Robust methods in biostatistics

Batch effects and noise in microarray experiments sources and solutions

Bayesian analysis for the social sciences

Robust methods in biostatistics

Decision theory principles and approaches

Smooth tests of goodness of fit using R

Bayesian networks an introduction

Robust statistics

Stage-wise adaptive designs

Statistical tolerance regions theory, applications, and computation

ROC curves for continuous data

Hidden Markov models for time series : an introduction using R

Optimal Stopping Rules

Statistical advances in the biomedical sciences clinical trials, epidemiology, survival analysis, and bioinformatics

Modern applied U-statistics

Design and analysis of experiments. Volume 1, Introduction to experimental design

A matrix handbook for statisticians

Simulation and the monte carlo method

Applied multiway data analysis

Applied survival analysis regression modeling of time-to-event data

Linear models the theory and application of analysis of variance

Multivariable model-building a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables

Stochastic Control of Hereditary Systems and Applications

Statistical rules of thumb

Statistical meta-analysis with applications

Meta analysis a guide to calibrating and combining statistical evidence

The EM algorithm and extensions

Loss models from data to decisions

Missing data in longitudinal studies : strategies for Bayesian modeling and sensitivity analysis

Structural equation modeling a Bayesian approach

Variations on split plot and split block experiment designs

The construction of optimal stated choice experiments theory and methods

Nonparametric statistics with applications to science and engineering

Management of data in clinical trials

Periodically correlated random sequences spectral theory and practice

Approximate dynamic programming solving the curses of dimensionality

Nonparametric analysis of univariate heavy-tailed data research and practice

Nonparametric statistics with applications to science and engineering

Stochastic Simulation: Algorithms and Analysis

Bayes linear statistics theory and methods

Response surfaces, mixtures, and ridge analyses

Modern experimental design

Long-memory time series theory and methods

Nonlinear time series : semiparametric and nonparametric methods

Statistical methods for spatio-temporal systems

Nonparametric regression methods for longitudinal data analysis

Robust statistics theory and methods

Longitudinal data analysis

Visual statistics seeing data with dynamic interactive graphics

Theory of preliminary test and Stein-type estimation with applications

Controlled Markov Processes and Viscosity Solutions

Modes of parametric statistical inference

Regression analysis by example

The theory of response-adaptive randomization in clinical trials

Reliability and risk a Bayesian perspective

Latent curve models a structural equation perspective

Introduction to nonparametric regression

Uncertainty analysis with high dimensional dependence modelling

Introductory stochastic analysis for finance and insurance

Bayesian statistical modelling

Operational risk modeling analytics

Linear model theory univariate, multivariate, and mixed models

Generalized linear models with random effects : unified analysis via h-likelihood

Constrained statistical inference inequality, order, and shape restrictions

Average—Cost Control of Stochastic Manufacturing Systems

Martingale Methods in Financial Modelling

Clinical trials a methodologic perspective

Contemporary Bayesian econometrics and statistics

Image processing and jump regression analysis

Recent advances in quantitative methods for cancer and human health risk assessment

Applied linear regression

Bayesian models for categorical data

Gaussian Markov random fields : theory and applications

Exploration and analysis of DNA microarray and protein array data

Applied spatial statistics for public health data