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Topic: Stochastic modelling

	Stochastic Calculus (Site not responding. Last check: 2007-10-16)
		CJM - A Stochastic Calculus Approach for the Brownian Snake...
		Stochastic Calculus for Fractional Brownian Motion I. Theory...
		Stochastic Calculus with Respect to Gaussian Processes, Elisa,1 2 and Alòs, Oli...
	www.scienceoxygen.com /math/601.html (193 words)

	Stochastic modelling and prediction of contractor default risk
		The purpose of this paper is to describe a systematic framework of stochastic modelling and prediction of financial default risk of construction contractors.
		A mean-reverting dynamic model for the contractor default process is found by statistical analysis and is justified by using the theory of optimal capital structure.
		A discrete time trinomial Markov chain model is developed to assess default risk in terms of a cumulative default probability function, a default probability function, and the mean and variance of time to default.
	ideas.repec.org /a/taf/conmgt/v17y1999i5p563-576.html (341 words)

	A STOCHASTIC MODELLING APPROACH TO PARTICLE RESIDENCE TIME DISTRIBUTION IN CONTINUOUS FLUIDIZED BEDS
		The mathematical formulation of the model is based on modelling the axial position of the particle by means of a Markov chain: the probability distribution of the axial position of the particle at a given time-step n depends only on its position at time-step n-1 and a set of transition probabilities.
		The convective particle velocity is due to the in- and outflow and the circulation caused by the wake transport and therefore increases with increasing height in the bed.
		Other possibilities are modelling of particles differing in size and density from the bulk bed particles and modelling of the particle transport in beds with internals and beds with in-and outflow via standpipes.
	www.fi.uib.no /~hoffmann/papershtml/part98h/part98hf.html (2494 words)

	Monte Carlo Methods in Financial Engineering Stochastic Modelling and Applied Probability :: Education by Design Store (Site not responding. Last check: 2007-10-16)
		Similar to this method are stochastic mesh methods, the difference being that stochastic mesh methods utilize information coming from all nodes in the next time step.
		The measurement of market risk in his view boils down to finding a statistical model for describing the movements in individual sources of risk and correlations between multiple sources of risk, and in calculating the change in the value of the portfolio as the underlying sources of risk change.
		All the methods for term structure modeling are clearly discussed, and the authors made improvements on some of the original works.
	www.edbydesign.com /books/0387004513.html (2878 words)

	Biophysics - Encyclopedia.WorldSearch (Site not responding. Last check: 2007-10-16)
		By drawing knowledge and experimental techniques from a wide variety of disciplines (as described below), biophysicists are able to indirectly observe or model the structures and interactions of individual molecules or complexes of molecules.
		In addition things like solving a protein structure or measuring the kinetics of single molecule interactions, biophysics is also understood to encompass research areas that apply models and experimental techniques derived from physics (e.g.
		Medicine and neuroscience - tackling neural networks experimentally (brain slicing) as well as theoretically (computer models), membrane permitivity, gene therapy, understanding tumors.
	encyclopedia.worldsearch.com /biophysics.htm (732 words)

	MSCI 932: Stochastic Modelling
		Objectives: the course considers OR techniques which have been developed to model the effects of stochastic influences.
		Learning outcomes: students will be introduced to a variety of mathematical techniques and be able to apply them critically to situations found in organisations.
		Models of stochastic processes such as Markov chains, Markov processes, queuing models, inventory modelling, replacement, inspection and maintenance models.
	www.lancs.ac.uk /users/acadreg/gcr/msci932.htm (161 words)

	First International Workshop on Practical Applications of Stochastic Modelling, PASM'04
		The common link is to see how researchers from diverse fields have overcome the problem of modelling large concurrent and stochastic communicating systems to obtain the particular style of stochastic metric that is important to their field.
		Successful contributions may have demonstrated some novel theoretic advance to model their system or will have been diligent in constructing a detailed and realistic stochastic or probabilistic model and carried the modelling through to the analysis phase.
		The aim is to end up with a collection of papers which could be used as outstanding examples of modelling practice in the field of stochastic modelling and exhibit all phases of the modelling lifecycle.
	www.nesc.ac.uk /events/PASM04 (301 words)

