Semiparametric inference for multiple nonnegative distributions with excess zero observations
A non-standard, but not uncommon, situation is to observe multiple samples of nonnegative data which have a high proportion of zeros. This talk will focus on some important, and fundamental, statistical inference problems for such data structure. A unique feature of the target populations is that the distribution of each sample is characterized by a non-standard mixture of a singular distribution at zero and a skewed nonnegative component. We propose modelling the nonnegative components using a semiparametric, multiple-sample, density ratio model. Under this semiparametric setup, we can exploit information from all available samples even with unspecified underlying distributions.