Statistical Models of Shape

Learn statistics, inferential tests, supervised & unsupervised learning, data science careers PLUS Python & libraries

An up-to-date approach to understanding statistical inference
Statistical inference is finding useful applications in numerous fields, from sociology and econometrics to biostatistics. This volume enables professionals in these and related fields to master the concepts of statistical inference under inequality constraints and to apply the theory to problems in a variety of areas.

Gain practical experience in R for Data Analysis, Machine Learning and Artificial Intelligence. Become a Data Scientist.

Application of Morphometrics and Machine Learning to Genetic Syndrome Classification Using Anatomical Facial Points

This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities.

Holism Theory, Dynamical Modeling in Biological Frameworks, PBPK Design, ADME, Tasting the Pharmaceutical Development