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R Software Module

rwasp_decompose.wasp

Title produced by software

Classical Decomposition

Date of computation

Thu, 22 Nov 2012 07:50:16 -0500

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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/Nov/22/t1353588694h5lr7i6yibv1bs2.htm/, Retrieved Thu, 02 May 2024 01:52:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=191631, Retrieved Thu, 02 May 2024 01:52:17 +0000

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

-       [Classical Decomposition] [WS 8 Classical de...] [2012-11-22 12:50:16] [46cc0db4bd6f6541b375e62191991224] [Current]

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3,06
3,07
3,08
3,07
3,08
3,06
3,07
3,04
3,05
3,06
3,05
3,06
3,07
3,07
3,1
3,1
3,1
3,1
3,09
3,08
3,1
3,08
3,08
3,09
3,11
3,19
3,24
3,25
3,22
3,21
3,21
3,19
3,21
3,21
3,19
3,18
3,16
3,15
3,15
3,14
3,14
3,12
3,12
3,12
3,12
3,13
3,14
3,14
3,16
3,19
3,18
3,18
3,19
3,18
3,17
3,17
3,16
3,15
3,14
3,15
3,15
3,16
3,18
3,18
3,19
3,18
3,19
3,2
3,2
3,18
3,2
3,21
3,24
3,29
3,28
3,27
3,29
3,27
3,27
3,25
3,25
3,23
3,23
3,25

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	7 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 & 7 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191631&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]7 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=191631&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191631&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	7 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Classical Decomposition by Moving Averages
t	Observations	Fit	Trend	Seasonal	Random
1	3.06	NA	NA	-0.0103530092592592	NA
2	3.07	NA	NA	0.0134664351851852	NA
3	3.08	NA	NA	0.0239525462962964	NA
4	3.07	NA	NA	0.0197164351851854	NA
5	3.08	NA	NA	0.0189525462962962	NA
6	3.06	NA	NA	0.00471643518518519	NA
7	3.07	3.06298032407407	3.06291666666667	6.36574074070593e-05	0.00701967592592601
8	3.04	3.05228587962963	3.06333333333333	-0.011047453703704	-0.0122858796296295
9	3.05	3.05686921296296	3.06416666666667	-0.00729745370370365	-0.00686921296296283
10	3.06	3.05117476851852	3.06625	-0.0150752314814814	0.00882523148148184
11	3.05	3.04874421296296	3.06833333333333	-0.0195891203703703	0.00125578703703733
12	3.06	3.0533275462963	3.07083333333333	-0.0175057870370369	0.00667245370370395
13	3.07	3.06298032407407	3.07333333333333	-0.0103530092592592	0.00701967592592601
14	3.07	3.08929976851852	3.07583333333333	0.0134664351851852	-0.0192997685185179
15	3.1	3.10353587962963	3.07958333333333	0.0239525462962964	-0.00353587962962854
16	3.1	3.10221643518519	3.0825	0.0197164351851854	-0.002216435185185
17	3.1	3.10353587962963	3.08458333333333	0.0189525462962962	-0.00353587962962942
18	3.1	3.09179976851852	3.08708333333333	0.00471643518518519	0.00820023148148152
19	3.09	3.09006365740741	3.09	6.36574074070593e-05	-6.36574074071028e-05
20	3.08	3.08561921296296	3.09666666666667	-0.011047453703704	-0.00561921296296264
21	3.1	3.1002025462963	3.1075	-0.00729745370370365	-0.000202546296296013
22	3.08	3.10450810185185	3.11958333333333	-0.0150752314814814	-0.0245081018518518
23	3.08	3.11124421296296	3.13083333333333	-0.0195891203703703	-0.0312442129629629
24	3.09	3.12291087962963	3.14041666666667	-0.0175057870370369	-0.0329108796296302
25	3.11	3.13964699074074	3.15	-0.0103530092592592	-0.0296469907407415
26	3.19	3.17304976851852	3.15958333333333	0.0134664351851852	0.0169502314814816
27	3.24	3.1927025462963	3.16875	0.0239525462962964	0.0472974537037039
28	3.25	3.19846643518519	3.17875	0.0197164351851854	0.051533564814815
29	3.22	3.2077025462963	3.18875	0.0189525462962962	0.0122974537037042
30	3.21	3.20179976851852	3.19708333333333	0.00471643518518519	0.00820023148148108
31	3.21	3.20298032407407	3.20291666666667	6.36574074070593e-05	0.00701967592592601
32	3.19	3.19228587962963	3.20333333333333	-0.011047453703704	-0.00228587962962967
33	3.21	3.19061921296296	3.19791666666667	-0.00729745370370365	0.0193807870370368
34	3.21	3.17450810185185	3.18958333333333	-0.0150752314814814	0.0354918981481478
