Sentences with phrase «stochastic methods»

The modern approach to resolving the difficult problems related to a larger scope for this instrument applies many advanced mathematical approaches, such as stochastic methods, game theory, and other tools of financial mathematics.

IMHO, applying stochastic methods on some specific grid points in the climate models that might have something «unusual», such as a random forest fire, forest clearance, crop failure, or a vast algal bloom, or overfishing going on, might be reasonable, but deteremining the boundary conditions for these to happen is another matter.

Koutsoyiannis (2011) showed that an ensemble of climate model projections is fully contained WITHIN the uncertainty envelope of traditional stochastic methods using historical data, including the Hurst phenomena... the Hurst phenomena (1951) describes the large and long excursions of natural events above and below their mean, as opposed to random processes which do not exhibit such behavior.

A reactor physicist by education and training, Mr. Marcille became the GE - Nuclear Chief Technologist and responsible engineer for control blades, nuclear fuel design and performance, spent fuel criticality and thermal management, nuclear cross-sections and deterministic and stochastic methods.

The new idea is to use the stochastic methods to identify the leading wave function components and the deterministic coupled - cluster computations, combined with suitable energy corrections, to provide the missing information.

The components of the program are 1) Stochastic Methods and Financial Instruments, 2) Economic Analysis and Asset Pricing, 3) Numerical Methods and Optimization, and 4) Statistical Techniques and Time Series Analysis.

The methodology developed in Lovejoy's two recent papers could also be used by researchers to help analyze precipitation trends and regional climate variability and to develop new stochastic methods of climate forecasting, he adds.

This foundational course provides a broad overview of approaches in applied mathematics, covering both deterministic and stochastic methods, with an emphasis on ecological questions, and is taken by general mathematics students who wish to obtain an introduction to graduate - level applied math, as well as by our students who are specifically interested in mathematical biology.

To do so, the researchers used and developed established methods such as analytical mathematics for the kinetics of gas properties and the Monte Carlo method — a stochastic method based on the theory of probability.

Not exact matches

It speaks of operations research, systems analysis, technological forecasting, information theory, game theory, simulation techniques, decision theory, Delphi method, cross-impact matrix analysis, statistical time - series, stochastic models, linear programming, input - output economics, computer based command and control systems, and so on.

This ultimate method for unraveling ensemble averages leads to the observation of new effects and to direct measurements of stochastic fluctuations.

By developing methods for systematically solving such equations, Hairer's work «allows one to give a rigorous meaning to a bunch of stochastic PDEs», says Ofer Zeitouni of the University of Minnesota in Minneapolis.

The first group participates in an intensive 4 - week collaborative learning experience on dynamical systems (broadly understood to include stochastic processes), modeling, and computational methods.

Johanna Grames investigated these questions as part of her PhD thesis supervised by Prof. Alexia Fürnkranz - Prskawetz at the Institute of Stochastics and Mathematical Methods in Economics at TU Wien.

Essentially, the researchers used a technique called stochastic optimization, which is a method to determine a central pattern from a group of data that seem chaotic or, as mathematicians call it, «noisy.»

As a proxy for splicing alteration, we computed the Shannon's entropy on the relative abundance of a gene's alternative splicing isoforms (Methods)-- higher values corresponding to more stochastic production of alternative isoforms.

The only plausible methods of repairing stochastic nuclear DNA damage look to be the aforementioned advanced molecular nanotechnology, something that lies some decades in the future, or major advances in gene therapy, to the point at which it could be cost - effective and safe to scan and conditionally alter the majority of genes in the majority of cells all at once.

As an application of our method, we examine thermal phase mixing in the context of Ginzburg - Landau models with short - range interac... ▽ More We show how to achieve lattice - spacing independent results in numerical simulations of finite - temperature stochastic scalar field theories.

These methods integrate single - cell experiments and discrete stochastic analysis to predict complex gene expression and signaling behaviors in Saccharomyces cerevisiae — or yeast, a scientific - lab standard since yeast and human cells share many genes.

Future forecasts are calculated from observed, lagged oceanographic indices and with stochastic simulations of winter SST (see Methods).

In addition to new experimental approaches for investigations of complex materials systems, she has pioneered stochastic simulation methods for complex condensed phase chemical reactions including transport in inorganic and organic solids and liquids.

QMC is a powerful stochastic quantum - mechanical technique for determining electronic ground - state energies, and is currently the most accurate atomistic simulation method that can be applied to extended systems such as solids and liquids.

Dr. Cobb suggests the use of a stochastic frontier model rather than the method we used.

Ask yourself why so many traders fail so often with quick - fix, complex, and outrageous «magic» trading methods like Elliot wave, Fibonacci extensions, and indicators like Stochastics, MACD and RSI... this stuff is haphazard at best and catalysts for blowing out your trading account at worst.

The program will include all aspects and methods of model development from deterministic numerics to stochastic forcing; process modelling to parametrization; observational constraints to diagnostic techniques; idealized modelling to operational forecasting and climate predictions.

The method combines the results of long - term atmospheric reanalyses downscaled with a stochastic statistical method and homogenized station observations to derive the meteorological forcing needed for hydrological modeling.

We investigate three methods for simultaneous estimation of the Hurst parameter (H) and the standard deviation (σ) for a Hurst - Kolmogorov stochastic process, namely the maximum likelihood method and two methods based on the variation of the standard deviation or of the variance with time scale.

Also, there are new non-parametric methods available which permit algorithms to find their own models using Bayesian principles and stochastic search.

Seven single - site statistical downscaling methods for daily temperature and precipitation, including four deterministic algorithms [analog model (ANM), quantile mapping with delta method extrapolation (QMD), cumulative distribution function transform (CDFt), and model - based recursive partitioning (MOB)-RSB- and three stochastic algorithms [generalized linear model (GLM), Conditional Density Estimation Network Creation and Evaluation (CaDENCE), and Statistical Downscaling Model — Decision Centric (SDSM — DC] are evaluated at nine stations located in the mountainous region of Iran's Midwest.

Yes, it's true there are examples in the literature of computer scientists and mathematicians who've worked on methods for predicting stochastic password generation with some degree of success.

This paper illustrates a method for operationalizing affect dynamics using a multilevel stochastic differential equation (SDE) model, and examines how those dynamics differ with age and trait - level tendencies to deploy emotion regulation strategies (reappraisal and suppression).