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Markov Chain model

Source: R/model_doc.R
MC.Rd

For more details see the Markov Chain vignette.

Arguments

K

Number of states of the Markov Chain

prior

Named list of the model's priors. If NULL, uses the default prior for the model (see default_prior()).

Details

Details of the model are available in the paper.

Parameters

  • p: matrix of size K * K where p[i, j] represents the transition probabilities from state i to state j.

See list_parameters(model = "MC") for more details.

Priors

The priors are passed as a named list with element p. The transition probabilities from state i p[i, ] are assumed to follow a Dirichlet distribution. The prior should be a matrix where each line correspond to the parameters of the Dirichlet distribution for p[i, ].

Default priors

The default prior for all p[i, ] is a symmetric uniform Dirichlet distribution (all concentration parameters are equal to 1).

Examples

EczemaModel("MC", K = 5)
#> MC model (discrete)
#> 5 categories 
#> Prior: 
#> - p[1, ] ~ dirichlet(1,1,1,1,1)
#> - p[2, ] ~ dirichlet(1,1,1,1,1)
#> - p[3, ] ~ dirichlet(1,1,1,1,1)
#> - p[4, ] ~ dirichlet(1,1,1,1,1)
#> - p[5, ] ~ dirichlet(1,1,1,1,1)