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Log-Linear Models And Logistic Regression

by Ronald Christensen

~~158,99€~~ 143,09€ 10% OFF

 This book examines statistical models for frequency data. After developing a sound applied and theoretical basis for frequency models analogous to ANOVA and regression, the book presents, for contingency tables, detailed discussions of the use of graphical models, of model selection procedures, and of models with quantitative factors.
ENGLISH

Log-Linear Models And Logistic Regression

by Ronald Christensen

~~162,21€~~ 145,99€ 10% OFF

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 This book examines statistical models for frequency data. After developing a sound applied and theoretical basis for frequency models analogous to ANOVA and regression, the book presents, for contingency tables, detailed discussions of the use of graphical models, of model selection procedures, and of models with quantitative factors.
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Applied Probability

by Kenneth Lange

~~133,84€~~ 120,46€ 10% OFF

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 Chapters 6 through 11 present core material on stochastic processes.If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes.
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Statistical Modeling And Computation

by Dirk P. Kroese e Joshua C. C. Chan

~~145,09€~~ 130,58€ 10% OFF

 It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications.The 2nd edition changes the programming language used in the text from MATLAB to Julia.
ENGLISH

Time Series Analysis And Its Applications - With R Examples

by David S. Stoffer e Robert H. Shumway

~~158,34€~~ 142,51€ 10% OFF

 <p>This 5th edition of this popular graduate textbook presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. It includes numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The R package ‘astsa’ has had major updates and the text will reflect those updates. In general, the graphics have been improved. New topics include random number generation, modeling and fitting predator-prey interactions, more emphasis on structural models, testing for linearity, discussion of EM algorithm is more extensive, Bayesian analysis of state space models and MCMC is more extensive (including new scripts in astsa), particle methods are introduced, stochastic volatility coverage is expanded, changepoint detection is introduced (new topic).</p><p>The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, and Markov chain Monte Carlo integration methods.</p><p>This edition includes R code for each numerical example.</p>
ENGLISH

Applied Probability

by Kenneth Lange

~~171,59€~~ 154,43€ 10% OFF

 Chapters 6 through 11 present core material on stochastic processes.If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes.
ENGLISH

Lectures On Advanced Topics In Categorical Data Analysis

by Tamas Rudas

~~118,59€~~ 106,73€ 10% OFF

 <p>This book continues the mission of the previous text by the author, <em>Lectures on Categorical Data Analysis</em>, by expanding on the introductory concepts from that volume and providing a mathematically rigorous presentation of advanced topics and current research in statistical techniques which can be applied in the social, political, behavioral, and life sciences. It presents an intuitive and unified discussion of an array of themes in categorical data analysis, and the emphasis on structure over stochastics renders many of the methods applicable in machine learning environments and for the analysis of big data.</p><p>The book focuses on graphical models, their application in causal analysis, the analytical properties of parameterizations of multivariate discrete distributions, marginal models, and coordinate-free relational models. To guide the readers in future research, the volume provides references to original papers and also offers detailed proofs of most of the significant results. Like the previous volume, it features exercises and research questions, making it appropriate for graduate students, as well as for active researchers.</p><p> </p>
ENGLISH

Statistical Modeling And Computation

by Dirk P. Kroese e Joshua C. C. Chan

~~148,70€~~ 133,83€ 10% OFF

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 It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications.The 2nd edition changes the programming language used in the text from MATLAB to Julia.
ENGLISH

Matrix Algebra - Theory, Computations And Applications In Statistics

by James E. Gentle

~~92,74€~~ 83,47€ 10% OFF

 This book presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra.
ENGLISH

Matrix Algebra - Theory, Computations And Applications In Statistics

by James E. Gentle

~~98,02€~~ 88,22€ 10% OFF

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 This book presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra.
ENGLISH

Introduction To Statistical Learning - With Applications In Python

by Daniela Witten, Gareth James, Jonathan Taylor, Robert Tibshirani e Trevor Hastie

92,74€ + 10% CARD

 An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years.
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Testing Statistical Hypotheses

by E.L. Lehmann e Joseph P. Romano

75,69€ + 10% CARD

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 New additions include an expanded treatment of multiple hypothesis testing, a new section on extensions of the Central Limit Theorem, coverage of high-dimensional testing, expanded discussions of permutation and randomization tests, coverage of testing moment inequalities, and many new problems throughout the text.
ENGLISH

