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Author's title

Author

*Unverified author*

R Software Module

rwasp_exponentialsmoothing.wasp

Title produced by software

Exponential Smoothing

Date of computation

Sun, 06 Jun 2010 20:20:36 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Jun/06/t1275855682rt08dzo768rka1j.htm/, Retrieved Sat, 27 Apr 2024 19:00:43 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=77795, Retrieved Sat, 27 Apr 2024 19:00:43 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

KDGP2W62

Estimated Impact

116

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

-       [Exponential Smoothing] [Opgave 10 Oefening 2] [2010-06-06 20:20:36] [5a7cbdb73d36823522b207a888c6ba9b] [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	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77795&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77795&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77795&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	2 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Estimated Parameters of Exponential Smoothing
Parameter	Value
alpha	0.9999383030001
beta	FALSE
gamma	FALSE

\begin{tabular}{lllllllll}
\hline
Estimated Parameters of Exponential Smoothing \tabularnewline
Parameter & Value \tabularnewline
alpha & 0.9999383030001 \tabularnewline
beta & FALSE \tabularnewline
gamma & FALSE \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77795&T=1

[TABLE]
[ROW][C]Estimated Parameters of Exponential Smoothing[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]alpha[/C][C]0.9999383030001[/C][/ROW]
[ROW][C]beta[/C][C]FALSE[/C][/ROW]
[ROW][C]gamma[/C][C]FALSE[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77795&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77795&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Estimated Parameters of Exponential Smoothing
Parameter	Value
alpha	0.9999383030001
beta	FALSE
gamma	FALSE

Interpolation Forecasts of Exponential Smoothing
t	Observed	Fitted	Residuals
2	0.9217	0.9383	-0.0166000000000001
3	0.9095	0.921701024170198	-0.0122010241701983
4	0.892	0.909500752766587	-0.0175007527665869
5	0.8742	0.892001079743942	-0.0178010797439417
6	0.8607	0.874201098273215	-0.0135010982732151
7	0.8607	0.860700832977259	-8.32977258835577e-07
8	0.9005	0.860700000051392	0.0397999999486077
9	0.9111	0.900497544459407	0.0106024555405929
10	0.9059	0.911099345860302	-0.00519934586030157
11	0.8883	0.905900320784041	-0.0176003207840411
12	0.8924	0.88830108588699	0.00409891411301033
13	0.8833	0.892399747109296	-0.0090997471092964
14	0.87	0.883300561427096	-0.0133005614270965
15	0.8758	0.870000820604737	0.00579917939526298
16	0.8858	0.87579964220803	0.0100003577919706
17	0.917	0.885799383007926	0.0312006169920737
18	0.9554	0.916998075015537	0.0384019249844634
19	0.9922	0.955397630716438	0.0368023692835618
20	0.9778	0.992197729404226	-0.014397729404226
21	0.9808	0.97780088829671	0.00299911170329037
22	0.9811	0.980799814963806	0.000300185036194445
23	1.0014	0.981099981479484	0.0203000185205162
24	1.0183	1.00139874754976	0.0169012524502405
25	1.0622	1.01829895724343	0.0439010427565707
26	1.0773	1.06219729143737	0.0151027085626305
27	1.0807	1.07729906820819	0.00340093179180867
28	1.0848	1.08069979017271	0.00410020982728843
29	1.1582	1.08479974702935	0.0734002529706452
30	1.1663	1.1581954714246	0.00810452857540023
31	1.1372	1.16629949997490	-0.0290994999749012
32	1.1139	1.13720179535185	-0.0233017953518471
33	1.1222	1.11390143765087	0.00829856234913473
34	1.1692	1.1221994880036	0.0470005119964003
35	1.1702	1.16919710020942	0.00100289979058377
36	1.2286	1.17019993812409	0.0584000618759082
37	1.2613	1.22859639689139	0.0327036031086119
38	1.2646	1.26129798228580	0.00330201771419758
39	1.2262	1.26459979627541	-0.0383997962754135
40	1.1985	1.22620236915223	-0.0277023691522269
41	1.2007	1.19850170915307	0.00219829084693335
42	1.2138	1.20069986437205	0.0131001356279501
43	1.2266	1.21379919176093	0.0128008082390665
44	1.2176	1.22659921022854	-0.00899921022853523
45	1.2218	1.21760055522427	0.00419944477572742
46	1.249	1.22179974090686	0.0272002590931439
47	1.2991	1.24899832182562	0.0501016781743824
48	1.3408	1.29909690887677	0.0417030911232334
49	1.3119	1.34079742704439	-0.0288974270443911
50	1.3014	1.31190178288455	-0.0105017828845537
51	1.3201	1.30140064792850	0.0186993520715026
52	1.2938	1.32009884630608	-0.0262988463060772
53	1.2694	1.29380162255992	-0.0244016225599180
54	1.2165	1.26940150550690	-0.0529015055069049
55	1.2037	1.21650326386418	-0.0128032638641800
56	1.2292	1.20370078992297	0.0254992100770308
57	1.2256	1.22919842677524	-0.00359842677523847
58	1.2015	1.22560022201214	-0.0241002220121365
59	1.1786	1.20150148691140	-0.0229014869113950
60	1.1856	1.17860141295304	0.00699858704696421
61	1.2103	1.18559956820818	0.0247004317918242
62	1.1938	1.21029847605746	-0.0164984760574622
63	1.202	1.19380101790648	0.00819898209352443
64	1.2271	1.20199949414740	0.0251005058525975
65	1.277	1.22709845137409	0.0499015486259069
66	1.265	1.27699692122416	-0.0119969212241595
67	1.2684	1.26500074017405	0.00339925982595246
68	1.2811	1.26839979027587	0.0127002097241331
69	1.2727	1.28109921643516	-0.00839921643516184
70	1.2611	1.27270051820646	-0.0116005182064554
71	1.2881	1.26110071571717	0.0269992842828293
72	1.3213	1.28809833422516	0.0332016657748395
73	1.2999	1.32129795155683	-0.0213979515568299
74	1.3074	1.29990132018942	0.00749867981058472
75	1.3242	1.30739953735395	0.0168004626460476
76	1.3516	1.32419896346186	0.0274010365381421
77	1.3511	1.35159830943825	-0.000498309438251354
78	1.3419	1.35110003074420	-0.00920003074419729
79	1.3716	1.34190056761430	0.0296994323857038
80	1.3622	1.37159816763412	-0.00939816763412304
81	1.3896	1.36220057983875	0.0273994201612522
82	1.4227	1.38959830953798	0.0331016904620232
83	1.4684	1.42269795772501	0.045702042274993
84	1.457	1.46839718032110	-0.0113971803211022
85	1.4718	1.45700070317183	0.0147992968281667
86	1.4748	1.47179908692779	0.00300091307221506
87	1.5527	1.47479981485267	0.0779001851473333
88	1.5751	1.55269519379228	0.0224048062077151
89	1.5557	1.57509861769067	-0.0193986176906735
90	1.5553	1.55570119683651	-0.000401196836513851
91	1.577	1.55530002475264	0.0216999752473588
92	1.4975	1.57699866117663	-0.0794986611766293
93	1.437	1.49750490482889	-0.0605049048288906
94	1.3322	1.43700373297111	-0.104803732971107
95	1.2732	1.33220646607590	-0.0590064660759024
96	1.3449	1.27320364052193	0.0716963594780684
97	1.3239	1.34489557654972	-0.0209955765497163
98	1.2785	1.32390129536408	-0.0454012953640843
99	1.305	1.27850280112372	0.0264971988762845
100	1.319	1.30499836520232	0.0140016347976764
101	1.365	1.31899913614114	0.0460008638588607
102	1.4016	1.36499716188471	0.0366028381152927
103	1.4088	1.4015977417147	0.00720225828529952
104	1.4268	1.40879955564227	0.0180004443577286
105	1.4562	1.42679888942659	0.0294011105734135
106	1.4816	1.45619818603968	0.0254018139603163
107	1.4914	1.48159843278429	0.00980156721571346
108	1.4614	1.49139939527271	-0.0299993952727085

