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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Mon, 21 May 2012 04:57:57 -0400

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/May/21/t1337590709ctese2w2ogveptt.htm/, Retrieved Thu, 02 May 2024 23:37:10 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=166887, Retrieved Thu, 02 May 2024 23:37:10 +0000

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IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W92

Estimated Impact

125

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

-     [Bootstrap Plot - Central Tendency] [Bootstrap Plot va...] [2012-05-02 19:39:36] [562ee1d5a96d07a2dc4978b28f7ac089]
- RMPD  [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2012-05-02 19:52:56] [562ee1d5a96d07a2dc4978b28f7ac089]
- RMPD    [Standard Deviation Plot] [Standard Deviatio...] [2012-05-02 20:02:11] [562ee1d5a96d07a2dc4978b28f7ac089]
- RMPD        [Classical Decomposition] [] [2012-05-21 08:57:57] [21ca38b5c207d9fbe3078e977c625188] [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	2 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166887&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166887&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166887&T=0

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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	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	31.1	NA	NA	-0.0692129629629638	NA
2	31.8	NA	NA	-0.533101851851852	NA
3	32.5	NA	NA	-0.192824074074073	NA
4	34.4	NA	NA	-0.581018518518513	NA
5	35.5	NA	NA	-0.583101851851852	NA
6	35.5	NA	NA	-0.869212962962964	NA
7	36.6	37.3703703703704	36.3625	1.00787037037037	-0.770370370370365
8	37.1	38.0481481481481	37.2291666666667	0.818981481481483	-0.948148148148142
9	37.9	38.4155092592593	38.1541666666667	0.26134259259259	-0.515509259259254
10	38.1	39.1293981481481	39.1458333333333	-0.0164351851851854	-1.02939814814814
11	39	40.5231481481481	40.0875	0.435648148148149	-1.52314814814814
12	41.5	41.3502314814815	41.0291666666667	0.321064814814816	0.14976851851852
13	41.8	41.9099537037037	41.9791666666667	-0.0692129629629638	-0.109953703703702
14	41.9	42.4127314814815	42.9458333333333	-0.533101851851852	-0.512731481481474
15	44.6	43.7321759259259	43.925	-0.192824074074073	0.867824074074079
16	46.1	44.2856481481481	44.8666666666667	-0.581018518518513	1.81435185185185
17	46.4	45.1877314814815	45.7708333333333	-0.583101851851852	1.21226851851851
18	47.2	45.6974537037037	46.5666666666667	-0.869212962962964	1.50254629629629
19	47.7	48.3537037037037	47.3458333333333	1.00787037037037	-0.653703703703705
20	49.2	49.0314814814815	48.2125	0.818981481481483	0.168518518518518
21	49.3	49.2780092592593	49.0166666666667	0.26134259259259	0.0219907407407405
22	49.3	49.6668981481481	49.6833333333333	-0.0164351851851854	-0.366898148148145
23	49.5	50.7314814814815	50.2958333333333	0.435648148148149	-1.23148148148147
24	50.1	51.1918981481482	50.8708333333333	0.321064814814816	-1.09189814814815
25	51.9	51.330787037037	51.4	-0.0692129629629638	0.569212962962965
26	52.6	51.3293981481481	51.8625	-0.533101851851852	1.27060185185186
27	53.2	52.1030092592593	52.2958333333333	-0.192824074074073	1.09699074074074
28	53.5	52.1981481481482	52.7791666666667	-0.581018518518513	1.30185185185184
29	53.7	52.7168981481481	53.3	-0.583101851851852	0.983101851851856
30	53.7	52.9766203703704	53.8458333333333	-0.869212962962964	0.723379629629633
31	53.9	55.4037037037037	54.3958333333333	1.00787037037037	-1.50370370370371
32	54.1	55.7648148148148	54.9458333333333	0.818981481481483	-1.66481481481481
33	54.8	55.7821759259259	55.5208333333333	0.26134259259259	-0.982175925925937
34	55.4	56.0918981481481	56.1083333333333	-0.0164351851851854	-0.691898148148141
35	55.9	57.1314814814815	56.6958333333333	0.435648148148149	-1.23148148148147
36	56.8	57.6168981481481	57.2958333333333	0.321064814814816	-0.816898148148141
