The consistency of a non-linear least squares estimator from diffusion processes
- Kasonga, R.A.
Publication date
December 1988
DOI Publisher
Published by Elsevier B.V. ISSN
0304-4149 Citation count (estimate)
23Abstract
AbstractConsider the following Itô stochastic differential equation dX(t) = ƒ(θ0, X(t)) dt + dW(t), where (W(t), t ⩾ 0), is a standard Wiener process in RN. On the basis of discrete data 0 = t0 < t1 < …<tn = T; X(t1),...,X(tn) we would like to estimate the parameter θ0. We shall define the least squares estimator ϴ̃n,τ and show that under some regularity conditions, ϴ̃n,τ is strongly consistent
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