Preface

Nature evolves mainly in a statistical way. Different strategies, formulas, and conformations are continuously confronted in the natural processes. Some of them are selected and then the evolution continues with a new loop of confrontation for the next generation of phenomena and living beings. Failings are corrected without a previous program or design. The new options generated by different statistical and random scenarios lead to solutions for surviving the present conditions. This is the general panorama for all scrutiny levels of the life cycles. Over three parts, this book examines different statistical questions and techniques in the context of machine learning and clustering methods, the frailty models used in survival analysis, and other studies of statistics applied to diverse problems.

The first section of the book presents different techniques and methods applied to clustering and machine learning. In Chapter 1, Dai et al. propose a framework for a clustering procedure based on functional rankings or depth. In Chapter 2, Fernandes et al. discuss the reasons to use dummy variables in cluster analysis. In Chapter 3, Yue is concerned with sparse boosting-based machine learning methods in different high-dimensional problems. Chapter 4 by Kuroda presents how to accelerate the convergence of the EM algorithm and apply it to mixture model estimation.

The second section of the book addresses the question of frailty models usually applied to survival analysis. In Chapter 5, Zhong et al. propose a generalized shared frailty model and develop a survival function to model the dependency among the baseline survival functions. Chapter 6 by Pandey and Lalpawimawha introduces a new frailty model with exponential power and generalized Rayleigh as baseline distributions.

The last section of the book presents the use of computational statistics in different contexts and problems. In Chapter 7, Yildiz depicts the use of the network meta-analysis tool through an example from diabetes. In Chapter 8, Ghosh constructs an N-ary variance balance design by using different techniques. In Chapter 9, Kumar proposes an improved randomized response model for the simultaneous estimation of population means of two quantitative sensitive variables. In Chapter 10, Ünvan and Nahmatli examine the causal relationship between imports, exports, and Exim bank loans in the Turkish economy.

As the editor of this book, I would like to thank all the contributing authors and reviewers. I am also grateful to the staff at IntechOpen, particularly Author Service Manager Ms. Romina Rovan. At this time when the omicron variant of the coronavirus continues to plague the world, I want to dedicate this book to all the teachers I had in the CP El Castelar of Villafranca and the IES Marqués de Villena of Marcilla. Finally, I acknowledge the support of my family, friends, and advisors.

> **Ricardo López-Ruiz** University of Zaragoza, Spain

Section 1
