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{ "item_title" : "Statistical Inference Under Mixture Models", "item_author" : [" Jiahua Chen "], "item_description" : "This book puts its weight on theoretical issues related to finite mixture models. It shows that a good applicant, is an applicant who understands the issues behind each statistical method. This book is intended for applicants whose interests include some understanding of the procedures they are using, while they do not have to read the technical derivations.At the same time, many researchers find most theories and techniques necessary for the development of various statistical methods, without chasing after one set of research papers, after another. Even though the book emphasizes the theory, it provides accessible numerical tools for data analysis. Readers with strength in developing statistical software, may find it useful.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/81/996/139/9819961394_b.jpg", "price_data" : { "retail_price" : "169.99", "online_price" : "169.99", "our_price" : "169.99", "club_price" : "169.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Statistical Inference Under Mixture Models|Jiahua Chen

Statistical Inference Under Mixture Models

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Overview

This book puts its weight on theoretical issues related to finite mixture models. It shows that a good applicant, is an applicant who understands the issues behind each statistical method. This book is intended for applicants whose interests include some understanding of the procedures they are using, while they do not have to read the technical derivations.

At the same time, many researchers find most theories and techniques necessary for the development of various statistical methods, without chasing after one set of research papers, after another. Even though the book emphasizes the theory, it provides accessible numerical tools for data analysis. Readers with strength in developing statistical software, may find it useful.


This item is Non-Returnable

Details

  • ISBN-13: 9789819961399
  • ISBN-10: 9819961394
  • Publisher: Springer
  • Publish Date: November 2023
  • Dimensions: 9.21 x 6.14 x 0.81 inches
  • Shipping Weight: 1.45 pounds
  • Page Count: 327

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