This volume contains a collection of papers dedicated to Professor Eckhard Platen to celebrate his 60th birthday, which occurred in 2009. The contributions have been written by a number of his colleagues and co-authors. All papers have been - viewed and presented as keynote talks at the international conference "Quantitative Methods in Finance" (QMF) in Sydney in December 2009. The QMF Conference Series was initiated by Eckhard Platen in 1993 when he was at the Australian - tional University (ANU) in Canberra. Since joining UTS in 1997 the conference came to be organised on a much larger scale and has grown to become a signi?cant international event in quantitative ?nance. Professor Platen has held the Chair of Quantitative Finance at the University of Technology, Sydney (UTS) jointly in the Faculties of Business and Science since 1997. Prior to this appointment, he was the Founding Head of the Centre for Fin- cial Mathematics at the Institute of Advanced Studies at ANU, a position to which he was appointed in 1994. Eckhard completed a PhD in Mathematics at the Technical University in Dresden in 1975 and in 1985 obtained his Doctor of Science degree (Habilitation degree in the German system) from the Academy of Sciences in Berlin where he headed the Stochastics group at the Weierstrass Institute.

This book assesses various intelligent-city evaluation systems around the globe, and subsequently combines that assessment with local-government and enterprise practices to create an evaluation index system for quantifying the Intelligent City concept. In addition, the book provides the results of the CityIQ indicator ranking of intelligent cities in China and worldwide, a system that focuses on three of the most crucial aspects of urban development: the development environment, future trends, and construction and operation. After data sorting, calculation and dimensionless treatment, a score system ranging from 0 to 100 is created for ranking and analyzing cities. Providing unique strategies for promoting an intelligent city evaluation system, the book offers a valuable reference guide for intelligent-city decision-makers, as well as leaders in public urban economy, social welfare and environmental authorities.

The series is designed to bring together those mathematicians who are seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking effective mathematical tools for their research. A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories.

The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate student (and the advanced undergraduate), best-selling author Sheldon Ross has developed the premier probability text for aspiring computer scientists involved in computer simulation and modeling. The math is precise and easily understood. As with his other texts, Sheldon Ross presents very clear explanations of concepts and covers those probability models that are most in demand by, and applicable to, computer science and related majors and practitioners.
Many interesting examples and exercises have been chosen to illuminate the techniques presented
Examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organising list problems, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queuing networks, distributed workload models, and many othersMany interesting examples and exercises have been chosen to illuminate the techniques presented

The problem of probability interpretation was long overlooked before exploding in the 20th century, when the frequentist and subjectivist schools formalized two conflicting conceptions of probability. Beyond the radical followers of the two schools, a circle of pluralist thinkers tends to reconcile the opposing concepts. The author uses two theorems in order to prove that the various interpretations of probability do come into opposition and can be used in different contexts. The goal here is to clarify the multi fold nature of probability by means of a purely mathematical approach and to show how philosophical arguments can only serve to deepen actual intellectual contrasts. The book can be considered as one of the most important contributions in the analysis of probability interpretation in the last 10-15 years.

One of the main aims of this book is to exhibit some fruitful links between renewal theory and regular variation of functions. Applications of renewal processes play a key role in actuarial and financial mathematics as well as in engineering, operations research and other fields of applied mathematics. On the other hand, regular variation of functions is a property that features prominently in many fields of mathematics. The structure of the book reflects the historical development of the authors' research work and approach - first some applications are discussed, after which a basic theory is created, and finally further applications are provided. The authors present a generalized and unified approach to the asymptotic behavior of renewal processes, involving cases of dependent inter-arrival times. This method works for other important functionals as well, such as first and last exit times or sojourn times (also under dependencies), and it can be used to solve several other problems. For example, various applications in function analysis concerning Abelian and Tauberian theorems can be studied as well as those in studies of the asymptotic behavior of solutions of stochastic differential equations. The classes of functions that are investigated and used in a probabilistic context extend the well-known Karamata theory of regularly varying functions and thus are also of interest in the theory of functions. The book provides a rigorous treatment of the subject and may serve as an introduction to the field. It is aimed at researchers and students working in probability, the theory of stochastic processes, operations research, mathematical statistics, the theory of functions, analytic number theory and complex analysis, as well as economists with a mathematical background. Readers should have completed introductory courses in analysis and probability theory.

