Ben Deitmar

activity

20222026

collaborators

5 papers

math.ST2026

Spectral approximation for the separable covariance mixture model

Ben Deitmar

This paper introduces the separable covariance mixture model, which assumes a data-matrix $Y$ to be of the form $r = 1 \sum R A_{r} X B_{r}$ for one random $(d \times n)$ -ma…

math.ST2025

Estimation of Population Linear Spectral Statistics by Marchenko--Pastur Inversion

Ben Deitmar

A new method of estimating population linear spectral statistics from high-dimensional data is introduced. When the dimension $d$ grows with the sample size $n$ such that $\frac{d}…

math.ST2024

Marchenko-Pastur laws for Daniell smoothed periodograms

Ben Deitmar

Given a sample $X_{0}, ..., X_{n - 1}$ from a $d$ -dimensional stationary time series $(X_{t})_{t \in Z}$ , the most commonly used estimator for the spectral density matrix $F (θ)$ a…

math.PR2023

A recursion formula for mixed trace moments of isotropic Wishart matrices and the Gaussian unitary/orthogonal ensembles

Ben Deitmar

Exact recursion formulas for mixed moments of four fundamental random matrix ensembles are derived. The reason such recursive formulas are possible is closely related to properties…

math.ST2022

Trace Moments of the Sample Covariance Matrix with Graph-Coloring

Ben Deitmar

Let $S_{p, n}$ denote the sample covariance matrix based on $n$ independent identically distributed $p$ -dimensional random vectors in the null-case. The main result of this paper is…