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[PDF] Top 20 State and parameter estimation for a class of schistosomiasis models

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State and parameter estimation for a class of schistosomiasis models

State and parameter estimation for a class of schistosomiasis models

... develop a general framework to estimate the proportion of infected snails and snail-human transmission parameter of a class of models that describes the ... Voir le document complet

25

Nonlinear reduced models for state and parameter estimation

Nonlinear reduced models for state and parameter estimation

... pwq of a single plausible state, the estimated distance of some of the other estimates u k pwq may be of comparable ...recovering a more complete estimate on a ... Voir le document complet

38

Nonlinear reduced models for state and parameter estimation

Nonlinear reduced models for state and parameter estimation

... 0q and ¯ V n,0 is computed with a greedy algorithm over Ă M ´ ¯ u 0 .... Of course the spaces V n,0 with n sufficiently large have high potential for approximation of the full manifold ... Voir le document complet

35

Backward importance sampling for online estimation of state space models

Backward importance sampling for online estimation of state space models

... Department of Mathematics, KTH Royal Institute of Technology, ...proposes a new Sequential Monte Carlo algorithm to perform online estimation in the con- text of state space ... Voir le document complet

27

Coupling stochastic EM and Approximate Bayesian computation for parameter inference in state-space models

Coupling stochastic EM and Approximate Bayesian computation for parameter inference in state-space models

... −1 for k ≥ K 1 as in Lavielle [ 2014 ...algorithms for Bayesian and “classical” inference, namely Gibbs sampling and particle marginal methods (PMM) [ Andrieu and Roberts , 2009 ] ... Voir le document complet

30

Local observers design for a class of neural mass models

Local observers design for a class of neural mass models

... design for a class of neural mass models Mohammed ...present a model-based approach to estimate the mean membrane potentials (and their time-derivatives) of ... Voir le document complet

7

Joint-state and parameters estimation using nudging and SEIK filters for HIV mechanistic models

Joint-state and parameters estimation using nudging and SEIK filters for HIV mechanistic models

... field and historically arose in the context of geophysics – ...oceanographics and weather forecasting ...uncertainties and also estimating uncertain quantities – as for example the ... Voir le document complet

7

saemix, an R version of the SAEM algorithm for parameter estimation in nonlinear mixed effect models

saemix, an R version of the SAEM algorithm for parameter estimation in nonlinear mixed effect models

... Detailed and omplete presentations of the nonlinear mixed ee ts model an be found in several referen e textbooks, for instan e ...model for ontinuous outputs: y ij = f (x ij , ψ i ) + g(x ij ... Voir le document complet

3

State and parameter estimation in 1-D hyperbolic PDEs based on an adjoint method

State and parameter estimation in 1-D hyperbolic PDEs based on an adjoint method

... negative and be out of the limits describing the physical meaning, we imposed also a linear ...itself a finite differ- ence method to calculate the gradient of estimated vari- able, ... Voir le document complet

9

Sequential Monte Carlo smoothing with application to parameter estimation in non-linear state space models

Sequential Monte Carlo smoothing with application to parameter estimation in non-linear state space models

... 100. For the subsequent 100 iterations, the number of particles in- creases at a quadratic rate with a final value (for the 250th Monte Carlo EM iteration) equal to N = ...number ... Voir le document complet

27

Maximum a Posteriori Parameter Estimation for Hidden Markov Models

Maximum a Posteriori Parameter Estimation for Hidden Markov Models

... EM and MCEM appear often trapped in congurations where one state of the Markov chain is not visited; besides, they are highly sensitive to the initial value, as shown by the variances in Table ... Voir le document complet

25

Parameter estimation in conditionally Gaussian pairwise Markov switching models and unsupervised smoothing

Parameter estimation in conditionally Gaussian pairwise Markov switching models and unsupervised smoothing

... identification of jump Markov systems (JMS) is known to be an important but difficult ...propose a new algorithm for the unsupervised estimation of parameters in a class ... Voir le document complet

7

MSE lower bounds for deterministic parameter estimation

MSE lower bounds for deterministic parameter estimation

... seems a difficult mathematical task to com- pute the bias transformation function h ( ) as a function of the LR transformation function t ( ) and of the ...is a class ... Voir le document complet

5

Parameter and state estimation of switched affine systems

Parameter and state estimation of switched affine systems

... On-line parameter and state estimation is a challenging problem from a theoretical point of view and most available results with analytical convergence guarantees ... Voir le document complet

7

Parameter estimation for peaky altimetric waveforms

Parameter estimation for peaky altimetric waveforms

... algorithm for the Brown, BGP, and BAGP ...nature of the peak, resulting in poor estimation performance for SWH < 4 m when applying the NM algorithm and for all SWHs ... Voir le document complet

11

Qualitative parameter estimation for a class of relaxation oscillators

Qualitative parameter estimation for a class of relaxation oscillators

... parameters and critical values at which a change of activity ...on a class of nonlinear systems with a single sigmoidal nonlinearity and two sharply separated ... Voir le document complet

7

A Class of Random Field Memory Models for Mortality Forecasting

A Class of Random Field Memory Models for Mortality Forecasting

... is, for two values of the parameter β, ceteris paribus, namely ...0.1 and 0.7. The right plot of Figure 3 shows the improvement rates for a model with parameter β = ... Voir le document complet

25

Investigating Parameter Transferability across Models and Events for a Semiarid Mediterranean Catchment.

Investigating Parameter Transferability across Models and Events for a Semiarid Mediterranean Catchment.

... by a greater thickness and reduced hydraulic conductivity due to the more compact soil and plays a key role in determining infiltration and base ...in a detailed manner the ... Voir le document complet

20

A MICROSCOPIC MODEL FOR A ONE PARAMETER CLASS OF FRACTIONAL LAPLACIANS WITH DIRICHLET BOUNDARY CONDITIONS

A MICROSCOPIC MODEL FOR A ONE PARAMETER CLASS OF FRACTIONAL LAPLACIANS WITH DIRICHLET BOUNDARY CONDITIONS

... Mandelbrot and is nothing but a random walk in which the step-lengths have a proba- bility distribution that is heavy ...tailed. A (one-dimensional) Lévy walker moves with a constant ... Voir le document complet

41

A class of fast-slow models for adaptive resistance evolution

A class of fast-slow models for adaptive resistance evolution

... [27] a time-discrete model is presented for three genotypes that considers a resistance allele with intermediate dominance in an autosomal ...locus. A time-discrete model of insecticide ... Voir le document complet

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