activity
20102018
most citedEstimating Discrete Markov Models From Various Incomplete Data Schemes

25 citations · 50 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2018

Validation of a computer code for the energy consumption of a building, with application to optimal electric bill pricing

M. Keller, G. Damblin, A. Pasanisi +4

In this paper, we propose a practical Bayesian framework for the calibration and validation of a computer code, and apply it to a case study concerning the energy consumption forec…

stat.CO2015★ 24 cited

Adaptive numerical designs for the calibration of computer codes

Guillaume Damblin, Pierre Barbillon, Merlin Keller +2

Making good predictions of a physical system using a computer code requires the inputs to be carefully specified. Some of these inputs called control variables have to reproduce ph…

stat.AP2014

On the practical interest of discrete Inverse Polya and Weibull-1 models in industrial reliability studies

Alberto Pasanisi, Côme Roero, Nicolas Bousquet +1

Engineers often cope with the problem of assessing the lifetime of industrial components, under the basis of observed industrial feedback data. Usually, lifetime is modelled as a c…

stat.AP2010★ 1 cited

On the Role of Decision Theory in Uncertainty Analysis

Merlin Keller, Eric Parent, Alberto Pasanisi

Maximum likelihood estimation (MLE) and heuristic predictive estimation (HPE) are two widely used approaches in industrial uncertainty analysis. We review them from the point of vi…

stat.CO2010★ 25 cited

Estimating Discrete Markov Models From Various Incomplete Data Schemes

Alberto Pasanisi, Shuai Fu, Nicolas Bousquet

The parameters of a discrete stationary Markov model are transition probabilities between states. Traditionally, data consist in sequences of observed states for a given number of…