Monty's Functional Doctrine


Book Description

Using a combination of new perspectives and new evidence, this book presents a reinterpretation of how 21st Army Group produced a successful combined arms doctrine by late 1944 and implemented this in early 1945. Historians, professional military personnel and those interested in military history should read this book, which contributes to the radical reappraisal of Great Britain’s fighting forces in the last years of the Second World War, with an exploration of the reasons why 21st Army Group was able in 1944–45 to integrate the operations of its armor and infantry. The key to understanding how the outcome developed lies in understanding the ways in which the two processes of fighting and the creation of doctrine interrelated. This requires both a conventional focus on command and a cross-level study of Montgomery and a significant group of commanders. The issue of whether or not this integration of combat arms (a guide to operational fighting capability) had any basis in a common doctrine is an important one. Alongside this stands the new light this work throws on how such doctrine was created. A third interrelated contribution is in answering how Montgomery commanded, and whether and to what extent, doctrine was imposed or generated. Further it investigates how a group of ‘effervescent’ commanders interrelated, and what the impact of those interrelationships was in the formulation of a workable doctrine. The book makes an original contribution to the debate on Montgomery’s command style in Northwest Europe and its consequences, and integrates this with tracking down and disentangling the roots of his ideas, and his role in the creation of doctrine for the British Army’s final push against the Germans. In particular the author is able to do something that has defeated previous authors: to explain how doctrine was evolved and, especially who was responsible for providing the crucial first drafts, and the role Montgomery played in revising, codifying and disseminating it.




Tank Warfare


Book Description

“An “insightful and informative” overview of the role of tanks in combat from the First World War to the present day (Dennis Showalter, author of Armor and Blood). The story of the battlefield in the twentieth century was dominated by a handful of developments. Foremost of these was the introduction and refinement of tanks. In Tank Warfare, Jeremy Black, a recipient of the Samuel Eliot Morison Prize from the Society for Military History, offers a comprehensive global account of the history of tanks and armored warfare in the twentieth and twenty-first centuries. First introduced onto the battlefield during World War I, tanks represented the reconciliation of firepower and mobility and immediately seized the imagination of commanders and commentators concerned about the constraints of ordinary infantry. The developments of technology and tactics in the interwar years were realized in the German blitzkrieg in World War II and beyond. Yet the account of armor on the battlefield is a tale of limitations and defeats as well as of potential and achievements. Tank Warfare examines the traditional narrative of armored warfare while at the same time challenging it, and Black suggests that tanks were no “silver bullet” on the battlefield. Instead, their success was based on their inclusion in the general mix of weaponry available to commanders and the context in which they were used. “An excellent overview of the subject.” —Alaric Searle, author of Armoured Warfare: A Military, Political and Global History




Theory of Statistical Inference


Book Description

Theory of Statistical Inference is designed as a reference on statistical inference for researchers and students at the graduate or advanced undergraduate level. It presents a unified treatment of the foundational ideas of modern statistical inference, and would be suitable for a core course in a graduate program in statistics or biostatistics. The emphasis is on the application of mathematical theory to the problem of inference, leading to an optimization theory allowing the choice of those statistical methods yielding the most efficient use of data. The book shows how a small number of key concepts, such as sufficiency, invariance, stochastic ordering, decision theory and vector space algebra play a recurring and unifying role. The volume can be divided into four sections. Part I provides a review of the required distribution theory. Part II introduces the problem of statistical inference. This includes the definitions of the exponential family, invariant and Bayesian models. Basic concepts of estimation, confidence intervals and hypothesis testing are introduced here. Part III constitutes the core of the volume, presenting a formal theory of statistical inference. Beginning with decision theory, this section then covers uniformly minimum variance unbiased (UMVU) estimation, minimum risk equivariant (MRE) estimation and the Neyman-Pearson test. Finally, Part IV introduces large sample theory. This section begins with stochastic limit theorems, the δ-method, the Bahadur representation theorem for sample quantiles, large sample U-estimation, the Cramér-Rao lower bound and asymptotic efficiency. A separate chapter is then devoted to estimating equation methods. The volume ends with a detailed development of large sample hypothesis testing, based on the likelihood ratio test (LRT), Rao score test and the Wald test. Features This volume includes treatment of linear and nonlinear regression models, ANOVA models, generalized linear models (GLM) and generalized estimating equations (GEE). An introduction to decision theory (including risk, admissibility, classification, Bayes and minimax decision rules) is presented. The importance of this sometimes overlooked topic to statistical methodology is emphasized. The volume emphasizes throughout the important role that can be played by group theory and invariance in statistical inference. Nonparametric (rank-based) methods are derived by the same principles used for parametric models and are therefore presented as solutions to well-defined mathematical problems, rather than as robust heuristic alternatives to parametric methods. Each chapter ends with a set of theoretical and applied exercises integrated with the main text. Problems involving R programming are included. Appendices summarize the necessary background in analysis, matrix algebra and group theory.




