Sep 9, 2016 · Our study makes explicit the deep links between model singularities, parameter estimation convergence rates and minimax lower bounds, and the ...

Singularities of a statistical model are the elements of the model's parameter space which make the corresponding Fisher information matrix degenerate.

This study makes explicit the deep links between model singularities, parameter estimation convergence rates and minimax lower bounds, and the algebraic ...

Sep 9, 2016 · Our study makes explicit the deep links between model singularities, parameter estimation convergence rates and minimax lower bounds, and the ...

Singularities of skewnormal mixtures lie in affine varieties. If we know that the parameters are bounded away from these algebraic sets,.

Jul 23, 2019 · Singularity structures and impacts on parameter estimation in finite mix- tures of distributions. Technical Report 540, Department of ...

Our study makes explicit the deep links between model singularities, parameter estimation convergence rates and minimax lower bounds, and the algebraic geometry ...

Our study makes explicit the deep links between model singularities, parameter estimation convergence rates and minimax lower bounds, and the algebraic geometry ...

[12] Singularity structures and impacts on parameter estimation in finite mixtures of distributions. Shannon Centennial Symposium, September, 2016, Ann ...

On the other hand, Ho and Nguyen [14,15] studied the singularity structure of finite mixture's parameter space and its impact on rates of parameter estimation ...