Likelihood inferences using PhyML for 16S with 28S
Empirical Likelihood Inferences in Survival Analysis
... with using standard numerical methods, for example, Brown and Wang (2007), Heller (2007), Johnson and Strawderman (2009), Wang and Fu (2011) and Chiou et ...
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PHYML Online: A Web Server for Fast Maximum Likelihood-Based Phylogenetic Inference
... Abstract PHYML Online is a web interface to PHYML, a software that implements a fast and accurate heuristic for estimating maximum likelihood phylogenies from DNA and protein ...
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New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0
... Summary.—Simulated data do not allow for a relevant ranking of compared methods and options, and more informative results are obtained with our large-scale real-world benchmarks comprising 60 DNA and 60 protein ...
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Jackknife Empirical Likelihood Inferences for the Skewness and Kurtosis
... ABSTRACT Skewness and kurtosis are measures used to describe shape characteristics of distribu- tions. In this thesis, we examine the interval estimates about the skewness and kurtosis by using jackknife empirical ...
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Empirical likelihood inferences for the semiparametric additive isotonic regression
... where X ∈ R p , W j ∈ R 1 , β ∈ R p is a non-random parameter and each function h j is assumed to be monotone, for j = 1 , . . . , J. For simplicity, we assume that the error term ϵ has mean zero and is independent of ...
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Multiple Choice Tests: Inferences Based on Estimators of Maximum Likelihood
... The behaviour of Delta can be observed by means of simulations. Figure 1 shows the point estimation of the parameter ∆ across the entire range of knowledge in the case of MCT with three alternatives where each indi- ...
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Efficient empirical-likelihood-based inferences for the single-index model
... by using the empirical likelihood ...empirical likelihood method to select the significant variables of the API is also of ...empirical likelihood method to construct the confidence interval ...
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PhyML Manual. Version 3.0 September 17,
... approximate likelihood ratios rather than SPR and non-parametric bootstrap are generally the most appropriate ...done using popular software such as Modeltest [24] or ProtTest [25] for ...in PhyML, ...
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A new transformed Weibull lifetime distribution and its inferences based on the Bayes and maximum likelihood procedures
... In the case of distribution, the estimation of parameters can be obtained by numerical methods. Bayesian inference and Confidence Interval for credibility: In Bayesian theory, given the fact that, we do not know the ...
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Data Fusion Using Weighted Likelihood
... classical likelihood method would concentrate solely on the sample from the the target population without incorporating other relevant ...maximum likelihood estimator (MLE) is well known to enjoy asymptotic ...
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Spatial Clustering Using the Likelihood Function
... 4.2.5 Spatial Weighting Since one of the goals of precision agriculture is to define areas with potential for differentiated treatments, targeted (guided) samples are taken to provide detailed information about the ...
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Discrete Power Distributions and Inference Using Likelihood
... S UMMARY Discrete power distributions are proposed and studied, by considering the positive jumps on the discontinuities of an original discrete distribution function. Inequalities in moments and distri- bution functions ...
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Inference of Population History Using a Likelihood Approach
... the likelihood of different population histories that utilizes an explicit model of sequence evolution for the DNA segment under ...a likelihood approach to conducting statistical inference within a class ...
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28S and 18S rdna Sequences Support the Monophyly of Lampreys and Hagfishes
... complete 28S rDNA sequences were obtained from the lancelet Branchiostoma floridae, the hagfish Eptatretus stouti, the lamprey Petromyzon marinus, and cartilaginous fishes Hydrolagus colliei and Squalus acanthias ...
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Causal inferences with large scale assessment data: using a validity framework
... causal inferences and ...causal inferences are rarely ...causal inferences and then suggest and apply a validity framework to evaluate the tenability of claims made in two well-cited ...
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Model-Free IRL Using Maximum Likelihood Estimation
... trajectories using our model-free IRL approach as well as the existing baselines MLIRL and REIRL, based on 10 independent trials for each ...states using standard dy- namical ...
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Calibration of stochastic computer simulators using likelihood emulation
... the likelihood function given the observed ...the likelihood reduces the computa- tional effort to emulating a univariate output, and enables us to implement an importance sampling approach for the ...the ...
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Bayesian inferences of the thermal properties of a wall using temperature and heat flux measurements
... The assessment of the thermal properties of walls is essential for accurate building energy simulations that are needed to make effective energy-saving policies. These properties are usually investigated through in-situ ...
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Chapter 23. Inferences for Regression
... The Problem: Infants who cry easily may be more easily stimulated than others. This may be a sign of higher IQ. Child development researchers explored the relationship between the crying of infants four to ten days old ...
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Generalized quasi-likelihood versus hierarchical likelihood inferences in generalized linear mixed models for count data
... As it is proven to be difficult to obtain consistent and efficient estimates of the parameters (regression effects and variance of the random effects) of such models, [r] ...
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