\begin{tabular}{lllllllll}
\hline
Interpolation Forecasts of Exponential Smoothing \tabularnewline
t & Observed & Fitted & Residuals \tabularnewline
2 & 0.9217 & 0.9383 & -0.0166000000000001 \tabularnewline
3 & 0.9095 & 0.921701024170198 & -0.0122010241701983 \tabularnewline
4 & 0.892 & 0.909500752766587 & -0.0175007527665869 \tabularnewline
5 & 0.8742 & 0.892001079743942 & -0.0178010797439417 \tabularnewline
6 & 0.8607 & 0.874201098273215 & -0.0135010982732151 \tabularnewline
7 & 0.8607 & 0.860700832977259 & -8.32977258835577e-07 \tabularnewline
8 & 0.9005 & 0.860700000051392 & 0.0397999999486077 \tabularnewline
9 & 0.9111 & 0.900497544459407 & 0.0106024555405929 \tabularnewline
10 & 0.9059 & 0.911099345860302 & -0.00519934586030157 \tabularnewline
11 & 0.8883 & 0.905900320784041 & -0.0176003207840411 \tabularnewline
12 & 0.8924 & 0.88830108588699 & 0.00409891411301033 \tabularnewline
13 & 0.8833 & 0.892399747109296 & -0.0090997471092964 \tabularnewline
14 & 0.87 & 0.883300561427096 & -0.0133005614270965 \tabularnewline
15 & 0.8758 & 0.870000820604737 & 0.00579917939526298 \tabularnewline
16 & 0.8858 & 0.87579964220803 & 0.0100003577919706 \tabularnewline
17 & 0.917 & 0.885799383007926 & 0.0312006169920737 \tabularnewline
18 & 0.9554 & 0.916998075015537 & 0.0384019249844634 \tabularnewline
19 & 0.9922 & 0.955397630716438 & 0.0368023692835618 \tabularnewline
20 & 0.9778 & 0.992197729404226 & -0.014397729404226 \tabularnewline
21 & 0.9808 & 0.97780088829671 & 0.00299911170329037 \tabularnewline
22 & 0.9811 & 0.980799814963806 & 0.000300185036194445 \tabularnewline
23 & 1.0014 & 0.981099981479484 & 0.0203000185205162 \tabularnewline
24 & 1.0183 & 1.00139874754976 & 0.0169012524502405 \tabularnewline
25 & 1.0622 & 1.01829895724343 & 0.0439010427565707 \tabularnewline
26 & 1.0773 & 1.06219729143737 & 0.0151027085626305 \tabularnewline
27 & 1.0807 & 1.07729906820819 & 0.00340093179180867 \tabularnewline
28 & 1.0848 & 1.08069979017271 & 0.00410020982728843 \tabularnewline
29 & 1.1582 & 1.08479974702935 & 0.0734002529706452 \tabularnewline
30 & 1.1663 & 1.1581954714246 & 0.00810452857540023 \tabularnewline
31 & 1.1372 & 1.16629949997490 & -0.0290994999749012 \tabularnewline
32 & 1.1139 & 1.13720179535185 & -0.0233017953518471 \tabularnewline
33 & 1.1222 & 1.11390143765087 & 0.00829856234913473 \tabularnewline
34 & 1.1692 & 1.1221994880036 & 0.0470005119964003 \tabularnewline
35 & 1.1702 & 1.16919710020942 & 0.00100289979058377 \tabularnewline
36 & 1.2286 & 1.17019993812409 & 0.0584000618759082 \tabularnewline
37 & 1.2613 & 1.22859639689139 & 0.0327036031086119 \tabularnewline
38 & 1.2646 & 1.26129798228580 & 0.00330201771419758 \tabularnewline
39 & 1.2262 & 1.26459979627541 & -0.0383997962754135 \tabularnewline
40 & 1.1985 & 1.22620236915223 & -0.0277023691522269 \tabularnewline
41 & 1.2007 & 1.19850170915307 & 0.00219829084693335 \tabularnewline
42 & 1.2138 & 1.20069986437205 & 0.0131001356279501 \tabularnewline
43 & 1.2266 & 1.21379919176093 & 0.0128008082390665 \tabularnewline
44 & 1.2176 & 1.22659921022854 & -0.00899921022853523 \tabularnewline
45 & 1.2218 & 1.21760055522427 & 0.00419944477572742 \tabularnewline
46 & 1.249 & 1.22179974090686 & 0.0272002590931439 \tabularnewline
47 & 1.2991 & 1.24899832182562 & 0.0501016781743824 \tabularnewline
48 & 1.3408 & 1.29909690887677 & 0.0417030911232334 \tabularnewline
49 & 1.3119 & 1.34079742704439 & -0.0288974270443911 \tabularnewline
50 & 1.3014 & 1.31190178288455 & -0.0105017828845537 \tabularnewline
51 & 1.3201 & 1.30140064792850 & 0.0186993520715026 \tabularnewline
52 & 1.2938 & 1.32009884630608 & -0.0262988463060772 \tabularnewline
53 & 1.2694 & 1.29380162255992 & -0.0244016225599180 \tabularnewline
54 & 1.2165 & 1.26940150550690 & -0.0529015055069049 \tabularnewline
55 & 1.2037 & 1.21650326386418 & -0.0128032638641800 \tabularnewline
56 & 1.2292 & 1.20370078992297 & 0.0254992100770308 \tabularnewline
57 & 1.2256 & 1.22919842677524 & -0.00359842677523847 \tabularnewline
58 & 1.2015 & 1.22560022201214 & -0.0241002220121365 \tabularnewline
59 & 1.1786 & 1.20150148691140 & -0.0229014869113950 \tabularnewline
60 & 1.1856 & 1.17860141295304 & 0.00699858704696421 \tabularnewline
61 & 1.2103 & 1.18559956820818 & 0.0247004317918242 \tabularnewline
62 & 1.1938 & 1.21029847605746 & -0.0164984760574622 \tabularnewline
63 & 1.202 & 1.19380101790648 & 0.00819898209352443 \tabularnewline
64 & 1.2271 & 1.20199949414740 & 0.0251005058525975 \tabularnewline
65 & 1.277 & 1.22709845137409 & 0.0499015486259069 \tabularnewline
66 & 1.265 & 1.27699692122416 & -0.0119969212241595 \tabularnewline
67 & 1.2684 & 1.26500074017405 & 0.00339925982595246 \tabularnewline
68 & 1.2811 & 1.26839979027587 & 0.0127002097241331 \tabularnewline
69 & 1.2727 & 1.28109921643516 & -0.00839921643516184 \tabularnewline
70 & 1.2611 & 1.27270051820646 & -0.0116005182064554 \tabularnewline
71 & 1.2881 & 1.26110071571717 & 0.0269992842828293 \tabularnewline
72 & 1.3213 & 1.28809833422516 & 0.0332016657748395 \tabularnewline
73 & 1.2999 & 1.32129795155683 & -0.0213979515568299 \tabularnewline
74 & 1.3074 & 1.29990132018942 & 0.00749867981058472 \tabularnewline
75 & 1.3242 & 1.30739953735395 & 0.0168004626460476 \tabularnewline
76 & 1.3516 & 1.32419896346186 & 0.0274010365381421 \tabularnewline
77 & 1.3511 & 1.35159830943825 & -0.000498309438251354 \tabularnewline
78 & 1.3419 & 1.35110003074420 & -0.00920003074419729 \tabularnewline
79 & 1.3716 & 1.34190056761430 & 0.0296994323857038 \tabularnewline
80 & 1.3622 & 1.37159816763412 & -0.00939816763412304 \tabularnewline
81 & 1.3896 & 1.36220057983875 & 0.0273994201612522 \tabularnewline
82 & 1.4227 & 1.38959830953798 & 0.0331016904620232 \tabularnewline
83 & 1.4684 & 1.42269795772501 & 0.045702042274993 \tabularnewline
84 & 1.457 & 1.46839718032110 & -0.0113971803211022 \tabularnewline
85 & 1.4718 & 1.45700070317183 & 0.0147992968281667 \tabularnewline
86 & 1.4748 & 1.47179908692779 & 0.00300091307221506 \tabularnewline
87 & 1.5527 & 1.47479981485267 & 0.0779001851473333 \tabularnewline
88 & 1.5751 & 1.55269519379228 & 0.0224048062077151 \tabularnewline
89 & 1.5557 & 1.57509861769067 & -0.0193986176906735 \tabularnewline
90 & 1.5553 & 1.55570119683651 & -0.000401196836513851 \tabularnewline
91 & 1.577 & 1.55530002475264 & 0.0216999752473588 \tabularnewline
92 & 1.4975 & 1.57699866117663 & -0.0794986611766293 \tabularnewline
93 & 1.437 & 1.49750490482889 & -0.0605049048288906 \tabularnewline
94 & 1.3322 & 1.43700373297111 & -0.104803732971107 \tabularnewline
95 & 1.2732 & 1.33220646607590 & -0.0590064660759024 \tabularnewline
96 & 1.3449 & 1.27320364052193 & 0.0716963594780684 \tabularnewline
97 & 1.3239 & 1.34489557654972 & -0.0209955765497163 \tabularnewline
98 & 1.2785 & 1.32390129536408 & -0.0454012953640843 \tabularnewline
99 & 1.305 & 1.27850280112372 & 0.0264971988762845 \tabularnewline
100 & 1.319 & 1.30499836520232 & 0.0140016347976764 \tabularnewline
101 & 1.365 & 1.31899913614114 & 0.0460008638588607 \tabularnewline
102 & 1.4016 & 1.36499716188471 & 0.0366028381152927 \tabularnewline
103 & 1.4088 & 1.4015977417147 & 0.00720225828529952 \tabularnewline
104 & 1.4268 & 1.40879955564227 & 0.0180004443577286 \tabularnewline
105 & 1.4562 & 1.42679888942659 & 0.0294011105734135 \tabularnewline
106 & 1.4816 & 1.45619818603968 & 0.0254018139603163 \tabularnewline
107 & 1.4914 & 1.48159843278429 & 0.00980156721571346 \tabularnewline
108 & 1.4614 & 1.49139939527271 & -0.0299993952727085 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77795&T=2

