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This book is a selection of peer-reviewed contributions presented at the third Bayesian Young Statisticians Meeting, BAYSM 2016, Florence, Italy, June 19-21. The meeting provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and postdocs dealing with Bayesian statistics to connect with the Bayesian community at large, to exchange ideas, and to network with others working in the same field. The contributions develop and apply Bayesian methods in a variety of fields, ranging from the traditional (e.g., biostatistics and reliability) to the most innovative ones (e.g., big data and networks).

Statistics. --- Statistical Theory and Methods. --- Statistics and Computing/Statistics Programs. --- Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Bayesian statistical decision theory --- Neural networks (Computer science) --- Mathematical statistics. --- Statistics for Social Sciences, Humanities, Law. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics .

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The volume includes a collection of peer-reviewed contributions from among those presented at the main conference organized yearly by the Mexican Statistical Association (AME) and every two years by a Latin-American Confederation of Statistical Societies. For the 2018 edition, particular attention was placed on the analysis of highly complex or large data sets, which have come to be known as “big data”. Statistical research in Latin America is prolific and research networks span within and outside the region. The goal of this volume is to provide access to selected works from Latin-American collaborators and their research networks to a wider audience. New methodological advances, motivated in part by the challenges of a data-driven world and the Latin American context, will be of interest to academics and practitioners around the world. .

Markov processes. --- Statistics . --- Big data. --- Markov model. --- Applied Statistics. --- Bayesian Inference. --- Big Data/Analytics. --- Big Data. --- Data sets, Large --- Large data sets --- Data sets --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Analysis, Markov --- Chains, Markov --- Markoff processes --- Markov analysis --- Markov chains --- Markov models --- Models, Markov --- Processes, Markov --- Stochastic processes --- Mathematical statistics --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistics. --- Quantitative research. --- Markov Process. --- Data Analysis and Big Data. --- Data analysis (Quantitative research) --- Exploratory data analysis (Quantitative research) --- Quantitative analysis (Research) --- Quantitative methods (Research) --- Research

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The volume includes a collection of peer-reviewed contributions from among those presented at the FNE, the main conference organized every two years by the Mexican Statistical Society (AME), and the 2020 AME Virtual Meeting. Statistical research in Latin America is prolific and research networks span both within and outside the region. As much of the work is typically carried out and published in Spanish, a large portion of the interested public is denied access to interesting findings, and the goal of this volume is therefore to provide access to selected works from Mexican collaborators and their international research networks to a wider audience. It may be especially attractive to academics interested in the latest methodological advances, while professionals from other disciplines may also find value in these new tools for data analysis. In 2021, the conference broadly focused on the interdisciplinary aspects of Statistics.

Statistical science --- Operational research. Game theory --- Probability theory --- waarschijnlijkheidstheorie --- stochastische analyse --- statistiek --- kansrekening --- statistisch onderzoek