High-Dimensional Regression Modeling
Methodology, Applications, and Software
Seiten
2024
Apple Academic Press Inc. (Verlag)
978-1-4822-4997-2 (ISBN)
Apple Academic Press Inc. (Verlag)
978-1-4822-4997-2 (ISBN)
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.
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.
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 |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Umwelttechnik / Biotechnologie | |
ISBN-10 | 1-4822-4997-9 / 1482249979 |
ISBN-13 | 978-1-4822-4997-2 / 9781482249972 |
Zustand | Neuware |
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