[TABLE]
[ROW][C]Interpolation Forecasts of Exponential Smoothing[/C][/ROW]
[ROW][C]t[/C][C]Observed[/C][C]Fitted[/C][C]Residuals[/C][/ROW]
[ROW][C]2[/C][C]0.9217[/C][C]0.9383[/C][C]-0.0166000000000001[/C][/ROW]
[ROW][C]3[/C][C]0.9095[/C][C]0.921701024170198[/C][C]-0.0122010241701983[/C][/ROW]
[ROW][C]4[/C][C]0.892[/C][C]0.909500752766587[/C][C]-0.0175007527665869[/C][/ROW]
[ROW][C]5[/C][C]0.8742[/C][C]0.892001079743942[/C][C]-0.0178010797439417[/C][/ROW]
[ROW][C]6[/C][C]0.8607[/C][C]0.874201098273215[/C][C]-0.0135010982732151[/C][/ROW]
[ROW][C]7[/C][C]0.8607[/C][C]0.860700832977259[/C][C]-8.32977258835577e-07[/C][/ROW]
[ROW][C]8[/C][C]0.9005[/C][C]0.860700000051392[/C][C]0.0397999999486077[/C][/ROW]
[ROW][C]9[/C][C]0.9111[/C][C]0.900497544459407[/C][C]0.0106024555405929[/C][/ROW]
[ROW][C]10[/C][C]0.9059[/C][C]0.911099345860302[/C][C]-0.00519934586030157[/C][/ROW]
[ROW][C]11[/C][C]0.8883[/C][C]0.905900320784041[/C][C]-0.0176003207840411[/C][/ROW]
[ROW][C]12[/C][C]0.8924[/C][C]0.88830108588699[/C][C]0.00409891411301033[/C][/ROW]
[ROW][C]13[/C][C]0.8833[/C][C]0.892399747109296[/C][C]-0.0090997471092964[/C][/ROW]
[ROW][C]14[/C][C]0.87[/C][C]0.883300561427096[/C][C]-0.0133005614270965[/C][/ROW]
[ROW][C]15[/C][C]0.8758[/C][C]0.870000820604737[/C][C]0.00579917939526298[/C][/ROW]
[ROW][C]16[/C][C]0.8858[/C][C]0.87579964220803[/C][C]0.0100003577919706[/C][/ROW]
[ROW][C]17[/C][C]0.917[/C][C]0.885799383007926[/C][C]0.0312006169920737[/C][/ROW]
[ROW][C]18[/C][C]0.9554[/C][C]0.916998075015537[/C][C]0.0384019249844634[/C][/ROW]
[ROW][C]19[/C][C]0.9922[/C][C]0.955397630716438[/C][C]0.0368023692835618[/C][/ROW]
[ROW][C]20[/C][C]0.9778[/C][C]0.992197729404226[/C][C]-0.014397729404226[/C][/ROW]
[ROW][C]21[/C][C]0.9808[/C][C]0.97780088829671[/C][C]0.00299911170329037[/C][/ROW]
[ROW][C]22[/C][C]0.9811[/C][C]0.980799814963806[/C][C]0.000300185036194445[/C][/ROW]
[ROW][C]23[/C][C]1.0014[/C][C]0.981099981479484[/C][C]0.0203000185205162[/C][/ROW]
[ROW][C]24[/C][C]1.0183[/C][C]1.00139874754976[/C][C]0.0169012524502405[/C][/ROW]
[ROW][C]25[/C][C]1.0622[/C][C]1.01829895724343[/C][C]0.0439010427565707[/C][/ROW]
[ROW][C]26[/C][C]1.0773[/C][C]1.06219729143737[/C][C]0.0151027085626305[/C][/ROW]
[ROW][C]27[/C][C]1.0807[/C][C]1.07729906820819[/C][C]0.00340093179180867[/C][/ROW]
[ROW][C]28[/C][C]1.0848[/C][C]1.08069979017271[/C][C]0.00410020982728843[/C][/ROW]
[ROW][C]29[/C][C]1.1582[/C][C]1.08479974702935[/C][C]0.0734002529706452[/C][/ROW]
[ROW][C]30[/C][C]1.1663[/C][C]1.1581954714246[/C][C]0.00810452857540023[/C][/ROW]
[ROW][C]31[/C][C]1.1372[/C][C]1.16629949997490[/C][C]-0.0290994999749012[/C][/ROW]
[ROW][C]32[/C][C]1.1139[/C][C]1.13720179535185[/C][C]-0.0233017953518471[/C][/ROW]
[ROW][C]33[/C][C]1.1222[/C][C]1.11390143765087[/C][C]0.00829856234913473[/C][/ROW]
[ROW][C]34[/C][C]1.1692[/C][C]1.1221994880036[/C][C]0.0470005119964003[/C][/ROW]
[ROW][C]35[/C][C]1.1702[/C][C]1.16919710020942[/C][C]0.00100289979058377[/C][/ROW]
[ROW][C]36[/C][C]1.2286[/C][C]1.17019993812409[/C][C]0.0584000618759082[/C][/ROW]
[ROW][C]37[/C][C]1.2613[/C][C]1.22859639689139[/C][C]0.0327036031086119[/C][/ROW]
[ROW][C]38[/C][C]1.2646[/C][C]1.26129798228580[/C][C]0.00330201771419758[/C][/ROW]
[ROW][C]39[/C][C]1.2262[/C][C]1.26459979627541[/C][C]-0.0383997962754135[/C][/ROW]
[ROW][C]40[/C][C]1.1985[/C][C]1.22620236915223[/C][C]-0.0277023691522269[/C][/ROW]
[ROW][C]41[/C][C]1.2007[/C][C]1.19850170915307[/C][C]0.00219829084693335[/C][/ROW]
[ROW][C]42[/C][C]1.2138[/C][C]1.20069986437205[/C][C]0.0131001356279501[/C][/ROW]
[ROW][C]43[/C][C]1.2266[/C][C]1.21379919176093[/C][C]0.0128008082390665[/C][/ROW]
[ROW][C]44[/C][C]1.2176[/C][C]1.22659921022854[/C][C]-0.00899921022853523[/C][/ROW]
[ROW][C]45[/C][C]1.2218[/C][C]1.21760055522427[/C][C]0.00419944477572742[/C][/ROW]
[ROW][C]46[/C][C]1.249[/C][C]1.22179974090686[/C][C]0.0272002590931439[/C][/ROW]
[ROW][C]47[/C][C]1.2991[/C][C]1.24899832182562[/C][C]0.0501016781743824[/C][/ROW]
[ROW][C]48[/C][C]1.3408[/C][C]1.29909690887677[/C][C]0.0417030911232334[/C][/ROW]
[ROW][C]49[/C][C]1.3119[/C][C]1.34079742704439[/C][C]-0.0288974270443911[/C][/ROW]
[ROW][C]50[/C][C]1.3014[/C][C]1.31190178288455[/C][C]-0.0105017828845537[/C][/ROW]
[ROW][C]51[/C][C]1.3201[/C][C]1.30140064792850[/C][C]0.0186993520715026[/C][/ROW]
[ROW][C]52[/C][C]1.2938[/C][C]1.32009884630608[/C][C]-0.0262988463060772[/C][/ROW]
[ROW][C]53[/C][C]1.2694[/C][C]1.29380162255992[/C][C]-0.0244016225599180[/C][/ROW]
[ROW][C]54[/C][C]1.2165[/C][C]1.26940150550690[/C][C]-0.0529015055069049[/C][/ROW]
[ROW][C]55[/C][C]1.2037[/C][C]1.21650326386418[/C][C]-0.0128032638641800[/C][/ROW]
[ROW][C]56[/C][C]1.2292[/C][C]1.20370078992297[/C][C]0.0254992100770308[/C][/ROW]
[ROW][C]57[/C][C]1.2256[/C][C]1.22919842677524[/C][C]-0.00359842677523847[/C][/ROW]
