Results 31 to 40 of about 1,618 (122)
Nonparametric C- and D-vine-based quantile regression
Dependence Modeling, 2022 Quantile regression is a field with steadily growing importance in statistical modeling. It is a complementary method to linear regression, since computing a range of conditional quantile functions provides more accurate modeling of the stochastic ...
Tepegjozova Marija +3 more
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Estimation error for blind Gaussian time series prediction [PDF]
, 2011 We tackle the issue of the blind prediction of a Gaussian time series. For this, we construct a projection operator build by plugging an empirical covariance estimation into a Schur complement decomposition of the projector. This operator is then used to
Espinasse, Thibault +2 more
core +3 more sources
About tests of the “simplifying” assumption for conditional copulas
Dependence Modeling, 2017 We discuss the so-called “simplifying assumption” of conditional copulas in a general framework. We introduce several tests of the latter assumption for non- and semiparametric copula models.
Derumigny Alexis, Fermanian Jean-David
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Local linear approach: Conditional density estimate for functional and censored data
Demonstratio Mathematica, 2022 Let YY be a random real response, which is subject to right censoring by another random variable CC. In this paper, we study the nonparametric local linear estimation of the conditional density of a scalar response variable and when the covariable takes ...
Benkhaled Abdelkader, Madani Fethi
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Majalah Ilmiah Matematika dan Statistika, 2023 Covid cases in Indonesia have started to decline since the vaccination program was carried out in January 2021. Until now the vaccination program in Indonesia has reached the third vaccination stage or booster vaccine.
Fadilla Zundina Ulya +3 more
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An iterative tomogravity algorithm for the estimation of network traffic
, 2007 This paper introduces an iterative tomogravity algorithm for the estimation of a network traffic matrix based on one snapshot observation of the link loads in the network.
Fang, Jiangang +2 more
core +1 more source
Strong consistency of regression function estimator with martingale difference errors
Open Mathematics, 2021 In this paper, we consider the regression model with fixed design: Yi=g(xi)+εi{Y}_{i}=g\left({x}_{i})+{\varepsilon }_{i}, 1≤i≤n1\le i\le n, where {xi}\left\{{x}_{i}\right\} are the nonrandom design points, and {εi}\left\{{\varepsilon }_{i}\right\} is a ...
Chen Yingxia
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Lasso type classifiers with a reject option
, 2007 We consider the problem of binary classification where one can, for a particular cost, choose not to classify an observation. We present a simple proof for the oracle inequality for the excess risk of structural risk minimizers using a lasso type penalty.
Wegkamp, Marten
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Marshall's lemma for convex density estimation
, 2007 Marshall's [Nonparametric Techniques in Statistical Inference (1970) 174--176] lemma is an analytical result which implies $\sqrt{n}$--consistency of the distribution function corresponding to the Grenander [Skand. Aktuarietidskr.
Duembgen, Lutz +2 more
core +2 more sources
Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions
Dependence ModelingKendall’s tau and conditional Kendall’s tau matrices are multivariate (conditional) dependence measures between the components of a random vector. For large dimensions, available estimators are computationally expensive and can be improved by averaging ...
van der Spek Rutger, Derumigny Alexis
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