Download or read book Testing Jumps Via False Discovery Rate Control written by Yu-Min Yen and published by . This book was released on 2019 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such situation becomes even worse when the jump occurrence is a rare event. To obtain more reliable results, we aim to control the false discovery rate (FDR), an e fficient compound error measure for erroneous rejections in multiple testing problems. We perform the test via the Barndor -Nielsen and Shephard (BNS) test statistic, and control the FDR with the Benjamini and Hochberg (BH) procedure. We provide asymptotic results for the FDR control. From simulations, we examine relevant theoretical results and demonstrate the advantages of controlling the FDR. The hybrid approach is then applied to empirical analysis on two benchmark stock indices with high frequency data.

Download or read book Testing and Detecting Jumps Based on a Discretely Observed Process written by Yingying Fan and published by . This book was released on 2009 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new nonparametric test for detecting the presence of jumps in asset prices using discretely observed data. Compared with the test statistic in A quot;{i}t-Sahalia and Jacod (2007), our new test statistic enjoys the same asymptotic properties but has smaller variance. These results are justified both theoretically and numerically. Thanks to the reduction of the variance, we also propose a new test procedure to identify the locations of jumps. The problem of jump identification thus reduces to a multiple comparison problem. We employ the False Discovery Rate (FDR) approach to control the type I error. Simulation studies and real data analysis further demonstrate the power of the newly proposed test method.

Download or read book Multiple Testing and False Discovery Rate Control written by Shiyun Chen and published by . This book was released on 2019 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple testing, a situation where multiple hypothesis tests are performed simultaneously, is a core research topic in statistics that arises in almost every scientific field. When more hypotheses are tested, more errors are bound to occur. Controlling the false discovery rate (FDR) [BH95], which is the expected proportion of falsely rejected null hypotheses among all rejections, is an important challenge for making meaningful inferences. Throughout the dissertation, we analyze the asymptotic performance of several FDR-controlling procedures under different multiple testing settings. In Chapter 1, we study the famous Benjamini-Hochberg (BH) method [BH95] which often serves as benchmark among FDR-controlling procedures, and show that it is asymptotic optimal in a stylized setting. We then prove that a distribution-free FDR control method of Barber and Candès [FBC15], which only requires the (unknown) null distribution to be symmetric, can achieve the same asymptotic performance as the BH method, thus is also optimal. Chapter 2 proposes an interval-type procedure which identifies the longest interval with the estimated FDR under a given level and rejects the corresponding hypotheses with P-values lying inside the interval. Unlike the threshold approaches, this procedure scans over all intervals with the left point not necessary being zero. We show that this scan procedure provides strong control of the asymptotic false discovery rate. In addition, we investigate its asymptotic false non-discovery rate (FNR), deriving conditions under which it outperforms the BH procedure. In Chapter 3, we consider an online multiple testing problem where the hypotheses arrive sequentially in a stream, and investigate two procedures proposed by Javanmard and Montanari [JM15] which control FDR in an online manner. We quantify their asymptotic performance in the same location models as in Chapter 1 and compare their power with the (static) BH method. In Chapter 4, we propose a new class of powerful online testing procedures which incorporates the available contextual information, and prove that any rule in this class controls the online FDR under some standard assumptions. We also derive a practical algorithm that can make more empirical discoveries in an online fashion, compared to the state-of-the-art procedures.

Download or read book Controlling the False Discovery Rate with Dynamic Adaptive Procedures and of Grouped Hypotheses written by Peter W. MacDonald and published by . This book was released on 2018 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the multiple testing problem with independent tests, the classical Benjamini-Hochberg (BH) procedure controls the false discovery rate (FDR) below the target FDR level. Adaptive procedures can improve power by incorporating estimates of the proportion of true null hypotheses, which typically rely on a tuning parameter. Fixed adaptive procedures set their tuning parameters before seeing the data and can be shown to control the FDR in finite samples. In Chapter 2 of this thesis, we develop theoretical results for dynamic adaptive procedures whose tuning parameters are determined by the data. We show that, if the tuning parameter is chosen according to a left-to-right stopping time rule, the corresponding dynamic adaptive procedure controls the FDR in finite samples. Examples include the recently proposed right-boundary procedure and the widely used lowest-slope procedure, among others. Simulation results show that the right-boundary procedure is more powerful than other dynamic adaptive procedures under independence and mild dependence conditions. The BH procedure implicitly assumes all hypotheses are exchangeable. When hypotheses come from known groups, this assumption is inefficient, and power can be improved through a ranking of significance that incorporates group information. In Chapter 3 of this thesis, we define a general sequential framework for multiple testing procedures in the grouped setting. We develop a flexible grouped mirrored knockoff (GMK) procedure which approximates the optimal ranking of significance. We show that the GMK procedure controls the FDR in finite samples, and give a particular data-driven implementation using the expectation-maximization algorithm. Simulation and a real data example demonstrate that the GMK procedure outperforms its competitors in terms of power and FDR control with independent tests.

