Stochastic Geometry, Spatial Statistics and Random Fields

Stochastic Geometry, Spatial Statistics and Random Fields

This volume provides a modern introduction to stochastic geometry, random fields and spatial statistics at a (post)graduate level. It is focused on asymptotic methods in geometric probability including weak and strong limit theorems for random spatial structures (point processes, sets, graphs, fields) with applications to statistics. Written as a contributed volume of lecture notes, it will be useful not only for students but also for lecturers and researchers interested in geometric probability and related subjects.

Stochastic Geometry, Spatial Statistics and Random Fields

Introduction to Stochastic Integration - Second Edition

Introduction to Stochastic Integration - Second Edition

A highly readable introduction to stochastic integration and stochastic differential equations, this book combines developments of the basic theory with applications. It is written in a style suitable for the text of a graduate course in stochastic calculus, following a course in probability.

Introduction to Stochastic Integration - Second Edition

Generalized, Linear, and Mixed Models

Generalized, Linear, and Mixed Models

Wiley Series in Probability and Statistics

Generalized, Linear, and Mixed Models

Probability in Social Science

Probability in Social Science

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Probability in Social Science

Fuzzy Probabilities New Approach and Applications

Fuzzy Probabilities New Approach and Applications

In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic because probabilities must add to one. Fuzzy random variables have fuzzy distributions. A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.

Fuzzy Probabilities New Approach and Applications