maximum likelihood estimation theory
Unified quasi maximum likelihood estimation theory for stable and unstable Markov bilinear processes
... quasi-maximum likelihood (QM L) estimation theory for stationary and nonstationary simple Markov bilinear (SM BL) models is ...the theory in …nite ...
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Can the Threshold Performance of Maximum Likelihood DOA Estimation be Improved by Tools from Random Matrix Theory?
... The theoretical results from RMT and their examination by direct Monte-Carlo simulations has confirmed that for Gaussian sources in Gaussian noise, ML DOA estimation in the so-called “threshold” region is not ...
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Application of novel statistical methods for biomarker selection to HIV infection data
... The past decade has seen an explosion in the availability and use of biomarkers data as a result of innovative discoveries and recent development of new biological and molecular techniques. Biomarkers are essential for ...
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Estimation and tests for power-transformed and threshold GARCH models
... quasi-maximum likelihood estimators (QMLE) of the parameters under the condition that the error distribution has finite fourth ...deviations estimation (LADE) for PTTGARCH(p,q) model, and prove that ...
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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 ...
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Maximum likelihood estimation for directional conditionally autoregressive models
... effects models to explain the latent spatial process using suitably formed neighbors (Breslow and Clayton, 1993). Gaussian CAR process has the merit that the finite dimensional joint distributions of the spatial process ...
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On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... give the simulation results more perspectives and to confirm the derived approximate bias and variance formulae in Section 5, we also computed the asymptotic bias and standard deviation based on the formulae (5.7) and ...
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Maximum likelihood parametric reconstruction of forest vertical structure from inclined laser quadrat sampling.
... the theory for maximum likelihood estimation of a parametric model of forest vertical structure, and illustrate it using inclined point quadrat sam- pling with a handheld ...
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Environmental extreme events detection: A survey
... Climatic events are occasional variations producing extreme values of climate indicators, such as temperature and precipitation. Climate change can potentially change the intensity, frequency, timing and duration of ...
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Approximate maximum likelihood estimation for population genetic inference
... the likelihood function consists of a computationally infeasible number of terms (Stephens, ...distribution theory, but a known data generating process under which data can be ...
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Maximum likelihood estimation for multiscale Ornstein Uhlenbeck processes
... the estimation problem for discretely observed diffusions (see [21, 22, ...The maximum likelihood estimator for the drift of a homogenized equation converges after proper ...
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Maximum-Likelihood Estimation of Coalescence Times in Genealogical Trees
... Our method has the advantage of the optimal as- ymptotic properties (as the sequence length increases) of maximum-likelihood estimation and in simulation stud- ies was shown to give slight ...
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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 of the Multivariate Normal Mixture Model
... The maximum likelihood estimates themselves are usually computed via the EM algorithm, which is a derivative-free method, but they can also be computed directly from the likelihood or by setting the ...
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Maximum-Likelihood Estimation of Relatedness
... less well than the former ( J. Wang, personal communi- frequent, and one in which allele frequencies at each cation). Note that some of these nonlikelihood estima- locus were independently drawn from the same Dirich- ...
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Research on Initialization on EM Algorithm Based on Gaussian Mixture Model
... the maximum-likelihood estimates ( MLEs ) for mixture distributions is the EM algorithm ( Dempster et ...the maximum likelihood estimate when the observation data is incomplete data, which has ...
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Estimation of Dynamic Stochastic Frontier Model using Likelihood based Approaches
... the likelihood function is not too complicated, the FML estimation is recommended for an empirical ...PCL estimation instead. The QML estimation may be used when the time span is extremely ...
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Computational approaches for maximum likelihood estimation for nonlinearmixed models.
... true likelihood be performed instead of using approximations and how can the optimization be performed with random in- put? By using numerical integration techniques, the likelihood can be approximated to ...
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A maximum likelihood approach to correlation dimension and entropy estimation
... To obtain the correlation dimension and entropy from an experimental time series we derive estimators for these quantities together with expressions for their variances [r] ...
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Model-Free IRL Using Maximum Likelihood Estimation
... The problem of learning an expert’s unknown reward func- tion using a limited number of demonstrations recorded from the expert’s behavior is investigated in the area of inverse re- inforcement learning (IRL). To gain ...
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