LEADER 04593nam 22006855 450 001 9910983031403321 005 20250922143225.0 010 $a9781071641323 010 $a1071641328 024 7 $a10.1007/978-1-0716-4132-3 035 $a(CKB)37313064200041 035 $a(MiAaPQ)EBC31886136 035 $a(Au-PeEL)EBL31886136 035 $a(DE-He213)978-1-0716-4132-3 035 $a(EXLCZ)9937313064200041 100 $a20250122d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical Modeling and Computation /$fby Joshua C. C. Chan, Dirk P. Kroese 205 $a2nd ed. 2025. 210 1$aNew York, NY :$cSpringer US :$cImprint: Springer,$d2025. 215 $a1 online resource (782 pages) 225 1 $aSpringer Texts in Statistics,$x2197-4136 311 08$a9781071641316 311 08$a107164131X 327 $aProbability Models -- Random Variables and Probability Distributions -- Joint Distributions -- Common Statistical Models -- Statistical Inference -- Likelihood -- Monte Carlo Sampling -- Bayesian Inference -- Generalized Linear Models -- Dependent Data Models -- State Space Models -- References -- Solutions -- MATLAB Primer -- Mathematical Supplement -- Index. 330 $aThis book, Statistical Modeling and Computation, provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. The 2nd edition changes the programming language used in the text from MATLAB to Julia. For all examples with computing components, the authors provide data sets and their own Julia codes. The new edition features numerous full color graphics to illustrate the concepts discussed in the text, and adds three entirely new chapters on a variety of popular topics, including: Regularization and the Lasso regression Bayesian shrinkage methods Nonparametric statistical tests Splines and the Gaussian process regression Joshua C. C. Chan is Professor of Economics, and holds the endowed Olson Chair at Purdue University. He is an elected fellow at the International Association for Applied Econometrics and served as Chair for the Economics, Finance and Business Section of the International Society for Bayesian Analysis from 2020-2022. His research focuses on building new high-dimensional time-series models and developing efficient estimation methods for these models. He has published over 50 papers in peer-reviewed journals, including some top-field journals such as Journal of Econometrics, Journal of the American Statistical Association and Journal of Business and Economic Statistics. Dirk Kroese is Professor of Mathematics and Statistics at the University of Queensland. He is known for his significant contributions to the fields of applied probability, mathematical statistics, machine learning, and Monte Carlo methods. He has published over 140 articles and 7 books. He is a pioneer of the well-known Cross-Entropy (CE) method, which is being used around the world to help solve difficult estimation and optimization problems in science, engineering, and finance. In addition to his scholarly contributions, Dirk Kroese is recognized for his role as an educator and mentor, having supervised and inspired numerous students and researchers. 410 0$aSpringer Texts in Statistics,$x2197-4136 606 $aMathematical statistics$xData processing 606 $aBiometry 606 $aStatistics 606 $aStatistics and Computing 606 $aBiostatistics 606 $aStatistical Theory and Methods 606 $aEstadística matemàtica$2thub 606 $aBiometria$2thub 606 $aEstadística$2thub 608 $aLlibres electrònics$2thub 615 0$aMathematical statistics$xData processing. 615 0$aBiometry. 615 0$aStatistics. 615 14$aStatistics and Computing. 615 24$aBiostatistics. 615 24$aStatistical Theory and Methods. 615 7$aEstadística matemàtica 615 7$aBiometria 615 7$aEstadística 676 $a519.5 700 $aChan$b Joshua$g(Joshua C. C.)$01859427 701 $aKroese$b Dirk P$0522154 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983031403321 996 $aStatistical Modeling and Computation$94463201 997 $aUNINA