High-Dimensional Regression Modeling

Methodology, Applications, and Software

Patrick Breheny, Jian Huang (Autoren)

Buch | Hardcover

450 Seiten

2024
Apple Academic Press Inc. (Verlag)
978-1-4822-4997-2 (ISBN)

Infos

This book covers the methodology, applications, and software used in high-dimensional regression modeling. Data collected in many fields is high-dimensional in the sense that many characteristics, or features, are recorded for each observation. The collection of this kind of data is a relatively recent phenomenon, and it poses many challenges that traditional statistical methods have proven incapable of addressing. During the past decade, penalized regression models have become a widespread and important tool for analyzing these kinds of data sets.

Inhalt

FOUNDATIONS. Introduction. The Lasso. Bias reduction. Stability and ridge-type penalties. INFERENCE. False discovery rates. Confidence intervals and hypothesis tests. Variable selection with FDR control. Resampling approaches to inference. OTHER LIKELIHOOD/LOSS FUNCTIONS. Logistic regression and generalized linear models. Cox regression. Accelerate failure time model. Robust regression. STRUCTURED SPARSITY. Bi-level selection. Fusion penalties. Additive and semiparametric models. Multivariate outcomes. Variable selection for interactions.

Produkt-Details

• Erscheinungsdatum: 30.08.2018
• Reihe/Serie: Chapman & Hall/CRC Texts in Statistical Science
• Zusatzinfo: 20 Illustrations, black and white
• Verlagsort: Oakville
• Sprache: englisch
• Maße: 156 x 234 mm
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Technik ► Umwelttechnik / Biotechnologie
• ISBN-10: 1-4822-4997-9 / 1482249979
• ISBN-13: 978-1-4822-4997-2 / 9781482249972
• Zustand: Neuware