Results 11 to 20 of about 15,953 (268)
Penalized splines model to estimate time-varying reproduction number for Covid-19 in India: A Bayesian semi-parametric approach [PDF]
Clinical Epidemiology and Global Health, 2022 Statistical modelling is pivotal in assessing intensity of a stochastic processes. Novel Corona virus disease demanded proactive measures to understand the severity of disease spread and to plan its control accordingly.
Ranjita Pandey, Himanshu Tolani
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Marginal longitudinal semiparametric regression via penalized splines. [PDF]
Stat Probab Lett, 2010 We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling
Kadiri MA, Carroll RJ, Wand MP.
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Efficient curve fitting with penalized B-splines for oceanographic and ecological applications [PDF]
Scientific ReportsThis study introduces a penalized B-spline approach for estimating smooth curves, incorporating a total variation penalty to balance flexibility and interpretability. By leveraging group penalties and the Alternating Direction Method of Multipliers (ADMM)
Kwan-Young Bak +6 more
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Robust Permutation Tests for Penalized Splines
Stats, 2022 Penalized splines are frequently used in applied research for understanding functional relationships between variables. In most applications, statistical inference for penalized splines is conducted using the random effects or Bayesian interpretation of ...
Nathaniel E. Helwig
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S-estimation for penalized regression splines. [PDF]
SSRN Electronic Journal, 2008 This paper is about S-estimation for penalized regression splines. Penalized regression splines are one of the currently most used methods for smoothing noisy data. The estimation method used for fitting such a penalized regression spline model is mostly
Claeskens, Gerda +3 more
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Describing variability of intensively collected longitudinal ordinal data with latent spline models [PDF]
Scientific ReportsPopulation health studies increasingly collect longitudinal, patient-reported symptom data via mobile devices, offering unique insights into experiences outside clinical settings, such as pain, fatigue or mood.
Mark Lunt +2 more
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Penalized hyperbolic-polynomial splines [PDF]
Applied Mathematics Letters, 2021 Splines and spline approximations using penality functions are especially useful tools in univariate approximation theory when univariate data are to be approximated, and when no interpolation property is needed. The methods using piecewise polynomial splines and penalty methods can be formulated via square (or otherwise, other \(L^p\)-norms are ...
Rosanna Campagna, Costanza Conti
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Change Point Detection Using Penalized Multidegree Splines
Axioms, 2021 We consider a function estimation method with change point detection using truncated power spline basis and elastic-net-type L1-norm penalty. The L1-norm penalty controls the jump detection and smoothness depending on the value of the parameter. In terms
Eun-Ji Lee, Jae-Hwan Jhong
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Demographic Research, 2021 Background: High-dimensional parametric models with penalized likelihood functions strike a good balance between bias and variance for estimating continuous age schedules from large samples. The penalized spline (P-spline) approach is particularly useful
Carl Schmertmann
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Out-of-Sample Prediction in Multidimensional P-Spline Models
Mathematics, 2021 The prediction of out-of-sample values is an interesting problem in any regression model. In the context of penalized smoothing using a mixed-model reparameterization, a general framework has been proposed for predicting in additive models but without ...
Alba Carballo +2 more
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