null
Loading... Please wait...
FREE SHIPPING on All Unbranded Items LEARN MORE
Print This Page

Markov Chain Monte Carlo (Stochastic Simulation for Bayesian Inference)

List Price: $79.99
SKU:
9781041004004
Quantity:
Minimum Purchase
25 unit(s)
Expected release date is Jul 29th 2026
  • Availability: Confirm prior to ordering
  • Branding: minimum 50 pieces (add’l costs below)
  • Check Freight Rates (branded products only)

Branding Options (v), Availability & Lead Times

  • 1-Color Imprint: $2.00 ea.
  • Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
  • Belly-Band Wrap: $2.50 ea. (full-color printed)
  • Set-Up Charge: $45 per decoration
FULL DETAILS
  • Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
  • Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
  • Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
  • RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
  • Product Details

    Author:
    Dani Gamerman, Hedibert F. Lopes, Flávio Bambirra Gonçalves
    Format:
    Paperback
    Pages:
    360
    Publisher:
    CRC Press (July 29, 2026)
    Imprint:
    Chapman and Hall/CRC
    Release Date:
    July 29, 2026
    Language:
    English
    Audience:
    College/higher education
    ISBN-13:
    9781041004004
    Weight:
    16oz
    Dimensions:
    7" x 10"
    File:
    TAYLORFRANCIS-TayFran_260210052413731-20260210.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $79.99
    Country of Origin:
    United States
    Pub Discount:
    30
    Series:
    Chapman & Hall/CRC Texts in Statistical Science
    As low as:
    $75.99
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
  • Overview

    Marking a pivotal moment in the evolution of Bayesian inference, the third edition of this seminal textbook on Markov Chain Monte Carlo (MCMC) methods reflects the profound transformations in both the field of Statistics and the broader landscape of data science over the past two decades.