Bayesian Inference on Complicated Data

Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling method...

Ful tanımlama

Kaydedildi:
Detaylı Bibliyografya
Diğer Yazarlar: Tang, Niansheng (Editör)
Materyal Türü: Elektronik Kitap Bölümü
Dil:İngilizce
Baskı/Yayın Bilgisi: IntechOpen 2020
Konular:
Online Erişim:DOAB: download the publication
DOAB: description of the publication
Etiketler: Etiketle
Etiket eklenmemiş, İlk siz ekleyin!
Diğer Bilgiler
Özet:Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling methods, Bayesian estimation, and selection of the prior. It is structured around topics on the impact of the choice of the prior on Bayesian statistics, some advances on Bayesian sampling methods, and Bayesian inference for complicated data including breast cancer data, cloud-based healthcare data, gene network data, and longitudinal data. This volume is designed for statisticians, engineers, doctors, and machine learning researchers.
Fiziksel Özellikler:1 electronic resource (118 p.)
ISBN:intechopen.83214
9781838803865
9781838803858
9781839627040
Erişim:Open Access