Abstract
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.
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.
| Original language | English |
|---|---|
| Place of Publication | Cham |
| Publisher | Springer, Springer Nature |
| Number of pages | 304 |
| ISBN (Electronic) | 9783031665011 |
| ISBN (Print) | 9783031665004, 9783031665035 |
| DOIs | |
| Publication status | Published - 2024 |
Keywords
- Nonparametric Estimation
- Probability Density Function
- Regresssion
- Kernel Estimator
- Survival Function
Fingerprint
Dive into the research topics of 'Flexible nonparametric curve estimation'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver