Marginal and Functional Quantization of Stochastic Processes: 105 (Probability Theory and Stochastic Modelling, 105) - Image 1

£97.00

It has never been this cheap. We have no record of a lower price.

£97 today · cheaper than every other day in the last 3 months

Springer Marginal and Functional Quantization of Stochastic Processes: 105 (Probability Theory and Stochastic Modelling, 105)

Name: Marginal and Functional Quantization of Stochastic Processes: 105 (Probability Theory and Stochastic Modelling, 105)
Brand: Springer
Price: 97.0 GBP
Availability: InStock

Higher Education

Price Distribution

Price distribution over 80 days • 1 price levels

Days at Price

Price Analysis

Most common price: £97 (80 days, 100.0%)

Price range: £97 - £97

Price levels: 1 different prices over 80 days

Description

Vector Quantization, a pioneering discretization method based on nearest neighbor search, emerged in the 1950s primarily in signal processing, electrical engineering, and information theory. Later in the 1960s, it evolved into an automatic classification technique for generating prototypes of extensive datasets. In modern terms, it can be recognized as a seminal contribution to unsupervised learning through the k-means clustering algorithm in data science. In contrast, Functional Quantization, a more recent area of study dating back to the early 2000s, focuses on the quantization of continuous-time stochastic processes viewed as random vectors in Banach function spaces. This book distinguishes itself by delving into the quantization of random vectors with values in a Banach space―a unique feature of its content. Its main objectives are twofold: first, to offer a comprehensive and cohesive overview of the latest developments as well as several new results in optimal quantization theory, spanning both finite and infinite dimensions, building upon the advancements detailed in Graf and Luschgy's Lecture Notes volume. Secondly, it serves to demonstrate how optimal quantization can be employed as a space discretization method within probability theory and numerical probability, particularly in fields like quantitative finance. The main applications to numerical probability are the controlled approximation of regular and conditional expectations by quantization-based cubature formulas, with applications to time-space discretization of Markov processes, typically Brownian diffusions, by quantization trees. While primarily catering to mathematicians specializing in probability theory and numerical probability, this monograph also holds relevance for data scientists, electrical engineers involved in data transmission, and professionals in economics and logistics who are intrigued by optimal allocation problems.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3031454634
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Education > Higher Education
Domain: Amazon UK
Release Date: 07 December 2023
Listed Since: 31 August 2023

Barcode

No barcode data available

It has never been this cheap. We have no record of a lower price.

Springer Marginal and Functional Quantization of Stochastic Processes: 105 (Probability Theory and Stochastic Modelling, 105)

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

High Dimensional Probability II - Birkhauser Progress Series

Measure, Probability and Functional Analysis (Universitext)

Probability in Banach Spaces 9: 35 - Progress in Probability

Simulation of Stochastic Processes with Given Accuracy and Reliability

Foundations of Quantitative Finance Book IV: Distribution Functions and Expectations (Chapman and Hall/CRC Financial Mathematics Series)

Hilbert And Banach Space-Valued Stochastic Processes: 13 (Series On Multivariate Analysis)

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference (Chapman & Hall/CRC Texts in Statistical Science)

Foundations of Quantitative Finance Book V - Measure and Integration Theory

Foundations of Quantitative Finance: Book V General Measure and Integration Theory (Chapman and Hall/CRC Financial Mathematics Series)

High Dimensional Probability VIII: The Oaxaca Volume: 74 (Progress in Probability, 74)

High Dimensional Probability VIII: The Oaxaca Volume - Birkhauser

Foundations of Quantitative Finance Book VI - Densities & Limit Theorems

Markov Chains: Theory and Applications (Iste)

Introduction to Probability with Mathematica (Textbooks in Mathematics)

Foundations of Quantitative Finance Book II: Probability Spaces and Random Variables (Chapman and Hall/CRC Financial Mathematics Series)

One-Dimensional Empirical Measures, Order Statistics, and Kantorovich Transport Distances (Memoirs of the American Mathematical Society)

On the Estimation of Multiple Random Integrals and U-Statistics: 2079 (Lecture Notes in Mathematics, 2079)

Quantitative Finance: A Simulation-Based Introduction Using Excel

Foundations of Quantitative Finance, Book I: Measure Spaces and Measurable Functions: 1 (Chapman and Hall/CRC Financial Mathematics Series)

Oxford University Press Probability and Random Processes 4th Ed

Real Analysis and Probability (Cambridge Studies in Advanced Mathematics): 74 (Cambridge Studies in Advanced Mathematics, Series Number 74)

Applied Probability and Stochastic Processes: 19 (International Series in Operations Research & Management Science, 19)

Introduction to Probability with Mathematica - Textbook

Springer Measure Theory, Probability, and Stochastic Processes

It has never been this cheap. We have no record of a lower price.

Springer Marginal and Functional Quantization of Stochastic Processes: 105 (Probability Theory and Stochastic Modelling, 105)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

High Dimensional Probability II - Birkhauser Progress Series

Measure, Probability and Functional Analysis (Universitext)

Probability in Banach Spaces 9: 35 - Progress in Probability

Simulation of Stochastic Processes with Given Accuracy and Reliability

Foundations of Quantitative Finance Book IV: Distribution Functions and Expectations (Chapman and Hall/CRC Financial Mathematics Series)

Hilbert And Banach Space-Valued Stochastic Processes: 13 (Series On Multivariate Analysis)

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference (Chapman & Hall/CRC Texts in Statistical Science)

Foundations of Quantitative Finance Book V - Measure and Integration Theory

Foundations of Quantitative Finance: Book V General Measure and Integration Theory (Chapman and Hall/CRC Financial Mathematics Series)

High Dimensional Probability VIII: The Oaxaca Volume: 74 (Progress in Probability, 74)

High Dimensional Probability VIII: The Oaxaca Volume - Birkhauser

Foundations of Quantitative Finance Book VI - Densities & Limit Theorems

Markov Chains: Theory and Applications (Iste)

Introduction to Probability with Mathematica (Textbooks in Mathematics)

Foundations of Quantitative Finance Book II: Probability Spaces and Random Variables (Chapman and Hall/CRC Financial Mathematics Series)

One-Dimensional Empirical Measures, Order Statistics, and Kantorovich Transport Distances (Memoirs of the American Mathematical Society)

On the Estimation of Multiple Random Integrals and U-Statistics: 2079 (Lecture Notes in Mathematics, 2079)

Quantitative Finance: A Simulation-Based Introduction Using Excel

Foundations of Quantitative Finance, Book I: Measure Spaces and Measurable Functions: 1 (Chapman and Hall/CRC Financial Mathematics Series)

Oxford University Press Probability and Random Processes 4th Ed

Real Analysis and Probability (Cambridge Studies in Advanced Mathematics): 74 (Cambridge Studies in Advanced Mathematics, Series Number 74)

Applied Probability and Stochastic Processes: 19 (International Series in Operations Research & Management Science, 19)

Introduction to Probability with Mathematica - Textbook

Springer Measure Theory, Probability, and Stochastic Processes