On estimating the diffusion coefficient [Abstract of thesis]
On estimating the diffusion coefficient : parametric versus nonparametric
On estimating the memory for finitarily markovian processes
On estimating the yield and volatility curves
On estimation and detection of infinite-variable functions.
On estimation in random fields generated by linear stochastic partial differential equations
On estimation of a covariance function of stationary errors in a nonlinear regression model.
On expontential autoregressive time series models.
On extrapolation in multiple ARMA processes
On Extrapolation of Moving Average and Autoregressive Processes
On filtering over Îto-Volterra observations.
On geometric ergodicity and prediction in nonnegative non-linear autoregressive processes
A non-linear AR(1) process is investigated when the associated white noise is positive. A criterion is derived for the geometric ergodicity of the process. Some explicit formulas are derived for one and two steps ahead extrapolation. Influence of parameter estimation on extrapolation is studied.
On improving sensitivity of the Kalman filter
The impact of additive outliers on a performance of the Kalman filter is discussed and less outlier-sensitive modification of the Kalman filter is proposed. The improved filter is then used to obtain an improved smoothing algorithm and an improved state-space model parameters estimation.
On interpolation in periodic autoregressive processes
The periodic autoregressive processes are useful in statistical analysis of seasonal time series. Some procedures (e.g. extrapolation) are quite analogous to those in the clasical autoregressive models. The problem of interpolation needs, however, some special methods. They are demonstrated in the paper on the case of the process of the second order with the period of length 2.
On interpolation of moving average processes
On invariant density estimation for ergodic diffusion processes.
We present a review of several results concerning invariant density estimation by observations of ergodic diffusion process and some related problems. In every problem we propose a lower minimax bound on the risks of all estimators and then we construct an asymptotically efficient estimator.
On invertibility of a random coefficient moving average model
A linear moving average model with random coefficients (RCMA) is proposed as more general alternative to usual linear MA models. The basic properties of this model are obtained. Although some model properties are similar to linear case the RCMA model class is too general to find general invertibility conditions. The invertibility of some special examples of RCMA(1) model are investigated in this paper.
On Kaiman Filtering, Posterior Mode Estimation and Fisher Scoring in Dynamic Exponential Family Regression.
On least squares estimation in continuous time linear stochastic systems
On linear inversion of moving averages, discrete equalizers and "whitening" filters, and the related difference equations and infinite systems of linear equations