Vai al contenuto principale della pagina

Statistical Methods for Astronomical Data Analysis / / by Asis Kumar Chattopadhyay, Tanuka Chattopadhyay



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Chattopadhyay Asis Kumar Visualizza persona
Titolo: Statistical Methods for Astronomical Data Analysis / / by Asis Kumar Chattopadhyay, Tanuka Chattopadhyay Visualizza cluster
Pubblicazione: New York, NY : , : Springer New York : , : Imprint : Springer, , 2014
Edizione: 1st ed. 2014.
Descrizione fisica: 1 online resource (356 p.)
Disciplina: 520.72
520.727
Soggetto topico: Statistics 
Astrophysics
Astronomy
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Astrophysics and Astroparticles
Astronomy, Astrophysics and Cosmology
Statistical Theory and Methods
Persona (resp. second.): ChattopadhyayTanuka
Note generali: Description based upon print version of record.
Nota di contenuto: Introduction to Astrophysics -- Introduction to Statistics -- Sources of Astronomical Data -- Statistical Inference -- Advanced Regression and its Application with Measurement Error -- Missing Observations and Imputation -- Dimension Reduction and Clustering -- Clustering, Classification and Data Mining -- Time Series Analysis -- Monte Carlo Simulation -- Uses of Softwares -- Appendix.  .
Sommario/riassunto: This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for astronomical problems, including regression techniques, along with their usefulness for data set problems related to size and dimension. Analysis of missing data is an important part of the book because of its significance for work with astronomical data. Both existing and new techniques related to dimension reduction and clustering are illustrated through examples. There is detailed coverage of applications useful for classification, discrimination, data mining and time series analysis. Later chapters explain simulation techniques useful for the development of physical models where it is difficult or impossible to collect data. Finally, coverage of the many R programs for techniques discussed makes this book a fantastic practical reference. Readers may apply what they learn directly to their data sets in addition to the data sets included by the authors.
Titolo autorizzato: Statistical Methods for Astronomical Data Analysis  Visualizza cluster
ISBN: 1-4939-1507-X
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299995103321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Springer Series in Astrostatistics, . 2199-1030 ; ; 3