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stat.ME2026
Stabilised weighted data subsampling for accelerated Bayesian inference in models with recursive likelihoods
Matias Quiroz, Aishwarya Bhaskaran, Zixuan Wang +1
Bayesian inference for models with recursively defined likelihoods is computationally demanding, limiting scalability to large datasets. We propose a stabilised weighted subsamplin…
stat.ME2024
A maximum penalised likelihood approach for semiparametric accelerated failure time models with time-varying covariates and partly interval censoring
Aishwarya Bhaskaran, Ding Ma, Benoit Liquet +4
Accelerated failure time (AFT) models are frequently used to model survival data, providing a direct quantification of the relationship between event times and covariates. These mo…