Optimizing Methods in Statistics: ProceedingsJagdish S. Rustagi The efficient estimation of a parameter measurable by two instruments of unknown precisions; Optimization problems in simulation; Some optimization problems in parameter estimation; Optimal designs and spline regressions; Isotonic approximation; Asymptotically efficient estimation of nonparametric regression coefficients; Comparisons of order statistics and of spacing from heterogeneous distributions; Moment problems with convexity conditions; Variational methods in adaptive filtering; Non linear filtering; A convergence theorem for non negative almost supermartingales and some applications; Statistical control of optimization. |
Contents
The Efficient Estimation of a Parameter Measurable by | 1 |
Optimization Problems in Simulation | 29 |
Optimal Designs and Spline Regressions | 63 |
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Air Force algorithm allocation applications assumed asymptotic bandit problem best linear bound cells censored samples chance-constrained Charnes components consider constraints contact set convergence convex convex set corresponding covariances defined denote density Department of Statistics derivative differential duality equal equation equivalent example exists feasible solution filtering finite follows function Gamma given Harter Hence hypothesis inequality integrable iterative Lemma linear estimation linear programming Location and Scale location parameter Math Mathematics matrix maximum likelihood method minimax minimize moment problem observations obtain Ohio State University optimal optimum order statistics pattern population probability measure procedure Proof properties quantiles random variable satisfies Scale Parameters Schur function Section solution to D-1 space stochastic approximation subblocks symbol symmetry Theorem theory tion uQ(z variance vector Weibull Wiener process zero