35	3.19	3.1620775462963	3.18166666666667	-0.0195891203703703	0.0279224537037037
36	3.18	3.1570775462963	3.17458333333333	-0.0175057870370369	0.0229224537037038
37	3.16	3.15673032407407	3.16708333333333	-0.0103530092592592	0.00326967592592586
38	3.15	3.17388310185185	3.16041666666667	0.0134664351851852	-0.0238831018518515
39	3.15	3.1777025462963	3.15375	0.0239525462962964	-0.0277025462962963
40	3.14	3.16638310185185	3.14666666666667	0.0197164351851854	-0.0263831018518519
41	3.14	3.1602025462963	3.14125	0.0189525462962962	-0.0202025462962965
42	3.12	3.14221643518519	3.1375	0.00471643518518519	-0.0222164351851855
43	3.12	3.13589699074074	3.13583333333333	6.36574074070593e-05	-0.0158969907407407
44	3.12	3.1264525462963	3.1375	-0.011047453703704	-0.0064525462962961
45	3.12	3.13311921296296	3.14041666666667	-0.00729745370370365	-0.0131192129629625
46	3.13	3.12825810185185	3.14333333333333	-0.0150752314814814	0.00174189814814874
47	3.14	3.12749421296296	3.14708333333333	-0.0195891203703703	0.0125057870370378
48	3.14	3.13416087962963	3.15166666666667	-0.0175057870370369	0.00583912037037093
49	3.16	3.14589699074074	3.15625	-0.0103530092592592	0.0141030092592596
50	3.19	3.17388310185185	3.16041666666667	0.0134664351851852	0.0161168981481485
51	3.18	3.18811921296296	3.16416666666667	0.0239525462962964	-0.00811921296296214
52	3.18	3.18638310185185	3.16666666666667	0.0197164351851854	-0.00638310185185142
53	3.19	3.1864525462963	3.1675	0.0189525462962962	0.00354745370370413
54	3.18	3.17263310185185	3.16791666666667	0.00471643518518519	0.0073668981481485
55	3.17	3.16798032407407	3.16791666666667	6.36574074070593e-05	0.00201967592592611
56	3.17	3.1552025462963	3.16625	-0.011047453703704	0.0147974537037037
57	3.16	3.1577025462963	3.165	-0.00729745370370365	0.00229745370370438
58	3.15	3.14992476851852	3.165	-0.0150752314814814	7.52314814818078e-05
59	3.14	3.14541087962963	3.165	-0.0195891203703703	-0.00541087962962949
60	3.15	3.14749421296296	3.165	-0.0175057870370369	0.00250578703703708
61	3.15	3.15548032407407	3.16583333333333	-0.0103530092592592	-0.00548032407407417
62	3.16	3.18138310185185	3.16791666666667	0.0134664351851852	-0.0213831018518515
63	3.18	3.19478587962963	3.17083333333333	0.0239525462962964	-0.0147858796296299
64	3.18	3.19346643518519	3.17375	0.0197164351851854	-0.0134664351851859
65	3.19	3.1964525462963	3.1775	0.0189525462962962	-0.00645254629629655
66	3.18	3.18721643518519	3.1825	0.00471643518518519	-0.00721643518518533
67	3.19	3.18881365740741	3.18875	6.36574074070593e-05	0.00118634259259265
68	3.2	3.18686921296296	3.19791666666667	-0.011047453703704	0.0131307870370372
69	3.2	3.2002025462963	3.2075	-0.00729745370370365	-0.000202546296295569
70	3.18	3.20034143518518	3.21541666666667	-0.0150752314814814	-0.0203414351851845
71	3.2	3.20374421296296	3.22333333333333	-0.0195891203703703	-0.00374421296296257
72	3.21	3.21374421296296	3.23125	-0.0175057870370369	-0.00374421296296301
73	3.24	3.22798032407407	3.23833333333333	-0.0103530092592592	0.0120196759259263
74	3.29	3.25721643518518	3.24375	0.0134664351851852	0.0327835648148151
75	3.28	3.27186921296296	3.24791666666667	0.0239525462962964	0.00813078703703729
76	3.27	3.27179976851852	3.25208333333333	0.0197164351851854	-0.00179976851851826
77	3.29	3.27436921296296	3.25541666666667	0.0189525462962962	0.0156307870370371
78	3.27	3.26304976851852	3.25833333333333	0.00471643518518519	0.00695023148148177
79	3.27	NA	NA	6.36574074070593e-05	NA
80	3.25	NA	NA	-0.011047453703704	NA
81	3.25	NA	NA	-0.00729745370370365	NA
82	3.23	NA	NA	-0.0150752314814814	NA
83	3.23	NA	NA	-0.0195891203703703	NA
84	3.25	NA	NA	-0.0175057870370369	NA

\begin{tabular}{lllllllll}
\hline
Classical Decomposition by Moving Averages \tabularnewline
t & Observations & Fit & Trend & Seasonal & Random \tabularnewline
1 & 3.06 & NA & NA & -0.0103530092592592 & NA \tabularnewline
2 & 3.07 & NA & NA & 0.0134664351851852 & NA \tabularnewline
3 & 3.08 & NA & NA & 0.0239525462962964 & NA \tabularnewline
4 & 3.07 & NA & NA & 0.0197164351851854 & NA \tabularnewline
