English
Related papers

Related papers: Nonparametric estimation of the tree structure of …

200 papers

Recent work has proven the existence of extreme inbreeding in a European ancestry sample taken from the contemporary UK population \cite{nature_01}. This result brings our attention again to a math problem related to inbreeding family trees…

Populations and Evolution · Quantitative Biology 2021-09-08 C. Jarne , F A. Gómez Albarracín , M. Caruso

We consider the task of learning Ising models when the signs of different random variables are flipped independently with possibly unequal, unknown probabilities. In this paper, we focus on the problem of robust estimation of…

Machine Learning · Statistics 2020-06-11 Ashish Katiyar , Vatsal Shah , Constantine Caramanis

We describe here a new method to estimate copula measure. From N observations of two variables X and Y, we draw a huge number m of subsamples (size n<N), and we compute the joint ranks in these subsamples. Then, for each bivariate rank…

Methodology · Statistics 2007-09-26 Jérôme Collet

In this paper, a robust non-parametric measure of statistical dependence, or correlation, between two random variables is presented. The proposed coefficient is a permutation-like statistic that quantifies how much the observed sample S_n :…

Methodology · Statistics 2020-07-27 Rami Mahdi

Tree-based networks are a class of phylogenetic networks that attempt to formally capture what is meant by "tree-like" evolution. A given non-tree-based phylogenetic network, however, might appear to be very close to being tree-based, or…

Populations and Evolution · Quantitative Biology 2020-01-17 Mareike Fischer , Andrew Francis

When the copula of the conditional distribution of two random variables given a covariate does not depend on the value of the covariate, two conflicting intuitions arise about the best possible rate of convergence attainable by…

Statistics Theory · Mathematics 2017-05-17 François Portier , Johan Segers

An efficient advanced numerical model for mapping the distribution of the buried tree roots is presented. It not only simplify the complicate root branches to an easy manipulated model, but also grasp the main structure of tree roots…

Geophysics · Physics 2025-01-16 Xiaolong Liang , Xiaoping Wu

Archimedean copulas are a popular type of copulas in which a variant of the Archimedean axiom apply. We provide a topological proof of the Archimedean Axiom which is applicable for non-continuous distribution functions.

Statistics Theory · Mathematics 2025-01-06 Victory Idowu

Consider jointly Gaussian random variables whose conditional independence structure is specified by a graphical model. If we observe realizations of the variables, we can compute the covariance matrix, and it is well known that the support…

Machine Learning · Statistics 2019-01-28 Ashish Katiyar , Jessica Hoffmann , Constantine Caramanis

In linear regression problems with related predictors, it is desirable to do variable selection and estimation by maintaining the hierarchical or structural relationships among predictors. In this paper we propose non-negative garrote…

Applications · Statistics 2010-11-03 Ming Yuan , V. Roshan Joseph , Hui Zou

An Archimedean copula is characterised by its generator. This is a real function whose inverse behaves as a survival function. We propose a semiparametric generator based on a quadratic spline. This is achieved by modelling the first…

Statistics Theory · Mathematics 2019-08-13 Ricardo Hoyos , Luis Nieto-Barajas

Many scientific and engineering challenges -- ranging from personalized medicine to customized marketing recommendations -- require an understanding of treatment effect heterogeneity. In this paper, we develop a non-parametric causal forest…

Methodology · Statistics 2017-07-11 Stefan Wager , Susan Athey

This article proposes copula-based dependence quantification between multiple groups of random variables of possibly different sizes via the family of $Phi$-divergences. An axiomatic framework for this purpose is provided, after which we…

Statistics Theory · Mathematics 2023-02-28 Steven De Keyser , Irène Gijbels

Standard methods of using categorical variables as predictors either endow them with an ordinal structure or assume they have no structure at all. However, categorical variables often possess structure that is more complicated than a linear…

Machine Learning · Statistics 2020-04-17 Brian Lucena

We study the asymptotic rank of adjacency matrices of a large class of edge-weighted configuration models. Here, the weight of a (multi-)edge can be any fixed non-zero element from an arbitrary field, as long as it is independent of the…

Combinatorics · Mathematics 2025-08-06 Remco van der Hofstad , Noela Müller , Haodong Zhu

Comparing multivariate yield quality distributions across spatially referenced agricultural fields is complicated by two pervasive features: non-normality and spatial autocorrelation. Classical procedures such as ANOVA, MANOVA, and standard…

Methodology · Statistics 2026-03-03 Marco Mandap

Regression trees and their ensemble methods are popular methods for nonparametric regression: they combine strong predictive performance with interpretable estimators. To improve their utility for locally smooth response surfaces, we study…

Methodology · Statistics 2021-09-13 Sören R. Künzel , Theo F. Saarinen , Edward W. Liu , Jasjeet S. Sekhon

The concept of weighted infinitesimal bialgebras provides an algebraic framework for understanding the non-homogeneous associative Yang-Baxter equation. In this paper, we endow the space of decorated planar rooted forests with a…

Combinatorics · Mathematics 2025-10-15 Loïc Foissy , Yunzhou Xie , Dawei Zhang , Yi Zhang

We analyze the structure of two dimensional disordered cellular systems generated by extensive computer simulations. These cellular structures are studied as topological trees rooted on a central cell or as closed shells arranged…

Disordered Systems and Neural Networks · Physics 2009-10-30 H. M. Ohlenbusch , T. Aste , B. Dubertret , N. Rivier

We propose, for multivariate Gaussian copula models with unknown margins and structured correlation matrices, a rank-based, semiparametrically efficient estimator for the Euclidean copula parameter. This estimator is defined as a one-step…

Methodology · Statistics 2014-10-02 Johan Segers , Ramon van den Akker , Bas J. M. Werker
‹ Prev 1 3 4 5 6 7 10 Next ›