Results 31 to 40 of about 1,695,629 (282)
Discrete probability density estimation using multirate DSP models [PDF]
, 2003 We propose a model based approach for estimation of probability mass functions for discrete random variables. The model is based on tools from multirate signal processing.
Vaidyanathan, P. P., Yoon, Byung-Jun
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High throughput nonparametric probability density estimation. [PDF]
PLoS ONE, 2018 In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity.
Jenny Farmer, Donald Jacobs
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Beating noise with abstention in state estimation [PDF]
, 2012 We address the problem of estimating pure qubit states with non-ideal (noisy) measurements in the multiple-copy scenario, where the data consists of a number N of identically prepared qubits.
Bagan E Munoz-Tapia R Olivares-Renteria G A Bergou J A +11 more
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Remote State Estimation with Smart Sensors over Markov Fading Channels
, 2021 We consider a fundamental remote state estimation problem of discrete-time linear time-invariant (LTI) systems. A smart sensor forwards its local state estimate to a remote estimator over a time-correlated $M$-state Markov fading channel, where the ...
Johansson, Karl Henrik +4 more
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Asymptotic Estimates Using Probability
Advances in Mathematics, 1998 The authors use probabilistic arguments in the spirit of the De Moivre-Laplace central limit theorem to obtain asymptotic estimates for combinatorial sums. The main question under discussion is the following. For a given sequence \(\chi_n=\sum_{\lambda\vdash n}f(\lambda)\chi_{\lambda}\) of \(S_n\)-characters defined in terms of the associated Young ...
Beckner, William, Regev, Amitai
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Revisiting the Optimal Probability Estimator from Small Samples for Data Mining
International Journal of Applied Mathematics and Computer Science, 2019 Estimation of probabilities from empirical data samples has drawn close attention in the scientific community and has been identified as a crucial phase in many machine learning and knowledge discovery research projects and applications.
Cestnik Bojan
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Maximal uniform convergence rates in parametric estimation problems [PDF]
, 2008 This paper considers parametric estimation problems with independent, identically nonregularly distributed data. It focuses on rate efficiency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality ...
Akahira +10 more
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Estimating tail probabilities [PDF]
, 1982 This paper investigates procedures for univariate nonparametric estimation of tail probabilities. Extrapolated values for tail probabilities beyond the data are also obtained based on the shape of the density in the tail. Several estimators which use exponential weighting are described.
Carr, D. B., Tolley, H. D.
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A Method for Assessing a Causation Factor for a Geometrical MDTC Model for Ship-Ship Collision Probability Estimation [PDF]
TransNav, 2011 In this paper a comparative method for assessing a causation factor for a geometrical model for ship-ship collision probability estimation is introduced.
Jakub Montewka +3 more
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Accuracy and Precision of Insect Density and Impact Estimates [PDF]
, 2017 In estimating insect density and impact, entomologists are understandably interested in accuracy of estimation, but they almost always are dealing with precision because of bias due to an invalid estimator, probability sampling, or nonsampling errors ...
Fowler, Gary W, Witter, John A
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