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Annotation of /tags/release-1.1-0/README

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1 : ingmarviss 111
2 : ingmarviss 421 FITTING HIDDEN MARKOV MODELS IN R
3 :    
4 : ingmarviss 408 depmixS4 provides a framework for specifying and fitting hidden Markov
5 :     models. The observation densities use an interface to the glm
6 :     distributions, most of which are now implemented. Besides these,
7 :     observations can be modelled using the multinomial distribution with
8 :     identity or logistic link function. The latter provides functionality for
9 :     multinomial logistic responses with covariates. The transition matrix and
10 :     the initial state probabilities are also modeled as multinomial logistics
11 : ingmarviss 421 (or multinomials with identity link, which is the default when no
12 :     covariates are present) with the possibility of including covariates.
13 : ingmarviss 434
14 : ingmarviss 421 Optimization is by default done using the EM algorithm. When linear
15 :     constraints are included, package Rsolnp is used for optimization (there is
16 :     also support for using Rdonlp2 as optimizer, see details below). New
17 :     response distributions can be added by extending the response-class and
18 : ingmarviss 408 writing appropriate methods for it (dens, and getpars and setpars); an
19 :     example of this is provided on the ?makeDepmix help page. depmixS4 also
20 : ingmarviss 421 fits latent class and mixture models, see ?mix for an example.
21 : ingmarviss 111
22 : ingmarviss 421 The latest development versions of depmixS4 (and depmix) can be found at:
23 : ingmarviss 111 https://r-forge.r-project.org/projects/depmix/
24 :    
25 :    
26 : ingmarviss 408 FOR DEPMIX USERS
27 : ingmarviss 111
28 : ingmarviss 408 depmixS4 is a completely new implementation of the depmix package using S4
29 :     classes. Model specification now uses formulae and family objects,
30 :     familiar from the lm and glm functions. Moreover, the transition matrix
31 :     and the initial state probabilities (as well as multinomial responses) are
32 :     now modeled as multinomial logistics with a baseline. Specification of
33 :     linear constraints uses the same mechanism as was used in depmix, with the
34 :     only difference that constraints are passed as arguments to the fit
35 :     function rather than the model specification function. See the help files
36 : ingmarviss 421 for further details. NOTE: most of the functionality of depmix is now
37 :     also provided in depmixS4; in the future therefor I may stop updating
38 :     depmix.
39 : ingmarviss 111
40 :    
41 : ingmarviss 408 USING RDONLP2
42 : ingmarviss 111
43 : ingmarviss 421 Optimization of models with (general) linear (in-)equality constraint is
44 :     done using Rsolnp (available from CRAN). Optionally the Rdonlp2 package
45 :     can be used; Rdonlp2 was written by Ryuichi Tamura(ry.tamura @ gmail.com),
46 :     and used to be available from: http://arumat.net/Rdonlp2/ The present
47 :     status of Rdonlp2 is unclear.

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