This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.

Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical methodology who seek guidance in defending their statistical decision-making in the worlds of research and practice. It is devoted to helping students and scholars find the information they need to select data analytic methods, and to speak knowledgeably about their statistical research processes. Each chapter opens with a conundrum relating to the selection of an analysis, or to explaining the nature of an analysis. Throughout the chapter, the analysis is described, along with some guidance in justifying the choices of that particular method. Designed to offer statistical knowledge to the non-specialist, this volume can be used in courses on research methods, or for courses on statistical applications to biological, medical, life, social, or physical sciences. It will also be useful to academic and industrial researchers in engineering and in the physical sciences who will benefit from a stronger understanding of how to analyze empirical data. The book is written for those with foundational education in calculus. However, a brief review of fundamental concepts of probability and statistics, together with a primer on some concepts in elementary calculus and matrix algebra, is included. R code and sample datasets are provided.

Thisbookisintendedformolecularbiologistswhoperformquantitativeanalysesondata emanatingfromtheir?eldandforthestatisticianswhoworkwithmolecularbiologists andotherbiomedicalresearchers. Therearemanyexcellenttextbooksthatprovidefun- mentalcomponentsforstatisticaltrainingcurricula. Therearealsomany"byexpertsfor experts"booksinstatisticsandmolecularbiologywhichrequirein-depthknowledgein bothsubjectstobetakenfulladvantageof. Sofar,nobookinstatisticshasbeenpublished thatprovidesthebasicprinciplesofproperstatisticalanalysesandprogressestoamore advancedstatisticsinresponsetorapidlydevelopingtechnologiesandmethodologiesin the?eldofmolecularbiology. Respondingtothissituation,ourbookaimsatbridgingthegapbetweenthesetwo extremes. Molecularbiologistswillbene?tfromtheprogressivestyleofthebookwhere basicstatisticalmethodsareintroducedandgraduallyelevatedtoanintermediatelevel. Similarly,statisticianswillbene?tfromlearningthevariousbiologicaldatageneratedfrom the?eldofmolecularbiology,thetypesofquestionsofinteresttomolecularbiologists, andthestatisticalapproachestoanalyzingthedata. Thestatisticalconceptsandmethods relevanttostudiesinmolecularbiologyarepresentedinasimpleandpracticalmanner. Speci?cally,thebookcoversbasicandintermediatestatisticsthatareusefulforclassical and molecular biology settings and advanced statistical techniques that can be used to helpsolveproblemscommonlyencounteredinmodernmolecularbiologystudies,such assupervisedandunsupervisedlearning,hiddenMarkovmodels,manipulationandan- ysisofdatafromhigh-throughputmicroarrayandproteomicplatform,andsynthesisof these evidences. A tutorial-type format is used to maximize learning in some chapters. Advicefromjournaleditorsonpeer-reviewedpublicationandsomeusefulinformationon softwareimplementationarealsoprovided. Thisbookisrecommendedforuseassupplementarymaterialbothinsideandoutside classroomsorasaself-learningguideforstudents,scientists,andresearcherswhodealwith numericdatainmolecularbiologyandrelated?elds. Thosewhostartasbeginners,but