[PDF] Top 20 The stochastic modelling of kleptoparasitism using a Markov process

... of kleptoparasitism models are currently deterministic, based upon a system of ordinary differential equations (ODEs), and thus effectively assume a very large population ...of kleptoparasitism increase and ... See full document

... a stochastic rainfall model that can generate many sequences of synthetic daily rainfall series with the similar properties as those of the ...is Markov chain-mixed exponential ...two-state Markov ... See full document

... hidden Markov model, as defined by Rabiner in [3], “is a doubly embedded stochastic process with an underlying process that is not observable (it is hidden), but can only be observed through ... See full document

... a Markov chain Monte Carlo ...Dirichlet process mixture prior, have been developed in Jensen and Maheu (2010) and Delatola and Griffin ...return process is considered for the ...log-volatility ... See full document

... Circulant Markov Modulated Poisson Process (CMMPP) is a Poisson process, the rate of which is changed according to circulant Markov chain ...Circulant Markov Modulated Poisson ... See full document

... the stochastic process of elemental distances, that is, the process that generates the sequence { d[1], d[2], ...this process, we arrive at a full expression for the probability of collision, ... See full document

... We first describe the deterministic epidemic model. The model consists of four differential equations, one for each of the three disease states; susceptibles, infectives and AIDS cases, with the number in each class ... See full document

... use Markov processes as the well defined class of stochastic processes that are well ...a stochastic process with independent increments is a Markov ...discrete Markov processes ... See full document

... the stochastic block model, are not able to model sparsity (Caron and Fox, ...suggest modelling networks using Bayesian nonparametric models; one Bayesian nonparametric model that has particularly ... See full document

... the stochastic volatility ...used stochastic volatility models in practice: the SABR model that was originally proposed in Hagan et ...a stochastic volatility extension of the constant elasticity of ... See full document

... The above assessment is not only interesting from the probabilistic point of view. As we shall see in the next chapter, limit theorems of this kind can be used to perform approximate statistical inference. Thus, the two ... See full document

... Applying the results from [12] on the boundary points of jump-type processes, one can directly deduce from Theorem 5.1 various regularity properties of the stopped process and its semigroup (extending the results ... See full document

... Levy process to better fit market ...price process is a superposition of a Brownian motion and an independent compound Poisson process with lognormally distributed ... See full document

... the process of prediction of the three dimensional structure of a protein from its amino acid ...to process hug amount of data to study the behaviour of various types of ...or process various type of ... See full document

... system to reduce the dimension of the stochastic dynamic programming model from 10 to 4. Although Saad and Turgeon [10] note that principal component analysis could be applied separately to subsystems, the method ... See full document

... hidden Markov modelling is dominated by Gaussian HMMs (Spezia, 2010; Bartolucci and Farcomeni, 2010; Geweke and Amisano, ...2011). Modelling multivariate time series with non-normal components of ... See full document

... The stochastic mortality approach has been proposed by Milevsky and Promis- low (2001) and developed by Dahl (2004), Cairns et al. (2005), Bi¢ s (2005), Schrager (2005), Luciano and Vigna (2005). The probabilistic ... See full document

... arrival process of demands, exponentially distributed processing times and zero replenishment lead times of raw ...a Markov decision process approach to determine when and how much raw material ... See full document

... [4] Khanduja, R., Tewari,P.C. and Chauhan, R.S., (2009), Performance analysis of screening unit in a paper using genetic algorithm.Tewari, P.C, Khanduja, R, and Gupta, M., “Performance enhancement for ... See full document

... of modelling, and was unable to find an author who gave a satisfactory comprehensive discussion of modelling and models, (in particular for stochastic ...of modelling, but I have been unable ... See full document