Information Theory for Complex Systems


Book Description

This book introduces a comprehensive framework tailored for dissecting complex systems across diverse disciplines. What defines a complex system? How can we harness information to quantify its order, structure, and intricacy? Delving into phenomena from the intricate processes in physical systems to the dynamic behaviours in cellular automata and pattern formation, readers will uncover the profound interplay between physics and information theory. This intricate relationship provides fresh insight into physical phenomena, reimagining them through the lens of information. Notably, the book demystifies how seemingly opposing forces—rising order and increasing disorder—coexist, ultimately shedding light on the second law of thermodynamics as an outcome of deterministic, reversible dynamics beneath the surface. Geared towards graduate students, this book presumes an undergraduate foundation in mathematics and physics, ensuring a deep, engaging exploration for its readers.




Rohit Parikh on Logic, Language and Society


Book Description

This book discusses major milestones in Rohit Jivanlal Parikh’s scholarly work. Highlighting the transition in Parikh’s interest from formal languages to natural languages, and how he approached Wittgenstein’s philosophy of language, it traces the academic trajectory of a brilliant scholar whose work opened up various new avenues in research. This volume is part of Springer’s book series Outstanding Contributions to Logic, and honours Rohit Parikh and his works in many ways. Parikh is a leader in the realm of ideas, offering concepts and definitions that enrich the field and lead to new research directions. Parikh has contributed to a variety of areas in logic, computer science and game theory. In mathematical logic his contributions have been in recursive function theory, proof theory and non-standard analysis; in computer science, in the areas of modal, temporal and dynamic logics of programs and semantics of programs, as well as logics of knowledge; in artificial intelligence in the area of belief revision; and in game theory in the formal analysis of social procedures, with a strong undercurrent of philosophy running through all his work.This is not a collection of articles limited to one theme, or even directly connected to specific works by Parikh, but instead all papers are inspired and influenced by Parikh in some way, adding structures to and enriching “Parikh-land”. The book presents a brochure-like overview of Parikh-land before providing an “introductory video” on the sights and sounds that you experience when reading the book.




Infogenomics


Book Description

The book presents a conceptual and methodological basis for the mathematical and computational analysis of genomes. Genomes are containers of biological information, which direct the cell functions and the evolution of organisms. Combinatorial, probabilistic, and informational aspects are fundamental ingredients of any mathematical investigation of genomes aimed at providing mathematical principles for extracting the information that they contain. The topics presented in the book include research themes developed by authors in the last 15 years, and in many aspects, the book continues a preceding volume (Vincenzo Manca, Infobiotics: Information in biotic systems, Springer, 2013). The main inspiring idea of the book is an informational perspective to Genomics. Information is the most recent, among the fundamental mathematical and physical concepts developed in the last two centuries. It has revolutionized the whole science and continues, in this direction, to dominate the trends of the contemporary science. In fact, any discipline collects data from observations, by providing theories able to explain, predict, and dominate natural phenomena. But data are containers of information, whence information is essential in any scientific elaboration. Many open problems in deciphering genomes will be addressed, by showing an informational approach to the discovery of “genome languages”, according to which genomic texts are written. Life strategies, at many levels of organization, are encoded in these texts, and randomness has a crucial role in the birth and in the development of biological information, where the interplay of casualty and computation is probably the most secret key of life intelligence.