desiretobeatanintermediatelevel,will?ndthisbookespeciallyusefulintheirlearning pathway. WewanttothankJohnWalker(serieseditor),PatrickMarton,DavidCasey,andAnne Meagher,(editorsatSpringerandHumana)andShanthyJaganathan(Integra-India). The followingpersonsprovidedusefuladviceandcommentsonselectionoftopics,referralto expertsineachtopic,and/orchapterreviewsthatwetrulyappreciate:StephenLooney(a former editor of this book), Stan Young, Dmitri Zaykin, Douglas Hawkins, Wei Pan, Alexandre Almeida, John Ho, Rebecca Doerge, Paula Trushin, Kevin Morgan, Jason Osborne,PeterWestfall,JennyXiang,Ya-linChiu,YolandaBarron,HuiboShao,Alvin Mushlin,andRonaldFanta. Drs. Bang,Zhou,andMazumdarwerepartiallysupported byClinicalTranslationalScienceCenter(CTSC)grant(UL1-RR024996). HeejungBang vii Contents Preface...vii Contributors...xi PARTIBASICSTATISTICS...1 1. ExperimentalStatisticsforBiologicalSciences...3 HeejungBangandMarieDavidian 2. NonparametricMethodsforMolecularBiology...105 KnutM. WittkowskiandTingtingSong 3. BasicsofBayesianMethods...155 SujitK. Ghosh 4. TheBayesiant-TestandBeyond ...179 MithatGonen PARTII DESIGNSANDMETHODSFORMOLECULARBIOLOGY...201 5. SampleSizeandPowerCalculationforMolecularBiologyStudies...203 Sin-HoJung 6. DesignsforLinkageAnalysisandAssociationStudiesofComplexDiseases...219 YuehuaCui,GengxinLi,ShaoyuLi,andRonglingWu 7. IntroductiontoEpigenomicsandEpigenome-WideAnalysis...243 MelissaJ. FazzariandJohnM. Greally 8. Exploration,Visualization,andPreprocessingofHigh-DimensionalData...267 ZhijinWuandZhiqiangWu PARTIII STATISTICALMETHODSFORMICROARRAYDATA ...285 9. IntroductiontotheStatisticalAnalysisofTwo-ColorMicroarrayData...287 MartinaBremer,EdwardHimelblau,andAndreasMadlung 10. BuildingNetworkswithMicroarrayData...315 BradleyM. Broom,WareeRinsurongkawong,LajosPusztai, andKim-AnhDo PARTIV ADVANCEDORSPECIALIZEDMETHODSFORMOLECULARBIOLOGY. . 345 11. SupportVectorMachinesforClassi?cation:AStatisticalPortrait...347 YoonkyungLee 12. AnOverviewofClusteringAppliedtoMolecularBiology ...369 RebeccaNugentandMarinaMeila ix xContents 13. HiddenMarkovModelandItsApplicationsinMotifFindings...405 JingWuandJunXie 14. DimensionReductionforHigh-DimensionalData...417 LexinLi 15. IntroductiontotheDevelopmentandValidationofPredictiveBiomarker ModelsfromHigh-ThroughputDataSets ...435 XutaoDengandFabienCampagne 16. Multi-geneExpression-basedStatisticalApproachestoPredicting Patients'ClinicalOutcomesandResponses...471 FengCheng,Sang-HoonCho,andJaeK. Lee 17. Two-StageTestingStrategiesforGenome-WideAssociationStudies inFamily-BasedDesigns ...485 AmyMurphy,ScottT. Weiss,andChristophLange 18. StatisticalMethodsforProteomics ...497 KlausJung PARTVMETA-ANALYSISFORHIGH-DIMENSIONALDATA ...509 19. StatisticalMethodsforIntegratingMultipleTypesofHigh-ThroughputData. . 511 YangXieandChulAhn 20. ABayesianHierarchicalModelforHigh-DimensionalMeta-analysis...531 FeiLiu 21. MethodsforCombiningMultipleGenome-WideLinkageStudies...541 TreciaA. KippolaandStephanieA. Santorico PARTVI OTHERPRACTICALINFORMATION ...561 22. ImprovedReportingofStatisticalDesignandAnalysis:Guidelines, Education,andEditorialPolicies...5 63 MadhuMazumdar,SampritBanerjee,andHeatherL. VanEpps 23. StataCompanion...599 JenniferSousaBrennan SubjectIndex...627 Contributors CHULAHN* Division of Biostatistics, Department of Clinical Sciences, The Harold C.

