Distributions and Composite Models for Size-Type Data

In the first part of this chapter, we present a sample of the best known and most used classical size distributions with their main statistical properties. In the second part, we introduce the concept of composite models and based on the size distributions of the first part, we describe those which already exist in the literature. In the last part of this chapter, we apply the described statistical size distributions and some of the composite models to two real data examples and compare their goodness-of-fit

Statistics Meets Sports : What We Can Learn from Sports Data

editorial reviewedThis book inscribes itself in the growing context of sports analytics and the combination of data science with sports medicine, which deeply impact the world of sports. Today, ever-more data are being collected and lead to ground-breaking and game-changing new insights. This book provides a solid understanding of these new trends in sports and offers the interested reader with a starting point from which to dive into this blossoming field

Marginal quantiles for stationary processes

We establish the asymptotic normality of marginal sample quantiles for S-mixing vector stationary processes. S-mixing is a recently introduced and widely applicable notion of dependence. Results of some Monte Carlo simulations are givenEstablecemos la normalidad asintótica de cuantiles muestrales marginales para un proceso vectorial estacionario S-mixing, una noción de dependencia recientemente propuesta y que cubre un amplio rango de procesos temporales. También mostramos resultados de una simulación de Monte Carl

Science meets Sports : when Statistics are more than Numbers

editorial reviewedThis book presents the field of sports statistics to two very distinct target audiences, namely academicians, in order to raise their interest in this growing field, and, on the other hand, sports fans, who, even without advanced mathematical knowledge, will be able to understand the data analysis and gain new insights into their favourite sports. The book thus offers a unique perspective on this attractive topic by combining sports analytics, data visualisation and advanced statistical procedures to extract new findings from sports data such as improved rankings or prediction methods. Bringing together insights from football, tennis, basketball, track and field, and baseball, the book will appeal to aficionados of any sport, and, thanks to its cutting-edge data analysis tools, will provide the reader with completely new insights into their favourite sport in an engaging and user-friendly way