Complex Models And Computational Methods In Statistics PDF Download
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Author | : Anna Maria Paganoni |
Publisher | : Springer |
Total Pages | : 210 |
Release | : 2014-11-04 |
Genre | : Mathematics |
ISBN | : 3319111493 |
Download Advances in Complex Data Modeling and Computational Methods in Statistics Book in PDF, ePub and Kindle
The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.
Author | : Matteo Grigoletto |
Publisher | : Springer Science & Business Media |
Total Pages | : 228 |
Release | : 2013-01-26 |
Genre | : Mathematics |
ISBN | : 884702871X |
Download Complex Models and Computational Methods in Statistics Book in PDF, ePub and Kindle
The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.
Author | : Pietro Mantovan |
Publisher | : Springer Science & Business Media |
Total Pages | : 170 |
Release | : 2011-01-27 |
Genre | : Computers |
ISBN | : 8847013860 |
Download Complex Data Modeling and Computationally Intensive Statistical Methods Book in PDF, ePub and Kindle
Selected from the conference "S.Co.2009: Complex Data Modeling and Computationally Intensive Methods for Estimation and Prediction," these 20 papers cover the latest in statistical methods and computational techniques for complex and high dimensional datasets.
Author | : |
Publisher | : |
Total Pages | : 176 |
Release | : 2011-08-14 |
Genre | : |
ISBN | : 9788847013926 |
Download Complex Data Modeling and Computationally Intensive Statistical Methods Book in PDF, ePub and Kindle
Author | : Shen Liu |
Publisher | : Academic Press |
Total Pages | : 206 |
Release | : 2015-11-20 |
Genre | : Mathematics |
ISBN | : 0081006519 |
Download Computational and Statistical Methods for Analysing Big Data with Applications Book in PDF, ePub and Kindle
Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. Advanced computational and statistical methodologies for analysing big data are developed Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable Case studies are discussed to demonstrate the implementation of the developed methods Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation Computing code/programs are provided where appropriate
Author | : Jesper Møller |
Publisher | : Springer |
Total Pages | : 205 |
Release | : 2003-04-03 |
Genre | : Mathematics |
ISBN | : 0387001360 |
Download Spatial Statistics and Computational Methods Book in PDF, ePub and Kindle
This volume shows how sophisticated spatial statistical and computational methods apply to a range of problems of increasing importance for applications in science and technology. It introduces topics of current interest in spatial and computational statistics, which should be accessible to postgraduate students as well as to experienced statistical researchers.
Author | : J. Nathan Kutz |
Publisher | : Oxford University Press |
Total Pages | : 657 |
Release | : 2013-08-08 |
Genre | : Computers |
ISBN | : 0199660336 |
Download Data-Driven Modeling & Scientific Computation Book in PDF, ePub and Kindle
Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.
Author | : |
Publisher | : Elsevier |
Total Pages | : 413 |
Release | : 2014-11-27 |
Genre | : Mathematics |
ISBN | : 044463441X |
Download Computational Statistics with R Book in PDF, ePub and Kindle
R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered. Addresses data examples that can be downloaded directly from the R website No other source is needed to gain practical experience Focus on the essentials in graphical outlays
Author | : Vijay Kumar Mago |
Publisher | : Springer Science & Business Media |
Total Pages | : 196 |
Release | : 2013-10-31 |
Genre | : Technology & Engineering |
ISBN | : 3319012851 |
Download Computational Models of Complex Systems Book in PDF, ePub and Kindle
Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the readers will have stimulating experiences to pursue research in these directions.
Author | : Radek Silhavy |
Publisher | : Springer |
Total Pages | : 386 |
Release | : 2018-08-29 |
Genre | : Technology & Engineering |
ISBN | : 303000211X |
Download Computational and Statistical Methods in Intelligent Systems Book in PDF, ePub and Kindle
This book presents real-world problems and pioneering research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of intelligent systems. It gathers the peer-reviewed proceedings of the 2nd Computational Methods in Systems and Software 2018 (CoMeSySo 2018), a conference that broke down traditional barriers by being held online. The goal of the event was to provide an international forum for discussing the latest high-quality research results.