New Developments In Statistical Modeling Inference And Application

Author : Zhezhen Jin,Mengling Liu,Xiaolong Luo
Publisher : Springer
Page : 214 pages
File Size : 47,6 Mb
Release : 2016-10-28
Category : Medical
ISBN : 9783319425719

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New Developments in Statistical Modeling, Inference and Application by Zhezhen Jin,Mengling Liu,Xiaolong Luo Pdf

The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.

Author : Vijay Nair
Publisher : World Scientific
Page : 698 pages
File Size : 43,5 Mb
Release : 2007
Category : Mathematics
ISBN : 9789812708298

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Advances in Statistical Modeling and Inference by Vijay Nair Pdf

There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics. This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 49,7 Mb
Release : 2024-07-03
Category : Electronic
ISBN : 9789814476614

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Advances in Statistical Modeling and Inference by Anonim Pdf

Author : Anna Maria Paganoni,Piercesare Secchi
Publisher : Springer
Page : 210 pages
File Size : 42,6 Mb
Release : 2014-11-04
Category : Mathematics
ISBN : 9783319111490

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Advances in Complex Data Modeling and Computational Methods in Statistics by Anna Maria Paganoni,Piercesare Secchi Pdf

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Author : Barry C. Arnold,N. Balakrishnan,Jose-Maria Sarabia Alegria,Roberto Minguez
Publisher : Springer Science & Business Media
Page : 374 pages
File Size : 40,9 Mb
Release : 2009-04-09
Category : Mathematics
ISBN : 9780817646264

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Advances in Mathematical and Statistical Modeling by Barry C. Arnold,N. Balakrishnan,Jose-Maria Sarabia Alegria,Roberto Minguez Pdf

Enrique Castillo is a leading figure in several mathematical and engineering fields. Organized to honor Castillo’s significant contributions, this volume is an outgrowth of the "International Conference on Mathematical and Statistical Modeling," and covers recent advances in the field. Applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques are presented.

Author : António Pacheco,Rui Santos,Maria do Rosário Oliveira,Carlos Daniel Paulino
Publisher : Springer
Page : 283 pages
File Size : 52,6 Mb
Release : 2014-05-12
Category : Mathematics
ISBN : 9783319053233

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New Advances in Statistical Modeling and Applications by António Pacheco,Rui Santos,Maria do Rosário Oliveira,Carlos Daniel Paulino Pdf

This volume of the Selected Papers is a product of the XIX Congress of the Portuguese Statistical Society, held at the Portuguese town of Nazaré, from September 28 to October 1, 2011. All contributions were selected after a thorough peer-review process. It covers a broad scope of papers in the areas of Statistical Science, Probability and Stochastic Processes, Extremes and Statistical Applications.

Author : George A. Marcoulides,Randall E. Schumacker
Publisher : Psychology Press
Page : 354 pages
File Size : 47,6 Mb
Release : 2001-03
Category : Mathematics
ISBN : 9781135657819

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New Developments and Techniques in Structural Equation Modeling by George A. Marcoulides,Randall E. Schumacker Pdf

The revision of this edited volume introduces the latest issues and developments in SEM techniques. The book provides an understanding and working knowledge of advanced SEM techniques with a minimum of mathematical derivations. Includes cases & examples.

Author : James H. Stapleton
Publisher : John Wiley & Sons
Page : 466 pages
File Size : 47,9 Mb
Release : 2007-12-14
Category : Mathematics
ISBN : 9780470183403

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Models for Probability and Statistical Inference by James H. Stapleton Pdf

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

Author : Deborah G. Mayo
Publisher : Cambridge University Press
Page : 503 pages
File Size : 50,5 Mb
Release : 2018-09-20
Category : Mathematics
ISBN : 9781107054134

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Statistical Inference as Severe Testing by Deborah G. Mayo Pdf

Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.

Author : Michael H. Kutner
Publisher : McGraw-Hill Education
Page : 1396 pages
File Size : 43,9 Mb
Release : 2005
Category : Analysis of variance
ISBN : 0071122214

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Applied Linear Statistical Models by Michael H. Kutner Pdf

Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

Author : Thorsten Dickhaus
Publisher : Springer Science & Business Media
Page : 182 pages
File Size : 54,7 Mb
Release : 2014-01-23
Category : Science
ISBN : 9783642451829

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Simultaneous Statistical Inference by Thorsten Dickhaus Pdf

This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.

Author : Vijay Nair
Publisher : World Scientific
Page : 698 pages
File Size : 54,5 Mb
Release : 2007
Category : Mathematics
ISBN : 9789812703699

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Advances in Statistical Modeling and Inference by Vijay Nair Pdf

There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics.This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.

Author : Simona Balzano,Giovanni C. Porzio,Renato Salvatore,Domenico Vistocco,Maurizio Vichi
Publisher : Springer
Page : 182 pages
File Size : 43,5 Mb
Release : 2021-07-14
Category : Mathematics
ISBN : 3030699439

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Statistical Learning and Modeling in Data Analysis by Simona Balzano,Giovanni C. Porzio,Renato Salvatore,Domenico Vistocco,Maurizio Vichi Pdf

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.

Author : Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu
Publisher : Springer
Page : 222 pages
File Size : 50,5 Mb
Release : 2016-11-30
Category : Mathematics
ISBN : 9789811025945

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Advanced Statistical Methods in Data Science by Ding-Geng Chen,Jiahua Chen,Xuewen Lu,Grace Y. Yi,Hao Yu Pdf

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Author : Indranil Ghosh,N. Balakrishnan,Hon Keung Tony Ng
Publisher : Springer Nature
Page : 443 pages
File Size : 52,7 Mb
Release : 2021-04-01
Category : Mathematics
ISBN : 9783030629007

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Advances in Statistics - Theory and Applications by Indranil Ghosh,N. Balakrishnan,Hon Keung Tony Ng Pdf

This edited collection brings together internationally recognized experts in a range of areas of statistical science to honor the contributions of the distinguished statistician, Barry C. Arnold. A pioneering scholar and professor of statistics at the University of California, Riverside, Dr. Arnold has made exceptional advancements in different areas of probability, statistics, and biostatistics, especially in the areas of distribution theory, order statistics, and statistical inference. As a tribute to his work, this book presents novel developments in the field, as well as practical applications and potential future directions in research and industry. It will be of interest to graduate students and researchers in probability, statistics, and biostatistics, as well as practitioners and technicians in the social sciences, economics, engineering, and medical sciences.