37	58.4	57.830787037037	57.9	-0.0692129629629638	0.569212962962972
38	59.3	57.9668981481481	58.5	-0.533101851851852	1.33310185185186
39	60.3	58.8821759259259	59.075	-0.192824074074073	1.41782407407408
40	60.5	59.0231481481481	59.6041666666667	-0.581018518518513	1.47685185185185
41	60.8	59.6085648148148	60.1916666666667	-0.583101851851852	1.19143518518519
42	61	59.9516203703704	60.8208333333333	-0.869212962962964	1.04837962962964
43	61.1	62.3578703703704	61.35	1.00787037037037	-1.25787037037036
44	61.3	62.6023148148148	61.7833333333333	0.818981481481483	-1.30231481481481
45	61.4	62.4196759259259	62.1583333333333	0.26134259259259	-1.01967592592592
46	61.5	62.4835648148148	62.5	-0.0164351851851854	-0.983564814814812
47	63.9	63.3148148148148	62.8791666666667	0.435648148148149	0.585185185185182
48	63.9	63.6543981481482	63.3333333333333	0.321064814814816	0.245601851851845
49	64	63.8224537037037	63.8916666666667	-0.0692129629629638	0.177546296296292
50	64.1	64.0043981481482	64.5375	-0.533101851851852	0.0956018518518391
51	64.5	65.0155092592593	65.2083333333333	-0.192824074074073	-0.515509259259275
52	64.5	65.3314814814815	65.9125	-0.581018518518513	-0.831481481481489
53	65.9	65.9710648148148	66.5541666666667	-0.583101851851852	-0.0710648148148181
54	66.8	66.2474537037037	67.1166666666667	-0.869212962962964	0.552546296296299
55	68.7	68.687037037037	67.6791666666667	1.00787037037037	0.0129629629629591
56	69.2	69.0648148148148	68.2458333333333	0.818981481481483	0.135185185185193
57	69.6	69.1113425925926	68.85	0.26134259259259	0.488657407407416
58	70.2	69.5335648148148	69.55	-0.0164351851851854	0.666435185185208
59	70.6	70.8481481481482	70.4125	0.435648148148149	-0.248148148148161
60	70.7	71.7502314814815	71.4291666666667	0.321064814814816	-1.05023148148148
61	70.7	72.8516203703704	72.9208333333333	-0.0692129629629638	-2.15162037037035
62	71	74.3585648148148	74.8916666666667	-0.533101851851852	-3.3585648148148
63	72.1	76.7446759259259	76.9375	-0.192824074074073	-4.64467592592592
64	73.7	78.5148148148148	79.0958333333333	-0.581018518518513	-4.8148148148148
65	77.4	80.9377314814815	81.5208333333333	-0.583101851851852	-3.53773148148147
66	79.7	83.293287037037	84.1625	-0.869212962962964	-3.59328703703704
67	91.6	87.8662037037037	86.8583333333333	1.00787037037037	3.73379629629629
68	93.6	90.4273148148148	89.6083333333333	0.818981481481483	3.17268518518519
69	94.3	92.7321759259259	92.4708333333333	0.26134259259259	1.5678240740741
70	97.3	95.3335648148148	95.35	-0.0164351851851854	1.96643518518518
71	101.7	98.4898148148148	98.0541666666666	0.435648148148149	3.21018518518521
72	103	100.875231481481	100.554166666667	0.321064814814816	2.12476851851852
73	103.1	102.593287037037	102.6625	-0.0692129629629638	0.506712962962965
74	104.6	103.866898148148	104.4	-0.533101851851852	0.733101851851856
75	107.2	105.861342592593	106.054166666667	-0.192824074074073	1.33865740740742
76	107.7	107.085648148148	107.666666666667	-0.581018518518513	0.614351851851879
77	108.3	108.516898148148	109.1	-0.583101851851852	-0.216898148148147
78	108.8	109.472453703704	110.341666666667	-0.869212962962964	-0.672453703703709
79	113.1	NA	NA	1.00787037037037	NA
80	113.8	NA	NA	0.818981481481483	NA
81	113.8	NA	NA	0.26134259259259	NA
82	116.5	NA	NA	-0.0164351851851854	NA
83	116.9	NA	NA	0.435648148148149	NA
84	117.6	NA	NA	0.321064814814816	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 31.1 & NA & NA & -0.0692129629629638 & NA \tabularnewline
2 & 31.8 & NA & NA & -0.533101851851852 & NA \tabularnewline
3 & 32.5 & NA & NA & -0.192824074074073 & NA \tabularnewline
4 & 34.4 & NA & NA & -0.581018518518513 & NA \tabularnewline
5 & 35.5 & NA & NA & -0.583101851851852 & NA \tabularnewline
6 & 35.5 & NA & NA & -0.869212962962964 & NA \tabularnewline
7 & 36.6 & 37.3703703703704 & 36.3625 & 1.00787037037037 & -0.770370370370365 \tabularnewline
8 & 37.1 & 38.0481481481481 & 37.2291666666667 & 0.818981481481483 & -0.948148148148142 \tabularnewline
