Grant: Discovery Grants Program - Individual

) My work focuses on constructing the experimental designs for regression problems. Good designs should lead to small biases in the estimates when the fitted model is incorrect, and should also be efficient (i.e., lead to small variances) in the estimates when the fitted model is in fact correct. I intend to work on the design constructions for the regression problem with a very general setup. The regression responses are considered to be a function of a linear function. We watch for the situation where the fitted model may not exactly represent the truth. Other possible departures from the usual assumptions are also taken into account. Errors may not equally vary as they are assumed, for instance. ) Applications to accelerated life testing (ALT) are explored as well. ALT is the process of determining the lifetime of a product or material with a long lifespan in a relatively short period of time. In order to obtain the failures, the normal use conditions such as voltage, temperature, pressure, and use rate have to be accelerated. An ALT model will be fitted to the data at accelerated levels and the estimates are extrapolated to the normal use levels. The designs constructed are also expected to incorporate censoring schemes and/or stress loading plans for ALT in a good manner. ) The derivation of the designs discussed above tends to be complicated mathematically, as I have demonstrated in my past work. I intend to investigate how to simplify design construction with a relatively small tradeoff in efficiency.