Long-rangedependent, or long-memory,time seriesarestationarytime series displaying a statistically signi?cant dependence between very distant obs- vations. We formalize this dependence by assuming that the autocorrelation function of these stationary series decays very slowly, hyperbolically, as a function of the time lag. Many economic series display these empirical features: volatility of asset prices returns, future interest rates, etc. There is a huge statistical literature on long-memory processes, some of this research is highly technical, so that it is cited, but often misused in the applied econometrics and empirical e- nomics literature. The ?rst purpose of this book is to present in a formal and pedagogical way some statistical methods for studying long-range dependent processes. Furthermore, the occurrence of long-memory in economic time series might be a statistical artefact as the hyperbolic decay of the sample autoc- relation function does not necessarily derive from long-range dependent p- cesses. Indeed, the realizations of non-homogeneous processes, e.g., switching regime and change-point processes, display the same empirical features. We thus also present in this book recent statistical methods able to discriminate between the long-memory and change-point alternatives. Going beyond the purely statistical analysis of economic series, it is of interest to determine which economic mechanisms are generating the strong dependence properties of economic series, whether they are genuine, or spu- ous. The regularities of the long-memory and change-point properties across economic time series, e.g., common degree of long-range dependence and/or common change-points, suggest the existence of a common economic cause.

Geostatistics is a common tool in reservoir characterization. Written from the basics of statistics, this book covers only those topics that are needed for the two goals of the text: to exhibit the diagnostic potential of statistics and to introduce the important features of statistical modelling. This revised edition contains expanded discussions of some materials, in particular conditional probabilities, Bayes Theorem, correlation, and Kriging. The coverage of estimation, variability, and modelling applications have been updated. Seventy examples illustrate concepts and show the role of geology for providing important information for data analysis and model building. Four reservoir case studies conclude the presentation, illustrating the application and importance of the earlier material. This book aims to help petroleum professionals develop more accurate models, leading to lower sampling costs. It is an ideal book for petroleum engineers, geoscientists, hydrologists, and faculty and students in these and related fields.

Now in its Seventh Edition, Neil J. Salkind's bestselling Statistics for People Who (Think They) Hate Statistics with new co-author Bruce B. Frey teaches an often intimidating subject with a humorous, personable, and informative approach that reduces statistics anxiety. With instruction in SPSS(R), the authors guide students through basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more. The Seventh Edition includes new real-world examples, additional coverage on multiple regression and power and effect size, and a robust interactive eBook with video tutorials and animations of key concepts. In the end, students who (think they) hate statistics will understand how to explain the results of many statistical analyses and won't be intimidated by basic statistical tasks.

This volume celebrates the tenth edition of the Brazilian School of Probability (EBP), held at IMPA, Rio de Janeiro, from July 30 to August 4, 2006, jointly with the 69th Annual Meeting of the Institute of Mathematical Statistics. It was indeed an exceptional occasion for the local community working in this ?eld. The EBP, ?rst envisioned and organized in 1997, has since developed into an annual meeting with two or three advanced mini-courses and a high level conference. This volume grew up from invited or contributed articles by researchers that during the last ten yearshave been participating in the BrazilianSchool of Pro- bility. As a consequence, its content partially re?ects the topics that have pred- inated in the activities during the various editions of the School, with a strong - peal that comes from statistical mechanics and areasof concentrationthat include interacting particlesystems, percolation, random media anddisordered systems. All articles of this volume were peer-refereed.

The most important properties of normal and Student t-distributions are presented. A number of applications of these properties are demonstrated. New related results dealing with the distributions of the sum, product and ratio of the independent normal and Student distributions are presented. The materials will be useful to the advanced undergraduate and graduate students and practitioners in the various fields of science and engineering.

Simulation is a controlled statistical sampling technique that can be used to study complex stochastic systems when analytic and/or numerical techniques do not suffice. The focus of this book is on simulations of discrete-event stochastic systems; namely, simulations in which stochastic state transitions occur only at an increasing sequence of random times. The discussion emphasizes simulations on a finite or countably infinite state space.
* Develops probabilistic methods for simulation of discrete-event stochastic systems
* Emphasizes stochastic modeling and estimation procedures based on limit theorems for regenerative stochastic processes
* Includes engineering applications of discrete-even simulation to computer, communication, manufacturing, and transportation systems
* Focuses on simulations with an underlying stochastic process that can specified as a generalized semi-Markov process
* Unique approach to simulation, with heavy emphasis on stochastic modeling
* Includes engineering applications for computer, communication, manufacturing, and transportation systems

The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses. The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources. The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.

