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In this paper we consider an expectation-maximization method for maximizing the likelihood of (time nonhomogeneous) evolutionary Markov models on trees.
Expectation maximization (EM; Dempster et al., 1977) is the most popular method for maximizing the likelihood.
This paper presents a new method for maximizing manufacturing yield when the realizations of system components are dependent random variables with general distributions.
This study proposes an optimal design method for maximizing the sustainability of an integrated wastewater treatment plant with a combined heat and power generation system.
Toward an efficient and easy-implement optimization for photonic band gap structures, this paper extends the bi-directional evolutionary structural optimization (BESO) method for maximizing photonic band gaps.
To devise a method for maximizing the amount of oxygen available to cells, it is necessary to understand and to realistically predict oxygen transport within an engineered tissue.
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Here, we explore the characteristic of modularity density D, and derive a new spectral clustering based method for maximize D (Dλ) (SpeMD).
We also describe and compare two alternative methods for maximizing the likelihood function of the probability-mixing model, which are direct maximization of the marginal likelihood and the expectation maximization (EM) algorithm.
We develop reserve selection methods for maximizing either species retention in the landscape or species representation in reserve areas.
The findings of this research provide insight into how and to what degree these factors influence the dependent variables, ultimately providing online auction hosts and sellers with possible methods for maximizing their potential income from online auctions.
In this article we present a set of new methods for maximizing the expected overlap, which can handle realistic situations when strata and the associated sample sizes are large.
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