Filtering and fixed-point smoothing from an innovation approach in systems with uncertainty.
Filtering and parameter estimation for a jump stochastic process with discrete observations.
Filtering of signals transmitted in multichannel from Chandrasekhar and Riccati recursions.
In this paper two recursive algorithms are proposed and compared as a solution of the least mean-squared error linear filtering problem of a wide-sense stationary scalar signal from uncertain observations perturbed by white and coloured additive noises. Considering that the state-space model of the signal is not available and that the variables modelling the uncertainty are not independent, the proposed algorithms are derived by using covariance information. The difference between both algorithms...
First-order autoregressive processes with time-dependent random parameters
Forecasting Telecommunication Traffic Using the Enhanced Stepwise Projection Multiple Regression Method
Forecasting time series with multivariate copulas
In this paper we present a forecasting method for time series using copula-based models for multivariate time series. We study how the performance of the predictions evolves when changing the strength of the different possible dependencies, as well as the structure of the dependence. We also look at the impact of the marginal distributions. The impact of estimation errors on the performance of the predictions is also considered. In all the experiments, we compare predictions from our multivariate...