6 papers
Local increment inference for time-inhomogeneous drift in Gaussian processes
Yasutaka Shimizu
We study statistical inference for deterministic drifts in Gaussian process models under high-frequency observations over an expanding time horizon. Using a least squares-type cont…
Semiparametric Estimation of Optimal Dividend Barrier for Spectrally Negative Lévy Process
Yasutaka Shimizu, Hiroshi Shiraishi
We disucss a statistical estimation problem of an optimal dividend barrier when the surplus process follows a Lévy insurance risk process. The optimal dividend barrier is defined a…
Least squares estimators for discretely observed stochastic processes driven by small fractional noise
S. Nakajima, S. Nakamura, Y. Shimizu
We study the problem of parameter estimation for discretely observed stochastic differential equations driven by small fractional noise. Under some conditions, we obtain strong con…
Parameter estimation of stochastic differential equation driven by small fractional noise
Shohei Nakajima, Yasutaka Shimizu
We study the problem of parametric estimation for continuously observed stochastic processes driven by additive small fractional Brownian motion with Hurst index 0<H<1/2 and 1/2<H<…
Asymptotic distributions for estimated expected functionals of general random elements
Yasutaka Shimizu
We consider an estimation problem of expected functionals of a general random element that values in a metric space. If the functional forms an explicit function of some unknown pa…
Moment convergence of the generalized maximum composite likelihood estimators for determinantal point processes
Kou Fujimori, Sota Sakamoto, Yasutaka Shimizu
The maximum composite likelihood estimator for parametric models of determinantal point processes (DPPs) is discussed. Since the joint intensities of these point processes are give…