Libros de Matemáticas, página 24 de 470

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Written by an expert author team consisting of former IB chief examiners, senior examiners and assistant examiners, experienced IB workshop leaders, and teachers with more than 160 years of combined

This textbook is aimed at newcomers to nonlinear dynamics and chaos, especially students taking a first course in the subject.The presentation stresses analytical methods, concrete examples and geometric intuition. The theory is developed systematically, starting with first-order differential equations and their bifurcations, followed by phase plane analysis, limit cycles and their bifurcations, and culminating with the Lorenz equations, chaos, iterated maps, period doubling, renormalization, fractals, and strange attractors.A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with the mathematical theory.Richly illustrated, and with many exercises and worked examples, this book is ideal for an introductory course at the junior/senior or first-year graduate level. It is also ideal for the scientist who has not had formal instruction in nonlinear dynamics, but who now desires to begin informal study. The prerequisites are multivariable calculus and introductory physics.

One Hundred Nineteen Stata Tips provides concise and insightful notes about commands, features, and tricks that will help you obtain a deeper understanding of Stata. The book comprises the contributions of the Stata community that have appeared in the Stata Journal since 2003.

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology In step by step detail the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood information theoretic and Bayesian techniques to analyze their own data using the programming language R Drawing on extensive experience teaching these techniques to graduate students in ecology Benjamin Bolker shows how to choose among and construct statistical models for data estimate their parameters and confidence limits and interpret the results The book also covers statistical frameworks the philosophy of statistical modeling and critical mathematical functions and probability distributions It requires no programming background only basic calculus and statistics Practical beginner friendly introduction to modern statistical techniques for ecology using the programming language R Step by step instructions for fitting models to messy real world data Balanced view of different statistical approaches Wide coverage of techniques from simple distribution fitting to complex state space modeling Techniques for data manipulation and graphical display Companion Web site with data and R code for

Environmental Mathematics seeks to marry the most pressing challenge of our time with the most powerful technology of our time - mathematics. This book does this at an elementary level and demonstrates a wide variety of significant environmental applications that can be explored without resorting to calculus. Environmental Mathematics in the Classroom includes several chapters accessible enough to be a text in a general education course, or to enrich an elementary algebra course. Ground-level ozone, pollution and water use, preservation of whales, mathematical economics, the movement of clouds over a mountain range, at least one population model and a smorgasbord of ''newspaper mathematics'' can be studied at this level and would form a stimulating course. It would prepare future teachers not only to learn basic mathematics, but to understand how they can integrate it into other topics that will intrigue students.

mlr3 is an award winning ecosystem of R packages that have been developed to enable state of the art machine learning capabilities in R This book gives an overview of flexible and robust machine learning methods with an emphasis on how to implement them using mlr3 in R

This book focuses on the major applications of martingales to the geometry of Banach spaces, and a substantial discussion of harmonic analysis in Banach space valued Hardy spaces is also presented. It covers exciting links between super-reflexivity and some metric spaces related to computer science, as well as an outline of the recently developed theory of non-commutative martingales, which has natural connections with quantum physics and quantum information theory. Requiring few prerequisites and providing fully detailed proofs for the main results, this self-contained study is accessible to graduate students with a basic knowledge of real and complex analysis and functional analysis. Chapters can be read independently, with each building from the introductory notes, and the diversity of topics included also means this book can serve as the basis for a variety of graduate courses.

The theory of elliptic curves is distinguished by its long history and by the diversity of the methods that have been used in its study. This book treats the arithmetic theory of elliptic curves in its modern formulation, through the use of basic algebraic number theory and algebraic geometry. The book begins with a brief discussion of the necessary algebro-geometric results, and proceeds with an exposition of the geometry of elliptic curves, the formal group of an elliptic curve, elliptic curves over finite fields, the complex numbers, local fields, and global fields. The last two chapters deal with integral and rational points, including Siegel''s theorem and explicit computations for the curve Y^2 = X^3 + DX. The book contains three appendices: Elliptic Curves in Characteristics 2 and 3, Group Cohomology, and a third appendix giving an overview of more advanced topics.