 & 51.17 & 51.0844357638889 & 50.53875 & 0.545685763888883 & 0.085564236111118 \tabularnewline
38 & 50.57 & 50.8702690972222 & 50.2258333333333 & 0.644435763888889 & -0.300269097222213 \tabularnewline
39 & 49.84 & 50.1098524305555 & 49.8354166666667 & 0.274435763888886 & -0.269852430555545 \tabularnewline
40 & 50.12 & 49.8627690972222 & 49.3341666666667 & 0.528602430555558 & 0.257230902777778 \tabularnewline
41 & 49.08 & 48.9729774305556 & 48.7325 & 0.240477430555555 & 0.107022569444446 \tabularnewline
42 & 48.57 & 47.8459982638889 & 48.0745833333333 & -0.228585069444441 & 0.724001736111113 \tabularnewline
43 & 47.22 & 46.9982899305556 & 47.46625 & -0.467960069444447 & 0.221710069444441 \tabularnewline
44 & 46.78 & 46.0838107638889 & 46.9270833333333 & -0.843272569444441 & 0.696189236111117 \tabularnewline
45 & 46.04 & 45.7652690972222 & 46.3841666666667 & -0.618897569444441 & 0.274730902777783 \tabularnewline
46 & 45.05 & 45.3302690972222 & 45.79875 & -0.46848090277778 & -0.280269097222231 \tabularnewline
47 & 44.42 & 45.5108940972222 & 45.215 & 0.295894097222223 & -1.09089409722223 \tabularnewline
48 & 44.09 & 44.7776649305556 & 44.68 & 0.097664930555554 & -0.687664930555549 \tabularnewline
49 & 44.46 & 44.7523524305556 & 44.2066666666667 & 0.545685763888883 & -0.292352430555553 \tabularnewline
50 & 44.34 & 44.4152690972222 & 43.7708333333333 & 0.644435763888889 & -0.0752690972222112 \tabularnewline
51 & 43.04 & 43.6369357638889 & 43.3625 & 0.274435763888886 & -0.596935763888887 \tabularnewline
52 & 42.87 & 43.5348524305556 & 43.00625 & 0.528602430555558 & -0.664852430555555 \tabularnewline
53 & 42.32 & 42.9521440972222 & 42.7116666666667 & 0.240477430555555 & -0.632144097222223 \tabularnewline
54 & 42.49 & 42.1905815972222 & 42.4191666666667 & -0.228585069444441 & 0.299418402777782 \tabularnewline
55 & 41.94 & 41.5907899305556 & 42.05875 & -0.467960069444447 & 0.349210069444439 \tabularnewline
56 & 41.6 & 40.8008940972222 & 41.6441666666667 & -0.843272569444441 & 0.799105902777782 \tabularnewline
57 & 41.42 & 40.6327690972222 & 41.2516666666667 & -0.618897569444441 & 0.787230902777779 \tabularnewline
58 & 41.12 & 40.4219357638889 & 40.8904166666667 & -0.46848090277778 & 0.698064236111115 \tabularnewline
59 & 41.28 & 40.7808940972222 & 40.485 & 0.295894097222223 & 0.499105902777778 \tabularnewline
60 & 40.21 & 40.1226649305556 & 40.025 & 0.097664930555554 & 0.0873350694444426 \tabularnewline
61 & 39.69 & 40.0819357638889 & 39.53625 & 0.545685763888883 & -0.391935763888888 \tabularnewline
62 & 39.16 & 39.7098524305556 & 39.0654166666667 & 0.644435763888889 & -0.54985243055556 \tabularnewline
63 & 38.8 & 38.9073524305556 & 38.6329166666667 & 0.274435763888886 & -0.107352430555565 \tabularnewline
64 & 38.44 & 38.7398524305556 & 38.21125 & 0.528602430555558 & -0.299852430555553 \tabularnewline
