Multicollinearity and maximum entropy leuven estimator

Multicollinearity is a serious problem in applied regression analysis. Q. Paris (2001) introduced the MEL estimator to resolve the multicollinearity problem. This paper improves the MEL estimator to the Modular MEL (MMEL) estimator and shows by Monte Carlo experiments that MMEL estimator performs significantly better than OLS as well as MEL estimators.maximum entropy

Network Externality and Software Piracy

copyright, software piracy, network externality, market structure, competition

Network Externality and Commercial Software Piracy

Contrary to the earlier findings under end-users piracy where the existence of strong network externality was shown to be a reason for allowing limited piracy, we find when the piracy is commercial in nature the optimal policy for the original software developer is to protect its product irrespective of the strength of network externality in the software users market.Copyright violations, Commercial/Retail piracy, Network externality, Quality

Clustering of Data with Missing Entries

The analysis of large datasets is often complicated by the presence of missing entries, mainly because most of the current machine learning algorithms are designed to work with full data. The main focus of this work is to introduce a clustering algorithm, that will provide good clustering even in the presence of missing data. The proposed technique solves an $\ell_0$ fusion penalty based optimization problem to recover the clusters. We theoretically analyze the conditions needed for the successful recovery of the clusters. We also propose an algorithm to solve a relaxation of this problem using saturating non-convex fusion penalties. The method is demonstrated on simulated and real datasets, and is observed to perform well in the presence of large fractions of missing entries.Comment: arXiv admin note: substantial text overlap with arXiv:1709.0187