Now showing items 697-702 of 702

• #### Weak and strong quantile representations for randomly truncated data with applications ﻿

(Elsevier, 1993-05-26)
Suppose that we observe bivariate data (X,. q) only when Y, < Xi (left truncation). Denote with F the marginal d.f. of the X’s In this paper we derive a Bahadur-type representation for the quantile function of the pertaining ...
• #### Wiener disorder problem with observations at fixed discrete time epochs ﻿

(Institute for Operations Research and the Management Sciences (I N F O R M S), 2010)
Suppose that a Wiener process gains a known drift rate at some unobservable disorder time with some zero-modified exponential distribution. The process is observed only at known fixed discrete time epochs, which may not ...
• #### Worst-case large deviations upper bounds for i.i.d. sequences under ambiguity ﻿

(TÜBİTAK, 2018)
An introductory study of large deviations upper bounds from a worst-case perspective under parameter uncertainty (referred to as ambiguity) of the underlying distributions is given. Borrowing ideas from robust optimization, ...
• #### Z-theorems: Limits of stochastic equations ﻿

(International Statistical Institute, 2000)
Let fn(è, ù) be a sequence of stochastic processes which converge weakly to a limit process f 0(è, ù). We show under some assumptions the weak inclusion of the solution sets èn(ù) fè : fn(è, ù) 0g in the limiting ...
• #### Zero-sum Markov games with impulse controls ﻿

(Society for Industrial and Applied Mathematics, 2020)
In this paper we consider a zero-sum Markov stopping game on a general state space with impulse strategies and infinite time horizon discounted payoff where the state dynamics is a weak Feller--Markov process. One of the ...
• #### ℓ1 solution of linear inequalities ﻿

(Oxford University Press, 1999)
The numerical solution of a possibly inconsistent system of linear inequalities in the ℓ1 sense is considered. The non-differentiable ℓ1 norm minimization problem is approximated by a piecewise quadratic Huber smooth ...