Download or read book Statistical Methods for Annotation Analysis written by Silviu Paun and published by Springer Nature. This book was released on 2022-05-31 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Labelling data is one of the most fundamental activities in science, and has underpinned practice, particularly in medicine, for decades, as well as research in corpus linguistics since at least the development of the Brown corpus. With the shift towards Machine Learning in Artificial Intelligence (AI), the creation of datasets to be used for training and evaluating AI systems, also known in AI as corpora, has become a central activity in the field as well. Early AI datasets were created on an ad-hoc basis to tackle specific problems. As larger and more reusable datasets were created, requiring greater investment, the need for a more systematic approach to dataset creation arose to ensure increased quality. A range of statistical methods were adopted, often but not exclusively from the medical sciences, to ensure that the labels used were not subjective, or to choose among different labels provided by the coders. A wide variety of such methods is now in regular use. This book is meant to provide a survey of the most widely used among these statistical methods supporting annotation practice. As far as the authors know, this is the first book attempting to cover the two families of methods in wider use. The first family of methods is concerned with the development of labelling schemes and, in particular, ensuring that such schemes are such that sufficient agreement can be observed among the coders. The second family includes methods developed to analyze the output of coders once the scheme has been agreed upon, particularly although not exclusively to identify the most likely label for an item among those provided by the coders. The focus of this book is primarily on Natural Language Processing, the area of AI devoted to the development of models of language interpretation and production, but many if not most of the methods discussed here are also applicable to other areas of AI, or indeed, to other areas of Data Science.
Download or read book Natural Language Annotation for Machine Learning written by James Pustejovsky and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes bibliographical references (p. 305-315) and index.
Download or read book Statistical Methods in Language and Linguistic Research written by Pascual Cantos Gómez and published by Equinox Publishing (UK). This book was released on 2013-01-01 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The linguistic community tend to regard statistical methods, or more generally quantitative techniques, with a certain amount of fear and suspicion. There is a feeling that statistics falls in the province of science and mathematics and such methods may destroy the magic of the literary text. This book seeks to make quantitative methods and statistical techniques less forbidding and show how they can contribute to linguistic analysis and research. It present some mathematical and statistical properties of natural languages and introduces some of the quantitative methods which are of the most value in working empirically with texts and corpora. The various issues are illustrated with helpful examples from the most basic descriptive techniques to decision-taking techniques and to more sophisticated multivariate statistical language models.
Download or read book Statistical Methods for Meta Analysis written by Larry V. Hedges and published by Academic Press. This book was released on 2014-06-28 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
Download or read book Quantitative Medical Data Analysis Using Mathematical Tools and Statistical Techniques written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Methods and Applications of Statistics in Clinical Trials Volume 2 written by Narayanaswamy Balakrishnan and published by John Wiley & Sons. This book was released on 2014-06-16 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods and Applications of Statistics in Clinical Trials, Volume 2: Planning, Analysis, and Inferential Methods includes updates of established literature from the Wiley Encyclopedia of Clinical Trials as well as original material based on the latest developments in clinical trials. Prepared by a leading expert, the second volume includes numerous contributions from current prominent experts in the field of medical research. In addition, the volume features: • Multiple new articles exploring emerging topics, such as evaluation methods with threshold, empirical likelihood methods, nonparametric ROC analysis, over- and under-dispersed models, and multi-armed bandit problems • Up-to-date research on the Cox proportional hazard model, frailty models, trial reports, intrarater reliability, conditional power, and the kappa index • Key qualitative issues including cost-effectiveness analysis, publication bias, and regulatory issues, which are crucial to the planning and data management of clinical trials
Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-02 with total page 1224 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Download or read book Statistical Methods for the Analysis of Genomic Data written by Hui Jiang and published by MDPI. This book was released on 2020-12-29 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.
Download or read book Advanced Statistical Methods for the Analysis of Large Data Sets written by Agostino Di Ciaccio and published by Springer Science & Business Media. This book was released on 2012-03-05 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”
Download or read book Statistical Methods Computing and Resources for Genome Wide Association Studies written by Riyan Cheng and published by Frontiers Media SA. This book was released on 2021-08-24 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Methods for Research Workers written by Sir Ronald Aylmer Fisher and published by Oliver & Boyd. This book was released on 1970 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diagrams; Distributions; Tests of goodness of fit, independence and homogeneity: with tabler of X2; Tests of significance of means, differences of means, and regression coefficients; The correlation coefficient; Intraclass correlations and the analysis of variance; Further applications of the analysis of variance; The principles of statistical estimation; Sources used for data and methods.
Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-09 with total page 1828 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Download or read book The Handbook of Metabolic Phenotyping written by John C. Lindon and published by Elsevier. This book was released on 2018-10-04 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Metabolic Phenotyping is the definitive work on the rapidly developing subject of metabolic phenotyping. It explores in detail the wide array of analytical chemistry and statistical modeling techniques used in the field, coupled with surveys of the various application areas in human development, nutrition, disease, therapy, and epidemiology to create a comprehensive exploration of the area of study. It covers recent studies that integrate the various -omics data sets to derive a systems biology view. It also addresses current issues on standardization, assay and statistics validation, and data storage and sharing. Written by experts with many years of practice in the field who pioneered many of the approaches widely used today, The Handbook of Metabolic Phenotyping is a valuable resource for postgrads and research scientists studying and furthering the field of metabolomics. Contains theoretical and practical explanations of all the main analytical chemistry techniques used in metabolic phenotyping Explores, in detail, the many diverse statistical approaches used in the field Offers practical tips for successfully conducting metabolic phenotyping studies Features reviews of all of the various fields of activity relating to human studies
Download or read book Bioinformatics in Aquaculture written by Zhanjiang (John) Liu and published by John Wiley & Sons. This book was released on 2017-01-24 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinformatics derives knowledge from computer analysis of biological data. In particular, genomic and transcriptomic datasets are processed, analysed and, whenever possible, associated with experimental results from various sources, to draw structural, organizational, and functional information relevant to biology. Research in bioinformatics includes method development for storage, retrieval, and analysis of the data. Bioinformatics in Aquaculture provides the most up to date reviews of next generation sequencing technologies, their applications in aquaculture, and principles and methodologies for the analysis of genomic and transcriptomic large datasets using bioinformatic methods, algorithm, and databases. The book is unique in providing guidance for the best software packages suitable for various analysis, providing detailed examples of using bioinformatic software and command lines in the context of real world experiments. This book is a vital tool for all those working in genomics, molecular biology, biochemistry and genetics related to aquaculture, and computational and biological sciences.
Download or read book Advances in Statistical Methods for the Genetic Dissection of Complex Traits in Plants written by Yuan-Ming Zhang and published by Frontiers Media SA. This book was released on 2024-01-26 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genome-wide association studies (GWAS) have been widely used in the genetic dissection of complex traits. However, there are still limits in current GWAS statistics. For example, (1) almost all the existing methods do not estimate additive and dominance effects in quantitative trait nucleotide (QTN) detection; (2) the methods for detecting QTN-by-environment interaction (QEI) are not straightforward and do not estimate additive and dominance effects as well as additive-by-environment and dominance-by-environment interaction effects, leading to unreliable results; and (3) no or too simple polygenic background controls have been employed in QTN-by-QTN interaction (QQI) detection. As a result, few studies of QEI and QQI for complex traits have been reported based on multiple-environment experiments. Recently, new statistical tools, including 3VmrMLM, have been developed to address these needs in GWAS. In 3VmrMLM, all the trait-associated effects, including QTN, QEI and QQI related effects, are compressed into a single effect-related vector, while all the polygenic backgrounds are compressed into a single polygenic effect matrix. These compressed parameters can be accurately and efficiently estimated through a unified mixed model analysis. To further validate these new GWAS methods, particularly 3VmrMLM, they should be rigorously tested in real data of various plants and a wide range of other species.
Download or read book Digital Libraries Technology and Management of Indigenous Knowledge for Global Access written by Tengku Mohd. T. Sembok and published by Springer. This book was released on 2003-12-01 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Asian Digital Libraries, ICADL 2003, held in Kuala Lumpur, Malaysia in December 2003. The 68 revised full papers presented together with 15 poster abstracts and 3 invited papers were carefully reviewed from numerous submissions. The papers are organized in topical sections on information retrieval techniques, multimedia digital libraries, data mining and digital libraries, machine architecture and organization, human resources and training, human-computer interaction, digital library infrastructure, building and using digital libraries, knowledge management, intellectual property rights and copyright, e-learning and mobile learning, data storage and retrieval, digital library services, content development, information retrieval and Asian languages, and metadata.
Download or read book Statistical Methods and the Improvement of Data Quality written by Tommy Wright and published by Academic Press. This book was released on 2014-05-10 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods and the Improvement of Data Quality contains the proceedings of The Small Conference on the Improvement of the Quality of Data Collected by Data Collection Systems, held on November 11-12, 1982, in Oak Ridge, Tennessee. The conference provided a forum for discussing the use of statistical methods to improve data quality, with emphasis on the problems of data collection systems and how to handle them using state-of-the-art techniques. Comprised of 16 chapters, this volume begins with an overview of some of the limitations of surveys, followed by an annotated bibliography on frames from which the probability sample is selected. The reader is then introduced to sample designs and methods for collecting data over space and time; response effects to behavior and attitude questions; and how to develop and use error profiles. Subsequent chapters focus on principles and methods for handling outliers in data sets; influence functions, outlier detection, and data editing; and application of pattern recognition techniques to data analysis. The use of exploratory data analysis as an aid in modeling and statistical forecasting is also described. This monograph is likely to be of primary benefit to students taking a general course in survey sampling techniques, and to individuals and groups who deal with large data collection systems and are constantly seeking ways to improve the overall quality of their data.
