A bold retooling of statistics to focus directly on predictive performance with traditional and contemporary data types and methodologies.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Bertrand S. Clarke is Chair of the Department of Statistics at the University of Nebraska, Lincoln. His research focuses on predictive statistics and statistical methodology in genomic data. He is a fellow of the American Statistical Association, serves as editor or associate editor for three journals, and has published numerous papers in several statistical fields as well as a book on data mining and machine learning.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. Bestandsnummer des Verkäufers 26375628239
Anzahl: 1 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 370417168
Anzahl: 1 verfügbar
Anbieter: Lucky's Textbooks, Dallas, TX, USA
Zustand: New. Bestandsnummer des Verkäufers ABLIING23Mar2317530264307
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 30336278-n
Anzahl: Mehr als 20 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. Bestandsnummer des Verkäufers 18375628229
Anzahl: 1 verfügbar
Anbieter: California Books, Miami, FL, USA
Zustand: New. Bestandsnummer des Verkäufers I-9781107028289
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 30336278
Anzahl: Mehr als 20 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9781107028289_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: new. Hardcover. All scientific disciplines prize predictive success. Conventional statistical analyses, however, treat prediction as secondary, instead focusing on modeling and hence estimation, testing, and detailed physical interpretation, tackling these tasks before the predictive adequacy of a model is established. This book outlines a fully predictive approach to statistical problems based on studying predictors; the approach does not require predictors correspond to a model although this important special case is included in the general approach. Throughout, the point is to examine predictive performance before considering conventional inference. These ideas are traced through five traditional subfields of statistics, helping readers to refocus and adopt a directly predictive outlook. The book also considers prediction via contemporary 'black box' techniques and emerging data types and methodologies where conventional modeling is so difficult that good prediction is the main criterion available for evaluating the performance of a statistical method. Well-documented open-source R code in a Github repository allows readers to replicate examples and apply techniques to other investigations. Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and 'black box' settings, with computed examples. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781107028289
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 30336278-n
Anzahl: Mehr als 20 verfügbar