Reverse-time diffusion in environmental models

TL;DR: In this paper, the authors explore questions of existence and uniqueness for solutions to stochastic differential equations and offer a study of their properties, using diffusion processes as a model of a Markov process with continuous sample paths.

TL;DR: In this paper, an estimator based on the combination of forward and reverse time estimators has been developed, which has a higher order of convergence than the classical estimator, and the computational complexity of the forward-reverse estimator is superior to the classical approach.

TL;DR: Density estimation, as discussed in this book, is the construction of an estimate of the density function from the observed data from an unknown probability density function.

TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.

TL;DR: In this paper, the authors present a characterization of continuous local martingales with respect to Brownian motion in terms of Markov properties, including the strong Markov property, and a generalized version of the Ito rule.

TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.