Throughout the physical and social sciences, researchers face the challenge of fitting statistical distributions to their data. Although the study of statistical modelling has made great strides in recent years, the number and variety of distributions to choose from-all with their own formulas, tables, diagrams, and general properties-continue to create problems. For a specific application, which of the dozens of distributions should one use? What if none of them fit well?

Fitting Statistical Distributions helps answer those questions. Focusing on techniques used successfully across many fields, the authors present all of the relevant results related to the Generalized Lambda Distribution (GLD), the Generalized Bootstrap (GB), and Monte Carlo simulation (MC). They provide the tables, algorithms, and computer programs needed for fitting continuous probability distributions to data in a wide variety of circumstances-covering bivariate as well as univariate distributions, and including situations where moments do not exist.

Regardless of your specific field-physical science, social science, or statistics, practitioner or theorist-Fitting Statistical Distributions is required reading. It includes wide-ranging applications illustrating the methods in practice and offers proofs of key results for those involved in theoretical development. Without it, you may be using obsolete methods, wasting time, and risking incorrect results.

Presents a number of new and potentially useful self-learning (adaptive) control algorithms and theoretical as well as practical results for both unconstrained and constrained finite Markov chains-efficiently processing new information by adjusting the control strategies directly or indirectly.

To fully function in today's global real estate industry, students and professionals increasingly need to understand how to implement essential and cutting-edge quantitative techniques. This book presents an easy-to-read guide to applying quantitative analysis in real estate aimed at non-cognate undergraduate and masters students, and meets the requirements of modern professional practice. Through case studies and examples illustrating applications using data sourced from dedicated real estate information providers and major firms in the industry, the book provides an introduction to the foundations underlying statistical data analysis, common data manipulations and understanding descriptive statistics, before gradually building up to more advanced quantitative analysis, modelling and forecasting of real estate markets. Our examples and case studies within the chapters have been specifically compiled for this book and explicitly designed to help the reader acquire a better understanding of the quantitative methods addressed in each chapter. Our objective is to equip readers with the skills needed to confidently carry out their own quantitative analysis and be able to interpret empirical results from academic work and practitioner studies in the field of real estate and in other asset classes. Both undergraduate and masters level students, as well as real estate analysts in the professions, will find this book to be essential reading.

Features Quickly and concisely builds from basic probability theory to advanced topics Suitable as a primary text for an advanced course in diffusion processes and stochastic differential equations Useful as supplementary reading across a range of topics.

Python for Scientific Computation and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web.

The scattering data of the considered inverse scattering problems (ISPs) are described completely. Solving the associated IVP or IBVP for the nonlinear evolution equations (NLEEs) is carried out step by step. Namely, the NLEE can be written as the compatibility condition of two linear equations. The inverse scattering method (ISM) to solving the IVPs or IBVPs for NLEEs is consistent. It is effectively embedded in the schema of the ISM. Application of ISM to solving the NLEEs is effectively embedded in the scheme of the ISM.

This text examines the emerging field of fractals and its applications in earth sciences. Topics covered include: concepts of fractal and multifractal chaos; the application of fractals in geophysics, geology, climate studies, and earthquake seismology.

'Stats to Go' is a user-friendly guide for hospitality, leisure and tourism students who need to learn statistics and statistical techniques. 'Stats to go' is an ideal companion to hospitality, leisure and tourism studies as the breadth of coverage supports all taught numerical aspects of these types of course. Examples from hospitality, leisure and tourism organizations: * licensed premises* fast food outlets* hotels * theme parksand their environments are used to illustrate key issues of the text.The area of quantitative methods is one which many students find unapproachable or daunting. With the use of a clear learning structure, and a user friendly, non-theoretical approach, Buglear has created a text which students and lecturers alike will find indispensable.

