Search results for "Restricted maximum likelihood"

showing 4 items of 4 documents

An approximation to maximum likelihood estimates in reduced models

1990

SUMMARY An approximation to the maximum likelihood estimates of the parameters in a model can be obtained from the corresponding estimates and information matrices in an extended model, i.e. a model with additional parameters. The approximation is close provided that the data are consistent with the first model. Applications are described to log linear models for discrete data, to models for multivariate normal distributions with special covariance matrices and to mixed discrete-continuous models.

Statistics and ProbabilityRestricted maximum likelihoodApplied MathematicsGeneral MathematicsMaximum likelihoodMultivariate normal distributionMaximum likelihood sequence estimationCovarianceAgricultural and Biological Sciences (miscellaneous)Extended modelStatisticsExpectation–maximization algorithmLog-linear modelStatistics Probability and UncertaintyGeneral Agricultural and Biological SciencesMathematicsBiometrika
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A multi-site study to classify semi-natural grassland types

2009

International audience; Calibration and validation of simulation models describing herbage growth or feed quality of seminatural grasslands is a complex task for agronomists without investing effort into botanical surveys. To facilitate such modelling efforts, a limited number of grassland types were identified using a functional classification of species. These grassland types were characterized by three descriptors required to model herbage growth or feed quality: the abundance-weighted mean leaf dry matter content across grass species, the relative abundance of grasses, and an estimate of species richness. We conducted a multi-site analysis over 749 grasslands from eight temperate region…

0106 biological sciencesleaf traitsRestricted maximum likelihoodManagement type01 natural sciencesGrasslandnitrogenland-use changeNutrientSemi-natural grasslandphosphorus2. Zero hunger[SDV.EE]Life Sciences [q-bio]/Ecology environmentgeography.geographical_feature_categoryEcology04 agricultural and veterinary sciencesVegetationClassification[ SDE.MCG ] Environmental Sciences/Global ChangesFunctional traitsplant-species richnessgrowth[SDE.MCG]Environmental Sciences/Global Changespermanent pastures[SDV.BID]Life Sciences [q-bio]/Biodiversity010603 evolutionary biologyEllenberg indicator values[ SDV.EE ] Life Sciences [q-bio]/Ecology environmentdiversity[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsTemperate climateRelative species abundance[ SDV.BID ] Life Sciences [q-bio]/Biodiversitygeography[ SDE.BE ] Environmental Sciences/Biodiversity and EcologySimulation modelingNutrients15. Life on land[SDE.ES]Environmental Sciences/Environmental and Society[ SDV.EE.ECO ] Life Sciences [q-bio]/Ecology environment/EcosystemsAgronomy040103 agronomy & agricultureresponses0401 agriculture forestry and fisheriesEnvironmental scienceAnimal Science and ZoologySpecies richness[SDE.BE]Environmental Sciences/Biodiversity and EcologyAgronomy and Crop Science[ SDE.ES ] Environmental Sciences/Environmental and SocietySpecies richness
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Maximum likelihood estimation for the exponential power function parameters

1995

This paper addresses the problem of obtaining maximum likelihood estimates for the three parameters of the exponential power function; the information matrix is derived and the covariance matrix is here presented; the regularity conditions which ensure asymptotic normality and efficiency are examined. A numerical investigation is performed for exploring the bias and variance of the maximum likelihood estimates and their dependence on sample size and shape parameter.

Statistics and ProbabilityEstimation theoryRestricted maximum likelihoodMaximum likelihood sequence estimationLikelihood principlesymbols.namesakeEstimation of covariance matricesModeling and SimulationStatisticsExpectation–maximization algorithmsymbolsFisher informationLikelihood functionMathematicsCommunications in Statistics - Simulation and Computation
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Electrical measurements in µ-EDM

2008

The phenomena occurring between the electrodes in electric discharge machining when manufacturing features on the micro-metre scale (µ-EDM) is not fully understood. Poor quantitative knowledge of the sources of variability affecting this process hinders the identification of its natural tolerance limits. Moreover, improvements in measuring systems contribute to the acquisition of new information that often conflicts with existent theoretical models of this process. The prime objective of this paper is to advance the experimental knowledge of µ-EDM by providing a measurement framework for the electrical discharges. The effects of the electrodes metallic materials (Ag, Ni, Ti, W) on the elect…

Materials scienceRestricted maximum likelihoodbusiness.industryTKMechanical EngineeringSystem of measurementProcess (computing)Electrical engineeringMechanical engineeringElectronic Optical and Magnetic MaterialsElectrical discharge machiningMachiningMechanics of MaterialsElectrodeElectrical measurementsTJElectrical and Electronic EngineeringQAbusinessVoltageJournal of Micromechanics and Microengineering
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