New exact inference methods for small size of lifetime data
Keming Yu (Brunel University London)
Friday 10th October, 2014 15:00-16:00 Maths 203
Small sizes of lifetime data with or without censoring are widely available in engineering and medicine. Some classical methods such as maximum likelihood estimate for fitting skewed probability distributions and non-Gaussian regression models with small sizes data often face a range of challenges such as something like that asymptotic confidence intervals and statistical tests are invalid. This talk will present some new ideas and alternative methods to achieve exact inference on the topic without requiring any bootstrapping or Bayesian inference.