Zero-Inflated Poisson Hidden (Semi-)Markov Models

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Documentation for package ‘ziphsmm’ version 2.0.6

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package-ziphsmm-package zero-inflated poisson hidden (semi-)Markov models
ziphsmm-package zero-inflated poisson hidden (semi-)Markov models
CAT Pseudo activity counts (per minute) data for cats
convolution Convolution of two real vectors of the same length.
dist_learn Distributed learning for a longitudinal continuous-time zero-inflated Poisson hidden Markov model, where zero-inflation only happens in State 1. Assume that priors, transition rates and state-dependent parameters can be subject-specific, clustered by group, or common. But at least one set of the parameters have to be common across all subjects.
dist_learn2 Distributed learning for a longitudinal continuous-time zero-inflated Poisson hidden Markov model, where zero-inflation only happens in State 1 and covariates are for state-dependent zero proportion and means. Assume that priors, transition rates, state-dependent intercepts and slopes can be subject-specific, clustered by group, or common. But at least one set of the parameters have to be common across all subjects.
dist_learn3 Distributed learning for a longitudinal continuous-time zero-inflated Poisson hidden Markov model, where zero-inflation only happens in State 1 with covariates in the state-dependent parameters and transition rates.
dzip pmf for zero-inflated poisson
fasthmmfit Fast gradient descent / stochastic gradient descent algorithm to learn the parameters in a specialized zero-inflated hidden Markov model, where zero-inflation only happens in State 1. And if there were covariates, they could only be the same ones for the state-dependent log Poisson means and the logit structural zero proportion.
fasthmmfit.cont Fast gradient descent algorithm to learn the parameters in a specialized continuous-time zero-inflated hidden Markov model, where zero-inflation only happens in State 1. And if there were covariates, they could only be the same ones for the state-dependent log Poisson means and the logit structural zero proportion.
fasthmmfit.cont3 Fast gradient descent algorithm to learn the parameters in a specialized continuous-time zero-inflated hidden Markov model, where zero-inflation only happens in State 1 with covariates in the state-dependent parameters and transition rates.
fasthsmmfit Fast gradient descent / stochastic gradient descent algorithm to learn the parameters in a specialized zero-inflated hidden semi-Markov model, where zero-inflation only happens in State 1. And if there were covariates, they could only be the same ones for the state-dependent log Poisson means and the logit structural zero proportion. In addition, the dwell time distributions are nonparametric for all hidden states.
grad_zipnegloglik_cov_cont gradient for negative log likelihood function in zero-inflated Poisson hidden Markov model with covariates, where zero-inflation only happens in state 1
grad_zipnegloglik_nocov_cont gradient for negative log likelihood function from zero-inflated Poisson hidden Markov model without covariates, where zero-inflation only happens in state 1
hmmfit Estimate the parameters of a general zero-inflated Poisson hidden Markov model by directly minimizing of the negative log-likelihood function using the gradient descent algorithm.
hmmsim Simulate a hidden Markov series and its underlying states with zero-inflated emission distributions
hmmsim.cont Simulate a hidden Markov series and its underlying states with zero-inflated emission distributions
hmmsim2 Simulate a hidden Markov series and its underlying states with covariates
hmmsim2.cont Simulate a continuous-time hidden Markov series and its underlying states with covariates
hmmsim3.cont Simulate a continuous-time hidden Markov series and its underlying states with covariates in state-dependent parameters and transition rates.
hmmsmooth.cont Compute the posterior state probabilities for continuous-time hidden Markov models without covariates where zero-inflation only happens in state 1
hmmsmooth.cont2 Compute the posterior state probabilities for continuous-time hidden Markov models where zero-inflation only happens in state 1 and covariates can only be included in the state-dependent parameters
hmmsmooth.cont3 Compute the posterior state probabilities for continuous-time hidden Markov models with covariates in the state-dependent parameters and transition rates
hmmviterbi Viterbi algorithm to decode the latent states for hidden Markov models
hmmviterbi.cont Viterbi algorithm to decode the latent states for continuous-time hidden Markov models without covariates
hmmviterbi2 Viterbi algorithm to decode the latent states in hidden Markov models with covariate values
hmmviterbi2.cont Viterbi algorithm to decode the latent states in continuous-time hidden Markov models with covariates
hsmmfit Estimate the parameters of a general zero-inflated Poisson hidden semi-Markov model by directly minimizing of the negative log-likelihood function using the gradient descent algorithm.
hsmmfit_exp Simulate a hidden semi-Markov series and its underlying states with covariates where the latent state distributions have accelerated failure time structure whose base densities are exponential
hsmmsim Simulate a hidden semi-Markov series and its corresponding states according to the specified parameters
hsmmsim2 Simulate a hidden semi-Markov series and its underlying states with covariates
hsmmsim2_exp Simulate a hidden semi-Markov series and its underlying states with covariates
hsmmviterbi Viterbi algorithm to decode the latent states for hidden semi-Markov models
hsmmviterbi2 Viterbi algorithm to decode the latent states in hidden semi-Markov models with covariates
hsmmviterbi_exp Viterbi algorithm to decode the latent states in hidden semi-Markov models with covariates where the latent state durations have accelerated failure time structure
package-ziphsmm zero-inflated poisson hidden (semi-)Markov models
retrieve_cov_cont retrieve the natural parameters from the working parameters in zero-inflated Poisson hidden Markov model with covariates, where zero-inflation only happens in state 1
retrieve_cov_cont3 retrieve the natural parameters from the working parameters in zero-inflated Poisson hidden Markov model with covariates in state-dependent parameters and transition rates
retrieve_nocov_cont retrieve the natural parameters from working parameters for a continuous-time zero-inflated Poisson hidden Markov model where zero-inflation only happens in state 1
rzip generate zero-inflated poisson random variables
zipnegloglik_cov_cont negative log likelihood function for zero-inflated Poisson hidden Markov model with covariates, where zero-inflation only happens in state 1
zipnegloglik_cov_cont3 negative log likelihood function for zero-inflated Poisson hidden Markov model with covariates in state-dependent parameters and transition rates
zipnegloglik_nocov_cont negative log likelihood function for zero-inflated Poisson hidden Markov model without covariates, where zero-inflation only happens in state 1