9 & 37.9 & 38.4155092592593 & 38.1541666666667 & 0.26134259259259 & -0.515509259259254 \tabularnewline
10 & 38.1 & 39.1293981481481 & 39.1458333333333 & -0.0164351851851854 & -1.02939814814814 \tabularnewline
11 & 39 & 40.5231481481481 & 40.0875 & 0.435648148148149 & -1.52314814814814 \tabularnewline
12 & 41.5 & 41.3502314814815 & 41.0291666666667 & 0.321064814814816 & 0.14976851851852 \tabularnewline
13 & 41.8 & 41.9099537037037 & 41.9791666666667 & -0.0692129629629638 & -0.109953703703702 \tabularnewline
14 & 41.9 & 42.4127314814815 & 42.9458333333333 & -0.533101851851852 & -0.512731481481474 \tabularnewline
15 & 44.6 & 43.7321759259259 & 43.925 & -0.192824074074073 & 0.867824074074079 \tabularnewline
16 & 46.1 & 44.2856481481481 & 44.8666666666667 & -0.581018518518513 & 1.81435185185185 \tabularnewline
17 & 46.4 & 45.1877314814815 & 45.7708333333333 & -0.583101851851852 & 1.21226851851851 \tabularnewline
18 & 47.2 & 45.6974537037037 & 46.5666666666667 & -0.869212962962964 & 1.50254629629629 \tabularnewline
19 & 47.7 & 48.3537037037037 & 47.3458333333333 & 1.00787037037037 & -0.653703703703705 \tabularnewline
20 & 49.2 & 49.0314814814815 & 48.2125 & 0.818981481481483 & 0.168518518518518 \tabularnewline
21 & 49.3 & 49.2780092592593 & 49.0166666666667 & 0.26134259259259 & 0.0219907407407405 \tabularnewline
22 & 49.3 & 49.6668981481481 & 49.6833333333333 & -0.0164351851851854 & -0.366898148148145 \tabularnewline
23 & 49.5 & 50.7314814814815 & 50.2958333333333 & 0.435648148148149 & -1.23148148148147 \tabularnewline
24 & 50.1 & 51.1918981481482 & 50.8708333333333 & 0.321064814814816 & -1.09189814814815 \tabularnewline
25 & 51.9 & 51.330787037037 & 51.4 & -0.0692129629629638 & 0.569212962962965 \tabularnewline
26 & 52.6 & 51.3293981481481 & 51.8625 & -0.533101851851852 & 1.27060185185186 \tabularnewline
27 & 53.2 & 52.1030092592593 & 52.2958333333333 & -0.192824074074073 & 1.09699074074074 \tabularnewline
28 & 53.5 & 52.1981481481482 & 52.7791666666667 & -0.581018518518513 & 1.30185185185184 \tabularnewline
29 & 53.7 & 52.7168981481481 & 53.3 & -0.583101851851852 & 0.983101851851856 \tabularnewline
30 & 53.7 & 52.9766203703704 & 53.8458333333333 & -0.869212962962964 & 0.723379629629633 \tabularnewline
31 & 53.9 & 55.4037037037037 & 54.3958333333333 & 1.00787037037037 & -1.50370370370371 \tabularnewline
32 & 54.1 & 55.7648148148148 & 54.9458333333333 & 0.818981481481483 & -1.66481481481481 \tabularnewline
33 & 54.8 & 55.7821759259259 & 55.5208333333333 & 0.26134259259259 & -0.982175925925937 \tabularnewline
34 & 55.4 & 56.0918981481481 & 56.1083333333333 & -0.0164351851851854 & -0.691898148148141 \tabularnewline
35 & 55.9 & 57.1314814814815 & 56.6958333333333 & 0.435648148148149 & -1.23148148148147 \tabularnewline
36 & 56.8 & 57.6168981481481 & 57.2958333333333 & 0.321064814814816 & -0.816898148148141 \tabularnewline
37 & 58.4 & 57.830787037037 & 57.9 & -0.0692129629629638 & 0.569212962962972 \tabularnewline
38 & 59.3 & 57.9668981481481 & 58.5 & -0.533101851851852 & 1.33310185185186 \tabularnewline
39 & 60.3 & 58.8821759259259 & 59.075 & -0.192824074074073 & 1.41782407407408 \tabularnewline
40 & 60.5 & 59.0231481481481 & 59.6041666666667 & -0.581018518518513 & 1.47685185185185 \tabularnewline
41 & 60.8 & 59.6085648148148 & 60.1916666666667 & -0.583101851851852 & 1.19143518518519 \tabularnewline
42 & 61 & 59.9516203703704 & 60.8208333333333 & -0.869212962962964 & 1.04837962962964 \tabularnewline
43 & 61.1 & 62.3578703703704 & 61.35 & 1.00787037037037 & -1.25787037037036 \tabularnewline
44 & 61.3 & 62.6023148148148 & 61.7833333333333 & 0.818981481481483 & -1.30231481481481 \tabularnewline
45 & 61.4 & 62.4196759259259 & 62.1583333333333 & 0.26134259259259 & -1.01967592592592 \tabularnewline
46 & 61.5 & 62.4835648148148 & 62.5 & -0.0164351851851854 & -0.983564814814812 \tabularnewline
47 & 63.9 & 63.3148148148148 & 62.8791666666667 & 0.435648148148149 & 0.585185185185182 \tabularnewline
