Search results for "probability"
showing 10 items of 3417 documents
New approach to delay-dependent H∞ control for continuous-time Markovian jump systems with time-varying delay and deficient transition descriptions
2015
Abstract This paper proposes an input–output (IO) approach to the delay-dependent stability analysis and H ∞ controller synthesis for a class of continuous-time Markovian jump linear systems (MJLSs). The concerned systems are with a time-varying delay in the state and deficient mode information in the Markov stochastic process, which simultaneously involves the exactly known, partially unknown and uncertain transition rates. It is first shown that the original system with time-varying delay can be reformulated by a new IO model through a process of two-term approximation and the stability problem of the original system can be transformed into the scaled small gain (SSG) problem of the IO mo…
Bayesian methods in cost-effectiveness studies: objectivity, computation and other relevant aspects.
2009
In a probabilistic sensitivity analysis (PSA) of a cost-effectiveness (CE) study, the unknown parameters are considered as random variables. A crucial question is what probabilistic distribution is suitable for synthesizing the available information (mainly data from clinical trials) about these parameters. In this context, the important role of Bayesian methodology has been recognized, where the parameters are of a random nature. We explore, in the context of CE analyses, how formal objective Bayesian methods can be implemented. We fully illustrate the methodology using two CE problems that frequently appear in the CE literature. The results are compared with those obtained with other popu…
A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes
2011
Published version of an article from the book: Hybrid artificial intelligent systems, Lecture notes in computer science. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-642-21219-2_2 There are numerous applications in Artificial Intelligence (AI) and Machine Learning (ML) where the criteria for decisions are based on testing procedures. The most common tools used in such random phenomena involve Random Walks (RWs). The theory of RWs and its applications have gained an increasing research interest since the start of the last century. [1]. In this context, we note that a RW is, usually, defined as a trajectory involving a series of successive ran…
Probability Measures on Product Spaces
2020
In order to model a random time evolution, the canonical procedure is to construct probability measures on product spaces. Roughly speaking, the first step is to take a probability measure that models the initial distribution. In the second step, on a different probability space, the distribution after one time step is modeled. Then in each subsequent step, on a further probability space, the random state in the next time step given the full history is modeled. On a formal level, we consider products of probability spaces and Markov kernels between such spaces. Finally, the Ionescu-Tulcea theorem shows that the whole procedure can be realized on a single infinite product space. Furthermore,…
ℓ1-Penalized Methods in High-Dimensional Gaussian Markov Random Fields
2016
In the last 20 years, we have witnessed the dramatic development of new data acquisition technologies allowing to collect massive amount of data with relatively low cost. is new feature leads Donoho to define the twenty-first century as the century of data. A major characteristic of this modern data set is that the number of measured variables is larger than the sample size; the word high-dimensional data analysis is referred to the statistical methods developed to make inference with this new kind of data. This chapter is devoted to the study of some of the most recent ℓ1-penalized methods proposed in the literature to make sparse inference in a Gaussian Markov random field (GMRF) defined …
Statistical Shape and Probability Prior Model for Automatic Prostate Segmentation
2011
International audience; Accurate prostate segmentation in Trans Rectal Ultra Sound (TRUS) images is an important step in different clinical applications. However, the development of computer aided automatic prostate segmentation in TRUS images is a challenging task due to low contrast, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow, and speckle. Significant variations in prostate shape, size and contrast between the datasets pose further challenges to achieve an accurate segmentation. In this paper we propose to use graph cuts in a Bayesian framework for automatic initialization and propagate multiple mean parametric models derived from princi…
Le martingale: aspetti teorici ed applicativi
2001
This paper offers an overview on the characteristics of martingales. These latter are markovian processes without underlying trend, in which the stochastic variable depends on its ultimate realisation. Some application fields are in studies relative to financial markets, and especially the derivative securities. Drawing from the theoretical and empirical literature, the main mathematical characteristics are presented. In order to transform processes with increasing or decreasing trends into martingales, the Doob-Meyer decomposition and the change of probability measure approaches can be adopted. Finally, four applications are considered with regard to the pricing of futures, call options an…
Secondary Circulation of Tropical Cyclones in Vertical Wind Shear: Lagrangian Diagnostic and Pathways of Environmental Interaction
2015
Abstract This study introduces a Lagrangian diagnostic of the secondary circulation of tropical cyclones (TCs), here defined by those trajectories that contribute to latent heat release in the region of high inertial stability of the TC core. This definition accounts for prominent asymmetries and transient flow features. Trajectories are mapped from the three-dimensional physical space to the (two dimensional) entropy–temperature space. The mass flux vector in this space subsumes the thermodynamic characteristics of the secondary circulation. The Lagrangian diagnostic is then employed to further analyze the impact of vertical wind shear on TCs in previously published idealized numerical exp…
Is there contextuality in behavioural and social systems?
2015
Most behavioral and social experiments aimed at revealing contextuality are confined to cyclic systems with binary outcomes. In quantum physics, this broad class of systems includes as special cases Klyachko-Can-Binicioglu-Shumovsky-type, Einstein-Podolsky-Rosen-Bell-type, and Suppes-Zanotti-Leggett-Garg-type systems. The theory of contextuality known as Contextuality-by-Default allows one to define and measure contextuality in all such system, even if there are context-dependent errors in measurements, or if something in the contexts directly interacts with the measurements. This makes the theory especially suitable for behavioral and social systems, where direct interactions of "everythin…
Multiple mating by females is a natural outcome of a null model of mate encounters
2012
Why do females of so many species mate multiply? The question makes use of an implicit null model that females by default should be monandrous and that polyandry requires an explanation. Here, we make thesimplepoint that females encountermates overtheir lifetimeina stochasticmanner,andas theyshouldacceptatleastonemale,acceptanceofallmales maybea betternullmodelthanthemore advanced strategy of accepting thefirst satisfactory one and rejecting all others. The advantage of this view is that it makes it explicit that females must accept and reject mates without precise knowledge of future mate encounters. In insects, for example, limitations of cognitive and sensory capabilities make it hard fo…