{
"item_title" : "Bayesian Theory and Applications",
"item_author" : [" Paul Damien", "Petros Dellaportas", "Nicholas G. Polson "],
"item_description" : "The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics.",
"item_img_path" : "https://covers3.booksamillion.com/covers/bam/0/19/873/907/0198739079_b.jpg",
"price_data" : {
"retail_price" : "95.00", "online_price" : "95.00", "our_price" : "95.00", "club_price" : "95.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : ""
}
}
Bayesian Theory and Applications
Overview
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics.
This item is Non-Returnable
Customers Also Bought
- 1
Details
- ISBN-13: 9780198739074
- ISBN-10: 0198739079
- Publisher: OUP Oxford
- Publish Date: April 2015
- Dimensions: 9.21 x 6.14 x 1.44 inches
- Shipping Weight: 2.18 pounds
- Page Count: 718
Related Categories
You May Also Like...
- 1