48 & 63.9 & 63.6543981481482 & 63.3333333333333 & 0.321064814814816 & 0.245601851851845 \tabularnewline
49 & 64 & 63.8224537037037 & 63.8916666666667 & -0.0692129629629638 & 0.177546296296292 \tabularnewline
50 & 64.1 & 64.0043981481482 & 64.5375 & -0.533101851851852 & 0.0956018518518391 \tabularnewline
51 & 64.5 & 65.0155092592593 & 65.2083333333333 & -0.192824074074073 & -0.515509259259275 \tabularnewline
52 & 64.5 & 65.3314814814815 & 65.9125 & -0.581018518518513 & -0.831481481481489 \tabularnewline
53 & 65.9 & 65.9710648148148 & 66.5541666666667 & -0.583101851851852 & -0.0710648148148181 \tabularnewline
54 & 66.8 & 66.2474537037037 & 67.1166666666667 & -0.869212962962964 & 0.552546296296299 \tabularnewline
55 & 68.7 & 68.687037037037 & 67.6791666666667 & 1.00787037037037 & 0.0129629629629591 \tabularnewline
56 & 69.2 & 69.0648148148148 & 68.2458333333333 & 0.818981481481483 & 0.135185185185193 \tabularnewline
57 & 69.6 & 69.1113425925926 & 68.85 & 0.26134259259259 & 0.488657407407416 \tabularnewline
58 & 70.2 & 69.5335648148148 & 69.55 & -0.0164351851851854 & 0.666435185185208 \tabularnewline
59 & 70.6 & 70.8481481481482 & 70.4125 & 0.435648148148149 & -0.248148148148161 \tabularnewline
60 & 70.7 & 71.7502314814815 & 71.4291666666667 & 0.321064814814816 & -1.05023148148148 \tabularnewline
61 & 70.7 & 72.8516203703704 & 72.9208333333333 & -0.0692129629629638 & -2.15162037037035 \tabularnewline
62 & 71 & 74.3585648148148 & 74.8916666666667 & -0.533101851851852 & -3.3585648148148 \tabularnewline
63 & 72.1 & 76.7446759259259 & 76.9375 & -0.192824074074073 & -4.64467592592592 \tabularnewline
64 & 73.7 & 78.5148148148148 & 79.0958333333333 & -0.581018518518513 & -4.8148148148148 \tabularnewline
65 & 77.4 & 80.9377314814815 & 81.5208333333333 & -0.583101851851852 & -3.53773148148147 \tabularnewline
66 & 79.7 & 83.293287037037 & 84.1625 & -0.869212962962964 & -3.59328703703704 \tabularnewline
67 & 91.6 & 87.8662037037037 & 86.8583333333333 & 1.00787037037037 & 3.73379629629629 \tabularnewline
68 & 93.6 & 90.4273148148148 & 89.6083333333333 & 0.818981481481483 & 3.17268518518519 \tabularnewline
69 & 94.3 & 92.7321759259259 & 92.4708333333333 & 0.26134259259259 & 1.5678240740741 \tabularnewline
70 & 97.3 & 95.3335648148148 & 95.35 & -0.0164351851851854 & 1.96643518518518 \tabularnewline
71 & 101.7 & 98.4898148148148 & 98.0541666666666 & 0.435648148148149 & 3.21018518518521 \tabularnewline
72 & 103 & 100.875231481481 & 100.554166666667 & 0.321064814814816 & 2.12476851851852 \tabularnewline
73 & 103.1 & 102.593287037037 & 102.6625 & -0.0692129629629638 & 0.506712962962965 \tabularnewline
74 & 104.6 & 103.866898148148 & 104.4 & -0.533101851851852 & 0.733101851851856 \tabularnewline
75 & 107.2 & 105.861342592593 & 106.054166666667 & -0.192824074074073 & 1.33865740740742 \tabularnewline
76 & 107.7 & 107.085648148148 & 107.666666666667 & -0.581018518518513 & 0.614351851851879 \tabularnewline
77 & 108.3 & 108.516898148148 & 109.1 & -0.583101851851852 & -0.216898148148147 \tabularnewline
78 & 108.8 & 109.472453703704 & 110.341666666667 & -0.869212962962964 & -0.672453703703709 \tabularnewline
79 & 113.1 & NA & NA & 1.00787037037037 & NA \tabularnewline
80 & 113.8 & NA & NA & 0.818981481481483 & NA \tabularnewline
81 & 113.8 & NA & NA & 0.26134259259259 & NA \tabularnewline
82 & 116.5 & NA & NA & -0.0164351851851854 & NA \tabularnewline
83 & 116.9 & NA & NA & 0.435648148148149 & NA \tabularnewline
84 & 117.6 & NA & NA & 0.321064814814816 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=166887&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]31.1[/C][C]NA[/C][C]NA[/C][C]-0.0692129629629638[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]31.8[/C][C]NA[/C][C]NA[/C][C]-0.533101851851852[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]32.5[/C][C]NA[/C][C]NA[/C][C]-0.192824074074073[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]34.4[/C][C]NA[/C][C]NA[/C][C]-0.581018518518513[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]35.5[/C][C]NA[/C][C]NA[/C][C]-0.583101851851852[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]35.5[/C][C]NA[/C][C]NA[/C][C]-0.869212962962964[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]36.6[/C][C]37.3703703703704[/C][C]36.3625[/C][C]1.00787037037037[/C][C]-0.770370370370365[/C][/ROW]
