Results 11 to 20 of about 231,426 (276)
Nonparametric Mean Estimation for Big-but-Biased Data
Proceedings, 2018 Some authors have recently warned about the risks of the sentence with enough data, the numbers speak for themselves. The problem of nonparametric statistical inference in big data under the presence of sampling bias is considered in this work.
Laura Borrajo, Ricardo Cao
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Media Statistika, 2008 If X is predictor variable and Y is response variable of following model Y = f (X) +e with function f is regression which not yet been known and e is independent random variable with mean 0 and variant , hence function of f can estimate with parametric ...
Suparti Suparti +2 more
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Characterization of the asymptotic distribution of semiparametric M-estimators [PDF]
, 2010 This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.
Ichimura, H, Lee, S
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The Annals of Mathematical Statistics, 1951 In the three papers, [1], [2], [3], entitled "Nonparametric estimation", Scheffe and Tukey generalized previous results on tolerance regions and extended them to cover all continuous and discontinuous distribution functions. This note contains four comments arising from these papers: first, on a method for giving bounds to the confidence level in the ...
Fraser, D. A. S., Wormleighton, R.
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Mathematics, 2023 For nonparametric regression estimation, conventional research all focus on isotropic regression function. In this paper, a linear wavelet estimator of anisotropic regression function is constructed, the rate of convergence of this estimator is discussed
Jia Chen, Junke Kou
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Nonparametric Bayesian Volatility Estimation [PDF]
SSRN Electronic Journal, 2018 Given discrete time observations over a fixed time interval, we study a nonparametric Bayesian approach to estimation of the volatility coefficient of a stochastic differential equation. We postulate a histogram-type prior on the volatility with piecewise constant realisations on bins forming a partition of the time interval. The values on the bins are
Gugushvili, S. +3 more
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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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Partition Learning for Multiagent Planning
Journal of Robotics, 2012 Automated surveillance of large geographic areas and target tracking by a team of autonomous agents is a topic that has received significant research and development effort. The standard approach is to decompose this problem into two steps.
Jared Wood, J. Karl Hedrick
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Nonparametric Estimation of the Interval Reliability [PDF]
Journal of Statistical Theory and Applications (JSTA), 2014 The interval reliability of a repairable system is the probability that the system is operating at a specified time and will continue to operate for a specified interval of time.
Angel Mathew, N. Balakrishna
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