@article{Mishura_Ralchenko_Shklyar_2017, title={Maximum Likelihood Drift Estimation for Gaussian Process with Stationary Increments}, volume={46}, url={https://ajs.or.at/index.php/ajs/article/view/vol46-3-4-7}, DOI={10.17713/ajs.v46i3-4.672}, abstractNote={The paper deals with the regression model X_t = \theta t + B_t , t\in[0, T ],<br />where B=\{B_t, t\geq 0\} is a centered Gaussian process with stationary increments.<br />We study the estimation of the unknown parameter $\theta$ and establish the formula for the likelihood function in terms of a solution to an integral equation.<br />Then we find the maximum likelihood estimator and prove its strong consistency. The results obtained generalize the known results for fractional and mixed fractional Brownian motion.}, number={3-4}, journal={Austrian Journal of Statistics}, author={Mishura, Yuliya and Ralchenko, Kostiantyn and Shklyar, Sergiy}, year={2017}, month={Apr.}, pages={67–78} }