menu
{ "item_title" : "Linear and Graphical Models", "item_author" : [" Heidi H. Andersen", "Malene Hojbjerre", "Dorte Sorensen "], "item_description" : "In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/0/38/794/521/0387945210_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Linear and Graphical Models|Heidi H. Andersen

Linear and Graphical Models : For the Multivariate Complex Normal Distribution

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

In the last decade, graphical models have become increasingly popular as a statistical tool. This book is the first which provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and parameter estimation and hypothesis testing for these models. After introducing undirected graphs, they then develop the theory of complex normal graphical models including the maximum likelihood estimation of the concentration matrix and hypothesis testing of conditional independence.

This item is Non-Returnable

Details

  • ISBN-13: 9780387945217
  • ISBN-10: 0387945210
  • Publisher: Springer
  • Publish Date: May 1995
  • Dimensions: 9.21 x 6.14 x 0.42 inches
  • Shipping Weight: 0.63 pounds
  • Page Count: 183

Related Categories

You May Also Like...

    1

BAM Customer Reviews