5 & 3.08 & NA & NA & 0.0189525462962962 & NA \tabularnewline
6 & 3.06 & NA & NA & 0.00471643518518519 & NA \tabularnewline
7 & 3.07 & 3.06298032407407 & 3.06291666666667 & 6.36574074070593e-05 & 0.00701967592592601 \tabularnewline
8 & 3.04 & 3.05228587962963 & 3.06333333333333 & -0.011047453703704 & -0.0122858796296295 \tabularnewline
9 & 3.05 & 3.05686921296296 & 3.06416666666667 & -0.00729745370370365 & -0.00686921296296283 \tabularnewline
10 & 3.06 & 3.05117476851852 & 3.06625 & -0.0150752314814814 & 0.00882523148148184 \tabularnewline
11 & 3.05 & 3.04874421296296 & 3.06833333333333 & -0.0195891203703703 & 0.00125578703703733 \tabularnewline
12 & 3.06 & 3.0533275462963 & 3.07083333333333 & -0.0175057870370369 & 0.00667245370370395 \tabularnewline
13 & 3.07 & 3.06298032407407 & 3.07333333333333 & -0.0103530092592592 & 0.00701967592592601 \tabularnewline
14 & 3.07 & 3.08929976851852 & 3.07583333333333 & 0.0134664351851852 & -0.0192997685185179 \tabularnewline
15 & 3.1 & 3.10353587962963 & 3.07958333333333 & 0.0239525462962964 & -0.00353587962962854 \tabularnewline
16 & 3.1 & 3.10221643518519 & 3.0825 & 0.0197164351851854 & -0.002216435185185 \tabularnewline
17 & 3.1 & 3.10353587962963 & 3.08458333333333 & 0.0189525462962962 & -0.00353587962962942 \tabularnewline
18 & 3.1 & 3.09179976851852 & 3.08708333333333 & 0.00471643518518519 & 0.00820023148148152 \tabularnewline
19 & 3.09 & 3.09006365740741 & 3.09 & 6.36574074070593e-05 & -6.36574074071028e-05 \tabularnewline
20 & 3.08 & 3.08561921296296 & 3.09666666666667 & -0.011047453703704 & -0.00561921296296264 \tabularnewline
21 & 3.1 & 3.1002025462963 & 3.1075 & -0.00729745370370365 & -0.000202546296296013 \tabularnewline
22 & 3.08 & 3.10450810185185 & 3.11958333333333 & -0.0150752314814814 & -0.0245081018518518 \tabularnewline
23 & 3.08 & 3.11124421296296 & 3.13083333333333 & -0.0195891203703703 & -0.0312442129629629 \tabularnewline
24 & 3.09 & 3.12291087962963 & 3.14041666666667 & -0.0175057870370369 & -0.0329108796296302 \tabularnewline
25 & 3.11 & 3.13964699074074 & 3.15 & -0.0103530092592592 & -0.0296469907407415 \tabularnewline
26 & 3.19 & 3.17304976851852 & 3.15958333333333 & 0.0134664351851852 & 0.0169502314814816 \tabularnewline
27 & 3.24 & 3.1927025462963 & 3.16875 & 0.0239525462962964 & 0.0472974537037039 \tabularnewline
28 & 3.25 & 3.19846643518519 & 3.17875 & 0.0197164351851854 & 0.051533564814815 \tabularnewline
29 & 3.22 & 3.2077025462963 & 3.18875 & 0.0189525462962962 & 0.0122974537037042 \tabularnewline
30 & 3.21 & 3.20179976851852 & 3.19708333333333 & 0.00471643518518519 & 0.00820023148148108 \tabularnewline
31 & 3.21 & 3.20298032407407 & 3.20291666666667 & 6.36574074070593e-05 & 0.00701967592592601 \tabularnewline
32 & 3.19 & 3.19228587962963 & 3.20333333333333 & -0.011047453703704 & -0.00228587962962967 \tabularnewline
33 & 3.21 & 3.19061921296296 & 3.19791666666667 & -0.00729745370370365 & 0.0193807870370368 \tabularnewline
34 & 3.21 & 3.17450810185185 & 3.18958333333333 & -0.0150752314814814 & 0.0354918981481478 \tabularnewline
35 & 3.19 & 3.1620775462963 & 3.18166666666667 & -0.0195891203703703 & 0.0279224537037037 \tabularnewline
36 & 3.18 & 3.1570775462963 & 3.17458333333333 & -0.0175057870370369 & 0.0229224537037038 \tabularnewline
37 & 3.16 & 3.15673032407407 & 3.16708333333333 & -0.0103530092592592 & 0.00326967592592586 \tabularnewline
38 & 3.15 & 3.17388310185185 & 3.16041666666667 & 0.0134664351851852 & -0.0238831018518515 \tabularnewline
39 & 3.15 & 3.1777025462963 & 3.15375 & 0.0239525462962964 & -0.0277025462962963 \tabularnewline
40 & 3.14 & 3.16638310185185 & 3.14666666666667 & 0.0197164351851854 & -0.0263831018518519 \tabularnewline
41 & 3.14 & 3.1602025462963 & 3.14125 & 0.0189525462962962 & -0.0202025462962965 \tabularnewline
42 & 3.12 & 3.14221643518519 & 3.1375 & 0.00471643518518519 & -0.0222164351851855 \tabularnewline
43 & 3.12 & 3.13589699074074 & 3.13583333333333 & 6.36574074070593e-05 & -0.0158969907407407 \tabularnewline
44 & 3.12 & 3.1264525462963 & 3.1375 & -0.011047453703704 & -0.0064525462962961 \tabularnewline
