Logo

Convergence of Stochastic Processes

Large book cover: Convergence of Stochastic Processes

Convergence of Stochastic Processes
by

Publisher: Springer
ISBN/ASIN: 1461297583
ISBN-13: 9781461297581
Number of pages: 223

Description:
An exposition od selected parts of empirical process theory, with related interesting facts about weak convergence, and applications to mathematical statistics. The high points of the book describe the combinatorial ideas needed to prove maximal inequalities for empirical processes indexed by classes of sets or classes of functions.

Home page url

Download or read it online for free here:
Download link
(8.6MB, PDF)

Similar books

Book cover: Probability, Statistics and Stochastic ProcessesProbability, Statistics and Stochastic Processes
by
Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Markov Processes, Continuous-Time Processes).
(8255 views)
Book cover: Introduction Probaility and StatisticsIntroduction Probaility and Statistics
by - University of Southern Maine
Topics: Data Analysis; Probability; Random Variables and Discrete Distributions; Continuous Probability Distributions; Sampling Distributions; Point and Interval Estimation; Large Sample Estimation; Large-Sample Tests of Hypothesis; etc.
(23340 views)
Book cover: Probability and Statistics for Geophysical ProcessesProbability and Statistics for Geophysical Processes
by - National Technical University of Athens
Contents: The utility of probability; Basic concepts of probability; Elementary statistical concepts; Special concepts of probability theory in geophysical applications; Typical univariate statistical analysis in geophysical processes; etc.
(3433 views)
Book cover: Introduction to Probability Theory and Statistics for LinguisticsIntroduction to Probability Theory and Statistics for Linguistics
by - UCLA
Contents: Basic Probability Theory (Conditional Probability, Random Variables, Limit Theorems); Elements of Statistics (Estimators, Tests, Distributions, Correlation and Covariance, Linear Regression, Markov Chains); Probabilistic Linguistics.
(9536 views)