| Interface | Description |
|---|---|
| MixtureDistribution |
This is the conditional distribution of the observations in each state
(possibly differently parameterized) of a mixture hidden Markov model.
|
| Class | Description |
|---|---|
| BetaMixtureDistribution |
The HMM states use the Beta distribution to model the observations.
|
| BetaMixtureDistribution.Lambda |
the Beta distribution parameters
|
| BinomialMixtureDistribution |
The HMM states use the Binomial distribution to model the observations.
|
| BinomialMixtureDistribution.Lambda |
the Binomial distribution parameters
|
| ExponentialMixtureDistribution |
The HMM states use the Exponential distribution to model the observations.
|
| GammaMixtureDistribution |
The HMM states use the Gamma distribution to model the observations.
|
| GammaMixtureDistribution.Lambda |
the Gamma distribution parameters
|
| LogNormalMixtureDistribution |
The HMM states use the Log-Normal distribution to model the observations.
|
| LogNormalMixtureDistribution.Lambda |
the log-normal distribution parameters
|
| NormalMixtureDistribution |
The HMM states use the Normal distribution to model the observations.
|
| NormalMixtureDistribution.Lambda |
the Normal distribution parameters
|
| PoissonMixtureDistribution |
The HMM states use the Poisson distribution to model the observations.
|
Copyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.