Extremal Large Deviations in Controlled I.I.D. Processes with Applications to Hypothesis Testing
, 1993 We consider a controlled i.i.d. process, where several i.i.d. sources are sampled sequentially. Any causal sampling policy, possibly history-dependent, may be employed.
Nahum Shimkin, Shimkin, Nahum
core
On the Quasi-Stationary Distribution for Some Randomly Perturbed Transformations of an Interval
, 1997 We consider a Markov chain X ffl n obtained by adding small noise to a discrete time dynamical system and study the chain's quasi-stationary distribution (qsd). The dynamics is given by iterating a function f : I !
Ofer Zeitouni +2 more
core
Joint large deviation result for empirical measures of the coloured random geometric graphs. [PDF]
Springerplus, 2016 Doku-Amponsah K.
europepmc +1 more source
Large deviations: From empirical mean and measure to partial sums process
The large deviation principle is known to hold for the empirical measures (occupation times) of Polish space valued random variables and for the empirical means of Banach space valued random variables under Markov dependence or mixing conditions, and ...
Zajic, Tim, Dembo, Amir
core
Large Deviations of Inverse Processes with Nonlinear Scalings
, 1998 We show, under regularity conditions, that a nonnegative nondecreasing real-valued stochastic process satisfies a large deviation principle (LDP) with nonlinear scaling if and only if its inverse process does. We also determine how the associated scaling
W. Whitt, N. G. Duffield
core
Tunnel engineering to accelerate product release for better biomass-degrading abilities in lignocellulolytic enzymes. [PDF]
Biotechnol Biofuels, 2019 Lu Z +5 more
europepmc +1 more source
Large Deviations for Small Noise Diffusions with Discontinuous Statistics
, 2007 This paper proves the large deviation principle for a class of non-degenerate small noise diffusions with discontinuous drift and with state-dependent diffusion matrix.
Richard S. Ellis +2 more
core
Weighted Chernoff Information and Optimal Loss Exponent in Context-Sensitive Hypothesis Testing. [PDF]
Entropy (Basel)Kelbert M, Kalimulina EY.
europepmc +1 more source
Self-Normalized Moderate Deviations for Degenerate U-Statistics. [PDF]
Entropy (Basel)Ge L, Sang H, Shao QM.
europepmc +1 more source