Isbn: 9781584885931 - statistical methods for spatio-temporal systems: 107 (20 risultati)

Condizione: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Hardcover. Condizione: New. No Jacket. 1st Edition. This is a new hardcover first edition, first printing copy, 286 pages with index, no DJ, dark green spine.

Hardcover. Condizione: Good. No jacket. Ex-library with usual stickers, tape and stamps. Ink stain on back cover.

hardcover. Condizione: New. In shrink wrap. Looks like an interesting title.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. pp. 316 Index.

Condizione: New. In English.

Condizione: New.

Condizione: New. Presents statistical research issues on spatio-temporal data modeling that promotes advances in research and an understanding between the mechanistic and the statistical modeling communities. This book offers a variety of statistical methods, including likelihood-based, nonparametric smoothing, Fourier, wavelet, and Markov chain Monte Carlo. Editor(s): Finkenstadt, Barbel; Held, Leonhard; Isham, Valerie. Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability. Num Pages: 286 pages, 122 black & white illustrations, 16 colour illustrations, 16 black & white tables. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 245 x 166 x 24. Weight in Grams: 624. . 2006. 1st Edition. hardcover. . . . . …

Condizione: New. pp. 316.

Condizione: New. Presents statistical research issues on spatio-temporal data modeling that promotes advances in research and an understanding between the mechanistic and the statistical modeling communities. This book offers a variety of statistical methods, including likelihood-based, nonparametric smoothing, Fourier, wavelet, and Markov chain Monte Carlo. Editor(s): Finkenstadt, Barbel; Held, Leonhard; Isham, Valerie. Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability. Num Pages: 286 pages, 122 black & white illustrations, 16 colour illustrations, 16 black & white tables. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 245 x 166 x 24. Weight in Grams: 624. . 2006. 1st Edition. hardcover. . . . . Books ship from the US and Ireland. …

Hardcover. Condizione: Brand New. 1st edition. 286 pages. 9.25x6.25x1.00 inches. In Stock.

Condizione: New. pp. 316 Illus. This item is printed on demand.

Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 612.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Baerbel Finkenstaedt, Leonhard Held, Valerie IshamStatistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding betwee.…

Buch. Condizione: Neu. Statistical Methods for Spatio-Temporal Systems | Barbel Finkenstadt (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2006 | Routledge | EAN 9781584885931 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time covariance functions. The contributors then describe stochastic and statistical models that are used to generate simulated rainfall sequences for hydrological use, such as flood risk assessment. The final chapter explores Gaussian Markov random field specifications and Bayesian computational inference via Gibbs sampling and Markov chain Monte Carlo, illustrating the methods with a variety of data examples, such as temperature surfaces, dioxin concentrations, ozone concentrations, and a well-established deterministic dynamical weather model.…