Search results for "Maximum Likelihood Estimation"

showing 3 items of 3 documents

Compensation of missing wedge effects with sequential statistical reconstruction in electron tomography.

2014

Electron tomography (ET) of biological samples is used to study the organization and the structure of the whole cell and subcellular complexes in great detail. However, projections cannot be acquired over full tilt angle range with biological samples in electron microscopy. ET image reconstruction can be considered an ill-posed problem because of this missing information. This results in artifacts, seen as the loss of three-dimensional (3D) resolution in the reconstructed images. The goal of this study was to achieve isotropic resolution with a statistical reconstruction method, sequential maximum a posteriori expectation maximization (sMAP-EM), using no prior morphological knowledge about …

Electron Microscope TomographyComputer scienceImage Processinglcsh:MedicineBioinformaticsDiagnostic Radiologylaw.inventionComputer-AssistedMathematical and Statistical TechniqueslawImage Processing Computer-AssistedMedicine and Health SciencesElectron Microscopylcsh:ScienceTomographyMicroscopyMultidisciplinaryMaximum Likelihood EstimationPhysical SciencesBiomedical ImagingTomographyCellular Structures and OrganellesArtifactsAlgorithmAlgorithmsStatistics (Mathematics)Research ArticleGeneral Science & TechnologyImaging TechniquesBioengineeringImage processingIterative reconstructionResearch and Analysis MethodsImaging phantomElectron Beam TomographyDiagnostic MedicineExpectation–maximization algorithmMaximum a posteriori estimationStatistical Methodsta217lcsh:Rta1182Biology and Life SciencesComputational BiologyCell BiologyElectron tomographyTransmission Electron Microscopylcsh:QGeneric health relevanceElectron microscopeMathematicsElectron Microscope TomographyPLoS ONE
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A penalized approach for the bivariate ordered logistic model with applications to social and medical data

2018

Bivariate ordered logistic models (BOLMs) are appealing to jointly model the marginal distribution of two ordered responses and their association, given a set of covariates. When the number of categories of the responses increases, the number of global odds ratios to be estimated also increases, and estimation gets problematic. In this work we propose a non-parametric approach for the maximum likelihood (ML) estimation of a BOLM, wherein penalties to the differences between adjacent row and column effects are applied. Our proposal is then compared to the Goodman and Dale models. Some simulation results as well as analyses of two real data sets are presented and discussed.

Statistics and ProbabilityAssociation (object-oriented programming)05 social sciencesDale modelBivariate analysisLogistic regression01 natural sciencesbivariate ordered logistic modelSet (abstract data type)010104 statistics & probabilityordinal associationpenalized maximum likelihood estimation0502 economics and businessStatisticsCovariateDale model bivariate ordered logistic model penalized maximum likelihood estimation ordinal associationSettore SECS-S/05 - Statistica Sociale0101 mathematicsStatistics Probability and UncertaintyMarginal distributionSettore SECS-S/01 - Statistica050205 econometrics MathematicsOrdinal association
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Goodness-of-fit tests for parametric excess hazard rate models with covariates

2017

In this paper we propose a general methodology for testing the null hypothesis that an excess hazard rate model, with or without covariates, belongs to a parametric family. Estimating the excess hazard rate function parametrically through the maximum likelihood method and non-parametrically (or semi-parametrically) we build a discrepancy process which is shown to be asymptotically Gaussian under the null hypothesis. Based on this result we are able to build some statistical tests in order to decide wether or not the null hypothesis is acceptable. We illustrate our results by the construction of chi-square tests which the behavior is studied through a Monte-Carlo study. Then the testing proc…

[STAT]Statistics [stat]Proportional excess hazards modelSemiparametric estimation[ STAT ] Statistics [stat]Maximum likelihood estimationNonparametric estimationcolon cancer dataCovariatesExcess hazard model[STAT] Statistics [stat]
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