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We consider in this paper a contamined regression model where the distribution of the contaminating component is known when the Eu- clidean parameters of the regression model, the noise distribution, the contamination ratio and the…

Statistics Theory · Mathematics 2011-11-10 Pierre Vandekerkhove

This paper studies identifiability and convergence behaviors for parameters of multiple types in finite mixtures, and the effects of model fitting with extra mixing components. First, we present a general theory for strong identifiability,…

Statistics Theory · Mathematics 2015-01-13 Nhat Ho , XuanLong Nguyen

Deriving stellar atmospheric parameters and chemical abundances from stellar spectra is crucial for understanding the evolution of the Milky Way. By performing a fitting with MARCS model atmospheric theoretical synthetic spectra combined…

Solar and Stellar Astrophysics · Physics 2023-06-28 Rui Wang , A-Li Luo , Shuo Zhang , Yuan-Sen Ting , Teaghan O'Briain , LAMOST MRS Collaboration

Mixture models are widely used to fit complex and multimodal datasets. In this paper we study mixtures with high dimensional sparse latent parameter vectors and consider the problem of support recovery of those vectors. While parameter…

Machine Learning · Computer Science 2022-09-13 Arya Mazumdar , Soumyabrata Pal

As we collect additional samples from a data population for which a known density function estimate may have been previously obtained by a black box method, the increased complexity of the data set may result in the true density being…

Machine Learning · Statistics 2022-10-28 Dat Do , Nhat Ho , XuanLong Nguyen

We study robust regression under a contamination model in which covariates are clean while the responses may be corrupted in an adaptive manner. Unlike the classical Huber's contamination model, where both covariates and responses may be…

Statistics Theory · Mathematics 2026-04-07 Ilias Diakonikolas , Chao Gao , Daniel M. Kane , Ankit Pensia , Dong Xie

We examine a quintessence model with a modified exponential potential given by $V(\phi) = V_0(1+e^{-\lambda \phi})$. Unlike quintessence with a standard exponential potential, our model can yield an acceptable accelerated expansion at late…

Cosmology and Nongalactic Astrophysics · Physics 2016-12-02 Hui-Yiing Chang , Robert J. Scherrer

We consider the problem of recovering a distribution function on the real line from observations additively contaminated with errors following the standard Laplace distribution. Assuming that the latent distribution is completely unknown…

Methodology · Statistics 2017-08-21 Catia Scricciolo

We consider a two-component mixture model with one known component. We develop methods for estimating the mixing proportion and the unknown distribution nonparametrically, given i.i.d.~data from the mixture model, using ideas from shape…

Methodology · Statistics 2015-11-10 Rohit Kumar Patra , Bodhisattva Sen

A new method is presented for recovering the abundances of Damped Ly alpha systems (DLAs) taking into account the effects of dust depletion. For the first time, possible variations of the chemical composition of the dust are taken into…

Astrophysics · Physics 2009-11-07 G. Vladilo

We consider an extension of the holographic Ricci dark energy model by introducing an interaction between dark energy and matter. In this model, the dark energy density is given by $rho_{Lambda}=-frac{1}{2}alpha M_{p}^{2}{R}$, where ${R}$…

Cosmology and Nongalactic Astrophysics · Physics 2010-04-06 Masashi Suwa , Takeshi Nihei

In a multiple testing context, we consider a semiparametric mixture model with two components where one component is known and corresponds to the distribution of $p$-values under the null hypothesis and the other component $f$ is…

Applications · Statistics 2013-04-04 Van Hanh Nguyen , Catherine Matias

We derive uniform convergence rates for the maximum likelihood estimator and minimax lower bounds for parameter estimation in two-component location-scale Gaussian mixture models with unequal variances. We assume the mixing proportions of…

Statistics Theory · Mathematics 2020-06-02 Tudor Manole , Nhat Ho

This work is concerned with the detection of a mixture distribution from a $\mathbb{R}$-valued sample. Given a sample $X_1,\dots,X_n$ and an even density $\phi$, our aim is to detect whether the sample distribution is $\phi(\cdot-\mu)$ for…

Statistics Theory · Mathematics 2016-01-22 Béatrice Laurent , Clément Marteau , Cathy Maugis-Rabusseau

We performed a theoretical investigation on the mixing-length parameter recovery from an eclipsing double-lined binary system. We focused on a syntetic system composed by a primary of mass M = 0.95 Msun and a secondary of M = 0.85 Msun.…

Solar and Stellar Astrophysics · Physics 2019-05-02 G. Valle , M. Dell'Omodarme , P. G. Prada Moroni , S. Degl'Innocenti

In this study, we address the inverse problem of recovering the Lam\'e parameters ($\lambda, \mu$) and the density $\rho$ of a medium from the Neumann-to-Dirichlet map for any dimension $d\geq 2$. This inverse problem finds its motivation…

Optimization and Control · Mathematics 2025-05-09 Houcine Meftahi , Chayma Nssibi

This paper concerns a spectral estimation problem in which we want to find a spectral density function that is consistent with estimated second-order statistics. It is an inverse problem admitting multiple solutions, and selection of a…

Optimization and Control · Mathematics 2019-08-08 Bin Zhu

The $\mu-\tau$ reflection symmetry of the lepton mixing matrix accommodates maximal atmospheric mixing ($\theta_{23}=\pi/4$) as well as maximal Dirac CP phase ($\delta=\pm \pi/2$) for the Dirac case. In the standard parametrization of the…

High Energy Physics - Phenomenology · Physics 2021-04-02 Chandan Duarah

Consider the following estimation problem: there are $n$ entities, each with an unknown parameter $p_i \in [0,1]$, and we observe $n$ independent random variables, $X_1,\ldots,X_n$, with $X_i \sim $ Binomial$(t, p_i)$. How accurately can…

Machine Learning · Computer Science 2017-11-23 Kevin Tian , Weihao Kong , Gregory Valiant

We consider a combined restarting and adaptive backtracking strategy for the popular Fast Iterative Shrinking-Thresholding Algorithm frequently employed for accelerating the convergence speed of large-scale structured convex optimization…

Optimization and Control · Mathematics 2023-07-27 Jean-François Aujol , Luca Calatroni , Charles Dossal , Hippolyte Labarrière , Aude Rondepierre
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