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nhm (version 0.1.2)

Non-Homogeneous Markov and Hidden Markov Multistate Models

Description

Fits non-homogeneous Markov multistate models and misclassification-type hidden Markov models in continuous time to intermittently observed data. Implements the methods in Titman (2011) . Uses direct numerical solution of the Kolmogorov forward equations to calculate the transition probabilities.

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Version

Install

install.packages('nhm')

Monthly Downloads

184

Version

0.1.2

License

GPL (>= 2)

Maintainer

Andrew Titman

Last Published

August 31st, 2025

Functions in nhm (0.1.2)

initialprob.nhm

Compute the initial probability vector from a fitted nhm model
state_occupation_probability.nhm

Compute state occupation probabilities from a fitted nhm model
plot.nhm

Plot transition probabilities, intensities or state occupation probabilities from a fitted nhm model.
predict.nhm

Compute transition probabilities from a fitted nhm model
ematrix.nhm

Compute the misclassification probability matrix from a fitted nhm model
nhm.control

Ancillary arguments for controlling nhm fits
example_data1

Example of data on a progressive 4 state process
expected_hitting_time

Compute the estimated hitting time for a state of a progressive multi-state model.
model.nhm

Model object set up for non-homogeneous Markov models
print.nhm_score

Print output from a score test of a nhm object
state_life_expectancy

State-specific life expectancies and quality-adjusted life years
qmatrix.nhm

Compute transition intensities from a fitted nhm model
nhm

Fit a non-homogeneous Markov model using maximum likelihood
example_data2

Example of data on a progressive 4 state process with state misclassification