This study investigates the audit firm's decision to protect its partners' personal assets by becoming a limited liability partnership (LLP). We find that the likelihood of an audit firm switching from unlimited to limited liability is increasing in its size and exposure to litigation risk. We...

This dissertation presents two topics from opposite disciplines:one is from a parametric realm and the other is based on nonparametric methods.The first topic is a jackknife maximum likelihoodapproach to statistical model selection and the second one is a convexhull peeling depth approach to...

Regression is the procedure that attempts to relate a$p$-dimensional vector of predictors $Xb$ with a response variable$Y$. Frequently, we deal with regression problems that have a largeamount of predictors. In those cases, we try to reduce thedimension of our predictor vector. The reason we are...

Parameter identifiability is very useful if one wishes to make inferences in a statistical model. There are two important nonidentifiabilities in finite mixture models : boundary nonidentifiability and label nonidentifiability. Although parameters are not identifiable in the strict sense, in...