Results 11 to 20 of about 43,652 (301)

Asymptotic unbiased density estimators [PDF]

ESAIM: Probability and Statistics, 2009
Summary: This paper introduces a computationally tractable density estimator that has the same asymptotic variance as the classical Nadaraya-Watson density estimator but whose asymptotic bias is zero. We achieve this result using a two stage estimator that applies a multiplicative bias correction to an oversmooth pilot estimator.
Hengartner, Nicolas W., Matzner-Løber, Eric   +1 more
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Ultrafilter extensions of asymptotic density [PDF]

Commentationes Mathematicae Universitatis Carolinae, 2019
This interesting paper deals with \(\sigma\)-additivity of the \textit{density functions}, i.e., extensions of the asymptotic density to finitely additive measures on the power set of natural numbers. In particular, given a free ultrafilter \(U\) on \(\mathbb{N}\), properties of the \(d_U\)-\textit{density} defined by \[d_U(A)=U\text{-}\lim \frac{|A ...
Grebík, Jan
openaire   +4 more sources

Asymptotic Expansion of Risk-Neutral Pricing Density

International Journal of Financial Studies, 2018
A new method for pricing contingent claims based on an asymptotic expansion of the dynamics of the pricing density is introduced. The expansion is conducted in a preferred coordinate frame, in which the pricing density looks stationary.
Thomas Mazzoni
doaj   +2 more sources

On the Connection Between the Beurling-Malliavin Density and the Asymptotic Density

Uniform distribution theory
Abstract We study the notion of Beurling-Malliavin density from the point of view of Number Theory. We prove a general relation between the Beurling-Malliavin density and the upper asymptotic density; we identify a class of sequences for which the two densities coincide; this class contains the arithmetic progressions.
Giuliano, Rita, Grekos, Georges
core   +5 more sources

Comparing weighted densities

Journal of Inequalities and Applications, 2022
In this paper we study inequalities between weighted densities of sets of natural numbers corresponding to different weight functions. Depending on the asymptotic relation between the weight functions, we give sharp bounds for possible values of one ...
József Bukor, Ferdinánd Filip, Jan Šustek, János T. Tóth   +3 more
doaj   +1 more source

Asymptotics for in-sample density forecasting [PDF]

The Annals of Statistics, 2015
Published in at http://dx.doi.org/10.1214/14-AOS1288 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Lee, Young K., Mammen, Enno, Nielsen, Jens P., Park, Byeong U.   +3 more
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Statistical Convergence of Nets Through Directed Sets

Universal Journal of Mathematics and Applications, 2019
The concept of statistical convergence based on asymptotic density is introduced in this article through nets. Some possible extensions of classical results for statistical convergence of sequences are obtained in this article, with extensions to nets.
Ar Murugan, J. Dianavinnarasi, C. Ganesa Moorthy   +2 more
doaj   +1 more source

Asymptotic results for the first and second moments and numerical computations in discrete-time bulk-renewal process [PDF]

Yugoslav Journal of Operations Research, 2019
This paper introduces a simplified solution to determine the asymptotic results for the renewal density. It also offers the asymptotic results for the first and second moments of the number of renewals for the discrete-time bulk-renewal process.
Kim James J., Chaudhry Mohan L., Mansur Abdalla   +2 more
doaj   +1 more source

Information Geometry of the Exponential Family of Distributions with Progressive Type-II Censoring

Entropy, 2021
In geometry and topology, a family of probability distributions can be analyzed as the points on a manifold, known as statistical manifold, with intrinsic coordinates corresponding to the parameters of the distribution. Consider the exponential family of
Fode Zhang, Xiaolin Shi, Hon Keung Tony Ng   +2 more
doaj   +1 more source

Intrinsic density, asymptotic computability, and stochasticity [PDF]

The Bulletin of Symbolic Logic, 2021
AbstractThere are many computational problems which are generally “easy” to solve but have certain rare examples which are much more difficult to solve. One approach to studying these problems is to ignore the difficult edge cases. Asymptotic computability is one of the formal tools that uses this approach to study these problems.
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