Micro and Macro Data in Statistical Inference on Markov Chains

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Publisher :
ISBN 13 :
Total Pages : 240 pages
Book Rating : 4.:/5 (42 download)

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Book Synopsis Micro and Macro Data in Statistical Inference on Markov Chains by : Gunnar Rosenqvist

Download or read book Micro and Macro Data in Statistical Inference on Markov Chains written by Gunnar Rosenqvist and published by . This book was released on 1986 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Inference from Stochastic Processes

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Publisher : American Mathematical Soc.
ISBN 13 : 0821850873
Total Pages : 406 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Statistical Inference from Stochastic Processes by : Narahari Umanath Prabhu

Download or read book Statistical Inference from Stochastic Processes written by Narahari Umanath Prabhu and published by American Mathematical Soc.. This book was released on 1988 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. This book provides students and researchers with a familiarity with the foundations of inference from stochastic processes and intends to provide a knowledge of the developments.

Statistical Inference for Discrete Time Stochastic Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 8132207637
Total Pages : 121 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Statistical Inference for Discrete Time Stochastic Processes by : M. B. Rajarshi

Download or read book Statistical Inference for Discrete Time Stochastic Processes written by M. B. Rajarshi and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is an overview of statistical inference in stationary, discrete time stochastic processes. Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis have been reviewed. The first chapter gives a background of results on martingales and strong mixing sequences, which enable us to generate various classes of CAN estimators in the case of dependent observations. Topics discussed include inference in Markov chains and extension of Markov chains such as Raftery's Mixture Transition Density model and Hidden Markov chains and extensions of ARMA models with a Binomial, Poisson, Geometric, Exponential, Gamma, Weibull, Lognormal, Inverse Gaussian and Cauchy as stationary distributions. It further discusses applications of semi-parametric methods of estimation such as conditional least squares and estimating functions in stochastic models. Construction of confidence intervals based on estimating functions is discussed in some detail. Kernel based estimation of joint density and conditional expectation are also discussed. Bootstrap and other resampling procedures for dependent sequences such as Markov chains, Markov sequences, linear auto-regressive moving average sequences, block based bootstrap for stationary sequences and other block based procedures are also discussed in some detail. This work can be useful for researchers interested in knowing developments in inference in discrete time stochastic processes. It can be used as a material for advanced level research students.

Efficient Learning Machines

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Publisher : Apress
ISBN 13 : 1430259906
Total Pages : 263 pages
Book Rating : 4.4/5 (32 download)

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Book Synopsis Efficient Learning Machines by : Mariette Awad

Download or read book Efficient Learning Machines written by Mariette Awad and published by Apress. This book was released on 2015-04-27 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.

Statistical Methods for Survival Data Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 0471458554
Total Pages : 527 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Statistical Methods for Survival Data Analysis by : Elisa T. Lee

Download or read book Statistical Methods for Survival Data Analysis written by Elisa T. Lee and published by John Wiley & Sons. This book was released on 2003-08-01 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Third Edition brings the text up to date with new material and updated references. New content includes an introduction to left and interval censored data; the log-logistic distribution; estimation procedures for left and interval censored data; parametric methods iwth covariates; Cox's proportional hazards model (including stratification and time-dependent covariates); and multiple responses to the logistic regression model. Coverage of graphical methods has been deleted. Large data sets are provided on an FTP site for readers' convenience. Bibliographic remarks conclude each chapter.

Point Processes and Their Statistical Inference

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Publisher : Routledge
ISBN 13 : 1351423835
Total Pages : 509 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Point Processes and Their Statistical Inference by : Alan Karr

Download or read book Point Processes and Their Statistical Inference written by Alan Karr and published by Routledge. This book was released on 2017-09-06 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maintaining the excellent features that made the first edition so popular, this outstanding reference/text presents the only comprehensive treatment of the theory of point processes and statistical inference for point processes-highlighting both pointprocesses on the real line and sp;,.tial point processes. Thoroughly updated and revised to reflect changes since publication of the firstedition, the expanded Second EdiLion now contains a better organized and easierto-understand treatment of stationary point processes ... expanded treatment ofthe multiplicative intensity model ... expanded treatment of survival analysis . ..broadened consideration of applications ... an expanded and extended bibliographywith over 1,000 references ... and more than 3('() end-of-chapter exercises.

