Frontiers Statistics Data Science (17 results)

Hardcover. Condition: new. Hardcover. This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily with a prior background on the topic should be able to get a summary of developments in the field. These chapters serve as basic introductory references for new researchers in these fields, as well as the basis of teaching a course on the topic, or with a part of the course on topics of precision medicine, deep learning, high-dimensional central limit theorems, multivariate rank testing, R programming for statistics, Bayesian nonparametrics, large deviation asymptotics, spatio-temporal modeling of Covid-19, statistical network models, hidden Markov models, statistical record linkage analysis. The edited volume will be most useful for graduate students looking for an overview of any of the covered topics for their research and for instructors for developing certain courses by including any of the topics as part of the course. Students enrolled in a course covering any of the included topics can also benefit from these chapters. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily with a prior background on the topic should be able to get a summary of developments in the field. These chapters serve as basic introductory references for new researchers in these fields, as well as the basis of teaching a course on the topic, or with a part of the course on topics of precision medicine, deep learning, high-dimensional central limit theorems, multivariate rank testing, R programming for statistics, Bayesian nonparametrics, large deviation asymptotics,spatio-temporal modeling of Covid-19, statistical network models,hidden Markov models, statistical record linkage analysis. The edited volume will be most useful for graduate students looking for an overview of any of the covered topics for their research and for instructors for developing certain courses by including any of the topics as part of the course. Students enrolled in a course covering any of the included topics can also benefit from these chapters.

Condition: New.

Hardcover. Condition: new. Hardcover. This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily with a prior background on the topic should be able to get a summary of developments in the field. These chapters serve as basic introductory references for new researchers in these fields, as well as the basis of teaching a course on the topic, or with a part of the course on topics of precision medicine, deep learning, high-dimensional central limit theorems, multivariate rank testing, R programming for statistics, Bayesian nonparametrics, large deviation asymptotics, spatio-temporal modeling of Covid-19, statistical network models, hidden Markov models, statistical record linkage analysis. The edited volume will be most useful for graduate students looking for an overview of any of the covered topics for their research and for instructors for developing certain courses by including any of the topics as part of the course. Students enrolled in a course covering any of the included topics can also benefit from these chapters. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condition: new. Hardcover. This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily with a prior background on the topic should be able to get a summary of developments in the field. These chapters serve as basic introductory references for new researchers in these fields, as well as the basis of teaching a course on the topic, or with a part of the course on topics of precision medicine, deep learning, high-dimensional central limit theorems, multivariate rank testing, R programming for statistics, Bayesian nonparametrics, large deviation asymptotics, spatio-temporal modeling of Covid-19, statistical network models, hidden Markov models, statistical record linkage analysis. The edited volume will be most useful for graduate students looking for an overview of any of the covered topics for their research and for instructors for developing certain courses by including any of the topics as part of the course. Students enrolled in a course covering any of the included topics can also benefit from these chapters. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: Brand New. 370 pages. 9.25x6.10x9.21 inches. In Stock.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). It covers a wide range of cutting-edge topics in both theoretical and applied statistics. Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Readers with a background in mathematics and statistics will find it particularly beneficial, while researchers from various scientific disciplines can explore numerous robust applications.

Condition: New.

Condition: New.

Buch. Condition: Neu. Neuware -This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). It covers a wide range of cutting-edge topics in both theoretical and applied statistics. Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Readers with a background in mathematics and statistics will find it particularly beneficial, while researchers from various scientific disciplines can explore numerous robust applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 472 pp. Englisch.

Hardcover. Condition: new. Hardcover. This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). It covers a wide range of cutting-edge topics in both theoretical and applied statistics. Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Readers with a background in mathematics and statistics will find it particularly beneficial, while researchers from various scientific disciplines can explore numerous robust applications. This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: Brand New. 469 pages. 9.25x6.10x9.46 inches. In Stock.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily with a prior background on the topic should be able to get a summary of developments in the field. These chapters serve as basic introductory references for new researchers in these fields, as well as the basis of teaching a course on the topic, or with a part of the course on topics of precision medicine, deep learning, high-dimensional central limit theorems, multivariate rank testing, R programming for statistics, Bayesian nonparametrics, large deviation asymptotics,spatio-temporal modeling of Covid-19, statistical network models,hidden Markov models, statistical record linkage analysis. The edited volume will be most useful for graduate students looking for an overview of any of the covered topics for their research and for instructors for developing certain courses by including any of the topics as part of the course. Students enrolled in a course covering any of the included topics can also benefit from these chapters. 215 pp. Englisch.

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book addresses a diverse set of topics of contemporary interest in statistics and data science such as biostatistics and machine learning. Each chapter provides an overview of the topic under discussion, so that any reader with an understanding of graduate-level statistics, but not necessarily with a prior background on the topic should be able to get a summary of developments in the field. These chapters serve as basic introductory references for new researchers in these fields, as well as the basis of teaching a course on the topic, or with a part of the course on topics of precision medicine, deep learning, high-dimensional central limit theorems, multivariate rank testing, R programming for statistics, Bayesian nonparametrics, large deviation asymptotics, spatio-temporal modeling of Covid-19, statistical network models, hidden Markov models, statistical record linkage analysis. The edited volume will be most useful for graduate students looking for an overview of any of the covered topics for their research and for instructors for developing certain courses by including any of the topics as part of the course. Students enrolled in a course covering any of the included topics can also benefit from these chapters.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Condition: New. PRINT ON DEMAND.