Wiley Series in Computational Statistics

Symbolic Data Analysis

Conceptual Statistics and Data Mining

Bayesian Modeling Using WinBUGS

Statistical and Machine Learning Approaches for Network Analysis

Multivariate Nonparametric Regression and Visualization

With R and Applications to Finance

Computational Statistics

Data Mining and Statistics for Decision Making

Large-Scale Inverse Problems and Quantification of Uncertainty

Clustering Methodology for Symbolic Data

Graphical Models

Representations for Learning, Reasoning and Data Mining

Advanced Markov Chain Monte Carlo Methods

Learning from Past Samples

Statistical Approach to Neural Networks for Pattern Recognition

Introduction to Statistical Computing

A Simulation-based Approach

Probabilistic Method

Response Surfaces, Mixtures, and Ridge Analyses

Modelling Under Risk and Uncertainty

An Introduction to Statistical, Phenomenological and Computational Methods

Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment

Bayesian Methods for Nonlinear Classification and Regression

Multivariate Density Estimation

Theory, Practice, and Visualization

Sensitivity Analysis in Linear Regression

Computational Molecular Biology

An Introduction

Computational Molecular Biology

An Introduction

Mathematical and Computational Modeling

With Applications in Natural and Social Sciences, Engineering, and the Arts

Geometry Driven Statistics

Digital Patient

Advancing Healthcare, Research, and Education

Fundamental Statistical Inference

A Computational Approach

Problems and Solutions in Mathematical Finance, Volume 1

Stochastic Calculus

Kernel Smoothing

Principles, Methods and Applications