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1. |
Record Nr. |
UNINA9910824925703321 |
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Autore |
Ghosh S (Sucharita) |
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Titolo |
Kernel smoothing : principles, methods and applications / / Sucharita Ghosh |
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Pubbl/distr/stampa |
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Hoboken, New Jersey : , : Wiley, , 2018 |
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©2018 |
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ISBN |
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1-118-89050-7 |
1-118-89037-X |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (1 volume) : illustrations |
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Collana |
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Disciplina |
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Soggetti |
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Smoothing (Statistics) |
Kernel functions |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and indexes. |
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Nota di contenuto |
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Density estimation -- Nonparametric regression -- Trend estimation -- Semiparametric regression -- Surface estimation. |
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Sommario/riassunto |
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Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of contexts, considering independent and correlated data e.g. with short-memory and long-memory correlations, as well as non-Gaussian data that are transformations of latent Gaussian processes. These types of data occur in many fields of research, e.g. the natural and the environmental sciences, and others. Nonparametric density estimation, nonparametric and semiparametric regression, trend and surface estimation in particular for time series and spatial data and other topics such as rapid change points, robustness etc. are introduced alongside a study of their theoretical properties and optimality issues, such as consistency and bandwidth selection. Addressing a variety of topics, Kernel Smoothing: Principles, Methods and Applications offers a user-friendly presentation of the mathematical content so that the reader can directly implement the formulas using any appropriate software. |
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The overall aim of the book is to describe the methods and their theoretical backgrounds, while maintaining an analytically simple approach and including motivating examples—making it extremely useful in many sciences such as geophysics, climate research, forestry, ecology, and other natural and life sciences, as well as in finance, sociology, and engineering. A simple and analytical description of kernel smoothing methods in various contexts Presents the basics as well as new developments Includes simulated and real data examples Kernel Smoothing: Principles, Methods and Applications is a textbook for senior undergraduate and graduate students in statistics, as well as a reference book for applied statisticians and advanced researchers. |
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2. |
Record Nr. |
UNINA9910961068603321 |
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Autore |
Klafter J (Joseph) |
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Titolo |
First steps in random walks : from tools to applications / / J. Klafter and I.M. Sokolov |
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Pubbl/distr/stampa |
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Oxford, : Oxford University Press, 2011 |
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ISBN |
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0-19-155295-X |
0-19-177502-9 |
1-299-48624-X |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Random walks (Mathematics) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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1. Characteristic functions -- 2. Generating functions and applications -- 3. Continuous-time random walks -- 4. CTRW and aging phenomena -- 5. Master equations -- 6. Fractional diffusion and Fokker-Planck equations for subdiffusion -- 7. Levy flights -- 8. Coupled CTRW and Levy walks -- 9. Simple reactions : A+B->B -- 10. Random walks on percolation structures. |
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Sommario/riassunto |
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"The name "random walk" for a problem of a displacement of a point in a sequence of independent random steps was coined by Karl Pearson in 1905 in a question posed to readers of "Nature". The same year, a |
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similar problem was formulated by Albert Einstein in one of his Annus Mirabilis works. Even earlier such a problem was posed by Louis Bachelier in his thesis devoted to the theory of financial speculations in 1900. Nowadays the theory of random walks has proved useful in physics and chemistry (diffusion, reactions, mixing in flows), economics, biology (from animal spread to motion of subcellular structures) and in many other disciplines. The random walk approach serves not only as a model of simple diffusion but of many complex sub- and super-diffusive transport processes as well. This book discusses the main variants of random walks and gives the most important mathematical tools for their theoretical description"-- |
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