Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods.
Helping you become a creative, logical thinker and skillful "e;simulator,"e; Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization.
Dieses Lehrbuch erklärt auf narrative und direkte Weise die wichtigen Zusammenhänge zwischen Data Science, Künstlicher Intelligenz und anderen Disziplinen und Domänen wie Datenschutz und Ethik, mit Fokus auf überwachtes Lernen (Supervised Learning).
Dieses Lehrbuch erklärt auf narrative und direkte Weise die wichtigen Zusammenhänge zwischen Data Science, Künstlicher Intelligenz und anderen Disziplinen und Domänen wie Datenschutz und Ethik, mit Fokus auf überwachtes Lernen (Supervised Learning).
Air Transportation Industry considers the influence of political, legal, economic, social, and technological factors on the developments in the industry.
A culmination of the author's many years of consulting and teaching, Design and Analysis of Experiments with SAS provides practical guidance on the computer analysis of experimental data.
This is the first book that focusses the attention on applying asymmetric multidimensional scaling (MDS) and describes how to apply it in a practical manner.
This is the first book that focusses the attention on applying asymmetric multidimensional scaling (MDS) and describes how to apply it in a practical manner.
Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences.
Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences.
Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data.
There are numerous advantages to using Bayesian methods in diagnostic medicine, which is why they are employed more and more today in clinical studies.
The book presents selected papers from NIELIT's International Conference on Communication, Electronics and Digital Technology (NICEDT-2024) held during 16-17 February 2024 in Guwahati, India.
Departing from traditional methodologies of teaching data analysis, this book presents a dual-track learning experience, with both Executive and Technical Tracks, designed to accommodate readers with various learning goals or skill levels.
Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB provides a concrete and intuitive yet rigorous introduction to modern linear optimization.
Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation.
The book presents selected papers from NIELIT's International Conference on Communication, Electronics and Digital Technology (NICEDT-2024) held during 16-17 February 2024 in Guwahati, India.
Handbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective.
This book delves into the realm of nonparametric estimations, offering insights into essential notions such as probability density, regression, Tsallis Entropy, Residual Tsallis Entropy, and intensity functions.
This book delves into the realm of nonparametric estimations, offering insights into essential notions such as probability density, regression, Tsallis Entropy, Residual Tsallis Entropy, and intensity functions.
Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free.
In recent decades, there has been enormous growth in biologics research and development, with the accompanying development of biological assays for emerging products.
This contributed volume offers practical implementation strategies for statistical learning and data science techniques, with fully peer-reviewed papers that embody insights and experiences gathered within the LISA 2020 Global Network.
Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors.
Mit diesem Buch gelingt dem Autor des bekannten Lehrwerkes Stochastik für Einsteiger auf geradezu spielerische Weise, den Leser mit zahlreichen überraschenden Zufallsphänomenen und Nicht-Standard-Grenzwertsätzen im Zusammenhang mit einfachen Irrfahrten und verwandten Themen zu fesseln.
Generalized Linear Models for Categorical and Continuous Limited Dependent Variables is designed for graduate students and researchers in the behavioral, social, health, and medical sciences.
Mit diesem Buch gelingt dem Autor des bekannten Lehrwerkes Stochastik für Einsteiger auf geradezu spielerische Weise, den Leser mit zahlreichen überraschenden Zufallsphänomenen und Nicht-Standard-Grenzwertsätzen im Zusammenhang mit einfachen Irrfahrten und verwandten Themen zu fesseln.
Introduction to Regression Methods for Public Health Using R teaches regression methods for continuous, binary, ordinal, and time-to-event outcomes using R as a tool.
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature.
Dieses einführende Lehrbuch zeigt den gesamten Weg von der elementaren Ermittlung von Wahrscheinlichkeiten bis zur Erstellung theoretischer Wahrscheinlichkeitsverteilungen auf.
Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics.