R: Markov Modulated Poisson Process - Deprecated Functions

HiddenMarkov-mmpp-deprecated {HiddenMarkov} | R Documentation

## Markov Modulated Poisson Process - Deprecated Functions

### Description

These functions are deprecated and will ultimately be removed from the package. Please change to the revised versions: `BaumWelch`, `Estep.mmpp`, `forwardback.mmpp`, `simulate` or `logLik`.

### Usage

    backward0.mmpp(tau, Q, lambda)
    forward0.mmpp(tau, Q, delta, lambda)

    logLikmmpp(tau, Q, delta, lambda)

    Estep0.mmpp(tau, Q, delta, lambda)

    Baum.Welch.mmpp(tau, Q, delta, lambda, nonstat = TRUE,
                    maxiter = 500, tol = 1e-05, prt = TRUE,
                    converge = expression(diff < tol))
    Baum.Welch0.mmpp(tau, Q, delta, lambda, nonstat = TRUE,
                     maxiter = 500, tol = 1e-05, prt = TRUE,
                     converge = expression(diff < tol))

    sim.mmpp(n, initial, Q, lambda)

### Arguments

`tau` | vector containing the interevent times. Note that the first event is at time zero.
`Q` | the infinitesimal generator matrix of the Markov process.
`lambda` | a vector containing the Poisson rates.
`delta` | is the marginal probability distribution of the m hidden states at time zero.
`n` | number of Poisson events to be simulated.
`initial` | integer, being the initial hidden Markov state (1, \cdots, m).
`nonstat` | is logical, `TRUE` if the homogeneous Markov chain is assumed to be non-stationary, default.
`maxiter` | is the maximum number of iterations, default is 500.
`tol` | is the convergence criterion, being the difference between successive values of the log-likelihood; default is 0.00001.
`prt` | is logical, and determines whether information is printed at each iteration; default is `TRUE`.
`converge` | is an expression giving the convergence criterion.

### Details

The functions with a suffix of zero are non-scaled, and hence will have numerical problems for series containing larger numbers of events; and are much slower.

These functions use the algorithm given by Ryden (1996) based on eigenvalue decompositions.

[Package HiddenMarkov version 1.8-8 Index]