A careful basic theoretical and econometric analysis of the factors determining the real exchange rates of Canada, the U.K., Japan, France and Germany with respect to the United States is conducted. The resulting conclusion is that real exchange rates are almost entirely determined by real factors relating to growth and technology such as oil and commodity prices, international allocations of world investment across countries, and underlying terms of trade changes. Unanticipated money supply shocks, calculated in five alternative ways have virtually no effects. A Blanchard-Quah VAR analysis also indicates that the effects of real shocks predominate over monetary shocks by a wide margin. The implications of these facts for the conduct of monetary policy in countries outside the U.S. are then explored leading to the conclusion that all countries, to avoid exchange rate overshooting, have tended to automatically follow the same monetary policy as the United States. The history of world monetary policy is reviewed along with the determination of real exchange rates within the Euro Area.

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.

This book was written for those who need to know how to collect, analyze and present data. It is meant to be a first course for practitioners, a book for private study or brush-up on statistics, and supplementary reading for general statistics classes. The book is untraditional, both with respect to the choice of topics and the presentation: Topics were determined by what is most useful for practical statistical work, and the presentation is as non-mathematical as possible. The book contains many examples using statistical functions in spreadsheets. In this second edition, new topics have been included e.g. within the area of statistical quality control, in order to make the book even more useful for practitioners working in industry.

This volume, dedicated to Carl Pearcy on the occasion of his 60th birthday, presents recent results in operator theory, nonselfadjoint operator algebras, measure theory and the theory of moments. The articles on these subjects have been contributed by leading area experts, many of whom were associated with Carl Pearcy as students or collaborators. The book testifies to his multifaceted interests and includes a biographical sketch and a list of publications.

A Problem Solving Approach Now available with Macmillan's Achieve, Introductory Statistics helps students develop the fundamental lifelong skill of solving problems and interpreting solutions in real-world terms. One of our goals was to make this problem-solving approach accessible and easy to apply in many situations. We certainly want students to appreciate the beauty of statistics and connections to so many other disciplines. However, it is even more important for students to be able to apply problem-solving skills to a wide range of academic and career pursuits, including business, science and technology, and education. Achieve for Introductory Statistics connects the problem-solving approach and real-world examples in the book to rich digital resources that foster further understanding and application of statistics. Assets in Achieve support learning before, during, and after class for students, while providing instructors with class performance analytics in an easy-to-use interface.

In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Ito integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view.
The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations."

This book reports a literature review on kaizen, its industrial applications, critical success factors, benefits gained, journals that publish about it, main authors (research groups) and universities. Kaizen is treated in this book in three stages: planning, implementation and control. The authors provide a questionnaire designed with activities in every stage, highlighting the benefits gained in each stage. The study has been applied to more than 400 managers and leaders in continuous improvement in Mexican maquiladoras. A univariate analysis is provided to the activities in every stage. Moreover, structural equation models associating those activities with the benefits gained are presented for a statistical validation. Such a relationship between activities and benefits helps managers to identify the most important factor affecting their benefits and financial income.

This book focuses on a development for assessing mental changes using eye pupil reactions, namely extracting emotional change from the response to evaluate the viewer's interest in visual information. The pupil of the eye reacts to both brightness and emotional state, including interest, enjoyment, and mental workload. Because pupillary change is a biological signal, various artifacts influence measurements of eye images. Technical procedures are required to extract mental activities from pupillary changes, and they are summarized here step by step, although some procedures contain earlier techniques such as analog video processing. This study examines the possibility of estimating the viewer's interest and enjoyment of viewing movies by measuring the dynamic pupillary changes, blinking, and subjective interest responses. In evaluation of pupil size, there was a significant difference in pupil size between the higher and the lower shot for the degree of subject interest response in each kind of movies. The first part of the book shows a pupil reaction model for brightness changes to extract mental activities. Pupil reactions were observed for various visual stimuli in brightness changes. With regard to the characteristics of pupillary changes, a model with a three-layer neural network was developed and the performance was evaluated. Characteristics of pupil reactions during model development are summarized here. The second part examines the possibility of estimating the viewer's interest and enjoyment of television programs by measuring dynamic pupillary changes, blinking, and subjective interest responses. The final part describes a development of estimation model of pupil size for blink artifact. The model development was able to estimate pupillary changes and pupil size while the viewer was blinking and was applied to pupillary changes in viewing television programs.