Semimartingales And Their Statistical Inference
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Semimartingales And Their Statistical Inference
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Author : B.L.S. Prakasa Rao
language : en
Publisher: CRC Press
Release Date : 1999-05-11
Semimartingales And Their Statistical Inference written by B.L.S. Prakasa Rao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-11 with Mathematics categories.
Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class of stochastic processes, including diffusion type processes, point processes, and diffusion type processes with jumps, widely used for stochastic modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. The author brings together into one volume the state-of-the-art in the inferential aspect for such processes. The topics discussed include: Asymptotic likelihood theory Quasi-likelihood Likelihood and efficiency Inference for counting processes Inference for semimartingale regression models The author addresses a number of stochastic modeling applications from engineering, economic systems, financial economics, and medical sciences. He also includes some of the new and challenging statistical and probabilistic problems facing today's active researchers working in the area of inference for stochastic processes.
Semimartingales And Their Statistical Inference
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Author : B.L.S. Prakasa Rao
language : en
Publisher: Routledge
Release Date : 2019-01-15
Semimartingales And Their Statistical Inference written by B.L.S. Prakasa Rao and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-15 with Mathematics categories.
Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class of stochastic processes, including diffusion type processes, point processes, and diffusion type processes with jumps, widely used for stochastic modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. The author brings together into one volume the state-of-the-art in the inferential aspect for such processes. The topics discussed include: Asymptotic likelihood theory Quasi-likelihood Likelihood and efficiency Inference for counting processes Inference for semimartingale regression models The author addresses a number of stochastic modeling applications from engineering, economic systems, financial economics, and medical sciences. He also includes some of the new and challenging statistical and probabilistic problems facing today's active researchers working in the area of inference for stochastic processes.
Stochastic Analysis For Gaussian Random Processes And Fields
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Author : Vidyadhar S. Mandrekar
language : en
Publisher: CRC Press
Release Date : 2015-06-23
Stochastic Analysis For Gaussian Random Processes And Fields written by Vidyadhar S. Mandrekar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-23 with Mathematics categories.
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).The book begins with preliminary results on covariance and associated RKHS
Asymptotic Analysis Of Mixed Effects Models
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Author : Jiming Jiang
language : en
Publisher: CRC Press
Release Date : 2017-09-19
Asymptotic Analysis Of Mixed Effects Models written by Jiming Jiang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-19 with Mathematics categories.
Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models. The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book for a graduate-level course on mixed effects models, or asymptotic analysis.
State Space Methods For Time Series Analysis
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Author : Jose Casals
language : en
Publisher: CRC Press
Release Date : 2018-09-03
State Space Methods For Time Series Analysis written by Jose Casals and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.
The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.
Data Analysis And Approximate Models
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Author : Patrick Laurie Davies
language : en
Publisher: CRC Press
Release Date : 2014-07-07
Data Analysis And Approximate Models written by Patrick Laurie Davies and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-07 with Mathematics categories.
The First Detailed Account of Statistical Analysis That Treats Models as Approximations The idea of truth plays a role in both Bayesian and frequentist statistics. The Bayesian concept of coherence is based on the fact that two different models or parameter values cannot both be true. Frequentist statistics is formulated as the problem of estimating the "true but unknown" parameter value that generated the data. Forgoing any concept of truth, Data Analysis and Approximate Models: Model Choice, Location-Scale, Analysis of Variance, Nonparametric Regression and Image Analysis presents statistical analysis/inference based on approximate models. Developed by the author, this approach consistently treats models as approximations to data, not to some underlying truth. The author develops a concept of approximation for probability models with applications to: Discrete data Location scale Analysis of variance (ANOVA) Nonparametric regression, image analysis, and densities Time series Model choice The book first highlights problems with concepts such as likelihood and efficiency and covers the definition of approximation and its consequences. A chapter on discrete data then presents the total variation metric as well as the Kullback–Leibler and chi-squared discrepancies as measures of fit. After focusing on outliers, the book discusses the location-scale problem, including approximation intervals, and gives a new treatment of higher-way ANOVA. The next several chapters describe novel procedures of nonparametric regression based on approximation. The final chapter assesses a range of statistical topics, from the likelihood principle to asymptotics and model choice.
Hierarchical Modeling And Analysis For Spatial Data
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Author : Sudipto Banerjee
language : en
Publisher: CRC Press
Release Date : 2014-09-12
Hierarchical Modeling And Analysis For Spatial Data written by Sudipto Banerjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-12 with Mathematics categories.
Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and ModelingSince the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflec
Sequential Analysis
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Author : Alexander Tartakovsky
language : en
Publisher: CRC Press
Release Date : 2014-08-27
Sequential Analysis written by Alexander Tartakovsky and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-27 with Mathematics categories.
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 detecti
Design And Analysis Of Cross Over Trials Third Edition
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Author : Byron Jones
language : en
Publisher: CRC Press
Release Date : 2014-10-08
Design And Analysis Of Cross Over Trials Third Edition written by Byron Jones and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-08 with Mathematics categories.
Design and Analysis of Cross-Over Trials is concerned with a specific kind of comparative trial known as the cross-over trial, in which subjects receive different sequences of treatments. Such trials are widely used in clinical and medical research, and in other diverse areas such as veterinary science, psychology, sports science, and agriculture. The first edition of this book was the first to be wholly devoted to the subject. The second edition was revised to mirror growth and development in areas where the design remained in widespread use and new areas where it had grown in importance. This new Third Edition: Contains seven new chapters written in the form of short case studies that address re-estimating sample size when testing for average bioequivalence, fitting a nonlinear dose response function, estimating a dose to take forward from phase two to phase three, establishing proof of concept, and recalculating the sample size using conditional power Employs the R package Crossover, specially created to accompany the book and provide a graphical user interface for locating designs in a large catalog and for searching for new designs Includes updates regarding the use of period baselines and the analysis of data from very small trials Reflects the availability of new procedures in SAS, particularly proc glimmix Presents the SAS procedure proc mcmc as an alternative to WinBUGS for Bayesian analysis Complete with real data and downloadable SAS code, Design and Analysis of Cross-Over Trials, Third Edition provides a practical understanding of the latest methods along with the necessary tools for implementation.
Analysis Of Variance For Functional Data
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Author : Jin-Ting Zhang
language : en
Publisher: CRC Press
Release Date : 2013-06-18
Analysis Of Variance For Functional Data written by Jin-Ting Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-18 with Mathematics categories.
Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional l