Maximum likelihood parameter estimation
Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo
... ML estimation – noting that the method can be easily adapted to Bayesian marginal Maximum a Pos- teriori setting by considering a slightly different sequence of target ...
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Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... Statistical entropy deals with a measure of uncertainty or disorder associated with a probability distribution. The principle of maximum entropy (ME) is a tool for infer- ence under uncertainty [1,2]. This ...
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The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models
... the estimation run time of the DE-assisted strategy relative to that of the conventional ...the estimation issue of interest is not to locate a unique maximum in the fastest time but to locate the ...
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Maximum likelihood estimation for stochastic processes - a martingale approach
... the estimation procedure (see 4.§1 for some discussion of this approach). In two papers, M.M. Rao [1, 2] discusses the asymptotic theory of ML estimation for stochastic processes. For the discrete time ...
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Parameter estimations and copula methods for burr type III and type XII distributions
... The process of analysis in this study involves the characteristics of Burr Type III and XII distributions, Maximum Likelihood Estimation (MLE) and Expectation- Maximization (EM) algorithm approaches ...
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Maximum Likelihood Estimation of the Multivariate Normal Mixture Model
... obtain parameter estimates and bootstrap-based stan- dard ...the parameter estimates into MATLAB and use them to obtain the information-based standard error ...
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Approximate maximum likelihood estimation for population genetic inference
... approximate maximum likelihood ...entire parameter space, we adapt stochastic approximation methods and propose two algorithms to approximate the maximum likelihood ...the ...
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Estimation of the Parameters of the Reversed Generalized Logistic Distribution with Progressive Censoring Data
... The maximum likelihood estimators MLEs for the scale and shape parameters of the RGL distribution based on progressive Type II censoring are ...scale parameter and an exact joint confidence region ...
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Asymptotics of Maximum Composite Likelihood Estimation for Geostatistical Data
... on maximum composite likelihood estimation in a geostatistical setting has lim- ited results on the statistical performance of such estimators relative to maximum likelihood ...
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Maximum likelihood estimation for multiscale Ornstein Uhlenbeck processes
... exact likelihood is straight ...Hurst parameter H ∈ (0, 1); and [18] studied strong consistency and asymptotic normality for the usual drift estimator for infinite dimensional fractional OU process, under ...
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A simple approach to maximum intractable likelihood estimation
... the likelihood is intractable, such a statistic may not be ...the likelihood approx- imation in this setting, it is difficult to draw useful conclusions from such a char- ...true parameter value if a ...
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On Maximum Likelihood Estimation for the Three Parameter Gamma Distribution Based on Left Censored Samples
... on maximum flood levels from Antle and Dumonceaux (1973) ...the maximum flood levels in millions of cubic feet per second for the Susquehanna River at Harrisburg, Pennsylvania, over 20 four-year periods ...
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Inference Based on k-Record Values from Generalized Exponential Distribution
... the maximum likelihood estimator (MLE) for scale parameter σ and shape parameter β of GE ...Bayes estimation of scale parameter σ and shape parameter β of GE ...
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On Maximum Likelihood Estimates for the Shape Parameter of the Generalized Pareto Distribution
... the parameter space to ( ) 1/ 2 < < − γ ( 1/ 2 ) and Grimshaw [7] for extreme value index, the shape parameter γ ≤ 1 , and we propose an algorithm, to estimate the extreme value index, the shape ...
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The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models
... the parameter space much more comprehen- sively than gradient-based algorithms, and can be expected to locate a point close to the global maximum more ...random parameter logit model featuring both ...
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The Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways
... the likelihood and the predictor gradient, which in turn requires the solution of a nonlinear filtering problem as shown in ...EM-based Maximum Likelihood estimation approach is developed for ...
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E-Bayesian Estimation for Burr-X Distribution Based on Type-I Hybrid Censoring Scheme
... E-Bayesian estimation (expectation of the Bayesian estimate) and the corresponding maximum likelihood and Bayesian estimation methods are discussed for the distribution parameter and ...
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Maximum Likelihood Estimation of Co-Channel Multicomponent Polynomial Phase Signals Using Importance Sampling
... (PPS) parameter estimation methods restricted to monocomponent case, this paper focuses on the parameter estimation of multicomponent PPSs mixed in a single channel, which is more ...
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Estimation of Multivariate Sample Selection Models via a Parameter Expanded Monte Carlo EM Algorithm
... a parameter-expanded Monte Carlo EM (PX-MCEM) algorithm to perform maximum likelihood estimation in a multivariate sample selection ...of estimation, the proposed algorithm does not ...
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On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... approximate likelihood functions, which are maximized to obtain the approximate maximum likelihood estimators ...approximate likelihood converges to the true likelihood as the number of ...
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