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BCA1SG: Block Coordinate Ascent with One-Step GR

Goal

BCA1SG is an R package implementing the block coordinate ascent with one-step Generalized Rosen (BCA1SG) algorithm on the semiparametric models for panel count data, interval-censored survival data, and degradation data.

Details

• A comprehensive description of the BCA1SG algorithm can be found in Wang et al. (2020).
• For panel count data, we focus on the semiparametric nonhomogeneous Poisson process model in Wellner and Zhang (2007).
• For interval-censored survival data, we focus on the semiparametric proportional hazard model in Section 4 of Huang and Wellner (1997).
• For degradation data, we focus on the semiparametric random-effects inverse Gaussian process model in Section 3 of Wang and Xu (2010).

References

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.

Huang J. and Wellner, J.A.(1997). Interval-Censored Survival Data: A Review of Recent Progress. Proceedings of the Fifth Seattle Symposium in Biostatistics, 123-169.

Wang X. and Xu, D.(2010). An Inverse Gaussian Process Model for Degradation Data. Technometrics, 52(2), 188-197.

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They may not be fully stable and should be used with caution. We make no claims about them.
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