45 & 3.12 & 3.13311921296296 & 3.14041666666667 & -0.00729745370370365 & -0.0131192129629625 \tabularnewline
46 & 3.13 & 3.12825810185185 & 3.14333333333333 & -0.0150752314814814 & 0.00174189814814874 \tabularnewline
47 & 3.14 & 3.12749421296296 & 3.14708333333333 & -0.0195891203703703 & 0.0125057870370378 \tabularnewline
48 & 3.14 & 3.13416087962963 & 3.15166666666667 & -0.0175057870370369 & 0.00583912037037093 \tabularnewline
49 & 3.16 & 3.14589699074074 & 3.15625 & -0.0103530092592592 & 0.0141030092592596 \tabularnewline
50 & 3.19 & 3.17388310185185 & 3.16041666666667 & 0.0134664351851852 & 0.0161168981481485 \tabularnewline
51 & 3.18 & 3.18811921296296 & 3.16416666666667 & 0.0239525462962964 & -0.00811921296296214 \tabularnewline
52 & 3.18 & 3.18638310185185 & 3.16666666666667 & 0.0197164351851854 & -0.00638310185185142 \tabularnewline
53 & 3.19 & 3.1864525462963 & 3.1675 & 0.0189525462962962 & 0.00354745370370413 \tabularnewline
54 & 3.18 & 3.17263310185185 & 3.16791666666667 & 0.00471643518518519 & 0.0073668981481485 \tabularnewline
55 & 3.17 & 3.16798032407407 & 3.16791666666667 & 6.36574074070593e-05 & 0.00201967592592611 \tabularnewline
56 & 3.17 & 3.1552025462963 & 3.16625 & -0.011047453703704 & 0.0147974537037037 \tabularnewline
57 & 3.16 & 3.1577025462963 & 3.165 & -0.00729745370370365 & 0.00229745370370438 \tabularnewline
58 & 3.15 & 3.14992476851852 & 3.165 & -0.0150752314814814 & 7.52314814818078e-05 \tabularnewline
59 & 3.14 & 3.14541087962963 & 3.165 & -0.0195891203703703 & -0.00541087962962949 \tabularnewline
60 & 3.15 & 3.14749421296296 & 3.165 & -0.0175057870370369 & 0.00250578703703708 \tabularnewline
61 & 3.15 & 3.15548032407407 & 3.16583333333333 & -0.0103530092592592 & -0.00548032407407417 \tabularnewline
62 & 3.16 & 3.18138310185185 & 3.16791666666667 & 0.0134664351851852 & -0.0213831018518515 \tabularnewline
63 & 3.18 & 3.19478587962963 & 3.17083333333333 & 0.0239525462962964 & -0.0147858796296299 \tabularnewline
64 & 3.18 & 3.19346643518519 & 3.17375 & 0.0197164351851854 & -0.0134664351851859 \tabularnewline
65 & 3.19 & 3.1964525462963 & 3.1775 & 0.0189525462962962 & -0.00645254629629655 \tabularnewline
66 & 3.18 & 3.18721643518519 & 3.1825 & 0.00471643518518519 & -0.00721643518518533 \tabularnewline
67 & 3.19 & 3.18881365740741 & 3.18875 & 6.36574074070593e-05 & 0.00118634259259265 \tabularnewline
68 & 3.2 & 3.18686921296296 & 3.19791666666667 & -0.011047453703704 & 0.0131307870370372 \tabularnewline
69 & 3.2 & 3.2002025462963 & 3.2075 & -0.00729745370370365 & -0.000202546296295569 \tabularnewline
70 & 3.18 & 3.20034143518518 & 3.21541666666667 & -0.0150752314814814 & -0.0203414351851845 \tabularnewline
71 & 3.2 & 3.20374421296296 & 3.22333333333333 & -0.0195891203703703 & -0.00374421296296257 \tabularnewline
72 & 3.21 & 3.21374421296296 & 3.23125 & -0.0175057870370369 & -0.00374421296296301 \tabularnewline
73 & 3.24 & 3.22798032407407 & 3.23833333333333 & -0.0103530092592592 & 0.0120196759259263 \tabularnewline
74 & 3.29 & 3.25721643518518 & 3.24375 & 0.0134664351851852 & 0.0327835648148151 \tabularnewline
75 & 3.28 & 3.27186921296296 & 3.24791666666667 & 0.0239525462962964 & 0.00813078703703729 \tabularnewline
76 & 3.27 & 3.27179976851852 & 3.25208333333333 & 0.0197164351851854 & -0.00179976851851826 \tabularnewline
77 & 3.29 & 3.27436921296296 & 3.25541666666667 & 0.0189525462962962 & 0.0156307870370371 \tabularnewline
78 & 3.27 & 3.26304976851852 & 3.25833333333333 & 0.00471643518518519 & 0.00695023148148177 \tabularnewline
79 & 3.27 & NA & NA & 6.36574074070593e-05 & NA \tabularnewline
80 & 3.25 & NA & NA & -0.011047453703704 & NA \tabularnewline
81 & 3.25 & NA & NA & -0.00729745370370365 & NA \tabularnewline
82 & 3.23 & NA & NA & -0.0150752314814814 & NA \tabularnewline
83 & 3.23 & NA & NA & -0.0195891203703703 & NA \tabularnewline
84 & 3.25 & NA & NA & -0.0175057870370369 & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191631&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]3.06[/C][C]NA[/C][C]NA[/C][C]-0.0103530092592592[/C][C]NA[/C][/ROW]
