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  • Sách/Book

  • Theory of statistical inference

    • Authors: Anthony Almudevar. (2021)

  • "The purpose of applying mathematical theory to the theory of statistical inference is to make it simpler and more elegant. Theory of Statistical Inference is concerned with the development of a type of optimization theory which can be used to inform the choice of statistical methodology. Of course, this would be pointless without reference to such methods. We are simply noting that they are included in support of the larger goal. This book distinguishes itself from other graduate textbooks because it is written from the point of view that some degree of understanding of measure theory, as well as other branches of mathematics, which include topology, group theory and complex analysis, should be a part of the canon of statistical inference
  • Sách/Book

  • Introduction to Mathematical Statistics

    • Authors: Robert V. Hogg (2006)

  • This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics. Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book. For a more complete understanding of mathematical statistics.
  • Sách/Book

  • Data Structures and Algorithms Made Easy in Java

    • Authors: Narasimha Karumanchi (2011)

  • A handy guide of sorts for any computer Science professional, data structures and algorithms made easy in Java: data structure and algorithmic puzzles is a solution Bank for various complex problems related to data structures and algorithms.
  • Sách/Book

  • All of nonparametric statistics

    • Authors: Larry Wasserman (2006)

  • This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory
  • Sách/Book

  • CMSC 451 Design and Analysis of Computer Algorithms

    • Authors: David M. Mount (2011)

  • The first will be a short review of some preliminary material, including asymptotics, summations, and recurrences and sorting. We will then discuss approaches to designing optimization algorithms, including dynamic programming and greedy algorithms.
  • Sách/Book

  • Statistical inference

    • Authors: George Casella (1990)

  • This text provides information on topics such as ancillarity, invariance, Bayesian methods, pivots, Stein estimation, errors in variables and inequalities. The authors discuss both theoretical statistics and the practical applications of the theoretical developments. Many ideas are introduced in the context of data analysis rather than pure mathematics
  • Sách/Book

  • Thống kê toán học

    • Authors: Nguyễn Văn Hữu (2004)

  • Cung cấp kiến thức cơ bản về thống kê mô tả, ước lượng tham số, kiểm định giả thuyết, kiểm định phù hợp, phân tích phương sai, kiểm định phi tham số
  • Sách/Book

  • Quantum Computing: An Applied Approach

    • Authors: Jack D. Hidary (2019)

  • This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data.
  • Sách/Book

  • Bài giảng nhi khoa - Tập 2

    • Authors: Lê Nam Trà (2006)

  • Một số kiến thức về nhi khoa như hệ tuần hoàn, huyết học, tiết niệu, nội tiết - chuyển hoá và thần kinh