Download or read book Adaptive Step Up Tests for the False Discovery Rate FDR Under Independence and Dependence written by Philipp Heesen and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book CONTROLLING THE FALSE DISCOVERY RATE VIA KNOCKOFFS written by Rina Foygel Barber and published by . This book was released on 2014 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Financial Econometrics and Empirical Market Microstructure written by Anil K. Bera and published by Springer. This book was released on 2014-11-18 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of Big Data our society is given the unique opportunity to understand the inner dynamics and behavior of complex socio-economic systems. Advances in the availability of very large databases, in capabilities for massive data mining, as well as progress in complex systems theory, multi-agent simulation and computational social science open the possibility of modeling phenomena never before successfully achieved. This contributed volume from the Perm Winter School address the problems of the mechanisms and statistics of the socio-economics system evolution with a focus on financial markets powered by the high-frequency data analysis. ​

Download or read book Biostatistics For Dummies written by John C. Pezzullo and published by John Wiley & Sons. This book was released on 2013-07-10 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Score your highest in biostatistics Biostatistics is a required course for students of medicine, epidemiology, forestry, agriculture, bioinformatics, and public health. In years past this course has been mainly a graduate-level requirement; however its application is growing and course offerings at the undergraduate level are exploding. Biostatistics For Dummies is an excellent resource for those taking a course, as well as for those in need of a handy reference to this complex material. Biostatisticians—analysts of biological data—are charged with finding answers to some of the world's most pressing health questions: how safe or effective are drugs hitting the market today? What causes autism? What are the risk factors for cardiovascular disease? Are those risk factors different for men and women or different ethnic groups? Biostatistics For Dummies examines these and other questions associated with the study of biostatistics. Provides plain-English explanations of techniques and clinical examples to help Serves as an excellent course supplement for those struggling with the complexities of the biostatistics Tracks to a typical, introductory biostatistics course Biostatistics For Dummies is an excellent resource for anyone looking to succeed in this difficult course.

Download or read book Statistical Methods in the Atmospheric Sciences written by Daniel S. Wilks and published by Academic Press. This book was released on 2011-07-04 with total page 697 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Methods in the Atmospheric Sciences, Third Edition, explains the latest statistical methods used to describe, analyze, test, and forecast atmospheric data. This revised and expanded text is intended to help students understand and communicate what their data sets have to say, or to make sense of the scientific literature in meteorology, climatology, and related disciplines. In this new edition, what was a single chapter on multivariate statistics has been expanded to a full six chapters on this important topic. Other chapters have also been revised and cover exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, and time series analysis. There is now an expanded treatment of resampling tests and key analysis techniques, an updated discussion on ensemble forecasting, and a detailed chapter on forecast verification. In addition, the book includes new sections on maximum likelihood and on statistical simulation and contains current references to original research. Students will benefit from pedagogical features including worked examples, end-of-chapter exercises with separate solutions, and numerous illustrations and equations. This book will be of interest to researchers and students in the atmospheric sciences, including meteorology, climatology, and other geophysical disciplines. - Accessible presentation and explanation of techniques for atmospheric data summarization, analysis, testing and forecasting - Many worked examples - End-of-chapter exercises, with answers provided