	Stochastic Modelling (Site not responding. Last check: 2007-10-16)
		To provide experience with the construction, fitting and analysis of stochastic models, including detailed analysis of some complex models; to introduce some general theory with applications.
		At the end of this module the students will be able to discuss deterministic, discrete-time and continuous-time models, define and make use of concepts used in advanced stochastic analysis, and calculate probabilities of long-term outcomes, as well as being able to make use of simulation techniques on problems too complex for exact mathematical analysis.
		Models which are not quite Markov: semi-Markov chains and applications, Markov chains with time-dependent or age-dependent transition rates.
	www.city.ac.uk /actstat/cseinfo/d3_02s.htm (321 words)

	Stochastic Modelling in Chemical Engineering, Course Page
		Many models in chemical engineering are based on population balances or density transport equation.
		Fields where these models are applied are polymerisation, turbulent flow, liquid-liquid reactions, and combustion just to name a few.
		We also want to show how a stochastic algorithm is related to the physical or chemical model which is usually given by a ordinary or differential equation.
	www.cheng.cam.ac.uk /c4e/StoMo (425 words)

	stochastic modelling 3 (Site not responding. Last check: 2007-10-16)
		This phenomena can be modeled by describing shopping rate as a function of time.
		Last class, you created a simple "rain generating" model using a uniform generator to determine "whether" it rained and a gaussian generator to determine the "amount" of rain that fell.
		It is possible to model seasonal rainfall characteristics using a time varying function of rain probability.
	grapevine.abe.msstate.edu /classes/abe4803/stoch-3.html (849 words)

	The Math Forum - Math Library - Stochastic Processes
		Stochastic Analysis Digest provides conference information and publication announcements in the areas of probability, stochastic analysis, statistics and related fields.
		Stochastic Networks Web - Richard Gibbens; Statistical Laboratory, Univ. of Cambridge, U.K. A collection of pages relating to the study of stochastic networks and their applications.
		A journal focusing on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, stochastic control theory and probabilistic networks and graphs.
	mathforum.org /library/topics/stochastic (1848 words)

	Stochastic modelling approaches
		Two main approaches have been developed to modelling stochastic events in gene expression, stochastic differential equations and the stochastic simulation algorithm.
		A characteristic of stochastic differential equation approaches is that they treat molecular concentrations as continuous variables.
		Some of the logical modelling approaches described in Section 4, such as the asynchronous Boolean model and the generalised logic formalism, also include an degree of noises arising from the non-deterministic timing of regulatory events.
	www.itee.uq.edu.au /~nic/_accs-grn/_node28.html (388 words)

	Martingale Methods in Financial Modelling (Stochastic Modelling and Applied Probability) (Site not responding. Last check: 2007-10-16)
		The models are compared and used as benchmark continuous time models and form the basis for all subsequent analysis.
		Many of the well-known models are studied in detail, such as CEV, local volatility, and mixture models.
		The stochastic volatility models of Wiggins (via Orenstien-Uhlenbeck processes), Hull-White, and Heston are studied, as is the SABR model.
	www.newenglandrealestatelistings.com /real-estate-books/3540209662.html (1566 words)

	CTSM - Continuous Time Stochastic Modelling (Site not responding. Last check: 2007-10-16)
		odelling means semi-physical modelling of dynamic systems based on stochastic differential equations.
		Stochastic differential equations contain a diffusion term to account for random effects, but are otherwise structurally similar to ordinary differential equations.
		This means that conventional modelling principles can be applied to set up the model.
	www2.imm.dtu.dk /~ctsm/features.html (178 words)

	A Multiple-Scale Stochastic Modelling Primitive - Stam, Fiume (ResearchIndex) (Site not responding. Last check: 2007-10-16)
		Abstract: Stochastic modelling has been successfully used in computer graphics to model a wide array of natural phenomena.
		In modelling three-dimensional fuzzy or partially translucent phenomena, however, many approaches are hampered by high memory and computation requirements, and by a general lack of user control.
		We will present a general stochastic modelling primitive that operates on two or more scales of visual detail, and which offers considerable flexibility and control of the model.
	citeseer.lcs.mit.edu /stam91multiplescale.html (606 words)

