• Corpus ID: 3560513

Parametric inference for stochastic differential equations: a smooth and match approach

  title={Parametric inference for stochastic differential equations: a smooth and match approach},
  author={Shota Gugushvili and Peter Spreij},
  journal={arXiv: Statistics Theory},
We study the problem of parameter estimation for a univariate discretely observed ergodic diffusion process given as a solution to a stochastic differential equation. The estimation procedure we propose consists of two steps. In the first step, which is referred to as a smoothing step, we smooth the data and construct a nonparametric estimator of the invariant density of the process. In the second step, which is referred to as a matching step, we exploit a characterisation of the invariant… 

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