Applied Math & Statistics

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Applied math and statistics research is crucial in today's increasingly complex and data-driven world. Developments in these fields provide the necessary models, tools, and insights to solve complex real-world problems, make more accurate predictions, and optimize systems, leading to improved decision-making, innovation, and societal impact.

Featured Journals & Articles

Journal of Statistical Theory and Practice Article: Multivariate Skew Normal-Based Stochastic Frontier Models	Extremes Article: Environmental contours as Voronoi cells	Statistical Inference for Stochastic Processes Article: Weak-convergence of empirical conditional processes and conditional U-processes involving functional mixing data
Water Waves Article: Numerical Simulations of Waves Breaking over a Rectangular Submerged Reef Consisting of a Double Step: Analogies with massive Natural Wave Breaking over Abrupt Bathymetries	GEM - International Journal on Geomathematics Article: Non-hydrostatic unified model of the ocean with application to ice/ocean interaction modeling	METRON Article: Gender inequalities at work in Southern Europe
Journal of Agricultural, Biological and Environmental Statistics Article: Spatial Modeling of Day-Within-Year Temperature Time Series: An Examination of Daily Maximum Temperatures in Aragón, Spain	Computational Statistics Article: Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features	Statistical Papers Article: Subdata selection algorithm for linear model discrimination

Featured Collections & Special Issues

Advances in Stochastics and Statistics

Advances in Actuarial Science and Quantitative Finance

Network Psychometrics in Action

Statistics in Sports

Featured Books & Chapters

Information Geometry and Its Applications Chapter: Machine Learning	What Mathematics Can Do for You Chapter: A Dialogue Between a Mathematician and Toyota’s Chairman: Think, Think, and Think Again	Predicting Pandemics in a Globally Connected World Chapter: Understanding COVID-19 Epidemics: A Multi-Scale Modeling Approach
Open Problems in Optimization and Data Analysis Chapter: Supply and Demand Selection Problems in Supply Chain Planning	Mesh Generation and Adaptation Chapter: Mixed Order Mesh Curving	Modeling Reality with Mathematics Chapter: Epidemics: The Mathematics of Contagion
Fundamentals of High-Dimensional Statistics Chapter: Graphical Models	Epidemics Chapter: Times Series Analysis	Geostatistics for Compositional Data with R Chapter: Geostatistical Estimation

Featured Book Series

Series cover: SEMA SIMAI Springer Series

Series cover: SpringerBriefs on PDEs and Data Science

Series cover: Springer Series in Statistics

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