Search results for " linear models"

showing 10 items of 40 documents

KFAS : Exponential Family State Space Models in R

2017

State space modelling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes an R package KFAS for state space modelling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modelling is presented.

FOS: Computer and information sciencesStatistics and ProbabilityaikasarjatGaussianNegative binomial distributionforecastingPoisson distribution01 natural sciencesStatistics - ComputationMethodology (stat.ME)010104 statistics & probability03 medical and health sciencessymbols.namesake0302 clinical medicineExponential familyexponential familyGamma distributionStatistical inferenceState spaceApplied mathematicsSannolikhetsteori och statistik030212 general & internal medicine0101 mathematicsProbability Theory and Statisticslcsh:Statisticslcsh:HA1-4737Computation (stat.CO)Statistics - MethodologyMathematicsR; exponential family; state space models; time series; forecasting; dynamic linear modelsta112state space modelsSeries (mathematics)RStatistics; Computer softwaresymbolsStatistics Probability and Uncertaintytime seriesSoftwaredynamic linear models
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Implicit differentiation for fast hyperparameter selection in non-smooth convex learning

2022

International audience; Finding the optimal hyperparameters of a model can be cast as a bilevel optimization problem, typically solved using zero-order techniques. In this work we study first-order methods when the inner optimization problem is convex but non-smooth. We show that the forward-mode differentiation of proximal gradient descent and proximal coordinate descent yield sequences of Jacobians converging toward the exact Jacobian. Using implicit differentiation, we show it is possible to leverage the non-smoothness of the inner problem to speed up the computation. Finally, we provide a bound on the error made on the hypergradient when the inner optimization problem is solved approxim…

FOS: Computer and information sciencesbilevel optimizationComputer Science - Machine Learninghyperparameter selec- tionMachine Learning (stat.ML)[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]generalized linear modelsMachine Learning (cs.LG)Convex optimizationStatistics - Machine Learning[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Optimization and Control (math.OC)FOS: Mathematics[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]hyperparameter optimizationLassoMathematics - Optimization and Control[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]
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Model averaging estimation of generalized linear models with imputed covariates

2015

a b s t r a c t We address the problem of estimating generalized linear models when some covariate values are missing but imputations are available to fill-in the missing values. This situation generates a bias-precision trade- off in the estimation of the model parameters. Extending the generalized missing-indicator method proposed by Dardanoni et al. (2011) for linear regression, we handle this trade-off as a problem of model uncertainty using Bayesian averaging of classical maximum likelihood estimators (BAML). We also propose a block model averaging strategy that incorporates information on the missing-data patterns and is computationally simple. An empirical application illustrates our…

Generalized linear modelEconomics and EconometricsApplied MathematicsSettore SECS-P/05 - EconometriaEstimatorMissing dataGeneralized linear mixed modelModel averaging Bayesian averaging of maximum likelihood destimators Generalized linear models Missing covariates Generalized missing-indicator method shareHierarchical generalized linear modelStatisticsLinear regressionCovariateApplied mathematicsGeneralized estimating equationMathematics
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Weighted-average least squares estimation of generalized linear models

2018

The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification framework that allows the development of asymptotic model averaging theory. We also investigate t…

Generalized linear modelEconomics and EconometricsGeneralized linear modelsBayesian probabilityGeneralized linear modelSettore SECS-P/05 - EconometriaLinear predictionContext (language use)01 natural sciencesLeast squares010104 statistics & probabilityWALS; Model averaging; Generalized linear models; Monte Carlo; AttritionFrequentist inference0502 economics and businessAttritionEconometricsApplied mathematicsStatistics::Methodology0101 mathematicsMonte Carlo050205 econometrics MathematicsWALSApplied Mathematics05 social sciencesLinear modelEstimatorModel averaging
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Using the dglars Package to Estimate a Sparse Generalized Linear Model

2015

dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve. dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, call…

Generalized linear modelFortranLeast-angle regressionGeneralized linear array modelFeature selectionSparse approximationdgLARS generalized linear models sparse models variable selectionGeneralized linear mixed modelSettore SECS-S/01 - StatisticacomputerGeneralized estimating equationAlgorithmMathematicscomputer.programming_language
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Understanding german fdi in latin america and asia: a comparison of glm estimators

2020

The growth of Foreign Direct Investment (FDI) in developing countries over the last decade has attracted an intense academic and policy-oriented interest for its determinants. Despite the gravity model being considered a useful tool to approximate bilateral FDI flows, the literature has seen a growing debate in relation to its econometric specification, so that which is the best estimator for the gravity equation is far from conclusive. This paper examines the determinants of German outward FDI in Latin America and Asia for the period 1996-2012 by evaluating the performance of alternative Generalized Linear Model (GLM) estimators. Our findings indicate that Negative Binomial Pseudo Maximum …

