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Shota Gugushvili
Shota Gugushvili
Wageningen University & Research
Verified email at yesdatasolutions.com - Homepage
Title
Cited by
Cited by
Year
A kernel type nonparametric density estimator for decompounding
B Van Es, S Gugushvili, P Spreij
Bernoulli 13 (3), 672-694, 2007
832007
Nonparametric estimation of the characteristic triplet of a discretely observed LÚvy process
S Gugushvili
Journal of Nonparametric Statistics 21 (3), 321-343, 2009
592009
-consistent parameter estimation for systems of ordinary differential equations: bypassing numerical integration via smoothing
S Gugushvili, CAJ Klaassen
Bernoulli 18 (3), 1061-1098, 2012
422012
Nonparametric inference for discretely sampled LÚvy processes
S Gugushvili
Annales de l'IHP ProbabilitÚs et statistiques 48 (1), 282-307, 2012
412012
Dynamic programming and mean-variance hedging in discrete time
S Gugushvili
Georgian Mathematical Journal 10 (2), 237-246, 2003
252003
Deconvolution for an atomic distribution
B Van Es, S Gugushvili, P Spreij
Electronic Journal of Statistics 2, 265-297, 2008
222008
Nonparametric Bayesian drift estimation for multidimensional stochastic differential equations*
S Gugushvili, P Spreij
Lithuanian Mathematical Journal 54 (2), 127-141, 2014
202014
Parametric inference for stochastic differential equations: a smooth and match approach
S Gugushvili, P Spreij
ALEA, Lat. Am. J. Probab. Math. Stat. 9 (2), 609-635, 2012
192012
Application of one-step method to parameter estimation in ODE models
I Dattner, S Gugushvili
Statistica Neerlandica, 2018
18*2018
Nonparametric Bayesian inference for multidimensional compound Poisson processes
S Gugushvili, F van der Meulen, P Spreij
Modern Stochastics: Theory and Applications 2 (1), 1-15, 2015
182015
Fast and scalable non-parametric Bayesian inference for Poisson point processes
S Gugushvili, F van der Meulen, M Schauer, P Spreij
https://www.researchers.one/article/2019-06-6, 2019
172019
Fast and scalable non-parametric Bayesian inference for Poisson point processes
S Gugushvili, F van der Meulen, M Schauer, P Spreij
https://doi.org/10.5281/zenodo.1215900, 2018
172018
Bayesian linear inverse problems in regularity scales
S Gugushvili, A van der Vaart, D Yan
Ann. Inst. H. PoincarÚ Probab. Statist. 56 (3), 2081-2107, 2020
122020
A non-parametric Bayesian approach to decompounding from high frequency data
S Gugushvili, F van der Meulen, P Spreij
Statistical Inference for Stochastic Processes 21 (1), 53-79, 2018
112018
Weak convergence of the supremum distance for supersmooth kernel deconvolution
B van Es, S Gugushvili
Statistics & Probability Letters 78 (17), 2932-2938, 2008
112008
Separable nonlinear least-squares parameter estimation for complex dynamic systems
I Dattner, S Gugushvili, H Ship, EO Voit
https://arxiv.org/abs/1908.03717, 2019
92019
Nonparametric Bayesian inference for Gamma-type LÚvy subordinators
D Belomestny, S Gugushvili, M Schauer, P Spreij
Communications in Mathematical Sciences 17 (3), 781-816, 2019
8*2019
Deconvolution for an atomic distribution: rates of convergence
S Gugushvili, B van Es, P Spreij
Journal of Nonparametric Statistics 23 (4), 1003-1029, 2011
82011
Decompounding under Gaussian noise
S Gugushvili
arXiv preprint arXiv:0711.0719, 2007
82007
Nonparametric inference for partially observed LÚvy processes
S Gugushvili
University of Amsterdam, 2008
72008
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Articles 1–20