Density Sharpening: Principles and Applications to Discrete Data Analysis

• Tác giả: Subhadeep Mukhopadhyay
• Ngôn ngữ: eng
• Ký hiệu phân loại: 519.4 Applied numerical analysis
• Thông tin xuất bản: 2021
• Bộ sưu tập: Metadata
• ID: 167639

Tóm tắt

 Comment: Keywords: Density sharpening principle
  LP-Fourier analysis
  Explanatory goodness-of-fit
  Jaynes' dice problem
  Compressive chi-square
  Data-efficient learningThis article introduces a general statistical modeling principle called "Density Sharpening" and applies it to the analysis of discrete count data. The underlying foundation is based on a new theory of nonparametric approximation and smoothing methods for discrete distributions which play a useful role in explaining and uniting a large class of applied statistical methods. The proposed modeling framework is illustrated using several real applications, from seismology to healthcare to physics.