Handbook of Statistics Vol.43 Principles and Methods for Data Science [推广有奖]

Handbook of Statistics Volume 43：Principles and Methods for Data Science

Edited by Arni S.R. Srinivasa Rao, C.R. Rao
Volume 43, 2020

Chapter 1 - Markov chain Monte Carlo methods: Theory and practice
David A. Spade

Chapter 2 - An information and statistical analysis pipeline for microbial metagenomic sequencing data
Shinji Nakaoka, Keisuke H. Ota

Chapter 3 - Machine learning algorithms, applications, and practices in data science
Kalidas Yeturu

Chapter 4 - Bayesian model selection for high-dimensional data
Naveen Naidu Narisetty

Chapter 5 - Competing risks: Aims and methods
Ronald B. Geskus

Chapter 6 - High-dimensional statistical inference: Theoretical development to data analytics
Deepak Nag Ayyala

Chapter 7 - Big data challenges in genomics
Hongyan Xu

Chapter 8 - Analysis of microarray gene expression data using information theory and stochastic algorithm
Narayan Behera

Chapter 9 - Human life expectancy is computed from an incomplete sets of data: Modeling and analysis
Arni S.R. Srinivasa Rao, James R. Carey

Chapter 10 - Support vector machines: A robust prediction method with applications in bioinformatics
Arnout Van Messem

Vol.43.pdf (12.98 MB)

2021-12-21 10:00:00 上传

Handbook of Statistics Vol.43