Results 1 to 10 of about 15,886 (254)

Penalized splines model to estimate time-varying reproduction number for Covid-19 in India: A Bayesian semi-parametric approach [PDF]

open access: yesClinical 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
doaj   +2 more sources

Efficient curve fitting with penalized B-splines for oceanographic and ecological applications [PDF]

open access: yesScientific Reports
This 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
doaj   +2 more sources

Robust Permutation Tests for Penalized Splines

open access: yesStats, 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
doaj   +2 more sources

Describing variability of intensively collected longitudinal ordinal data with latent spline models [PDF]

open access: yesScientific Reports
Population 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
doaj   +2 more sources

Change Point Detection Using Penalized Multidegree Splines

open access: yesAxioms, 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
doaj   +1 more source

D-splines: Estimating rate schedules using high-dimensional splines with empirical demographic penalties

open access: yesDemographic 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
doaj   +1 more source

Out-of-Sample Prediction in Multidimensional P-Spline Models

open access: yesMathematics, 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
doaj   +1 more source

Conditional Model Selection in Mixed-Effects Models with cAIC4

open access: yesJournal of Statistical Software, 2021
Model selection in mixed models based on the conditional distribution is appropriate for many practical applications and has been a focus of recent statistical research.
Benjamin Säfken   +3 more
doaj   +1 more source

Realization of a recursive digital filter based on penalized splines [PDF]

open access: yesКомпьютерная оптика, 2018
In this paper the possibility of development of the recursive digital filter using a P-spline is considered. The frequency and time response of the spline filter for real-time data are analytically obtained and investigated. The influence of the P-spline
Elena Kochegurova, Danni Wu
doaj   +1 more source

Cross-Validation, Information Theory, or Maximum Likelihood? A Comparison of Tuning Methods for Penalized Splines

open access: yesStats, 2021
Functional data analysis techniques, such as penalized splines, have become common tools used in a variety of applied research settings. Penalized spline estimators are frequently used in applied research to estimate unknown functions from noisy data ...
Lauren N. Berry, Nathaniel E. Helwig
doaj   +1 more source

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