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.
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.
A Cohesive Approach to Regression ModelsConfidence Intervals in Generalized Regression Models introduces a unified representation-the generalized regression model (GRM)-of various types of regression models.
From ancient soothsayers and astrologists to today's pollsters and economists, probability theory has long been used to predict the future on the basis of past and present knowledge.
Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds.
Statistical distributions are one of the most important applied mathematical tools across a wide spectrum of disciplines, including engineering, biological sciences, and health and social sciences.
In response to unanswered difficulties in the generalized case of conditional expectation and to treat the topic in a well-deservedly thorough manner, M.
The application of engineering principles in divergent fields such as management science and communications as well as the advancement of several approaches in theory and computation have led to growing interest in queueing models, creating the need for a comprehensive text.
Although there are many Bayesian statistical books that focus on biostatistics and economics, there are few that address the problems faced by engineers.
Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications.
Simple, clear, and to the point, Probability and Statistics Applications for Environmental Science delineates the fundamentals of statistics, imparting a basic understanding of the theory and mechanics of the calculations.
Electromagnetic complex media are artificial materials that affect the propagation of electromagnetic waves in surprising ways not usually seen in nature.
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.
Stochastic geometry, based on current developments in geometry, probability and measure theory, makes possible modeling of two- and three-dimensional random objects with interactions as they appear in the microstructure of materials, biological tissues, macroscopically in soil, geological sediments etc.
Since the 18th century, one phenomenon, the proportion of the sexes at birth among human beings, has contributed to various developments such as the calculus of probabilities, administrative statistics, the moral and social sciences, the statistics of variability, post-Darwinian biology and Durkheimian sociology.
There is currently ever pressing need to provide a critical assessment of the current knowledge and indicate new challenges which are brought by the present time in fighting the man-made and natural hazards in transient analysis of structures.
While the primary purpose of the book is a celebration of John's contributions to the field of measurement, a second and related purpose is to provide a useful resource.
Stochastic analysis is a field of mathematical research having numerous interactions with other domains of mathematics such as partial differential equations, riemannian path spaces, dynamical systems, optimization.
This book is the first to comprehensively explore elasticity imaging and examines recent, important developments in asymptotic imaging, modeling, and analysis of deterministic and stochastic elastic wave propagation phenomena.
Mathematical statistics typically represents one of the most difficult challenges in statistics, particularly for those with more applied, rather than mathematical, interests and backgrounds.
From ancient soothsayers and astrologists to today's pollsters and economists, probability theory has long been used to predict the future on the basis of past and present knowledge.
Financial Modelling in Commodity Markets provides a basic and self-contained introduction to the ideas underpinning financial modelling of products in commodity markets.
Financial Modelling in Commodity Markets provides a basic and self-contained introduction to the ideas underpinning financial modelling of products in commodity markets.
This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis.
Engineers are expected to design structures and machines that can operate in challenging and volatile environments, while allowing for variation in materials and noise in measurements and signals.
