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Related papers: Penalization of Galton-Watson processes

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Given a random walk $(S_n)$ with typical step distributed according to some fixed law and a fixed parameter $p \in (0,1)$, the associated positively step-reinforced random walk is a discrete-time process which performs at each step, with…

Probability · Mathematics 2022-10-19 Marco Bertenghi , Alejandro Rosales-Ortiz

In this article, we develop a semigroup-theoretic framework for the analytic characterisation of martingales with path-dependent terminal conditions. Our main result establishes that a measurable adapted process of the form \[ V(t) -…

Probability · Mathematics 2025-07-03 Robert Denk , Markus Kunze , Michael Kupper

We consider a stochastic process $Y$ defined by an integral in quadratic mean of a deterministic function $f$ with respect to a Gaussian process $X$, which need not have stationary increments. For a class of Gaussian processes $X$, it is…

Probability · Mathematics 2015-06-01 Rimas Norvaiša

We introduce a new empirical Bayes approach for large-scale multiple linear regression. Our approach combines two key ideas: (i) the use of flexible "adaptive shrinkage" priors, which approximate the nonparametric family of scale mixture of…

Methodology · Statistics 2024-06-13 Youngseok Kim , Wei Wang , Peter Carbonetto , Matthew Stephens

We prove local convergence results of rerooted conditioned multi-type Galton--Watson trees. The limit objects are multitype variants of the random sin-tree constructed by Aldous (1991), and differ according to which types recur infinitely…

Probability · Mathematics 2021-02-24 Benedikt Stufler

The Yamada-Watanabe theory provides a robust framework for understanding stochastic equations driven by Wiener processes. Despite its comprehensive treatment in the literature, the applicability of the theory to SPDEs driven by Poisson…

Probability · Mathematics 2025-01-07 Kistosil Fahim , Erika Hausenblas , Kenneth H. Karlsen

We construct $P(phi)_1$-processes indexed by the full time-line, separately derived from the functional integral representations of the relativistic and non-relativistic Nelson models in quantum field theory. These two cases differ…

Mathematical Physics · Physics 2020-11-25 Soumaya Gheryan , Fumio Hiroshima , Jozsef Lorinczi , Achref Majid , Habib Ouerdiane

We introduce a novel machine learning method called the Penalized Profile Support Vector Machine based on the Gabriel edited set for the computation of the probability of failure for a complex system as determined by a threshold condition…

Machine Learning · Statistics 2026-01-30 Jacob Zhu , Donald Estep

We investigate a system of Brownian particles weakly bound by attractive parity-symmetric potentials that grow at large distances as $V(x) \sim |x|^\alpha$, with $0 < \alpha < 1$. The probability density function $P(x,t)$ at long times…

Statistical Mechanics · Physics 2024-07-24 Lucianno Defaveri , Eli Barkai , David A. Kessler

We estimate the unknown parameters of an asymmetric bifurcating autoregressive process (BAR) when some of the data are missing. In this aim, we model the observed data by a two-type Galton-Watson process consistent with the binary tree…

Probability · Mathematics 2011-10-10 Benoîte de Saporta , Anne Gégout-Petit , Laurence Marsalle

Given a Galton-Watson process conditioned to have total progeny equal to $n$, we study the asymptotic probability that this conditioned Galton-Watson process has distance to the border bigger or equal than $k$, as the number of nodes $n…

Probability · Mathematics 2025-03-05 Víctor J. Maciá

Quasi-invariance under translation is established for the $ \sigma $-finite measure unifying Brownian penalisations, which has been introduced by Najnudel, Roynette and Yor. For this purpose, the theory of Wiener integrals for centered…

Probability · Mathematics 2009-11-10 Kouji Yano

We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (1977)'s work, but it is able to deal with models that have a precision matrix for the…

Methodology · Statistics 2018-06-13 María Xosé Rodríguez-Álvarez , Maria Durban , Dae-Jin Lee , Paul H. C. Eilers

This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it…

Optimization and Control · Mathematics 2019-01-28 Stephan Eckstein , Michael Kupper

We consider an outward degenerate drifted Brownian motion in the quarter plane with oblique reflections on the boundaries. In this article, we explicitly compute the Laplace transforms of the Green's functions associated with the process.…

Probability · Mathematics 2026-05-08 Maxence Petit

This paper describes techniques for growing classification and regression trees designed to induce visually interpretable trees. This is achieved by penalizing splits that extend the subset of features used in a particular branch of the…

Methodology · Statistics 2013-10-22 Alex Goldstein , Andreas Buja

We prove a law of large numbers and functional central limit theorem for a class of multivariate Hawkes processes with time-dependent reproduction rate. We address the difficulties induced by the use of non-convolutive Volterra processes by…

Probability · Mathematics 2025-01-30 Thomas Deschatre , Pierre Gruet , Antoine Lotz

Some classes of increment martingales, and the corresponding localized classes, are studied. An increment martingale is indexed by the real line and its increment processes are martingales. We focus primarily on the behavior as time goes to…

Probability · Mathematics 2015-03-17 Andreas Basse-O'Connor , Svend-Erik Graversen , Jan Pedersen

We investigate subcritical Galton-Watson branching processes with immigration in a random environment. Using Goldie's implicit renewal theory we show that under general Cram\'er condition the stationary distribution has a power law tail. We…

Probability · Mathematics 2020-02-04 Bojan Basrak , Peter Kevei

The aim of this paper is to introduce a new formalism for the deterministic analysis associated with backward stochastic differential equations driven by general c{\`a}dl{\`a}g martingales. When the martingale is a standard Brownian motion,…

Probability · Mathematics 2016-03-25 Ismail Laachir , Francesco Russo