[ROW][C]58[/C][C]1.2015[/C][C]1.22560022201214[/C][C]-0.0241002220121365[/C][/ROW]
[ROW][C]59[/C][C]1.1786[/C][C]1.20150148691140[/C][C]-0.0229014869113950[/C][/ROW]
[ROW][C]60[/C][C]1.1856[/C][C]1.17860141295304[/C][C]0.00699858704696421[/C][/ROW]
[ROW][C]61[/C][C]1.2103[/C][C]1.18559956820818[/C][C]0.0247004317918242[/C][/ROW]
[ROW][C]62[/C][C]1.1938[/C][C]1.21029847605746[/C][C]-0.0164984760574622[/C][/ROW]
[ROW][C]63[/C][C]1.202[/C][C]1.19380101790648[/C][C]0.00819898209352443[/C][/ROW]
[ROW][C]64[/C][C]1.2271[/C][C]1.20199949414740[/C][C]0.0251005058525975[/C][/ROW]
[ROW][C]65[/C][C]1.277[/C][C]1.22709845137409[/C][C]0.0499015486259069[/C][/ROW]
[ROW][C]66[/C][C]1.265[/C][C]1.27699692122416[/C][C]-0.0119969212241595[/C][/ROW]
[ROW][C]67[/C][C]1.2684[/C][C]1.26500074017405[/C][C]0.00339925982595246[/C][/ROW]
[ROW][C]68[/C][C]1.2811[/C][C]1.26839979027587[/C][C]0.0127002097241331[/C][/ROW]
[ROW][C]69[/C][C]1.2727[/C][C]1.28109921643516[/C][C]-0.00839921643516184[/C][/ROW]
[ROW][C]70[/C][C]1.2611[/C][C]1.27270051820646[/C][C]-0.0116005182064554[/C][/ROW]
[ROW][C]71[/C][C]1.2881[/C][C]1.26110071571717[/C][C]0.0269992842828293[/C][/ROW]
[ROW][C]72[/C][C]1.3213[/C][C]1.28809833422516[/C][C]0.0332016657748395[/C][/ROW]
[ROW][C]73[/C][C]1.2999[/C][C]1.32129795155683[/C][C]-0.0213979515568299[/C][/ROW]
[ROW][C]74[/C][C]1.3074[/C][C]1.29990132018942[/C][C]0.00749867981058472[/C][/ROW]
[ROW][C]75[/C][C]1.3242[/C][C]1.30739953735395[/C][C]0.0168004626460476[/C][/ROW]
[ROW][C]76[/C][C]1.3516[/C][C]1.32419896346186[/C][C]0.0274010365381421[/C][/ROW]
[ROW][C]77[/C][C]1.3511[/C][C]1.35159830943825[/C][C]-0.000498309438251354[/C][/ROW]
[ROW][C]78[/C][C]1.3419[/C][C]1.35110003074420[/C][C]-0.00920003074419729[/C][/ROW]
[ROW][C]79[/C][C]1.3716[/C][C]1.34190056761430[/C][C]0.0296994323857038[/C][/ROW]
[ROW][C]80[/C][C]1.3622[/C][C]1.37159816763412[/C][C]-0.00939816763412304[/C][/ROW]
[ROW][C]81[/C][C]1.3896[/C][C]1.36220057983875[/C][C]0.0273994201612522[/C][/ROW]
[ROW][C]82[/C][C]1.4227[/C][C]1.38959830953798[/C][C]0.0331016904620232[/C][/ROW]
[ROW][C]83[/C][C]1.4684[/C][C]1.42269795772501[/C][C]0.045702042274993[/C][/ROW]
[ROW][C]84[/C][C]1.457[/C][C]1.46839718032110[/C][C]-0.0113971803211022[/C][/ROW]
[ROW][C]85[/C][C]1.4718[/C][C]1.45700070317183[/C][C]0.0147992968281667[/C][/ROW]
[ROW][C]86[/C][C]1.4748[/C][C]1.47179908692779[/C][C]0.00300091307221506[/C][/ROW]
[ROW][C]87[/C][C]1.5527[/C][C]1.47479981485267[/C][C]0.0779001851473333[/C][/ROW]
[ROW][C]88[/C][C]1.5751[/C][C]1.55269519379228[/C][C]0.0224048062077151[/C][/ROW]
[ROW][C]89[/C][C]1.5557[/C][C]1.57509861769067[/C][C]-0.0193986176906735[/C][/ROW]
[ROW][C]90[/C][C]1.5553[/C][C]1.55570119683651[/C][C]-0.000401196836513851[/C][/ROW]
[ROW][C]91[/C][C]1.577[/C][C]1.55530002475264[/C][C]0.0216999752473588[/C][/ROW]
[ROW][C]92[/C][C]1.4975[/C][C]1.57699866117663[/C][C]-0.0794986611766293[/C][/ROW]
[ROW][C]93[/C][C]1.437[/C][C]1.49750490482889[/C][C]-0.0605049048288906[/C][/ROW]
[ROW][C]94[/C][C]1.3322[/C][C]1.43700373297111[/C][C]-0.104803732971107[/C][/ROW]
[ROW][C]95[/C][C]1.2732[/C][C]1.33220646607590[/C][C]-0.0590064660759024[/C][/ROW]
[ROW][C]96[/C][C]1.3449[/C][C]1.27320364052193[/C][C]0.0716963594780684[/C][/ROW]
[ROW][C]97[/C][C]1.3239[/C][C]1.34489557654972[/C][C]-0.0209955765497163[/C][/ROW]
[ROW][C]98[/C][C]1.2785[/C][C]1.32390129536408[/C][C]-0.0454012953640843[/C][/ROW]
[ROW][C]99[/C][C]1.305[/C][C]1.27850280112372[/C][C]0.0264971988762845[/C][/ROW]
[ROW][C]100[/C][C]1.319[/C][C]1.30499836520232[/C][C]0.0140016347976764[/C][/ROW]
[ROW][C]101[/C][C]1.365[/C][C]1.31899913614114[/C][C]0.0460008638588607[/C][/ROW]
[ROW][C]102[/C][C]1.4016[/C][C]1.36499716188471[/C][C]0.0366028381152927[/C][/ROW]
[ROW][C]103[/C][C]1.4088[/C][C]1.4015977417147[/C][C]0.00720225828529952[/C][/ROW]
[ROW][C]104[/C][C]1.4268[/C][C]1.40879955564227[/C][C]0.0180004443577286[/C][/ROW]
[ROW][C]105[/C][C]1.4562[/C][C]1.42679888942659[/C][C]0.0294011105734135[/C][/ROW]
[ROW][C]106[/C][C]1.4816[/C][C]1.45619818603968[/C][C]0.0254018139603163[/C][/ROW]
[ROW][C]107[/C][C]1.4914[/C][C]1.48159843278429[/C][C]0.00980156721571346[/C][/ROW]
[ROW][C]108[/C][C]1.4614[/C][C]1.49139939527271[/C][C]-0.0299993952727085[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77795&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77795&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Interpolation Forecasts of Exponential Smoothing
t	Observed	Fitted	Residuals
2	0.9217	0.9383	-0.0166000000000001
3	0.9095	0.921701024170198	-0.0122010241701983
4	0.892	0.909500752766587	-0.0175007527665869
5	0.8742	0.892001079743942	-0.0178010797439417
6	0.8607	0.874201098273215	-0.0135010982732151
7	0.8607	0.860700832977259	-8.32977258835577e-07
