A unified estimation procedure is proposed for the analysis of censored data using linear transformation models, which include the proportional hazards model and the proportional odds model as special cases. This procedure is easily implemented numerically and its validity does not rely on the assumption of independence between the covariates and the censoring variable. The estimator is the sam...

For survival data regression, the Cox proportional hazards model is the most popular model, but in certain situations the Cox model is inappropriate. Various authors have proposed the proportional odds model as an alternative. Yang and Prentice recently presented a number of easily implemented estimators for the proportional odds model. Here we show how to extend the methods of Yang and Prentic...

Cox's proportional hazards model is often t to grouped survival data, i.e. occurrence/exposure data over given time intervals and covariate strata. We derive a Sheppard correction for the bias in the grouped data analogue of Cox's maximum partial likelihood estimator. This is done via a large sample theory in which the covariate strata and time intervals shrink as the sample size increases.

Recently, a new optimizer, called the Aquila Optimizer (AO), was developed to solve different optimization problems. Although AO has significant performance in various problems, like other algorithms, suffers from certain limitations its search mechanism, such as local optima stagnation and convergence speed. This is general problem that faces almost all which can be solved by enhancing process...