This volume presents recent methodological developments in Applied/Computational Statistics. A wide range of topics is covered including Advances on Statistical Computing Environments, Classification and Clustering, Graphical Models and Bayes Nets, Computational Econometrics, Data Mining, Model Selection, Latent Class Detection, Multiple Testing Procedures, Random Search Algorithms, Robust Statistics and Signal Extraction and Filtering. Besides theoretical results, the book presents a variety of applications in fields such as time-series analysis, finance and insurance, micro-array analysis, astronomy and text analysis. Combining new methodological advances with a wide variety of real applications, this volume is specially valuable for researchers and practitioners, providing new analytical tools useful in theoretical research and daily practice in computational statistics and applied statistics.