Given a realization on a finite interval of a continuous-time stationary process, we construct estimators for higher order spectral densities. Tapering and shift-in-time methods are used to build estimators which are asymptotically unbiased and consistent for all admissible values of the argument. Asymptotic results for the fourth-order densities are given. Detailed attention is paid to the nth order case
AbstractWeakly and strongly consistent nonparametric estimates, along with rates of convergence, are...
The estimation of mutual spectral density with polynomial window of data viewing of stationary stoch...
This paper considers the case where a stochastic process may display both long-range dependence and ...
Recent work in econometrics has provided large bandwidth asymptotic theory for taper-based studentiz...
Recent work in econometrics has provided large bandwidth asymptotic theory for taper-based studentiz...
This paper presents a class of minimum contrast estimators for stochastic processes with possible lo...
AbstractThis paper presents a class of minimum contrast estimators for stochastic processes with pos...
Let g([lambda]) be the spectral density of a stationary process and let f[theta]([lambda]), [theta] ...
AbstractThis paper presents a class of minimum contrast estimators for stochastic processes with pos...
SIGLEAvailable from British Library Document Supply Centre-DSC:3597.760(no 00/514) / BLDSC - British...
AbstractThis paper deals with issues pertaining to estimating the spectral density of a stationary h...
AbstractThis paper considers statistical inference for nonstationary Gaussian processes with long-ra...
This paper considers statistical inference for nonstationary Gaussian processes with long-range depe...
AbstractIn this paper, the spectral density estimation of a nonstationary class of stochastic proces...
AbstractLet X = {X(t), − ∞ < t < ∞} be a continuous-time stationary process with spectral density fu...
AbstractWeakly and strongly consistent nonparametric estimates, along with rates of convergence, are...
The estimation of mutual spectral density with polynomial window of data viewing of stationary stoch...
This paper considers the case where a stochastic process may display both long-range dependence and ...
Recent work in econometrics has provided large bandwidth asymptotic theory for taper-based studentiz...
Recent work in econometrics has provided large bandwidth asymptotic theory for taper-based studentiz...
This paper presents a class of minimum contrast estimators for stochastic processes with possible lo...
AbstractThis paper presents a class of minimum contrast estimators for stochastic processes with pos...
Let g([lambda]) be the spectral density of a stationary process and let f[theta]([lambda]), [theta] ...
AbstractThis paper presents a class of minimum contrast estimators for stochastic processes with pos...
SIGLEAvailable from British Library Document Supply Centre-DSC:3597.760(no 00/514) / BLDSC - British...
AbstractThis paper deals with issues pertaining to estimating the spectral density of a stationary h...
AbstractThis paper considers statistical inference for nonstationary Gaussian processes with long-ra...
This paper considers statistical inference for nonstationary Gaussian processes with long-range depe...
AbstractIn this paper, the spectral density estimation of a nonstationary class of stochastic proces...
AbstractLet X = {X(t), − ∞ < t < ∞} be a continuous-time stationary process with spectral density fu...
AbstractWeakly and strongly consistent nonparametric estimates, along with rates of convergence, are...
The estimation of mutual spectral density with polynomial window of data viewing of stationary stoch...
This paper considers the case where a stochastic process may display both long-range dependence and ...