8	0.9005	0.860700000051392	0.0397999999486077
9	0.9111	0.900497544459407	0.0106024555405929
10	0.9059	0.911099345860302	-0.00519934586030157
11	0.8883	0.905900320784041	-0.0176003207840411
12	0.8924	0.88830108588699	0.00409891411301033
13	0.8833	0.892399747109296	-0.0090997471092964
14	0.87	0.883300561427096	-0.0133005614270965
15	0.8758	0.870000820604737	0.00579917939526298
16	0.8858	0.87579964220803	0.0100003577919706
17	0.917	0.885799383007926	0.0312006169920737
18	0.9554	0.916998075015537	0.0384019249844634
19	0.9922	0.955397630716438	0.0368023692835618
20	0.9778	0.992197729404226	-0.014397729404226
21	0.9808	0.97780088829671	0.00299911170329037
22	0.9811	0.980799814963806	0.000300185036194445
23	1.0014	0.981099981479484	0.0203000185205162
24	1.0183	1.00139874754976	0.0169012524502405
25	1.0622	1.01829895724343	0.0439010427565707
26	1.0773	1.06219729143737	0.0151027085626305
27	1.0807	1.07729906820819	0.00340093179180867
28	1.0848	1.08069979017271	0.00410020982728843
29	1.1582	1.08479974702935	0.0734002529706452
30	1.1663	1.1581954714246	0.00810452857540023
31	1.1372	1.16629949997490	-0.0290994999749012
32	1.1139	1.13720179535185	-0.0233017953518471
33	1.1222	1.11390143765087	0.00829856234913473
34	1.1692	1.1221994880036	0.0470005119964003
35	1.1702	1.16919710020942	0.00100289979058377
36	1.2286	1.17019993812409	0.0584000618759082
37	1.2613	1.22859639689139	0.0327036031086119
38	1.2646	1.26129798228580	0.00330201771419758
39	1.2262	1.26459979627541	-0.0383997962754135
40	1.1985	1.22620236915223	-0.0277023691522269
41	1.2007	1.19850170915307	0.00219829084693335
42	1.2138	1.20069986437205	0.0131001356279501
43	1.2266	1.21379919176093	0.0128008082390665
44	1.2176	1.22659921022854	-0.00899921022853523
45	1.2218	1.21760055522427	0.00419944477572742
46	1.249	1.22179974090686	0.0272002590931439
47	1.2991	1.24899832182562	0.0501016781743824
48	1.3408	1.29909690887677	0.0417030911232334
49	1.3119	1.34079742704439	-0.0288974270443911
50	1.3014	1.31190178288455	-0.0105017828845537
51	1.3201	1.30140064792850	0.0186993520715026
52	1.2938	1.32009884630608	-0.0262988463060772
53	1.2694	1.29380162255992	-0.0244016225599180
54	1.2165	1.26940150550690	-0.0529015055069049
55	1.2037	1.21650326386418	-0.0128032638641800
56	1.2292	1.20370078992297	0.0254992100770308
57	1.2256	1.22919842677524	-0.00359842677523847
58	1.2015	1.22560022201214	-0.0241002220121365
59	1.1786	1.20150148691140	-0.0229014869113950
60	1.1856	1.17860141295304	0.00699858704696421
61	1.2103	1.18559956820818	0.0247004317918242
62	1.1938	1.21029847605746	-0.0164984760574622
63	1.202	1.19380101790648	0.00819898209352443
64	1.2271	1.20199949414740	0.0251005058525975
65	1.277	1.22709845137409	0.0499015486259069
66	1.265	1.27699692122416	-0.0119969212241595
67	1.2684	1.26500074017405	0.00339925982595246
68	1.2811	1.26839979027587	0.0127002097241331
69	1.2727	1.28109921643516	-0.00839921643516184
70	1.2611	1.27270051820646	-0.0116005182064554
71	1.2881	1.26110071571717	0.0269992842828293
72	1.3213	1.28809833422516	0.0332016657748395
73	1.2999	1.32129795155683	-0.0213979515568299
74	1.3074	1.29990132018942	0.00749867981058472
75	1.3242	1.30739953735395	0.0168004626460476
76	1.3516	1.32419896346186	0.0274010365381421
77	1.3511	1.35159830943825	-0.000498309438251354
78	1.3419	1.35110003074420	-0.00920003074419729
79	1.3716	1.34190056761430	0.0296994323857038
80	1.3622	1.37159816763412	-0.00939816763412304
81	1.3896	1.36220057983875	0.0273994201612522
82	1.4227	1.38959830953798	0.0331016904620232
83	1.4684	1.42269795772501	0.045702042274993
84	1.457	1.46839718032110	-0.0113971803211022
85	1.4718	1.45700070317183	0.0147992968281667
86	1.4748	1.47179908692779	0.00300091307221506
87	1.5527	1.47479981485267	0.0779001851473333
88	1.5751	1.55269519379228	0.0224048062077151
89	1.5557	1.57509861769067	-0.0193986176906735
90	1.5553	1.55570119683651	-0.000401196836513851
91	1.577	1.55530002475264	0.0216999752473588
92	1.4975	1.57699866117663	-0.0794986611766293
93	1.437	1.49750490482889	-0.0605049048288906
94	1.3322	1.43700373297111	-0.104803732971107
95	1.2732	1.33220646607590	-0.0590064660759024
96	1.3449	1.27320364052193	0.0716963594780684
97	1.3239	1.34489557654972	-0.0209955765497163
98	1.2785	1.32390129536408	-0.0454012953640843
99	1.305	1.27850280112372	0.0264971988762845
100	1.319	1.30499836520232	0.0140016347976764
101	1.365	1.31899913614114	0.0460008638588607
102	1.4016	1.36499716188471	0.0366028381152927
103	1.4088	1.4015977417147	0.00720225828529952
104	1.4268	1.40879955564227	0.0180004443577286
105	1.4562	1.42679888942659	0.0294011105734135
106	1.4816	1.45619818603968	0.0254018139603163
107	1.4914	1.48159843278429	0.00980156721571346
108	1.4614	1.49139939527271	-0.0299993952727085

