Top 9 recommendation sequential analysis 2022
When you looking for sequential analysis, you must consider not only the quality but also price and customer reviews. But among hundreds of product with different price range, choosing suitable sequential analysis is not an easy task. In this post, we show you how to find the right sequential analysis along with our top-rated reviews. Please check out our suggestions to find the best sequential analysis for you.
1. Sequential Analysis: Hypothesis Testing and Changepoint Detection (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
Description
Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results can be used efficiently.
The book reviews recent accomplishments in hypothesis testing and changepoint detection both in decision-theoretic (Bayesian) and non-decision-theoretic (non-Bayesian) contexts. The authors not only emphasize traditional binary hypotheses but also substantially more difficult multiple decision problems. They address scenarios with simple hypotheses and more realistic cases of two and finitely many composite hypotheses. The book primarily focuses on practical discrete-time models, with certain continuous-time models also examined when general results can be obtained very similarly in both cases. It treats both conventional i.i.d. and general non-i.i.d. stochastic models in detail, including Markov, hidden Markov, state-space, regression, and autoregression models. Rigorous proofs are given for the most important results.
Written by leading authorities in the field, this book covers the theoretical developments and applications of sequential hypothesis testing and sequential quickest changepoint detection in a wide range of engineering and environmental domains. It explains how the theoretical aspects influence the hypothesis testing and changepoint detection problems as well as the design of algorithms.
2. Sequential Analysis
Description
In 1943, while in charge of Columbia University's Statistical Research Group, Abraham Wald devised Sequential Design, an innovative statistical inference system. Because the decision to terminate an experiment is not predetermined, sequential analysis can arrive at a decision much sooner and with substantially fewer observations than equally reliable test procedures based on a predetermined number of observations. The system's immense value was immediately recognized, and its use was restricted to wartime research and procedures. In 1945, it was released to the public and has since revolutionized many aspects of statistical practice.
This book is Professor Wald's own description of the system. Part I contains a discussion of the general theory of the sequential probability ratio test, with comparisons to traditional statistical inference systems. Part II discusses applications that illustrate the general theory and raise points of theoretical interest specific to these applications. Part III outlines a possible approach to the problem of sequential multi-valued decisions and estimation. All three sections can be understood by readers with only a background in college algebra and a first course in calculus. Mathematical derivations of somewhat intricate nature appear in the appendix.
Sequential Analysis offers statistical researchers a time- and money-saving approach, introduces students to one of the major systems in contemporary use, and presents those already acquainted with the system with valuable background information.
3. Sequential Analysis and Observational Methods for the Behavioral Sciences
Description
Behavioral scientists - including those in psychology, infant and child development, education, animal behavior, marketing, and usability studies - use many methods to measure behavior. Systematic observation is used to study relatively natural, spontaneous behavior as it unfolds sequentially in time. This book emphasizes digital means to record and code such behavior; while observational methods do not require them, they work better with them. Key topics include devising coding schemes, training observers, and assessing reliability, as well as recording, representing, and analyzing observational data. In clear and straightforward language, this book provides a thorough grounding in observational methods along with considerable practical advice. It describes standard conventions for sequential data and details how to perform sequential analysis with a computer program developed by the authors. The book is rich with examples of coding schemes and different approaches to sequential analysis, including both statistical and graphical means.4. Sequential Analysis: Tests and Confidence Intervals (Springer Series in Statistics)
Description
The modern theory of Sequential Analysis came into existence simultaneously in the United States and Great Britain in response to demands for more efficient sampling inspection procedures during World War II. The develop ments were admirably summarized by their principal architect, A. Wald, in his book Sequential Analysis (1947). In spite of the extraordinary accomplishments of this period, there remained some dissatisfaction with the sequential probability ratio test and Wald's analysis of it. (i) The open-ended continuation region with the concomitant possibility of taking an arbitrarily large number of observations seems intol erable in practice. (ii) Wald's elegant approximations based on "neglecting the excess" of the log likelihood ratio over the stopping boundaries are not especially accurate and do not allow one to study the effect oftaking observa tions in groups rather than one at a time. (iii) The beautiful optimality property of the sequential probability ratio test applies only to the artificial problem of testing a simple hypothesis against a simple alternative. In response to these issues and to new motivation from the direction of controlled clinical trials numerous modifications of the sequential probability ratio test were proposed and their properties studied-often by simulation or lengthy numerical computation. (A notable exception is Anderson, 1960; see III.7.) In the past decade it has become possible to give a more complete theoretical analysis of many of the proposals and hence to understand them better.5. Sequential Statistics
Description
This book contains topics that can be covered in a single-semester course. Only elementary proofs are provided, and thus the mathematics and statistics are maintained at a basic level. Only a course in each of three areas advanced calculus, probability and statistical inference is assumed of the student. The book has a chapter on applications to biostatistics and a supplement presenting computer programs for selected sequential procedures. Identified problems are provided at the end of each chapter.6. Sequential Analysis and Optimal Design (CBMS-NSF Regional Conference Series in Applied Mathematics)
Description
An exploration of the interrelated fields of design of experiments and sequential analysis with emphasis on the nature of theoretical statistics and how this relates to the philosophy and practice of statistics.7. Observing Interaction: An Introduction to Sequential Analysis
Feature
Used Book in Good ConditionDescription
Mothers and infants exchanging gleeful vocalizations, married couples discussing their problems, children playing, birds courting, and monkeys fighting all have this in common: their interactions unfold over time. Almost anyone who is interested can observe and describe such phenomena. However, scientists usually demand more than a desription--they want observations that are replicable and amenable to scientific analysis, while still faithful to the dynamics of the phenomena studied. This book provides a straightforward introduction to scientific methods for observing social behavior. The second edition clarifies and extends material from the first edition, especially with respect to data analysis. A common standard for sequential data is introduced and sequential analysis is placed on firmer, log-linear statistical footing. The second edition is designed to work as a companion volume to Analyzing Interaction (1995). Because of the importance of time in the dynamics of social interaction, sequential approaches to analyzing and understanding social behavior are emphasized. An advanced knowledge of statistical analysis is not required. Instead, the authors present fundamental concepts and offer practical advice.8. Statistical Design and Analysis of Clinical Trials: Principles and Methods (Chapman & Hall/CRC Biostatistics Series)
Description
Statistical Design and Analysis of Clinical Trials: Principles and Methods concentrates on the biostatistics component of clinical trials. Developed from the authors courses taught to public health and medical students, residents, and fellows during the past 15 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods.
Teach Your Students How to Design, Monitor, and Analyze Clinical Trials
The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, explain the concept of different missing data processes, and describe how to analyze incomplete data by proper multiple imputations.
Turn Your Students into Better Clinical Trial Investigators
This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students a multidisciplinary understanding of the concepts and techniques involved in designing and analyzing various types of trials. The books balanced set of homework assignments and in-class exercises are appropriate for students in (bio)statistics, epidemiology, medicine, pharmacy, and public health.
9. Sequence Learning: Paradigms, Algorithms, and Applications (Lecture Notes in Computer Science)
Recent Comments