Persons : their identity and individuation

This study is about the nature of persons and personal identity. It belongs to a tradition that maintains that in order to understand what it is to be a person we must clarify what personal identity consists in. In this pursuit, I differentiate between the problems (i) How do persons persist? and (ii) What facts, if any, does personal identity consist in? Concerning the first question, I argue that persons persist three-dimensionally (the endurance view), and not four-dimensionally (the perdurarne view), on the ground that objects must always fall under some substance sortal concept S (the sortal dependency of individuation), and that the concept person entails that objects falling under it are three-dimensional. Concerning the second question, I differentiate between Criterianists, who maintain that it is possible to specify a non-circular and informative criterion for personal identity, and Non-Criterianists, who deny that such a specification is possible. I argue against Criterianist accounts of personal identity on the ground that they are either (i) circular, (ii) violate the intrinsicality of identity or (iii) do not adequately represent what we are essentially. I further criticise three Psychological Non-Criterianist accounts of personal identity on the ground that they wrongly assume that 'person' refers to mental entities. Instead I formulate the Revised Animal Attribute View where person is understood as a basic sortal concept which picks out a biological sort of enduring animals. In this, I claim that the real essence of a person is determined by the real essence of the kind of animal he is, without thereby denying that persons have a real essence as persons.

Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.