Generalized linear modelLatin Americansfdi determinantsEconomics Econometrics and Finance (miscellaneous)gravity modelsNegative binomial distributionDeveloping countryForeign direct investmentDevelopmentgermany:CIENCIAS ECONÓMICAS [UNESCO]German0502 economics and businessddc:330EconometricsEconomicsC13050207 economicsC33050208 financelcsh:HB71-7405 social sciencesEstimatorlcsh:Economics as a scienceUNESCO::CIENCIAS ECONÓMICASgeneralized linear modelslanguage.human_languageGravity model of tradelanguageF21F23outward foreign direct investment
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Perceived Burden among Spouse, Adult Child and Parent Caregivers

2018

Aims To identify what factors are associated with the caregiver burden of spouse caregivers, adult child caregivers, and parent caregivers. Background Caregivers often feel stressed and perceive caregiving as a burden. The caregiver burden has been little studied from the perspective of the personal relationship between caregiver and care recipient. Design Cross-sectional study. Methods A random sample of 4,000 caregivers in Finland was drawn in 2014 and those who remained either spouse, adult child, or parent caregivers at data collection were included in the analysis (N = 1,062). Data collection included recipients' characteristics. Caregivers' perceived burden was measured using the Care…

GerontologyMaleParents0302 clinical medicineCost of IllnessomaishoitajatnursingSurveys and QuestionnairesNursing Interventions ClassificationMedicine030212 general & internal medicinenursing (work)General NursingFinlandmedia_commonta316Aged 80 and overDaughteradult child caregiverDepressionPersonal relationshipCognitionCaregiver burdenta3142Middle AgedSpouse Caregiversspouse caregiverCaregiversSpouseAdult ChildrenFemaleAdultmedia_common.quotation_subjectcaregivingparent caregivergeneral linear models03 medical and health sciencesYoung AdultHumansomaishoitoSpousesAgedperceived caregiver burdenbusiness.industrySocial SupportCross-Sectional Studiestyön kuormittavuusPerceptionbusinessOlder peopleCognition Disorderskoettu hyvinvointi030217 neurology & neurosurgeryStress PsychologicalJournal of Advanced Nursing
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Internal Test Sets Studies in a Group of Antimalarials

2006

Topological indices have been applied to build QSAR models for a set of 20 an- timalarial cyclic peroxy cetals. In order to evalua te the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have b een considered. The pro- posed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard c ross-validation algorithms involving multilinear regression models.

Internal test sets method; topological indices; linear models; QSAR; statistical validation.Quantitative structure–activity relationshipMultilinear mapInternal test sets methodLinear models (Statistics)CatalysisInorganic ChemistrySet (abstract data type)lcsh:ChemistryQSAR (Bioquímica)Order (group theory)Applied mathematicsPhysical and Theoretical ChemistryMolecular Biologylcsh:QH301-705.5SpectroscopyReliability (statistics)Mathematicsstatistical validation.Group (mathematics)QSAROrganic ChemistryLinear modelRegression analysisGeneral MedicineComputer Science Applicationslcsh:Biology (General)lcsh:QD1-999Models lineals (Estadística)topological indiceslinear modelsInternational Journal of Molecular Sciences
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Severe reduction of blood lysosomal acid lipase activity in cryptogenic cirrhosis: A nationwide multicentre cohort study

2017

Background and aims Blood lysosomal acid lipase (LAL) is reduced in non-alcoholic steatohepatitis, which is the major cause of cryptogenic cirrhosis (CC); few data on LAL activity in CC do exist. We investigated LAL activity in a cohort of patients with liver cirrhosis. Methods This is a multicentre cohort study including 274 patients with liver cirrhosis of different aetiology from 19 centres of Internal Medicine, Gastroenterology and Hepatology distributed throughout Italy. Blood LAL activity (nmol/spot/h) was measured with dried blood spot extracts using Lalistat 2. Results Overall, 133 patients had CC, and 141 patients had cirrhosis by other causes (61 viral, 53 alcoholic, 20 alcoholic …

