Branch Lengths Do Not Indicate Support—Even in Maximum Likelihood
نویسندگان
چکیده
منابع مشابه
Do tree split probabilities determine the branch lengths?
The evolution of aligned DNA sequence sites is generally modeled by a Markov process operating along the edges of a phylogenetic tree. It is well known that the probability distribution on the site patterns at the tips of the tree determines the tree topology, and its branch lengths. However, the number of patterns is typically much larger than the number of edges, suggesting considerable redun...
متن کاملBranch lengths and support.
Although technical definitions exist for various support metrics, the notion of support per se has received little explicit attention. Thus, despite its widespread use in phylogenetics, “support” is absent from the glossaries and/or indices of several recent texts (e.g., Kitching et al., 1998; Page and Holmes, 1998; Schuh, 2001). Farris et al. (2001) recently argued that interpreting branch len...
متن کاملMaximum Likelihood Estimation of Parameters in Generalized Functional Linear Model
Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...
متن کاملMaximum Likelihood
In this paper we discuss maximum likelihood estimation when some observations are missing in mixed graphical interaction models assuming a conditional Gaussian distribution as introduced by Lauritzen & Wermuth (1989). For the saturated case ML estimation with missing values via the EM algorithm has been proposed by Little & Schluchter (1985). We expand their results to the special restrictions ...
متن کاملMaximum likelihood
Assume that we have some data D and a model M of the process that generated the data. The model has some parameters θ, the specific value of which we do not know but wish to estimate. If the model is properly constructed, we will be able to calculate the probability of it generating the observed data given a specific set of parameter values, P (D|θ,M). Often, the conditioning on the model is su...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Cladistics
سال: 2001
ISSN: 0748-3007
DOI: 10.1006/clad.2001.0167