[ROW][C]8[/C][C]37.1[/C][C]38.0481481481481[/C][C]37.2291666666667[/C][C]0.818981481481483[/C][C]-0.948148148148142[/C][/ROW]
[ROW][C]9[/C][C]37.9[/C][C]38.4155092592593[/C][C]38.1541666666667[/C][C]0.26134259259259[/C][C]-0.515509259259254[/C][/ROW]
[ROW][C]10[/C][C]38.1[/C][C]39.1293981481481[/C][C]39.1458333333333[/C][C]-0.0164351851851854[/C][C]-1.02939814814814[/C][/ROW]
[ROW][C]11[/C][C]39[/C][C]40.5231481481481[/C][C]40.0875[/C][C]0.435648148148149[/C][C]-1.52314814814814[/C][/ROW]
[ROW][C]12[/C][C]41.5[/C][C]41.3502314814815[/C][C]41.0291666666667[/C][C]0.321064814814816[/C][C]0.14976851851852[/C][/ROW]
[ROW][C]13[/C][C]41.8[/C][C]41.9099537037037[/C][C]41.9791666666667[/C][C]-0.0692129629629638[/C][C]-0.109953703703702[/C][/ROW]
[ROW][C]14[/C][C]41.9[/C][C]42.4127314814815[/C][C]42.9458333333333[/C][C]-0.533101851851852[/C][C]-0.512731481481474[/C][/ROW]
[ROW][C]15[/C][C]44.6[/C][C]43.7321759259259[/C][C]43.925[/C][C]-0.192824074074073[/C][C]0.867824074074079[/C][/ROW]
[ROW][C]16[/C][C]46.1[/C][C]44.2856481481481[/C][C]44.8666666666667[/C][C]-0.581018518518513[/C][C]1.81435185185185[/C][/ROW]
[ROW][C]17[/C][C]46.4[/C][C]45.1877314814815[/C][C]45.7708333333333[/C][C]-0.583101851851852[/C][C]1.21226851851851[/C][/ROW]
[ROW][C]18[/C][C]47.2[/C][C]45.6974537037037[/C][C]46.5666666666667[/C][C]-0.869212962962964[/C][C]1.50254629629629[/C][/ROW]
[ROW][C]19[/C][C]47.7[/C][C]48.3537037037037[/C][C]47.3458333333333[/C][C]1.00787037037037[/C][C]-0.653703703703705[/C][/ROW]
[ROW][C]20[/C][C]49.2[/C][C]49.0314814814815[/C][C]48.2125[/C][C]0.818981481481483[/C][C]0.168518518518518[/C][/ROW]
[ROW][C]21[/C][C]49.3[/C][C]49.2780092592593[/C][C]49.0166666666667[/C][C]0.26134259259259[/C][C]0.0219907407407405[/C][/ROW]
[ROW][C]22[/C][C]49.3[/C][C]49.6668981481481[/C][C]49.6833333333333[/C][C]-0.0164351851851854[/C][C]-0.366898148148145[/C][/ROW]
[ROW][C]23[/C][C]49.5[/C][C]50.7314814814815[/C][C]50.2958333333333[/C][C]0.435648148148149[/C][C]-1.23148148148147[/C][/ROW]
[ROW][C]24[/C][C]50.1[/C][C]51.1918981481482[/C][C]50.8708333333333[/C][C]0.321064814814816[/C][C]-1.09189814814815[/C][/ROW]
[ROW][C]25[/C][C]51.9[/C][C]51.330787037037[/C][C]51.4[/C][C]-0.0692129629629638[/C][C]0.569212962962965[/C][/ROW]
[ROW][C]26[/C][C]52.6[/C][C]51.3293981481481[/C][C]51.8625[/C][C]-0.533101851851852[/C][C]1.27060185185186[/C][/ROW]
[ROW][C]27[/C][C]53.2[/C][C]52.1030092592593[/C][C]52.2958333333333[/C][C]-0.192824074074073[/C][C]1.09699074074074[/C][/ROW]
[ROW][C]28[/C][C]53.5[/C][C]52.1981481481482[/C][C]52.7791666666667[/C][C]-0.581018518518513[/C][C]1.30185185185184[/C][/ROW]
[ROW][C]29[/C][C]53.7[/C][C]52.7168981481481[/C][C]53.3[/C][C]-0.583101851851852[/C][C]0.983101851851856[/C][/ROW]
[ROW][C]30[/C][C]53.7[/C][C]52.9766203703704[/C][C]53.8458333333333[/C][C]-0.869212962962964[/C][C]0.723379629629633[/C][/ROW]
[ROW][C]31[/C][C]53.9[/C][C]55.4037037037037[/C][C]54.3958333333333[/C][C]1.00787037037037[/C][C]-1.50370370370371[/C][/ROW]
[ROW][C]32[/C][C]54.1[/C][C]55.7648148148148[/C][C]54.9458333333333[/C][C]0.818981481481483[/C][C]-1.66481481481481[/C][/ROW]
[ROW][C]33[/C][C]54.8[/C][C]55.7821759259259[/C][C]55.5208333333333[/C][C]0.26134259259259[/C][C]-0.982175925925937[/C][/ROW]
[ROW][C]34[/C][C]55.4[/C][C]56.0918981481481[/C][C]56.1083333333333[/C][C]-0.0164351851851854[/C][C]-0.691898148148141[/C][/ROW]
[ROW][C]35[/C][C]55.9[/C][C]57.1314814814815[/C][C]56.6958333333333[/C][C]0.435648148148149[/C][C]-1.23148148148147[/C][/ROW]
[ROW][C]36[/C][C]56.8[/C][C]57.6168981481481[/C][C]57.2958333333333[/C][C]0.321064814814816[/C][C]-0.816898148148141[/C][/ROW]
