Gaussian processes that can be decomposed into a smooth mean function and a stationary autocorrelated noise process are considered and a fully automatic nonparametric method to simultaneous estimation of mean and auto-covariance ...

Gaussian processes that can be decomposed into a smooth mean function and a stationary autocorrelated noise process are considered and a fully automatic nonparametric method to simultaneous estimation of mean and auto-covariance ...

Conditions under which sums, products and time-aggregation of ARMA processes follow ARMA models are derived from a single theorem. This characterizes these processes in terms of difference equations satisfied by their ...

Multi-Output Gaussian Processes (MOGPs) are the multivariate extension of Gaussian processes (GPs \cite{Rasmussen:2006}), a Bayesian nonparametric method for univariate regression. MOGPs address the multi-channel regression ...

This document focus on the study of methodologies used for estimating the long memory parameter in ARFIMA processes contaminated by atypical data. The suggested methodologies are based on robust estimators for the spectrum ...

Se evalúa el desempeño de la metodología propuesta por Nieto(2005) para el ajuste de un modelo autorregresivo de umbrales (TAR) en series de tipo financiero. Se obtienen expresiones para la curtosis y la función de ...