SMAPHMM-class: Class "SMAPHMM": A class to manage HMMs for the SMAP package

In SMAP: A Segmental Maximum A Posteriori Approach to Array-CGH Copy Number Profiling

Description

Holds parameters for a Hidden Markov Model (HMM) used in the SMAP package.

Objects from the Class

Objects should not be created directly but via the constructor function SMAPHMM.

Slots

A:

Object of class "matrix" The transition probability matrix between states.

Pi:

Object of class "numeric" The initial probabilities of starting in a certain state.

Phi:

Object of class "matrix" A matrix that specifies the paramaters of Gaussian distributions associated with each hidden state. The first column specifies standard deviations, the second specifies means.

noStates:

Object of class "numeric" The number of hidden states in the HMM.

Z:

Object of class "matrix" Matrix of transition probabilities.

Y:

Object of class "numeric" Vector of initial probabilities.

eta:

Object of class "ANY". Internal slot.

grad:

Object of class "ANY". Internal slot.

Methods

A

signature(object = "SMAPHMM"): Returns the transition matrix.

Pi

signature(object = "SMAPHMM"): Returns the initial probabilities.

Phi

signature(object = "SMAPHMM"): Returns the distribution parameter matrix.

noStates

signature(object = "SMAPHMM"): Returns the number of hidden states in the HMM.

Author(s)

Robin Andersson, [e-mail]

References

Andersson, R., Bruder, C. E. G., Piotrowski, A., Menzel, U., Nord, H., Sandgren, J., Hvidsten, T. R., Diaz de Stahl, T., Dumanski, J. P., Komorowski, J., A Segmental Maximum A Posteriori Approach to Array-CGH Copy Number Profiling, submitted

See Also

smap, SMAPHMM

SMAP documentation built on Nov. 8, 2020, 8:26 p.m.