Extrapolation Forecasts of Exponential Smoothing
t	Forecast	95% Lower Bound	95% Upper Bound
109	1.46140185087269	1.40219697261222	1.52060672913316
110	1.46140185087269	1.37767609193199	1.54512760981338
111	1.46140185087269	1.35886021147408	1.56394349027129
112	1.46140185087269	1.34299757345455	1.57980612829083
113	1.46140185087269	1.32902225270412	1.59378144904125
114	1.46140185087269	1.31638756498461	1.60641613676077
115	1.46140185087269	1.30476875024582	1.61803495149956
116	1.46140185087269	1.29395420737674	1.62884949436864
117	1.46140185087269	1.28379695676021	1.63900674498517
118	1.46140185087269	1.27418998289135	1.64861371885403
119	1.46140185087269	1.26505249738910	1.65775120435627
120	1.46140185087269	1.25632173551827	1.66648196622710

\begin{tabular}{lllllllll}
\hline
Extrapolation Forecasts of Exponential Smoothing \tabularnewline
t & Forecast & 95% Lower Bound & 95% Upper Bound \tabularnewline
109 & 1.46140185087269 & 1.40219697261222 & 1.52060672913316 \tabularnewline
110 & 1.46140185087269 & 1.37767609193199 & 1.54512760981338 \tabularnewline
111 & 1.46140185087269 & 1.35886021147408 & 1.56394349027129 \tabularnewline
112 & 1.46140185087269 & 1.34299757345455 & 1.57980612829083 \tabularnewline
113 & 1.46140185087269 & 1.32902225270412 & 1.59378144904125 \tabularnewline
114 & 1.46140185087269 & 1.31638756498461 & 1.60641613676077 \tabularnewline
115 & 1.46140185087269 & 1.30476875024582 & 1.61803495149956 \tabularnewline
116 & 1.46140185087269 & 1.29395420737674 & 1.62884949436864 \tabularnewline
117 & 1.46140185087269 & 1.28379695676021 & 1.63900674498517 \tabularnewline
118 & 1.46140185087269 & 1.27418998289135 & 1.64861371885403 \tabularnewline
119 & 1.46140185087269 & 1.26505249738910 & 1.65775120435627 \tabularnewline
120 & 1.46140185087269 & 1.25632173551827 & 1.66648196622710 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=77795&T=3

