Download or read book Universally Efficient Estimation of the First order Autoregressive Parameter and Universal Data Compression written by Neri Merhav and published by . This book was released on 1988 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Documentation Abstracts written by and published by . This book was released on 1991 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Sequential Estimation of Parameters in a First Order Autoregressive Model written by Tharuvai Narayanaswami Sriram and published by . This book was released on 1986 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Current Index to Statistics Applications Methods and Theory written by and published by . This book was released on 1990 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.

Download or read book On the Estimation of the First Order Autoregressive Parameter written by F. Giannella and published by . This book was released on 1984 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents Cramer-Rao (C-R) bounds for parameter estimation of a first-order autoregressive process from a finite record of data. The authors used these bounds to evaluate the performance of Maximum Likelihood Estimation (MLE) and linear prediction approaches. Some estimators use low-rank approximation of an estimated covariance matrix. The latter estimates are based on the method of Tufts and Kumaresan. In this document a zero selection techniques in the last step of the procedure was added. The low-rank, high order, linear prediction estimator performs better than the other methods which were tested, when the pole is close to the unit circle. It is slightly biased and its variance is small and close to the variance given by the C-R bound for unbiased estimators. For a small number of samples (25 to 100) this estimator performs substantially better than the MLE. (Author).

Download or read book Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer Valued Ar P Models written by Feike C. Drost and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on the nonnegative integers, called an immigration or innovation distribution. Traditionally, parametric models are considered where the innovation distribution is assumed to belong to a parametric family. This paper instead considers a more realistic semiparametric INAR(p) model where there are essentially no restrictions on the innovation distribution. We provide an (semiparametrically) efficient estimator of both the autoregression parameters and the innovation distribution.

Download or read book Efficient Estimation for Periodic Autoregressive Coefficients Via Residuals written by L. Tang and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A two-step estimation method is proposed for periodic autoregressive parameters via residuals when the observations contain trend and periodic autoregressive time series. The oracle efficiency of the proposed Yule-Walker-type estimator is established. The performance is illustrated by simulation studies and real data analysis.

Download or read book 1990 IEEE International Symposium on Information Theory ISIT written by Laurence B. Milstein and published by . This book was released on 1990 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer valued AR p Models written by Feike Cornelis Drost and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book IEEE International Symposium on Information Theory written by and published by . This book was released on 1990 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Estimation in Nonlinear Autoregressive Time Series Models written by Hira L. Koul and published by . This book was released on 1995 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Estimation of a Model with an Autoregressive Signal with White Noise written by STANFORD UNIV CALIF DEPT OF STATISTICS. and published by . This book was released on 1979 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers the estimation of parameters in the model of X sub t = S sub t + epsilon sub t where the S sub t are generated by a stationary autoregressive model sum from i = o to p of (alpha sub i) (S sub t-i) = eta sub t and the eta sub t and the epsilon sub t are i.i.d. random variables. This paper gives the asymptotic distribution of an approximate maximum-likelihood estimate using only a condition on the fourth-order moment of epsilon sub t and eta sub t and without the assumption of normality. This paper also contains a theorem which shows that under general conditions an estimate given by the second-step in the Newton-Raphson iteration with a consistent estimate as an initial value is second-order efficient.

Download or read book Adaptive parameter estimation in the dynamic autoregressive model of first order written by Roland Günther and published by . This book was released on 1984 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Science Abstracts written by and published by . This book was released on 1993 with total page 2332 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Statistical Parametric Mapping The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. An essential reference and companion for users of the SPM software Provides a complete description of the concepts and procedures entailed by the analysis of brain images Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data Stands as a compendium of all the advances in neuroimaging data analysis over the past decade Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes Structured treatment of data analysis issues that links different modalities and models Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible

Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2013-09-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

Download or read book Strengthening Forensic Science in the United States written by National Research Council and published by National Academies Press. This book was released on 2009-07-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scores of talented and dedicated people serve the forensic science community, performing vitally important work. However, they are often constrained by lack of adequate resources, sound policies, and national support. It is clear that change and advancements, both systematic and scientific, are needed in a number of forensic science disciplines to ensure the reliability of work, establish enforceable standards, and promote best practices with consistent application. Strengthening Forensic Science in the United States: A Path Forward provides a detailed plan for addressing these needs and suggests the creation of a new government entity, the National Institute of Forensic Science, to establish and enforce standards within the forensic science community. The benefits of improving and regulating the forensic science disciplines are clear: assisting law enforcement officials, enhancing homeland security, and reducing the risk of wrongful conviction and exoneration. Strengthening Forensic Science in the United States gives a full account of what is needed to advance the forensic science disciplines, including upgrading of systems and organizational structures, better training, widespread adoption of uniform and enforceable best practices, and mandatory certification and accreditation programs. While this book provides an essential call-to-action for congress and policy makers, it also serves as a vital tool for law enforcement agencies, criminal prosecutors and attorneys, and forensic science educators.