Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download An Mcem Algorithm For The State Space Model With Missing Observations full books in PDF, epub, and Kindle. Read online An Mcem Algorithm For The State Space Model With Missing Observations ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Damaris Santana
Publisher :
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.E/5 ( download)
Download or read book An MCEM Algorithm for the State-space Model with Missing Observations written by Damaris Santana and published by . This book was released on 2001 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Luigi Ippoliti
Publisher :
ISBN 13 :
Total Pages : 11 pages
Book Rating : 4.:/5 (955 download)
Download or read book State space model and smoothing algorithm to solve a missing data problem in spatial temporal series written by Luigi Ippoliti and published by . This book was released on 1998 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Tianni Zhou
Publisher :
ISBN 13 :
Total Pages : 192 pages
Book Rating : 4.:/5 (65 download)
Download or read book Approximate EM Algorithms for State Space Models with Markov Regime Changes written by Tianni Zhou and published by . This book was released on 2002 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Olivier Cappé
Publisher : Springer Science & Business Media
ISBN 13 : 0387289828
Total Pages : 656 pages
Book Rating : 4.3/5 (872 download)
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.
Author : Peter J. Brockwell
Publisher : Springer
ISBN 13 : 3319298542
Total Pages : 428 pages
Book Rating : 4.3/5 (192 download)
Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer. This book was released on 2016-08-19 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered. New to this edition: A chapter devoted to Financial Time Series Introductions to Brownian motion, Lévy processes and Itô calculus An expanded section on continuous-time ARMA processes
Author : Craig Joseph Johns
Publisher :
ISBN 13 :
Total Pages : 250 pages
Book Rating : 4.:/5 (59 download)
Download or read book Estimation of Nonlinear State-space Models in the Presence of Censored Observations written by Craig Joseph Johns and published by . This book was released on 1999 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter X. -K. Song
Publisher : Springer Science & Business Media
ISBN 13 : 038771393X
Total Pages : 352 pages
Book Rating : 4.3/5 (877 download)
Download or read book Correlated Data Analysis: Modeling, Analytics, and Applications written by Peter X. -K. Song and published by Springer Science & Business Media. This book was released on 2007-06-30 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.
Author : Nawaz Mohamudally
Publisher : IntechOpen
ISBN 13 : 9535137425
Total Pages : 182 pages
Book Rating : 4.5/5 (351 download)
Download or read book Time Series Analysis and Applications written by Nawaz Mohamudally and published by IntechOpen. This book was released on 2018-01-24 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time Series Analysis (TSA) and Applications offers a dense content of current research and development in the field of data science. The book presents time series from a multidisciplinary approach that covers a wide range of sectors ranging from biostatistics to renewable energy forecasting. Contrary to previous literatures on time, serious readers will discover the potential of TSA in areas other than finance or weather forecasting. The choice of the algorithmic transform for different scenarios, which is a key determinant in the application of TSA, can be understood through the diverse domain applications. Readers looking for deep understanding and practicability of TSA will be delighted. Early career researchers too will appreciate the technicalities and refined mathematical complexities surrounding TSA. Our wish is that this book adds to the body of TSA knowledge and opens up avenues for those who are looking forward to applying TSA in their own context.
Author : David Barber
Publisher : Cambridge University Press
ISBN 13 : 0521196760
Total Pages : 432 pages
Book Rating : 4.5/5 (211 download)
Download or read book Bayesian Time Series Models written by David Barber and published by Cambridge University Press. This book was released on 2011-08-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.
Author : Roger Payne
Publisher : Springer Science & Business Media
ISBN 13 : 366201131X
Total Pages : 508 pages
Book Rating : 4.6/5 (62 download)
Download or read book COMPSTAT written by Roger Payne and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Volume contains the Keynote, Invited and Full Contributed papers presented at COMPSTAT'98. A companion volume (Payne & Lane, 1998) contains papers describing the Short Communications and Posters. COMPSTAT is a one-week conference held every two years under the auspices of the International Association of Statistical Computing, a section of the International Statistical Institute. COMPSTAT'98 is organised by IACR-Rothamsted, IACR-Long Ashton, the University of Bristol Department of Mathematics and the University of Bath Department of Mathematical Sciences. It is taking place from 24-28 August 1998 at University of Bristol. Previous COMPSTATs (from 1974-1996) were in Vienna, Berlin, Leiden, Edinburgh, Toulouse, Prague, Rome, Copenhagen, Dubrovnik, Neuchatel, Vienna and Barcelona. The conference is the main European forum for developments at the interface between statistics and computing. This was encapsulated as follows in the COMPSTAT'98 Call for Papers. Statistical computing provides the link between statistical theory and applied statistics. The scientific programme of COMPSTAT ranges over all aspects of this link, from the development and implementation of new computer-based statistical methodology through to innovative applications and software evaluation. The programme should appeal to anyone working in statistics and using computers, whether in universities, industrial companies, research institutes or as software developers.