Statistical Inferences for Stochasic Processes

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Publisher : Elsevier
ISBN 13 : 1483296148
Total Pages : 455 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Statistical Inferences for Stochasic Processes by : Ishwar V. Basawa

Download or read book Statistical Inferences for Stochasic Processes written by Ishwar V. Basawa and published by Elsevier. This book was released on 2014-06-28 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stats Inference Stochasic Process

Hilbert Space Methods in Probability and Statistical Inference

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Publisher : John Wiley & Sons
ISBN 13 : 1118165535
Total Pages : 268 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Hilbert Space Methods in Probability and Statistical Inference by : Christopher G. Small

Download or read book Hilbert Space Methods in Probability and Statistical Inference written by Christopher G. Small and published by John Wiley & Sons. This book was released on 2011-09-15 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory of martingales stochastic integration, interpolation and density estimation. Includes a copious amount of problems and examples.

Statistical Inference for Piecewise-deterministic Markov Processes

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Publisher : John Wiley & Sons
ISBN 13 : 1119544033
Total Pages : 279 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Statistical Inference for Piecewise-deterministic Markov Processes by : Romain Azais

Download or read book Statistical Inference for Piecewise-deterministic Markov Processes written by Romain Azais and published by John Wiley & Sons. This book was released on 2018-07-31 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple yet challenging models to study. Nevertheless, the issue of statistical estimation of the parameters ruling the jump mechanism is far from trivial. Responding to new developments in the field as well as to current research interests and needs, Statistical inference for piecewise-deterministic Markov processes offers a detailed and comprehensive survey of state-of-the-art results. It covers a wide range of general processes as well as applied models. The present book also dwells on statistics in the context of Markov chains, since piecewise-deterministic Markov processes are characterized by an embedded Markov chain corresponding to the position of the process right after the jumps.

Stochastic Epidemic Models with Inference

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Publisher : Springer Nature
ISBN 13 : 3030309002
Total Pages : 477 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Stochastic Epidemic Models with Inference by : Tom Britton

Download or read book Stochastic Epidemic Models with Inference written by Tom Britton and published by Springer Nature. This book was released on 2019-11-30 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.

Statistical Analysis of Stochastic Processes in Time

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Publisher : Cambridge University Press
ISBN 13 : 9781139454513
Total Pages : 356 pages
Book Rating : 4.4/5 (545 download)

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Book Synopsis Statistical Analysis of Stochastic Processes in Time by : J. K. Lindsey

Download or read book Statistical Analysis of Stochastic Processes in Time written by J. K. Lindsey and published by Cambridge University Press. This book was released on 2004-08-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was first published in 2004. Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time: stochastic processes are designed to study them. This book introduces practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics. It covers almost all aspects of the subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes. Software (available from www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.

The Econometrics of Panel Data

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Publisher : Springer Science & Business Media
ISBN 13 : 9400901372
Total Pages : 944 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis The Econometrics of Panel Data by : László Mátyás

Download or read book The Econometrics of Panel Data written by László Mátyás and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this volume is to provide a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Edwin Kuh (1959), Yair Mundlak (1961), Irving Hoch (1962), and Pietro Balestra and Marc Nerlove (1966), the pooling of cross sections and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Over the last 30 years much work has been done: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific diffi culties associated with the use of panel data, such as attrition, heterogeneity, selectivity bias, pseudo panels etc., have also been explored. The first objective of this book, which takes up Parts I and II, is to give as complete and up-to-date a presentation of these theoretical developments as possible. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and pro bit models, latent variable models, duration and count data models, incomplete panels and selectivity bias, point processes, and simulation techniques.

