Biostatistics.- Discriminant Analysis Based on Continuous and Discrete Variables.- Longitudinal Data Analysis with Linear Regression.- A Kernel Method Used for the Analysis of Replicated Micro-array Experiments.- Kernel Estimates of Hazard Functions for Biomedical Data Sets.- Partially Linear Models.- Analysis of Contingency Tables.- Identifying Coexpressed Genes.- Bootstrap Methods for Testing Interactions in GAMs.- Survival Trees.- A Semiparametric Approach to Estimate Reference Curves for Biophysical Properties of the Skin.- Survival Analysis.- Related Sciences.- Ozone Pollution Forecasting Using Conditional Mean and Conditional Quantiles with Functional Covariates.- Nonparametric Functional Methods: New Tools for Chemometric Analysis.- Variable Selection in Principal Component Analysis.- Spatial Statistics.- Functional Data Analysis.- Analysis of Failure Time with Microearthquakes Applications.- Polychotomous Regression: Application to Landcover Prediction.- The Application of Fuzzy Clustering to Satellite Images Data.

Biostatistics is one of the scientific fields for which the recent developments have been extremely important. It is also strongly related to other scientific disciplines involving statistical methodology. The aim of this book is to cover a wide scope of recent statistical methods used by scientists in biostatistics as well as in other related fields such as chemometrics, environmetrics and geophysics. The contributed papers, coming from internationally recognized researchers, present various statistical methodologies together with a selected scope of their main mathematical properties and their applications in real case studies, making this book of interest to a wide audience among researchers and students in statistics. Each method is accompanied with interactive and automatic Xplore routines, available on-line, allowing people to reproduce the proposed examples or to apply the methods to their own real datasets. Thus this book will also be of special interest to practitioners.