Local asymptotic normality for ergodic jump-diffusion processes via transition density approximation

Rates of convergence and asymptotic normality of curve estimators for ergodic diffusion processes

Asymptotic Normality for Deconvolving Kernel Density Estimators

Suppose that we have 11 observations from the convolution model Y = X + £, where X and £ are the independent unobservable random variables, and £ is measurement error with a known distribution. We will discuss the asymptotic normality for deconvolving kernel density estimators of the unknown density f x 0 of X by assuming either the tail of the characteristic function of £ behaves as II I~Oexp(...

Asymptotic Normality in Density Support Estimation

Estimation Gérard BIAU a,∗, Benôıt CADRE b, David M. MASON c and Bruno PELLETIER d a LSTA & LPMA Université Pierre et Marie Curie – Paris VI Bôıte 158, 175 rue du Chevaleret 75013 Paris, France [email protected] b IRMAR, ENS Cachan Bretagne, CNRS, UEB Campus de Ker Lann Avenue Robert Schuman 35170 Bruz, France [email protected] c University of Delaware Food and Resource Econ...

Ergodic control of diffusion processes

Results concerning existence and characterization of optimal controls for ergodic control of nondegenerate diffusion processes are described. Extensions to the general ‘controlled martingale problem’ are indicated, which cover in particular degenerate diffusions and some infinite dimensional problems. In conclusion, some related problems and open issues are discussed. Mathematics Subject Classi...

Moment estimation for ergodic diffusion processes

We investigate the moment estimation for an ergodic diffusion process with unknown trend coefficient. We consider nonparametric and parametric estimation. In each case, we present a lower bound for the risk and then construct an asymptotically efficient estimator of the moment type functional or of a parameter which has a one-to-one correspondence to such a functional. Next, we clarify a higher...