Description Usage Arguments Details Value

This function directly maximize the log likelihood function through optimization. With this function, three models can be fitted: (1) Generalized Poisson mixture with equal dispersion (E model); (2) Generalized Poisson mixture with unequal dispersion (V model); (3) 0-inflated Generalized Poisson model. The 0-inflated Generalized Poisson has the following density function:

1 |

`y` |
A vector representing the RNAseq raw count. |

`d` |
A vector of the same length as y representing the normalization constant to be applied to the data. |

`inits` |
Initial value to fit the mixture model. A vector with elements mu1, mu2, phi1, phi2 and pi1. |

`model` |
Character specifying E or V model. E model fits the mixture model with equal dispersion phi while V model doesn't put any constraint. |

`zeroPercentThr` |
A |

scalar specifying the minimum percent of zero counts needed when fitting a zero-inflated Generalized Poisson model. This parameter is used to deal with zero-inflation in RNAseq count data. When the percent of zero exceeds this threshold, rather than fitting a 2-component Generalized Poisson mixture, a mixture of point mass at 0 and Generalized Poisson is fitted.

*P(Y=y)=π D(y) + (1-π)GP(μ, φ)* where D is the point mass at 0 while *GP(μ, φ)* is the density
of Generalized Poisson distribution with mean *μ* and dispersion *φ*. The variance is *φ μ*.

The rule to fit 0-inflated model is that the observed percentage of count exceeds the user specified threshold. This rule overrides the model argument when observed percentae of zero count exceeds the threshold.

A vector consisting parameter estimates of mu1, mu2, phi1, phi2, pi1, logLik and BIC. For 0-inflated model, mu1=phi1=0.

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