A Discontinuous Galerkin Method for Approximating the Stationary Distribution of Stochastic Fluid-Fluid Processes
نویسندگان
چکیده
Abstract The stochastic fluid-fluid model (SFFM) is a Markov process $$\{(X_t,Y_t,\varphi _t),t\ge 0\}$$ { ( X t , Y φ ) ≥ 0 } , where $$\{\varphi _t,{t\ge 0}\}$$ continuous-time chain, the first fluid, $$\{X_t,t\ge classical fluid driven by _t,t\ge and second $$\{Y_t,t\ge pair $$\{(X_t,\varphi . Operator-analytic expressions for stationary distribution of SFFM, in terms infinitesimal generator are known. However, these operator-analytic do not lend themselves to direct computation. In this paper discontinuous Galerkin (DG) method used construct approximations operators, form finite dimensional matrices, enable DG results verified simulation. numerics demonstrate that scheme can have superior rate convergence compared other methods.
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ژورنال
عنوان ژورنال: Methodology and Computing in Applied Probability
سال: 2022
ISSN: ['1387-5841', '1573-7713']
DOI: https://doi.org/10.1007/s11009-022-09945-2