Search results for "Linear Models"
showing 10 items of 440 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.
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…
Uneven economic burden of non-communicable diseases among Indian households: A comparative analysis
2021
Background Non-communicable diseases (NCDs) are the leading global cause of death and disproportionately concentrate among those living in low-income and middle-income countries. However, its economic impact on households remains less well known in the Indian context. This study aims to assess the economic impact of NCDs in terms of out-of-pocket expenditure (OOPE) and its catastrophic impact on NCDs affected households in India. Materials and methods Data were collected from the 75th round of the National Sample Survey Office, Government of India, conducted in the year 2017–18. This is the latest round of data available on health, which constitutes a sample of 113,823 households. The coll…
Aggregation ofArgulus coregoni(Crustacea: Branchiura) on rainbow trout (Oncorhynchus mykiss): a consequence of host susceptibility or exposure?
2005
By sampling individual rainbow trout,Oncorhynchus mykiss, at a fish farm we showed thatArgulus coregoniwere aggregated within their host population. The relative significance of susceptibility and exposure generating the observed pattern was tested using experimental infections. We examined, whether rainbow trout developed protective resistance mechanisms against the louse following a challenge infection and if there was variation between individual trout in their susceptibility toA. coregonimetanauplii. Fish were exposed to 20A. coregonifor 5, 25, 50, 85 or 120 min and the numbers attaching recorded. Three weeks later, developing argulids were removed and the experiment repeated with a sta…
Simultaneous determination of four 5-hydroxy polymethoxyflavones by reversed-phase high performance liquid chromatography with electrochemical detect…
2009
Accumulating evidence has suggested the potential health-promoting effects of 5-hydroxy polymethoxyflavones (5-OH-PMFs) naturally existing in citrus genus. However, research efforts are hampered by the lack of reliable and sensitive methods for their determination in plant materials and biological samples. Using reversed-phase high performance liquid chromatography (HPLC) equipped with electrochemical (EC) detection, we have developed a fast and highly sensitive method for quantification of four 5-OH-PMFs, namely 5-hydroxy-6,7,8,3',4'-pentamethoxyflavone, 5-hydroxy-3,6,7,8,3',4'-hexamethoxyflavone, 5-hydroxy-6,7,4'-trimethoxyflavone, and 5-hydroxy-6,7,8,4'-tetramethoxyflavone. The method wa…
Capillary electrophoresis–inductively coupled plasma-mass spectrometry hyphenation for the determination at the nanogram scale of metal affinities an…
2012
Abstract A screening strategy based on hyphenated capillary electrophoresis and inductively coupled plasma mass spectrometry (CE–ICP-MS) was developed to classify phosphorylated ligands according to their europium(III) binding affinity in a hydro-organic medium (sodium formate, pH 3.7, H2O/MeOH 90:10, v/v). Taking advantage of the high sensibility of ICP-MS for detecting phosphorus, this method enabled to assess the affinity of a variety of phosphorylated compounds, including phosphine oxides, thiophosphines, phosphonates, and phosphinates, in less than 1 h and using less than 5 ng of substance. By varying the total europium concentration, complexation constants could be determined accordin…
Predictors and mediators of differences in soft drinks consumption according to gender and plans of further education among Norwegian secondary-schoo…
2013
AbstractObjectiveTo explore mediators of gender and educational differences in sugar-sweetened soft drinks consumption (SDC) and whether gender and level of future education moderate the associations of accessibility, modelling, attitudes and preferences with SDC.DesignA cross-sectional school-based survey within the Fruits and Vegetables Makes the Marks (FVMM) project from 2005.SettingThe questionnaires were completed by the pupils in the classroom guided by a trained project worker during one class session. The questionnaire included questions on SDC (times/week), the potential mediators and moderators. Multilevel linear regression models were used to calculate the mediating and moderatin…
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…
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…
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…