	SMV group home site (Site not responding. Last check: 2007-10-16)
		In the presence of structured models which are composed of interacting submodels, the symbolic approach leads to extremely compact representations of huge state spaces, a property which may be also enjoyed by Kronecker-based representations.
		We are developing a prototype model checker (ETMCC) [TACAS'2000 paper] that enables the user to check properties against labelled continuous time Markov chains, where the Continuous Stochastic Logic (CSL) is used as the basic requirements specification language.
		We are planning to support other model input formats in the near future, in order to link the model checker ETMCC to a wide range of existing high-level modelling tools based on stochastic Petri nets and queueing networks.
	www7.informatik.uni-erlangen.de /tree/IMMD-VII/Research/Groups/smv (574 words)

	Energy Citations Database (ECD) - Energy and Energy-Related Bibliographic Citations
		In recent years probabilistic modelling of reservoir heterogeneities has become an integrated part of reservoir description, and various methods and software programs have been introduced.
		In general, the process of generating a stochastic 3D model consists of four stages: (1) simulate isochore maps of each time-zone, (2) distribute facies heterogeneities within the isochores, (3) simulate petrophysical properties and (4) translate the fine-scale model to a coarser flow simulation grid.
		The aim of the stochastic modelling work was threefold: (1) to make realistic fine-scale geological models that are consistent with observed data and geological understanding, (2) to calculate uncertainties in oil in place volume and (3) to match production history to be able to predict future reservoir behaviour and detect unswept oil.
	www.osti.gov /energycitations/product.biblio.jsp?osti_id=127711 (402 words)

	FIRST CALL FOR PAPERS (Site not responding. Last check: 2007-10-16)
		This Conference is a continuation of series of Conferences in Analytical, Numerical and Stochastic Modelling Techniques held as a part of European Simulation Conferences.
		Taking into account the complexity of real models of complex technical and information systems, methods of stochastic modelling based on analytical and approximate results for Markov and semi-Markov stochastic processes, queueing networks, Petri nets, etc. have recently become increasingly popular.
		In many fields of applications involving performance and reliability modelling of discrete flow systems, such as computer systems, high speed communication networks, flexible manufacturing systems and workflow management systems, it has been widely recognized that analytical and approximate approaches in stochastic modelling can successfully complement simulation methods.
	www.inf.brad.ac.uk /~kbegain/conf/ASMT2002.html (805 words)

	GMPP - Stochastic modelling of facies architecture (Site not responding. Last check: 2007-10-16)
		A clear vertical trend in intensity in the facies consisting of brown/grey colours and a trend in both intensity and size is the facies with blue bodies.
		Modeling of facies architecture by marked point models (1997), Lia, Oddvar; Tjelmeland, Håkon and Kjellesvik, Lars Edward (Geomatic,Stavanger), in Geostatistics Wollongong '96, Kluwer academic publishers, proceedings from 5th International Geostatistics Congress, Wollongong Australia, sep. 22.-27., 1996.
		A marked point process model conditioned on inverted seismic data (1998), Lia, Oddvar and Gjerde, Jon, in IAMG '98 Proceedings of the Fourth Annual Conference of the International Association for Mathematical Geology, October 1998, pp.
	www.nr.no /documents/sand/research_areas/reservoir_characterization/facies/gmpp/gmpp.html (337 words)

	Discrete Stochastic Modelling (Site not responding. Last check: 2007-10-16)
		This module (or equivalent) is a prerequisite for AS3103 Continuous Stochastic Modelling.
		The models introduced in this module are used in other modules later in the degree programme.
		The use of models; stochastic as opposed to determinstic models.
	www.city.ac.uk /actstat/cseinfo/as2103_03.html (217 words)

	Applied Stochastic Modelling (Site not responding. Last check: 2007-10-16)
		The construction, fitting and evaluation of statistical and stochastic models are important in subjects such as geology, sociology, biology and economics.
		This book presents many of the most important advances of the last 30 years in the theory and practice of statistics.
		It grew out of a series of talks on aspects of fitting stochastic models to data and a resulting lecture course.
	www.booknews.co.uk /Books/1743.htm (91 words)

