{"product_id":"multivariate-nonparametric-regression-and-visualization-with-r-and-applications-to-finance-hardback-9780470384428","title":"Multivariate Nonparametric Regression and Visualization; With R and Applications to Finance (Hardback) 9780470384428","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eMultivariate Nonparametric Regression and Visualization\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eWith R and Applications to Finance\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eJussi Sakari Klemelä (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470384428, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 23 May 2014\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e396 pages, Charts: 30 B\u0026amp;W, 0 Color; Drawings: 130 B\u0026amp;W, 0 Color; Screen captures: 50 B\u0026amp;W, 0 Color; Graphs: 40 B\u0026amp;W, 0 Color\u003cbr\u003e24.1 x 16.3 x 2.3 cm, 0.794 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e“Altogether, the book provides a very nice overview of nonparametric and semiparametric regression methods with interesting applications to problems in quantitative finance.”  (\u003ci\u003eMathematical Reviews\u003c\/i\u003e, 1 October 2015)\u003c\/p\u003e \u003cp\u003e \u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eA modern approach to statistical learning and \u003c\/b\u003e\u003cb\u003eits applications through visualization methods\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWith a unique and innovative presentation, \u003ci\u003eMultivariate Nonparametric Regression and Visualization\u003c\/i\u003e provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generating mechanisms, the book begins with an overview of classification and regression.\u003c\/p\u003e \u003cp\u003eThe book then introduces and examines various tested and proven visualization techniques for learning samples and functions. \u003ci\u003eMultivariate Nonparametric Regression and Visualization\u003c\/i\u003e identifies risk management, portfolio selection, and option pricing as the main areas in which statistical methods may be implemented in quantitative finance. The book provides coverage of key statistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, and nearest neighbor methods. Exploring the additional applications of nonparametric and semiparametric methods, \u003ci\u003eMultivariate\u003c\/i\u003e \u003ci\u003eNonparametric Regression and Visualization\u003c\/i\u003e features:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eAn extensive appendix with R-package training material to encourage duplication and modification of the presented computations and research\u003c\/li\u003e \u003cli\u003eMultiple examples to demonstrate the applications in the field of finance\u003c\/li\u003e \u003cli\u003eSections with formal definitions of the various applied methods for readers to utilize throughout the book\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eMultivariate Nonparametric Regression and Visualization\u003c\/i\u003e is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance. The book is also an excellent reference for practitioners who apply statistical methods in quantitative finance.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xvii\u003c\/p\u003e \u003cp\u003eIntroduction xix\u003c\/p\u003e \u003cp\u003eI.1 Estimation of Functionals of Conditional Distributions xx\u003c\/p\u003e \u003cp\u003eI.2 Quantitative Finance xxi\u003c\/p\u003e \u003cp\u003eI.3 Visualization xxi\u003c\/p\u003e \u003cp\u003eI.4 Literature xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I METHODS OF REGRESSION AND CLASSIFICATION\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Overview of Regression and Classification 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Regression 3\u003c\/p\u003e \u003cp\u003e1.2 Discrete Response Variable 29\u003c\/p\u003e \u003cp\u003e1.3 Parametric Family Regression 33\u003c\/p\u003e \u003cp\u003e1.4 Classification 37\u003c\/p\u003e \u003cp\u003e1.5 Applications in Quantitative Finance 42\u003c\/p\u003e \u003cp\u003e1.6 Data Examples 52\u003c\/p\u003e \u003cp\u003e1.7 Data Transformations 53\u003c\/p\u003e \u003cp\u003e1.8 Central Limit Theorems 58\u003c\/p\u003e \u003cp\u003e1.9 Measuring the Performance of Estimators 61\u003c\/p\u003e \u003cp\u003e1.10 Confidence Sets 73\u003c\/p\u003e \u003cp\u003e1.11 Testing 