Maximum Likelihood Trees from DNA Sequences: A Peculiar Statistical Estimation Problem

1995 ◽  
Vol 44 (3) ◽  
pp. 384 ◽  
Author(s):  
Ziheng Yang ◽  
Nick Goldman ◽  
Adrian Friday
Keyword(s):  
Maximum Likelihood ◽  
Dna Sequences ◽  
Statistical Estimation ◽  
Estimation Problem ◽  
Statistical Estimation Problem

scholarly journals Discussion of Identification, Estimation and Approximation of Risk under Interventions that Depend on the Natural Value of Treatment Using Observational Data, by Jessica Young, Miguel Hernán, and James Robins

2014 ◽  
Vol 3 (1) ◽  
Author(s):  
Mark J. van der Laan ◽  
Alexander R. Luedtke ◽  
Iván Díaz
Keyword(s):  
Statistical Model ◽  
Observational Data ◽  
Robust Estimation ◽  
Statistical Estimation ◽  
Estimation Problem ◽  
Target Parameter ◽  
Adaptive Parameters ◽  
The Mean ◽  
Data Adaptive ◽  
Statistical Estimation Problem

AbstractYoung, Hernán, and Robins consider the mean outcome under a dynamic intervention that may rely on the natural value of treatment. They first identify this value with a statistical target parameter, and then show that this statistical target parameter can also be identified with a causal parameter which gives the mean outcome under a stochastic intervention. The authors then describe estimation strategies for these quantities. Here we augment the authors’ insightful discussion by sharing our experiences in situations where two causal questions lead to the same statistical estimand, or the newer problem that arises in the study of data adaptive parameters, where two statistical estimands can lead to the same estimation problem. Given a statistical estimation problem, we encourage others to always use a robust estimation framework where the data generating distribution truly belongs to the statistical model. We close with a discussion of a framework which has these properties.

Why Uninformed Agents (Pretend to) Know More

2013 ◽  
Vol 4 (3) ◽  
pp. 32-53
Author(s):  
Peter Schanbacher
Keyword(s):  
Social Interactions ◽  
Statistical Estimation ◽  
Estimation Problem ◽  
Rational Behavior ◽  
Statistical Estimation Problem

Many social interactions (examples are market overreactions, high rates of acquisitions, strikes, wars) are the result of agents' overconfidence. Agents are in particular overconfident for difficult tasks. This paper analyzes overconfidence in the context of a statistical estimation problem. The authors find that it is rational to (i) be overconfident and (ii) to be notably overconfident if the task is difficult. The counterintuitive finding that uninformed agents which should be the least confident ones show the highest degree of overconfidence can be explained as a rational behavior.

scholarly journals A Chromosome-Based Model for Estimating the Number of Conserved Segments Between Pairs of Species From Comparative Genetic Maps

Genetics ◽  
2000 ◽  
Vol 154 (1) ◽  
pp. 323-332
Author(s):  
David Waddington ◽  
Anthea J Springbett ◽  
David W Burt
Keyword(s):  
Maximum Likelihood ◽  
Dna Sequences ◽  
Common Ancestor ◽  
Length Distribution ◽  
Genetic Maps ◽  
Segment Length ◽  
Syntenic Block ◽  
Comparative Maps

Abstract Comparative genetic maps of two species allow insights into the rearrangements of their genomes since divergence from a common ancestor. When the map details the positions of genes (or any set of orthologous DNA sequences) on chromosomes, syntenic blocks of one or more genes may be identified and used, with appropriate models, to estimate the number of chromosomal segments with conserved content conserved between species. We propose a model for the distribution of the lengths of unobserved segments on each chromosome that allows for widely differing chromosome lengths. The model uses as data either the counts of genes in a syntenic block or the distance between extreme members of a block, or both. The parameters of the proposed segment length distribution, estimated by maximum likelihood, give predictions of the number of conserved segments per chromosome. The model is applied to data from two comparative maps for the chicken, one with human and one with mouse.

Systematic status of Campydora Cobb, 1920 (Nematoda: Campydorina)

Nematology ◽  
2003 ◽  
Vol 5 (5) ◽  
pp. 699-711 ◽  
Author(s):  
Peter Mullin ◽  
Timothy Harris ◽  
Thomas Powers
Keyword(s):  
Maximum Likelihood ◽  
Ribosomal Dna ◽  
Dna Sequences ◽  
Maximum Parsimony ◽  
Phylogenetic Analyses ◽  
Small Subunit ◽  
Systematic Position ◽  
Nominal Species ◽  
Competing Hypotheses ◽  
Small Subunit Ribosomal Dna

AbstractThe systematic position of Campydora Cobb, 1920, which possesses many unique morphological features, especially in pharyngeal structure and stomatal armature, has long been a matter of uncertainty with the 'position of the Campydorinae' (containing only Campydora) being questionable. A review of the morphology of C. demonstrans, the only nominal species of Campydora concluded that the species warranted placement as the sole member of a monotypic suborder, Campydorina, in the order Dorylaimida. Others placed Campydorina in the order Enoplida. We conducted phylogenetic analyses, using 18s small subunit ribosomal DNA sequences generated from a number of taxa in the subclasses Enoplia and Dorylaimia, to evaluate these competing hypotheses. Although precise taxonomic placement of the genus Campydora and the identity of its closest living relatives is in need of further investigation, our analyses, under maximum parsimony, distance, and maximum likelihood criteria, unambiguously indicate that Campydora shares a common, more recent, ancestry with genera such as Alaimus, Pontonema, Tripyla and Ironus (Enoplida), rather than with any members of Dorylaimida, Mononchida or Triplonchida.