	Deterministic in Contrast to Stochastic Modelling (ResearchIndex) (Site not responding. Last check: 2007-10-16)
		Abstract: The first attempt to model a process is often a deterministic setup with differential equations.
		The existing stochastic influence is suppressed and hopefully negligible.
		The corresponding stochastic equation is X n+1 = X n + g(X n)(1 + n) or dX t = g(X t...
	citeseer.ist.psu.edu /322426.html (198 words)

	Group of Stochastic Modelling of Relaxation Phenomena in Complex Systems (Site not responding. Last check: 2007-10-16)
		Hence, the question of the origins of the universal relaxation law has to be addressed in terms of probabilistic models which can provide a clue to a better understanding of the physical mechanism of relaxation.
		Such models, even with their inability to assign a precise physical meaning to some variates give strict constrains on the matematical form of the relaxation function and the practical value of rigorous results in claryfying of the relaxation nature cannot be denied.
		It is worth noting the result on the equivalence between the parallel channel and the correlated cluster models.
	www.if.pwr.wroc.pl /instytut/Group2Statys.htm (498 words)

	Stochastic Modelling in Innovative Manufacturing: Proceedings, Cambridge, U.K., July 21-22, 1995 (Lecture Notes in ... (Site not responding. Last check: 2007-10-16)
		Stochastic Modelling in Innovative Manufacturing: Proceedings, Cambridge, U.K., July 21-22, 1995 (Lecture Notes in Economics and Mathematical Systems)
		The first group of papers looks at modelling, and solution techniques that have proved useful in the operational and strategic levels of manufacturing-greedy algorithms, Markov Decision processes and Petri Nets.
		The volume shows that the need for stochastic modelling is an important factor in support of decision making, and that this is a growing, exciting and rewarding area of research.
	www.adultdvdmagic.com /isbn_354061768X.html (138 words)

	IngentaConnect Stochastic modelling of ion dynamics in complex systems: dipolar ... (Site not responding. Last check: 2007-10-16)
		Stochastic modelling of ion dynamics in complex systems: dipolar effects
		After a brief summary of the present status of stochastic models in explaining the dynamical behaviour, we focus on the localized degrees of freedom, described as a random lattice of Brownian dipoles.
		From Brownian dynamics simulations in two dimensions we find an ac response at intermediate frequencies which is of the power-law type, with exponents depending both on temperature and on the degree of randomness.
	www.ingentaconnect.com /content/tandf/tphb/1998/00000077/00000005/art00023 (237 words)

	620-301 Stochastic Modelling (Site not responding. Last check: 2007-10-16)
		This subject introduces the concept of a stochastic process and deals with the important standard stochastic processes, including Poisson process, Markov chains, birth-and-death processes, queuing processes and renewal processes, demonstrating the standard techniques of describing such processes.
		Students learn to develop a stochastic process model from a real-life situation and to derive the behaviour and properties of particular stochastic processes.
		This subject demonstrates the importance of stochastic processes in modelling real-life phenomena and in particular shows the applications of stochastic models to industry and the sciences.
	www.unimelb.edu.au /HB/1998/subjects/620-301.html (220 words)

	WL :: Stochastic modelling of river morphology
		Therefore, Delft Hydraulics and Delft University of Technology have embarked on a four-year research programme on methods for the stochastic modelling of morphological processes in rivers.
		Herein, the goal is to express morphological predictions in statistical properties of river bed topography, such as expected bed levels, variance and probabilities.
		To illustrate this effect of uncertainty in the river discharge, a case study was performed on scouring in a straight alluvial channel containing a constriction.
	www.wldelft.nl /rnd/intro/topic/stoch-rivmor (278 words)

	Stochastic Modelling
		I worked on a number of research projects that involve stochastic modelling.
		Emre Otay from Bogazici University to develop a physics-based model that evaluates the expected number of casualties based on the arrival traffic and also the hydrodynamic model of the waterway.
		This model gives you the likelihood of winning a (local) war depending on the number of attackers and defendants with the expected number of casualties.
	home.ku.edu.tr /%7Ebtan/research/stochastic_modelling.htm (303 words)

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