65 & 37.02 & 38.0463107638889 & 37.8058333333333 & 0.240477430555555 & -1.02631076388889 \tabularnewline
66 & 36.75 & 37.2276649305556 & 37.45625 & -0.228585069444441 & -0.477664930555555 \tabularnewline
67 & 35.95 & NA & NA & -0.467960069444447 & NA \tabularnewline
68 & 36.29 & NA & NA & -0.843272569444441 & NA \tabularnewline
69 & 36.35 & NA & NA & -0.618897569444441 & NA \tabularnewline
70 & 36.07 & NA & NA & -0.46848090277778 & NA \tabularnewline
71 & 36.6 & NA & NA & 0.295894097222223 & NA \tabularnewline
72 & 36.5 & NA & NA & 0.097664930555554 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=12961&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]58.1[/C][C]NA[/C][C]NA[/C][C]0.545685763888883[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]57.9[/C][C]NA[/C][C]NA[/C][C]0.644435763888889[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]57.3[/C][C]NA[/C][C]NA[/C][C]0.274435763888886[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]55.9[/C][C]NA[/C][C]NA[/C][C]0.528602430555558[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]55[/C][C]NA[/C][C]NA[/C][C]0.240477430555555[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]55.9[/C][C]NA[/C][C]NA[/C][C]-0.228585069444441[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]56.6[/C][C]56.4237065972222[/C][C]56.8916666666667[/C][C]-0.467960069444447[/C][C]0.176293402777780[/C][/ROW]
[ROW][C]8[/C][C]57.3[/C][C]56.0692274305556[/C][C]56.9125[/C][C]-0.843272569444441[/C][C]1.23077256944445[/C][/ROW]
[ROW][C]9[/C][C]56.2[/C][C]56.2894357638889[/C][C]56.9083333333333[/C][C]-0.618897569444441[/C][C]-0.0894357638888863[/C][/ROW]
[ROW][C]10[/C][C]57.7[/C][C]56.4731857638889[/C][C]56.9416666666667[/C][C]-0.46848090277778[/C][C]1.22681423611112[/C][/ROW]
[ROW][C]11[/C][C]56.8[/C][C]57.3583940972222[/C][C]57.0625[/C][C]0.295894097222223[/C][C]-0.558394097222227[/C][/ROW]
[ROW][C]12[/C][C]57.9[/C][C]57.1601649305555[/C][C]57.0625[/C][C]0.097664930555554[/C][C]0.739835069444453[/C][/ROW]
[ROW][C]13[/C][C]58.3[/C][C]57.4373524305556[/C][C]56.8916666666667[/C][C]0.545685763888883[/C][C]0.862647569444441[/C][/ROW]
[ROW][C]14[/C][C]58.2[/C][C]57.2194357638889[/C][C]56.575[/C][C]0.644435763888889[/C][C]0.9805642361111[/C][/ROW]
[ROW][C]15[/C][C]56.9[/C][C]56.4369357638889[/C][C]56.1625[/C][C]0.274435763888886[/C][C]0.463064236111101[/C][/ROW]
[ROW][C]16[/C][C]57.1[/C][C]56.2494357638889[/C][C]55.7208333333333[/C][C]0.528602430555558[/C][C]0.850564236111111[/C][/ROW]
[ROW][C]17[/C][C]56.7[/C][C]55.5571440972222[/C][C]55.3166666666667[/C][C]0.240477430555555[/C][C]1.14285590277778[/C][/ROW]
[ROW][C]18[/C][C]54.2[/C][C]54.7005815972222[/C][C]54.9291666666667[/C][C]-0.228585069444441[/C][C]-0.500581597222222[/C][/ROW]
[ROW][C]19[/C][C]54.2[/C][C]53.9866232638889[/C][C]54.4545833333333[/C][C]-0.467960069444447[/C][C]0.213376736111115[/C][/ROW]