Mathematics for Engineering has been carefully designed to provide a maths course for a wide ability range, and does not go beyond the requirements of Advanced GNVQ. It is an ideal text for any pre-degree engineering course where students require revision of the basics and plenty of practice work. Bill Bolton introduces the key concepts through examples set firmly in engineering contexts, which students will find relevant and motivating. The second edition has been carefully matched to the Curriculum 2000 Advanced GNVQ units: Applied Mathematics in Engineering (compulsory unit 5) Further Mathematics for Engineering (Edexcel option unit 13) Further Applied Mathematics for Engineering (AQA / City & Guilds option unit 25) A new introductory section on number and mensuration has been added, as well as a new section on series and some further material on applications of differentiation and definite integration. Bill Bolton is a leading author of college texts in engineering and other technical subjects. As well as being a lecturer for many years, he has also been Head of Research, Development and Monitoring at BTEC and acted as a consultant for the Further Education Unit.

A PRACTICAL GUIDE TO OPTIMIZATION PROBLEMS WITH DISCRETE OR INTEGER VARIABLES, REVISED AND UPDATED The revised second edition of Integer Programming explains in clear and simple terms how to construct custom-made algorithms or use existing commercial software to obtain optimal or near-optimal solutions for a variety of real-world problems. The second edition also includes information on the remarkable progress in the development of mixed integer programming solvers in the 22 years since the first edition of the book appeared. The updated text includes information on the most recent developments in the field such as the much improved preprocessing/presolving and the many new ideas for primal heuristics included in the solvers. The result has been a speed-up of several orders of magnitude. The other major change reflected in the text is the widespread use of decomposition algorithms, in particular column generation (branch-(cut)-and-price) and Benders' decomposition. The revised second edition: Contains new developments on column generation Offers a new chapter on Benders' algorithm Includes expanded information on preprocessing, heuristics, and branch-and-cut Presents several basic and extended formulations, for example for fixed cost network flows Also touches on and briefly introduces topics such as non-bipartite matching, the complexity of extended formulations or a good linear program for the implementation of lift-and-project Written for students of integer/mathematical programming in operations research, mathematics, engineering, or computer science, Integer Programming offers an updated edition of the basic text that reflects the most recent developments in the field.

Because elementary mathematics is vital to be able to properly design biological experiments and interpret their results. As a student of the life sciences you will only make your life harder by ignoring mathematics entirely. Equally, you do not want to spend your time struggling with complex mathematics that you will never use. This book is the perfect answer to your problems. Inside, it explains the necessary mathematics in easy-to-follow steps, introducing the basics and showing you how to apply these to biological situations.
Easy Mathematics for Biologists covers the basic mathematical ideas of fractions, decimals and percentages, through ratio and proportion, exponents and logarithms, to straight line graphs, graphs that are not straight lines, and their transformation. Direct application of each of these leads to a clear understanding of biological calculations such as those involving concentrations and dilutions, changing units, pH, and linear and non-linear rates of reaction. Each chapter contains worked examples, and is followed by numerous problems, both pure and applied, that can be worked through in your own time. Answers to these can be found at the back.

Useful in physics, economics, psychology, and other fields, random matrices play an important role in the study of multivariate statistical methods. Until now, however, most of the material on random matrices could only be found scattered in various statistical journals. Matrix Variate Distributions gathers and systematically presents most of the recent developments in continuous matrix variate distribution theory and includes new results.
After a review of the essential background material, the authors investigate the range of matrix variate distributions, including:
· matrix variate normal distribution
· Wishart distribution
· Matrix variate t-distribution
· Matrix variate beta distribution
· F-distribution
· Matrix variate Dirichlet distribution
· Matrix quadratic forms
With its inclusion of new results, Matrix Variate Distributions promises to stimulate further research and help advance the field of multivariate statistical analysis.

Sixty-five papers cover a wide range of topics from engineering applications to theoretical developments in the areas of embankment and slope stability, underground cavity design and mining; dynamic analysis, soil and structure interaction, and coupled processes and fluid flow.

