BCA1SG_NHPP {BCA1SG} | R Documentation |

This function implements the BCA1SG algorithm on the semiparametric nonhomogeneous Poisson process model for panel count data to solve the ML estimates of the model parameters.

BCA1SG_NHPP(input_data, initial_beta, initial_Lambda = function(x){x}, threshold = 1e-05, max_iter = 5000, max_stepsize = 10000, xi = 0.3, contraction = 0.5)

`input_data` |
An object of class data.frame. The structure of the data frame must be {patient ID, time of measurement, measurement(cumulative counts),covariate_1,...,covariate_p}. This data frame cannot contain missing values. See the dataset "skiTum" for an example. |

`initial_beta` |
The initial value of the regression coefficients. The dimension of this input should comply with the dimension of the covariates. |

`initial_Lambda` |
An R function which serves as the initial value of the baseline mean cumulative function. |

`threshold` |
Convergence threshold. The algorithm is terminated when the infinity norm of the difference between successive iterates is less than the convergence threshold. |

`max_iter` |
Maximum number of iterations allowed. |

`max_stepsize` |
Maximum stepsize allowed. |

`xi` |
The xi parameter in the inexact backtracking line search algorithm. See Wang et al. (2020) for details. |

`contraction` |
The contraction parameter in the inexact backtracking line search algorithm. See Wang et al. (2020) for details. |

Details about the BCA1SG algorithm can be found in Wang et al. (2020), and the details concerning the semiparametric NHPP model can be found in Wellner and Zhang (2007).

`distinct_time` |
The set of distinct observation time points. |

`est_Lambda` |
The estimated baseline mean cumulative function at the set of distinct observation time points. |

`est_beta` |
The estimated regression coefficients. |

`iteration` |
The number of iterations. |

`timecost` |
The computational time in seconds. |

Wang Y., Ye Z., and Cao H.

Wang Y., Ye, Z.-S., and Cao, H.(2020). On Computation of Semi-Parametric Maximum Likelihood Estimators with Shape Constraints. Submitted.

Wellner J.A. and Zhang Y.(2007). Two Likelihood-Based Semiparametric Estimation Methods for Panel Count Data with Covariates. The Annals of Statistics, 35(5), 2106-2142.

data(adapt_skiTum) res<-BCA1SG_NHPP(adapt_skiTum, initial_beta = rep(0,4), threshold = 2e-3) res$est_beta res$iteration res$timecost plot(res$distinct_time,res$est_Lambda,type="s",lwd=3, xlab="Time",ylab="Baseline mean cumulative function")

[Package *BCA1SG* version 0.1.0 Index]