Bayesian Inference Of State Space Models - Kalman Filtering And Beyond

by Kostas Triantafyllopoulos

89,21€ + 10% CARD

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 Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
ENGLISH

Fundamentals Of High-Dimensional Statistics - With Exercises And R Labs

by Johannes Lederer

71,64€ + 10% CARD

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 This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. The book covers the theory and practice of high-dimensional linear regression, graphical models, and inference, ensuring readers have a smooth start in the field. It also offers suggestions for further reading.
ENGLISH

Bayes Factors For Forensic Decision Analyses With R

by Alex Biedermann, Franco Taroni e Silvia Bozza

3,96€ + 10% CARD

 <p><i>Bayes Factors for Forensic Decision Analyses with R</i> provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics:</p><p></p><ul><li>Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence.</li></ul><ul><li>Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law.</li></ul><ul><li>Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context.</li></ul><p></p><p>Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes'' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist''s thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty.</p><p>This book would be relevant to students, practitioners, and applied statisticiansinterested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes.</p><p>This book is Open Access.</p><p><br></p><p></p>
ENGLISH

Testing Statistical Hypotheses

by E.L. Lehmann e Joseph P. Romano

105,34€ + 10% CARD

 New additions include an expanded treatment of multiple hypothesis testing, a new section on extensions of the Central Limit Theorem, coverage of high-dimensional testing, expanded discussions of permutation and randomization tests, coverage of testing moment inequalities, and many new problems throughout the text.
ENGLISH

Modern Mathematical Statistics With Applications

by Jay L. Devore, Kenneth N. Berk e Matthew A. Carlton

135,18€ + 10% CARD

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 This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice.
ENGLISH

Large Sample Techniques For Statistics

by Jiming Jiang

79,49€ + 10% CARD

 This book offers a comprehensive guide to large sample techniques in statistics. With a focus on developing analytical skills and understanding motivation, <i>Large Sample Techniques for Statistics</i> begins with fundamental techniques, and connects theory and applications in engaging ways.<div><br></div><div>The first five chapters review some of the basic techniques, such as the fundamental epsilon-delta arguments, Taylor expansion, different types of convergence, and inequalities. The next five chapters discuss limit theorems in specific situations of observational data. Each of the first ten chapters contains at least one section of case study. The last six chapters are devoted to special areas of applications. This new edition introduces a final chapter dedicated to random matrix theory, as well as expanded treatment of inequalities and mixed effects models. </div><div><br></div><div>The book''s case studies and applications-oriented chapters demonstrate how to use methods developed from large sample theory in real world situations. The book is supplemented by a large number of exercises, giving readers opportunity to practice what they have learned. Appendices provide context for matrix algebra and mathematical statistics. The Second Edition seeks to address new challenges in data science.</div><div><br></div><div>This text is intended for a wide audience, ranging from senior undergraduate students to researchers with doctorates. A first course in mathematical statistics and a course in calculus are prerequisites..</div>
ENGLISH

Testing Statistical Hypotheses

by E.L. Lehmann e Joseph P. Romano

106,80€ + 10% CARD

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 New additions include an expanded treatment of multiple hypothesis testing, a new section on extensions of the Central Limit Theorem, coverage of high-dimensional testing, expanded discussions of permutation and randomization tests, coverage of testing moment inequalities, and many new problems throughout the text.
ENGLISH

Transcranial Direct Current Stimulation In Neuropsychiatric Disorders - Clinical Principles And Management

270,36€ + 10% CARD

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 The 2nd edition of this book incorporates the tremendous clinical advances that have occurred in the field of transcranial direct current stimulation (tDCS) over the past 5 years.
ENGLISH

Modern Mathematical Statistics With Applications

by Jay L. Devore, Kenneth N. Berk e Matthew A. Carlton

115,59€ + 10% CARD

free shipping

 This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice.
ENGLISH

Fundamentals Of High-Dimensional Statistics - With Exercises And R Labs

by Johannes Lederer

98,71€ + 10% CARD

 This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. The book covers the theory and practice of high-dimensional linear regression, graphical models, and inference, ensuring readers have a smooth start in the field. It also offers suggestions for further reading.
ENGLISH

Bayesian Inference Of State Space Models - Kalman Filtering And Beyond

by Kostas Triantafyllopoulos

124,37€ + 10% CARD

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 Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
ENGLISH

Bayesian Inference Of State Space Models - Kalman Filtering And Beyond

by Kostas Triantafyllopoulos

92,74€ + 10% CARD

 Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
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