AbstractWe use standard results from convex geometry to obtain representations of the prior and posterior degrees of imprecision in terms of width functions and difference bodies. These representations are used to construct algorithms for the calculation of the prior and the posterior degree of imprecision
The theory of lower previsions is designed around the principles of coherence and sure-loss avoidanc...
Imprecision arises naturally in the context of computer models and their relation to reality. An imp...
We study a unified approach and algorithm for constructive discrepancy minimization based on a stoch...
AbstractWe use standard results from convex geometry to obtain representations of the prior and post...
AbstractThis article investigates the computation of posterior upper expectations induced by impreci...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Resea...
Imprecise probabilism—which holds that rational belief/credence is permissibly represented by a set ...
This thesis provides an exploration of the interplay between imprecise probability and statistics. M...
Traditional geometric algorithms are often presented as if input imprecision does not exist, even th...
Let p and q be two imprecise points, given as probability density functions on R^2, and let R be a s...
This special issue of the International Journal of Approximate Reasoning (IJAR) grew out of the 4th...
My dissertation examines two kinds of statistical tools for taking prior information into account, a...
Bayesian inference is a method of statistical inference in which all forms of uncertainty are expres...
In this paper we study two classes of imprecise previsions, which we termed convex and centered conv...
discrepancy in numerical analysis and statistics Josef Dick∗ In this paper we discuss various connec...
The theory of lower previsions is designed around the principles of coherence and sure-loss avoidanc...
Imprecision arises naturally in the context of computer models and their relation to reality. An imp...
We study a unified approach and algorithm for constructive discrepancy minimization based on a stoch...
AbstractWe use standard results from convex geometry to obtain representations of the prior and post...
AbstractThis article investigates the computation of posterior upper expectations induced by impreci...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Resea...
Imprecise probabilism—which holds that rational belief/credence is permissibly represented by a set ...
This thesis provides an exploration of the interplay between imprecise probability and statistics. M...
Traditional geometric algorithms are often presented as if input imprecision does not exist, even th...
Let p and q be two imprecise points, given as probability density functions on R^2, and let R be a s...
This special issue of the International Journal of Approximate Reasoning (IJAR) grew out of the 4th...
My dissertation examines two kinds of statistical tools for taking prior information into account, a...
Bayesian inference is a method of statistical inference in which all forms of uncertainty are expres...
In this paper we study two classes of imprecise previsions, which we termed convex and centered conv...
discrepancy in numerical analysis and statistics Josef Dick∗ In this paper we discuss various connec...
The theory of lower previsions is designed around the principles of coherence and sure-loss avoidanc...
Imprecision arises naturally in the context of computer models and their relation to reality. An imp...
We study a unified approach and algorithm for constructive discrepancy minimization based on a stoch...
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