Results 1  10
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70
If Estimation Of HigherOrder Polynomial Fm Signals Corrupted By Multiplicative And Additive Noise
, 2001
"... In this paper, we propose the peak of the polynomial WignerVille distribution as an instantaneous frequency estimator for polynomial frequency modulated signals in the presence of multiplicative and additive complex Gaussian processes. We show that this estimator is unbiased and we derive an analyt ..."
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an analytic expression of its asymptotic variance. Simulation results, based on MonteCarlo realisations, are presented in order to show the validity of the theoretical derivations. 1.
What is the largest Einstein radius in the universe?
, 2009
"... The Einstein radius plays a central role in lens studies as it characterises the strength of gravitational lensing. In particular, the distribution of Einstein radii near the upper cutoff should probe the probability distribution of the largest mass concentrations in the universe. Adopting a triaxia ..."
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triaxial halo model, we compute expected distributions of large Einstein radii. To assess the cosmic variance, we generate a number of MonteCarlo realisations of allsky catalogues of massive clusters. We find that the expected largest Einstein radius in the universe is sensitive to parameters
A numerical testbed for hypotheses of extraterrestrial life and intelligence
 Int. J. Astrobiology
, 2009
"... Abstract The search for extraterrestrial intelligence (SETI) has been heavily influenced by solutions to the Drake Equation, which returns an integer value for the number of communicating civilisations resident in the Milky Way, and by the Fermi Paradox, glibly stated as: "If they are there, w ..."
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Cited by 3 (1 self)
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of evolution itself. This paper outlines a method of Monte Carlo realisation which does this, and hence allows an estimation of the distribution of key parameters in SETI, as well as allowing a quantification of their errors (and the level of ignorance therein). Furthermore, it provides a means for competing
New Mass Estimators For Tracer Populations
, 2002
"... We introduce the tracer mass estimator. This is a new and simple way to estimate the enclosed mass from the projected positions and line of sight velocities of a tracer population (such as globular clusters, halo stars and planetary nebulae). Like the projected mass estimator, it works by averaging ..."
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(projected distance)× (radial velocity) 2 /G over the sample. However, it applies to the commonest case of all, when the tracer population does not follow the overall dark matter density. The method is verified against simulated datasets drawn from Monte Carlo realisations of exact solutions
Assessing Convergence of Markov Chain Monte Carlo Algorithms
 Statistics and Computing
, 1997
"... We motivate the use of convergence diagnostic techniques for Markov Chain Monte Carlo algorithms and review various methods proposed in the MCMC literature. A common notation is established and each method is discussed with particular emphasis on implementational issues and possible extensions. The ..."
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Cited by 85 (11 self)
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We motivate the use of convergence diagnostic techniques for Markov Chain Monte Carlo algorithms and review various methods proposed in the MCMC literature. A common notation is established and each method is discussed with particular emphasis on implementational issues and possible extensions
An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
 Biometrika
, 2006
"... Maximum likelihood parameter estimation and sampling from Bayesian posterior distributions are problematic when the probability density for the parameter of interest involves an intractable normalising constant which is also a function of that parameter. In this paper, an auxiliary variable method i ..."
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Cited by 89 (4 self)
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for parameters of the Ising model given a particular lattice realisation.
Why does the clustering of haloes depend on their formation history?
, 2008
"... We discuss in the framework of the excursion set formalism a recent discovery from Nbody simulations that the clustering of haloes of given mass depends on their formation history. We review why the standard implementation of this formalism is unable to explain such dependencies, and we show that t ..."
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and filaments, together with the assumption that formation history depends on when these barriers are crossed. We implement both these extensions in a generalised excursion set method, and run large Monte Carlo realisations to quantify the effects. Our results suggest that effects as large as those found
Monte Carlo Filtering of Piecewise Deterministic Processes
"... We present efficient Monte Carlo algorithms for performing Bayesian inference in a broad class of models: those in which the distributions of interest may be represented by time marginals of continuoustime jump processes conditional on a realisation of some noisy observation sequence. The sequential ..."
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Cited by 1 (0 self)
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We present efficient Monte Carlo algorithms for performing Bayesian inference in a broad class of models: those in which the distributions of interest may be represented by time marginals of continuoustime jump processes conditional on a realisation of some noisy observation sequence
Monte Carlo Filtering And Smoothing With Application To TimeVarying Spectral Estimation
"... We develop methods for performing filtering and smoothing in nonlinear nonGaussian dynamical models. The methods rely on a particle cloud representation of the filtering distribution which evolves through time using importance sampling and resampling ideas. In particular, novel techniques are pres ..."
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Cited by 22 (7 self)
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are presented for generation of random realisations from the joint smoothing distribution and for MAP estimation of the state sequence. Realisations of the smoothing distribution are generated in a forwardbackward procedure, while the MAP estimation procedure can be performed in a single forward pass
Coarse Graining Monte Carlo Methods for Wireless Channels and Stochastic Differential Equations
"... ii This thesis consists of two papers considering different aspects of stochastic process modelling and the minimisation of computational cost. In the first paper, we analyse statistical signal properties and develop a Gaussian process model for scenarios with a moving receiver in a scattering envir ..."
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. That is, we verify that under certain assumptions, signal realisations of the MFC model converge to a Gaussian process and thereafter compute the Gaussian process ’ covariance matrix, which is needed to construct Gaussian process signal realisations. The obtained Gaussian process model is under certain
Results 1  10
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70