Techniques of handling high-dimensional data is a really active research area lately as data collection and storage methods are advanced now. Variable selection and dimension reduction are two main sections of this area. In this dissertation, we introduce three techniques for dealing
with situations where the number of predictors is extremely high, which are suited for various data types and models.