Self‐concordance for empirical likelihood
Copyright policy )Self‐concordance for empirical likelihood
AbstractAbstractThe usual approach to computing empirical likelihood for the mean uses Newton's method after eliminating a Lagrange multiplier and replacing the function by a quadratic Taylor approximation to the left of . This paper replaces the quadratic approximation by a quartic. The result is a self‐concordant function for which Newton's method with backtracking has theoretical convergence guarantees. The Canadian Journal of Statistics 41: 387–397; 2013 © 2013 Statistical Society of Canada
- Stanford University United States
Convex programming, confidence regions, Nonparametric tolerance and confidence regions, nonparametric inference, Computational problems in statistics, convex optimisation, global optimisation, Nonparametric estimation
Convex programming, confidence regions, Nonparametric tolerance and confidence regions, nonparametric inference, Computational problems in statistics, convex optimisation, global optimisation, Nonparametric estimation
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