5 citations · 9 across the 6 of their papers we have counts for
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Introducing Gaussian covariance graph models in genome-wide prediction
Carlos Alberto Martínez, Kshitij Khare, Syed Rahman +1
Several statistical models used in genome-wide prediction assume independence of marker allele substitution effects, but it is known that these effects might be correlated. In stat…
Modelling correlated marker effects in genome-wide prediction via Gaussian concentration graph models
Carlos Alberto Martínez, Kshitij Khare, Syed Rahman +1
In genome-wide prediction, independence of marker allele substitution effects is typically assumed; however, since early stages of this technology it has been known that nature poi…
A convex framework for high-dimensional sparse Cholesky based covariance estimation
Kshitij Khare, Sang Oh, Syed Rahman +1
Covariance estimation for high-dimensional datasets is a fundamental problem in modern day statistics with numerous applications. In these high dimensional datasets, the number of…