Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to demonstrate how to create a naive Bayes classification system when the predictor values are numeric, using the C# ...

SIAM Journal on Numerical Analysis, Vol. 48, No. 1 (2010), pp. 322-345 (24 pages) Inverse problems are often ill posed, with solutions that depend sensitively on data. In any numerical approach to the ...

This uncertainty primarily arises from the limitations in modeling gravitational wave signals. Just as accurately determining the location of an earthquake source requires precise models of the ...

A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum ...

Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 40, No. 4 (1991), pp. 365-372 (8 pages) A numerical approach to Bayesian prediction for the two-parameter Weibull ...

Parameter estimation in differential equation models is a critical endeavour in the mathematical modelling of dynamic systems. Such models, represented by ordinary differential equations (ODEs), ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...