[TABLE]
[ROW][C]Extrapolation Forecasts of Exponential Smoothing[/C][/ROW]
[ROW][C]t[/C][C]Forecast[/C][C]95% Lower Bound[/C][C]95% Upper Bound[/C][/ROW]
[ROW][C]109[/C][C]1.46140185087269[/C][C]1.40219697261222[/C][C]1.52060672913316[/C][/ROW]
[ROW][C]110[/C][C]1.46140185087269[/C][C]1.37767609193199[/C][C]1.54512760981338[/C][/ROW]
[ROW][C]111[/C][C]1.46140185087269[/C][C]1.35886021147408[/C][C]1.56394349027129[/C][/ROW]
[ROW][C]112[/C][C]1.46140185087269[/C][C]1.34299757345455[/C][C]1.57980612829083[/C][/ROW]
[ROW][C]113[/C][C]1.46140185087269[/C][C]1.32902225270412[/C][C]1.59378144904125[/C][/ROW]
[ROW][C]114[/C][C]1.46140185087269[/C][C]1.31638756498461[/C][C]1.60641613676077[/C][/ROW]
[ROW][C]115[/C][C]1.46140185087269[/C][C]1.30476875024582[/C][C]1.61803495149956[/C][/ROW]
[ROW][C]116[/C][C]1.46140185087269[/C][C]1.29395420737674[/C][C]1.62884949436864[/C][/ROW]
[ROW][C]117[/C][C]1.46140185087269[/C][C]1.28379695676021[/C][C]1.63900674498517[/C][/ROW]
[ROW][C]118[/C][C]1.46140185087269[/C][C]1.27418998289135[/C][C]1.64861371885403[/C][/ROW]
[ROW][C]119[/C][C]1.46140185087269[/C][C]1.26505249738910[/C][C]1.65775120435627[/C][/ROW]
[ROW][C]120[/C][C]1.46140185087269[/C][C]1.25632173551827[/C][C]1.66648196622710[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=77795&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=77795&T=3

