Abduction as Incomplete Parameter Estimation

Ranking as parameter estimation

Ranking of alternatives is a common, difficult and repeatedly addressed problem, especially when it requires negotiation of experts. The celebrated Arrow’s impossibility theorem expresses formally its difficulty. In spite of theprogressmadebyadopting soft ranking, the problem is far from being generically solved. The paper provides a, probably novel, problem formulation by viewing ranking of al...

Credit risk and incomplete information: filtering and EM parameter estimation

We consider a reduced-form credit risk model where default intensities and interest rate are functions of a not fully observable Markovian factor process, thereby introducing an information-driven default contagion effect among defaults of different issuers. We determine arbitrage-free prices of OTC products coherently with information from the financial market, in particular yields and credit ...

Parameter Estimation in Bayesian Networks from Incomplete Databases

Abduction for Extending Incomplete Information Sources

The extraction of information from a source containing termclassified objects is plagued with uncertainty, due, among other things, to the possible incompleteness of the source index. To overcome this incompleteness, the study proposes to expand the index of the source, in a way that is as reasonable as possible with respect to the original classification of objects. By equating reasonableness ...

On the estimation of a parameter with incomplete knowledge on a nuisance parameter

In this paper we consider the problem of estimating a parameter of a probability distribution when we have some prior information on a nuisance parameter. We start by the very simple case where we know perfectly the value of the nuisance parameter. The complete likelihood is the classical tool in this case. Then, progressively, we consider the case where we are given a prior probability distrib...