[ROW][C]20[/C][C]52.1[/C][C]53.1225607638889[/C][C]53.9658333333333[/C][C]-0.843272569444441[/C][C]-1.02256076388888[/C][/ROW]
[ROW][C]21[/C][C]51.5[/C][C]52.9386024305556[/C][C]53.5575[/C][C]-0.618897569444441[/C][C]-1.43860243055556[/C][/ROW]
[ROW][C]22[/C][C]51.8[/C][C]52.7256857638889[/C][C]53.1941666666667[/C][C]-0.46848090277778[/C][C]-0.925685763888886[/C][/ROW]
[ROW][C]23[/C][C]53[/C][C]53.0892274305556[/C][C]52.7933333333333[/C][C]0.295894097222223[/C][C]-0.0892274305555532[/C][/ROW]
[ROW][C]24[/C][C]52.4[/C][C]52.5726649305555[/C][C]52.475[/C][C]0.097664930555554[/C][C]-0.172664930555548[/C][/ROW]
[ROW][C]25[/C][C]52.41[/C][C]52.7652690972222[/C][C]52.2195833333333[/C][C]0.545685763888883[/C][C]-0.355269097222219[/C][/ROW]
[ROW][C]26[/C][C]52.36[/C][C]52.6644357638889[/C][C]52.02[/C][C]0.644435763888889[/C][C]-0.304435763888875[/C][/ROW]
[ROW][C]27[/C][C]52.94[/C][C]52.2356857638889[/C][C]51.96125[/C][C]0.274435763888886[/C][C]0.70431423611111[/C][/ROW]
[ROW][C]28[/C][C]52.34[/C][C]52.4823524305556[/C][C]51.95375[/C][C]0.528602430555558[/C][C]-0.142352430555547[/C][/ROW]
[ROW][C]29[/C][C]51.84[/C][C]52.1571440972222[/C][C]51.9166666666667[/C][C]0.240477430555555[/C][C]-0.317144097222219[/C][/ROW]
[ROW][C]30[/C][C]51.42[/C][C]51.6422482638889[/C][C]51.8708333333333[/C][C]-0.228585069444441[/C][C]-0.222248263888879[/C][/ROW]
[ROW][C]31[/C][C]50.85[/C][C]51.3337065972222[/C][C]51.8016666666667[/C][C]-0.467960069444447[/C][C]-0.483706597222216[/C][/ROW]
[ROW][C]32[/C][C]50.66[/C][C]50.8321440972222[/C][C]51.6754166666667[/C][C]-0.843272569444441[/C][C]-0.172144097222215[/C][/ROW]
[ROW][C]33[/C][C]51.53[/C][C]50.8527690972222[/C][C]51.4716666666667[/C][C]-0.618897569444441[/C][C]0.677230902777787[/C][/ROW]
[ROW][C]34[/C][C]51.59[/C][C]50.7815190972222[/C][C]51.25[/C][C]-0.46848090277778[/C][C]0.808480902777781[/C][/ROW]
[ROW][C]35[/C][C]52.32[/C][C]51.3383940972222[/C][C]51.0425[/C][C]0.295894097222223[/C][C]0.981605902777787[/C][/ROW]
[ROW][C]36[/C][C]51.98[/C][C]50.9064149305555[/C][C]50.80875[/C][C]0.097664930555554[/C][C]1.07358506944445[/C][/ROW]
[ROW][C]37[/C][C]51.17[/C][C]51.0844357638889[/C][C]50.53875[/C][C]0.545685763888883[/C][C]0.085564236111118[/C][/ROW]
[ROW][C]38[/C][C]50.57[/C][C]50.8702690972222[/C][C]50.2258333333333[/C][C]0.644435763888889[/C][C]-0.300269097222213[/C][/ROW]
[ROW][C]39[/C][C]49.84[/C][C]50.1098524305555[/C][C]49.8354166666667[/C][C]0.274435763888886[/C][C]-0.269852430555545[/C][/ROW]
[ROW][C]40[/C][C]50.12[/C][C]49.8627690972222[/C][C]49.3341666666667[/C][C]0.528602430555558[/C][C]0.257230902777778[/C][/ROW]
[ROW][C]41[/C][C]49.08[/C][C]48.9729774305556[/C][C]48.7325[/C][C]0.240477430555555[/C][C]0.107022569444446[/C][/ROW]
[ROW][C]42[/C][C]48.57[/C][C]47.8459982638889[/C][C]48.0745833333333[/C][C]-0.228585069444441[/C][C]0.724001736111113[/C][/ROW]
[ROW][C]43[/C][C]47.22[/C][C]46.9982899305556[/C][C]47.46625[/C][C]-0.467960069444447[/C][C]0.221710069444441[/C][/ROW]
