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Elisabeth GASSIAT (Université Paris-Sud) – "Estimation of the proportion of explained variation in high dimensions"
Time: 2:00 pm – 3:15 pm
Date: 27th of November 2017
Place: Room 3001.
Elisabeth GASSIAT (Université Paris-Sud) “Estimation of the proportion of explained variation in high dimensions“
Abstract
Estimation of heritability of a phenotypic trait based on genetic data may be set as estimation of the proportion of explained variation in high dimensional linear models. I will be interested in understanding the impact of:
— not knowing the sparsity of the regression parameter,
— not knowing the variance matrix of the covariates
on minimax estimation of heritability.
In the situation where the variance of the design is known, I will present an estimation procedure that adapts to unknown sparsity.
when the variance of the design is unknown and no prior estimator of it is available, I will show that consistent estimation of heritability is impossible.
(Joint work with N. Verzelen, and PHD thesis of A. Bonnet).
Organizers:
Cristina BUTUCEA, Alexandre TSYBAKOV, Eric MOULINES, Mathieu ROSENBAUM
Sponsors:
CREST-CMAP