Anna Maria Paganoni – författare

This book was created with the goal of helping students transition from the theoretical and methodological concepts of statistical inference to their implementation on a computer.

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Questo testo nasce con l'obiettivo di aiutare lo studente nella transizione fra i concetti teorici e metodologici dell'inferenza statistica e la loro implementazione al computer. La prima parte del testo è infatti focalizzata principalmente su esercizi da risolvere con carta e penna, in modo da far applicare nozioni derivanti da lemmi e teoremi; mentre la seconda parte del testo è costituita da laboratori, in cui si propone sia l'implementazione manuale di algoritmi, sia l'apprendimento di built-in tools per un'analisi efficiente di dataset derivanti da problemi reali.Per ottimizzare la fruizione degli argomenti sviluppati, e per accompagnare il lettore nello studio, il testo è organizzato in capitoli, ciascuno dei quali composto, a sua volta, da una prima parte introduttiva, in cui vengono richiamate le basi teoriche dell'inferenza statistica, e da una seconda parte di esercizi, corredati di un esaustivo svolgimento su carta e, se opportuno, su software.Il testo è rivolto agli studenti dei corsi di laurea di primo livello di Statistica, Matematica, Ingegneria e per i corsi di secondo livello in Data Science.

This book collects several contributions, written both by statisticians and medical doctors, which focus on the identification of new diagnostic, therapeutic and organizational strategies in order to improve the occurrence of clinical outcomes for Acute Coronary Syndromes (ACS) patients.