Search results for "Exponent"

showing 10 items of 896 documents

Maximum probability estimators in the case of exponential distribution

1975

In 1966–1969L. Weiss andJ. Wolfowitz developed the theory of „maximum probability” estimators (m.p.e.'s). M.p.e.'s have the property of minimizing the limiting value of the risk (see (2.10).) In the present paper, therfore, after a short description of the new method, a fundamental loss function is introduced, for which—in the so-called regular case—the optimality property of the maximum probability estimators yields the classical result ofR.A. Fisher on the asymptotic efficiency of the maximum likelihood estimator. Thereby it turns out that the m.p.e.'s possess still another important optimality property for this loss function. For the latter the parameters of the exponential distribution—…

Statistics and ProbabilityExponentially modified Gaussian distributionExponential distributionUniform distribution (continuous)Location parameterStatisticsGamma distributionEstimatorApplied mathematicsStatistics Probability and UncertaintyNatural exponential familyMathematicsExponential functionMetrika
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Explicit, identical maximum likelihood estimates for some cyclic Gaussian and cyclic Ising models

2017

Cyclic models are a subclass of graphical Markov models with simple, undirected probability graphs that are chordless cycles. In general, all currently known distributions require iterative procedures to obtain maximum likelihood estimates in such cyclic models. For exponential families, the relevant conditional independence constraint for a variable pair is given all remaining variables, and it is captured by vanishing canonical parameters involving this pair. For Gaussian models, the canonical parameter is a concentration, that is, an off-diagonal element in the inverse covariance matrix, while for Ising models, it is a conditional log-linear, two-factor interaction. We give conditions un…

Statistics and ProbabilityGaussianBinary numberMarkov modelCombinatoricsConstraint (information theory)symbols.namesakeExponential familyConditional independencesymbolsApplied mathematicsIsing modelStatistics Probability and UncertaintyVariable (mathematics)MathematicsStat
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Extended differential geometric LARS for high-dimensional GLMs with general dispersion parameter

2018

A large class of modeling and prediction problems involves outcomes that belong to an exponential family distribution. Generalized linear models (GLMs) are a standard way of dealing with such situations. Even in high-dimensional feature spaces GLMs can be extended to deal with such situations. Penalized inference approaches, such as the $$\ell _1$$ or SCAD, or extensions of least angle regression, such as dgLARS, have been proposed to deal with GLMs with high-dimensional feature spaces. Although the theory underlying these methods is in principle generic, the implementation has remained restricted to dispersion-free models, such as the Poisson and logistic regression models. The aim of this…

Statistics and ProbabilityGeneralized linear modelMathematical optimizationGeneralized linear modelsPredictor-€“corrector algorithmGeneralized linear model02 engineering and technologyPoisson distributionDANTZIG SELECTOR01 natural sciencesCross-validationHigh-dimensional inferenceTheoretical Computer Science010104 statistics & probabilitysymbols.namesakeExponential familyLEAST ANGLE REGRESSION0202 electrical engineering electronic engineering information engineeringApplied mathematicsStatistics::Methodology0101 mathematicsCROSS-VALIDATIONMathematicsLeast-angle regressionLinear model020206 networking & telecommunicationsProbability and statisticsVARIABLE SELECTIONEfficient estimatorPredictor-corrector algorithmComputational Theory and MathematicsDispersion paremeterLINEAR-MODELSsymbolsSHRINKAGEStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaStatistics and Computing
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Differential geometric least angle regression: a differential geometric approach to sparse generalized linear models

2013

Summary Sparsity is an essential feature of many contemporary data problems. Remote sensing, various forms of automated screening and other high throughput measurement devices collect a large amount of information, typically about few independent statistical subjects or units. In certain cases it is reasonable to assume that the underlying process generating the data is itself sparse, in the sense that only a few of the measured variables are involved in the process. We propose an explicit method of monotonically decreasing sparsity for outcomes that can be modelled by an exponential family. In our approach we generalize the equiangular condition in a generalized linear model. Although the …

Statistics and ProbabilityGeneralized linear modelSparse modelMathematical optimizationGeneralized linear modelsVariable selectionPath following algorithmEquiangular polygonGeneralized linear modelLASSODANTZIG SELECTORsymbols.namesakeExponential familyLasso (statistics)Sparse modelsDifferential geometryInformation geometryCOORDINATE DESCENTFisher informationERRORMathematicsLeast-angle regressionLeast angle regressionGeneralized degrees of freedomsymbolsSHRINKAGEStatistics Probability and UncertaintySimple linear regressionInformation geometrySettore SECS-S/01 - StatisticaAlgorithmCovariance penalty theory
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Generating survival times to simulate Cox proportional hazards models

2005

Simulation studies present an important statistical tool to investigate the performance, properties and adequacy of statistical models in pre-specified situations. One of the most important statistical models in medical research is the proportional hazards model of Cox. In this paper, techniques to generate survival times for simulation studies regarding Cox proportional hazards models are presented. A general formula describing the relation between the hazard and the corresponding survival time of the Cox model is derived, which is useful in simulation studies. It is shown how the exponential, the Weibull and the Gompertz distribution can be applied to generate appropriate survival times f…

Statistics and ProbabilityHazard (logic)Exponential distributionEpidemiologyComputer scienceProportional hazards modelStatisticsEconometricsStatistical modelSurvival analysisGompertz distributionExponential functionWeibull distributionStatistics in Medicine
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Thermodynamic limit of particle-hole form factors in the massless XXZ Heisenberg chain

