[PDF] Top 20 Approximate Profile Maximum Likelihood
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Approximate Profile Maximum Likelihood
... for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than ... See full document
55
Maximum likelihood representation of MIPAS profiles
... The approximate allowed mini- mum gridwidth is determined with the method presented by von Clarmann and Grabowski (2007), who allow one ver- tical grid point for the ML retrieval per altitude range over which the ... See full document
9
Rates of Nucleotide Substitution and Mammalian Nuclear Gene Evolution: Approximate and Maximum-Likelihood Methods Lead to Different Conclusions
... employed approximate methods to estimate rates of nonsynonymous and synonymous ...both approximate and maximum-likelihood methods. Maximum-likelihood analysis indicated that ... See full document
10
Fast and Accurate Direction-of-Arrival Estimation for a Single Source
... the maximum likelihood (ML) approach, the deterministic ML algorithm [4] and modified ML estimator based on the principal eigenvector method [5] are ...explicit approximate ML algorithm with lower ... See full document
8
Fast Bayesian methods for genetic mapping applicable for high-throughput datasets
... direct approximate QTL posterior probabilities at all putative gene locations, but also offer highly interpretable posterior densities for linkage, without the need for Bayes factors in model ...the profile ... See full document
128
Fine Timing synchronization for OFDM Receiver
... discuss approximate maximum-likelihood (ML) carrier frequency offset CFO)estimation scheme based on time-domain channel estimates which retain the CFO information in the form of phase ...used ... See full document
6
Estimation in Interacting Diffusions: Continuous and Discrete Sampling
... an approximate maximum likelihood esti- mator of the drift coefficient of an interacting particles of diffusions are ...the approximate maximum likelihood estimator, dis- crete ... See full document
5
A simple approach to maximum intractable likelihood estimation
... the likelihood function, even up to a normalising constant, is impossible or computationally ...Composite Likelihood methods (Cox and Reid, 2004), for approximating the likelihood function, and ... See full document
24
Spectral methods to approximate the likelihood for irregularly spaced spatial data
... parameters of the point-covariance of Z. Figure 12 shows the true semivariogram for Z and the empirical semivariogram with a confidence envelope, obtained simulating 1000 versions of the process Z, the upper and lower ... See full document
38
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 ... See full document
24
Distributions of Maximum Likelihood Estimators and Model Comparisons
... Analysts should consider using exact densities for maxi- mum likelihood estimates whenever it is practical to do so. The densities are particularly appropriate where al- ternative models are to be compared and ... See full document
7
Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
... an approximate sparse maximum likelihood problem for multivariate binary data, using a log determinant relaxation for the log partition function given by Wainwright and Jordan ... See full document
32
Which quantile is the most informative? Maximum likelihood, maximum entropy and quantile regression
... The implementation of the estimator is simple. As discussed in the previous section, an iteration algorithm can be used to solve for the estimates in the estimating equations above. Computationally, the estimates can be ... See full document
41
On the Maximum Likelihood and Least Squares Estimation for the Inverse Weibull Parameters with Progressively First Failure Censoring
... the maximum likelihood, approximate maximum likelihood and the least squares method estimators for the unknown pa- rameters of the inverse Weibull distribution are ...the maximum ... See full document
16
Approximate maximum likelihood estimation for population genetic inference
... intractable likelihood function. Therefore, approximate estimation methods have been developed, and with grow- ing computational power, sampling-based methods became ...as Approximate Bayesian ... See full document
22
Particle filter-based approximate maximum likelihood inference asymptotics in state-space models
... implement maximum likelihood estimation in state-space models, the log-likelihood function must be ...corresponding approximate maximum likelihood ... See full document
6
Semidefinite Programming for Approximate Maximum Likelihood Sinusoidal Parameter Estimation
... nonconvex maximum likelihood (ML) optimization problems regarding the periodogram, linear prediction polynomial (LPP), and nonlinear least squares (NLS) methods, to convex ... See full document
19
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... The major application for the asymptotic normality of both the full and approximate MLEs is for statistical inference of θ, which include confidence regions and testing hypotheses for θ. For such purposes, the ... See full document
39
Maximum Likelihood Estimation of Feature Based Distributions
... The flexibility of the framework and the generality of the normalized co-emission product allow researchers to consider feature-based distributions which allow any two features to intera[r] ... See full document
10
On The Comparison Of Methods Of Estimating Variance Components: A Case Of Gudali Beef Cattle
... Modified likelihood method (ML), Restricted maximum-likelihood method (REML), and Modified maximum likelihood method (MML), recommended “modified maximum likelihood method ... See full document
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