Towards a monophyletic classification of Lejeuneaceae III: the systematic position of Leiolejeunea

Phytotaxa ◽  
2014 ◽  
Vol 170 (3) ◽  
pp. 187 ◽  
Author(s):  
ALFONS SCHÄFER-VERWIMP ◽  
KATHRIN FELDBERG ◽  
SHANSHAN DONG ◽  
HUUB VAN MELICK ◽  
DENILSON F. PERALTA ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Maximum Likelihood ◽  
Dna Sequences ◽  
Its Region ◽  
Systematic Position ◽  
Leaf Cell ◽  
Oil Bodies ◽  
Sister Relationship ◽  
First Time

The derived liverwort Leiolejeunea grandiflora was recollected at the type locality in Jamaica after more than 100 years. The characteristics of its oil bodies were described for the first time based on the new collections. Each leaf cell possesses 2-4(-6) rather small, subhomogeneous to very finely segmented, subglobose to ellipsoidal, colorless oil bodies. The plants were either dioicous or autoicous. DNA sequences of two chloroplast regions (trnL-trnF, rbcL) and the nuclear ribosomal ITS region were obtained for two accessions of Leiolejeunea to enable the inference of the phylogenetic relationships of these plants. Based on Bayesian inference of phylogeny as well as maximum parsimony and maximum likelihood analyses of a dataset including 87 representatives of Lejeuneaceae, Leiolejeunea was found as the putative sister to either Echinolejeuneinae or Cheilolejeuneinae. Thus, we propose the new monogeneric subtribe Leiolejeuneinae with relationships to Cheilolejeuneinae and Echinolejeuneinae. The analyses included also one accession of the generitype of Cheilolejeunea, C. decidua [= Cheilolejeunea adnata]. This species was found in a well supported sister relationship with Cystolejeunea. To avoid nomenclatural confusion, we propose a wide genus concept for Cheilolejeunea including Aureolejeunea, Cyrtolejeunea, Cystolejeunea, Evansiolejeunea, Leucolejeunea, and Omphalanthus.

A reassessment of apheloriine millipede phylogeny: additional taxa, Bayesian inference, and direct optimization (Polydesmida: Xystodesmidae)

Zootaxa ◽  
2007 ◽  
Vol 1610 (1) ◽  
pp. 27-39 ◽  
Author(s):  
PAUL E. MAREK ◽  
JASON E. BOND
Keyword(s):  
Maximum Likelihood ◽  
Dna Sequences ◽  
Bayes Factor ◽  
Appalachian Mountains ◽  
Deciduous Forests ◽  
Eastern United States ◽  
Undescribed Species ◽  
Direct Optimization ◽  
Species List ◽  
Phylogenetic Hypotheses

Millipedes in the tribe Apheloriini occur throughout the eastern United States, predominately in the deciduous forests of the Appalachian Mountains. Herein we present a reassessment of apheloriine millipede phylogeny using mitochondrial DNA sequences and an additional 29 exemplar taxa (including 15 undescribed species and all of the species in the genus Brachoria, except one). In this study, first we check the results of the previous phylogeny of the tribe (Marek and Bond, 2006) with different alignment and phylogenetic techniques (direct optimization and maximum likelihood), and second reconstruct a new phylogeny evaluating it in the same way with Bayesian, maximum likelihood, and direct optimization. Using this updated and expanded phylogeny, we tested historical classifications with Bayes factor and Shimodaira-Hasegawa hypothesis testing, consistently finding very strong evidence against their implied phylogenetic hypotheses. Lastly, using the new phylogeny as a foundation, we make taxonomic modifications and provide an updated species list of Apheloriini (106 species/17 genera).

scholarly journals Efficient Maximum-Likelihood Inference For The Isolation-With-Initial-Migration Model With Potentially Asymmetric Gene Flow

2016 ◽  
Author(s):  
Rui J. Costa ◽  
Hilde Wilkinson-Herbots
Keyword(s):  
Gene Flow ◽  
Maximum Likelihood ◽  
Dna Sequences ◽  
Computing Time ◽  
Likelihood Method ◽  
Ancestral Population ◽  
Parameter Estimates ◽  
Fast Method ◽  
Data Set ◽  
Im Model

AbstractThe isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, Becquet and Przeworski (2009) report that the parameter estimates obtained by fitting the IM model are very sensitive to the model's assumptions (including the assumption of constant gene flow until the present). This paper is concerned with the isolation-with-initial-migration (IIM) model of Wilkinson-Herbots (2012), which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used to distinguish between alternative models representing different evolutionary scenarios, by means of likelihood ratio tests. We illustrate the procedure on pairs of Drosophila sequences from approximately 30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this paper.

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