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Springer Boston Heidelberg New York Dordrecht London While the advice and information in this book are believed to be true and accurate at the date of. Research Center. Yorktown Heights, New York. November 25, PDF Downloadable from Pages Open Access. PDF · How This Book was Created Using Collaborative Authoring and Cloud Tools. Sönke Bartling. Pages Open Access.
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The solution of differential equations using R is the springer pdf books focus of this book. It is therefore intended for the practitioner, the student and the scientist, who wants to know how to use R for solving differential equations.
However, it has been our goal that non-mathematicians should at least understand the basics of the methods, while obtaining entrance into the relevant literature that provides more mathematical background. Therefore, each chapter that deals with R examples is preceded by a chapter where the theory behind the numerical methods being used is introduced.
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springer pdf books In the sections that deal with the use of R for solving differential equations, springer pdf books have taken examples from a variety of disciplines, including biology, chemistry, physics, pharmacokinetics. Many examples are well-known test examples, used frequently in the field of numerical analysis.
An Introduction to R for Statistical Analysis. It is suitable for anyone that is familiar with basic statistics and wants to begin using R to analyse data and create statistical plots.
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Wiley, Chichester, UK, Graduate and postgraduate students in finance, economics, risk management as well as practitioners in springer pdf books and portfolio optimisation will find this book beneficial.
It also serves well as an accompanying text in computer-lab classes and is therefore suitable for self-study.
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A Practical Introduction to Bayesian Analysis. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents complete coverage of all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity.
It also features a large number of worked examples and a wide range of applications from various disciplines. The book introduces regression models, techniques for criticism and comparison, and a wide range of modelling issues before going into the vital area of hierarchical models, one springer pdf books the most common applications of Bayesian methods.
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It deals with essentials of modelling without getting bogged down in complexity. Springer pdf books of the examples are biostatistical, but they do not require domain knowledge and are generalisable to a wide range of other application areas.
Full code and data for examples, exercises, and some solutions can be found on the book's website. Programming Graphical User Interfaces in R.
With examples woven through the text as well as stand-alone demonstrations of simple yet reasonably complete applications, the book features topics especially relevant to statisticians who aim to provide a practical interface springer pdf books functionality implemented in R.
The accompanying package, ProgGUIinR, includes springer pdf books complete code for all examples as well as functions for browsing the examples from the respective chapters. Accessible to seasoned, novice, and occasional R users, this book shows that for many purposes, adding a graphical interface to one's work is not terribly sophisticated or time consuming.
Event History Analysis with R.
Keeping mathematical details springer pdf books a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional hazards, and accelerated failure times. A much-needed primer, Event History Analysis with R is a didactically excellent resource for students and practitioners of applied event history and survival analysis.
These models constitute an attractive paradigm for the analysis of follow-up data that is mainly applicable in two settings: First, when focus is on a survival outcome and we wish to account for the effect of an endogenous time-dependent covariate measured with error, and second, when focus is on the longitudinal outcome and we wish to correct for nonrandom dropout.
Aimed at applied springer pdf books and graduate students, this text provides a comprehensive overview of the framework of random effects joint models.
Emphasis is given on applications such that readers will obtain a clear view on the type of research questions that are best answered using a joint springer pdf books approach, the basic features of these models, and how they can be extended in practice.
Special mention is given in checking the assumptions using residual plots, and on dynamic springer pdf books for the survival and longitudinal outcomes.
The R Student Companion. The R Student Companion is a student-oriented manual describing how to use R in high school and college science and mathematics courses.
Written for beginners in scientific computation, the book assumes the reader has just some high school algebra and has no computer programming background.