In today's manufacturing environment, managing inventories is one of the basic concerns of enterprises dealing with materials according to their activities.
Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers.
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology.
Interactively Run Simulations and Experiment with Real or Simulated Data to Make Sequential Analysis Come AliveTaking an accessible, nonmathematical approach to this field, Sequential Methods and Their Applications illustrates the efficiency of sequential methodologies when dealing with contemporary statistical challenges in many areas.
This book of peer-reviewed short papers on methodological and applied statistics and demography is the fourth of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024), held in Bari, Italy, on June 17-20, 2024.
Magnetic energy release plays an important role in a wide variety of cosmic objects such as the Sun, stellar coronae, stellar and galactic accretion disks and pulsars.
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.
When two of us (Jifi Kolbek, Miroslav Sriltek) were working in North Korea on the Czech- Slovak field expeditions of the early 1990s, we did not think initially of comparing our results with the vegetation of surrounding areas or of writing a book.
Spatial predictive modeling (SPM) is an emerging discipline in applied sciences, playing a key role in the generation of spatial predictions in various disciplines.
This book offers a design research methodology intended to improve the quality of design research- its academic credibility, industrial significance and societal contribution by enabling more thorough, efficient and effective procedures.
This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications.
This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning.
Michael Harrison returns to an important topic in stochastic process theory, and illustrates its many influential applications in business and economics.
Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on optimization techniques used to solve problems with adaptive, dynamic, and stochastic features.
This book is written for statisticians, data analysts, programmers, researchers, professionals, and general consumers on how to perform different types of statistical data analysis for research purposes using R object-oriented programming language and RStudio integrated development environment (IDE).
This book provides detailed empirical analysis of countries in Asia to examine various dynamic models that incorporate the impact of technology and innovations on the industry evolution and overall economic growth.
This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties.
Game-theoretic probability and finance come of age Glenn Shafer and Vladimir Vovk s Probability and Finance, published in 2001, showed that perfect-information games can be used to define mathematical probability.
This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis.
An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and
The aim of this book is to show that the probabilistic formalisms of classical statistical mechanics and quantum mechanics can be unified on the basis of a general contextual probabilistic model.
