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The purpose of this book is to thoroughly prepare diverse areas of researchers in quantification theory. Unlike many books on quantification theory, the current book places more emphasis on preliminary requisites of mathematical tools than on details of quantification theory.
This book is designed to provide a comprehensive introduction to R programming for data analysis, manipulation and presentation.
This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). The book also reports advances on classic but... Læs mere
This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R.
This book includes a wide selection of papers presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS2021), held virtually on 21-25 June 2021.
This book helps readers easily learn basic model checking by presenting examples, exercises and case studies. For example, biological cells,... Læs mere
This innovative textbook presents material for a course on industrial statistics that incorporates Python as a pedagogical and practical resource.
This book provides the essential theoretical tools for stochastic modeling. The authors address the most used models in applications such as Markov chains with discrete-time parameters, hidden Markov chains, Poisson processes, and birth and death processes.
Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics, 2023, the third volume of ten from the Conference brings together contributions to this important area of research and engineering.
This open access book offers a comprehensive exploration of the digital innovations that have emerged in recent years for the circular built environment.