The stochastic approximation method for the estimation of a multivariate probability density
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Publication:1015895
DOI10.1016/j.jspi.2008.11.012zbMath1160.62077arXiv0807.2960OpenAlexW2121087843WikidataQ57519991 ScholiaQ57519991MaRDI QIDQ1015895
Mariane Pelletier, Abdelkader Mokkadem, Yousri Slaoui
Publication date: 30 April 2009
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0807.2960
Density estimation (62G07) Nonparametric tolerance and confidence regions (62G15) Stochastic approximation (62L20)
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Cites Work
- Unnamed Item
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- A one-measurement form of simultaneous perturbation stochastic approximation
- Optimal order of accuracy of search algorithms in stochastic optimization
- Recursive estimation of the mode of a multivariate distribution
- Lower rate of convergence for locating a maximum of a function
- Almost sure approximations to the Robbins-Monro and Kiefer-Wolfowitz processes with dependent noise
- Effect of bias estimation on coverage accuracy of bootstrap confidence intervals for a probability density
- Stochastic approximation methods for constrained and unconstrained systems
- Remarks on some recursive estimators of a probability density
- The law of the iterated logarithm for a triangular array of empirical processes
- Accelerated randomized stochastic optimization.
- Stochastic algorithms
- A companion for the Kiefer-Wolfowitz-Blum stochastic approximation algorithm
- A unified theory of regularly varying sequences
- Remarks on Some Nonparametric Estimates of a Density Function
- Exact rates of almost sure convergence of a recursive kernel estimate of a probability densiy function: Application to regression and hazard rate estimation
- Compact Law of the Iterated Logarithm for Matrix-Normalized Sums of Random Vectors
- Laws of the iterated logarithm for nonparametric density estimators
- How to apply the method of stochastic approximation in the non-parametric estimation of a regression function1
- On the efficiency of on-line density estimators
- Weighted Means in Stochastic Approximation of Minima
- A Kiefer-Wolfowitz algorithm with randomized differences
- Stochastic Approximation of Minima with Improved Asymptotic Speed
- Asymptotically optimal discriminant functions for pattern classification
- Regularly Varying Sequences
- A Note on Permanents
- On Estimation of a Probability Density Function and Mode
- Stochastic Estimation of the Maximum of a Regression Function
- Multidimensional Stochastic Approximation Methods
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