1,987 research outputs found
Multivariate extremality measure
We propose a new multivariate order based on a concept that we will call extremality". Given a unit vector, the extremality allows to measure the "farness" of a point with respect to a data cloud or to a distribution in the vector direction. We establish the most relevant properties of this measure and provide the theoretical basis for its nonparametric estimation. We include two applications in Finance: a multivariate Value at Risk (VaR) with level sets constructed through extremality and a portfolio selection strategy based on the order induced by extremality.Extremality, Oriented cone, Value at risk, Portfolio selection
Clustering and classifying images with local and global variability
A procedure for clustering and classifying images determined by three classification variables is presented. A measure of global variability based on the singular value decomposition of the image matrices, and two average measures of local variability based on spatial correlation and spatial changes. The performance of the procedure is compared using three different databases.Images, Cluster, Classification
Electric field and strain induced Rashba effect in hybrid halide perovskites
Using first principles density functional theory calculations, we show how
Rashba-type energy band splitting in the hybrid organic-inorganic halide
perovskites APbX (A=CHNH, CH(NH), Cs and X=I, Br)
can be tuned and enhanced with electric fields and anisotropic strain. In
particular, we demonstrate that the magnitude of the Rashba splitting of
tetragonal (CHNH)PbI grows with increasing macroscopic alignment of
the organic cations and electric polarization, indicating appreciable
tunability with experimentally-feasible applied fields, even at room
temperature. Further, we quantify the degree to which this effect can be tuned
via chemical substitution at the A and X sites, which alters amplitudes of
different polar distortion patterns of the inorganic PbX cage that directly
impact Rashba splitting. In addition, we predict that polar phases of CsPbI
and (CHNH)PbI with symmetry possessing considerable Rashba
splitting might be accessible at room temperature via anisotropic strain
induced by epitaxy, even in the absence of electric fields
On identifiability of MAP processes
Two types of transitions can be found in the Markovian Arrival process or MAP: with and without arrivals. In transient transitions the chain jumps from one state to another with no arrival; in effective transitions, a single arrival occurs. We assume that in practice, only arrival times are observed in a MAP. This leads us to define and study the Effective Markovian Arrival process or E-MAP. In this work we define identifiability of MAPs in terms of equivalence between the corresponding E-MAPs and study conditions under which two sets of parameters induce identical laws for the observable process, in the case of 2 and 3-states MAP. We illustrate and discuss our results with examples.Batch Markovian Arrival process, Hidden Markov models, Identifiability problems
BAYESIAN ESTIMATION FOR THE M/G/1 QUEUE USING A PHASE TYPE APPROXIMATION
This article deals with Bayesian inference and prediction for M/G/1 queueing systems. The general service time density is approximated with a class of Erlang mixtures which are phase type distributions. Given this phase type approximation, an explicit evaluation of measures such as the stationary queue size, waiting time and busy period distributions can be obtained. Given arrival and service data, a Bayesian procedure based on reversible jump Markov Chain Monte Carlo methods is proposed to estimate system parameters and predictive distributions.
- …