Estimation of P{Y
J. Bartoszewicz (1977)
Applicationes Mathematicae
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Displaying similar documents to “About a fixed precision estimation of the parameter of uniform density”
Estimation of P{Y
Dependent Gaussian samples: estimation of the scatter uniform in dimension.
Sudakov, V.N., Sudakov, A.V. (2004)
Zapiski Nauchnykh Seminarov POMI
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Two problems of minimax estimation
S. Trybuła (1974)
Applicationes Mathematicae
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Fixed precision estimation of a normal mean
Beniamin Goldys (1985)
Banach Center Publications
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On One Estimation Problem
Jelena Bulatović, Alobodanka Janjić (1979)
Publications de l'Institut Mathématique
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Consistency of a Nonparametric Estimation of a Density Functional.
I.A. Ahmad, P.E. Lin (1983)
Metrika
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Simultaneous minimax estimation of parameters of multinomial distribution
Stanisław Trybuła (2002)
Applicationes Mathematicae
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The problem of minimax estimation of parameters of multinomial distribution is considered for a loss function being the sum of the losses of the statisticians taking part in the estimation process.
Bayesian density estimation.
Ghosh, Jayanta K. (1998)
Documenta Mathematica
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On the inequality of Mathieu.
Acu, Dumitru (1996)
General Mathematics
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On estimation and detection of infinite-variable functions.
Ingster, Yu., Suslina, I. (2005)
Zapiski Nauchnykh Seminarov POMI
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On estimation of parameters in linear models
R. Zmyślony (1976)
Applicationes Mathematicae
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Nonparametric Maximum Likelihood Estimation of a Probability Density via Mathematical Programming.
J. Fischer (1982)
Metrika
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Density smoothness estimation problem using a wavelet approach
Karol Dziedziul, Bogdan Ćmiel (2014)
ESAIM: Probability and Statistics
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In this paper we consider a smoothness parameter estimation problem for a density function. The smoothness parameter of a function is defined in terms of Besov spaces. This paper is an extension of recent results (K. Dziedziul, M. Kucharska, B. Wolnik, ). The construction of the estimator is based on wavelets coefficients. Although we believe that the effective estimation of the smoothness parameter is impossible in general case, we can show that it becomes possible for some classes...
An approximate necessary condition for the optimal bandwidth selector in kernel density estimation
L. Gajek, A. Lenic (1993)
Applicationes Mathematicae
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An approximate necessary condition for the optimal bandwidth choice is derived. This condition is used to construct an iterative bandwidth selector. The algorithm is based on resampling and step-wise fitting the bandwidth to the density estimator from the previous iteration. Examples show fast convergence of the algorithm to the bandwidth value which is surprisingly close to the optimal one no matter what is the initial knowledge on the unknown density.
On minimax estimation of the parameter in the Pólya urn scheme
A. Styszyński (1984)
Applicationes Mathematicae
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Aspects of Nonparametric Density Estimation, CWI Tract 77 - A. J. van Es.
W. Wertz (1994)
Metrika
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