[ROW][C]2[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]0.0134664351851852[/C][C]NA[/C][/ROW]
[ROW][C]3[/C][C]3.08[/C][C]NA[/C][C]NA[/C][C]0.0239525462962964[/C][C]NA[/C][/ROW]
[ROW][C]4[/C][C]3.07[/C][C]NA[/C][C]NA[/C][C]0.0197164351851854[/C][C]NA[/C][/ROW]
[ROW][C]5[/C][C]3.08[/C][C]NA[/C][C]NA[/C][C]0.0189525462962962[/C][C]NA[/C][/ROW]
[ROW][C]6[/C][C]3.06[/C][C]NA[/C][C]NA[/C][C]0.00471643518518519[/C][C]NA[/C][/ROW]
[ROW][C]7[/C][C]3.07[/C][C]3.06298032407407[/C][C]3.06291666666667[/C][C]6.36574074070593e-05[/C][C]0.00701967592592601[/C][/ROW]
[ROW][C]8[/C][C]3.04[/C][C]3.05228587962963[/C][C]3.06333333333333[/C][C]-0.011047453703704[/C][C]-0.0122858796296295[/C][/ROW]
[ROW][C]9[/C][C]3.05[/C][C]3.05686921296296[/C][C]3.06416666666667[/C][C]-0.00729745370370365[/C][C]-0.00686921296296283[/C][/ROW]
[ROW][C]10[/C][C]3.06[/C][C]3.05117476851852[/C][C]3.06625[/C][C]-0.0150752314814814[/C][C]0.00882523148148184[/C][/ROW]
[ROW][C]11[/C][C]3.05[/C][C]3.04874421296296[/C][C]3.06833333333333[/C][C]-0.0195891203703703[/C][C]0.00125578703703733[/C][/ROW]
[ROW][C]12[/C][C]3.06[/C][C]3.0533275462963[/C][C]3.07083333333333[/C][C]-0.0175057870370369[/C][C]0.00667245370370395[/C][/ROW]
[ROW][C]13[/C][C]3.07[/C][C]3.06298032407407[/C][C]3.07333333333333[/C][C]-0.0103530092592592[/C][C]0.00701967592592601[/C][/ROW]
[ROW][C]14[/C][C]3.07[/C][C]3.08929976851852[/C][C]3.07583333333333[/C][C]0.0134664351851852[/C][C]-0.0192997685185179[/C][/ROW]
[ROW][C]15[/C][C]3.1[/C][C]3.10353587962963[/C][C]3.07958333333333[/C][C]0.0239525462962964[/C][C]-0.00353587962962854[/C][/ROW]
[ROW][C]16[/C][C]3.1[/C][C]3.10221643518519[/C][C]3.0825[/C][C]0.0197164351851854[/C][C]-0.002216435185185[/C][/ROW]
[ROW][C]17[/C][C]3.1[/C][C]3.10353587962963[/C][C]3.08458333333333[/C][C]0.0189525462962962[/C][C]-0.00353587962962942[/C][/ROW]
[ROW][C]18[/C][C]3.1[/C][C]3.09179976851852[/C][C]3.08708333333333[/C][C]0.00471643518518519[/C][C]0.00820023148148152[/C][/ROW]
[ROW][C]19[/C][C]3.09[/C][C]3.09006365740741[/C][C]3.09[/C][C]6.36574074070593e-05[/C][C]-6.36574074071028e-05[/C][/ROW]
[ROW][C]20[/C][C]3.08[/C][C]3.08561921296296[/C][C]3.09666666666667[/C][C]-0.011047453703704[/C][C]-0.00561921296296264[/C][/ROW]
[ROW][C]21[/C][C]3.1[/C][C]3.1002025462963[/C][C]3.1075[/C][C]-0.00729745370370365[/C][C]-0.000202546296296013[/C][/ROW]
[ROW][C]22[/C][C]3.08[/C][C]3.10450810185185[/C][C]3.11958333333333[/C][C]-0.0150752314814814[/C][C]-0.0245081018518518[/C][/ROW]
[ROW][C]23[/C][C]3.08[/C][C]3.11124421296296[/C][C]3.13083333333333[/C][C]-0.0195891203703703[/C][C]-0.0312442129629629[/C][/ROW]
[ROW][C]24[/C][C]3.09[/C][C]3.12291087962963[/C][C]3.14041666666667[/C][C]-0.0175057870370369[/C][C]-0.0329108796296302[/C][/ROW]
[ROW][C]25[/C][C]3.11[/C][C]3.13964699074074[/C][C]3.15[/C][C]-0.0103530092592592[/C][C]-0.0296469907407415[/C][/ROW]
[ROW][C]26[/C][C]3.19[/C][C]3.17304976851852[/C][C]3.15958333333333[/C][C]0.0134664351851852[/C][C]0.0169502314814816[/C][/ROW]
[ROW][C]27[/C][C]3.24[/C][C]3.1927025462963[/C][C]3.16875[/C][C]0.0239525462962964[/C][C]0.0472974537037039[/C][/ROW]
[ROW][C]28[/C][C]3.25[/C][C]3.19846643518519[/C][C]3.17875[/C][C]0.0197164351851854[/C][C]0.051533564814815[/C][/ROW]
[ROW][C]29[/C][C]3.22[/C][C]3.2077025462963[/C][C]3.18875[/C][C]0.0189525462962962[/C][C]0.0122974537037042[/C][/ROW]
[ROW][C]30[/C][C]3.21[/C][C]3.20179976851852[/C][C]3.19708333333333[/C][C]0.00471643518518519[/C][C]0.00820023148148108[/C][/ROW]
[ROW][C]31[/C][C]3.21[/C][C]3.20298032407407[/C][C]3.20291666666667[/C][C]6.36574074070593e-05[/C][C]0.00701967592592601[/C][/ROW]
[ROW][C]32[/C][C]3.19[/C][C]3.19228587962963[/C][C]3.20333333333333[/C][C]-0.011047453703704[/C][C]-0.00228587962962967[/C][/ROW]
[ROW][C]33[/C][C]3.21[/C][C]3.19061921296296[/C][C]3.19791666666667[/C][C]-0.00729745370370365[/C][C]0.0193807870370368[/C][/ROW]
[ROW][C]34[/C][C]3.21[/C][C]3.17450810185185[/C][C]3.18958333333333[/C][C]-0.0150752314814814[/C][C]0.0354918981481478[/C][/ROW]
[ROW][C]35[/C][C]3.19[/C][C]3.1620775462963[/C][C]3.18166666666667[/C][C]-0.0195891203703703[/C][C]0.0279224537037037[/C][/ROW]
