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Nonparametric Estimation for Control Engineering
 Proceedings of the 4th WSEAS/IASME International Conference DYNAMICAL SYSTEMS and CONTROL (CONTROL'08) Corfu
"... in particular statistical kernel estimators – for control engineering. Such methods allow the useful characterization of probability distributions without arbitrary assumptions regarding their membership to a fixed class. A detailed description of the Bayes parameter estimation with asymmetrical pol ..."
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Cited by 5 (2 self)
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research and calculations. KeyWords: soft computing, nonparametric estimation, kernel estimators, information technology, data analysis and
Applicational possibilities of nonparametric estimation
"... Abstract. Together with the dynamic development of modern computer systems, the possibilities of applying refined methods of nonparametric estimation to control engineering tasks have grown just as fast. This broad and complex theme is presented in this paper for the case of estimation of density o ..."
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Abstract. Together with the dynamic development of modern computer systems, the possibilities of applying refined methods of nonparametric estimation to control engineering tasks have grown just as fast. This broad and complex theme is presented in this paper for the case of estimation of density
_________________________________________________________________________________ Nonparametric estimation of diffusion process: a closer look
, 2004
"... Nonparametric estimation of diffusion process: a closer look ..."
Nonparametric estimation of conditional distributions ∗
, 2005
"... Estimation of conditional distributions is considered. It is assumed that the conditional distribution is either discrete or that it has a density with respect to the LebesgueBorelmeasure. Partitioning estimates of the conditional distribution are constructed and results concerning consistency and ..."
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Cited by 8 (0 self)
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Estimation of conditional distributions is considered. It is assumed that the conditional distribution is either discrete or that it has a density with respect to the LebesgueBorelmeasure. Partitioning estimates of the conditional distribution are constructed and results concerning consistency
Nonparametric Estimation Of Jump Surface
, 1997
"... In this paper, we discuss estimation of bivariate jump regression functions. An a.s. consistent estimator of the jump location curve is suggested. This estimator is based on difference of two onesided kernel smoothers. A rotation transformation is also used. We consider an ideal case that the jump ..."
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Cited by 8 (4 self)
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In this paper, we discuss estimation of bivariate jump regression functions. An a.s. consistent estimator of the jump location curve is suggested. This estimator is based on difference of two onesided kernel smoothers. A rotation transformation is also used. We consider an ideal case that the jump
Nonparametric estimation of finite mixtures
, 2013
"... Abstract. The aim of this paper is to provide simple nonparametric methods to estimate finitemixture models from data with repeated measurements. Three measurements suffice for the mixture to be fully identified and so our approach can be used even with very short panel data. We provide distribution ..."
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Cited by 4 (2 self)
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Abstract. The aim of this paper is to provide simple nonparametric methods to estimate finitemixture models from data with repeated measurements. Three measurements suffice for the mixture to be fully identified and so our approach can be used even with very short panel data. We provide
NONPARAMETRIC ESTIMATION BY CONVEX PROGRAMMING
, 2009
"... The problem we concentrate on is as follows: given (1) a convex compact set X in R n, an affine mapping x ↦ → A(x), a parametric family {pμ(·)} of probability densities and (2) N i.i.d. observations of the random variable ω, distributed with the density pA(x)(·) for some (unknown) x ∈ X, estimate th ..."
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Cited by 6 (4 self)
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The problem we concentrate on is as follows: given (1) a convex compact set X in R n, an affine mapping x ↦ → A(x), a parametric family {pμ(·)} of probability densities and (2) N i.i.d. observations of the random variable ω, distributed with the density pA(x)(·) for some (unknown) x ∈ X, estimate
Nonparametric Estimation of Large Covariance
 Matrices of Longitudinal Data,’’ Biometrika
, 2003
"... matrices of longitudinal data ..."
Identification and Nonparametric Estimation of a . . .
"... Let r (x, z) be a function that, along with its derivatives, can be consistently estimated nonparametrically. This paper discusses identification and consistent estimation of the unknown functions H, ..."
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Let r (x, z) be a function that, along with its derivatives, can be consistently estimated nonparametrically. This paper discusses identification and consistent estimation of the unknown functions H,
A note on nonparametric estimations
 In the conference volume to the 65. birthday of Miklós Csörgő.759–774
, 1998
"... Dedicated to Miklós Csörgő on the occasion of his 65th birthday Abstract: We give an informal explanation with the help of a Taylor expansion about the most important properties of the maximum likelihood estimate in the parametric case. Then an analogous estimate in two nonparametric models, in the ..."
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Dedicated to Miklós Csörgő on the occasion of his 65th birthday Abstract: We give an informal explanation with the help of a Taylor expansion about the most important properties of the maximum likelihood estimate in the parametric case. Then an analogous estimate in two nonparametric models
Results 11  20
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7,997