Statistical Inference and Simulation for Spatial Point Processes

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Publisher : CRC Press
ISBN 13 : 9780203496930
Total Pages : 320 pages
Book Rating : 4.4/5 (969 download)

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Book Synopsis Statistical Inference and Simulation for Spatial Point Processes by : Jesper Moller

Download or read book Statistical Inference and Simulation for Spatial Point Processes written by Jesper Moller and published by CRC Press. This book was released on 2003-09-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.

COMPARISON OF INFERENCE TECHNIQUES FOR MARKOV PROCESS ESTIMATED FROM MICRO VS. MACRO DATA

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Publisher :
ISBN 13 :
Total Pages : 20 pages
Book Rating : 4.L/5 ( download)

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Book Synopsis COMPARISON OF INFERENCE TECHNIQUES FOR MARKOV PROCESS ESTIMATED FROM MICRO VS. MACRO DATA by : Christina M.L. Kelton, W. David Kelton

Download or read book COMPARISON OF INFERENCE TECHNIQUES FOR MARKOV PROCESS ESTIMATED FROM MICRO VS. MACRO DATA written by Christina M.L. Kelton, W. David Kelton and published by . This book was released on with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Inference in Hidden Markov Models

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Publisher : Springer Science & Business Media
ISBN 13 : 0387289828
Total Pages : 656 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Inference in Hidden Markov Models by : Olivier Cappé

Download or read book Inference in Hidden Markov Models written by Olivier Cappé and published by Springer Science & Business Media. This book was released on 2006-04-12 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.

Handbook of Income Inequality Measurement

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Publisher : Springer Science & Business Media
ISBN 13 : 9401144133
Total Pages : 669 pages
Book Rating : 4.4/5 (11 download)

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Book Synopsis Handbook of Income Inequality Measurement by : Jacques Silber

Download or read book Handbook of Income Inequality Measurement written by Jacques Silber and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amartya Sen "Equality," I spoke the word As if a wedding vow Ah, but I was so much older then, I am younger than that now. Thus sang Bob Dylan in 1964. Approbation of equality varies not only with our age (though it is not absolutely clear in which direction the values may shift over one's life time), but also with the spirit of the times. The 1960s were good years for singing in praise of equality. The spirit of the present times would probably be better reflected by melodies in admiration of the Federal Reserve System. And yet the technical literature on the evaluation and measurement of economic inequality has grown remarkably over the last three decades. Even as actual economic policies (especially in North America and Europe) have tended to move towards focusing on virtues other than the avoidance of economic inequality, the professional literature on assessing and gauging economic inequality has taken quite a jump forward. A great many different problems have been addressed and effectively sorted out, and new problems continue to be posed and analyzed. The Contents: A Review Jacques Silber has done a great service to the subject by producing this collection of admirablyhelpful and illuminating papers on different aspects of the measurement of income inequality. The reach of this collection is quite remarkable. Along with a thorough overview from the editor himself, the major areas in this complex field have been carefully examined and accessibly discussed.

GARCH Models

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Publisher : John Wiley & Sons
ISBN 13 : 1119957397
Total Pages : 469 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis GARCH Models by : Christian Francq

Download or read book GARCH Models written by Christian Francq and published by John Wiley & Sons. This book was released on 2011-06-24 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation and tests. The book also provides coverage of several extensions such as asymmetric and multivariate models and looks at financial applications. Key features: Provides up-to-date coverage of the current research in the probability, statistics and econometric theory of GARCH models. Numerous illustrations and applications to real financial series are provided. Supporting website featuring R codes, Fortran programs and data sets. Presents a large collection of problems and exercises. This authoritative, state-of-the-art reference is ideal for graduate students, researchers and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.