[ROW][C]36[/C][C]3.18[/C][C]3.1570775462963[/C][C]3.17458333333333[/C][C]-0.0175057870370369[/C][C]0.0229224537037038[/C][/ROW]
[ROW][C]37[/C][C]3.16[/C][C]3.15673032407407[/C][C]3.16708333333333[/C][C]-0.0103530092592592[/C][C]0.00326967592592586[/C][/ROW]
[ROW][C]38[/C][C]3.15[/C][C]3.17388310185185[/C][C]3.16041666666667[/C][C]0.0134664351851852[/C][C]-0.0238831018518515[/C][/ROW]
[ROW][C]39[/C][C]3.15[/C][C]3.1777025462963[/C][C]3.15375[/C][C]0.0239525462962964[/C][C]-0.0277025462962963[/C][/ROW]
[ROW][C]40[/C][C]3.14[/C][C]3.16638310185185[/C][C]3.14666666666667[/C][C]0.0197164351851854[/C][C]-0.0263831018518519[/C][/ROW]
[ROW][C]41[/C][C]3.14[/C][C]3.1602025462963[/C][C]3.14125[/C][C]0.0189525462962962[/C][C]-0.0202025462962965[/C][/ROW]
[ROW][C]42[/C][C]3.12[/C][C]3.14221643518519[/C][C]3.1375[/C][C]0.00471643518518519[/C][C]-0.0222164351851855[/C][/ROW]
[ROW][C]43[/C][C]3.12[/C][C]3.13589699074074[/C][C]3.13583333333333[/C][C]6.36574074070593e-05[/C][C]-0.0158969907407407[/C][/ROW]
[ROW][C]44[/C][C]3.12[/C][C]3.1264525462963[/C][C]3.1375[/C][C]-0.011047453703704[/C][C]-0.0064525462962961[/C][/ROW]
[ROW][C]45[/C][C]3.12[/C][C]3.13311921296296[/C][C]3.14041666666667[/C][C]-0.00729745370370365[/C][C]-0.0131192129629625[/C][/ROW]
[ROW][C]46[/C][C]3.13[/C][C]3.12825810185185[/C][C]3.14333333333333[/C][C]-0.0150752314814814[/C][C]0.00174189814814874[/C][/ROW]
[ROW][C]47[/C][C]3.14[/C][C]3.12749421296296[/C][C]3.14708333333333[/C][C]-0.0195891203703703[/C][C]0.0125057870370378[/C][/ROW]
[ROW][C]48[/C][C]3.14[/C][C]3.13416087962963[/C][C]3.15166666666667[/C][C]-0.0175057870370369[/C][C]0.00583912037037093[/C][/ROW]
[ROW][C]49[/C][C]3.16[/C][C]3.14589699074074[/C][C]3.15625[/C][C]-0.0103530092592592[/C][C]0.0141030092592596[/C][/ROW]
[ROW][C]50[/C][C]3.19[/C][C]3.17388310185185[/C][C]3.16041666666667[/C][C]0.0134664351851852[/C][C]0.0161168981481485[/C][/ROW]
[ROW][C]51[/C][C]3.18[/C][C]3.18811921296296[/C][C]3.16416666666667[/C][C]0.0239525462962964[/C][C]-0.00811921296296214[/C][/ROW]
[ROW][C]52[/C][C]3.18[/C][C]3.18638310185185[/C][C]3.16666666666667[/C][C]0.0197164351851854[/C][C]-0.00638310185185142[/C][/ROW]
[ROW][C]53[/C][C]3.19[/C][C]3.1864525462963[/C][C]3.1675[/C][C]0.0189525462962962[/C][C]0.00354745370370413[/C][/ROW]
[ROW][C]54[/C][C]3.18[/C][C]3.17263310185185[/C][C]3.16791666666667[/C][C]0.00471643518518519[/C][C]0.0073668981481485[/C][/ROW]
[ROW][C]55[/C][C]3.17[/C][C]3.16798032407407[/C][C]3.16791666666667[/C][C]6.36574074070593e-05[/C][C]0.00201967592592611[/C][/ROW]
[ROW][C]56[/C][C]3.17[/C][C]3.1552025462963[/C][C]3.16625[/C][C]-0.011047453703704[/C][C]0.0147974537037037[/C][/ROW]
[ROW][C]57[/C][C]3.16[/C][C]3.1577025462963[/C][C]3.165[/C][C]-0.00729745370370365[/C][C]0.00229745370370438[/C][/ROW]
[ROW][C]58[/C][C]3.15[/C][C]3.14992476851852[/C][C]3.165[/C][C]-0.0150752314814814[/C][C]7.52314814818078e-05[/C][/ROW]
[ROW][C]59[/C][C]3.14[/C][C]3.14541087962963[/C][C]3.165[/C][C]-0.0195891203703703[/C][C]-0.00541087962962949[/C][/ROW]
[ROW][C]60[/C][C]3.15[/C][C]3.14749421296296[/C][C]3.165[/C][C]-0.0175057870370369[/C][C]0.00250578703703708[/C][/ROW]
[ROW][C]61[/C][C]3.15[/C][C]3.15548032407407[/C][C]3.16583333333333[/C][C]-0.0103530092592592[/C][C]-0.00548032407407417[/C][/ROW]
[ROW][C]62[/C][C]3.16[/C][C]3.18138310185185[/C][C]3.16791666666667[/C][C]0.0134664351851852[/C][C]-0.0213831018518515[/C][/ROW]
[ROW][C]63[/C][C]3.18[/C][C]3.19478587962963[/C][C]3.17083333333333[/C][C]0.0239525462962964[/C][C]-0.0147858796296299[/C][/ROW]
[ROW][C]64[/C][C]3.18[/C][C]3.19346643518519[/C][C]3.17375[/C][C]0.0197164351851854[/C][C]-0.0134664351851859[/C][/ROW]
[ROW][C]65[/C][C]3.19[/C][C]3.1964525462963[/C][C]3.1775[/C][C]0.0189525462962962[/C][C]-0.00645254629629655[/C][/ROW]
[ROW][C]66[/C][C]3.18[/C][C]3.18721643518519[/C][C]3.1825[/C][C]0.00471643518518519[/C][C]-0.00721643518518533[/C][/ROW]
[ROW][C]67[/C][C]3.19[/C][C]3.18881365740741[/C][C]3.18875[/C][C]6.36574074070593e-05[/C][C]0.00118634259259265[/C][/ROW]
