Results 31 to 40 of about 15,886 (254)
Penalized regression splines in Mixture Density Networks
The International Journal of Biostatistics, 2022 Abstract Mixture Density Networks (MDN) belong to a class of models that can be applied to data which cannot be sufficiently described by a single distribution since it originates from different components of the main unit and therefore needs to be described by a mixture of densities.
Seifert, Quentin Edward +6 more
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Frontiers in Aging Neuroscience, 2022 PurposePreviously, sex and apolipoprotein E (APOE) genotype had distinct effects on the cognitive trajectory across the Alzheimer’s disease (AD) continuum.
Jun Pyo Kim +21 more
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Mathematics, 2021 The financial catastrophe resulting from the out-of-pocket payments necessary to access and use healthcare systems has been widely studied in the literature. The aim of this work is to predict the impact of the financial catastrophe a household will face
Maria-Carmen García-Centeno +2 more
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Smoothing sparse and unevenly sampled curves using semiparametric mixed models: An application to online auctions [PDF]
, 2006 Functional data analysis can be challenging when the functional objects are sampled only very sparsely and unevenly. Most approaches rely on smoothing to recover the underlying functional object from the data which can be difficult if the data is ...
Jank, Wolfgang +3 more
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‘Asymptotic properties of penalized spline estimators’
Biometrika, 2009 We study the class of penalized spline estimators, which enjoy similarities to both regression splines, without penalty and with fewer knots than data points, and smoothing splines, with knots equal to the data points and a penalty controlling the roughness of the fit.
Gerda Claeskens +2 more
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Asymptotics for penalized spline estimators in quantile regression [PDF]
, 2012 Quantile regression predicts the $\tau$-quantile of the conditional distribution of a response variable given the explanatory variable for $\tau\in(0,1)$.
Yoshida, Takuma
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A Semiparametric Sequential Ordinal Model with Applications to Analyse First Birth Intervals
Austrian Journal of Statistics, 2016 A semiparametric sequential ordinal model is proposed to analyze socio-demographic and spatial determinants of first birth intervals after marriage. Random effects are introduced to capture spatially structured and unstructured latent covariates.
Lawrence Kazembe
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Quantifying spatial disparities in neonatal mortality using a structured additive regression model. [PDF]
PLoS ONE, 2010 BACKGROUND: Neonatal mortality contributes a large proportion towards early childhood mortality in developing countries, with considerable geographical variation at small areas within countries.
Lawrence N Kazembe, Placid M G Mpeketula
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Comparative Analysis for Robust Penalized Spline Smoothing Methods [PDF]
Mathematical Problems in Engineering, 2014 Smoothing noisy data is commonly encountered in engineering domain, and currently robust penalized regression spline models are perceived to be the most promising methods for coping with this issue, due to their flexibilities in capturing the nonlinear trends in the data and effectively alleviating the disturbance from the outliers.
Bin Wang, Wenzhong Shi, Zelang Miao
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Geoadditive hazard regression for interval censored survival times [PDF]
, 2005 The Cox proportional hazards model is the most commonly used method when analyzing the impact of covariates on continuous survival times. In its classical form, the Cox model was introduced in the setting of right-censored observations.
Kneib, Thomas
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