[ROW][C]44[/C][C]46.78[/C][C]46.0838107638889[/C][C]46.9270833333333[/C][C]-0.843272569444441[/C][C]0.696189236111117[/C][/ROW]
[ROW][C]45[/C][C]46.04[/C][C]45.7652690972222[/C][C]46.3841666666667[/C][C]-0.618897569444441[/C][C]0.274730902777783[/C][/ROW]
[ROW][C]46[/C][C]45.05[/C][C]45.3302690972222[/C][C]45.79875[/C][C]-0.46848090277778[/C][C]-0.280269097222231[/C][/ROW]
[ROW][C]47[/C][C]44.42[/C][C]45.5108940972222[/C][C]45.215[/C][C]0.295894097222223[/C][C]-1.09089409722223[/C][/ROW]
[ROW][C]48[/C][C]44.09[/C][C]44.7776649305556[/C][C]44.68[/C][C]0.097664930555554[/C][C]-0.687664930555549[/C][/ROW]
[ROW][C]49[/C][C]44.46[/C][C]44.7523524305556[/C][C]44.2066666666667[/C][C]0.545685763888883[/C][C]-0.292352430555553[/C][/ROW]
[ROW][C]50[/C][C]44.34[/C][C]44.4152690972222[/C][C]43.7708333333333[/C][C]0.644435763888889[/C][C]-0.0752690972222112[/C][/ROW]
[ROW][C]51[/C][C]43.04[/C][C]43.6369357638889[/C][C]43.3625[/C][C]0.274435763888886[/C][C]-0.596935763888887[/C][/ROW]
[ROW][C]52[/C][C]42.87[/C][C]43.5348524305556[/C][C]43.00625[/C][C]0.528602430555558[/C][C]-0.664852430555555[/C][/ROW]
[ROW][C]53[/C][C]42.32[/C][C]42.9521440972222[/C][C]42.7116666666667[/C][C]0.240477430555555[/C][C]-0.632144097222223[/C][/ROW]
[ROW][C]54[/C][C]42.49[/C][C]42.1905815972222[/C][C]42.4191666666667[/C][C]-0.228585069444441[/C][C]0.299418402777782[/C][/ROW]
[ROW][C]55[/C][C]41.94[/C][C]41.5907899305556[/C][C]42.05875[/C][C]-0.467960069444447[/C][C]0.349210069444439[/C][/ROW]
[ROW][C]56[/C][C]41.6[/C][C]40.8008940972222[/C][C]41.6441666666667[/C][C]-0.843272569444441[/C][C]0.799105902777782[/C][/ROW]
[ROW][C]57[/C][C]41.42[/C][C]40.6327690972222[/C][C]41.2516666666667[/C][C]-0.618897569444441[/C][C]0.787230902777779[/C][/ROW]
[ROW][C]58[/C][C]41.12[/C][C]40.4219357638889[/C][C]40.8904166666667[/C][C]-0.46848090277778[/C][C]0.698064236111115[/C][/ROW]
[ROW][C]59[/C][C]41.28[/C][C]40.7808940972222[/C][C]40.485[/C][C]0.295894097222223[/C][C]0.499105902777778[/C][/ROW]
[ROW][C]60[/C][C]40.21[/C][C]40.1226649305556[/C][C]40.025[/C][C]0.097664930555554[/C][C]0.0873350694444426[/C][/ROW]
[ROW][C]61[/C][C]39.69[/C][C]40.0819357638889[/C][C]39.53625[/C][C]0.545685763888883[/C][C]-0.391935763888888[/C][/ROW]
[ROW][C]62[/C][C]39.16[/C][C]39.7098524305556[/C][C]39.0654166666667[/C][C]0.644435763888889[/C][C]-0.54985243055556[/C][/ROW]
[ROW][C]63[/C][C]38.8[/C][C]38.9073524305556[/C][C]38.6329166666667[/C][C]0.274435763888886[/C][C]-0.107352430555565[/C][/ROW]
[ROW][C]64[/C][C]38.44[/C][C]38.7398524305556[/C][C]38.21125[/C][C]0.528602430555558[/C][C]-0.299852430555553[/C][/ROW]
[ROW][C]65[/C][C]37.02[/C][C]38.0463107638889[/C][C]37.8058333333333[/C][C]0.240477430555555[/C][C]-1.02631076388889[/C][/ROW]
[ROW][C]66[/C][C]36.75[/C][C]37.2276649305556[/C][C]37.45625[/C][C]-0.228585069444441[/C][C]-0.477664930555555[/C][/ROW]