[ROW][C]68[/C][C]3.2[/C][C]3.18686921296296[/C][C]3.19791666666667[/C][C]-0.011047453703704[/C][C]0.0131307870370372[/C][/ROW]
[ROW][C]69[/C][C]3.2[/C][C]3.2002025462963[/C][C]3.2075[/C][C]-0.00729745370370365[/C][C]-0.000202546296295569[/C][/ROW]
[ROW][C]70[/C][C]3.18[/C][C]3.20034143518518[/C][C]3.21541666666667[/C][C]-0.0150752314814814[/C][C]-0.0203414351851845[/C][/ROW]
[ROW][C]71[/C][C]3.2[/C][C]3.20374421296296[/C][C]3.22333333333333[/C][C]-0.0195891203703703[/C][C]-0.00374421296296257[/C][/ROW]
[ROW][C]72[/C][C]3.21[/C][C]3.21374421296296[/C][C]3.23125[/C][C]-0.0175057870370369[/C][C]-0.00374421296296301[/C][/ROW]
[ROW][C]73[/C][C]3.24[/C][C]3.22798032407407[/C][C]3.23833333333333[/C][C]-0.0103530092592592[/C][C]0.0120196759259263[/C][/ROW]
[ROW][C]74[/C][C]3.29[/C][C]3.25721643518518[/C][C]3.24375[/C][C]0.0134664351851852[/C][C]0.0327835648148151[/C][/ROW]
[ROW][C]75[/C][C]3.28[/C][C]3.27186921296296[/C][C]3.24791666666667[/C][C]0.0239525462962964[/C][C]0.00813078703703729[/C][/ROW]
[ROW][C]76[/C][C]3.27[/C][C]3.27179976851852[/C][C]3.25208333333333[/C][C]0.0197164351851854[/C][C]-0.00179976851851826[/C][/ROW]
[ROW][C]77[/C][C]3.29[/C][C]3.27436921296296[/C][C]3.25541666666667[/C][C]0.0189525462962962[/C][C]0.0156307870370371[/C][/ROW]
[ROW][C]78[/C][C]3.27[/C][C]3.26304976851852[/C][C]3.25833333333333[/C][C]0.00471643518518519[/C][C]0.00695023148148177[/C][/ROW]
[ROW][C]79[/C][C]3.27[/C][C]NA[/C][C]NA[/C][C]6.36574074070593e-05[/C][C]NA[/C][/ROW]
[ROW][C]80[/C][C]3.25[/C][C]NA[/C][C]NA[/C][C]-0.011047453703704[/C][C]NA[/C][/ROW]
[ROW][C]81[/C][C]3.25[/C][C]NA[/C][C]NA[/C][C]-0.00729745370370365[/C][C]NA[/C][/ROW]
[ROW][C]82[/C][C]3.23[/C][C]NA[/C][C]NA[/C][C]-0.0150752314814814[/C][C]NA[/C][/ROW]
[ROW][C]83[/C][C]3.23[/C][C]NA[/C][C]NA[/C][C]-0.0195891203703703[/C][C]NA[/C][/ROW]
[ROW][C]84[/C][C]3.25[/C][C]NA[/C][C]NA[/C][C]-0.0175057870370369[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191631&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191631&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	3.06	NA	NA	-0.0103530092592592	NA
2	3.07	NA	NA	0.0134664351851852	NA
3	3.08	NA	NA	0.0239525462962964	NA
4	3.07	NA	NA	0.0197164351851854	NA
5	3.08	NA	NA	0.0189525462962962	NA
6	3.06	NA	NA	0.00471643518518519	NA
7	3.07	3.06298032407407	3.06291666666667	6.36574074070593e-05	0.00701967592592601
8	3.04	3.05228587962963	3.06333333333333	-0.011047453703704	-0.0122858796296295
9	3.05	3.05686921296296	3.06416666666667	-0.00729745370370365	-0.00686921296296283
10	3.06	3.05117476851852	3.06625	-0.0150752314814814	0.00882523148148184
11	3.05	3.04874421296296	3.06833333333333	-0.0195891203703703	0.00125578703703733
12	3.06	3.0533275462963	3.07083333333333	-0.0175057870370369	0.00667245370370395
13	3.07	3.06298032407407	3.07333333333333	-0.0103530092592592	0.00701967592592601
14	3.07	3.08929976851852	3.07583333333333	0.0134664351851852	-0.0192997685185179
15	3.1	3.10353587962963	3.07958333333333	0.0239525462962964	-0.00353587962962854
16	3.1	3.10221643518519	3.0825	0.0197164351851854	-0.002216435185185
17	3.1	3.10353587962963	3.08458333333333	0.0189525462962962	-0.00353587962962942
18	3.1	3.09179976851852	3.08708333333333	0.00471643518518519	0.00820023148148152
19	3.09	3.09006365740741	3.09	6.36574074070593e-05	-6.36574074071028e-05
20	3.08	3.08561921296296	3.09666666666667	-0.011047453703704	-0.00561921296296264
21	3.1	3.1002025462963	3.1075	-0.00729745370370365	-0.000202546296296013
22	3.08	3.10450810185185	3.11958333333333	-0.0150752314814814	-0.0245081018518518
23	3.08	3.11124421296296	3.13083333333333	-0.0195891203703703	-0.0312442129629629
24	3.09	3.12291087962963	3.14041666666667	-0.0175057870370369	-0.0329108796296302
25	3.11	3.13964699074074	3.15	-0.0103530092592592	-0.0296469907407415
26	3.19	3.17304976851852	3.15958333333333	0.0134664351851852	0.0169502314814816
27	3.24	3.1927025462963	3.16875	0.0239525462962964	0.0472974537037039
28	3.25	3.19846643518519	3.17875	0.0197164351851854	0.051533564814815
29	3.22	3.2077025462963	3.18875	0.0189525462962962	0.0122974537037042