2010

We study the thermodynamic limit of the particle-hole form factors of the XXZ Heisenberg chain in the massless regime. We show that, in this limit, such form factors decrease as an explicitly computed power-law in the system-size. Moreover, the corresponding amplitudes can be obtained as a product of a "smooth" and a "discrete" part: the former depends continuously on the rapidities of the particles and holes, whereas the latter has an additional explicit dependence on the set of integer numbers that label each excited state in the associated logarithmic Bethe equations. We also show that special form factors corresponding to zero-energy excitations lying on the Fermi surface decrease as a …

Statistics and ProbabilityHigh Energy Physics - Theory[NLIN.NLIN-SI] Nonlinear Sciences [physics]/Exactly Solvable and Integrable Systems [nlin.SI]LogarithmIntegrable systemfacteurs de formemodèles intégrables[PHYS.MPHY]Physics [physics]/Mathematical Physics [math-ph]FOS: Physical sciences01 natural sciencesPower law[ PHYS.HTHE ] Physics [physics]/High Energy Physics - Theory [hep-th][PHYS.COND.CM-SM] Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech]Chain (algebraic topology)[MATH.MATH-MP]Mathematics [math]/Mathematical Physics [math-ph]0103 physical sciencesddc:550[NLIN.NLIN-SI]Nonlinear Sciences [physics]/Exactly Solvable and Integrable Systems [nlin.SI]Limit (mathematics)[MATH.MATH-MP] Mathematics [math]/Mathematical Physics [math-ph][PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech]010306 general physicsMathematical PhysicsCondensed Matter - Statistical MechanicsMathematical physicsPhysicsNonlinear Sciences - Exactly Solvable and Integrable SystemsStatistical Mechanics (cond-mat.stat-mech)010308 nuclear & particles physics[PHYS.HTHE]Physics [physics]/High Energy Physics - Theory [hep-th][ MATH.MATH-MP ] Mathematics [math]/Mathematical Physics [math-ph]Statistical and Nonlinear PhysicsMathematical Physics (math-ph)[PHYS.MPHY] Physics [physics]/Mathematical Physics [math-ph]Massless particleHigh Energy Physics - Theory (hep-th)[ PHYS.COND.CM-SM ] Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech]Thermodynamic limitfonctions de corélation[PHYS.HTHE] Physics [physics]/High Energy Physics - Theory [hep-th][ PHYS.MPHY ] Physics [physics]/Mathematical Physics [math-ph]Statistics Probability and UncertaintyExactly Solvable and Integrable Systems (nlin.SI)Critical exponent[ NLIN.NLIN-SI ] Nonlinear Sciences [physics]/Exactly Solvable and Integrable Systems [nlin.SI]
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Effective electrical conductivity of microstructural patterns of binary mixtures on a square lattice in the presence of nearest-neighbour interactions

2018

Abstract The effective conductivity and percolative behaviour of microstructural patterns of binary mixtures are studied. Microstructure patterns are not entirely random, but result from the presence of attractive or repulsive interactions and thermal fluctuations. The interactions of the particles with one another lead to the formation of correlations between particle positions, while thermal fluctuations weaken these correlations. A simple lattice model is used, where each site is occupied by a single particle, and interactions can occur only between the nearest neighbours. The Kawasaki algorithm is adopted to create 2D microstructure samples. The microstructure is treated as a continuous…

Statistics and ProbabilityMaterials scienceCondensed matter physicsThermal fluctuationsPercolationPercolation thresholdAtmospheric temperature rangeConductivityCondensed Matter Physics01 natural sciencesSquare lattice010305 fluids & plasmasmaterialsLattice modelEffective properties of heterogeneous0103 physical sciencesParticle010306 general physicsCritical exponentLattice model (physics)Physica A-Statistical Mechanics and Its Applications
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Lyapunov exponent and topological entropy plateaus in piecewise linear maps

2013

We consider a two-parameter family of piecewise linear maps in which the moduli of the two slopes take different values. We provide numerical evidence of the existence of some parameter regions in which the Lyapunov exponent and the topological entropy remain constant. Analytical proof of this phenomenon is also given for certain cases. Surprisingly however, the systems with that property are not conjugate as we prove by using kneading theory.

Statistics and ProbabilityMathematical analysisGeneral Physics and AstronomyStatistical and Nonlinear PhysicsTopological entropyLyapunov exponentTopological entropy in physicsModuliPiecewise linear functionsymbols.namesakeModeling and SimulationsymbolsConstant (mathematics)Mathematical PhysicsMathematicsJournal of Physics A: Mathematical and Theoretical
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Statistics of return times for weighted maps of the interval

2000

For non markovian, piecewise monotonic maps of the interval associated to a potential, we prove that the law of the entrance time in a cylinder, when renormalized by the measure of the cylinder, converges to an exponential law for almost all cylinders. Thanks to this result, we prove that the fluctuations of Rn, first return time in a cylinder, are lognormal.

Statistics and ProbabilityMathematical analysisMarkov processMonotonic functionCylinder (engine)law.inventionPhysics::Fluid DynamicsReturn timesymbols.namesakelawLog-normal distributionPiecewisesymbolsStatistics Probability and UncertaintyExponential lawMathematicsAnnales de l'Institut Henri Poincare (B) Probability and Statistics
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Exponential and bayesian conjugate families: Review and extensions

1997

The notion of a conjugate family of distributions plays a very important role in the Bayesian approach to parametric inference. One of the main features of such a family is that it is closed under sampling, but a conjugate family often provides prior distributions which are tractable in various other respects. This paper is concerned with the properties of conjugate families for exponential family models. Special attention is given to the class of natural exponential families having a quadratic variance function, for which the theory is particularly fruitful. Several classes of conjugate families have been considered in the literature and here we describe some of their most interesting feat…

Statistics and ProbabilityMathematical optimizationClass (set theory)Exponential familyQuadratic equationBayesian probabilityApplied mathematicsStatistics Probability and UncertaintyBayesian inferenceExponential functionConjugateVariance functionMathematicsTest
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