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Flexible Nonparametric Curve Estimation / edited by Hassan Doosti

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Cham : Springer International Publishing, 2024Publisher: Cham : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(VIII, 304 p. 79 illus., 50 illus. in color.)ISBN:
  • 9783031665011
Subject(s): Additional physical formats: 9783031665004 | 9783031665028 | 9783031665035 | Erscheint auch als: 9783031665004 Druck-Ausgabe | Erscheint auch als: 9783031665028 Druck-Ausgabe | Erscheint auch als: 9783031665035 Druck-AusgabeDOI: DOI: 10.1007/978-3-031-66501-1Online resources: Summary: - Tilted Nonparametric Regression Function Estimation -- Some Asymptotic Properties of Kernel Density Estimation Under Length-Biased and Right-Cencored Data -- Functional Data Analysis: Key Concepts and Applications -- Convolution Process revisited in finite location mixtures and GARFISMA long memory time series -- Non-parametric Estimation of Tsallis Entropy and Residual Tsallis Entropy Under ρ-mixing Dependent Data -- Non-parametric intensity estimation for spatial point patterns with R -- A Censored Semicontinuous Regression for Modeling Clustered /Longitudinal Zero-Inflated Rates and Proportions: An Application to Colorectal Cancer -- Singular Spectrum Analysis -- Hellinger-Bhattacharyya cross-validation for shape-preserving multivariate wavelet thresholding -- Bayesian nonparametrics and mixture modelling -- A kernel scale mixture of the skew-normal distribution -- M-estimation of an intensity function and an underlying population size under random right truncation.Summary: This book delves into the realm of nonparametric estimations, offering insights into essential notions such as probability density, regression, Tsallis Entropy, Residual Tsallis Entropy, and intensity functions. Through a series of carefully crafted chapters, the theoretical foundations of flexible nonparametric estimators are examined, complemented by comprehensive numerical studies. From theorem elucidation to practical applications, the text provides a deep dive into the intricacies of nonparametric curve estimation. Tailored for postgraduate students and researchers seeking to expand their understanding of nonparametric statistics, this book will serve as a valuable resource for anyone who wishes to explore the applications of flexible nonparametric techniques.PPN: PPN: 1902232933Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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