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Statistical Modelling using Local Gaussian Approximation
- Author : Dag Bjarne Tjostheim,Hakon Otneim,Bard Stove
- Publisher :Unknown
- Release Date :2021-11-15
- Total pages :352
- ISBN : 0128158611
Summary : Statistical Modeling using Local Gaussian Approximation extends powerful characteristics of the Gaussian distribution - perhaps the most well-known and most used distribution in statistics - to a large class of non-Gaussian and nonlinear situations through local approximation. This extension enables the reader to follow new methods in assessing conditional distribution functions, conditional mean functions and conditional quantile functions. Three R packages are integrated with the text, based on local Gaussian correlation, density and conditional density estimation, and local spectral analysis. The book is of particular relevance and interest to researchers in econometrics and financial econometrics. Reviews local dependence modelling with applications to time series and finance markets Introduces new techniques for density estimation, conditional density estimation and tests of conditional independence with applications in economics Evaluates local spectral analysis, discovering hidden frequencies in extremes and hidden phase differences Integrates textual content with three useful R packages
Stochastic Models, Statistics and Their Applications
- Author : Ansgar Steland,Ewaryst Rafajłowicz,Krzysztof Szajowski
- Publisher :Unknown
- Release Date :2015-02-04
- Total pages :492
- ISBN : 9783319138817
Summary : This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Biomedical Image Segmentation
- Author : Ayman El-Baz,Xiaoyi Jiang,Jasjit S. Suri
- Publisher :Unknown
- Release Date :2016-11-17
- Total pages :526
- ISBN : 9781482258561
Summary : As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.
Probabilistic Finite Element Model Updating Using Bayesian Statistics
- Author : Tshilidzi Marwala,Ilyes Boulkaibet,Sondipon Adhikari
- Publisher :Unknown
- Release Date :2016-09-23
- Total pages :248
- ISBN : 9781119153009
Summary : Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering. The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering. Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering. Key features: Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students. Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations. The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.
Multi-Robot Exploration for Environmental Monitoring
- Author : Kshitij Tiwari,Nak-Young Chong
- Publisher :Unknown
- Release Date :2019-11
- Total pages :290
- ISBN : 9780128176078
Summary : Multi-robot Exploration for Environmental Monitoring: The Resource Constrained Perspective provides readers with the necessary robotics and mathematical tools required to realize the correct architecture. The architecture discussed in the book is not confined to environment monitoring, but can also be extended to search-and-rescue, border patrolling, crowd management and related applications. Several law enforcement agencies have already started to deploy UAVs, but instead of using teleoperated UAVs this book proposes methods to fully automate surveillance missions. Similarly, several government agencies like the US-EPA can benefit from this book by automating the process. Several challenges when deploying such models in real missions are addressed and solved, thus laying stepping stones towards realizing the architecture proposed. This book will be a great resource for graduate students in Computer Science, Computer Engineering, Robotics, Machine Learning and Mechatronics. Analyzes the constant conflict between machine learning models and robot resources Presents a novel range estimation framework tested on real robots (custom built and commercially available)
Mathematical Reviews
- Author : Anonim
- Publisher :Unknown
- Release Date :2004
- Total pages :229
- ISBN : UOM:39015055144706
Summary :
Current Index to Statistics, Applications, Methods and Theory
- Author : Anonim
- Publisher :Unknown
- Release Date :1999
- Total pages :229
- ISBN : UOM:39015053598119
Summary :
Computing Science and Statistics
- Author : Kenneth Berk,Linda Malone,Terence M. Mulligan
- Publisher :Unknown
- Release Date :1989
- Total pages :619
- ISBN : UOM:39015026811912
Summary :
AI Magazine
- Author : Anonim
- Publisher :Unknown
- Release Date :2003
- Total pages :229
- ISBN : UOM:39015058898704
Summary :
Dissertation Abstracts International
- Author : Anonim
- Publisher :Unknown
- Release Date :2008
- Total pages :229
- ISBN : STANFORD:36105131549649
Summary :
Computational Mathematics and Mathematical Physics
- Author : Anonim
- Publisher :Unknown
- Release Date :1992
- Total pages :229
- ISBN : UCSD:31822017773151
Summary :
ICC 2004
- Author : Institute of electrical and electronics engineers
- Publisher :Unknown
- Release Date :2004
- Total pages :229
- ISBN : 0780385330
Summary :
Bulletin
- Author : Anonim
- Publisher :Unknown
- Release Date :1996
- Total pages :229
- ISBN : UCAL:B4595231
Summary :
Mathematical Methods of Statistics
- Author : Anonim
- Publisher :Unknown
- Release Date :2002
- Total pages :229
- ISBN : UOM:39015057302401
Summary :
A Survey of Asymptotic Equivalence of Statistical Experiments
- Author : Hui Tang
- Publisher :Unknown
- Release Date :2003
- Total pages :122
- ISBN : CORNELL:31924097215200
Summary :
Nonlinear Statistical Models
- Author : Andrej Pázman
- Publisher :Unknown
- Release Date :2013-03-14
- Total pages :260
- ISBN : 9789401724500
Summary : Nonlinear statistical modelling is an area of growing importance. This monograph presents mostly new results and methods concerning the nonlinear regression model. Among the aspects which are considered are linear properties of nonlinear models, multivariate nonlinear regression, intrinsic and parameter effect curvature, algorithms for calculating the L2-estimator and both local and global approximation. In addition to this a chapter has been added on the large topic of nonlinear exponential families. The volume will be of interest to both experts in the field of nonlinear statistical modelling and to those working in the identification of models and optimization, as well as to statisticians in general.
Bulletin of the Novosibirsk Computing Center
- Author : Anonim
- Publisher :Unknown
- Release Date :1993
- Total pages :229
- ISBN : PSU:000046890320
Summary :
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
- Author : Elias T. Krainski,Virgilio Gómez-Rubio,Haakon Bakka,Amanda Lenzi,Daniela Castro-Camilo,Daniel Simpson,Finn Lindgren,Håvard Rue
- Publisher :Unknown
- Release Date :2018-12-07
- Total pages :284
- ISBN : 9780429629853
Summary : Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio-temporal models * Measurement error spatial models * Modeling preferential sampling * Spatial and spatio-temporal models with physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with spatial effects * Penalized Complexity priors for spatial models All the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book. The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.
Local Approximation Techniques in Signal and Image Processing
- Author : Vladimir Katkovnik,Vladimir I︠A︡kovlevich Katkovnik,Karen Egiazarian,Jaakko Astola
- Publisher :Unknown
- Release Date :2006
- Total pages :553
- ISBN : UOM:39015069109836
Summary : This book deals with a wide class of novel and efficient adaptive signal processing techniques developed to restore signals from noisy and degraded observations. These signals include those acquired from still or video cameras, electron microscopes, radar, X-rays, or ultrasound devices, and are used for various purposes, including entertainment, medical, business, industrial, military, civil, security, and scientific. In many cases useful information and high quality must be extracted from the imaging. However, often raw signals are not directly suitable for this purpose and must be processed in some way. Such processing is called signal reconstruction. This book is devoted to a recent and original approach to signal reconstruction based on combining two independent ideas: local polynomial approximation and the intersection of confidence interval rule.
Proceedings ISAI/IFIS ...
- Author : Anonim
- Publisher :Unknown
- Release Date :1996
- Total pages :229
- ISBN : UOM:39015036297557
Summary :
Journal of the American Statistical Association
- Author : Anonim
- Publisher :Unknown
- Release Date :2008
- Total pages :229
- ISBN : UCSD:31822036057495
Summary :