Linear Inferential Modeling: Theoretical Perspectives, Extensions, and Comparative Analysis

A Comparative Longitudinal Analysis of Theoretical Perspectives of Interorganizational

Abduction and Induction: Syllogistic and Inferential Perspectives

Abduction and induction are reasoning forms for drawing conclusions from incomplete information. Induction, i.e. inferring properties of sets of individuals from properties of individuals, was already distinguished by Aristotle, while the term ‘abduction’ was introduced much later by Peirce for inference of explanations for observed phenomena. Both reasoning forms are presently being studied an...

Analysis and Modeling of VoIP Servers: A Linear Programming Approach

The SIP protocol was standardized by the IETF at the application layer for initiating, managing, and terminating multimedia sessions and has been widely used as the main signaling protocol on both the Internet and VoIP networks. Most challenges in this protocol are overload and lack of proper state distribution. These challenges cause a wide range of next-generation network users to face a shar...

Inferential models for linear regression

Linear regression is arguably one of the most widely used statistical methods. However, important problems, especially variable selection, remain a challenge for classical modes of inference. This paper develops a recently proposed framework of inferential models (IMs) in the linear regression context. In general, the IM framework is able to produce meaningful probabilistic summaries of the sta...

Concave Extended Linear Modeling: a Theoretical Synthesis

Extended linear modeling provides a flexible framework for functional estimation problems with multiple covariates. Such problems include ordinary and generalized regression, density and conditional density estimation, hazard regression, spectral density estimation and polychotomous regression. In this paper, we develop a general theory on the rate of convergence of maximum likelihood estimatio...