Maximum-likelihood estimation
Maximum Likelihood Estimation of Modal Parameters in Structures Using the Expectation Maximization Algorithm
... on Maximum Likelihood Estimation (MLE) with the Expectation Maximization (EM) ...proposed Maximum Likelihood Estimation with Expectation Maximization algo- rithm has been ...
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Operational Modal Analysis using Expectation Maximization Algorithm
... squares estimation (LSE), maximum likelihood estimation (MLE), eigensystem re- alization algorithm (ERA) and stochastic subspace identification method ...
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Using the EM algorithm to estimate the state space model for OMAX
... on Maximum Likelihood Estimation and the Expectation Maximization algorithm that is applied to the estimation of modal parameters from system input and output ...
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Eigenvalues and constraints in mixture modeling: geometric and computational issues
... constrained estimation, that serves a twofold purpose: to avoid convergence to degenerate solutions and to reduce the onset of non interesting (spurious) maximizers, related to complex likelihood ...imum ...
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SAGE and Maximum Entropy Algorithmic Comparison for Adaptive Antenna Array Calibration
... (Maximum Likelihood Estimation) and MEE (Maximum Entropy Estimation) are analyzed and simulated, in order to obtain their relative ...
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Rediscovery of the nemertean Prostoma graecense from Xochimilco, 75 years after its first and only record
... the maximum likelihood (ML) criterion, employing a GTR+GAMMA+I model as suggested by jModelTest ...2012). Likelihood inference (20 replicates), model parameters, and bootstrap (BS) support (500 ...
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ANALYSIS OF THE LAND USE AND COVER CHANGES IN THE METROPOLITAN AREA OF TEPIC-XALISCO (1973–2015) THROUGH LANDSAT IMAGES
... In this context, the objective of this study was to analyze the dynamics on urban LUCC at local scale. The methodology was developed through the analysis and processing of four Landsat satellite images corresponding to ...
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Molecular phylogenetic analyses reveal the importance of taxon sampling in cryptic diversity: Liolaemus nigroviridis and L monticola (Liolaeminae) as focal species
... rearrangements); this should be considered in the design of studies. The lizard genus Liolaemus is widely distributed in southern South America and includes more than 250 described species. The number of taxa and the ...
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Distribución asintotica de estimadores de momentos
... point estimation. Undoubt- edly, the area of point estimation lays in the core of the statistical method- ology, and a major step in every theoretical or applied analysis is the deter- mination of estimates ...
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First substantiated record of Raja asterias Delaroche, 1809 (Elasmobranchii: Rajiformes: Rajidae) in the Gulf of Cádiz, North eastern Atlantic
... The maximum likelihood (ML) method was used to infer phylogenetic relation between taxa, using the Hasegawa-Kishino-Yano (1985) methodology with invariant sites (HKY+I) as substitution model, selected by ...
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Updating weighting matrices by cross entropy
... AbstrAct: The classical approach to estimate spatial models lays on the choice of a spatial weights matrix that reflects the interactions among locations. The rule used to define this matrix is supposed to be the most ...
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Critical Sections and Software Transactional Memory Comparison in the Context of a TLS Runtime Library
... an estimation of the maximum speedup attainable (applying Amhdahls Law), the percentage of iterations of the target loop that lead to runtime dependence violations, the number of speculative variables ...
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Rodents of the eastern and western slopes of the Tropical Andes: phylogenetic and taxonomic insights using DNA barcodes
... Species delimitation. We performed species delimita- tion analyses for the best maximum likelihood trees using the Poisson tree processes (PTP) method in the bPTP web server (Zhang et al. 2013). The PTP ...
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Microeconometria_ métodos y aplicaciones_ Cameron&Trivedi
... descriptive statistics. The following techniques are useful. First, use summary statistics (min, max, mean, and median) to make sure that the data are in the proper interval and on the proper scale. For instance, ...
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Robust Approaches for Fuzzy Clusterwise Regression Based on Trimming and Constraints
... in Section 2.2 and 2.3). The choice of the fuzzifier parameter m depends on the desired degree of fuzziness in the clustering solution. Unfortunately, as happens with other likelihood-based fuzzy clustering ...
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Fitting phase type distribution to service process with sequential phases
... discussed maximum likelihood estimation for a class of ergodic queueing models which give rise to birth and death ...the maximum likelihood estimators of the arrival and the service ...
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Introducing the photometric maximum likelihood method: galaxy luminosity functions at z < 1 2 in MUSYC ECDFS
... fact that, when evaluating the distribution of galaxies in photo- metric space, in principle, any galaxy population at any redshift can contribute to the galaxy counts at a given point in photometric space. It is not ...
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FIML estimation of treatment effect models with endogenous selection and multiple censored responses via a Monte Carlo EM algorithm
... information maximum likelihood (FIML), being the later more efficient than the ...FIML estimation of a multivariate treatment model can be challenging for two ...
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TítuloThe Phylogenetic Likelihood Library
... SIMD instructions can be used by loading data into specific vector registers (storage space within the (co)processor) with a length of 128, 256, and soon 512 bits. Those registers can hold multiple, independent data ...
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A computerized adaptive test for enterprising personality assessment in youth
... using maximum likelihood procedures, an item from the total data matrix with a maximum information function at that estimated ability level (θ*) is presented; (c) Using maximum ...
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