[ROW][C]37[/C][C]58.4[/C][C]57.830787037037[/C][C]57.9[/C][C]-0.0692129629629638[/C][C]0.569212962962972[/C][/ROW]
[ROW][C]38[/C][C]59.3[/C][C]57.9668981481481[/C][C]58.5[/C][C]-0.533101851851852[/C][C]1.33310185185186[/C][/ROW]
[ROW][C]39[/C][C]60.3[/C][C]58.8821759259259[/C][C]59.075[/C][C]-0.192824074074073[/C][C]1.41782407407408[/C][/ROW]
[ROW][C]40[/C][C]60.5[/C][C]59.0231481481481[/C][C]59.6041666666667[/C][C]-0.581018518518513[/C][C]1.47685185185185[/C][/ROW]
[ROW][C]41[/C][C]60.8[/C][C]59.6085648148148[/C][C]60.1916666666667[/C][C]-0.583101851851852[/C][C]1.19143518518519[/C][/ROW]
[ROW][C]42[/C][C]61[/C][C]59.9516203703704[/C][C]60.8208333333333[/C][C]-0.869212962962964[/C][C]1.04837962962964[/C][/ROW]
[ROW][C]43[/C][C]61.1[/C][C]62.3578703703704[/C][C]61.35[/C][C]1.00787037037037[/C][C]-1.25787037037036[/C][/ROW]
[ROW][C]44[/C][C]61.3[/C][C]62.6023148148148[/C][C]61.7833333333333[/C][C]0.818981481481483[/C][C]-1.30231481481481[/C][/ROW]
[ROW][C]45[/C][C]61.4[/C][C]62.4196759259259[/C][C]62.1583333333333[/C][C]0.26134259259259[/C][C]-1.01967592592592[/C][/ROW]
[ROW][C]46[/C][C]61.5[/C][C]62.4835648148148[/C][C]62.5[/C][C]-0.0164351851851854[/C][C]-0.983564814814812[/C][/ROW]
[ROW][C]47[/C][C]63.9[/C][C]63.3148148148148[/C][C]62.8791666666667[/C][C]0.435648148148149[/C][C]0.585185185185182[/C][/ROW]
[ROW][C]48[/C][C]63.9[/C][C]63.6543981481482[/C][C]63.3333333333333[/C][C]0.321064814814816[/C][C]0.245601851851845[/C][/ROW]
[ROW][C]49[/C][C]64[/C][C]63.8224537037037[/C][C]63.8916666666667[/C][C]-0.0692129629629638[/C][C]0.177546296296292[/C][/ROW]
[ROW][C]50[/C][C]64.1[/C][C]64.0043981481482[/C][C]64.5375[/C][C]-0.533101851851852[/C][C]0.0956018518518391[/C][/ROW]
[ROW][C]51[/C][C]64.5[/C][C]65.0155092592593[/C][C]65.2083333333333[/C][C]-0.192824074074073[/C][C]-0.515509259259275[/C][/ROW]
[ROW][C]52[/C][C]64.5[/C][C]65.3314814814815[/C][C]65.9125[/C][C]-0.581018518518513[/C][C]-0.831481481481489[/C][/ROW]
[ROW][C]53[/C][C]65.9[/C][C]65.9710648148148[/C][C]66.5541666666667[/C][C]-0.583101851851852[/C][C]-0.0710648148148181[/C][/ROW]
[ROW][C]54[/C][C]66.8[/C][C]66.2474537037037[/C][C]67.1166666666667[/C][C]-0.869212962962964[/C][C]0.552546296296299[/C][/ROW]
[ROW][C]55[/C][C]68.7[/C][C]68.687037037037[/C][C]67.6791666666667[/C][C]1.00787037037037[/C][C]0.0129629629629591[/C][/ROW]
[ROW][C]56[/C][C]69.2[/C][C]69.0648148148148[/C][C]68.2458333333333[/C][C]0.818981481481483[/C][C]0.135185185185193[/C][/ROW]
[ROW][C]57[/C][C]69.6[/C][C]69.1113425925926[/C][C]68.85[/C][C]0.26134259259259[/C][C]0.488657407407416[/C][/ROW]
[ROW][C]58[/C][C]70.2[/C][C]69.5335648148148[/C][C]69.55[/C][C]-0.0164351851851854[/C][C]0.666435185185208[/C][/ROW]
[ROW][C]59[/C][C]70.6[/C][C]70.8481481481482[/C][C]70.4125[/C][C]0.435648148148149[/C][C]-0.248148148148161[/C][/ROW]
[ROW][C]60[/C][C]70.7[/C][C]71.7502314814815[/C][C]71.4291666666667[/C][C]0.321064814814816[/C][C]-1.05023148148148[/C][/ROW]
[ROW][C]61[/C][C]70.7[/C][C]72.8516203703704[/C][C]72.9208333333333[/C][C]-0.0692129629629638[/C][C]-2.15162037037035[/C][/ROW]
[ROW][C]62[/C][C]71[/C][C]74.3585648148148[/C][C]74.8916666666667[/C][C]-0.533101851851852[/C][C]-3.3585648148148[/C][/ROW]
[ROW][C]63[/C][C]72.1[/C][C]76.7446759259259[/C][C]76.9375[/C][C]-0.192824074074073[/C][C]-4.64467592592592[/C][/ROW]
[ROW][C]64[/C][C]73.7[/C][C]78.5148148148148[/C][C]79.0958333333333[/C][C]-0.581018518518513[/C][C]-4.8148148148148[/C][/ROW]
[ROW][C]65[/C][C]77.4[/C][C]80.9377314814815[/C][C]81.5208333333333[/C][C]-0.583101851851852[/C][C]-3.53773148148147[/C][/ROW]
[ROW][C]66[/C][C]79.7[/C][C]83.293287037037[/C][C]84.1625[/C][C]-0.869212962962964[/C][C]-3.59328703703704[/C][/ROW]
[ROW][C]67[/C][C]91.6[/C][C]87.8662037037037[/C][C]86.8583333333333[/C][C]1.00787037037037[/C][C]3.73379629629629[/C][/ROW]
[ROW][C]68[/C][C]93.6[/C][C]90.4273148148148[/C][C]89.6083333333333[/C][C]0.818981481481483[/C][C]3.17268518518519[/C][/ROW]
