Nonparametric regression models for right-censored data using Bernstein polynomials

DOI10.1016/j.csda.2011.08.019zbMath1239.62044OpenAlexW2044857991WikidataQ57432537 ScholiaQ57432537MaRDI QIDQ425652

Muhtarjan Osman, Sujit Kumar Ghosh

Publication date: 8 June 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.08.019

zbMATH Keywords

sievenonproportional hazards

Mathematics Subject Classification ID

Related Items (12)

Linearizations of matrix polynomials in Bernstein bases ⋮ EM algorithm for the additive risk mixture cure model with interval-censored data ⋮ Regression analysis of dependent current status data with the accelerated failure time model ⋮ Modelling the association in bivariate survival data by using a Bernstein copula ⋮ Quantifiers induced by subjective expected value of sample information with Bernstein polynomials ⋮ Joint analysis of interval-censored failure time data and panel count data ⋮ Efficient estimation for the non-mixture cure model with current status data ⋮ Approximating moments of continuous functions of random variables using Bernstein polynomials ⋮ A fuzzy regression approach using Bernstein polynomials for the spreads: computational aspects and applications to economic models ⋮ Analysis of transformation models with doubly truncated data ⋮ Asymptotic properties of Bernstein estimators on the simplex ⋮ Modeling right-skewed heavy-tail right-censored survival data with application to HIV viral load

Uses Software

• LBFGS-B

Cites Work

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• A flexible additive multiplicative hazard model
• Local Linear Estimation for Time‐Dependent Coefficients in Cox's Regression Models
• Bayesian Estimation of the Spectral Density of a Time Series
• Hazard Regression
• A Limited Memory Algorithm for Bound Constrained Optimization
• Survival analysis with temporal covariate effects
• Bayesian Survival Analysis Using Bernstein Polynomials
• Exponential survivals with censoring and explanatory variables
• On the Cox Model With Time-Varying Regression Coefficients

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