[PDF] Top 20 Robust parameter estimation for the Ornstein-Uhlenbeck process
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Robust parameter estimation for the Ornstein-Uhlenbeck process
... problems for future research in ...suggested the problem of robust parameter estimation for the Ornstein–Uhlenbeck process to ...Rieder for ... Voir le document complet
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A wavelet analysis of the Rosenblatt process: chaos expansion and estimation of the self-similarity parameter
... very robust method: it is not sensitive to possible polynomial trends as soon as the number of vanishing moments Q is large ...in the case of fBm and later it has been extended to more general ... Voir le document complet
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Central limit theorem for the robust log-regression wavelet estimation of the memory parameter in the Gaussian semi-parametric context
... WAVELET ESTIMATION OF THE MEMORY PARAMETER IN THE GAUSSIAN SEMI-PARAMETRIC CONTEXT ...study robust estimators of the memory parameter d of a (possi- bly) non stationary ... Voir le document complet
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Estimation of the Memory Parameter of the Infinite Source Poisson Process
... yields the second claim of Theorem ...proved the validity of a wavelet method for the estimation of the long-memory parameter of an infinite-source Poisson traffic model, ... Voir le document complet
21
Robust Design of Parameter Identification
... In the non-linear case [5], unknown parameters are classically computed by an iterative optimisation algorithm, starting from an initial ...erative process, states and measures remain unchanged and ... Voir le document complet
9
Standard and robust intensity parameter estimation for stationary determinantal point processes
... inference; Robust statistics; Sample quantiles; Brillinger ...containing the random locations of some event of interest which arise in many scientific fields such as biology, epidemiology, seismology and ... Voir le document complet
22
Q-intersection Algorithms for Constraint-Based Robust Parameter Estimation
... Introduction The combinatorial q-intersection operator can handle a spe- cific class of numerical (real-valued) Constraint Satisfaction ...CSPs, the domain of the n variables is an n-dimensional box ... Voir le document complet
8
Parameter estimation by contrast minimization for noisy observations of a diffusion process
... of the distribution of the noise on the estimation, Ornstein-Uhlenbeck ...than the variance observed for α = 2. The second remark concerns the number ... Voir le document complet
30
Parameter estimation for a bidimensional partially observed Ornstein-Uhlenbeck process with biological application
... study the SDE. We detail in Section 3 the computation of the exact likelihood, the score and hessian ...present the EM method in Section 4. In Section 5, we establish the link ... Voir le document complet
32
Characterising the nonequilibrium stationary states of Ornstein-Uhlenbeck processes Nonequilibrium stationary states of Ornstein-Uhlenbeck processes
... characterise the nonequilibrium stationary state of a generic multivariate Ornstein-Uhlenbeck process involving N degrees of ...freedom. The irreversibility of the process ... Voir le document complet
41
Phase diagram of the random frequency oscillator: The case of Ornstein-Uhlenbeck noise
... of the simplest systems that can be used as a paradigm for the study of noise-induced phase transitions is the random frequency oscillator [8, ...9]. For instance, in practical ... Voir le document complet
18
Parameter estimation for multivariate generalized Gaussian distributions
... received the Master’s degree (“Probabili- ties, Statistics and Applications: Signal, Image and Networks”) with merit, in Applied Statistics from University Paris VII—Jussieu, Paris, France, in ...and ... Voir le document complet
13
Bayesian parameter estimation for asymmetric power distributions
... SAMPLER The principle of MCMC methods is to construct a Markov chain whose equilibrium distribution is the target posterior ...that, the basic Gibbs sampler gen- erates samples according to ... Voir le document complet
6
Adaptive Parameter Estimation for Satellite Image Deconvolution
... Key-words: Deconvolution, Regularization, Hyperparameters, Inhomogeneous models, Complex Wavelet Packets, Markov Random Fields, Local estimation, Maximum Likelihood, Satellite images Ack[r] ... Voir le document complet
82
Nonlinear reduced models for state and parameter estimation
... While the reduced model selection approach provides us with an estimator w ÞÑ u ˚ pwq of a single plausible state, the estimated distance of some of the other estimates u k pwq may be of comparable ... Voir le document complet
35
MSE lower bounds for deterministic parameter estimation
... as the SNR decreases. It is the alternative case where the transition region is smooth when the de- tection threshold effect is ...Intuitively, the detection step is expected to modify ... Voir le document complet
5
Parameter estimation of a microbial fuel cell process control-oriented model
... PublicationsArchive-ArchivesPublications@nrc-cnrc.gc.ca. If you wish to email the authors directly, please see the first page of the publication for their contact information. ... Voir le document complet
2
Statistical inference of Ornstein-Uhlenbeck processes : generation of stochastic graphs, sparsity, applications in finance
... hypothesis for explaining mean-reversion has been formulated in [DBT85], where the authors provide first evidence of the existence of mean-reversion in the US stock ...where the authors ... Voir le document complet
185
Parameter estimation for peaky altimetric waveforms
... to the analysis of coastal altimetric waveforms. When approaching the coast, altimetric waveforms are sometimes corrupted by peaks caused by high reflective areas inside the illuminated land surfaces ... Voir le document complet
11
Regularizing parameter estimation for Poisson noisy image restoration
... select the regularizing parameter for the deconvolution of images corrupted by blur and Poisson ...on the accuracy of the estimators and on the validity of the ap- ... Voir le document complet
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