Author : Konstantinos Fokianos
Publisher : CRC Press
ISBN 13 : 9781482248050
Total Pages : 220 pages
Book Rating : 4.2/5 (48 download)
Download or read book Count Time Series written by Konstantinos Fokianos and published by CRC Press. This book was released on 2020-06-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)
Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Author : Subir Ghosh
Publisher : CRC Press
ISBN 13 : 9780824700515
Total Pages : 864 pages
Book Rating : 4.7/5 (5 download)
Download or read book Asymptotics, Nonparametrics, and Time Series written by Subir Ghosh and published by CRC Press. This book was released on 1999-02-18 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."
Author : Randal Douc
Publisher : CRC Press
ISBN 13 : 1466502347
Total Pages : 548 pages
Book Rating : 4.4/5 (665 download)
Download or read book Nonlinear Time Series written by Randal Douc and published by CRC Press. This book was released on 2014-01-06 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary approaches. They discuss the main limit theorems for Markov chains, useful inequalities, statistical techniques to infer model parameters, and GLMs. Moving on to HMM models, the book examines filtering and smoothing, parametric and nonparametric inference, advanced particle filtering, and numerical methods for inference.
Author : Robert Kohn
Publisher :
ISBN 13 :
Total Pages : 10 pages
Book Rating : 4.:/5 (287 download)
Download or read book Fixed Interval Estimation in State Space Models when Some of the Data are Missing Or Aggregated 1/2 written by Robert Kohn and published by . This book was released on 1983 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Christian Robert
Publisher : Springer Science & Business Media
ISBN 13 : 1441915753
Total Pages : 297 pages
Book Rating : 4.4/5 (419 download)
Download or read book Introducing Monte Carlo Methods with R written by Christian Robert and published by Springer Science & Business Media. This book was released on 2010 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
Author : Antara Majumdar
Publisher :
ISBN 13 :
Total Pages : 194 pages
Book Rating : 4.:/5 (181 download)
Download or read book Maximum Likelihood Estimation of Measurement Error Models Based on the Monte Carlo EM Algorithm written by Antara Majumdar and published by . This book was released on 2007 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Likelihood based estimation of stochastic models when one of the explanatory variables is masked by measurement error, is presented. Special methods are required to estimate the parameters of a model with one or more explanatory variables that are measured with error. In such models, the variable measured with error is unobservable. Only an unbiased manifestation is observable. The method proposed, provides an adjustment to obtain unbiased estimates of model parameters. The correction of bias, however, is not possible without additional identifying information. An instrumental variable is a practical form of additional information that can be used for this purpose. By treating the unobservable explanatory variable as 'missing' data the Markov Chain Monte Carlo Expectation Maximization (MCEM) algorithm is applied for maximum likelihood estimation of the parameters of a measurement error model with identifying information in the form of an instrumental variable. Implementation strategies, computational aspects, behavior of the estimators and inference resulting from application of the MCEM algorithm to the instrumental variable measurement error model are studied. A general methodology is developed that encompasses a variety of previously studied special case models and it is shown how they all can be modeled and estimated using the MCEM algorithm. Through our method it is shown how a structural logistic regression measurement error model can be directly fitted without the probit approximation. This was not possible prior to the research presented in this dissertation. The proposed methodology is compared numerically with the exact maximum likelihood estimates for two normal family models. Also, the behavior of the method is investigated when one of the variance parameters is near the boundary of the parameter space. The problem of measurement error in a survival time model with right censoring is considered and it is shown how the proposed method can be used to estimate a hazard function model, by construction of some special likelihoods and further methodological development. Two methods have been proposed, one of which is a semi-parametric method and the other is full parametric.
