Efficient estimation of the accuracy of the maximum likelihood method for ancestral state reconstruction

2009 ◽  
Vol 21 (4) ◽  
pp. 409-422 ◽  
Author(s):  
Bin Ma ◽  
Louxin Zhang
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Ancestral State Reconstruction ◽  
Efficient Estimation ◽  
Likelihood Method ◽  
Ancestral State ◽  
State Reconstruction

scholarly journals A comparison of ancestral state reconstruction methods for quantitative characters

2016 ◽  
Author(s):  
Manuela Royer-Carenzi ◽  
Gilles Didier
Keyword(s):  
Maximum Likelihood ◽  
Generalized Least Squares ◽  
Ancestral State Reconstruction ◽  
Likelihood Method ◽  
Reconstruction Method ◽  
Ancestral State ◽  
State Reconstruction ◽  
Evaluation Scheme ◽  
Reconstruction Methods ◽  
Ancestral States

Choosing an ancestral state reconstruction method among the alternatives available for quantita- tive characters may be puzzling. We present here a comparison of five of them, namely the maximum likelihood, restricted maximum likelihood, generalized least squares, phylogenetic independent con- trasts and squared parsimony methods. A review of the relations between these methods shows that the first three ones infer the same ancestral states and can only be distinguished by the distributions accounting for the reconstruction uncertainty which they provide. The respective accuracy of the methods is assessed over character evolution simulated under a Brownian motion with (and without) drift. We start by giving the general form of ancestral state distributions conditioned on leaf states under the simulation model. Ancestral distributions are used first, to give a theoretical lower bound of the expected recon- struction error, and second, to develop an original evaluation scheme which is more efficient than comparing the reconstructed and the simulated states. Our simulations show that: (i) the methods do not perform well as the evolution drift increases; (ii) the maximum likelihood method is generally the most accurate and (iii) not all the distributions of the reconstruction uncertainty provided by the methods are equally relevant.

scholarly journals Using ancestral state reconstruction methods for onomasiological reconstruction in multilingual word lists

2018 ◽  
Vol 8 (1) ◽  
pp. 22-54 ◽  
Author(s):  
Gerhard Jäger ◽  
Johann-Mattis List
Keyword(s):  
Maximum Likelihood ◽  
Ancestral State Reconstruction ◽  
Ancestral State ◽  
State Reconstruction ◽  
Reconstruction Methods ◽  
Lexical Change ◽  
Word Lists ◽  
Automatic Methods ◽  
Test Sets ◽  
Inference Methods

AbstractCurrent efforts in computational historical linguistics are predominantly concerned with phylogenetic inference. Methods for ancestral state reconstruction have only been applied sporadically. In contrast to phylogenetic algorithms, automatic reconstruction methods presuppose phylogenetic information in order to explain what has evolved when and where. Here we report a pilot study exploring how well automatic methods for ancestral state reconstruction perform in the task of onomasiological reconstruction in multilingual word lists, where algorithms are used to infer how the words evolved along a given phylogeny, and reconstruct which cognate classes were used to express a given meaning in the ancestral languages. Comparing three different methods, Maximum Parsimony, Minimal Lateral Networks, and Maximum Likelihood on three different test sets (Indo-European, Austronesian, Chinese) using binary and multi-state coding of the data as well as single and sampled phylogenies, we find that Maximum Likelihood largely outperforms the other methods. At the same time, however, the general performance was disappointingly low, ranging between 0.66 (Chinese) and 0.79 (Austronesian) for the F-Scores. A closer linguistic evaluation of the reconstructions proposed by the best method and the reconstructions given in the gold standards revealed that the majority of the cases where the algorithms failed can be attributed to problems of independent semantic shift (homoplasy), to morphological processes in lexical change, and to wrong reconstructions in the independently created test sets that we employed.

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