scholarly journals Mixed Bayesian implementation in general environments

2019 ◽  
Vol 82 ◽  
pp. 247-263
Author(s):  
Takashi Kunimoto
Keyword(s):  
Bayesian Implementation

Integrative taxonomy of giant crested Eusirus in the Southern Ocean, including the description of a new species (Crustacea: Amphipoda: Eusiridae)

2020 ◽  
Author(s):  
Marie L Verheye ◽  
Cédric D’Udekem D’Acoz
Keyword(s):  
New Species ◽  
Species Diversity ◽  
Morphological Analysis ◽  
Integrative Taxonomy ◽  
Putative Species ◽  
Species Complexes ◽  
Statistical Parsimony ◽  
Bayesian Implementation ◽  
A New Species ◽  
Giant Species

Abstract Among Antarctic amphipods of the genus Eusirus, a highly distinctive clade of giant species is characterized by a dorsal, blade-shaped tooth on pereionites 5–7 and pleonites 1–3. This lineage, herein named ‘crested Eusirus’, includes two potential species complexes, the Eusirus perdentatus and Eusirus giganteus complexes, in addition to the more distinctive Eusirus propeperdentatus. Molecular phylogenies and statistical parsimony networks (COI, CytB and ITS2) of crested Eusirus are herein reconstructed. This study aims to formally revise species diversity within crested Eusirus by applying several species delimitation methods (Bayesian implementation of the Poisson tree processes model, general mixed Yule coalescent, multi-rate Poisson tree processes and automatic barcode gap discovery) on the resulting phylogenies. In addition, results from the DNA-based methods are benchmarked against a detailed morphological analysis of all available specimens of the E. perdentatus complex. Our results indicate that species diversity of crested Eusirus is underestimated. Overall, DNA-based methods suggest that the E. perdentatus complex is composed of three putative species and that the E. giganteus complex includes four or five putative species. The morphological analysis of available specimens from the E. perdentatus complex corroborates molecular results by identifying two differentiable species, the genuine E. perdentatus and a new species, herein described as Eusirus pontomedon sp. nov.

2-person Bayesian implementation

1994 ◽  
Vol 1 (1) ◽  
pp. 41-54 ◽  
Author(s):  
Bhaskar Dutta ◽  
Arunava Sen
Keyword(s):  
Bayesian Implementation

Full Implementation under Ambiguity

2021 ◽  
Vol 13 (1) ◽  
pp. 148-178
Author(s):  
Huiyi Guo ◽  
Nicholas C. Yannelis
Keyword(s):  
Social Choice ◽  
Expected Utility ◽  
Sufficient Conditions ◽  
Choice Functions ◽  
Maxmin Expected Utility ◽  
Special Cases ◽  
Social Choice Functions ◽  
Bayesian Implementation ◽  
Pareto Efficient ◽  
Choice Set

This paper introduces the maxmin expected utility framework into the problem of fully implementing a social choice set as ambiguous equilibria. Our model incorporates the Bayesian framework and the Wald-type maxmin preferences as special cases and provides insights beyond the Bayesian implementation literature. We establish necessary and almost sufficient conditions for a social choice set to be fully implementable. Under the Wald-type maxmin preferences, we provide easy-to-check sufficient conditions for implementation. As applications, we implement the set of ambiguous Pareto-efficient and individually rational social choice functions, the maxmin core, the maxmin weak core, and the maxmin value. (JEL D71, D81, D82)

Bayesian Implementation

2013 ◽  
Author(s):  
T. Palfrey ◽  
S. Srivastave
Keyword(s):  
Bayesian Implementation

scholarly journals Uncertain-tree: discriminating among competing approaches to the phylogenetic analysis of phenotype data

2017 ◽  
Vol 284 (1846) ◽  
pp. 20162290 ◽  
Author(s):  
Mark N. Puttick ◽  
Joseph E. O'Reilly ◽  
Alastair R. Tanner ◽  
James F. Fleming ◽  
James Clark ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Accurate Method ◽  
Morphological Data ◽  
Or Groups ◽  
Phenotype Data ◽  
Bayesian Implementation ◽  
Phylogenetic Estimation ◽  
The Impact

Morphological data provide the only means of classifying the majority of life's history, but the choice between competing phylogenetic methods for the analysis of morphology is unclear. Traditionally, parsimony methods have been favoured but recent studies have shown that these approaches are less accurate than the Bayesian implementation of the Mk model. Here we expand on these findings in several ways: we assess the impact of tree shape and maximum-likelihood estimation using the Mk model, as well as analysing data composed of both binary and multistate characters. We find that all methods struggle to correctly resolve deep clades within asymmetric trees, and when analysing small character matrices. The Bayesian Mk model is the most accurate method for estimating topology, but with lower resolution than other methods. Equal weights parsimony is more accurate than implied weights parsimony, and maximum-likelihood estimation using the Mk model is the least accurate method. We conclude that the Bayesian implementation of the Mk model should be the default method for phylogenetic estimation from phenotype datasets, and we explore the implications of our simulations in reanalysing several empirical morphological character matrices. A consequence of our finding is that high levels of resolution or the ability to classify species or groups with much confidence should not be expected when using small datasets. It is now necessary to depart from the traditional parsimony paradigms of constructing character matrices, towards datasets constructed explicitly for Bayesian methods.

scholarly journals On the Recovery of Galaxy Properties from Spectral Fits

2012 ◽  
Vol 8 (S295) ◽  
pp. 317-317
Author(s):  
G. Magris ◽  
C. Mateu ◽  
G. Bruzual A. ◽  
I. Cabrera
Keyword(s):  
Statistical Treatment ◽  
Physical Parameters ◽  
Assembly Process ◽  
Spectral Fitting ◽  
Fitting Algorithm ◽  
The Galaxy ◽  
Bayesian Implementation ◽  
Galaxy Assembly ◽  
Fully Bayesian ◽  
Non Parametric

AbstractWe show the results of a non-parametric, fully bayesian implementation of a spectral fitting algorithm, designed to calculate the main physical parameters that govern the galaxy assembly process. In this work, we present results from a statistical treatment of SED fitting that allows for easy recovery and visualization of the galaxy physical parameters.

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