Liver CirrhosisMaleCryptogenic cirrhosis; Liver disease; Lysosomal acid lipase; PathogenesisCirrhosisCryptogenic cirrhosisCryptogenic cirrhosis; Liver disease; Lysosomal acid lipase; Pathogenesis; Cardiology and Cardiovascular MedicineComorbidityPathogenesisLysosonal acid lipase; non-alcoolic fatty liver disease; cirrhosis030204 cardiovascular system & hematologyGastroenterologyLiver disease0302 clinical medicineModel for End-Stage Liver DiseasePathogenesiRisk FactorsPrevalenceProspective cohort studyMultivariate AnalysiSettore MED/12 - GastroenterologiaMiddle AgedItalyCohortLinear Model030211 gastroenterology & hepatologyFemaleCardiology and Cardiovascular MedicineLiver diseaseHumanmedicine.medical_specialtyLiver CirrhosiDown-Regulation03 medical and health sciencesInternal medicineCryptogenic cirrhosis; Liver disease; Lysosomal acid lipase; Pathogenesis; Aged; Biomarkers; Chi-Square Distribution; Comorbidity; Cross-Sectional Studies; Down-Regulation; Dried Blood Spot Testing; Female; Humans; Italy; Linear Models; Liver Cirrhosis; Male; Middle Aged; Multivariate Analysis; Platelet Count; Prevalence; Risk Factors; Sterol EsterasemedicineLysosonal acid lipaseHumansnon-alcoolic fatty liver diseaseAgedCross-Sectional StudieChi-Square Distributionbusiness.industryPlatelet CountcirrhosisRisk FactorBiomarkerCholesterol ester storage diseaseHepatologySterol Esterasemedicine.diseaseCross-Sectional StudiesMultivariate AnalysisLysosomal acid lipaseLinear ModelsDried Blood Spot TestingSteatohepatitisbusinessCryptogenic cirrhosiBiomarkers
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Novel and known genetic variants for male breast cancer risk at 8q24.21, 9p21.3, 11q13.3 and 14q24.1: Results from a multicenter study in Italy

2015

Increasing evidence indicates that common genetic variants may contribute to the heritable risk of breast cancer (BC). In this study, we investigated whether single nucleotide polymorphisms (SNPs), within the 8q24.21 multi-cancer susceptibility region and within BC-associated loci widespread in the genome, may influence the risk of BC in men, and whether they may be associated with specific clinical-pathologic characteristics of male BC (MBC). In the frame of the ongoing Italian Multicenter Study on MBC, we performed a case-control study on 386 MBC cases, including 50 BRCA1/2 mutation carriers, and 1105 healthy male controls, including 197 unaffected BRCA1/2 mutation carriers. All 1491 subj…

MaleCancer ResearchPredictive Value of Test8q24.21; BRCA1/2; Clinical-pathologic characteristics; Low-penetrance BC alleles; Male breast cancer; SNPs; BRCA1 Protein; BRCA2 Protein; Biomarkers Tumor; Breast Neoplasms Male; Case-Control Studies; Chi-Square Distribution; Gene Frequency; Genetic Predisposition to Disease; Heterozygote; Homozygote; Humans; Italy; Linear Models; Logistic Models; Male; Multivariate Analysis; Mutation; Odds Ratio; Phenotype; Predictive Value of Tests; Risk Factors; Chromosomes Human Pair 11; Chromosomes Human Pair 14; Chromosomes Human Pair 8; Chromosomes Human Pair 9; Polymorphism Single Nucleotide; Oncology; Cancer ResearchGene FrequencyRisk FactorsGenotypeOdds RatioMedicineskin and connective tissue diseasesMultivariate AnalysiSettore MED/36 - DIAGNOSTICA PER IMMAGINI E RADIOTERAPIAGeneticsClinical-pathologic characteristicsBRCA1 ProteinClinical-pathologic characteristicHomozygoteLow-penetrance BC allelesPhenotype8q24.21OncologyItalyMale breast cancer8q24.21; BRCA1/2; Clinical-pathologic characteristics; Low-penetrance BC alleles; Male breast cancer; SNPs; Cancer Research; OncologyLinear ModelCase-Control StudieChromosomes Human Pair 9HumanChromosomes Human Pair 8SNPsHeterozygoteLogistic ModelSNPSingle-nucleotide polymorphismPolymorphism Single NucleotideBreast Neoplasms MaleBreast cancerPredictive Value of TestsBRCA1/2Biomarkers TumorSNPHumansGenetic Predisposition to DiseaseAllele frequencyBRCA2 ProteinChromosomes Human Pair 14Chi-Square Distributionbusiness.industryRisk FactorChromosomes Human Pair 11Case-control studyOdds ratiomedicine.diseaseMale breast cancerLogistic ModelsCase-Control StudiesMultivariate AnalysisMutationLinear ModelsbusinessLow-penetrance BC allele
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