[ROW][C]69[/C][C]94.3[/C][C]92.7321759259259[/C][C]92.4708333333333[/C][C]0.26134259259259[/C][C]1.5678240740741[/C][/ROW]
[ROW][C]70[/C][C]97.3[/C][C]95.3335648148148[/C][C]95.35[/C][C]-0.0164351851851854[/C][C]1.96643518518518[/C][/ROW]
[ROW][C]71[/C][C]101.7[/C][C]98.4898148148148[/C][C]98.0541666666666[/C][C]0.435648148148149[/C][C]3.21018518518521[/C][/ROW]
[ROW][C]72[/C][C]103[/C][C]100.875231481481[/C][C]100.554166666667[/C][C]0.321064814814816[/C][C]2.12476851851852[/C][/ROW]
[ROW][C]73[/C][C]103.1[/C][C]102.593287037037[/C][C]102.6625[/C][C]-0.0692129629629638[/C][C]0.506712962962965[/C][/ROW]
[ROW][C]74[/C][C]104.6[/C][C]103.866898148148[/C][C]104.4[/C][C]-0.533101851851852[/C][C]0.733101851851856[/C][/ROW]
[ROW][C]75[/C][C]107.2[/C][C]105.861342592593[/C][C]106.054166666667[/C][C]-0.192824074074073[/C][C]1.33865740740742[/C][/ROW]
[ROW][C]76[/C][C]107.7[/C][C]107.085648148148[/C][C]107.666666666667[/C][C]-0.581018518518513[/C][C]0.614351851851879[/C][/ROW]
[ROW][C]77[/C][C]108.3[/C][C]108.516898148148[/C][C]109.1[/C][C]-0.583101851851852[/C][C]-0.216898148148147[/C][/ROW]
[ROW][C]78[/C][C]108.8[/C][C]109.472453703704[/C][C]110.341666666667[/C][C]-0.869212962962964[/C][C]-0.672453703703709[/C][/ROW]
[ROW][C]79[/C][C]113.1[/C][C]NA[/C][C]NA[/C][C]1.00787037037037[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]113.8[/C][C]NA[/C][C]NA[/C][C]0.818981481481483[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]113.8[/C][C]NA[/C][C]NA[/C][C]0.26134259259259[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]116.5[/C][C]NA[/C][C]NA[/C][C]-0.0164351851851854[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]116.9[/C][C]NA[/C][C]NA[/C][C]0.435648148148149[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]117.6[/C][C]NA[/C][C]NA[/C][C]0.321064814814816[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=166887&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=166887&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	31.1	NA	NA	-0.0692129629629638	NA
2	31.8	NA	NA	-0.533101851851852	NA
3	32.5	NA	NA	-0.192824074074073	NA
4	34.4	NA	NA	-0.581018518518513	NA
5	35.5	NA	NA	-0.583101851851852	NA
6	35.5	NA	NA	-0.869212962962964	NA
7	36.6	37.3703703703704	36.3625	1.00787037037037	-0.770370370370365
8	37.1	38.0481481481481	37.2291666666667	0.818981481481483	-0.948148148148142
9	37.9	38.4155092592593	38.1541666666667	0.26134259259259	-0.515509259259254
10	38.1	39.1293981481481	39.1458333333333	-0.0164351851851854	-1.02939814814814
11	39	40.5231481481481	40.0875	0.435648148148149	-1.52314814814814
12	41.5	41.3502314814815	41.0291666666667	0.321064814814816	0.14976851851852
13	41.8	41.9099537037037	41.9791666666667	-0.0692129629629638	-0.109953703703702
14	41.9	42.4127314814815	42.9458333333333	-0.533101851851852	-0.512731481481474
15	44.6	43.7321759259259	43.925	-0.192824074074073	0.867824074074079
16	46.1	44.2856481481481	44.8666666666667	-0.581018518518513	1.81435185185185
17	46.4	45.1877314814815	45.7708333333333	-0.583101851851852	1.21226851851851
18	47.2	45.6974537037037	46.5666666666667	-0.869212962962964	1.50254629629629
19	47.7	48.3537037037037	47.3458333333333	1.00787037037037	-0.653703703703705
20	49.2	49.0314814814815	48.2125	0.818981481481483	0.168518518518518
21	49.3	49.2780092592593	49.0166666666667	0.26134259259259	0.0219907407407405
22	49.3	49.6668981481481	49.6833333333333	-0.0164351851851854	-0.366898148148145
23	49.5	50.7314814814815	50.2958333333333	0.435648148148149	-1.23148148148147
24	50.1	51.1918981481482	50.8708333333333	0.321064814814816	-1.09189814814815
25	51.9	51.330787037037	51.4	-0.0692129629629638	0.569212962962965
26	52.6	51.3293981481481	51.8625	-0.533101851851852	1.27060185185186
27	53.2	52.1030092592593	52.2958333333333	-0.192824074074073	1.09699074074074
28	53.5	52.1981481481482	52.7791666666667	-0.581018518518513	1.30185185185184
29	53.7	52.7168981481481	53.3	-0.583101851851852	0.983101851851856
