Search results for " Likelihood"

showing 5 items of 115 documents

The new criteria for classification of rheumatoid arthritis: what we need to know for clinical practice.

2011

The new criteria for classification of Rheumatoid Arthritis have been recently released. They incorporate the anti-Citrullinated Protein antibody testing and the other classic criteria in a score system (the diagnosis of definite rheumatoid arthritis is made by a total score ≥6). These criteria try to meet the pressing needs to gain sensitivity in early disease. Symptoms, elevated acute-phase response, serologic abnormality, joint involvement were all considered for scoring after confirming the presence of synovitis in at least 1 joint in the absence of an alternative diagnosis that better explains the synovitis. However, no sensitivity and specificity has been showed. Moreover, Area Under …

medicine.medical_specialtySettore MED/09 - Medicina InternaArthritisDiseasePeptides CyclicSensitivity and SpecificityArthritis RheumatoidRheumatologyInternal medicineSynovitisInternal MedicineMedicineHumansIntensive care medicineAutoantibodiesReceiver operating characteristicbusiness.industryAutoantibodymedicine.diseaseSettore MED/45 - Scienze Infermieristiche Generali Cliniche E PediatricheRheumatoid arthritis Classification criteria Anti-citrullinated peptide autoantibodies Bayesian reasoning Likelihood ratio Sensitivity and specificityRheumatologySettore MED/16 - ReumatologiaRheumatoid arthritisPhysical therapyAbnormalitybusinessBiomarkersEuropean journal of internal medicine
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CALIBRATION OF LÉVY PROCESSES USING OPTIMAL CONTROL OF KOLMOGOROV EQUATIONS WITH PERIODIC BOUNDARY CONDITIONS

2018

We present an optimal control approach to the problem of model calibration for L\'evy processes based on a non parametric estimation procedure. The calibration problem is of considerable interest in mathematical finance and beyond. Calibration of L\'evy processes is particularly challenging as the jump distribution is given by an arbitrary L\'evy measure, which form a infinite dimensional space. In this work, we follow an approach which is related to the maximum likelihood theory of sieves. The sampling of the L\'evy process is modelled as independent observations of the stochastic process at some terminal time $T$. We use a generic spline discretization of the L\'evy jump measure and selec…

non-parametric maximum likelihood methodOptimization problemDiscretizationL ́evy processesoptimal control of PIDE010103 numerical & computational mathematics01 natural sciences93E10 (primary) 49K20 60G51 62G05 (secondary)010104 statistics & probabilitysymbols.namesakeConjugate gradient methodIMEX numerical methodQA1-939Applied mathematics0101 mathematicsMathematics - Optimization and ControlMathematicsKolmogorov-Fokker-Planck equationoptimal control of PIDE Kolmogorov-Fokker-Planck equation L ́evy processes non-parametric maximum likelihood method IMEX numerical method.SolverOptimal controlSpline (mathematics)Lévy processesModeling and SimulationLagrange multipliersymbolsAkaike information criterionMathematicsAnalysisMathematical Modelling and Analysis
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Mixed estimation technique in semi-parametric space-time point processes for earthquake description

2013

An estimation approach for the semi-parametric intensity function of a particular space-time point process is introduced. In particular we want to account for the estimation of parametric and nonparametric components simultaneously, applying a forward predictive likelihood to semi-parametric models. For each event, the probability of being a background event or one belonging to a seismic sequence is therefore estimated.

point proceNonparametric estimationSettore SECS-S/01 - Statisticaforward predictive likelihoodearthquakesETAS model
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Two‐sample problems in statistical data modelling

2010

A common problem in mathematical statistics is to check whether two samples differ from each other. From modelling point of view it is possible to make a statistical test for the equality of two means or alternatively two distribution functions. The second approach allows to represent the two‐sample test graphically. This can be done by adding simultaneous confidence bands to the probability‐probability (P — P) or quantile‐quantile (Q — Q) plots. In this paper we compare empirically the accuracy of the classical two‐sample t‐test, empirical likelihood method and several bootstrap methods. For a real data example both Q — Q and P — P plots with simultaneous confidence bands have been plotted…

simultaneous bandsMathematical statisticstwo‐sample problemt‐testempirical likelihoodData modelingquantile‐quantile plotEmpirical likelihoodDistribution functionprobability‐probability plotModeling and SimulationStatisticsQA1-939Point (geometry)Two sampleQ–Q plotAnalysisMathematicsStatistical hypothesis testingMathematicsMathematical Modelling and Analysis
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SNP and SML estimation of univariate and bivariate binary–choice models

2008

We discuss the semi-nonparametric approach of Gallant and Nychka (1987, Econometrica 55: 363–390), the semiparametric maximum likelihood approach of Klein and Spady (1993, Econometrica 61: 387–421), and a set of new Stata commands for semiparametric estimation of three binary-choice models. The first is a univariate model, while the second and the third are bivariate models without and with sample selection, respectively. The proposed estimators are root-n consistent and asymptotically normal for the model parameters of interest under weak assumptions on the distribution of the underlying error terms. Our Monte Carlo simulations suggest that the efficiency losses of the semi-nonparametric a…

st0000 snp snp2 snp2s sml sml2s binary-choice models seminonparametric approach SNP estimation semiparametric maximum likelihood SML estimation Monte Carlo simulationSettore SECS-P/05 - EconometriaSettore SECS-P/01 - Economia Politica
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