Trends and Perspectives in Linear Statistical Inference

Trends and Perspectives in Linear Statistical Inference PDF Author: Müjgan Tez
Publisher: Springer
ISBN: 3319732412
Category : Mathematics
Languages : en
Pages : 257

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Book Description
This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference.

Trends and Perspectives in Linear Statistical Inference

Trends and Perspectives in Linear Statistical Inference PDF Author: Müjgan Tez
Publisher: Springer
ISBN: 3319732412
Category : Mathematics
Languages : en
Pages : 257

Get Book

Book Description
This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference.

Linear Statistical Inference and its Applications

Linear Statistical Inference and its Applications PDF Author: C. Radhakrishna Rao
Publisher: John Wiley & Sons
ISBN: 0470317140
Category : Mathematics
Languages : en
Pages : 656

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Book Description
"C. R. Rao would be found in almost any statistician's list of five outstanding workers in the world of Mathematical Statistics today. His book represents a comprehensive account of the main body of results that comprise modern statistical theory." -W. G. Cochran "[C. R. Rao is] one of the pioneers who laid the foundations of statistics which grew from ad hoc origins into a firmly grounded mathematical science." -B. Efrom Translated into six major languages of the world, C. R. Rao's Linear Statistical Inference and Its Applications is one of the foremost works in statistical inference in the literature. Incorporating the important developments in the subject that have taken place in the last three decades, this paperback reprint of his classic work on statistical inference remains highly applicable to statistical analysis. Presenting the theory and techniques of statistical inference in a logically integrated and practical form, it covers: * The algebra of vectors and matrices * Probability theory, tools, and techniques * Continuous probability models * The theory of least squares and the analysis of variance * Criteria and methods of estimation * Large sample theory and methods * The theory of statistical inference * Multivariate normal distribution Written for the student and professional with a basic knowledge of statistics, this practical paperback edition gives this industry standard new life as a key resource for practicing statisticians and statisticians-in-training.

Linear Statistical Inference and Its Applications

Linear Statistical Inference and Its Applications PDF Author: Calyampudi Radhakrishna Rao
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 552

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Book Description


Hybrid Censoring Know-How

Hybrid Censoring Know-How PDF Author: Narayanaswamy Balakrishnan
Publisher: Academic Press
ISBN: 0123983908
Category : Mathematics
Languages : en
Pages : 408

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Book Description
Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The readers will find information on the significance of censored data in theoretical and applied contexts, and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur. The existing literature on censoring methodology, life-testing procedures, and lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap, featuring statistical tools applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all inferential methods discussed Mentions some open problems and possible directions for future work Reviews developments on Type-II and Type-I HCS, including the most recent research and trends Explains why hybrid censored sampling is important in practice Provides details about the use of HCS under different settings and on various designs of HCS Describes the use of hybrid censoring in other reliability applications such as reliability sampling plans, step-stress testing, and quality control

Linear Statistical Inference

Linear Statistical Inference PDF Author: T. Calinski
Publisher:
ISBN: 9781461573548
Category :
Languages : en
Pages : 328

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Book Description


Multivariate, Multilinear and Mixed Linear Models

Multivariate, Multilinear and Mixed Linear Models PDF Author: Katarzyna Filipiak
Publisher: Springer Nature
ISBN: 3030754944
Category : Mathematics
Languages : en
Pages : 357

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Book Description
This book presents the latest findings on statistical inference in multivariate, multilinear and mixed linear models, providing a holistic presentation of the subject. It contains pioneering and carefully selected review contributions by experts in the field and guides the reader through topics related to estimation and testing of multivariate and mixed linear model parameters. Starting with the theory of multivariate distributions, covering identification and testing of covariance structures and means under various multivariate models, it goes on to discuss estimation in mixed linear models and their transformations. The results presented originate from the work of the research group Multivariate and Mixed Linear Models and their meetings held at the Mathematical Research and Conference Center in Będlewo, Poland, over the last 10 years. Featuring an extensive bibliography of related publications, the book is intended for PhD students and researchers in modern statistical science who are interested in multivariate and mixed linear models.

