Almost optimal convergence rates for kernel density estimation under association
Exponential inequalities for associated variables are derived under an assumption milder than the absolute continuity of joint distributions of the sample variables. This inequality is used to prove convergence rates for the kernel estimator for the density which are just slightly slower than the op...
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| Formato: | other |
| Idioma: | eng |
| Publicado em: |
2004
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| Texto completo: | http://hdl.handle.net/10316/11422 |
| País: | Portugal |
| Oai: | oai:estudogeral.sib.uc.pt:10316/11422 |
| Resumo: | Exponential inequalities for associated variables are derived under an assumption milder than the absolute continuity of joint distributions of the sample variables. This inequality is used to prove convergence rates for the kernel estimator for the density which are just slightly slower than the optimal rates known form independent samples. |
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