75\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Linear Methods and Extensions 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Linear Regression 78\u003c\/p\u003e \u003cp\u003e2.2 Varying Coefficient Linear Regression 97\u003c\/p\u003e \u003cp\u003e2.3 Generalized Linear and Related Models 102\u003c\/p\u003e \u003cp\u003e2.4 Series Estimators 107\u003c\/p\u003e \u003cp\u003e2.5 Conditional Variance and ARCH models 111\u003c\/p\u003e \u003cp\u003e2.6 Applications in Volatility and Quantile Estimation 115\u003c\/p\u003e \u003cp\u003e2.7 Linear Classifiers 124\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Kernel Methods and Extensions 127\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Regressogram 129\u003c\/p\u003e \u003cp\u003e3.2 Kernel Estimator 130\u003c\/p\u003e \u003cp\u003e3.3 Nearest Neighborhood Estimator 147\u003c\/p\u003e \u003cp\u003e3.4 Classification with Local Averaging 148\u003c\/p\u003e \u003cp\u003e3.5 Median Smoothing 151\u003c\/p\u003e \u003cp\u003e3.6 Conditional Density Estimators 152\u003c\/p\u003e \u003cp\u003e3.7 Conditional Distribution Function Estimation 158\u003c\/p\u003e \u003cp\u003e3.8 Conditional Quantile Estimation 160\u003c\/p\u003e \u003cp\u003e3.9 Conditional Variance Estimation 162\u003c\/p\u003e \u003cp\u003e3.10 Conditional Covariance Estimation 176\u003c\/p\u003e \u003cp\u003e3.11 Applications in Risk Management 181\u003c\/p\u003e \u003cp\u003e3.12 Applications in Portfolio Selection 205\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Semiparametric and Structural Models 229\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Single Index Model 230\u003c\/p\u003e \u003cp\u003e4.2 Additive Model 234\u003c\/p\u003e \u003cp\u003e4.3 Other Semiparametric Models 237\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Empirical Risk Minimization 241\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Empirical Risk 243\u003c\/p\u003e \u003cp\u003e5.2 Local Empirical Risk 247\u003c\/p\u003e \u003cp\u003e5.3 Support Vector Machines 257\u003c\/p\u003e \u003cp\u003e5.4 Stagewise Methods 259\u003c\/p\u003e \u003cp\u003e5.5 Adaptive Regressograms 264\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II VISUALIZATION\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Visualization of Data 277\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Scatter Plots 278\u003c\/p\u003e \u003cp\u003e6.2 Histogram and Kernel Density Estimator 282\u003c\/p\u003e \u003cp\u003e6.3 Dimension Reduction 284\u003c\/p\u003e \u003cp\u003e6.4 Observations as Objects 288\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Visualization of Functions 295\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Slices 296\u003c\/p\u003e \u003cp\u003e7.2 Partial Dependence Functions 296\u003c\/p\u003e \u003cp\u003e7.3 Reconstruction of Sets 299\u003c\/p\u003e \u003cp\u003e7.4 Level Set Trees 303\u003c\/p\u003e \u003cp\u003e7.5 Unimodal Densities 326\u003c\/p\u003e \u003cp\u003e7.5.1 Probability Content of Level Sets 327\u003c\/p\u003e \u003cp\u003e7.5.2 Set Visualization 328\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: R Tutorial 329\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Data Visualization 329\u003c\/p\u003e \u003cp\u003eA.2 Linear Regression 331\u003c\/p\u003e \u003cp\u003eA.3 Kernel Regression 332\u003c\/p\u003e \u003cp\u003eA.4 Local Linear Regression 341\u003c\/p\u003e \u003cp\u003eA.5 Additive Models: Backfitting 344\u003c\/p\u003e \u003cp\u003eA.6 Single Index Regression 345\u003c\/p\u003e \u003cp\u003eA.7 Forward Stagewise Modeling 347\u003c\/p\u003e \u003cp\u003eA.8 Quantile Regression 349\u003c\/p\u003e \u003cp\u003eReferences 351\u003c\/p\u003e \u003cp\u003eAuthor Index 361\u003c\/p\u003e \u003cp\u003eTopic Index 365\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Mathematics [\u003ca title=\"See our other books on Mathematics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Mathematics%20%5BPB%5D%22\"\u003ePB\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Interscience","offers":[{"title":"Brand New","offer_id":52276214300952,"sku":"9780470384428","price":89.75,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780470384428.jpg?v=1781365243","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/multivariate-nonparametric-regression-and-visualization-with-r-and-applications-to-finance-hardback-9780470384428","provider":"Freshly Printed Books","version":"1.0","type":"link"}