Search results for "selector"

showing 9 items of 9 documents

Henstock–Kurzweil–Pettis integrability of compact valued multifunctions with values in an arbitrary Banach space

2013

Abstract The aim of this paper is to describe Henstock–Kurzweil–Pettis (HKP) integrable compact valued multifunctions. Such characterizations are known in case of functions (see Di Piazza and Musial (2006)  [16] ). It is also known (see Di Piazza and Musial (2010)  [19] ) that each HKP-integrable compact valued multifunction can be represented as a sum of a Pettis integrable multifunction and of an HKP-integrable function. Invoking to that decomposition, we present a pure topological characterization of integrability. Having applied the above results, we obtain two convergence theorems, that generalize results known for HKP-integrable functions. We emphasize also the special role played in …

Discrete mathematicsMathematics::Functional AnalysisProperty (philosophy)Henstock integralIntegrable systemApplied MathematicsBanach spaceconvergence theoremsFunction (mathematics)Characterization (mathematics)set-valued Henstock-Kurzweil-Pettis integralset-valued Pettis integralsupport functionMultifunctionSettore MAT/05 - Analisi MatematicaConvergence (routing)AnalysisselectorMathematicsJournal of Mathematical Analysis and Applications
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PBX1 acts as terminal selector for olfactory bulb dopaminergic neurons

2020

15 páginas, 8 figuras. Supplementary information available online at http://dev.biologists.org/lookup/doi/10.1242/dev.186841.supplemental

MaleInterneuronCell SurvivalNeurogenesisRNA SplicingNeuron differentiationMitosisBiologyAdult neurogenesis03 medical and health sciencesOlfactory bulb0302 clinical medicineNeuroblastInterneuronsmedicineAnimalsProtein IsoformsCell LineageProgenitor cellTerminal selector10. No inequalityMolecular BiologyTranscription factorBody Patterning030304 developmental biologyMice KnockoutDopaminergic neuron0303 health sciencesDopaminergic NeuronsPre-B-Cell Leukemia Transcription Factor 1fungiNeurogenesisDopaminergicCell DifferentiationExonsEmbryo Mammalian3. Good healthOlfactory bulbmedicine.anatomical_structureMutationNeuron differentiationNeuroscience030217 neurology & neurosurgeryTranscription FactorsAlternative splicingDevelopmental BiologyDevelopment
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Estudio del papel de PBX1 como selector terminal de las neuronas dopaminérgicas del bulbo olfatorio

2021

Tesis doctoral 177 p, figuras y tablas.

PBX1diferenciación terminalUNESCO::CIENCIAS DE LA VIDAneuronas dopaminérgicasneurobiologíaselector terminalbulbo olfatorio:CIENCIAS DE LA VIDA [UNESCO]factor de transcripción
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Measurable selectors and set-valued Pettis integral in non-separable Banach spaces

2009

AbstractKuratowski and Ryll-Nardzewski's theorem about the existence of measurable selectors for multi-functions is one of the keystones for the study of set-valued integration; one of the drawbacks of this result is that separability is always required for the range space. In this paper we study Pettis integrability for multi-functions and we obtain a Kuratowski and Ryll-Nardzewski's type selection theorem without the requirement of separability for the range space. Being more precise, we show that any Pettis integrable multi-function F:Ω→cwk(X) defined in a complete finite measure space (Ω,Σ,μ) with values in the family cwk(X) of all non-empty convex weakly compact subsets of a general (n…

Pettis integralDiscrete mathematicsPure mathematicsUniform integrabilityIntegrable systemMulti-functionClosure (topology)Banach spaceSpace (mathematics)Measure (mathematics)Multi-measureSeparable spacePettis integralMeasurable selectorAnalysisMathematicsJournal of Functional Analysis
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A decomposition of Denjoy-Khintchine-Pettis and Henstock-Kurzweil-Pettis integrable multifunctions

2010

We proved in one of our earlier papers that in case of separable Banach space valued multifunctions each Henstock-Kurzweil-Pettis integrable multifunction can be represented as a sum of one of its Henstock-Kurzweil-Pettis integrable selector and a Pettis integrable multifunction. Now, we prove that the same result can be achieved in case of an arbitrary Banach space. Moreover we show that an analogous result holds true also for the Denjoy-Khintchine-Pettis integrable multifunctions. Applying the representation theorem we describe the multipliers of HKP and DKP integrable functions. Then we use this description to obtain an operator characterization of HKP and DKP integrability.

Settore MAT/05 - Analisi MatematicaMultifunctions Pettis set-valued integral Kurzweil-Henstock integral Kurzweil-Henstock-Pettis integral support function Denjoy-Khintchine-Pettis integral selectors.
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dglars: An R Package to Estimate Sparse Generalized Linear Models

2014

dglars is a publicly available R package that implements the method proposed in Augugliaro, Mineo, and Wit (2013), developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method proposed in Efron, Hastie, Johnstone, and Tibshirani (2004). The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve: a predictor-corrector algorithm, proposed in Augugliaro et al. (2013), and a cyclic coordinate descent algorithm, proposed in Augugliaro, Mineo, and Wit (2012). The latter algorithm, as shown here, is significan…

Statistics and ProbabilityGeneralized linear modelEXPRESSIONMathematical optimizationTISSUESFortrancyclic coordinate descent algorithmdgLARSFeature selectionDANTZIG SELECTORpredictor-corrector algorithmLIKELIHOODLEAST ANGLE REGRESSIONsparse modelsDifferential (infinitesimal)differential geometrylcsh:Statisticslcsh:HA1-4737computer.programming_languageMathematicsLeast-angle regressionExtension (predicate logic)Expression (computer science)generalized linear modelsBREAST-CANCER RISKVARIABLE SELECTIONDifferential geometrydifferential geometry generalized linear models dgLARS predictor-corrector algorithm cyclic coordinate descent algorithm sparse models variable selection.MARKERSHRINKAGEStatistics Probability and UncertaintyHAPLOTYPESSettore SECS-S/01 - StatisticacomputerAlgorithmSoftware
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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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Cyclodextrins: heterocyclic molecules able to perform chiral recognition (Part II)

2006

The present paper collects the most significant advances appeared since late 1998 up to June 2005 in the field of applications of natural and modified cyclodextrins as chiral selectors, with particular regard for pharmaceuticals and natural products.

cyclodextrinpharmaceuticals and natural productschiral selector
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