Nonparametric Kernel Density Estimation And Its Computational Aspects
DOWNLOAD
Download Nonparametric Kernel Density Estimation And Its Computational Aspects PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Nonparametric Kernel Density Estimation And Its Computational Aspects book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Nonparametric Kernel Density Estimation And Its Computational Aspects
DOWNLOAD
Author : Artur Gramacki
language : en
Publisher: Springer
Release Date : 2017-12-21
Nonparametric Kernel Density Estimation And Its Computational Aspects written by Artur Gramacki and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-21 with Technology & Engineering categories.
This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. The theory of KDE appears to have matured and is now well developed and understood. However, there is not much progress observed in terms of performance improvements. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects. The book contains both some background and much more sophisticated material, hence also more experienced researchers in the KDE area may find it interesting. The presented material is richly illustrated with many numerical examples using both artificial and real datasets. Also, a number of practical applications related to KDE are presented.
Deep Neural Networks And Data For Automated Driving
DOWNLOAD
Author : Tim Fingscheidt
language : en
Publisher: Springer Nature
Release Date : 2022-07-19
Deep Neural Networks And Data For Automated Driving written by Tim Fingscheidt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-19 with Technology & Engineering categories.
This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above.
Probability Statistics And Life Cycle Assessment
DOWNLOAD
Author : Reinout Heijungs
language : en
Publisher: Springer Nature
Release Date : 2024-05-20
Probability Statistics And Life Cycle Assessment written by Reinout Heijungs and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-20 with Science categories.
This textbook discusses the use of uncertainty analysis and sensitivity analysis in environmental life cycle assessment (LCA). This is a topic which has received a lot of attention by journals, including the leading (Springer) International Journal of Life Cycle Assessment. Despite its importance, no coherent textbook exists that summarizes the progress that has been made in the last 20 years. This book attempts to fill that gap. Its audience is practitioners (professional and academic) of LCA, teachers, and Ph.D. students. It gives a very broad overview of the field: probability theory, descriptive statistics, inferential statistics, error analysis, sensitivity analysis, decision theory, etc., all in relation to LCA. Much effort has been taken to give a balanced overview, with a uniform terminology and mathematical notation.
Motion Planning For Autonomous Vehicles In Partially Observable Environments
DOWNLOAD
Author : Taş, Ömer Şahin
language : en
Publisher: KIT Scientific Publishing
Release Date : 2023-10-23
Motion Planning For Autonomous Vehicles In Partially Observable Environments written by Taş, Ömer Şahin and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-23 with categories.
This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.
Monitoring Multimode Continuous Processes
DOWNLOAD
Author : Marcos Quiñones-Grueiro
language : en
Publisher: Springer Nature
Release Date : 2020-08-04
Monitoring Multimode Continuous Processes written by Marcos Quiñones-Grueiro and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with Technology & Engineering categories.
This book examines recent methods for data-driven fault diagnosis of multimode continuous processes. It formalizes, generalizes, and systematically presents the main concepts, and approaches required to design fault diagnosis methods for multimode continuous processes. The book provides both theoretical and practical tools to help readers address the fault diagnosis problem by drawing data-driven methods from at least three different areas: statistics, unsupervised, and supervised learning.
Flexible Nonparametric Curve Estimation
DOWNLOAD
Author : Hassan Doosti
language : en
Publisher: Springer Nature
Release Date : 2024-09-04
Flexible Nonparametric Curve Estimation written by Hassan Doosti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Mathematics categories.
This book delves into the realm of nonparametric estimations, offering insights into essential notions such as probability density, regression, Tsallis Entropy, Residual Tsallis Entropy, and intensity functions. Through a series of carefully crafted chapters, the theoretical foundations of flexible nonparametric estimators are examined, complemented by comprehensive numerical studies. From theorem elucidation to practical applications, the text provides a deep dive into the intricacies of nonparametric curve estimation. Tailored for postgraduate students and researchers seeking to expand their understanding of nonparametric statistics, this book will serve as a valuable resource for anyone who wishes to explore the applications of flexible nonparametric techniques.
Statistical Theory And Computational Aspects Of Smoothing
DOWNLOAD
Author : Wolfgang Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-08
Statistical Theory And Computational Aspects Of Smoothing written by Wolfgang Härdle and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-08 with Business & Economics categories.
One of the main applications of statistical smoothing techniques is nonparametric regression. For the last 15 years there has been a strong theoretical interest in the development of such techniques. Related algorithmic concepts have been a main concern in computational statistics. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. But they are also relevant for medical and psychological research. Introduced are new developments in scatterplot smoothing and applications in statistical modelling. The treatment of the topics is on an intermediate level avoiding too much technicalities. Computational and applied aspects are considered throughout. Of particular interest to readers is the discussion of recent local fitting techniques.
Semiparametric And Nonparametric Econometrics
DOWNLOAD
Author : Aman Ullah
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Semiparametric And Nonparametric Econometrics written by Aman Ullah and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
Over the last three decades much research in empirical and theoretical economics has been carried on under various assumptions. For example a parametric functional form of the regression model, the heteroskedasticity, and the autocorrelation is always as sumed, usually linear. Also, the errors are assumed to follow certain parametric distri butions, often normal. A disadvantage of parametric econometrics based on these assumptions is that it may not be robust to the slight data inconsistency with the particular parametric specification. Indeed any misspecification in the functional form may lead to erroneous conclusions. In view of these problems, recently there has been significant interest in 'the semiparametric/nonparametric approaches to econometrics. The semiparametric approach considers econometric models where one component has a parametric and the other, which is unknown, a nonparametric specification (Manski 1984 and Horowitz and Neumann 1987, among others). The purely non parametric approach, on the other hand, does not specify any component of the model a priori. The main ingredient of this approach is the data based estimation of the unknown joint density due to Rosenblatt (1956). Since then, especially in the last decade, a vast amount of literature has appeared on nonparametric estimation in statistics journals. However, this literature is mostly highly technical and this may partly be the reason why very little is known about it in econometrics, although see Bierens (1987) and Ullah (1988).
Smoothing Methods In Statistics
DOWNLOAD
Author : Jeffrey S. Simonoff
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Smoothing Methods In Statistics written by Jeffrey S. Simonoff and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
The existence of high speed, inexpensive computing has made it easy to look at data in ways that were once impossible. Where once a data analyst was forced to make restrictive assumptions before beginning, the power of the computer now allows great freedom in deciding where an analysis should go. One area that has benefited greatly from this new freedom is that of non parametric density, distribution, and regression function estimation, or what are generally called smoothing methods. Most people are familiar with some smoothing methods (such as the histogram) but are unlikely to know about more recent developments that could be useful to them. If a group of experts on statistical smoothing methods are put in a room, two things are likely to happen. First, they will agree that data analysts seriously underappreciate smoothing methods. Smoothing meth ods use computing power to give analysts the ability to highlight unusual structure very effectively, by taking advantage of people's abilities to draw conclusions from well-designed graphics. Data analysts should take advan tage of this, they will argue.
Nonparametric Functional Estimation And Related Topics
DOWNLOAD
Author : G.G Roussas
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Nonparametric Functional Estimation And Related Topics written by G.G Roussas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.