An expectation–maximization algorithm for the Lasso estimation of quantitative trait locus effects
The least absolute shrinkage and selection operator (Lasso) estimation of regression coefficients can be expressed as Bayesian posterior mode estimation of the regression coefficients under various ...
We present a novel methodology for estimating the parameters of a finite mixture model (FMM) based on partially rank-ordered set (PROS) sampling and use it in a fishery application. A PROS sampling ...
Changepoint models are widely used to model the heterogeneity of sequential data. We present a novel sequential Monte Carlo (SMC) online expectation-maximization (EM) algorithm for estimating the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results