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This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Among various mathematical frameworks, multidimensional continuous-time Markov jump processes $(Z_t)$ on $\N^d$ form a natural set-up for modeling $SIR$-like epidemics. In this study we extend the res...
We consider the problem of the construction of the asymptotically distribution free test by the observations of ergodic diffusion process. It is supposedd that under the basic hypothesis the trend coe...
We consider the problem of the construction of the asymptotically distribution free test by the observations of ergodic diffusion process. It is supposedd that under the basic hypothesis the trend coe...
The LASSO is a widely used statistical methodology for simultaneous estimation and variable selection. In the last years, many authors analyzed this technique from a theoretical and applied point of...
Some equations are obtained for the moments of the first passage time of a one-dimensional time-homogeneous diffusion process, through each of two accessible boundaries cr and fl, given that the pr...
Some problems of first-crossing times over two time- -dependent boundaries lor one-dimensional jump-difiusion processes are considered. The moments of the first-crossing times over each boundary ar...
Hitting Parabolas and Exponential Curves with Diffusion Processes
This work was motivated by the recent work by H. Dette, J. Pitman and W.J. Studden on a new duality relation for random walks. In this note we consider the diffusion process limit of their result, and...
We consider the goodness of fit testing problem for ergodic diffusion processes. The basic hypothesis is supposed to be simple. The diffusion coefficient is known and the alternatives are described ...
The two parameter Poisson-Dirichlet distribution PD( , ) is the distribution of an infinite dimensional random discrete probability. It is a generalization of Kingman’s Poisson-Dirichlet distributi...
This paper introduces a Monte Carlo method for maximum likelihood inference in the context of discretely observed diffusion processes. The method gives unbiased and a.s. continuous estimators of th...
In this paper we propose the use of -divergences as test statistics to verify simple hypotheses about a one-dimensional parametric diffusion process dXt = b(Xt, )dt + (Xt, )dWt, from discrete ob...
We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a s...

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