maximum-likelihood-estimate approach
The Equivalence of the Maximum Likelihood and a Modified Least Squares for a Case of Generalized Linear Model
... this maximum likelihood approach is applied when the data are approximately ...second approach that we will consider is applied for normal or not normal data, but it is often applied for the ...
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Graph matching with a dual-step EM algorithm
... new approach to matching geometric structure in 2D ...expected likelihood function used to estimate maximum likelihood transformation ...
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Maximum likelihood approach to DoA estimation using lens antenna array
... for focusing the energy. It is illustrated that the power dis- tribution of receive signals is a sinc function of the incident signal direction. As a result, we for the first time, propose the use of LNA for estimating ...
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A Maximum Likelihood Approach to Least Absolute Deviation Regression
... To overcome these limitations, the iterative algorithm must be modified exploiting the fact that the optimal solution is at an intersection of edge lines. Thus, if the search is di- rected along the edge lines, then a ...
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Maximum likelihood estimation for stochastic processes - a martingale approach
... the likelihood function is a ...the likelihood and the maximum likelihood estimate (MLE), we can often use these limit theorems to prove asymptotic properties of the ...
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A ridge restricted maximum likelihood approach to spatial models
... validation estimate for ...the approach analogous to Type II maximum likelihood as an alter- native approach to estimating ...This approach is a natural alternative, since the ...
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Multiple 3D Target Tracking in Binary Wireless Sensor Network
... to estimate the targets locations using maximum likelihood ...This approach generalizes the existing work in the literature about a single target localization if we considered that the number ...
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Using Maximum Likelihood to Estimate Population Size From Temporal Changes in Allele Frequencies
... using likelihood to estimate N is Bayesian approach and then estimate a posterior distri- that it is more computationally intensive than using F-sta- bution for ...to estimate popu- ...
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A Maximum Likelihood Approach to Single-channel Source Separation
... thus least redundant. In constrast, correlation-based transformations such as principal component analysis (PCA) are based on dimensionality reduction. They search for the axis that has minimum correlations, which does ...
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Modeling of Imperfect Data in Medical Sciences by Markov Chain with Numerical Computation
... finding maximum likelihood estimate of transition ...This approach is known as EM algorithm, which includes main optimum advantages among other approaches, and consists of two phases: phase ...
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A simple approach to maximum intractable likelihood estimation
... ducting likelihood-based inference, despite the complexity of the corresponding likelihood function, on time series models which allow for simulating realisations at any parameter ...whose approach ...
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Using interviewer random effects to remove selection bias from HIV prevalence estimates
... the maximum like- lihood estimate (by definition, the value with the highest posterior probability) ignores less likely values, even where their posterior probability is ...the likelihood for each ...
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Pitfalls of the most commonly used models of context dependent substitution
... the TF variant that does contain the independent process, substantially complicating inference of LRTs and the inter- pretability of exchangeability parameter MLEs. Contrast this with the NF form where NF nuGTR is the ...
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Testing for equality of evolutionary rates.
... If the two parameter model (model I) is used on twofold degenerate sites, the estimate of transition rate is the maximum likelihood estimate of. the synonymous rate at tw[r] ...
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Estimation and tests for power-transformed and threshold GARCH models
... which is a natural generalization of power-transformed and threshold GARCH(1,1) model in Hwang and Basawa (2004) and includes the standard GARCH model and many other models as special cases. We first establish the ...
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Novel maximum likelihood approach for passive detection and localisation of multiple emitters
... This mechanism for handling the complex multi- sensor/multi-target association problem, based on manip- ulating multiple competing hypotheses, removes the need to perform global data association (which can be a com- ...
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Maximum Likelihood with Auxiliary Information
... classical approach is to consider them ‘in isolation’ in the modelling process, implicitly assuming that the model fitted to these sample data is also appropriate for the population from which the sample is ...
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A New Class of Generalized Burr III Distribution for Lifetime Data
... presented. Maximum likelihood estimation technique is used to estimate the model parameters and applications to real datasets in order to illustrate the usefulness of the model are ...
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Parameter Estimation of Maneuvering Target Using Maximum Likelihood Estimation for MIMO Radar with Colocated Antennas
... This paper studies the performance of parameters estimation of maneuvering target in coherent MIMO radars with the application of maximum likelihood es- timation. Numerical simulation results show that MIMO ...
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Inference for the shape parameter of lognormal distribution in presence of fuzzy data
... In the Newton-Raphson algorithm, the solution of likelihood equation (5) is obtained through an iterative procedure. In each iterative step, the correction to the previous estimate 0 produces new ...
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