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Trade Paperback. Zustand: Good. No Dust Jacket. First U.S. Edition. An ex-library copy of this large-format paperback. The usual ex-libris markings. The binding is sound, the text is clean/unmarked, and there is little cover wear. Book.

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Zustand: New. Series: Oberwolfach Seminars. Num Pages: 124 pages, biography. BIC Classification: PBT; PBWL. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 170 x 6. Weight in Grams: 217. . 1992. Paperback. . . . .

Zustand: New. Series: Oberwolfach Seminars. Num Pages: 124 pages, biography. BIC Classification: PBT; PBWL. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 170 x 6. Weight in Grams: 217. . 1992. Paperback. . . . . Books ship from the US and Ireland.

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HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

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Hardcover. Zustand: Brand New. 250 pages. 9.25x6.25x0.75 inches. In Stock.

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Hardcover. Zustand: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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hardcover. Zustand: Sehr gut. 666 Seiten; 9780387954417.2 Gewicht in Gramm: 1.

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Hardback. Zustand: New. 2002 ed. This monograph presents a modern approach to nonparametric regression with random design. The audience is graduate students and researchers in statistics, mathematics, computer science, and engineering.

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Hardback. Zustand: New. 2002 ed. This monograph presents a modern approach to nonparametric regression with random design. The audience is graduate students and researchers in statistics, mathematics, computer science, and engineering.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The regression estimation problem has a long history. Already in 1632 Galileo Galilei used a procedure which can be interpreted as tting a linear relationship to contaminated observed data. Such tting of a line through a cloud of points is the classical linear regression problem. A solution of this problem is provided by the famous principle of least squares, which was discovered independently by A. M. Legendre and C. F. Gauss and published in 1805 and 1809, respectively. The principle of least squares can also be applied to construct nonparametric regression estimates, where one does not restrict the class of possible relationships, and will be one of the approaches studied in this book. Linear regression analysis, based on the concept of a regression function, was introduced by F. Galton in 1889, while a probabilistic approach in the context of multivariate normal distributions was already given by A. B- vais in 1846. The rst nonparametric regression estimate of local averaging type was proposed by J. W. Tukey in 1947. The partitioning regression - timate he introduced, by analogy to the classical partitioning (histogram) density estimate, can be regarded as a special least squares estimate.…

Zustand: gut. 2002. A Distribution-Free Theory of Nonparametric Regression (Springer Series in Statistics) In englischer Sprache. pages.

Thick Octavo. 647 pages, illustrated with 86 figures, index and bibliography. This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates. The relevant mathematical theory is systematically developed and requires only a basic knowledge of probability theory. Reprinted from the hardcover edition, in stiff paper wraps, light crease to upper corner of rear panel. A very good copy.…

Hardcover. Zustand: Brand New. 250 pages. 9.25x6.25x0.75 inches. In Stock. This item is printed on demand.

Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial markets. This title is suitable for researchers and graduate students in computer science, finance, statistics, mathematics, and eng.…

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &nbspThis book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates. |The regression estimation problem has a l.…

Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &nbspThis book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates. |The regression estimation problem has a l.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This monograph presents a modern approach to nonparametric regression with random design. The audience is graduate students and researchers in statistics, mathematics, computer science, and engineering.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 668 pp. Englisch.…

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The regression estimation problem has a long history. Already in 1632 Galileo Galilei used a procedure which can be interpreted as tting a linear relationship to contaminated observed data. Such tting of a line through a cloud of points is the classical linear regression problem. A solution of this problem is provided by the famous principle of least squares, which was discovered independently by A. M. Legendre and C. F. Gauss and published in 1805 and 1809, respectively. The principle of least squares can also be applied to construct nonparametric regression estimates, where one does not restrict the class of possible relationships, and will be one of the approaches studied in this book. Linear regression analysis, based on the concept of a regression function, was introduced by F. Galton in 1889, while a probabilistic approach in the context of multivariate normal distributions was already given by A. B- vais in 1846. The rst nonparametric regression estimate of local averaging type was proposed by J. W. Tukey in 1947. The partitioning regression - timate he introduced, by analogy to the classical partitioning (histogram) density estimate, can be regarded as a special least squares estimate.…