Probabilistic Machine Learning for Finance and Investing


Book Description

Whether based on academic theories or discovered empirically by humans and machines, all financial models are at the mercy of modeling errors that can be mitigated but not eliminated. Probabilistic ML technologies are based on a simple and intuitive definition of probability and the rigorous calculus of probability theory. Unlike conventional AI systems, probabilistic machine learning (ML) systems treat errors and uncertainties as features, not bugs. They quantify uncertainty generated from inexact model inputs and outputs as probability distributions, not point estimates. Most importantly, these systems are capable of forewarning us when their inferences and predictions are no longer useful in the current market environment. These ML systems provide realistic support for financial decision-making and risk management in the face of uncertainty and incomplete information. Probabilistic ML is the next generation ML framework and technology for AI-powered financial and investing systems for many reasons. They are generative ensembles that learn continually from small and noisy financial datasets while seamlessly enabling probabilistic inference, prediction and counterfactual reasoning. By moving away from flawed statistical methodologies (and a restrictive conventional view of probability as a limiting frequency), you can embrace an intuitive view of probability as logic within an axiomatic statistical framework that comprehensively and successfully quantifies uncertainty. This book shows you why and how to make that transition.




Handbook of Trait-Based Ecology


Book Description

Functional ecology is the branch of ecology that focuses on various functions that species play in the community or ecosystem in which they occur. This accessible guide offers the main concepts and tools in trait-based ecology, and their tricks, covering different trophic levels and organism types. It is designed for students, researchers and practitioners who wish to get a handy synthesis of existing concepts, tools and trends in trait-based ecology, and wish to apply it to their own field of interest. Where relevant, exercises specifically designed to be run in R are included, along with accompanying on-line resources including solutions for exercises and R functions, and updates reflecting current developments in this fast-changing field. Based on more than a decade of teaching experience, the authors developed and improved the way theoretical aspects and analytical tools of trait-based ecology are introduced and explained to readers.




Introduction to the Physics of Electron Emission


Book Description

A practical, in-depth description of the physics behind electron emission physics and its usage in science and technology Electron emission is both a fundamental phenomenon and an enabling component that lies at the very heart of modern science and technology. Written by a recognized authority in the field, with expertise in both electron emission physics and electron beam physics, An Introduction to Electron Emission provides an in-depth look at the physics behind thermal, field, photo, and secondary electron emission mechanisms, how that physics affects the beams that result through space charge and emittance growth, and explores the physics behind their utilization in an array of applications. The book addresses mathematical and numerical methods underlying electron emission, describing where the equations originated, how they are related, and how they may be correctly used to model actual sources for devices using electron beams. Writing for the beam physics and solid state communities, the author explores applications of electron emission methodology to solid state, statistical, and quantum mechanical ideas and concepts related to simulations of electron beams to condensed matter, solid state and fabrication communities. Provides an extensive description of the physics behind four electron emission mechanisms—field, photo, and secondary, and how that physics relates to factors such as space charge and emittance that affect electron beams. Introduces readers to mathematical and numerical methods, their origins, and how they may be correctly used to model actual sources for devices using electron beams Demonstrates applications of electron methodology as well as quantum mechanical concepts related to simulations of electron beams to solid state design and manufacture Designed to function as both a graduate-level text and a reference for research professionals Introduction to the Physics of Electron Emission is a valuable learning tool for postgraduates studying quantum mechanics, statistical mechanics, solid state physics, electron transport, and beam physics. It is also an indispensable resource for academic researchers and professionals who use electron sources, model electron emission, develop cathode technologies, or utilize electron beams.




Probability Theory and Statistical Inference


Book Description

Doubt over the trustworthiness of published empirical results is not unwarranted and is often a result of statistical mis-specification: invalid probabilistic assumptions imposed on data. Now in its second edition, this bestselling textbook offers a comprehensive course in empirical research methods, teaching the probabilistic and statistical foundations that enable the specification and validation of statistical models, providing the basis for an informed implementation of statistical procedure to secure the trustworthiness of evidence. Each chapter has been thoroughly updated, accounting for developments in the field and the author's own research. The comprehensive scope of the textbook has been expanded by the addition of a new chapter on the Linear Regression and related statistical models. This new edition is now more accessible to students of disciplines beyond economics and includes more pedagogical features, with an increased number of examples as well as review questions and exercises at the end of each chapter.