30	3.21	3.20179976851852	3.19708333333333	0.00471643518518519	0.00820023148148108
31	3.21	3.20298032407407	3.20291666666667	6.36574074070593e-05	0.00701967592592601
32	3.19	3.19228587962963	3.20333333333333	-0.011047453703704	-0.00228587962962967
33	3.21	3.19061921296296	3.19791666666667	-0.00729745370370365	0.0193807870370368
34	3.21	3.17450810185185	3.18958333333333	-0.0150752314814814	0.0354918981481478
35	3.19	3.1620775462963	3.18166666666667	-0.0195891203703703	0.0279224537037037
36	3.18	3.1570775462963	3.17458333333333	-0.0175057870370369	0.0229224537037038
37	3.16	3.15673032407407	3.16708333333333	-0.0103530092592592	0.00326967592592586
38	3.15	3.17388310185185	3.16041666666667	0.0134664351851852	-0.0238831018518515
39	3.15	3.1777025462963	3.15375	0.0239525462962964	-0.0277025462962963
40	3.14	3.16638310185185	3.14666666666667	0.0197164351851854	-0.0263831018518519
41	3.14	3.1602025462963	3.14125	0.0189525462962962	-0.0202025462962965
42	3.12	3.14221643518519	3.1375	0.00471643518518519	-0.0222164351851855
43	3.12	3.13589699074074	3.13583333333333	6.36574074070593e-05	-0.0158969907407407
44	3.12	3.1264525462963	3.1375	-0.011047453703704	-0.0064525462962961
45	3.12	3.13311921296296	3.14041666666667	-0.00729745370370365	-0.0131192129629625
46	3.13	3.12825810185185	3.14333333333333	-0.0150752314814814	0.00174189814814874
47	3.14	3.12749421296296	3.14708333333333	-0.0195891203703703	0.0125057870370378
48	3.14	3.13416087962963	3.15166666666667	-0.0175057870370369	0.00583912037037093
49	3.16	3.14589699074074	3.15625	-0.0103530092592592	0.0141030092592596
50	3.19	3.17388310185185	3.16041666666667	0.0134664351851852	0.0161168981481485
51	3.18	3.18811921296296	3.16416666666667	0.0239525462962964	-0.00811921296296214
52	3.18	3.18638310185185	3.16666666666667	0.0197164351851854	-0.00638310185185142
53	3.19	3.1864525462963	3.1675	0.0189525462962962	0.00354745370370413
54	3.18	3.17263310185185	3.16791666666667	0.00471643518518519	0.0073668981481485
55	3.17	3.16798032407407	3.16791666666667	6.36574074070593e-05	0.00201967592592611
56	3.17	3.1552025462963	3.16625	-0.011047453703704	0.0147974537037037
57	3.16	3.1577025462963	3.165	-0.00729745370370365	0.00229745370370438
58	3.15	3.14992476851852	3.165	-0.0150752314814814	7.52314814818078e-05
59	3.14	3.14541087962963	3.165	-0.0195891203703703	-0.00541087962962949
60	3.15	3.14749421296296	3.165	-0.0175057870370369	0.00250578703703708
61	3.15	3.15548032407407	3.16583333333333	-0.0103530092592592	-0.00548032407407417
62	3.16	3.18138310185185	3.16791666666667	0.0134664351851852	-0.0213831018518515
63	3.18	3.19478587962963	3.17083333333333	0.0239525462962964	-0.0147858796296299
64	3.18	3.19346643518519	3.17375	0.0197164351851854	-0.0134664351851859
65	3.19	3.1964525462963	3.1775	0.0189525462962962	-0.00645254629629655
66	3.18	3.18721643518519	3.1825	0.00471643518518519	-0.00721643518518533
67	3.19	3.18881365740741	3.18875	6.36574074070593e-05	0.00118634259259265
68	3.2	3.18686921296296	3.19791666666667	-0.011047453703704	0.0131307870370372
69	3.2	3.2002025462963	3.2075	-0.00729745370370365	-0.000202546296295569
70	3.18	3.20034143518518	3.21541666666667	-0.0150752314814814	-0.0203414351851845
71	3.2	3.20374421296296	3.22333333333333	-0.0195891203703703	-0.00374421296296257
72	3.21	3.21374421296296	3.23125	-0.0175057870370369	-0.00374421296296301
73	3.24	3.22798032407407	3.23833333333333	-0.0103530092592592	0.0120196759259263
74	3.29	3.25721643518518	3.24375	0.0134664351851852	0.0327835648148151
75	3.28	3.27186921296296	3.24791666666667	0.0239525462962964	0.00813078703703729
76	3.27	3.27179976851852	3.25208333333333	0.0197164351851854	-0.00179976851851826
77	3.29	3.27436921296296	3.25541666666667	0.0189525462962962	0.0156307870370371
78	3.27	3.26304976851852	3.25833333333333	0.00471643518518519	0.00695023148148177
79	3.27	NA	NA	6.36574074070593e-05	NA
80	3.25	NA	NA	-0.011047453703704	NA
81	3.25	NA	NA	-0.00729745370370365	NA
82	3.23	NA	NA	-0.0150752314814814	NA
83	3.23	NA	NA	-0.0195891203703703	NA
84	3.25	NA	NA	-0.0175057870370369	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