LEADER 04144nam 22005655 450 001 9910862097103321 005 20231110214755.0 024 7 $a10.1051/978-2-7598-2741-1 035 $a(CKB)5580000000328569 035 $a(DE-B1597)624844 035 $a(DE-B1597)9782759827411 035 $a(NjHacI)995580000000328569 035 $a(MiAaPQ)EBC7156228 035 $a(Au-PeEL)EBL7156228 035 $a(OCoLC)1340426085 035 $a(MiAaPQ)EBC30810413 035 $a(Au-PeEL)EBL30810413 035 $a(PPN)262552736 035 $a(EXLCZ)995580000000328569 100 $a20221004h20222022 fg 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistics for astrophysics $eTime series analysis /$fDidier Fraix?Burnet, Gérard Grégoire 205 $a1st ed. 210 1$aLes Ulis : $cEDP Sciences, $d[2022] 210 4$d©2022 215 $a1 online resource (258 p.) 225 0 $aEDP Sciences Proceedings 311 $a2-7598-2741-0 327 $tFrontmatter -- $tOrganisers -- $tLecturers -- $tAcknowledgments -- $tList of Participants -- $tTable of Contents -- $tForeword -- $t1 - AN OVERVIEW OF THIS BOOK -- $t2 - TIME SERIES, FUNDAMENTAL CONCEPTS -- $t3 - ARMA AND ARIMA TIME SERIES -- $t4 - COMPLEMENTS AND APPLICATIONS -- $t5 - KALMAN FILTER AND TIME SERIES -- $t6 - AN INTRODUCTION TO STATE SPACE MODELS 330 $aThis book is the result of the 2019 session of the School of Statistics for Astrophysics (Stat4Astro) that took place on October, 6 to 11, 2019, at Autrans near Grenoble, in France. The topic of this fourth session was the time series that, from celestial mechanics to gravitational waves, from exoplanets to quasars, concern nearly all the astrophysics. Variable phenomena are ubiquitous in the Universe: periodic (orbits, cycles, pulses, rotations.), transient (explosions, bursts, stellar activity.),random (accretion, ejection.) or regular (apparent motions.). The detection, the characterization and the classification of these variabilities is a discipline of statistics called time series analysis.Time series analysis is not new in astrophysics, but has been the subject of major developments in many other disciplines (meteorology, finance, economy, medical sciences.). In this book,you will find lectures from two statisticians who are experts in this field.Gérard Grégoire, who has a long experience in econometrics and made a huge contribution to both this book and the session. He covers the basic elements of classical L2 time series, in the time domain as well as in the frequency domain, for univariate and multivariate series, and provides also tools for statistical inference. He gives an extensive presentation of ARMA and ARIMA series, and addresses some related advanced topics. He also devotes a chapter to linear Gaussian state space models and Kalman filtering that will be helpful to follow the last chapter written by Éric Moulines and collaborators: this final chapter is dedicated to state space models in a general framework and sequential MonteCarlo methods to leverage recursions generalizing the Kalman recursions for filtering and smoothing. Many practical exercises are given using the R environment. 410 0$aEDP Sciences Proceedings 606 $aSCIENCE / Physics / Astrophysics$2bisacsh 615 7$aSCIENCE / Physics / Astrophysics. 676 $a523.01 700 $aFraix?Burnet$b Didier, $4aut$4http://id.loc.gov/vocabulary/relators/aut$01740743 702 $aDouc$b Randal, $4ctb$4https://id.loc.gov/vocabulary/relators/ctb 702 $aGrégoire$b Gérard, $4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aGrégoire$b Gérard, $4ctb$4https://id.loc.gov/vocabulary/relators/ctb 702 $aMoulines$b Éric, $4ctb$4https://id.loc.gov/vocabulary/relators/ctb 702 $aStoffer$b David, $4ctb$4https://id.loc.gov/vocabulary/relators/ctb 801 0$bDE-B1597 801 1$bDE-B1597 906 $aBOOK 912 $a9910862097103321 996 $aStatistics for astrophysics$94166551 997 $aUNINA