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We discuss approximations of the relative limit densities of descendants in Galton--Watson processes that follow from the Karlin--McGregor near-constancy phenomena. These approximations are based on the fast exponentially decaying Fourier…

Probability · Mathematics 2023-03-22 Anton A Kutsenko

Markov chain Monte Carlo methods provide an essential tool in statistics for sampling from complex probability distributions. While the standard approach to MCMC involves constructing discrete-time reversible Markov chains whose transition…

Computation · Statistics 2020-09-29 Joris Bierkens , Andrew Duncan

We present an efficient finite difference method for the computation of parameter sensitivities that is applicable to a wide class of continuous time Markov chain models. The estimator for the method is constructed by coupling the perturbed…

Numerical Analysis · Mathematics 2012-05-14 David F. Anderson

In this paper, we investigate a stochastic approximation procedure $\left(X_n\right)_{n\ge 0}$ taking values in $R$. The process is adapted to a filtration $(F_n)_{n\ge 0}$ and satisfies the recursion…

Probability · Mathematics 2026-05-11 Jianan Shi , Qing Yin , Yu Miao

We provide sufficient conditions which ensure that the intrinsic martingale in the supercritical branching random walk converges exponentially fast to its limit. The case of Galton-Watson processes is particularly included so that our…

Probability · Mathematics 2011-12-12 A. Iksanov , M. Meiners

The goal of this paper is to show that a single robust estimator of the mean of a multivariate Gaussian distribution can enjoy five desirable properties. First, it is computationally tractable in the sense that it can be computed in a time…

Statistics Theory · Mathematics 2022-10-28 Arnak S. Dalalyan , Arshak Minasyan

Given a super-critical Galton-Watson process $\{Z_n\}$ and a positive sequence $\{\epsilon_n\}$, we study the limiting behaviors of $P(S_{Z_n}/Z_n\geq\epsilon_n)$ and $P(S_{Z_n}/m^n\geq\epsilon_n) $ with sums $S_{n}$ of i.i.d. random…

Probability · Mathematics 2015-08-31 Hui He

We present a new pruning procedure on discrete trees by adding marks on the nodes of trees. This procedure allows us to construct and study a tree-valued Markov process $\{{\cal G}(u)\}$ by pruning Galton-Watson trees and an analogous…

Probability · Mathematics 2012-06-28 Romain Abraham , Jean-Francois Delmas , Hui He

In estimation of a normal mean matrix under the matrix quadratic loss, we develop a general formula for the matrix quadratic risk of orthogonally invariant estimators. The derivation is based on several formulas for matrix derivatives of…

Statistics Theory · Mathematics 2023-08-07 Takeru Matsuda

The classical Galton--Watson process works with a fixed probability of fission at each time step. One of the generalizations is that the probabilities depend on time. We consider one of the most complex and interesting cases when we do not…

Probability · Mathematics 2024-01-23 Anton A. Kutsenko

We apply Lindeberg's method, invented to prove a central limit theorem, to analyze the moderate deviations around such a central limit theorem. In particular, we will show moderate deviation principles for martingales as well as for random…

Probability · Mathematics 2018-10-03 Peter Eichelsbacher , Matthias Löwe

In this paper, we study the Galton-Watson process in the random environment for the particular case when the number of the offsprings in each generation has the fractional linear generation function with random parameters. In this case, the…

Probability · Mathematics 2020-12-01 Dan Han , Stanislav Molchanov , Yanjmaa Jutmaan

We introduce a new interpretation of sparse variational approximations for Gaussian processes using inducing points, which can lead to more scalable algorithms than previous methods. It is based on decomposing a Gaussian process as a sum of…

Machine Learning · Statistics 2024-02-27 Jiaxin Shi , Michalis K. Titsias , Andriy Mnih

We investigate Kesten-Stigum-like results for multi-type Galton-Watson processes with a countable number of types in a general setting, allowing us in particular to consider processes with an infinite total population at each generation.…

Probability · Mathematics 2025-03-10 Mathilde André , Jean-Jil Duchamps

In this paper, we establish the exact Fourier dimensions of all standard sub-critical Gaussian multiplicative chaos on the unit interval, thereby confirming the Garban-Vargas conjecture. The proof relies on a significant improvement of the…

Probability · Mathematics 2025-05-07 Zhaofeng Lin , Yanqi Qiu , Mingjie Tan

We consider the problem of approximating the product of $n$ expectations with respect to a common probability distribution $\mu$. Such products routinely arise in statistics as values of the likelihood in latent variable models. Motivated…

Computation · Statistics 2017-09-05 Anthony Lee , Simone Tiberi , Giacomo Zanella

We prove exponential moments for linear combinations of the number of individuals of each type of a whole multitype Poissonian Galton Watson process. We give sharp estimates for such quantities, which depend on the expectation of the…

Probability · Mathematics 2025-07-14 Théo Leblanc

In the common nonparametric regression model the problem of testing for a specific parametric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process…

Statistics Theory · Mathematics 2008-09-30 H. Dette , B. Hetzler

As well known, for a supercritical Galton-Watson process $Z_n$ whose offspring distribution has mean $m>1$, the ratio $W_n:=Z_n/m^n$ has a.s. limit, say $W$. We study tail behaviour of the distributions of $W_n$ and $W$ in the case where…

Probability · Mathematics 2013-03-12 Denis Denisov , Dmitry Korshunov , Vitali Wachtel

This paper studies quantitative deviation bounds for statistical ensembles evolving under the one-parameter flow of a nearly integrable Hamiltonian system. Combining Nekhoroshev-type stability estimates with phase-mixing arguments, we…

Dynamical Systems · Mathematics 2026-02-23 Xinyu Liu , Yong Li