Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results write by Jing Lei. This book was released on 2010. Non-linear Filtering for State Space Models - High-Dimensional Applications and Theoretical Results available in PDF, EPUB and Kindle. State space models are powerful modeling tools for stochastic dynamical systems and have been an important research area in the statistics community in the last several decades. This thesis makes contributions to the filtering problem, a key inference problem in general state space models. Our work in this area is motivated by both high-dimensional, nonlinear applications such as numerical weather forecasting and fundamental theoretical problems such as the convergence of filters. First we study the ensemble Kalman filters (EnKF), a popular class of filtering methods in geophysics because they are easy to implement in large systems. However, their behavior in non-Gaussian situations is only partially understood. We compare two common versions of EnKF's under non-Gaussianity from a robustness perspective. The results support previous empirical studies on the same issue and provide additional insight in choosing a free parameter in the EnKF algorithms. Second, we consider the filtering problem in high dimensional situations such as numerical weather forecasting. We review the EnKF from a statistical perspective and analyze its sources of bias. Then we propose a new method to reduces the bias, namely the non-linear ensemble adjustment filter (NLEAF). The one-step consistency of the NLEAF is studied and the performance is examined through simulations in two common testbeds in the weather forecasting literature. Finally we look at the theoretical properties of another popular class of filtering methods, the sequential Monte Carlo (SMC) filter. The convergence of SMC filters has been a challenging problem in both probability and statistics. The previous results either depend on strong mixing conditions which only hold in compact spaces or provide no rates of convergence or are under weak notions of distance, limiting the application of their practical use. We provide checkable sufficient conditions under which explicit rates of convergence of the SMC filter can be derived. The conditions essentially requires the regularity of the tail behavior of the process and they are general enough to include a wide class of autoregressive models as well as Gaussian linear models.
Filtering None-Linear State Space Models. Methods and Economic Applications
Filtering None-Linear State Space Models. Methods and Economic Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Filtering None-Linear State Space Models. Methods and Economic Applications write by Kai Ming Lee. This book was released on 2010. Filtering None-Linear State Space Models. Methods and Economic Applications available in PDF, EPUB and Kindle.
Nonlinear Speech Modeling and Applications
Nonlinear Speech Modeling and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Nonlinear Speech Modeling and Applications write by Gerard Chollet. This book was released on 2005-07-12. Nonlinear Speech Modeling and Applications available in PDF, EPUB and Kindle. This book presents the revised tutorial lectures given at the International Summer School on Nonlinear Speech Processing-Algorithms and Analysis held in Vietri sul Mare, Salerno, Italy in September 2004. The 14 revised tutorial lectures by leading international researchers are organized in topical sections on dealing with nonlinearities in speech signals, acoustic-to-articulatory modeling of speech phenomena, data driven and speech processing algorithms, and algorithms and models based on speech perception mechanisms. Besides the tutorial lectures, 15 revised reviewed papers are included presenting original research results on task oriented speech applications.
Selected Works of Peter J. Bickel
Selected Works of Peter J. Bickel - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Selected Works of Peter J. Bickel write by Jianqing Fan. This book was released on 2012-11-28. Selected Works of Peter J. Bickel available in PDF, EPUB and Kindle. This volume presents selections of Peter J. Bickel’s major papers, along with comments on their novelty and impact on the subsequent development of statistics as a discipline. Each of the eight parts concerns a particular area of research and provides new commentary by experts in the area. The parts range from Rank-Based Nonparametrics to Function Estimation and Bootstrap Resampling. Peter’s amazing career encompasses the majority of statistical developments in the last half-century or about about half of the entire history of the systematic development of statistics. This volume shares insights on these exciting statistical developments with future generations of statisticians. The compilation of supporting material about Peter’s life and work help readers understand the environment under which his research was conducted. The material will also inspire readers in their own research-based pursuits. This volume includes new photos of Peter Bickel, his biography, publication list, and a list of his students. These give the reader a more complete picture of Peter Bickel as a teacher, a friend, a colleague, and a family man.
State-Space Models
State-Space Models - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook State-Space Models write by Yong Zeng. This book was released on 2013-08-15. State-Space Models available in PDF, EPUB and Kindle. State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book includes nonlinear and non-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous) observations. The contributed chapters are divided into four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models. The second part focuses on the application of Linear State-Space Models in Macroeconomics and Finance. The third part deals with Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals.
