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| Online-Ressource |
Titel: | Flexible Nonparametric Curve Estimation |
Mitwirkende: | Doosti, Hassan [HerausgeberIn]  |
Verf.angabe: | edited by Hassan Doosti |
Ausgabe: | 1st ed. 2024. |
Verlagsort: | Cham |
| Cham |
Verlag: | Springer International Publishing |
| Imprint: Springer |
E-Jahr: | 2024 |
Jahr: | 2024. |
| 2024. |
Umfang: | 1 Online-Ressource(VIII, 304 p. 79 illus., 50 illus. in color.) |
ISBN: | 978-3-031-66501-1 |
Abstract: | - 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. |
| 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. |
DOI: | doi:10.1007/978-3-031-66501-1 |
URL: | Resolving-System: https://doi.org/10.1007/978-3-031-66501-1 |
| DOI: https://doi.org/10.1007/978-3-031-66501-1 |
Datenträger: | Online-Ressource |
Sprache: | eng |
Bibliogr. Hinweis: | Erscheint auch als : Druck-Ausgabe |
| Erscheint auch als : Druck-Ausgabe |
| Erscheint auch als : Druck-Ausgabe |
K10plus-PPN: | 1902232933 |
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Lokale URL UB: | Zum Volltext |
978-3-031-66501-1
Flexible Nonparametric Curve Estimation / Doosti, Hassan [HerausgeberIn]; 2024. (Online-Ressource)
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