Download or read book Handbook of High Frequency Trading and Modeling in Finance written by Ionut Florescu and published by John Wiley & Sons. This book was released on 2016-04-05 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reflecting the fast pace and ever-evolving nature of the financial industry, the Handbook of High-Frequency Trading and Modeling in Finance details how high-frequency analysis presents new systematic approaches to implementing quantitative activities with high-frequency financial data. Introducing new and established mathematical foundations necessary to analyze realistic market models and scenarios, the handbook begins with a presentation of the dynamics and complexity of futures and derivatives markets as well as a portfolio optimization problem using quantum computers. Subsequently, the handbook addresses estimating complex model parameters using high-frequency data. Finally, the handbook focuses on the links between models used in financial markets and models used in other research areas such as geophysics, fossil records, and earthquake studies. The Handbook of High-Frequency Trading and Modeling in Finance also features: • Contributions by well-known experts within the academic, industrial, and regulatory fields • A well-structured outline on the various data analysis methodologies used to identify new trading opportunities • Newly emerging quantitative tools that address growing concerns relating to high-frequency data such as stochastic volatility and volatility tracking; stochastic jump processes for limit-order books and broader market indicators; and options markets • Practical applications using real-world data to help readers better understand the presented material The Handbook of High-Frequency Trading and Modeling in Finance is an excellent reference for professionals in the fields of business, applied statistics, econometrics, and financial engineering. The handbook is also a good supplement for graduate and MBA-level courses on quantitative finance, volatility, and financial econometrics. Ionut Florescu, PhD, is Research Associate Professor in Financial Engineering and Director of the Hanlon Financial Systems Laboratory at Stevens Institute of Technology. His research interests include stochastic volatility, stochastic partial differential equations, Monte Carlo Methods, and numerical methods for stochastic processes. Dr. Florescu is the author of Probability and Stochastic Processes, the coauthor of Handbook of Probability, and the coeditor of Handbook of Modeling High-Frequency Data in Finance, all published by Wiley. Maria C. Mariani, PhD, is Shigeko K. Chan Distinguished Professor in Mathematical Sciences and Chair of the Department of Mathematical Sciences at The University of Texas at El Paso. Her research interests include mathematical finance, applied mathematics, geophysics, nonlinear and stochastic partial differential equations and numerical methods. Dr. Mariani is the coeditor of Handbook of Modeling High-Frequency Data in Finance, also published by Wiley. H. Eugene Stanley, PhD, is William Fairfield Warren Distinguished Professor at Boston University. Stanley is one of the key founders of the new interdisciplinary field of econophysics, and has an ISI Hirsch index H=128 based on more than 1200 papers. In 2004 he was elected to the National Academy of Sciences. Frederi G. Viens, PhD, is Professor of Statistics and Mathematics and Director of the Computational Finance Program at Purdue University. He holds more than two dozen local, regional, and national awards and he travels extensively on a world-wide basis to deliver lectures on his research interests, which range from quantitative finance to climate science and agricultural economics. A Fellow of the Institute of Mathematics Statistics, Dr. Viens is the coeditor of Handbook of Modeling High-Frequency Data in Finance, also published by Wiley.

Download or read book Statistical Bioinformatics with R written by Sunil K. Mathur and published by Academic Press. This book was released on 2009-12-21 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications. Designed for a one or two semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications. The inclusion of R & SAS code as well as the development of advanced methodology such as Bayesian and Markov models provides students with the important foundation needed to conduct bioinformatics. - Integrates biological, statistical and computational concepts - Inclusion of R & SAS code - Provides coverage of complex statistical methods in context with applications in bioinformatics - Exercises and examples aid teaching and learning presented at the right level - Bayesian methods and the modern multiple testing principles in one convenient book

Download or read book Detection Methods in Precision Medicine written by Mengsu Yang and published by Royal Society of Chemistry. This book was released on 2020-12-14 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will be among the first to cover the detection methods for precision medicine that are set to transform health care in the future.

Download or read book Lectures on Biostatistics An Introduction to Statistics With Applications in Biology and Medicine written by D. Colquhoun and published by David Colquhoun. This book was released on 1971 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Encyclopedia of Biopharmaceutical Statistics Four Volume Set written by Shein-Chung Chow and published by CRC Press. This book was released on 2018-09-03 with total page 2434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995.

Download or read book Combinatorial Library written by Lisa B. English and published by Springer Science & Business Media. This book was released on 2008-02-04 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The continued successes of large- and small-scale genome sequencing projects are increasing the number of genomic targets available for drug d- covery at an exponential rate. In addition, a better understanding of molecular mechanisms—such as apoptosis, signal transduction, telomere control of ch- mosomes, cytoskeletal development, modulation of stress-related proteins, and cell surface display of antigens by the major histocompatibility complex m- ecules—has improved the probability of identifying the most promising genomic targets to counteract disease. As a result, developing and optimizing lead candidates for these targets and rapidly moving them into clinical trials is now a critical juncture in pharmaceutical research. Recent advances in com- natorial library synthesis, purification, and analysis techniques are not only increasing the numbers of compounds that can be tested against each specific genomic target, but are also speeding and improving the overall processes of lead discovery and optimization. There are two main approaches to combinatorial library production: p- allel chemical synthesis and split-and-mix chemical synthesis. These approaches can utilize solid- or solution-based synthetic methods, alone or in combination, although the majority of combinatorial library synthesis is still done on solid support. In a parallel synthesis, all the products are assembled separately in their own reaction vessels or microtiter plates. The array of rows and columns enables researchers to organize the building blocks to be c- bined, and provides an easy way to identify compounds in a particular well.

Download or read book New insights of immune cells in cardiovascular and metabolic disorders written by Yingmei Feng and published by Frontiers Media SA. This book was released on 2023-10-26 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fuzzy Systems and Knowledge Discovery written by Lipo Wang and published by Springer. This book was released on 2006-09-28 with total page 1362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2006, held in federation with the Second International Conference on Natural Computation ICNC 2006. The book presents 115 revised full papers and 50 revised short papers. Coverage includes neural computation, quantum computation, evolutionary computation, DNA computation, fuzzy computation, granular computation, artificial life, innovative applications to knowledge discovery, finance, operations research, and more.