Exclusive book integrating thermal sciences and computational approaches Covers both philosophical concepts related to systems and design, to numerical methods, to design of specific systems, to computational fluid dynamics strategies Focus on solving complex real-world thermal system design problems instead of just designing a single component or simple systems Introduces usage of statistics and machine learning methods to optimize the system Includes sample PYTHON codes, exercise problems, special projects

Quantitative Modeling of Derivative Securities demonstrates how to take the basic ideas of arbitrage theory and apply them - in a very concrete way - to the design and analysis of financial products. Based primarily (but not exclusively) on the analysis of derivatives, the book emphasizes relative-value and hedging ideas applied to different financial instruments. Using a "financial engineering approach," the theory is developed progressively, focusing on specific aspects of pricing and hedging and with problems that the technical analyst or trader has to consider in practice.

More than just an introductory text, the reader who has mastered the contents of this one book will have breached the gap separating the novice from the technical and research literature.

In this volume a number of developments on a variety of topics have been reported. These topics include: partially saturated soil; instabilities in soil behaviour; environmental geomechanics; parallel computing; and applications to tunnels, embankments, slopes, foundations and anchors.

As occupational health and safety professionals require increased awareness of the whole field-and not just its specialized areas-they've started to need an all-encompassing reference work of necessary mathematical relationships.
Concise Guide to Environmental Definitions, Conversions, and Formulae is the quick and proficient source for that information. Professionals will find it's ideal for immediate reference; students and interns can benefit from it as a comprehensive study guide for certification exam preparation purposes.
Based on information presented in another essential reference (Definitions, Conversions, and Calculations for Occupational Safety and Health Professionals, Second Edition), the Concise Guide brings its most-cited details to an easily carried, portable size (41/2 x 6 3/4). Essential conversions, formulae, and definitions all await within those pages.
Virtually all of the mathematical relationships, formulas, definitions, and conversion factors any health and safety expert or trainee will ever need are all contained in the Concise Guide to Environmental Definitions, Conversions, and Formulae.

Discusses the concepts of mechanical, thermal, and thermodynamic equilibrium and their applications. Covers the molecular basis for internal energy, entropy, thermodynamic equilibrium, and reversibility. Enables the reader to model irreversibility and determine the net loss in performance of a thermal system compared to an idealized system and approach an ideal one. Demonstrates entropy as a path independent property by use of reversible heat engines and reversible heat pumps interacting with a process between two states, the environment and the reservoir. Covers the role of reversibility from a thermodynamics standpoint and relates it to other areas, such as gas dynamics, combustion, propulsion, power plant engineering, and engines.

Mathematical Analysis for Modeling is intended for those who want to understand the substance of mathematics, rather than just having familiarity with its techniques. It provides a thorough understanding of how mathematics is developed for and applies to solving scientific and engineering problems. The authors stress the construction of mathematical descriptions of scientific and engineering situations, rather than rote memorizations of proofs and formulas. Emphasis is placed on algorithms as solutions to problems and on insight rather than formal derivations.

Dark Silicon and the Future of On-chip Systems, Volume 110, the latest release in the Advances in Computers series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design and applications, with this release focusing on an Introduction to dark silicon and future processors, a Revisiting of processor allocation and application mapping in future CMPs in the dark silicon era, Multi-objectivism in the dark silicon age, Dark silicon aware resource management for many-core systems, Dynamic power management for dark silicon multi-core processors, Topology specialization for networks-on-chip in the dark silicon era, and Emerging SRAM-based FPGA architectures.

Provides an understanding of the physics of flight during take-off and landing, from aerodynamics to flight performance, from simulation to design. Discusses the physical limits of lift generation giving the lift generation potential. Concentrates on the specifics of high-lift aerodynamics to provide a first insight. Analyzes the needs of an aircraft to improve its performance during take-off, approach, and landing. Focus on civil transport aircraft application, but the associated physics can apply to any other aircraft.

