Bayesian semi-parametric inference is considered for a log-linear model. This model consists of a parametric component for the regression coeecients and a nonparametric component for the unknown error distribution. Bayesian analysis is studied for the case of a parametric prior on the regression coeecients and a mixture-of-Dirichlet-processes prior on the unknown error distribution. A Markov ch...

In this manuscript, we discuss the distinction of two types of data generating scheme for the accelerated failure time model. We identify two different empirical likelihood formulations under random right censoring, case-wise and residual-wise, each reflecting the relevant features of the stochastic model assumed to have generated the data. We specifically propose the case-wise empirical likeli...

a real-time optimization (rto) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. furthermore, the objective function is penalized by a fuzzified form of the key process constraints. to enable using conventional optimization techniques, the resulting fuzzy optimization problem is then re...

Consider the optimal control of a manufacturing system consisting of stages in which a single consumable good is produced in a random jump environment. At each stage of the manufacturing process there are workstations that can fail and be repaired. The workstations are assumed to have different operating parameters for a given stage. The mean time to failure for a given workstation, on a given ...