30	53.7	52.9766203703704	53.8458333333333	-0.869212962962964	0.723379629629633
31	53.9	55.4037037037037	54.3958333333333	1.00787037037037	-1.50370370370371
32	54.1	55.7648148148148	54.9458333333333	0.818981481481483	-1.66481481481481
33	54.8	55.7821759259259	55.5208333333333	0.26134259259259	-0.982175925925937
34	55.4	56.0918981481481	56.1083333333333	-0.0164351851851854	-0.691898148148141
35	55.9	57.1314814814815	56.6958333333333	0.435648148148149	-1.23148148148147
36	56.8	57.6168981481481	57.2958333333333	0.321064814814816	-0.816898148148141
37	58.4	57.830787037037	57.9	-0.0692129629629638	0.569212962962972
38	59.3	57.9668981481481	58.5	-0.533101851851852	1.33310185185186
39	60.3	58.8821759259259	59.075	-0.192824074074073	1.41782407407408
40	60.5	59.0231481481481	59.6041666666667	-0.581018518518513	1.47685185185185
41	60.8	59.6085648148148	60.1916666666667	-0.583101851851852	1.19143518518519
42	61	59.9516203703704	60.8208333333333	-0.869212962962964	1.04837962962964
43	61.1	62.3578703703704	61.35	1.00787037037037	-1.25787037037036
44	61.3	62.6023148148148	61.7833333333333	0.818981481481483	-1.30231481481481
45	61.4	62.4196759259259	62.1583333333333	0.26134259259259	-1.01967592592592
46	61.5	62.4835648148148	62.5	-0.0164351851851854	-0.983564814814812
47	63.9	63.3148148148148	62.8791666666667	0.435648148148149	0.585185185185182
48	63.9	63.6543981481482	63.3333333333333	0.321064814814816	0.245601851851845
49	64	63.8224537037037	63.8916666666667	-0.0692129629629638	0.177546296296292
50	64.1	64.0043981481482	64.5375	-0.533101851851852	0.0956018518518391
51	64.5	65.0155092592593	65.2083333333333	-0.192824074074073	-0.515509259259275
52	64.5	65.3314814814815	65.9125	-0.581018518518513	-0.831481481481489
53	65.9	65.9710648148148	66.5541666666667	-0.583101851851852	-0.0710648148148181
54	66.8	66.2474537037037	67.1166666666667	-0.869212962962964	0.552546296296299
55	68.7	68.687037037037	67.6791666666667	1.00787037037037	0.0129629629629591
56	69.2	69.0648148148148	68.2458333333333	0.818981481481483	0.135185185185193
57	69.6	69.1113425925926	68.85	0.26134259259259	0.488657407407416
58	70.2	69.5335648148148	69.55	-0.0164351851851854	0.666435185185208
59	70.6	70.8481481481482	70.4125	0.435648148148149	-0.248148148148161
60	70.7	71.7502314814815	71.4291666666667	0.321064814814816	-1.05023148148148
61	70.7	72.8516203703704	72.9208333333333	-0.0692129629629638	-2.15162037037035
62	71	74.3585648148148	74.8916666666667	-0.533101851851852	-3.3585648148148
63	72.1	76.7446759259259	76.9375	-0.192824074074073	-4.64467592592592
64	73.7	78.5148148148148	79.0958333333333	-0.581018518518513	-4.8148148148148
65	77.4	80.9377314814815	81.5208333333333	-0.583101851851852	-3.53773148148147
66	79.7	83.293287037037	84.1625	-0.869212962962964	-3.59328703703704
67	91.6	87.8662037037037	86.8583333333333	1.00787037037037	3.73379629629629
68	93.6	90.4273148148148	89.6083333333333	0.818981481481483	3.17268518518519
69	94.3	92.7321759259259	92.4708333333333	0.26134259259259	1.5678240740741
70	97.3	95.3335648148148	95.35	-0.0164351851851854	1.96643518518518
71	101.7	98.4898148148148	98.0541666666666	0.435648148148149	3.21018518518521
72	103	100.875231481481	100.554166666667	0.321064814814816	2.12476851851852
73	103.1	102.593287037037	102.6625	-0.0692129629629638	0.506712962962965
74	104.6	103.866898148148	104.4	-0.533101851851852	0.733101851851856
75	107.2	105.861342592593	106.054166666667	-0.192824074074073	1.33865740740742
76	107.7	107.085648148148	107.666666666667	-0.581018518518513	0.614351851851879
77	108.3	108.516898148148	109.1	-0.583101851851852	-0.216898148148147
78	108.8	109.472453703704	110.341666666667	-0.869212962962964	-0.672453703703709
79	113.1	NA	NA	1.00787037037037	NA
80	113.8	NA	NA	0.818981481481483	NA
81	113.8	NA	NA	0.26134259259259	NA
82	116.5	NA	NA	-0.0164351851851854	NA
83	116.9	NA	NA	0.435648148148149	NA
84	117.6	NA	NA	0.321064814814816	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