Handbook of Grid Generation addresses the use of grids (meshes) in the numerical solutions of partial differential equations by finite elements, finite volume, finite differences, and boundary elements. Four parts divide the chapters: structured grids, unstructured girds, surface definition, and adaption/quality. An introduction to each section provides a roadmap through the material. This handbook covers: -Fundamental concepts and approaches -Grid generation process -Essential mathematical elements from tensor analysis and differential geometry, particularly relevant to curves and surfaces -Cells of any shape - Cartesian, structured curvilinear coordinates, unstructured tetrahedra, unstructured hexahedra, or various combinations -Separate grids overlaid on one another, communicating data through interpolation -Moving boundaries and internal interfaces in the field -Resolving gradients and controlling solution error -Grid generation codes, both commercial and freeware, as well as representative and illustrative grid configurations Handbook of Grid Generation contains 37 chapters as well as contributions from more than 100 experts from around the world, comprehensively evaluating this expanding field and providing a fundamental orientation for practitioners.

Assuming only basic knowledge of mathematics and engineering mechanics, this lucid reference introduces the fundamentals of finite element theory using easy-to-understand terms and simple problems-systematically grounding the practitioner in the basic principles then suggesting applications to more general cases. Furnishes a wealth of practical insights drawn from the extensive experience of a specialist in the field Providing an in-depth overview of the analysis process, Practical Guide to Finite Elements describes the casting of elementary mechanics problems into a simplified form with idealization techniques shows how energy methods are employed to solve engineering problems involving stress, strain, and displacement outlines a process for computer-aided engineering analysis explains how numerical integration is utilized in conjunction with parametric elements demonstrates how a simple FORTRAN software routine computes element stiffness considers the use of loads and boundary conditions in finite element models presents common pitfalls that beginning analysts are likely to encounter addresses the interpretation of finite element analysis results and more Generously illustrated with over 200 detailed drawings to clarify discussions and containing key literature citations for more in-depth study of particular topics, this clearly written resource is an exceptional guide for mechanical, civil, aeronautic, automotive, electrical and electronics, and design engineers; engineering managers; and upper-level undergraduate, graduate, and continuing-education students in these disciplines.

For those who have a background in advanced calculus, elementary topology and functional analysis - from applied mathematicians and engineers to physicists - researchers and graduate students alike - this work provides a comprehensive analysis of the many important integral transforms and renders particular attention to all of the technical aspects of the subject. The author presents the last two decades of research and includes important results from other works.
With a description in Chapter 1 of foundational, topological information for the study of the distributions (generalized functions) and ultradistributions to be considered, including the structure of these distributions, the author then moves on to an analysis of the transforms and ends with a discussion of the eigenfunction expansion of generalized functions. Applications of the transforms to various mathematical, physical, and engineering problems are given, and open research problems present a challenge to the reader. An extensi

This textbook covers fundamental and advanced concepts of computational fluid dynamics, a powerful and essential tool for fluid flow analysis. It discusses various governing equations used in the field, their derivations, and the physical and mathematical significance of partial differential equations and the boundary conditions. It covers fundamental concepts of finite difference and finite volume methods for diffusion, convection-diffusion problems both for cartesian and non-orthogonal grids. The solution of algebraic equations arising due to finite difference and finite volume discretization are highlighted using direct and iterative methods. Pedagogical features including solved problems and unsolved exercises are interspersed throughout the text for better understanding. The textbook is primarily written for senior undergraduate and graduate students in the field of mechanical engineering and aerospace engineering, for a course on computational fluid dynamics and heat transfer. The textbook will be accompanied by teaching resources including a solution manual for the instructors. Written clearly and with sufficient foundational background to strengthen fundamental knowledge of the topic. Offers a detailed discussion of both finite difference and finite volume methods. Discusses various higher-order bounded convective schemes, TVD discretisation schemes based on the flux limiter essential for a general purpose CFD computation. Discusses algorithms connected with pressure-linked equations for incompressible flow. Covers turbulence modelling like k- , k- , SST k- , Reynolds Stress Transport models. A separate chapter on best practice guidelines is included to help CFD practitioners.