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math.PR2023
Classification of small-ball modes and maximum a posteriori estimators in metric spaces
Ilja Klebanov, Hefin Lambley, T. J. Sullivan
A mode, or `most likely point', for a probability measure can be defined in various ways via the asymptotic behaviour of the -mass of balls as their radius tends to zero. Su…
math.PR2023
Images of Gaussian and other stochastic processes under closed, densely-defined, unbounded linear operators
Tadashi Matsumoto, T. J. Sullivan
Gaussian processes (GPs) are widely-used tools in spatial statistics and machine learning and the formulae for the mean function and covariance kernel of a GP that is the ima…