Maximum-likelihood (ML)
Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... and Maximum Likelihood (ML) ...the ML is too sensitive to ex- treme values, especially for small samples although but it may be satisfactory for large samples, and the final esti- mate is not ...
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On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... full maximum likelihood estimation (MLE) based on discretely observed sample ...approximate maximum likelihood estimation (AMLE) for ...
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Distributions of Maximum Likelihood Estimators and Model Comparisons
... using maximum likelihood estimation under a specified ...of maximum likelihood estimates in terms of their probabil- ity density functions (estimator ...
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A time-domain control signal detection technique for OFDM
... a maximum likelihood (ML) criterion is often used as the standard detec- tion approach ...the ML estimation scheme normally requires some form of channel mit- igation through the use of, for ...
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5sociolinguistics pdf
... resulting likelihood values λ . The aim of maximum likelihood estimation is to find the value of π that has the highest ...this likelihood function, the point that is chosen as the best ...
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Characterization of the complete mitochondrial genomes of Nematodirus oiratianus and Nematodirus spathiger of small ruminants
... Amino acid sequences inferred from the 12 protein- coding genes were concatenated into a single alignment, and then aligned with those of eight other Trichostron- gyloid nematodes (Cooperia oncophora, NC_004806 [33]; ...
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Estimators of Linear Regression Model and Prediction under Some Assumptions Violation
... estimator, Maximum Likelihood (ML) estimator and the estimators based on Principal Component (PC) analysis in prediction of linear regression model under the joint violations of the assumption of ...
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Efficient maximum likelihood pedigree reconstruction
... the likelihood of the profile according to the true pedigree, and the maximum likelihood were ...the maximum likelihood pedigree for each pedigree ...
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The Dual of the Maximum Likelihood
... The Maximum Likelihood method estimates the parameter values of a statistical model that maximizes the corresponding likelihood function, given the sample ...the Maximum Likelih- ood method ...
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Reconstruction of Pet Image Based On Kernelized Expectation Maximization Method
... Abstract - Positron emission tomography (PET) image reconstruction is challenging for low count frame. The reconstruction is important method to retrieve information that has been lost in the images. To improve image ...
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Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo
... We present a sequential Monte Carlo (SMC) method for maximum likelihood (ML) parameter estimation in latent variable models. Stan- dard methods rely on gradient algorithms such as the Expectation- ...
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Target sequence capture in the Brazil nut family (Lecythidaceae): marker selection and in silico capture from genome skimming data
... best-scoring maximum likelihood (ML) tree and performed 1000 rapid bootstraps employing the option “-f a” in RAxML ...scoring ML tree from the concatenated sequence matrix (hereafter called ...
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Maximum Likelihood Under Response Biased Sampling
... estimating equations that arise. We show that under array sampling both sample-based and MIP approaches lead to the same MLE for the parameter θ of interest. By way of comparison, in Section 3 we develop the weighted ...
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Redescription, molecular characterisation and taxonomic re evaluation of a unique African monitor lizard haemogregarine Karyolysus paradoxa (Dias, 1954) n comb (Karyolysidae)
... To infer phylogenetic relationships of the aligned dataset both Bayesian inference (BI) and Maximum likelihood (ML) methods were used. A comprehensive model test was preformed to determine the most ...
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Smoothing Algorithms by Constrained Maximum Likelihood
... constrained maximum likelihood for rating level probability of default and for rating migration ...constrained maximum likelihood, with a fair risk scale determined by constrained ...
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Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression
... distribution, maximum likelihood and maximum ...the maximum likeli- hood problem is equivalent to the solution of a maximum entropy problem where we impose moment constraints given by ...
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Measuring Financial Risk using Extreme Value Theory: evidence from Pakistan
... the parameter estimates, and from that extract the parameter standard er- rors. Which is 0 . 666 and 0 . 0012 for ξ, σ respectively. Interpretation of the standard errors usually involves assuming that, if the same fit ...
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Composite Likelihood for Bilinear GARCH Model
... composite maximum likelihood methods, that are widely used in parametric statistical inference, because of the good asymptotic properties of the ...composite likelihood is to reduce and simplify the ...
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On the extrema of integrable functions
... Abstract. This paper contains the definition of the extremum of integrable functions (e.g., the mode of density function). It seems to be a generalization of well-known stan- dard definition and can be applied in ...
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Maximum likelihood estimates of pairwise rearrangement distances
... This paper introduces a maximum likelihood estimator for the evolutionary distance between two genomes under a large-scale genome rearrangement model. One may view this as a correction method for a family ...
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