maximum likelihood parameter estimation method
On Maximum Likelihood Estimation for the Three Parameter Gamma Distribution Based on Left Censored Samples
... proposed method is considered in this section by fitting the three-parameter gamma distribution to the well known dataset on maximum flood levels from Antle and Dumonceaux (1973) ...the ...
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The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models
... The standard approach to maximizing the simulated log-likelihood function is to use a gradient-based method such as the Newton–Raphson or Broyden–Fletcher–Goldfarb–Shanno algorithms. See Train (2009), pages ...
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Two Parameter Laplace Type Bimodal Distribution
... two parameter Laplace type bimodal ...like estimation of the parameters by method of moments, Maximum likelihood method of estimation were ...
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Three Parameter Laplace Type Bimodal Distribution
... Three parameter Laplace type Bimodal ...through Method of Moments and Maximum Likelihood Estimation ...location parameter and best linear unbiased estimator of the location and ...
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Parameter Estimation of Maneuvering Target Using Maximum Likelihood Estimation for MIMO Radar with Colocated Antennas
... parameters estimation of maneuvering target in colo- cated MIMO radar by developing a maximum-likelihood ...of estimation for phased array radar and MIMO radar are compared under the same ...
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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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The Maximum Lq-Likelihood Method: an Application to Extreme Quantile Estimation in Finance
... distortion parameter q is properly chosen, the Mean Squared Error of the MLqE is sensibly smaller than that of ...quantile estimation, assessing the performance of MLqE on a financial stock market index for ...
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Maximum-Likelihood Estimation of Relatedness
... the parameter range itself, as opposed to Equation ...another method- the type of estimator, all method-of-moments estimators of-moments one based on the regression of similarity were examined in ...
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Inference for the shape parameter of lognormal distribution in presence of fuzzy data
... shape parameter of lognormal distribution involving experiment whose observations are described in terms of fuzzy ...The maximum likelihood procedure are developed for estimating the unknown ...of ...
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Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo
... general method for obtaining a set of samples from a sequence of distributions which can exist on the same or different ...SMC method (commonly referred to as particle fil- tering and summarised by [8]) in ...
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Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models
... the maximum likelihood method, estimates are very sensitive to deviations from a model, such as heteroscedastic- ity and data ...the maximum trimmed like- lihood are not applicable since, by ...
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Research on Initialization on EM Algorithm Based on Gaussian Mixture Model
... popular maximum likelihood estimation method, the iterative algorithm for solving the maximum likelihood estimator when the observation data is the incomplete data, but also is ...
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Comparison of Different methods of Estimation for Transmuted Lomax Distribution
... efficient parameter estimation of the parametric distribution than those estimated by the maximum likelihood estimation and method of moments for small samples (Hosking (1990), ...
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Readings in Targeted Maximum Likelihood Estimation
... Fisher’s method of maxi- mum likelihood estimation can be applied, or closely related M-estimate ...conditions. Maximum likelihood estimation in semiparametric models has been an ...
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PARAMETER ESTIMATION OF EXPONENTIAL HIDDEN MARKOV MODEL AND CONVERGENCE OF ITS PARAMETER ESTIMATOR SEQUENCE
... the parameter estimator, a maximum likelihood method is used. Numerical approximation is used through an Expectation Maximization (EM) algorithm. Under the continuous assumption, the sequence ...
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Selecting Best Software Reliability Growth Models: A Social Spider Algorithm based Approach
... matrix method applied on two datasets of ...for parameter estimation instead of relying on parameter estimated using the Least Square and Maximum Likelihood ...criteria ...
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Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... the method of Lagrange multipliers, such that the general solution form of the ME distribu- tions from maximizing the BGS entropy Equation (3) (Levine and Tribus, [11]) is ...
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Burr type III Software Reliability Growth Model with Interval Domain Data
... the parameter estimation of SRGMs are the maximum likelihood estimation (MLE) and the least squares estimation ...ML Estimation method is used for finding unknown ...
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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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On robust estimation for slope in linear functional relationship model
... new parameter estimation method based on the robust estimator and robust coefficient correlation in estimating the slope ...the maximum likelihood estimation including the ...
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