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Extrapolation Forecasts of Exponential Smoothing
t	Forecast	95% Lower Bound	95% Upper Bound
109	1.46140185087269	1.40219697261222	1.52060672913316
110	1.46140185087269	1.37767609193199	1.54512760981338
111	1.46140185087269	1.35886021147408	1.56394349027129
112	1.46140185087269	1.34299757345455	1.57980612829083
113	1.46140185087269	1.32902225270412	1.59378144904125
114	1.46140185087269	1.31638756498461	1.60641613676077
115	1.46140185087269	1.30476875024582	1.61803495149956
116	1.46140185087269	1.29395420737674	1.62884949436864
117	1.46140185087269	1.28379695676021	1.63900674498517
118	1.46140185087269	1.27418998289135	1.64861371885403
119	1.46140185087269	1.26505249738910	1.65775120435627
120	1.46140185087269	1.25632173551827	1.66648196622710

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 12 ; par2 = Single ; par3 = additive ;

Parameters (R input):

par1 = 12 ; par2 = Single ; par3 = additive ;

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

par1 <- as.numeric(par1)
if (par2 == 'Single') K <- 1
if (par2 == 'Double') K <- 2
if (par2 == 'Triple') K <- par1
nx <- length(x)
nxmK <- nx - K
x <- ts(x, frequency = par1)
if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F)
if (par2 == 'Double') fit <- HoltWinters(x, gamma=F)
if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3)
fit
myresid <- x - fit$fitted[,'xhat']
bitmap(file='test1.png')
op <- par(mfrow=c(2,1))
plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing')
plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors')
par(op)
dev.off()
bitmap(file='test2.png')
p <- predict(fit, par1, prediction.interval=TRUE)
np <- length(p[,1])
plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing')
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF')
spectrum(myresid,main='Residals Periodogram')
cpgram(myresid,main='Residal Cumulative Periodogram')
qqnorm(myresid,main='Residual Normal QQ Plot')
qqline(myresid)
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,fit$alpha)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,fit$beta)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'gamma',header=TRUE)
a<-table.element(a,fit$gamma)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observed',header=TRUE)
a<-table.element(a,'Fitted',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:nxmK) {
a<-table.row.start(a)
a<-table.element(a,i+K,header=TRUE)
a<-table.element(a,x[i+K])
a<-table.element(a,fit$fitted[i,'xhat'])
a<-table.element(a,myresid[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Extrapolation Forecasts of Exponential Smoothing',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Forecast',header=TRUE)
a<-table.element(a,'95% Lower Bound',header=TRUE)
a<-table.element(a,'95% Upper Bound',header=TRUE)
a<-table.row.end(a)
for (i in 1:np) {
a<-table.row.start(a)
a<-table.element(a,nx+i,header=TRUE)
a<-table.element(a,p[i,'fit'])
a<-table.element(a,p[i,'lwr'])
a<-table.element(a,p[i,'upr'])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code