[ROW][C]67[/C][C]35.95[/C][C]NA[/C][C]NA[/C][C]-0.467960069444447[/C][C]NA[/C][/ROW]
[ROW][C]68[/C][C]36.29[/C][C]NA[/C][C]NA[/C][C]-0.843272569444441[/C][C]NA[/C][/ROW]
[ROW][C]69[/C][C]36.35[/C][C]NA[/C][C]NA[/C][C]-0.618897569444441[/C][C]NA[/C][/ROW]
[ROW][C]70[/C][C]36.07[/C][C]NA[/C][C]NA[/C][C]-0.46848090277778[/C][C]NA[/C][/ROW]
[ROW][C]71[/C][C]36.6[/C][C]NA[/C][C]NA[/C][C]0.295894097222223[/C][C]NA[/C][/ROW]
[ROW][C]72[/C][C]36.5[/C][C]NA[/C][C]NA[/C][C]0.097664930555554[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=12961&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=12961&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	58.1	NA	NA	0.545685763888883	NA
2	57.9	NA	NA	0.644435763888889	NA
3	57.3	NA	NA	0.274435763888886	NA
4	55.9	NA	NA	0.528602430555558	NA
5	55	NA	NA	0.240477430555555	NA
6	55.9	NA	NA	-0.228585069444441	NA
7	56.6	56.4237065972222	56.8916666666667	-0.467960069444447	0.176293402777780
8	57.3	56.0692274305556	56.9125	-0.843272569444441	1.23077256944445
9	56.2	56.2894357638889	56.9083333333333	-0.618897569444441	-0.0894357638888863
10	57.7	56.4731857638889	56.9416666666667	-0.46848090277778	1.22681423611112
11	56.8	57.3583940972222	57.0625	0.295894097222223	-0.558394097222227
12	57.9	57.1601649305555	57.0625	0.097664930555554	0.739835069444453
13	58.3	57.4373524305556	56.8916666666667	0.545685763888883	0.862647569444441
14	58.2	57.2194357638889	56.575	0.644435763888889	0.9805642361111
15	56.9	56.4369357638889	56.1625	0.274435763888886	0.463064236111101
16	57.1	56.2494357638889	55.7208333333333	0.528602430555558	0.850564236111111
17	56.7	55.5571440972222	55.3166666666667	0.240477430555555	1.14285590277778
18	54.2	54.7005815972222	54.9291666666667	-0.228585069444441	-0.500581597222222
19	54.2	53.9866232638889	54.4545833333333	-0.467960069444447	0.213376736111115
20	52.1	53.1225607638889	53.9658333333333	-0.843272569444441	-1.02256076388888
21	51.5	52.9386024305556	53.5575	-0.618897569444441	-1.43860243055556
22	51.8	52.7256857638889	53.1941666666667	-0.46848090277778	-0.925685763888886
23	53	53.0892274305556	52.7933333333333	0.295894097222223	-0.0892274305555532
24	52.4	52.5726649305555	52.475	0.097664930555554	-0.172664930555548
25	52.41	52.7652690972222	52.2195833333333	0.545685763888883	-0.355269097222219
26	52.36	52.6644357638889	52.02	0.644435763888889	-0.304435763888875
27	52.94	52.2356857638889	51.96125	0.274435763888886	0.70431423611111
28	52.34	52.4823524305556	51.95375	0.528602430555558	-0.142352430555547
29	51.84	52.1571440972222	51.9166666666667	0.240477430555555	-0.317144097222219
30	51.42	51.6422482638889	51.8708333333333	-0.228585069444441	-0.222248263888879
31	50.85	51.3337065972222	51.8016666666667	-0.467960069444447	-0.483706597222216
32	50.66	50.8321440972222	51.6754166666667	-0.843272569444441	-0.172144097222215
33	51.53	50.8527690972222	51.4716666666667	-0.618897569444441	0.677230902777787