Principles of Statistical Inference

Principles of Statistical Inference PDF Author: Luigi Pace
Publisher: World Scientific
ISBN: 9789812386946
Category : Mathematics
Languages : en
Pages : 584

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Book Description
In this book, an integrated introduction to statistical inference is provided from a frequentist likelihood-based viewpoint. Classical results are presented together with recent developments, largely built upon ideas due to R.A. Fisher. The term ?neo-Fisherian? highlights this.After a unified review of background material (statistical models, likelihood, data and model reduction, first-order asymptotics) and inference in the presence of nuisance parameters (including pseudo-likelihoods), a self-contained introduction is given to exponential families, exponential dispersion models, generalized linear models, and group families. Finally, basic results of higher-order asymptotics are introduced (index notation, asymptotic expansions for statistics and distributions, and major applications to likelihood inference).The emphasis is more on general concepts and methods than on regularity conditions. Many examples are given for specific statistical models. Each chapter is supplemented with problems and bibliographic notes. This volume can serve as a textbook in intermediate-level undergraduate and postgraduate courses in statistical inference.

Contemporary Biostatistics with Biopharmaceutical Applications

Contemporary Biostatistics with Biopharmaceutical Applications PDF Author: Lanju Zhang
Publisher: Springer
ISBN: 303015310X
Category : Medical
Languages : en
Pages : 339

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Book Description
This edited volume presents current research in biostatistics with emphasis on biopharmaceutical applications. Featuring contributions presented at the 2017 ICSA Applied Statistics Symposium held in Chicago, IL on June 25 to 28, 2017, this book explores timely topics that have a high potential impact on statistical methodology and future research in biostatistics and biopharmaceuticals. The theme of this conference was Statistics for a New Generation: Challenges and Opportunities, in recognition of the advent of a new generation of statisticians. The conference attracted statisticians working in academia, government, and industry; domestic and international statisticians. From the conference, the editors selected 28 high-quality presentations and invited the speakers to prepare full chapters for this book. These contributions are divided into four parts: Part I Biostatistical Methodology, Part II Statistical Genetics and Bioinformatics, Part III Regulatory Statistics, and Part IV Biopharmaceutical Research and Applications. Featuring contributions on topics such as statistics in genetics, bioinformatics, biostatistical methodology, and statistical computing, this book is beneficial to researchers, academics, practitioners and policy makers in biostatistics and biopharmaceuticals.

Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining

Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining PDF Author: Om Prakash Jena
Publisher: Bentham Science Publishers
ISBN: 9815040413
Category : Computers
Languages : en
Pages : 236

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Book Description
Augmented intelligence is an alternate approach of artificial intelligence (AI), which emphasizes AI’s assistive role. Augmented intelligence enhances human skills of reasoning in a robotic system or software by simulating expectancy, educational mining, problem solving, recollection, sequencing, and decision-making capabilities. It is based on a combination of techniques such as machine learning, deep learning and cognitive computing. This book explains artificial intelligence models that support assistive processes in different situations. The contributors aim to provide information to a diverse audience with groundbreaking developments in mathematical computing. The book presents 8 chapters on these topics: - Educational data mining in augmented reality virtual learning environment - Brain and computer interfaces - Tree-based tools for chemometric analysis of infrared spectra - Applications of deep learning in medical engineering - Bankruptcy prediction model using an enhanced boosting classifier - Reputation systems for mobile agent security - The crow search algorithm - COVID-19 diagnosis and treatment The contents attempt to integrate various facets of augmented Intelligence, by describing recent research developments and advanced topics of interest to academicians and researchers working on machine learning problems and AI.

Combinatorial Matrix Theory and Generalized Inverses of Matrices

Combinatorial Matrix Theory and Generalized Inverses of Matrices PDF Author: Ravindra B. Bapat
Publisher: Springer Science & Business Media
ISBN: 8132210530
Category : Mathematics
Languages : en
Pages : 283

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Book Description
This book consists of eighteen articles in the area of `Combinatorial Matrix Theory' and `Generalized Inverses of Matrices'. Original research and expository articles presented in this publication are written by leading Mathematicians and Statisticians working in these areas. The articles contained herein are on the following general topics: `matrices in graph theory', `generalized inverses of matrices', `matrix methods in statistics' and `magic squares'. In the area of matrices and graphs, speci_c topics addressed in this volume include energy of graphs, q-analog, immanants of matrices and graph realization of product of adjacency matrices. Topics in the book from `Matrix Methods in Statistics' are, for example, the analysis of BLUE via eigenvalues of covariance matrix, copulas, error orthogonal model, and orthogonal projectors in the linear regression models. Moore-Penrose inverse of perturbed operators, reverse order law in the case of inde_nite inner product space, approximation numbers, condition numbers, idempotent matrices, semiring of nonnegative matrices, regular matrices over incline and partial order of matrices are the topics addressed under the area of theory of generalized inverses. In addition to the above traditional topics and a report on CMTGIM 2012 as an appendix, we have an article on old magic squares from India.