eBook - ePub
Mixture Modelling for Medical and Health Sciences
This is a test
- 300 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Mixture Modelling for Medical and Health Sciences
Book details
Table of contents
Citations
About This Book
Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in
Frequently asked questions
At the moment all of our mobile-responsive ePub books are available to download via the app. Most of our PDFs are also available to download and we're working on making the final remaining ones downloadable now. Learn more here.
Both plans give you full access to the library and all of Perlegoâs features. The only differences are the price and subscription period: With the annual plan youâll save around 30% compared to 12 months on the monthly plan.
We are an online textbook subscription service, where you can get access to an entire online library for less than the price of a single book per month. With over 1 million books across 1000+ topics, weâve got you covered! Learn more here.
Look out for the read-aloud symbol on your next book to see if you can listen to it. The read-aloud tool reads text aloud for you, highlighting the text as it is being read. You can pause it, speed it up and slow it down. Learn more here.
Yes, you can access Mixture Modelling for Medical and Health Sciences by Shu Kay Ng, Liming Xiang, Kelvin Kai Wing Yau in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Dedication
- Contents
- Preface
- 1. Introduction
- 2. Mixture of Normal Distributions for Continuous Data
- 3. Mixture of Gamma Distributions for Continuous Non-Normal Data
- 4. Mixture of Generalized Linear Models for Count or Categorical Data
- 5. Mixture Models for Survival Data
- 6. Advanced Mixture Modelling with Random-Effects Components
- 7. Advanced Mixture Models for Multilevel or Repeated-Measured Data
- 8. Advanced Mixture Models for Correlated Multivariate Continuous Data
- 9. Miscellaneous: Handling of Missing Data
- 10. Miscellaneous: Cluster Analysis of âBig Dataâ Using Mixture Models
- Bibliography
- Index