10 citations · 14 across the 6 of their papers we have counts for
6 papers
Rates of Convergence of Maximum Smoothed Log-Likelihood Estimators for Semi-Parametric Multivariate Mixtures
Marie Du Roy de Chaumaray, Michael Levine, Matthieu Marbac
Theoretical guarantees are established for a standard estimator in a semi-parametric finite mixture model, where each component density is modeled as a product of univariate densit…
Estimation of the Order of Non-Parametric Hidden Markov Models using the Singular Values of an Integral Operator
Marie Du Roy de Chaumaray, Salima El Kolei, Marie-Pierre Etienne +1
We are interested in assessing the order of a finite-state Hidden Markov Model (HMM) with the only two assumptions that the transition matrix of the latent Markov chain has full ra…
Clustering Data with Nonignorable Missingness using Semi-Parametric Mixture Models
Marie Du Roy de Chaumaray, Matthieu Marbac
We are concerned in clustering continuous data sets subject to non-ignorable missingness. We perform clustering with a specific semi-parametric mixture, under the assumption of con…
Mixture of hidden Markov models for accelerometer data
Marie du Roy de Chaumaray, Matthieu Marbac, Fabien Navarro
Motivated by the analysis of accelerometer data, we introduce a specific finite mixture of hidden Markov models with particular characteristics that adapt well to the specific natu…
Sharp large deviations for the drift parameter of the explosive Cox-Ingersoll-Ross process
marie du Roy de Chaumaray
We consider a non-stationary Cox-Ingersoll-Ross process. We establish a sharp large deviation principle for the maximum likelihood estimator of its drift parameter.
Weighted least squares estimation for the subcritical Heston process
Marie du Roy de Chaumaray
We simultaneously estimate the four parameters of a subcritical Heston process. We do not restrict ourself to the case where the stochastic volatility process never reaches zero. I…