Descript 
1 online resource (VIII, 346 pages) 

text txt rdacontent 

computer c rdamedia 

online resource cr rdacarrier 
Series 
Progress in Probability ; 55 

Progress in probability ; 55

Note 
Preface  1. Measures on General Spaces and Inequalities  2. Gaussian Processes  3. Limit Theorems  4. Local Times  5. Large and Small Deviations  6. Density Estimation  7. Statistics via Empirical Process Theory 

The title High Dimensional Probability is used to describe the many tributaries of research on Gaussian processes and probability in Banach spaces that started in the early 1970s. Many of the problems that motivated researchers at that time were solved. But the powerful new tools created for their solution, such as randomization, isoperimetry, concentration of measure, moment and exponential inequalities, chaining, series representations, and decoupling turned out to be applicable to other important areas of probability. They led to significant advances in the study of empirical processes and other topics in theoretical statistics and to a new approach to the study of aspects of Lvy processes and Markov processes in general. The papers in this book reflect these broad categories. They are divided into seven sections:  measures on general spaces and inequalities  Gaussian processes  limit theorems  local times  large and small deviations  density estimation  statistics via empirical process theory 
Subject 
Mathematics


Distribution (Probability theory)


Statistics


Distribution (Probability theory) fast (OCoLC)fst00895600


Mathematics. fast (OCoLC)fst01012163


Statistics. fast (OCoLC)fst01132103


Electronic books

Alt Author 
Wellner, Jon A


Marcus, Michael B

