Flexible Nonparametric Curve Estimation
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...
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| Format: | Électronique eBook |
| Langue: | anglais |
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Cham :
Springer International Publishing : Imprint: Springer,
2024.
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| Édition: | 1st ed. 2024. |
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| Accès en ligne: | https://doi.org/10.1007/978-3-031-66501-1 |
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| Résumé: | 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. |
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| Description matérielle: | 1 online resource (VIII, 304 p. 79 illus.). 50 illus. in color. |
| ISBN: | 9783031665011 |
| DOI: | 10.1007/978-3-031-66501-1 |