34	51.59	50.7815190972222	51.25	-0.46848090277778	0.808480902777781
35	52.32	51.3383940972222	51.0425	0.295894097222223	0.981605902777787
36	51.98	50.9064149305555	50.80875	0.097664930555554	1.07358506944445
37	51.17	51.0844357638889	50.53875	0.545685763888883	0.085564236111118
38	50.57	50.8702690972222	50.2258333333333	0.644435763888889	-0.300269097222213
39	49.84	50.1098524305555	49.8354166666667	0.274435763888886	-0.269852430555545
40	50.12	49.8627690972222	49.3341666666667	0.528602430555558	0.257230902777778
41	49.08	48.9729774305556	48.7325	0.240477430555555	0.107022569444446
42	48.57	47.8459982638889	48.0745833333333	-0.228585069444441	0.724001736111113
43	47.22	46.9982899305556	47.46625	-0.467960069444447	0.221710069444441
44	46.78	46.0838107638889	46.9270833333333	-0.843272569444441	0.696189236111117
45	46.04	45.7652690972222	46.3841666666667	-0.618897569444441	0.274730902777783
46	45.05	45.3302690972222	45.79875	-0.46848090277778	-0.280269097222231
47	44.42	45.5108940972222	45.215	0.295894097222223	-1.09089409722223
48	44.09	44.7776649305556	44.68	0.097664930555554	-0.687664930555549
49	44.46	44.7523524305556	44.2066666666667	0.545685763888883	-0.292352430555553
50	44.34	44.4152690972222	43.7708333333333	0.644435763888889	-0.0752690972222112
51	43.04	43.6369357638889	43.3625	0.274435763888886	-0.596935763888887
52	42.87	43.5348524305556	43.00625	0.528602430555558	-0.664852430555555
53	42.32	42.9521440972222	42.7116666666667	0.240477430555555	-0.632144097222223
54	42.49	42.1905815972222	42.4191666666667	-0.228585069444441	0.299418402777782
55	41.94	41.5907899305556	42.05875	-0.467960069444447	0.349210069444439
56	41.6	40.8008940972222	41.6441666666667	-0.843272569444441	0.799105902777782
57	41.42	40.6327690972222	41.2516666666667	-0.618897569444441	0.787230902777779
58	41.12	40.4219357638889	40.8904166666667	-0.46848090277778	0.698064236111115
59	41.28	40.7808940972222	40.485	0.295894097222223	0.499105902777778
60	40.21	40.1226649305556	40.025	0.097664930555554	0.0873350694444426
61	39.69	40.0819357638889	39.53625	0.545685763888883	-0.391935763888888
62	39.16	39.7098524305556	39.0654166666667	0.644435763888889	-0.54985243055556
63	38.8	38.9073524305556	38.6329166666667	0.274435763888886	-0.107352430555565
64	38.44	38.7398524305556	38.21125	0.528602430555558	-0.299852430555553
65	37.02	38.0463107638889	37.8058333333333	0.240477430555555	-1.02631076388889
66	36.75	37.2276649305556	37.45625	-0.228585069444441	-0.477664930555555
67	35.95	NA	NA	-0.467960069444447	NA
68	36.29	NA	NA	-0.843272569444441	NA
69	36.35	NA	NA	-0.618897569444441	NA
70	36.07	NA	NA	-0.46848090277778	NA
71	36.6	NA	NA	0.295894097222223	NA
72	36.5	NA	NA	0.097664930555554	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$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$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