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Versatile Curve Design by Level Set with Quadratic Convergence.
IEEE Trans Vis Comput Graph
July 2024
Many 3D mesh processing tasks revolve around generating and manipulating curves on surface meshes. While it is intuitive to explicitly model these curves using mesh edges or parametric curves in the ambient space, these methods often suffer from numerical instability or inaccuracy due to the projection operation. Another natural strategy is to adapt spline based tools, these methods are quite fast but are hard to be extended to more versatile constraints and need heavy manual interactions.
View Article and Find Full Text PDFPartially linear Bayesian modeling of longitudinal rank and time-to-event data using accelerated failure time model with application to brain tumor data.
Stat Med
June 2023
Neurosurgery Department, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Joint modeling of longitudinal rank and time-to-event data with random effects model using a Bayesian approach is presented. Accelerated failure time (AFT) models can be used for the analysis of time-to-event data to estimate the effects of covariates on acceleration/deceleration of the survival time. The parametric AFT models require determining the event time distribution.
View Article and Find Full Text PDFRe: Spline-based accelerated failure time model.
Stat Med
March 2022
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Spline-based accelerated failure time model.
Stat Med
January 2021
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada.
The accelerated failure time (AFT) model has been suggested as an alternative to the Cox proportional hazards model. However, a parametric AFT model requires the specification of an appropriate distribution for the event time, which is often difficult to identify in real-life studies and may limit applications. A semiparametric AFT model was developed by Komárek et al based on smoothed error distribution that does not require such specification.
View Article and Find Full Text PDFEffects of Proportional Hazard Assumption on Variable Selection Methods for Censored Data.
Stat Biopharm Res
December 2019
Department of Statistics, North Carolina State University.
The Cox proportional hazard (PH) model is widely used to determine the effects of risk factors and treatments (covariates) on survival time of subjects that might be right censored. The selection of covariates depends crucially on the specific form of the conditional hazard model, which is often assumed to be PH, Accelerated Failure time (AFT) or proportional odds (PO). However, we show that none of these semi-parametric models allow for the crossing of the survival functions and hence such strong assumptions may adversely affect the selection of variables.
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